diff --git a/.gitignore b/.gitignore index dc28192..3819836 100644 --- a/.gitignore +++ b/.gitignore @@ -26,6 +26,13 @@ share/python-wheels/ *.egg-info/ .installed.cfg *.egg +*.out +*.png +*.pdf +*stats*.p +*.zip + + MANIFEST # PyInstaller @@ -128,3 +135,10 @@ dmypy.json # Pyre type checker .pyre/ + + +eda/csv_explorer.ipynb +*.html +*.txt +*.mp3 +*.p \ No newline at end of file diff --git a/eda/frequent_wordcounts.py b/eda/frequent_wordcounts.py new file mode 100644 index 0000000..64ce66f --- /dev/null +++ b/eda/frequent_wordcounts.py @@ -0,0 +1,67 @@ +import numpy as np +import os +import glob +import pandas as pd +import matplotlib.pyplot as plt +import subprocess +import seaborn as sns +import nltk +from typing import Set, List, Dict +import functools +from collections import Counter +import csv +import pathlib +from tqdm import tqdm +from pathlib import Path + +fw_path1 = Path('/mnt/disks/std2/data/generated/common_voice/frequent_words') +fw_path1 = Path('/mnt/disks/std3/compressed_cleaned3/generated/common_voice/frequent_words') +# fw_path2 = Path('/mnt/disks/std3/data/generated/common_voice/frequent_words') +langs = os.listdir(fw_path1) +# langs += os.listdir(fw_path2) + +# new_langs = ['gn','ha'] + +# langs = [i for i in langs if i in new +lang_to_c = {} + +for l in tqdm(langs): + c = Counter() + words1_path = fw_path1 / l / 'clips' + # words2_path = fw_path2 / l / 'clips' + if words1_path.is_dir(): + words1 = os.listdir(words1_path) + else: + words1 = [] + # if words2_path.is_dir(): + # words2 = os.listdir(words2_path) + # else: + # words2 = [] + # words1 = os.listdir() + # words2 = os.listdir(fw_path2 / l / 'clips') + # words = os.listdir(f"/mnt/disks/std750/data/frequent_words/{l}/clips/") + for w in tqdm(words1): + wavs = os.listdir(fw_path1 / l / 'clips' / w) + # wavs = glob.glob(f"/mnt/disks/std750/data/frequent_words/{l}/clips/{w}/*.wav") + c[w] = len(wavs) + + # for w in tqdm(words2): + # wavs = os.listdir(fw_path2 / l / 'clips' / w) + # # wavs = glob.glob(f"/mnt/disks/std750/data/frequent_words/{l}/clips/{w}/*.wav") + # if w in c: + # c[w] += len(wavs) + # else: + # c[w] = len(wavs) + # c[w] += len(wavs) + + lang_to_c[l] = c + +import pickle +# prev = pickle.load(open('frequent_words_stats_std4.p','rb')) + +# for k,v in lang_to_c.items(): +# prev[k] = v + + +pickle.dump(lang_to_c, open('frequent_words_stats_std_final.p','wb')) + diff --git a/eda/get_data.py b/eda/get_data.py new file mode 100644 index 0000000..9b61e6a --- /dev/null +++ b/eda/get_data.py @@ -0,0 +1,78 @@ +#%% + +import numpy as np +import pandas as pd +import argparse +from argparse import ArgumentParser + +from typing import Dict + +def argparser(): + """ + Argument parser + """ + parser = ArgumentParser() + parser.add_argument("--input_file", type=str, help="input file") + parser.add_argument("--output_file", type=str, help="output file") + args = parser.parse_args() + + return args + +def get_number_of_keywords(df: pd.DataFrame, min_num_of_extractions: int = 20) -> Dict[str, int]: + langs = np.unique(df['language'].values) + vals = {} + for l in langs: + tdf = df[df['language'] == l] + tdf = tdf[tdf['counts']>=min_num_of_extractions] + vals[l] = len(tdf) + + return vals + +def max_and_min_num_extraction_each_language(df: pd.DataFrame): + langs = np.unique(df['language'].values) + min, max = {}, {} + for l in langs: + max[l], min[l] = (df[df['language'] == l]['counts'].max(), df[df['language'] == l]['counts'].min()) + + return min, max + +def get_avg_extractions(df: pd.DataFrame): + langs = np.unique(df['language'].values) + vals = {} + for l in langs: + tdf = df[df['language'] == l] + vals[l] = tdf['counts'].mean() + + return vals +#%% +if __name__ == '__main__': + args = argparser() + # input_file = "../../data/csvs/new.csv" + df = pd.read_csv(args.input_file) + + df = df[df.counts >= 5] + #%% + # vals0 = get_number_of_keywords(df, 0) + vals5 = get_number_of_keywords(df, 5) + vals20 = get_number_of_keywords(df, 20) + vals50 = get_number_of_keywords(df, 50) + vals100 = get_number_of_keywords(df, 100) + vals200 = get_number_of_keywords(df, 200) + + # table = pd.DataFrame(dict(zip(['Language', 'Atleast 0 extractions', 'Atleast 5 extractions', 'Atleast 20 extractions', 'Atleast 50 extractions', 'Atleast 100 extractions', 'Atleast 200 extractions'], [np.unique(df['language'].values).tolist(), vals0.values(), vals5.values(), vals20.values(), vals50.values(), vals100.values(), vals200.values()])), index=vals5.keys()) + table = pd.DataFrame(dict(zip(['Language', 'Atleast 5 extractions', 'Atleast 20 extractions', 'Atleast 50 extractions', 'Atleast 100 extractions', 'Atleast 200 extractions'], [np.unique(df['language'].values).tolist(), vals5.values(), vals20.values(), vals50.values(), vals100.values(), vals200.values()])), index=vals5.keys()) + + min, max = max_and_min_num_extraction_each_language(df) + avg = get_avg_extractions(df) + + table['Minimum'] = min.values() + table['Maximum'] = max.values() + table['Average'] = avg.values() + + # output_file = "../../data/csvs/new2.csv" + + table.to_csv(args.output_file, index=False) + + + # print(vals) +# %% diff --git a/eda/plot.py b/eda/plot.py new file mode 100644 index 0000000..c30dd43 --- /dev/null +++ b/eda/plot.py @@ -0,0 +1,137 @@ +import matplotlib.pyplot as plt +import seaborn as sns +import pickle +import pandas as pd +import numpy as np + +import collections +from collections import Counter + +from tqdm import tqdm + +import plotly.express as px + +#fig =px.scatter(x=range(10), y=range(10)) +#fig.write_html("path/to/file.html") + +stats = pickle.load(open('frequent_words_stats_std2.p','rb')) +# wordlengths = {} + +# for l in stats: +# wordlengths[l] = len(stats[l]) +# wordlengths = dict(sorted(wordlengths.items(), key=lambda item: item[1], reverse=True)) + +# #plt.gcf().set_size_inches(70,15) +# #plt.bar(wordlengths.keys(), wordlengths.values()) +# fig, ax = plt.subplots() +# fig.set_size_inches(30,20) +# #plt.gcf().set_size_inches(70,15) +# ax.bar(wordlengths.keys(), wordlengths.values()) +# ax.set_xticklabels(wordlengths.keys(), rotation=70) +# ax.set_xlabel("Languages") +# ax.set_ylabel("Number of words") +# ax.set_title("Number of Words for various languages in Common Voice") +# #ax.bar_label(p1) +# plt.savefig('numwords.png') +# plt.cla() + +# wordlengths = {} + +# for l in stats: +# wordlengths[l] = sum([len(i) for i in stats[l].keys()]) / len(stats[l].keys()) + +# fig, ax = plt.subplots() +# fig.set_size_inches(30,20) +# #plt.gcf().set_size_inches(70,15) +# ax.bar(wordlengths.keys(), wordlengths.values()) +# ax.set_xticklabels(wordlengths.keys(), rotation=70) +# ax.set_xlabel("Languages") +# ax.set_ylabel("Word Length") +# ax.set_title("Average Word Length for various languages in Common Voice") +# #ax.bar_label(p1) +# plt.savefig('wordlengths.png') +# plt.cla() + +def plot_counts(counts, title, lang): + counts = Counter(counts) + data = [(i, counts[i][1]) for i in range(len(counts.most_common(500)))] +# df = pd.DataFrame([data, columns=["index", "counts"]]) + #sns.barplot(x="counts", y="keyword", data=df).set_title(title) + #length +# print(len(np.arange(0,50)), len(counts.most_common(50))) +# print(counts.most_common(50)) + fig = px.line(df, x='index',y='counts', color = lang) + #plt.plot(np.arange(0,50).tolist(), [i[1] for i in counts.most_common(50)], label = lang) + print([i[1] for i in counts.most_common(500)]) + #plt.gcf().set_size_inches(15,70) +# plt.savefig(f"plots/words/{lang}.png") +# plt.cla() + return fig + + +data =[] +for l in tqdm(stats): + counts = stats[l] + counts = Counter(counts).most_common(500) + #counts + #print(counts) + datat = [(i, counts[i][1], l) for i in range(len(counts))] + data.extend(datat) + +df = pd.DataFrame(data, columns=['index','counts','language']) + +fig = px.line(df, x='index', y='counts', color='language') + +#for l in tqdm(stats): +# fig = plot_counts(stats[l], f"{l} frequent words", l) + #plt.draw() + #plt.pause(0.0001) + +fig.write_html('line.html') +#plt.legend() +#plt.savefig('line.png') +# + +from tqdm import tqdm + +def wordlengths(main_data): + languages = main_data['language'].unique() + plot_saves = "plots/wordlengths/" + for l in tqdm(languages): + + sub_df = main_data[main_data['language']==l] + words = sub_df['word'].unique().tolist() + + wordlengths = {} + for w in words: + if type(w) == str: + if len(w) in wordlengths: + wordlengths[len(w)] += 1 + else: + wordlengths[len(w)] = 1 + + fig, ax = plt.subplots(figsize=(8,8)) + ax.bar(wordlengths.keys(), wordlengths.values()) + ax.set_xlabel("Word Length") + ax.set_ylabel("Number of Keywords") + ax.set_title(f"Number of Keywords v/s Word Length for {l}") + save_path = plot_saves + f"{l}.png" + fig.savefig(f"{save_path}") + +def graph1(): + plot_saves = "plots/wordlengths/" + from tqdm import tqdm + for l in tqdm(languages): + + sub_df = main_data[main_data['language']==l] + + plotdata = sub_df[['word','counts']].groupby('counts').count().reset_index() + # plotdata = sub_df_w_counts + + fig, ax = plt.subplots(figsize=(8,8)) + ax.bar(plotdata.counts, wordlengths.word) + ax.set_xlabel("Word Length") + ax.set_ylabel("Number of Keywords") + ax.set_title(f"Number of Keywords v/s Word Length for {l}") + save_path = plot_saves + f"{l}.png" + fig.savefig(f"{save_path}") \ No newline at end of file diff --git a/eda/plot2.ipynb b/eda/plot2.ipynb new file mode 100644 index 0000000..1b08cbd --- /dev/null +++ b/eda/plot2.ipynb @@ -0,0 +1 @@ +{"cells":[{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[],"source":["\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","import pickle\n","import pandas as pd\n","import numpy as np\n","\n","from pathlib import Path\n","import collections\n","from collections import Counter\n","\n","from tqdm import tqdm\n","\n","# import plotly.express as px\n","\n","base = Path(\"/mnt/disks/std750\")\n","\n","data = pd.read_csv(base / \"data\" / \"csvs\" / \"new4.csv\")\n","main_data = pd.read_csv(base / \"data\" / \"csvs\" / \"new3.csv\")\n",""]},{"cell_type":"code","execution_count":2,"metadata":{},"outputs":[{"output_type":"error","ename":"KeyError","evalue":"'count'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3360\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3361\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3362\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n","\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n","\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: 'count'","\nThe above exception was the direct cause of the following exception:\n","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmain_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'count'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m>=\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mlanguages\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'language'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mplot_saves\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"plots/wordlengths/\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0ml\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtqdm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlanguages\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3453\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlevels\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3454\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3455\u001b[0;31m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3456\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3457\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3361\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3362\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3363\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3364\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3365\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_scalar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0misna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhasnans\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: 'count'"]}],"source":"main_data = main_data[main_data['count']>=5]\nlanguages = main_data['language'].unique()\nplot_saves = \"plots/wordlengths/\"\nfor l in tqdm(languages):\n\n sub_df = main_data[main_data['language']==l]\n words = sub_df['word'].unique().tolist()\n\n wordlengths = {}\n for w in words:\n if type(w) == str:\n if len(w) in wordlengths:\n wordlengths[len(w)] += 1\n else:\n wordlengths[len(w)] = 1\n\n fig, ax = plt.subplots(figsize=(8,8))\n ax.bar(wordlengths.keys(), wordlengths.values())\n ax.set_xlabel(\"Word Length\")\n ax.set_ylabel(\"Number of Keywords\")\n ax.set_title(f\"Number of Keywords v/s Word Length for {l}\")\n save_path = plot_saves + f\"{l}.png\"\n # fig.savefig(f\"{save_path}\")"},{"cell_type":"code","execution_count":3,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" index word counts language\n","0 0 che 9624 it\n","1 1 per 8938 it\n","2 2 del 8419 it\n","3 3 non 7403 it\n","4 4 della 7323 it\n","... ... ... ... ...\n","354274 16073 данных» 0 ru\n","354275 16074 старше… 0 ru\n","354276 16075 специальности» 0 ru\n","354277 16076 абстракциониста» 0 ru\n","354278 16077 месте… 0 ru\n","\n","[354279 rows x 4 columns]"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
indexwordcountslanguage
00che9624it
11per8938it
22del8419it
33non7403it
44della7323it
...............
35427416073данных»0ru
35427516074старше…0ru
35427616075специальности»0ru
35427716076абстракциониста»0ru
35427816077месте…0ru
\n

354279 rows × 4 columns

\n
"},"metadata":{},"execution_count":3}],"source":"main_data"},{"cell_type":"code","execution_count":4,"metadata":{},"outputs":[{"output_type":"display_data","data":{"text/plain":"
","image/svg+xml":"\n\n\n \n \n \n \n 2021-08-06T17:28:07.042979\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n"},"metadata":{"needs_background":"light"}}],"source":"main_data = main_data[main_data['counts']>=5]\nlanguages = main_data['language'].unique()\nplot_saves = \"plots/wordlengths/\"\nl = 'en'\n# for l in tqdm(languages):\n\nsub_df = main_data[main_data['language']==l]\nwords = sub_df['word'].unique().tolist()\n\nwordlengths = {}\nfor w in words:\n if type(w) == str:\n if len(w) in wordlengths:\n wordlengths[len(w)] += 1\n else:\n wordlengths[len(w)] = 1\n\nfig, ax = plt.subplots(figsize=(8,8))\nax.bar(wordlengths.keys(), wordlengths.values())\nax.set_xlabel(\"Word Length\")\nax.set_ylabel(\"Number of Keywords\")\nax.set_title(f\"Number of Keywords v/s Word Length for {l}\")\nsave_path = plot_saves + f\"{l}.png\"\n # fig.savefig(f\"{save_path}\")"},{"cell_type":"code","execution_count":5,"metadata":{},"outputs":[{"output_type":"error","ename":"AttributeError","evalue":"'dict' object has no attribute 'word'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0max\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msubplots\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfigsize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m8\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m8\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mplotdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcounts\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwordlengths\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mword\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 8\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_xlabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Word Length\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_ylabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Number of Keywords\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mAttributeError\u001b[0m: 'dict' object has no attribute 'word'"]}],"source":" sub_df = main_data[main_data['language']==l]\n\n plotdata = sub_df[['word','counts']].groupby('counts').count().reset_index()\n # plotdata = sub_df_w_counts\n\n fig, ax = plt.subplots(figsize=(8,8))\n ax.bar(plotdata.counts, wordlengths.word)\n ax.set_xlabel(\"Word Length\")\n ax.set_ylabel(\"Number of Keywords\")\n ax.set_title(f\"Number of Keywords v/s Word Length for {l}\")\n # save_path = plot_saves + f\"{l}.png\""},{"cell_type":"code","execution_count":6,"metadata":{},"outputs":[{"output_type":"error","ename":"AttributeError","evalue":"'dict' object has no attribute 'word'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0max\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msubplots\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfigsize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m8\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m8\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mplotdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcounts\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwordlengths\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mword\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 8\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_xlabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Word Length\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_ylabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Number of Keywords\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mAttributeError\u001b[0m: 'dict' object has no attribute 'word'"]}],"source":" sub_df = main_data[main_data['language']==l]\n\n plotdata = sub_df[['word','counts']].groupby('counts').count().reset_index()\n # plotdata = sub_df_w_counts\n\n fig, ax = plt.subplots(figsize=(8,8))\n ax.bar(plotdata.counts, wordlengths.word)\n ax.set_xlabel(\"Word Length\")\n ax.set_ylabel(\"Number of Keywords\")\n ax.set_title(f\"Number of Keywords v/s Word Length for {l}\")\n # save_path = plot_saves + f\"{l}.png\""},{"cell_type":"code","execution_count":7,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["{3: 936,\n"," 4: 2786,\n"," 5: 4616,\n"," 6: 6156,\n"," 7: 6585,\n"," 9: 4882,\n"," 10: 3402,\n"," 8: 5952,\n"," 13: 640,\n"," 11: 2066,\n"," 12: 1157,\n"," 14: 251,\n"," 15: 120,\n"," 16: 14,\n"," 17: 3,\n"," 18: 1}"]},"metadata":{},"execution_count":7}],"source":"wordlengths"},{"cell_type":"code","execution_count":8,"metadata":{},"outputs":[{"output_type":"error","ename":"ValueError","evalue":"shape mismatch: objects cannot be broadcast to a single shape","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0max\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msubplots\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfigsize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m8\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m8\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mplotdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcounts\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwordlengths\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 8\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_xlabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Word Length\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_ylabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Number of Keywords\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/matplotlib/__init__.py\u001b[0m in \u001b[0;36minner\u001b[0;34m(ax, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1359\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0minner\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1360\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mdata\u001b[0m \u001b[0;32mis\u001b[0m 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iterable too.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2306\u001b[0m np.atleast_1d(x), height, width, y, linewidth, hatch)\n","\u001b[0;32m<__array_function__ internals>\u001b[0m in \u001b[0;36mbroadcast_arrays\u001b[0;34m(*args, **kwargs)\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/numpy/lib/stride_tricks.py\u001b[0m in \u001b[0;36mbroadcast_arrays\u001b[0;34m(subok, *args)\u001b[0m\n\u001b[1;32m 536\u001b[0m \u001b[0margs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_m\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msubok\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msubok\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0m_m\u001b[0m \u001b[0;32min\u001b[0m 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\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/numpy/lib/stride_tricks.py\u001b[0m in \u001b[0;36m_broadcast_shape\u001b[0;34m(*args)\u001b[0m\n\u001b[1;32m 418\u001b[0m \u001b[0;31m# use the old-iterator because np.nditer does not handle size 0 arrays\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 419\u001b[0m \u001b[0;31m# consistently\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 420\u001b[0;31m \u001b[0mb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbroadcast\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m32\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 421\u001b[0m \u001b[0;31m# unfortunately, it cannot handle 32 or more arguments directly\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 422\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mpos\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m32\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m31\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mValueError\u001b[0m: shape mismatch: objects cannot be broadcast to a single shape"]}],"source":" sub_df = main_data[main_data['language']==l]\n\n plotdata = sub_df[['word','counts']].groupby('counts').count().reset_index()\n # plotdata = sub_df_w_counts\n\n fig, ax = plt.subplots(figsize=(8,8))\n ax.bar(plotdata.counts, wordlengths.keys())\n ax.set_xlabel(\"Word Length\")\n ax.set_ylabel(\"Number of Keywords\")\n ax.set_title(f\"Number of Keywords v/s Word Length for {l}\")\n # save_path = plot_saves + f\"{l}.png\""},{"cell_type":"code","execution_count":9,"metadata":{},"outputs":[{"output_type":"error","ename":"ValueError","evalue":"shape mismatch: objects cannot be broadcast to a single shape","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0max\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msubplots\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfigsize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m8\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m8\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mplotdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcounts\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwordlengths\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 9\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_xlabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Word Length\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_ylabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Number of Keywords\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/matplotlib/__init__.py\u001b[0m in \u001b[0;36minner\u001b[0;34m(ax, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1359\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0minner\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1360\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mdata\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1361\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0mmap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msanitize_sequence\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1362\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1363\u001b[0m \u001b[0mbound\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnew_sig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbind\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/matplotlib/axes/_axes.py\u001b[0m in \u001b[0;36mbar\u001b[0;34m(self, x, height, width, bottom, align, **kwargs)\u001b[0m\n\u001b[1;32m 2302\u001b[0m \u001b[0myerr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_convert_dx\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0myerr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconvert_yunits\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2303\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2304\u001b[0;31m x, height, width, y, linewidth, hatch = np.broadcast_arrays(\n\u001b[0m\u001b[1;32m 2305\u001b[0m \u001b[0;31m# Make args iterable too.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2306\u001b[0m np.atleast_1d(x), height, width, y, linewidth, hatch)\n","\u001b[0;32m<__array_function__ internals>\u001b[0m in \u001b[0;36mbroadcast_arrays\u001b[0;34m(*args, **kwargs)\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/numpy/lib/stride_tricks.py\u001b[0m in \u001b[0;36mbroadcast_arrays\u001b[0;34m(subok, *args)\u001b[0m\n\u001b[1;32m 536\u001b[0m \u001b[0margs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_m\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msubok\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msubok\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0m_m\u001b[0m \u001b[0;32min\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 537\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 538\u001b[0;31m \u001b[0mshape\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_broadcast_shape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 539\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 540\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mall\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mshape\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0marray\u001b[0m \u001b[0;32min\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/numpy/lib/stride_tricks.py\u001b[0m in \u001b[0;36m_broadcast_shape\u001b[0;34m(*args)\u001b[0m\n\u001b[1;32m 418\u001b[0m \u001b[0;31m# use the old-iterator because np.nditer does not handle size 0 arrays\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 419\u001b[0m \u001b[0;31m# consistently\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 420\u001b[0;31m \u001b[0mb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbroadcast\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m32\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 421\u001b[0m \u001b[0;31m# unfortunately, it cannot handle 32 or more arguments directly\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 422\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mpos\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m32\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m31\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mValueError\u001b[0m: shape mismatch: objects cannot be broadcast to a single shape"]}],"source":" sub_df = main_data[main_data['language']==l]\n\n\n plotdata = sub_df[['word','counts']].groupby('counts').count().reset_index()\n # plotdata = sub_df_w_counts\n\n fig, ax = plt.subplots(figsize=(8,8))\n ax.bar(plotdata.counts, wordlengths.keys())\n ax.set_xlabel(\"Word Length\")\n ax.set_ylabel(\"Number of Keywords\")\n ax.set_title(f\"Number of Keywords v/s Word Length for {l}\")\n # save_path = plot_saves + f\"{l}.png\""},{"cell_type":"code","execution_count":10,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":10}],"source":"plotdata.count"},{"cell_type":"code","execution_count":11,"metadata":{},"outputs":[{"output_type":"error","ename":"NameError","evalue":"name 'splotdata' is not defined","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msplotdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcount\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;31mNameError\u001b[0m: name 'splotdata' is not defined"]}],"source":"splotdata.count"},{"cell_type":"code","execution_count":12,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["0 5\n","1 6\n","2 7\n","3 8\n","4 9\n"," ... \n","1782 69139\n","1783 80814\n","1784 100463\n","1785 131469\n","1786 150846\n","Name: counts, Length: 1787, dtype: int64"]},"metadata":{},"execution_count":12}],"source":"plotdata.counts"},{"cell_type":"code","execution_count":13,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" counts word\n","0 5 3794\n","1 6 2700\n","2 7 2502\n","3 8 2049\n","4 9 1668\n","... ... ...\n","1782 69139 1\n","1783 80814 1\n","1784 100463 1\n","1785 131469 1\n","1786 150846 1\n","\n","[1787 rows x 2 columns]"],"text/html":"
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"},"metadata":{},"execution_count":13}],"source":"plotdata"},{"cell_type":"code","execution_count":14,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0.5, 1.0, 'Number of Keywords v/s Word Length for en')"]},"metadata":{},"execution_count":14},{"output_type":"display_data","data":{"text/plain":"
","image/svg+xml":"\n\n\n \n \n \n \n 2021-08-06T17:30:24.030127\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n"},"metadata":{"needs_background":"light"}}],"source":" sub_df = main_data[main_data['language']==l]\n\n\n plotdata = sub_df[['word','counts']].groupby('counts').count().reset_index()\n # plotdata = sub_df_w_counts\n\n fig, ax = plt.subplots(figsize=(8,8))\n ax.bar(plotdata.counts, plotdata.word)\n ax.set_xlabel(\"Word Length\")\n ax.set_ylabel(\"Number of Keywords\")\n ax.set_title(f\"Number of Keywords v/s Word Length for {l}\")\n # save_path = plot_saves + f\"{l}.png\""},{"cell_type":"code","execution_count":15,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" index word counts language\n","0 0 che 9624 it\n","1 1 per 8938 it\n","2 2 del 8419 it\n","3 3 non 7403 it\n","4 4 della 7323 it\n","... ... ... ... ...\n","354102 15901 нептунием 5 ru\n","354103 15902 поддерживается 5 ru\n","354104 15903 барнаулом 5 ru\n","354105 15904 березы 5 ru\n","354106 15905 окончена 5 ru\n","\n","[347772 rows x 4 columns]"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
indexwordcountslanguage
00che9624it
11per8938it
22del8419it
33non7403it
44della7323it
...............
35410215901нептунием5ru
35410315902поддерживается5ru
35410415903барнаулом5ru
35410515904березы5ru
35410615905окончена5ru
\n

347772 rows × 4 columns

\n
"},"metadata":{},"execution_count":15}],"source":"main_data"},{"cell_type":"code","execution_count":16,"metadata":{},"outputs":[{"output_type":"error","ename":"TypeError","evalue":"object of type 'float' has no len()","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'wl'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'word'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/series.py\u001b[0m in \u001b[0;36mapply\u001b[0;34m(self, func, convert_dtype, args, **kwargs)\u001b[0m\n\u001b[1;32m 4354\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mfloat64\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4355\u001b[0m \"\"\"\n\u001b[0;32m-> 4356\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mSeriesApply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconvert_dtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4357\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4358\u001b[0m def _reduce(\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/apply.py\u001b[0m in \u001b[0;36mapply\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1034\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply_str\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1035\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1036\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply_standard\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1037\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1038\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0magg\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/apply.py\u001b[0m in \u001b[0;36mapply_standard\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1090\u001b[0m \u001b[0;31m# List[Union[Callable[..., Any], str]]]]]\"; expected\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1091\u001b[0m \u001b[0;31m# \"Callable[[Any], Any]\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1092\u001b[0;31m mapped = lib.map_infer(\n\u001b[0m\u001b[1;32m 1093\u001b[0m \u001b[0mvalues\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1094\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;31m# type: ignore[arg-type]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/_libs/lib.pyx\u001b[0m in \u001b[0;36mpandas._libs.lib.map_infer\u001b[0;34m()\u001b[0m\n","\u001b[0;31mTypeError\u001b[0m: object of type 'float' has no len()"]}],"source":"main_data['wl'] = main_data['word'].apply(len)"},{"cell_type":"code","execution_count":17,"metadata":{},"outputs":[],"source":"# main_data['wl'] = main_data['word'].apply(len)"},{"cell_type":"code","execution_count":18,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["0 che\n","1 per\n","2 del\n","3 non\n","4 della\n"," ... \n","354102 нептунием\n","354103 поддерживается\n","354104 барнаулом\n","354105 березы\n","354106 окончена\n","Name: word, Length: 347772, dtype: object"]},"metadata":{},"execution_count":18}],"source":"main_data['word']"},{"cell_type":"code","execution_count":19,"metadata":{},"outputs":[{"output_type":"error","ename":"ValueError","evalue":"Columns must be same length as key","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'word'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmain_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__setitem__\u001b[0;34m(self, key, value)\u001b[0m\n\u001b[1;32m 3597\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_setitem_array\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3598\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mDataFrame\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3599\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_set_item_frame_value\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3600\u001b[0m elif is_list_like(value) and 1 < len(\n\u001b[1;32m 3601\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_indexer_for\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_set_item_frame_value\u001b[0;34m(self, key, value)\u001b[0m\n\u001b[1;32m 3722\u001b[0m \u001b[0mlen_cols\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m1\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_scalar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcols\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcols\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3723\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mlen_cols\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3724\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Columns must be same length as key\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3725\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3726\u001b[0m \u001b[0;31m# align right-hand-side columns if self.columns\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mValueError\u001b[0m: Columns must be same length as key"]}],"source":"main_data['word'] = main_data.astype(str)"},{"cell_type":"code","execution_count":20,"metadata":{},"outputs":[{"output_type":"stream","name":"stderr","text":["/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/frame.py:3607: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n self._set_item(key, value)\n"]}],"source":"main_data['word'] = main_data['word'].astype(str)"},{"cell_type":"code","execution_count":21,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["0 che\n","1 per\n","2 del\n","3 non\n","4 della\n"," ... \n","354102 нептунием\n","354103 поддерживается\n","354104 барнаулом\n","354105 березы\n","354106 окончена\n","Name: word, Length: 347772, dtype: object"]},"metadata":{},"execution_count":21}],"source":"main_data['word']"},{"cell_type":"code","execution_count":22,"metadata":{},"outputs":[{"output_type":"stream","name":"stderr","text":["/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py:1773: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n self._setitem_single_column(ilocs[0], value, pi)\n"]}],"source":"main_data.loc[:,'word'] = main_data.loc[:,'word'].astype(str)"},{"cell_type":"code","execution_count":23,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["dtype('O')"]},"metadata":{},"execution_count":23}],"source":"main_data['word'].dtype"},{"cell_type":"code","execution_count":24,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["dtype('O')"]},"metadata":{},"execution_count":24}],"source":"main_data['word'].dtype"},{"cell_type":"code","execution_count":25,"metadata":{},"outputs":[{"output_type":"stream","name":"stderr","text":["/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/frame.py:3607: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n self._set_item(key, value)\n"]}],"source":"main_data['wl'] = main_data['word'].str.len()"},{"cell_type":"code","execution_count":26,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" index word counts language wl\n","0 0 che 9624 it 3\n","1 1 per 8938 it 3\n","2 2 del 8419 it 3\n","3 3 non 7403 it 3\n","4 4 della 7323 it 5\n","... ... ... ... ... ..\n","354102 15901 нептунием 5 ru 9\n","354103 15902 поддерживается 5 ru 14\n","354104 15903 барнаулом 5 ru 9\n","354105 15904 березы 5 ru 6\n","354106 15905 окончена 5 ru 8\n","\n","[347772 rows x 5 columns]"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
indexwordcountslanguagewl
00che9624it3
11per8938it3
22del8419it3
33non7403it3
44della7323it5
..................
35410215901нептунием5ru9
35410315902поддерживается5ru14
35410415903барнаулом5ru9
35410515904березы5ru6
35410615905окончена5ru8
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347772 rows × 5 columns

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"},"metadata":{},"execution_count":26}],"source":"main_data"},{"cell_type":"code","execution_count":27,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([ 3, 5, 4, 6, 7, 8, 15, 10, 9, 11, 13, 14, 12, 18, 16, 17, 19,\n"," 20, 21, 22, 24, 26, 23, 25, 29, 27, 28, 31, 33, 34, 30])"]},"metadata":{},"execution_count":27}],"source":"main_data['wl'].unique()"},{"cell_type":"code","execution_count":28,"metadata":{},"outputs":[{"output_type":"error","ename":"AttributeError","evalue":"'DataFrame' object has no attribute 'bar'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'counts'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'wl'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbar\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m 5476\u001b[0m ):\n\u001b[1;32m 5477\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5478\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mobject\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__getattribute__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 5479\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5480\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mAttributeError\u001b[0m: 'DataFrame' object has no attribute 'bar'"]}],"source":"main_data[['counts','wl']].bar"},{"cell_type":"code","execution_count":29,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":29},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"main_data[['counts','wl']].plot()"},{"cell_type":"code","execution_count":30,"metadata":{},"outputs":[{"output_type":"error","ename":"KeyboardInterrupt","evalue":"","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'counts'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'wl'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'bar'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 970\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlabel_name\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 971\u001b[0m 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out, **kwargs)\u001b[0m\n\u001b[1;32m 84\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mreduction\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mout\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mpasskwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 85\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 86\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mufunc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreduce\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mout\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mpasskwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 87\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 88\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mKeyboardInterrupt\u001b[0m: "]}],"source":"main_data[['counts','wl']].plot(kind='bar')"},{"cell_type":"code","execution_count":31,"metadata":{},"outputs":[{"output_type":"error","ename":"KeyError","evalue":"'count'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3360\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3361\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3362\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n","\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n","\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: 'count'","\nThe above exception was the direct cause of the following exception:\n","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'counts'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'wl'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'wl'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'count'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'bar'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 956\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 957\u001b[0m \u001b[0;31m# don't overwrite\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 958\u001b[0;31m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 959\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 960\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mABCSeries\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3453\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlevels\u001b[0m \u001b[0;34m>\u001b[0m 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\u001b[0;34m[\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3361\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3362\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3363\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3364\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3365\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_scalar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0misna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhasnans\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: 'count'"]}],"source":"main_data[['counts','wl']].plot(x='wl',y='count',kind='bar')"},{"cell_type":"code","execution_count":32,"metadata":{},"outputs":[{"output_type":"error","ename":"SyntaxError","evalue":"invalid syntax (2288672763.py, line 1)","traceback":["\u001b[0;36m File \u001b[0;32m\"/tmp/ipykernel_11406/2288672763.py\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m main_data[['language']='en'][['counts','wl']]\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"]}],"source":"main_data[['language']='en'][['counts','wl']]"},{"cell_type":"code","execution_count":33,"metadata":{},"outputs":[{"output_type":"error","ename":"KeyError","evalue":"False","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3360\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3361\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3362\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n","\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n","\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: False","\nThe above exception was the direct cause of the following exception:\n","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'language'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;34m'en'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'counts'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'wl'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3453\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlevels\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3454\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3455\u001b[0;31m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3456\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3457\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3361\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3362\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3363\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3364\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3365\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_scalar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0misna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhasnans\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: False"]}],"source":"main_data[['language']=='en'][['counts','wl']]"},{"cell_type":"code","execution_count":34,"metadata":{},"outputs":[{"output_type":"error","ename":"SyntaxError","evalue":"unmatched ']' (3493353706.py, line 1)","traceback":["\u001b[0;36m File \u001b[0;32m\"/tmp/ipykernel_11406/3493353706.py\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m main_data[['language']=='en']]\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m unmatched ']'\n"]}],"source":"main_data[['language']=='en']]"},{"cell_type":"code","execution_count":35,"metadata":{},"outputs":[{"output_type":"error","ename":"SyntaxError","evalue":"unmatched ']' (2738966241.py, line 1)","traceback":["\u001b[0;36m File \u001b[0;32m\"/tmp/ipykernel_11406/2738966241.py\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m main_data[main_data['language']=='en']]\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m unmatched ']'\n"]}],"source":"main_data[main_data['language']=='en']]"},{"cell_type":"code","execution_count":36,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" index word counts language wl\n","256041 0 was 150846 en 3\n","256042 1 and 131469 en 3\n","256043 2 you 100463 en 3\n","256044 3 that 80814 en 4\n","256045 4 his 69139 en 3\n","... ... ... ... ... ..\n","295605 39564 metastasized 5 en 12\n","295606 39565 wyeth 5 en 5\n","295607 39566 allegories 5 en 10\n","295608 39567 mcmurtry 5 en 8\n","295609 39568 massa 5 en 5\n","\n","[39569 rows x 5 columns]"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
indexwordcountslanguagewl
2560410was150846en3
2560421and131469en3
2560432you100463en3
2560443that80814en4
2560454his69139en3
..................
29560539564metastasized5en12
29560639565wyeth5en5
29560739566allegories5en10
29560839567mcmurtry5en8
29560939568massa5en5
\n

39569 rows × 5 columns

\n
"},"metadata":{},"execution_count":36}],"source":"main_data[main_data['language']=='en']"},{"cell_type":"code","execution_count":37,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" counts wl\n","256041 150846 3\n","256042 131469 3\n","256043 100463 3\n","256044 80814 4\n","256045 69139 3\n","... ... ..\n","295605 5 12\n","295606 5 5\n","295607 5 10\n","295608 5 8\n","295609 5 5\n","\n","[39569 rows x 2 columns]"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
countswl
2560411508463
2560421314693
2560431004633
256044808144
256045691393
.........
295605512
29560655
295607510
29560858
29560955
\n

39569 rows × 2 columns

\n
"},"metadata":{},"execution_count":37}],"source":"main_data[main_data['language']=='en'][['counts','wl']]"},{"cell_type":"code","execution_count":38,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" wl index counts\n","0 3 15738778 1388789\n","1 4 46312098 1647976\n","2 5 82082363 1145729\n","3 6 118427591 872236\n","4 7 129742247 741493\n","5 8 121102618 511727\n","6 9 102230560 339622\n","7 10 73175533 204458\n","8 11 44888745 103044\n","9 12 25346222 56223\n","10 13 14548718 25893\n","11 14 5740898 9492\n","12 15 3065969 2513\n","13 16 322479 362\n","14 17 69691 53\n","15 18 38586 5"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
wlindexcounts
03157387781388789
14463120981647976
25820823631145729
36118427591872236
47129742247741493
58121102618511727
69102230560339622
71073175533204458
81144888745103044
9122534622256223
10131454871825893
111457408989492
121530659692513
1316322479362
14176969153
1518385865
\n
"},"metadata":{},"execution_count":38}],"source":"main_data[main_data['language']=='en'].groupby('wl').sum().reset_index()"},{"cell_type":"code","execution_count":39,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" index counts\n","wl \n","3 15738778 1388789\n","4 46312098 1647976\n","5 82082363 1145729\n","6 118427591 872236\n","7 129742247 741493\n","8 121102618 511727\n","9 102230560 339622\n","10 73175533 204458\n","11 44888745 103044\n","12 25346222 56223\n","13 14548718 25893\n","14 5740898 9492\n","15 3065969 2513\n","16 322479 362\n","17 69691 53\n","18 38586 5"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
indexcounts
wl
3157387781388789
4463120981647976
5820823631145729
6118427591872236
7129742247741493
8121102618511727
9102230560339622
1073175533204458
1144888745103044
122534622256223
131454871825893
1457408989492
1530659692513
16322479362
176969153
18385865
\n
"},"metadata":{},"execution_count":39}],"source":"main_data[main_data['language']=='en'].groupby('wl').sum()"},{"cell_type":"code","execution_count":40,"metadata":{},"outputs":[{"output_type":"error","ename":"KeyError","evalue":"\"['index'] not found in axis\"","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'language'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;34m'en'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroupby\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'wl'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'index'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/util/_decorators.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 309\u001b[0m \u001b[0mstacklevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstacklevel\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 310\u001b[0m )\n\u001b[0;32m--> 311\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 312\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 313\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[1;32m 4899\u001b[0m \u001b[0mweight\u001b[0m \u001b[0;36m1.0\u001b[0m \u001b[0;36m0.8\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4900\u001b[0m \"\"\"\n\u001b[0;32m-> 4901\u001b[0;31m return super().drop(\n\u001b[0m\u001b[1;32m 4902\u001b[0m \u001b[0mlabels\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4903\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[1;32m 4145\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabels\u001b[0m \u001b[0;32min\u001b[0m \u001b[0maxes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4146\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mlabels\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4147\u001b[0;31m \u001b[0mobj\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_drop_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4148\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4149\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m_drop_axis\u001b[0;34m(self, labels, axis, level, errors)\u001b[0m\n\u001b[1;32m 4180\u001b[0m \u001b[0mnew_axis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4181\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4182\u001b[0;31m \u001b[0mnew_axis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4183\u001b[0m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0maxis_name\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mnew_axis\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4184\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, errors)\u001b[0m\n\u001b[1;32m 6016\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mmask\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0many\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6017\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0merrors\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m\"ignore\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 6018\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"{labels[mask]} not found in axis\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 6019\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m~\u001b[0m\u001b[0mmask\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6020\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdelete\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: \"['index'] not found in axis\""]}],"source":"main_data[main_data['language']=='en'].groupby('wl').sum().drop('index')"},{"cell_type":"code","execution_count":41,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" counts\n","wl \n","3 1388789\n","4 1647976\n","5 1145729\n","6 872236\n","7 741493\n","8 511727\n","9 339622\n","10 204458\n","11 103044\n","12 56223\n","13 25893\n","14 9492\n","15 2513\n","16 362\n","17 53\n","18 5"],"text/html":"
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counts
wl
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"},"metadata":{},"execution_count":41}],"source":"main_data[main_data['language']=='en'].groupby('wl').sum().drop('index', axis=1)"},{"cell_type":"code","execution_count":42,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":42},{"output_type":"display_data","data":{"text/plain":"
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axis=1).plot(kind='bar')"},{"cell_type":"code","execution_count":43,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":43},{"output_type":"display_data","data":{"text/plain":"
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axis=1).plot(kind='bar', figsize=(10,10))"},{"cell_type":"code","execution_count":44,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":44},{"output_type":"display_data","data":{"text/plain":"
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axis=1).plot(kind='bar', figsize=(10,10))"},{"cell_type":"code","execution_count":45,"metadata":{},"outputs":[{"output_type":"error","ename":"SyntaxError","evalue":"invalid syntax (332369716.py, line 1)","traceback":["\u001b[0;36m File \u001b[0;32m\"/tmp/ipykernel_11406/332369716.py\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m main_data[]\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"]}],"source":"main_data[]"},{"cell_type":"code","execution_count":46,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":46},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"main_data[main_data['language']=='en'].groupby('wl').sum().drop('index', axis=1).plot(kind='bar', figsize=(10,10), xlabel='Word Length', ylabel='Total Audio Clips', title='Total Audio Clips v/s Word Length in English')"},{"cell_type":"code","execution_count":47,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":47},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"main_data[main_data['language']=='en'].groupby('wl').sum().drop('index', axis=1).plot(kind='bar', figsize=(10,10), xlabel='Word Length', ylabel='Total Audio Clips', title='Total Audio Clips v/s Word Length in English')"},{"cell_type":"code","execution_count":48,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["0"]},"metadata":{},"execution_count":48}],"source":"(main_data['counts']<5).sum()"},{"cell_type":"code","execution_count":49,"metadata":{},"outputs":[{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"main_data[main_data['language']=='en'].groupby('wl').sum().drop('index', axis=1).plot(kind='bar', figsize=(10,10), xlabel='Word Length', ylabel='Total Audio Clips', title='Total Audio Clips v/s Word Length in English')\nplt.savefig('check.png')"},{"cell_type":"code","execution_count":50,"metadata":{},"outputs":[{"output_type":"stream","name":"stderr","text":[" 42%|████▏ | 20/48 [00:02<00:03, 7.46it/s]/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/plotting/_matplotlib/core.py:345: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n"," fig = self.plt.figure(figsize=self.figsize)\n","100%|██████████| 48/48 [00:08<00:00, 5.85it/s]\n"]},{"output_type":"display_data","data":{"text/plain":"
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KlRAwtqSbZOckaSXyS5NMlbu/Z/SXJNkgu6115967wjyZVJLk/y3L72Pbu2K5McOqiaJUmSWjLIJxMsBf6hqs5PsiFwXpLTu3kfr6r/179wku2BVwI7AFsC303yiG72Z4DnAIuAc5PMr6pfDLB2SZKkoRtYUKuq64Druunbk1wGbDXOKvsAJ1XVn4BfJ7kS2KWbd2VVXQWQ5KRuWYOaJEma0abkHLUkc4HHAT/tmt6c5KIkxyTZpGvbCri6b7VFXdtY7Svu4+AkC5IsWLx48WQfgiRJ0pQbeFBLsgHwZeBtVXUbcCSwLbAzvR63j07Gfqrq6KqaV1XzZs+ePRmblCRJGqpBnqNGknXphbQTquorAFV1Q9/8zwLf7D5eA2zdt/qcro1x2iVJkmasQV71GeDzwGVV9bG+9i36FnsxcEk3PR94ZZL1kmwDbAf8DDgX2C7JNknuR++Cg/mDqluSJKkVg+xReyqwP3Bxkgu6tncCr0qyM1DAQuANAFV1aZKT6V0ksBR4U1XdDZDkzcC3gbWBY6rq0gHWLUmS1IRBXvV5FpBRZp02zjofBD44Svtp460nSZI0E/lkAkmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkho1sKCWZOskZyT5RZJLk7y1a980yelJrujeN+nak+STSa5MclGSx/dt64Bu+SuSHDComiVJkloyyB61pcA/VNX2wJOANyXZHjgU+F5VbQd8r/sM8Dxgu+51MHAk9IIdcBjwRGAX4LCRcCdJkjSTDSyoVdV1VXV+N307cBmwFbAPcFy32HHAi7rpfYDjq+cnwMZJtgCeC5xeVUuq6hbgdGDPQdUtSZLUiik5Ry3JXOBxwE+Bzavqum7W9cDm3fRWwNV9qy3q2sZqlyRJmtEGHtSSbAB8GXhbVd3WP6+qCqhJ2s/BSRYkWbB48eLJ2KQkSdJQDTSoJVmXXkg7oaq+0jXf0A1p0r3f2LVfA2zdt/qcrm2s9uVU1dFVNa+q5s2ePXtyD0SSJGkIBnnVZ4DPA5dV1cf6Zs0HRq7cPAD4el/7q7urP58E/K4bIv02sEeSTbqLCPbo2iRJkma0dQa47acC+wMXJ7mga3sncDhwcpLXAr8BXtHNOw3YC7gSuAM4CKCqliR5P3But9z7qmrJAOuWJElqwsCCWlWdBWSM2buPsnwBbxpjW8cAx0xedZIkSe3zyQSSJEmNMqhJkiQ1yqAmSZLUKIOaJElSowxqkiRJjTKoSZIkNcqgJkmS1CiDmiRJUqMMapIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqAmSZLUKIOaJElSowxqkiRJjTKoSZIkNcqgJkmS1CiDmiRJUqMMapIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqAmSZLUKIOaJElSowxqkiRJjTKoSZIkNcqgJkmS1CiDmiRJUqMMapIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqAmSZLUKIOaJElSowxqkiRJjTKoSZIkNcqgJkmS1CiDmiRJUqMMapIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqAmSZLUKIOaJElSowxqkiRJjTKoSZIkNcqgJkmS1CiDmiRJUqMMapIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqAmSZLUKIOaJElSowxqkiRJjTKoSZIkNWqlQS3JtknW66Z3TXJIko0HXpkkSdIabiI9al8G7k7ycOBoYGvgiwOtSpIkSRMKasuqainwYuBTVfWPwBaDLUuSJEkTCWp3JXkVcADwza5t3cGVJEmSJJhYUDsIeDLwwar6dZJtgP8YbFmSJElaaVCrql8AbwcuTfJY4Jqq+vDAK5MkSVrDrbOyBZLsDRwF/A8QYJskb6iq/x50cZIkSWuylQY14KPAblV1JfRu1wGcChjUJEmSBmgi56jdPhLSOlcBtw+oHkmSJHUm0qO2IMlpwMlAAS8Hzk3yEoCq+soA65MkSVpjTSSorQ/cADyz+7wYuD/wAnrBzaAmSZI0ACsNalV10FQUIkmSpOWNGdSS/FNV/d8kn6LXc7acqjpkoJVJkiSt4cbrUbuse18wFYVIkiRpeWMGtar6Rvd+3NSVI0mSpBHjDX1+g1GGPEdU1QsHUpEkSZKA8Yc+/9+UVSFJkqR7GS+o/QKY3T3r8x5Jtqd3iw5JkiQN0HhPJvgUMGuU9s2ATwymHEmSJI0YL6g9vKrOXLGxqn4E7Di4kiRJkgTjB7UNx5m37mQXIkmSpOWNF9SuTLLXio1JnkfvwezjSnJMkhuTXNLX9i9JrklyQffaq2/eO5JcmeTyJM/ta9+za7syyaETPzRJkqTpbbyLCd4GnJrkFcB5Xds84MnA8yew7S8AnwaOX6H941W13BWl3QUKrwR2ALYEvpvkEd3szwDPARbRexj8/BUvcJAkSZqJxuxRq6orgMcCPwTmdq8fAjtW1a9WtuHu/LYlE6xjH+CkqvpTVf0auBLYpXtdWVVXVdWfgZO6ZSVJkma8cR/KXlV/Ao6d5H2+Ocmr6T2a6h+q6hZgK+Anfcss6toArl6h/YmjbTTJwcDBAA95yEMmuWRJkqSpN945aoNwJLAtsDNwHfDRydpwVR1dVfOqat7s2bMna7OSJElDM26P2mSrqhtGppN8Fvhm9/EaYOu+Red0bYzTLkmSNKNNqEctyf2SPKZ73edbcyTZou/ji4GRK0LnA69Msl6SbYDtgJ8B5wLbJdkmyf3oXXAw/77uX5IkaTpZaY9akl2B44CFQICtkxww2s1wV1jvRGBXYFaSRcBhwK5Jdqb3sPeFwBsAqurSJCfTe2zVUuBNVXV3t503A98G1gaOqapLV/EYJUmSpqWJDH1+FNijqi4H6G6bcSLwhPFWqqpXjdL8+XGW/yDwwVHaTwNOm0CdkiRJM8pEhj7XHQlpAN2tOXwygSRJ0oBNpEdtQZLPAf/Zfd6P3q01JEmSNEATCWp/B7wJOKT7/CPg3wZWkSRJkoAJBLXuprcf616SJEmaImMGtSQnV9UrklxM7yrN5VTVjgOtTJIkaQ03Xo/aW7v3iTyAXZIkSZNszKBWVdd177+ZunIkSZI0Yryhz9sZZchzRFVtNJCKJEmSBIzfo7YhQJL303uA+n/QezLBfsAWY60nSZKkyTGR23O8sKp26vt8ZJILgfcMqCZJo5h76KlTur+Fh+89pfuTJN3bRJ5M8Ick+yVZO8laSfYD/jDowiRJktZ0Ewlq+wKvAG7oXi/v2iRJkjRAE7nh7UJgn8GXIkmSpH4rDWpJjmX0G96+ZiAVSZIkCZjYxQTf7JteH3gxcO1gypEkSdKIiQx9frn/c5ITgbMGVpEkSZKAiV1MsKLtgL+a7EIkSZK0vImco7biEwquB/7PwCqSJEkSMLGhzw2nohBJkiQtb5WGPpNsm+Sfk1w6qIIkSZLUs9KglmTLJH+f5Fzg0m6dVw68MkmSpDXcmEEtycFJzgB+AGwKvBa4rqreW1UXT1F9kiRJa6zxzlH7NHAOsG9VLQBIcq8b30qSJGkwxgtqW9B7rudHkzwYOBlYd0qqkiRJ0thDn1V1c1UdVVXPBHYHbgVuSHJZkn+dqgIlSZLWVBO66rOqFlXVR6tqHr0HtN852LIkSZI0kWd9LqeqfgW8bwC1SJIkqc99eYSUJEmSpoBBTZIkqVFjDn0mefx4K1bV+ZNfjiRJkkaMd47aR8eZV8CzJrkWSZIk9RkzqFXVblNZiCRJkpY3oas+kzwG2B5Yf6Stqo4fVFGSJEmaQFBLchiwK72gdhrwPOAswKAmSZI0QBO56vNl9J5McH1VHQTsBDxooFVJkiRpQkHtj1W1DFiaZCPgRmDrwZYlSZKkiZyjtiDJxsBngfOA3wPnDLIoSZIkTSCoVdUbu8mjknwL2KiqLhpsWZIkSVrp0GeS741MV9XCqrqov02SJEmDMd6TCdYHHgDMSrIJkG7WRsBWU1CbJEnSGm28oc83AG8DtgT6Hxd1G/DpAdYkSZIkxn8ywSeATyR5S1V9agprkiRJEhO76vPfkxwCPKP7/APg36vqroFVJUmSpAkFtX8D1u3eAfYHjgReN6iiJEmSNP7FBOtU1VLgr6tqp75Z309y4eBLkyRJWrONd3uOn3XvdyfZdqQxycOAuwdalSRJksYd+hy5HcfbgTOSXNV9ngscNMiiJEmSNH5Qm53k77vpfwfW7qbvBh4HnDHIwiRJktZ04wW1tYEN+EvPWv86Gw6sIkmSJAHjB7Xrqup9U1aJJEmSljPexQQr9qRJkiRpCo0X1HafsiokSZJ0L2MGtapaMpWFSJIkaXnj9ahJkiRpiAxqkiRJjTKoSZIkNcqgJkmS1CiDmiRJUqMMapIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqAmSZLUKIOaJElSowxqkiRJjTKoSZIkNcqgJkmS1CiDmiRJUqMMapIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqAmSZLUKIOaJElSowxqkiRJjTKoSZIkNcqgJkmS1CiDmiRJUqMMapIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNGlhQS3JMkhuTXNLXtmmS05Nc0b1v0rUnySeTXJnkoiSP71vngG75K5IcMKh6JUmSWjPIHrUvAHuu0HYo8L2q2g74XvcZ4HnAdt3rYOBI6AU74DDgicAuwGEj4U6SJGmmG1hQq6ozgSUrNO8DHNdNHwe8qK/9+Or5CbBxki2A5wKnV9WSqroFOJ17hz9JkqQZaarPUdu8qq7rpq8HNu+mtwKu7ltuUdc2Vvu9JDk4yYIkCxYvXjy5VUuSJA3B0C4mqKoCahK3d3RVzauqebNnz56szUqSJA3NVAe1G7ohTbr3G7v2a4Ct+5ab07WN1S5JkjTjTXVQmw+MXLl5APD1vvZXd1d/Pgn4XTdE+m1gjySbdBcR7NG1SZIkzXjrDGrDSU4EdgVmJVlE7+rNw4GTk7wW+A3wim7x04C9gCuBO4CDAKpqSZL3A+d2y72vqla8QEGSJGlGGlhQq6pXjTFr91GWLeBNY2znGOCYSSxNkiRpWvDJBJIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqAmSZLUKIOaJElSowxqkiRJjTKoSZIkNcqgJkmS1CiDmiRJUqMMapIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqAmSZLUKIOaJElSowxqkiRJjTKoSZIkNcqgJkmS1CiDmiRJUqMMapIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqAmSZLUKIOaJElSowxqkiRJjTKoSZIkNcqgJkmS1CiDmiRJUqMMapIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqAmSZLUKIOaJElSowxqkiRJjTKoSZIkNcqgJkmS1CiDmiRJUqMMapIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqAmSZLUKIOaJElSowxqkiRJjTKoSZIkNcqgJkmS1Kh1hl2AJAHMPfTUKd3fwsP3ntL9SdJ9YY+aJElSowxqkiRJjTKoSZIkNcqgJkmS1CiDmiRJUqMMapIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqAmSZLUKIOaJElSowxqkiRJjTKoSZIkNcqgJkmS1CiDmiRJUqMMapIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqAmSZLUKIOaJElSowxqkiRJjRpKUEuyMMnFSS5IsqBr2zTJ6Umu6N436dqT5JNJrkxyUZLHD6NmSZKkqTbMHrXdqmrnqprXfT4U+F5VbQd8r/sM8Dxgu+51MHDklFcqSZI0BC0Nfe4DHNdNHwe8qK/9+Or5CbBxki2GUJ8kSdKUGlZQK+A7Sc5LcnDXtnlVXddNXw9s3k1vBVzdt+6irm05SQ5OsiDJgsWLFw+qbkmSpCmzzpD2+7SquibJXwGnJ/ll/8yqqiS1KhusqqOBowHmzZu3SutKkiS1aCg9alV1Tfd+I/BVYBfghpEhze79xm7xa4Ct+1af07VJkiTNaFMe1JI8MMmGI9PAHsAlwHzggG6xA4Cvd9PzgVd3V38+Cfhd3xCpJEnSjDWMoc/Nga8mGdn/F6vqW0nOBU5O8lrgN8AruuVPA/YCrgTuAA6a+pIlSZKm3pQHtaq6CthplPabgd1HaS/gTVNQmiRJUlNauj2HJEmS+hjUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhq1zrALkKSZbu6hp07p/hYevveU7k/S4NijJkmS1CiDmiRJUqMMapIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqAmSZLUKIOaJElSowxqkiRJjTKoSZIkNcqgJkmS1CiDmiRJUqMMapIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqAmSZLUKIOaJElSowxqkiRJjTKoSZIkNWqdYRcgSZre5h566pTub+Hhe0/p/qRhskdNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElq1DrDLkCSpJbNPfTUKd3fwsP3ntL9qW32qEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqs+JUlag3lVa9umTY9akj2TXJ7kyiSHDrseSZKkQZsWPWpJ1gY+AzwHWAScm2R+Vf1iuJVJkqSWTfcew+nSo7YLcGVVXVVVfwZOAvYZck2SJEkDlaoadg0rleRlwJ5V9bru8/7AE6vqzX3LHAwc3H18JHD5FJY4C7hpCvc31Ty+6c3jm75m8rGBxzfdeXyT56FVNXu0GdNi6HMiqupo4Ohh7DvJgqqaN4x9TwWPb3rz+KavmXxs4PFNdx7f1JguQ5/XAFv3fZ7TtUmSJM1Y0yWonQtsl2SbJPcDXgnMH3JNkiRJAzUthj6rammSNwPfBtYGjqmqS4dcVr+hDLlOIY9vevP4pq+ZfGzg8U13Ht8UmBYXE0iSJK2JpsvQpyRJ0hrHoCZJktQog5okSVKjpsXFBK1JsgtQVXVuku2BPYFfVtVpQy5tIJIcX1WvHnYdg5DkafSefHFJVX1n2PWsjiRPBC6rqtuS3B84FHg88AvgX6vqd0MtcDUlOQT4alVdPexaBqHvivZrq+q7SfYFngJcBhxdVXcNtcBJkORhwEvo3W7pbuBXwBer6rahFiY1zIsJVlGSw4Dn0Qu5pwNPBM6g9xzSb1fVB4dY3mpLsuJtTwLsBnwfoKpeOOVFTaIkP6uqXbrp1wNvAr4K7AF8o6oOH2Z9qyPJpcBO3VXSRwN3AF8Cdu/aXzLUAldTkt8BfwD+BzgROKWqFg+3qsmT5AR6f688ALgV2AD4Cr3vL1V1wPCqW31d0H4+cCawF/Bzesf5YuCNVfWDoRUnNcygtoqSXAzsDKwHXA/M6evB+GlV7TjM+lZXkvPp9cB8Dih6Qe1Eev/Tp6p+OLzqVl+Sn1fV47rpc4G9qmpxkgcCP6mqxw63wvsuyWVV9ehu+vyqenzfvAuqauehFTcJkvwceALwbOBvgBcC59H7/fxKVd0+xPJWW5KLqmrHJOvQu6H3llV1d5IAF86Av1suBnbujukBwGlVtWuShwBfH/lzOV0leRDwDuBFwF/R+/vzRuDrwOFVdevQitNKJXkwcBiwDHgP8BbgpfR6tN9aVdcNqzbPUVt1S6vq7qq6A/ifkS77qvojvS94uptH7x+/dwG/6/6X+8eq+uF0D2mdtZJskmQzev9RWQxQVX8Alg63tNV2SZKDuukLk8wDSPIIYNoPm9E73WBZVX2nql4LbAn8G71TD64abmmTYq1u+HNDer1qD+ra1wPWHVpVk2vkdJv16PUYUlW/ZWYc38nALcCuVbVpVW1GbzTilm7ejJXkv4ddwyT4Ar1OiqvpjZL9kV7P74+Ao4ZXlueo3Rd/TvKALqg9YaSx+9/UtA9qVbUM+HiSU7r3G5hZvycPohdEA1SSLarquiQbdG3T2euATyR5N70HCZ+T5Gp6f/G8bqiVTY7lvp/unK35wPyuh2a6+zzwS3o39X4XcEqSq4AnAScNs7BJ8jng3CQ/BZ4OfBggyWxgyTALmyRzq+rD/Q1VdT3w4SSvGVJNkybJ48eaRW+UabrbvKo+BZDkjX3f5aeSvHaIdTn0uaqSrFdVfxqlfRawRVVdPISyBibJ3sBTq+qdw65lkLp/6Devql8Pu5bVlWQjYBt6AXtRVd0w5JImRZJHVNWvhl3HICXZEqCqrk2yMb1h3t9W1c+GWtgkSbID8Gh6F+/8ctj1TKYk3wG+Cxw38mcuyebAgcBzqurZQyxvtSW5G/gho/+H9klVdf8pLmlSJbmwqnbqpj9QVe/um3fxME+LMahJkrSakmxC70rrfeidowZwA71e38Or6pZh1TYZklwCvLiqrhhl3tVVtfUQypo0Sd4H/N+q+v0K7Q+n9/29bDiVGdQkSRqoJAdV1bHDrmN1JHkZcHFVXT7KvBdV1demvqqpMezvz6AmSdIAJfltVT1k2HUMyrCDzKAN+/szqEmStJqSXDTWLOARVbXeVNYzlYYdZCZDy9/fTLqaT5KkYdkceC6923H0C3D21JczuVYSZDafyloGpNnvz6AmSdLq+yawQVVdsOKMJD+Y8momX7NBZpI0+/059ClJksaV5PPAsVV11ijzvlhV+w6hrDWCQU2SJKlRPkJKkiSpUQY1SZKkRhnUJE0rST6e5G19n7+d5HN9nz+a5O/v47Z3TfLNibZPliQbJ3njVO1P0vRhUJM03fwYe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v4PPvhg9t57b7beemuOPPJIDjrooLtH5f7lX/5lRl5DqmpGOmrJ4sWLa+nSpaMuQ5Kktdoll1zCox71qFGX0ZSJvidJzqmqxRPt79SnJElSowxqkiRJjTKoSZKkoVkTT7G6v+7P98KgJkmShmKDDTbghhtuMKzRhbQbbriBDTbY4D49z6s+JUnSUCxcuJDly5ezYsWKUZfShA022ICFCxfep+cY1CRJ0lCst956bL/99qMuY05z6lOSJKlRa/2I2qJDTxlKv7P9oX6SJGnN44iaJElSowxqkiRJjTKoSZIkNcqgJkmS1CiDmiRJUqMMapIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqAmSZLUKIOaJElSowxqkiRJjTKoSZIkNcqgJkmS1KihBrUkmyY5KcmPklyS5MlJNk9yapJL+6+b9fsmyfuSXJbk/CS7DvSzpN//0iRLhlmzJElSK4Y9ovZe4MtV9UhgZ+AS4FDg61W1A/D1fh3gOcAO/eNg4CiAJJsDhwFPBHYDDhsLd5IkSWuyoQW1JJsATwc+DFBVv6uqm4B9geP63Y4Dnt8v7wt8rDpnApsm2Qp4NnBqVa2sqhuBU4G9h1W3JElSK4Y5orY9sAL4SJLzknwoyYOBLavq6n6fa4At++VtgCsGnr+8b5usfRVJDk6yNMnSFStWzPBLkSRJmn3DDGrzgF2Bo6rq8cBvuGeaE4CqKqBm4mBVdUxVLa6qxQsWLJiJLiVJkkZqmEFtObC8qs7q10+iC27X9lOa9F+v67dfCWw78PyFfdtk7ZIkSWu0oQW1qroGuCLJI/qmPYGLgZOBsSs3lwCf75dPBl7eX/35JOCX/RTpV4C9kmzWX0SwV98mSZK0Rps35P5fA3wiyQOAy4GD6MLhiUleAfwceHG/7xeBfYDLgFv6famqlUneBpzd7/fWqlo55LolSZJGbqhBrap+ACyeYNOeE+xbwKsn6edY4NgZLU6SJKlx3plAkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRg01qCVZluSCJD9IsrRv2zzJqUku7b9u1rcnyfuSXJbk/CS7DvSzpN//0iRLhlmzJElSK2ZjRG2Pqtqlqhb364cCX6+qHYCv9+sAzwF26B8HA0dBF+yAw4AnArsBh42FO0mSpDXZKKY+9wWO65ePA54/0P6x6pwJbJpkK+DZwKlVtbKqbgROBfae5ZolSZJm3bCDWgFfTXJOkoP7ti2r6up++Rpgy355G+CKgecu79sma19FkoOTLE2ydMWKFTP5GiRJkkZi3pD7/8OqujLJ7wGnJvnR4MaqqiQ1EweqqmOAYwAWL148I31KkiSN0lBH1Krqyv7rdcBn6c4xu7af0qT/el2/+5XAtgNPX9i3TdYuSZK0RhtaUEvy4CQbjS0DewEXAicDY1duLgE+3y+fDLy8v/rzScAv+ynSrwB7Jdmsv4hgr75NkiRpjTbMqc8tgc8mGTvO8VX15SRnAycmeQXwc+DF/f5fBPYBLgNuAQ4CqKqVSd4GnN3v99aqWjnEuiVJkpowtKBWVZcDO0/QfgOw5wTtBbx6kr6OBY6d6RolSZJa5p0JJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJatTQg1qSdZOcl+QL/fr2Sc5KclmS/07ygL59/X79sn77ooE+3ti3/zjJs4ddsyRJUgtmY0TttcAlA+vvBN5TVQ8HbgRe0be/Arixb39Pvx9JHg28FNgJ2Bv4YJJ1Z6FuSZKkkRpqUEuyEHgu8KF+PcAzgZP6XY4Dnt8v79uv02/fs99/X+CEqrqtqn4GXAbsNsy6JUmSWjDsEbUjgTcAd/XrWwA3VdUd/fpyYJt+eRvgCoB++y/7/e9un+A5d0tycJKlSZauWLFihl+GJEnS7BtaUEvyx8B1VXXOsI4xqKqOqarFVbV4wYIFs3FISZKkoZo3xL6fCjwvyT7ABsDGwHuBTZPM60fNFgJX9vtfCWwLLE8yD9gEuGGgfczgcyRJktZYQxtRq6o3VtXCqlpEdzHAaVW1P3A6sF+/2xLg8/3yyf06/fbTqqr69pf2V4VuD+wAfH9YdUuSJLVimCNqk/lH4IQkhwPnAR/u2z8MfDzJZcBKunBHVV2U5ETgYuAO4NVVdefsly1JkjS7ZiWoVdUZwBn98uVMcNVmVd0KvGiS578dePvwKpQkSWqPdyaQJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJatQoPp5D99OiQ0+Z8T6XHfHcGe9TkiTNDEfUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIatdqgluRhSdbvl3dPckiSTYdemSRJ0lpuOiNqnwbuTPJw4BhgW+D4oVYlSZKkaQW1u6rqDuBPgfdX1euBrYZbliRJkqYT1G5P8mfAEuALfdt6wytJkiRJML2gdhDwZODtVfWzJNsDHx9uWZIkSVptUKuqi4F/AC5K8ljgyqp659ArkyRJWsvNW90OSZ4LHA38FAiwfZK/qKovDbs4SZKktdlqgxrwLmCPqroMuo/rAE4BDGqSJElDNJ1z1G4eC2m9y4Gbh1SPJEmSetMZUVua5IvAiUABLwLOTvICgKr6zBDrkyRJWmtNJ6htAFwLPKNfXwE8EPgTuuBmUJMkSRqC1Qa1qjpoNgqRJEnSqiYNakneUFX/muT9dCNnq6iqQ4ZamSRJ0lpuqhG1S/qvS2ejEEmSJK1q0qBWVf/Tfz1u9sqRJEnSmKmmPv+HCaY8x1TV84ZSkSRJkoCppz7//1mrQpIkSfcyVVC7GFjQ3+vzbkkeTfcRHZIkSRqiqe5M8H5g/gTtWwDvHU45kiRJGjNVUHt4VX1zfGNVfQt43PBKkiRJEkwd1DaaYtt6M12IJEmSVjVVULssyT7jG5M8h+7G7JIkSRqiqS4meB1wSpIXA+f0bYuBJwN/POS6JEmS1nqTjqhV1aXAY4FvAIv6xzeAx1XVT2ajOEmSpLXZlDdlr6rbgI/MUi2SJEkaMNU5apIkSRohg5okSVKjppz6HJPkAcCO/eqPq+r24ZUkSZIkmEZQS7I7cBywDAiwbZIlE30YriRJkmbOdEbU3gXsVVU/BkiyI/BJ4AnDLEySJGltN51z1NYbC2kA/UdzeGcCSZKkIZvOiNrSJB8C/qtf3x9YOrySJEmSBNMLan8FvBo4pF//FvDBoVUkSZIkYBpBrf/Q23f3D0mSJM2SSYNakhOr6sVJLgBq/PaqetxQK5MkSVrLTTWi9tr+qzdglyRJGoFJg1pVXd1//fnslSNJkqQxU0193swEU55jqmrjoVQkSZIkYOoRtY0AkrwNuBr4ON2dCfYHtpqV6iRJktZi0/nA2+dV1Qer6uaq+lVVHQXsO+zCJEmS1nbTCWq/SbJ/knWTrJNkf+A3wy5MkiRpbTedoPYy4MXAtf3jRX2bJEmShmg6H3i7DKc6JUmSZt1qg1qSjzDxB97++VAqkiRJEjC9e31+YWB5A+BPgauGU44kSZLGTGfq89OD60k+CXx7aBVJkiQJmN7FBOPtAPzeTBciSZKkVU3nHLXxdyi4BvjHoVUkSZIkYHpTnxvNRiGSJEla1X2a+kzysCT/J8lFwypIkiRJndUGtSRbJ/m7JGcDF/XPeenQK5MkSVrLTRrUkhyc5HTgDGBz4BXA1VX1lqq6YJbqkyRJWmtNdY7aB4DvAS+rqqUASe71wbeSJEkajqmC2lZ09/V8V5LfB04E1puVqiRJkjT51GdV3VBVR1fVM4A9gZuAa5NckuQds1WgJEnS2mpaV31W1fKqeldVLaa7Qfutwy1LkiRJ07nX5yqq6ifAW4dQiyRJkgbcn1tISZIkaRYY1CRJkho16dRnkl2nemJVnTvV9iQbAN8E1u+Pc1JVHZZke+AEYAvgHOCAqvpdkvWBjwFPAG4AXlJVy/q+3kj3OW53AodU1Vem9/IkSZLmrqnOUXvXFNsKeOZq+r4NeGZV/TrJesC3k3wJ+DvgPVV1QpKj6QLYUf3XG6vq4UleCrwTeEmSR9PdCWEnYGvga0l2rKo7p/MCJUmS5qpJg1pV7fG/6biqCvh1v7pe/xgLeC/r248D/pkuqO3bLwOcBHwgSfr2E6rqNuBnSS4DdqP7MF5JkqQ11rSu+kzyGODRwAZjbVX1sWk8b1266c2HA/8O/BS4qaru6HdZDmzTL28DXNH3fUeSX9JNj24DnDnQ7eBzBo91MHAwwHbbbTedlyVJktS06dyU/TDg/f1jD+BfgedNp/OqurOqdgEW0o2CPfJ+V7r6Yx1TVYuravGCBQuGdRhJkqRZM52rPvejuzPBNVV1ELAzsMl9OUhV3QScDjwZ2DTJ2EjeQuDKfvlKYFuAfvsmdBcV3N0+wXMkSZLWWNMJar+tqruAO5JsDFzHqsFpQkkWJNm0X34g8EfAJXSBbb9+tyXA5/vlk/t1+u2n9ee5nQy8NMn6/RWjOwDfn0bdkiRJc9p0zlFb2geu/6Q73+zXTO9E/q2A4/rz1NYBTqyqLyS5GDghyeHAecCH+/0/DHy8v1hgJd2VnlTVRUlOBC4G7gBe7RWfkiRpbbDaoFZVf90vHp3ky8DGVXX+NJ53PvD4CdovpztfbXz7rcCLJunr7cDbV3dMSZKkNcl0Lib4+thyVS2rqvMH2yRJkjQcU92ZYAPgQcD8JJsB6TdtzAQfjyFJkqSZNdXU518Ar6O7G8Dg7aJ+BXxgiDVJkiSJqe9M8F7gvUleU1Xvn8WaJEmSxPSu+vyPJIcAT+/XzwD+o6puH1pVkiRJmlZQ+yDdfTo/2K8fQHdvzlcOqyhJkiRNfTHBvP6enH9QVTsPbDotyQ+HX5okSdLabaqP5xj79P87kzxsrDHJQwE/cFaSJGnIppr6HPs4jn8ATk9yeb++CDhomEVJkiRp6qC2IMnf9cv/AazbL99Jd8eB04dZmCRJ0tpuqqC2LrAh94ysDT5no6FVJEmSJGDqoHZ1Vb111iqRJEnSKqa6mGD8SJokSZJm0VRBbc9Zq0KSJEn3MmlQq6qVs1mIJEmSVjXViJokSZJGyKAmSZLUKIOaJElSowxqkiRJjTKoSZIkNcqgJkmS1CiDmiRJUqMMapIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqAmSZLUKIOaJElSowxqkiRJjTKoSZIkNcqgJkmS1CiDmiRJUqMMapIkSY2aN+oCtGZadOgpM97nsiOeO+N9SpLUMkfUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWrUvFEXII3aokNPmfE+lx3x3BnvU5K09nFETZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaNbSglmTbJKcnuTjJRUle27dvnuTUJJf2Xzfr25PkfUkuS3J+kl0H+lrS739pkiXDqlmSJKklwxxRuwP4+6p6NPAk4NVJHg0cCny9qnYAvt6vAzwH2KF/HAwcBV2wAw4DngjsBhw2Fu4kSZLWZEMLalV1dVWd2y/fDFwCbAPsCxzX73Yc8Px+eV/gY9U5E9g0yVbAs4FTq2plVd0InArsPay6JUmSWjEr56glWQQ8HjgL2LKqru43XQNs2S9vA1wx8LTlfdtk7eOPcXCSpUmWrlixYmZfgCRJ0ggMPagl2RD4NPC6qvrV4LaqKqBm4jhVdUxVLa6qxQsWLJiJLiVJkkZqqEEtyXp0Ie0TVfWZvvnafkqT/ut1ffuVwLYDT1/Yt03WLkmStEYb5lWfAT4MXFJV7x7YdDIwduXmEuDzA+0v76/+fBLwy36K9CvAXkk26y8i2KtvkyRJWqPNG2LfTwUOAC5I8oO+7U3AEcCJSV4B/Bx4cb/ti8A+wGXALcBBAFW1MsnbgLP7/d5aVSuHWLckSVIThhbUqurbQCbZvOcE+xfw6kn6OhY4duaqkyRJap93JpAkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJatS8URcgafoWHXrKjPe57IjnznifkqSZ4YiaJElSowxqkiRJjTKoSZIkNcqgJkmS1KihBbUkxya5LsmFA22bJzk1yaX918369iR5X5LLkpyfZNeB5yzp9780yZJh1StJktSaYY6ofRTYe1zbocDXq2oH4Ov9OsBzgB36x8HAUdAFO+Aw4InAbsBhY+FOkiRpTTe0oFZV3wRWjmveFziuXz4OeP5A+8eqcyawaZKtgGcDp1bVyqq6ETiVe4c/SZKkNdJsn6O2ZVVd3S9fA2zZL28DXDGw3/K+bbL2e0lycJKlSZauWLFiZquWJEkagZFdTFBVBdQM9ndMVS2uqsULFiyYqW4lSZJGZraD2rX9lCb91+v69iuBbQf2W9i3TdYuSZK0xpvtoHYyMHbl5hLg8wPtL++v/nwS8Mt+ivQrwF5JNusvItirb5MkSVrjDe1en0k+CewOzE+ynO7qzSOAE5O8Avg58OJ+9y8C+wCXAbcABwFU1cokbwPO7vd7a1WNv0BBkiRpjTS0oFZVfzbJpj0n2LeAV0/Sz7HAsTNYmiRJ0pzgnQkkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWqUQU2SJKlRBjVJkqRGGdQkSZIaZVCTJElqlEFNkiSpUQY1SZKkRhnUJEmSGmVQkyRJapRBTZIkqVEGNUmSpEYZ1CRJkhplUJMkSWrUvFEXIGnNtOjQU2a8z2VHPHfG+5SkljmiJkmS1CiDmiRJUqMMapIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqAmSZLUKIOaJElSowxqkiRJjTKoSZIkNcqgJkmS1CiDmiRJUqMMapIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqAmSZLUqHmjLkCSRm3RoafMeJ/LjnjujPcpae3jiJokSVKjDGqSJEmNMqhJkiQ1yqAmSZLUKIOaJElSowxqkiRJjTKoSZIkNcqgJkmS1CiDmiRJUqMMapIkSY0yqEmSJDXKe31K0hzifUmltYsjapIkSY0yqEmSJDXKoCZJktQog5okSVKjDGqSJEmNMqhJkiQ1yqAmSZLUKIOaJElSo/zAW0nSjBvGB/OCH86rtY8japIkSY0yqEmSJDXKoCZJktQoz1GTJK3VPJ9OLXNETZIkqVEGNUmSpEYZ1CRJkhplUJMkSWrUnAlqSfZO8uMklyU5dNT1SJIkDducuOozybrAvwN/BCwHzk5yclVdPNrKJEmaPV6huvaZKyNquwGXVdXlVfU74ARg3xHXJEmSNFSpqlHXsFpJ9gP2rqpX9usHAE+sqr8Z2Odg4OB+9RHAj4dQynzg+iH0OwzWOhxzpda5UidY67BY63BY63Cs7bU+pKoWTLRhTkx9TkdVHQMcM8xjJFlaVYuHeYyZYq3DMVdqnSt1grUOi7UOh7UOh7VObq5MfV4JbDuwvrBvkyRJWmPNlaB2NrBDku2TPAB4KXDyiGuSJEkaqjkx9VlVdyT5G+ArwLrAsVV10QhKGerU6gyz1uGYK7XOlTrBWofFWofDWofDWicxJy4mkCRJWhvNlalPSZKktY5BTZIkqVEGNUmSpEbNiYsJRiXJbkBV1dlJHg3sDfyoqr444tKmlORjVfXyUdexOkn+kO6uExdW1VdHXc+gJE8ELqmqXyV5IHAosCtwMfCOqvrlSAsckOQQ4LNVdcWoa1mdgau2r6qqryV5GfAU4BLgmKq6faQFjpPkocAL6D4e6E7gJ8DxVfWrkRYmaa3hxQSTSHIY8By6MHsq8ETgdLr7jX6lqt4+wvLulmT8x5QE2AM4DaCqnjfrRU0iyferard++VXAq4HPAnsB/1NVR4yyvkFJLgJ27q84Pga4BTgJ2LNvf8FICxyQ5JfAb4CfAp8EPlVVK0Zb1cSSfILu39SDgJuADYHP0H1fU1VLRlfdqvoA/MfAN4F9gPPoav5T4K+r6oyRFSetYZL8XlVdN+o6WmRQm0SSC4BdgPWBa4CFA6MrZ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7HTTjvlwAMPXHQZWzVDnwAAg9KjtoINzzxpYcde74cBAgDj0qMGADAoQQ0AYFCCGgDAoAQ1AIBBCWoAAIMS1AAABiWoAQAMSlADABiUoAYAMChBDQBgUIIaAMCgBDUAgEEJagAAgxLUAAAGJagBAAxKUAMAGJSgBgAwKEENAGBQghoAwKAENQCAQQlqAACDEtQAAAYlqAEADEpQAwAYlKAGADAoQQ0AYFCCGgDAoAQ1AIBBCWoAAIMS1AAABiWoAQAMSlADABiUoAYAMChBDQBgUIIaAMCgBDUAgEEJagAAgxLUAAAGJagBAAxKUAMAGJSgBgAwKEENAGBQghoAwKAENQCAQQlqAACDEtQAAAYlqAEADEpQAwAYlKAGADAoQQ0AYFCCGgDAoAQ1AIBBCWoAAIMS1AAABiWoAQAMSlADABiUoAYAMChBDQBgUIIaAMCgBDUAgEEJagAAgxLUAAAGJagBAAxKUAMAGJSgBgAwqLkGtar6tao6s6o+VVVvrKpdqurAqvpIVZ1dVX9XVTef1t15mj97Wr5h2X5+Z2r/bFU9cp41AwCMYm5Brar2S3JskoO7+x5JdkjyxCTPT/LC7r5jkkuTPHXa5KlJLp3aXzitl6q627Td3ZMcnuSlVbXDvOoGABjFvIc+d0zyPVW1Y5JbJLkwycOSnDAtf22Sx07TR0zzmZYfVlU1tb+pu7/d3Z9PcnaSQ+ZcNwDAws0tqHX3+Un+d5IvZhbQvpbk1CSXdfdV02obk+w3Te+X5Lxp26um9fda3r7CNgAA26x5Dn3umVlv2IFJ9k1yy8yGLud1vGOq6pSqOuWiiy6a12EAANbNPIc+H57k8919UXdfmeStSR6UZI9pKDRJ9k9y/jR9fpIDkmRafqskFy9vX2Gba3X3K7r74O4+eJ999pnH+QAArKt5BrUvJnlAVd1iutbssCSfTvKeJI+b1jkqydun6ROn+UzL393dPbU/cbor9MAkd0ry0TnWDQAwhB1veJWbprs/UlUnJDktyVVJTk/yiiQnJXlTVT13anvVtMmrkvxNVZ2d5JLM7vRMd59ZVW/OLORdleQZ3X31vOoGABjF3IJaknT3s5M8e5Pmc7LCXZvdfUWSx6+yn+cled4WLxAAYGDeTAAAMChBDQBgUIIaAMCgBDUAgEEJagAAgxLUAAAGJagBAAxKUAMAGJSgBgAwqLm+mYCty4ZnnrSwY5973GMWdmwAGJUeNQCAQQlqAACDEtQAAAYlqAEADEpQAwAYlKAGADAoQQ0AYFCCGgDAoAQ1AIBBCWoAAIMS1AAABiWoAQAMSlADABiUoAYAMChBDQBgUIIaAMCgBDUAgEEJagAAgxLUAAAGJagBAAxKUAMAGJSgBgAwKEENAGBQghoAwKAENQCAQQlqAACDEtQAAAYlqAEADEpQAwAYlKAGADAoQQ0AYFCCGgDAoAQ1AIBBCWoAAIMS1AAABiWoAQAMSlADABiUoAYAMChBDQBgUIIaAMCgBDUAgEEJagAAgxLUAAAGJagBAAxKUAMAGJSgBgAwKEENAGBQghoAwKAENQCAQQlqAACDEtQAAAYlqAEADEpQAwAYlKAGADAoQQ0AYFCCGgDAoAQ1AIBBCWoAAIMS1AAABiWoAQAMSlADABiUoAYAMChBDQBgUIIaAMCgBDUAgEEJagAAgxLUAAAGJagBAAxKUAMAGJSgBgAwKEENAGBQghoAwKAENQCAQQlqAACDEtQAAAYlqAEADEpQAwAYlKAGADAoQQ0AYFCCGgDAoAQ1AIBBCWoAAIMS1AAABiWoAQAMSlADABiUoAYAMChBDQBgUIIaAMCgBDUAgEEJagAAgxLUAAAGJagBAAxKUAMAGNRcg1pV7VFVJ1TVZ6rqrKp6YFXduqreVVWfmz7vOa1bVfXiqjq7qj5ZVfddtp+jpvU/V1VHzbNmAIBRzLtH7UVJ/rm775Lk3knOSvLMJP/W3XdK8m/TfJI8Ksmdpo9jkrwsSarq1kmeneT+SQ5J8uylcAcAsC2bW1Crqlsl+eEkr0qS7v5Od1+W5Igkr51We22Sx07TRyR5Xc98OMkeVXXbJI9M8q7uvqS7L03yriSHz6tuAIBRzLNH7cAkFyV5TVWdXlWvrKpbJrlNd184rfOlJLeZpvdLct6y7TdObau1AwBs0+YZ1HZMct8kL+vu+yT5Rv57mDNJ0t2dpLfEwarqmKo6papOueiii7bELgEAFmqeQW1jko3d/ZFp/oTMgtuXpyHNTJ+/Mi0/P8kBy7bff2pbrf06uvsV3X1wdx+8zz77bNETAQBYhLkFte7+UpLzqur7p6bDknw6yYlJlu7cPCrJ26fpE5P87HT35wOSfG0aIv2XJI+oqj2nmwgeMbUBAGzTdpzz/n85yeur6uZJzklydGbh8M1V9dQkX0jyhGnddyZ5dJKzk3xzWjfdfUlV/XGSj03rPae7L5lz3QAACzfXoNbdH09y8AqLDlth3U7yjFX28+okr96ixQEADM6bCQAABiWoAQAMSlADABiUoAYAMChBDQBgUIIaAMCgBDUAgEEJagAAgxLUAAAGJagBAAxKUAMAGJSgBgAwKEENAGBQghoAwKAENQCAQQlqAACDEtQAAAYlqAEADEpQAwAYlKAGADCoGwxqVXWHqtp5mj60qo6tqj3mXhkAwHZuLT1qf5/k6qq6Y5JXJDkgyRvmWhUAAGsKatd091VJfiLJS7r7N5Pcdr5lAQCwlqB2ZVX9TJKjkrxjattpfiUBAJCsLagdneSBSZ7X3Z+vqgOT/M18ywIA4AaDWnd/OslvJDmzqu6Z5Pzufv7cKwMA2M7teEMrVNVjkrw8yX8mqSQHVtX/7O5/mndxAADbsxsMaklekOSh3X12MntcR5KTkghqAABztJZr1C5fCmmTc5JcPqd6AACYrKVH7ZSqemeSNyfpJI9P8rGq+skk6e63zrE+AIDt1lqC2i5JvpzkIdP8RUm+J8mPZRbcBDUAgDm4waDW3UevRyEAAFzXqkGtqn6ru///qnpJZj1n19Hdx861MgCA7dzmetTOmj6fsh6FAABwXasGte7+x+nza9evHAAAlmxu6PMfs8KQ55Lu/vG5VAQAQJLND33+73WrAgCA69lcUPt0kn2md31eq6rultkjOgAAmKPNvZngJUn2XqF9ryQvmk85AAAs2VxQu2N3v3/Txu7+9yT3ml9JAAAkmw9qu21m2U5buhAAAK5rc0Ht7Kp69KaNVfWozF7MDgDAHG3uZoJfTXJSVT0hyalT28FJHpjkR+dcFwDAdm/VHrXu/lySeyZ5X5IN08f7ktyru/9jPYoDANiebfal7N397SSvWadaAABYZnPXqAEAsECCGgDAoDY79Lmkqm6e5M7T7Ge7+8r5lQQAQLKGoFZVhyZ5bZJzk1SSA6rqqJUehgsAwJazlh61FyR5RHd/Nkmq6s5J3pjkfvMsDABge7eWa9R2WgppSTI9msObCQAA5mwtPWqnVNUrk/ztNP/kJKfMryQAAJK1BbVfSPKMJMdO8/+e5KVzqwgAgCRrCGrTQ2//fPoAAGCdrBrUqurN3f2EqjojSW+6vLvvNdfKAAC2c5vrUfuV6bMXsAMALMCqQa27L5w+f2H9ygEAYMnmhj4vzwpDnku6e/e5VAQAQJLN96jtliRV9cdJLkzyN5m9meDJSW67LtXBOtjwzJMWduxzj3vMwo4NwPjW8sDbH+/ul3b35d399e5+WZIj5l0YAMD2bi1B7RtV9eSq2qGqblZVT07yjXkXBgCwvVtLUHtSkick+fL08fipDQCAOVrLA2/PjaFOAIB1d4NBrapek5UfePtzc6kIAIAka3vX5zuWTe+S5CeSXDCfcgAAWLKWoc+/Xz5fVW9M8oG5VQQAQJK13UywqTsl+R9buhAAAK5rLdeobfqGgi8l+e25VQQAQJK1DX3uth6FAABwXTdq6LOq7lBVv19VZ86rIAAAZm4wqFXVvlX161X1sSRnTts8ce6VAQBs51YNalV1TFW9J8l7k9w6yVOTXNjdf9TdZ6xTfQAA263NXaP2F0lOTvKk7j4lSarqeg++BQBgPjYX1G6b2Xs9X1BV35vkzUl2WpeqAABYfeizuy/u7pd390OSHJbksiRfrqqzqupP1qtAAIDt1Zru+uzujd39gu4+OLMXtF8x37IAAFjLuz6vo7v/I8lz5lALAADL3JRXSAEAsA4ENQCAQa069FlV993cht192pYvBwCAJZu7Ru0Fm1nWSR62hWsBAGCZVYNadz90PQsBAOC61nTXZ1XdI8ndkuyy1Nbdr5tXUQAArCGoVdWzkxyaWVB7Z5JHJflAEkENAGCO1nLX5+MyezPBl7r76CT3TnKruVYFAMCagtq3uvuaJFdV1e5JvpLkgPmWBQDAWq5RO6Wq9kjyV0lOTfJfSU6eZ1EAAKwhqHX3L06TL6+qf06ye3d/cr5lAQBwg0OfVfVvS9PdfW53f3J5GwAA87G5NxPskuQWSfauqj2T1LRo9yT7rUNtAADbtc0Nff7PJL+aZN8ky18X9fUkfzHHmgAAyObfTPCiJC+qql/u7pesY00AAGRtd33+ZVUdm+SHp/n3JvnL7r5yblUBALCmoPbSJDtNn5PkyCQvS/K0eRUFAMDmbybYsbuvSvID3X3vZYveXVWfmH9pAADbt809nuOj0+erq+oOS41VdfskV8+1KgAANjv0ufQ4jt9I8p6qOmea35Dk6HkWBQDA5oPaPlX169P0XybZYZq+Osl9krxnnoUBAGzvNhfUdkiya/67Z235NrvNrSIAAJJsPqhd2N3PWbdKAAC4js3dTLBpTxoAAOtoc0HtsHWrAgCA61k1qHX3JetZCAAA17W5HjUAABZo7kGtqnaoqtOr6h3T/IFV9ZGqOruq/q6qbj617zzNnz0t37BsH78ztX+2qh4575oBAEawHj1qv5LkrGXzz0/ywu6+Y5JLkzx1an9qkkun9hdO66Wq7pbkiUnunuTwJC+tqh0CALCNm2tQq6r9kzwmySun+UrysCQnTKu8Nsljp+kjpvlMyw+b1j8iyZu6+9vd/fkkZyc5ZJ51AwCMYN49ascn+a0k10zzeyW5bHrZe5JsTLLfNL1fkvOSZFr+tWn9a9tX2OZaVXVMVZ1SVadcdNFFW/g0AADW39yCWlX9aJKvdPep8zrGct39iu4+uLsP3meffdbjkAAAc7W5NxN8tx6U5Mer6tFJdkmye5IXJdmjqnaces32T3L+tP75SQ5IsrGqdkxyqyQXL2tfsnwbAIBt1tx61Lr7d7p7/+7ekNnNAO/u7idn9jL3x02rHZXk7dP0idN8puXv7u6e2p843RV6YJI7JfnovOoGABjFPHvUVvPbSd5UVc9NcnqSV03tr0ryN1V1dpJLMgt36e4zq+rNST6d5Kokz+juq9e/bACA9bUuQa2735vkvdP0OVnhrs3uviLJ41fZ/nlJnje/CgEAxuPNBAAAgxLUAAAGJagBAAxKUAMAGJSgBgAwKEENAGBQghoAwKAENQCAQQlqAACDEtQAAAYlqAEADEpQAwAYlKAGADAoQQ0AYFCCGgDAoAQ1AIBBCWoAAIMS1AAABiWoAQAMSlADABiUoAYAMChBDQBgUIIaAMCgBDUAgEEJagAAgxLUAAAGJagBAAxKUAMAGJSgBgAwKEENAGBQghoAwKAENQCAQQlqAACDEtQAAAa146ILABZjwzNPWtixzz3uMQs7NsDWRI8aAMCgBDUAgEEJagAAgxLUAAAGJagBAAxKUAMAGJSgBgAwKEENAGBQghoAwKAENQCAQQlqAACDEtQAAAYlqAEADEpQAwAYlKAGADAoQQ0AYFCCGgDAoAQ1AIBBCWoAAIMS1AAABiWoAQAMSlADABiUoAYAMChBDQBgUIIaAMCgBDUAgEEJagAAgxLUAAAGJagBAAxKUAMAGJSgBgAwKEENAGBQghoAwKAENQCAQQlqAACDEtQAAAYlqAEADEpQAwAYlKAGADAoQQ0AYFCCGgDAoAQ1AIBBCWoAAIMS1AAABiWoAQAMSlADABiUoAYAMChBDQBgUIIaAMCgBDUAgEEJagAAgxLUAAAGJagBAAxKUAMAGJSgBgAwKEENAGBQghoAwKAENQCAQQlqAACDEtQAAAYlqAEADEpQAwAYlKAGADAoQQ0AYFCCGgDAoAQ1AIBBCWoAAIMS1AAABjW3oFZVB1TVe6rq01V1ZlX9ytR+66p6V1V9bvq859ReVfXiqjq7qj5ZVfddtq+jpvU/V1VHzatmAICRzLNH7aok/6u775bkAUmeUVV3S/LMJP/W3XdK8m/TfJI8Ksmdpo9jkrwsmQW7JM9Ocv8khyR59lK4AwDYls0tqHX3hd192jR9eZKzkuyX5Igkr51We22Sx07TRyR5Xc98OMkeVXXbJI9M8q7uvqS7L03yriSHz6tuAIBRrMs1alW1Icl9knwkyW26+8Jp0ZeS3Gaa3i/Jecs22zi1rda+6TGOqapTquqUiy66aMueAADAAsw9qFXVrkn+PsmvdvfXly/r7k7SW+I43f2K7j64uw/eZ599tsQuAQAWaq5Brap2yiykvb673zo1f3ka0sz0+StT+/lJDli2+f5T22rtAADbtHne9VlJXpXkrO7+82WLTkyydOfmUUnevqz9Z6e7Px+Q5GvTEOm/JHlEVe053UTwiKkNAGCbtuMc9/2gJEcmOaOqPj61/W6S45K8uaqemuQLSZ4wLXtnkkcnOTvJN5McnSTdfUlV/XGSj03rPae7L5lj3QAAQ5hbUOvuDySpVRYftsL6neQZq+zr1UleveWqAwAYnzcTAAAMSlADABiUoAYAMChBDQBgUIIaAMCgBDUAgEEJagAAgxLUAAAGNc83EwAMZ8MzT1rYsc897jELOzawddKjBgAwKEENAGBQghoAwKAENQCAQQlqAACDEtQAAAYlqAEADEpQAwAYlKAGADAoQQ0AYFCCGgDAoAQ1AIBBCWoAAIMS1AAABiWoAQAMSlADABiUoAYAMChBDQBgUIIaAMCgBDUAgEEJagAAgxLUAAAGJagBAAxKUAMAGJSgBgAwKEENAGBQghoAwKAENQCAQQlqAACDEtQAAAYlqAEADEpQAwAYlKAGADAoQQ0AYFCCGgDAoAQ1AIBBCWoAAIMS1AAABiWoAQAMSlADABiUoAYAMChBDQBgUIIaAMCgBDUAgEEJagAAgxLUAAAGJagBAAxKUAMAGJSgBgAwKEENAGBQghoAwKAENQCAQQlqAACDEtQAAAYlqAEADEpQAwAYlKAGADAoQQ0AYFCCGgDAoAQ1AIBBCWoAAIMS1AAABiWoAQAMSlADABiUoAYAMChBDQBgUIIaAMCgBDUAgEEJagAAgxLUAAAGJagBAAxKUAMAGJSgBgAwKEENAGBQghoAwKAENQCAQQlqAACDEtQAAAYlqAEADEpQAwAYlKAGADAoQQ0AYFCCGgDAoAQ1AIBB7bjoAgCYvw3PPGlhxz73uMcs7NiwtdOjBgAwKEENAGBQghoAwKAENQCAQQlqAACDEtQAAAYlqAEADMpz1ADYZm2vz4/bXs97W6RHDQBgUFtNUKuqw6vqs1V1dlU9c9H1AADM21YR1KpqhyT/J8mjktwtyc9U1d0WWxUAwHxtLdeoHZLk7O4+J0mq6k1Jjkjy6YVWBQAMY1u8Nq+6ey473pKq6nFJDu/up03zRya5f3f/0rJ1jklyzDT7/Uk+u+6Fzuyd5KsLOvYiOe/ti/Pevjjv7YvzXn/f1937rLRga+lRu0Hd/Yokr1h0HVV1SncfvOg61pvz3r447+2L896+OO+xbBXXqCU5P8kBy+b3n9oAALZZW0tQ+1iSO1XVgVV18yRPTHLigmsCAJirrWLos7uvqqpfSvIvSXZI8uruPnPBZa1m4cOvC+K8ty/Oe/vivLcvznsgW8XNBAAA26OtZegTAGC7I6gBAAxKUAMAGNRWcTPByKrqkCTd3R+bXmt1eJLPdPc7F1zauqqq13X3zy66jvVUVT+U2VszPtXd/7roeualqu6f5Kzu/npVfU+SZya5b2ZvBvmT7v7aQguck6o6Nsk/dPd5i65lPS27s/6C7v6/VfWkJD+Y5Kwkr+juKxda4BxV1e2T/GRmj4O6Osl/JHlDd399oYWxXXMzwXehqp6d2ftHd0zyriT3T/KeJD+S5F+6+3kLLG9uqmrTR6NUkocmeXeSdPePr3tR66CqPtrdh0zTT0/yjCT/kOQRSf6xu49bZH3zUlVnJrn3dPf1K5J8M8kJSQ6b2n9yoQXOSVV9Lck3kvxnkjcmeUt3X7TYquavql6f2f9pt0hyWZJdk7w1s+93dfdRi6tufqZg/qNJ3p/k0UlOz+z8fyLJL3b3exdWHNs1Qe27UFVnJDkoyc5JvpRk/2W9Dh/p7nstsr55qarTMutNeWWSziyovTGzv8LT3e9bXHXzU1Wnd/d9pumPJXl0d19UVbdM8uHuvudiK5yPqjqru+86TZ/W3fddtuzj3X3Qwoqbo6o6Pcn9kjw8yU8n+fEkp2b2s/7W7r58geXNTVV9srvvVVU7ZvZg8X27++qqqiSf2Ib/XzsjyUHTud4iyTu7+9Cqul2Sty/929/WVNWtkvxOkscm+R+Z/Z/+lSRvT3Jcd1+2sOJI4hq179ZV3X11d38zyX8udY9397eSXLPY0ubq4Mx+YT0rydemvzS/1d3v21ZD2uRmVbVnVe2V2R85FyVJd38jyVWLLW2uPlVVR0/Tn6iqg5Okqu6cZJsdBsvskoZruvtfu/upSfZN8tLMLm84Z7GlzdXNpuHP3TLrVbvV1L5zkp0WVtX6WLocaOfMehLT3V/Mtn3eb05yaZJDu/vW3b1XZiMkl07LtjtV9U+LrmE516h9d75TVbeYgtr9lhqnv1C22aDW3dckeWFVvWX6/OVsHz9Lt8osoFaSrqrbdveFVbXr1LatelqSF1XV72X2wuKTq+q8JOdNy7ZV1/meTtdmnZjkxKnHZVv1qiSfyezh4s9K8paqOifJA5K8aZGFzdkrk3ysqj6S5MFJnp8kVbVPkksWWdicbeju5y9v6O4vJXl+Vf3cgmqau6q672qLMhspG4ahz+9CVe3c3d9eoX3vJLft7jMWUNa6q6rHJHlQd//uomtZhOmX9m26+/OLrmWeqmr3JAdmFso3dveXF1zSXFXVnbv7PxZdxyJU1b5J0t0XVNUemQ3/frG7P7rQwuasqu6e5K6Z3SD0mUXXsx6q6l+T/N8kr136N11Vt0nylCQ/0t0PX2B5c1NVVyd5X1b+I/sB3f0961zSqgQ1ANhOVdWemd3JfURm16glyZcz6z0+rrsvXVRt81RVn0ryE939uRWWndfdByygrBUJagDA9VTV0d39mkXXMQ9V9bgkZ3T3Z1dY9tjuftv6V7UyQQ0AuJ6q+mJ3327Rday30QKqoAYA26mq+uRqi5Lcubt3Xs96RjBaQN0e7tQDAFZ2mySPzOxxHMtVkg+tfznr4wYC6m3Ws5YbIqgBwPbrHUl27e6Pb7qgqt677tWsn60moApqALCdmh7mvNqyJ61nLetsqwmorlEDABiUV0gBAAxKUAMAGJSgBmxVquqFVfWry+b/papeuWz+BVX16zdx34dW1TvW2r6lVNUeVfWL63U8YOshqAFbmw8m+cEkqaqbJdk7yd2XLf/BrPGuraraYYtXd9PskeQXb2glYPsjqAFbmw8leeA0ffckn0pyeVXtWVU7Z/ZS7dOq6rCqOr2qzqiqV0/LUlXnVtXzq+q0JI+vqsOr6jPT/E/emEKq6hFVdXJVnVZVb6mqXZcd44+m9jOq6i5T+z5V9a6qOrOqXllVX6iqvZMcl+QOVfXxqvqzafe7VtUJU22vr6qVXh4NbOMENWCr0t0XJLmqqm6XWe/ZyUk+kll4OzjJGZn93/bXSX66u++Z2aOIfmHZbi7u7vsmeVuSv0ryY0nul+R711rHFLB+L8nDp32dkmT5kOtXp/aXJ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\n"},"metadata":{"needs_background":"light"}},{"output_type":"display_data","data":{"text/plain":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EnSetnQpjQN0/p8LwxhkiRpnW2xxRasWrXKIEYXwFatWsUWW2yxTo/z05GSJGmd7bDDDqxYsYKVK1e2LmUsbLHFFuywww7r9BhDmCRJWmebbbYZO++8c+syNmgOR0qSJDVgT9iQLT7y1Dt8jFFfAE+SJA2fPWGSJEkNGMIkSZIaMIRJkiQ1YAiTJElqwBAmSZLUgCFMkiSpAUOYJElSA4YwSZKkBgxhkiRJDRjCJEmSGjCESZIkNTC0EJbkuCTXJrlohjZLk3wrycVJvjqsWiRJksbNMHvCjgf2mW5nkrsB7wP2q6oHA88eYi2SJEljZWghrKrOAK6focmBwKer6od9+2uHVYskSdK4aTknbFfg7km+kuTcJM+frmGSw5MsS7Js5cqVIyxRkiRpOFqGsAXAI4B9gd8H/iHJrlM1rKpjq2pJVS1ZtGjRKGuUJEkaigUNz70CWFVVPwd+nuQMYA/guw1rkiRJGomWPWGfAR6XZEGSuwCPBC5tWI8kSdLIDK0nLMkJwFJgYZIVwOuAzQCq6piqujTJ54ELgDXAh6pq2stZSJIkzSdDC2FVdcAs2rwVeOuwapAkSRpXXjFfkiSpAUOYJElSA4YwSZKkBgxhkiRJDRjCJEmSGjCESZIkNWAIkyRJasAQJkmS1IAhTJIkqQFDmCRJUgOGMEmSpAYMYZIkSQ0YwiRJkhowhEmSJDVgCJMkSWrAECZJktSAIUySJKkBQ5gkSVIDhjBJkqQGDGGSJEkNGMIkSZIaMIRJkiQ1YAiTJElqwBAmSZLUgCFMkiSpAUOYJElSA4YwSZKkBgxhkiRJDRjCJEmSGjCESZIkNWAIkyRJasAQJkmS1IAhTJIkqQFDmCRJUgOGMEmSpAYMYZIkSQ0YwiRJkhowhEmSJDVgCJMkSWrAECZJktSAIUySJKkBQ5gkSVIDhjBJkqQGDGGSJEkNGMIkSZIaMIRJkiQ1YAiTJElqwBAmSZLUgCFMkiSpAUOYJElSA4YwSZKkBgxhkiRJDRjCJEmSGjCESZIkNTC0EJbkuCTXJrloLe1+N8nqJM8aVi2SJEnjZpg9YccD+8zUIMmmwFuALw6xDkmSpLEztBBWVWcA16+l2UuBTwHXDqsOSZKkcdRsTliS7YE/Bt4/i7aHJ1mWZNnKlSuHX5wkSdKQtZyYfzTwt1W1Zm0Nq+rYqlpSVUsWLVo0/MokSZKGbEHDcy8BTkwCsBB4epLVVXVyw5okSZJGolkIq6qdJ5aTHA981gAmSZI2FkMLYUlOAJYCC5OsAF4HbAZQVccM67wAi4889Q4fY/lR+85BJZIkSVMbWgirqgPWoe2hw6pDkiRpHHnFfEmSpAYMYZIkSQ0YwiRJkhowhEmSJDVgCJMkSWrAECZJktSAIUySJKkBQ5gkSVIDhjBJkqQGDGGSJEkNGMIkSZIaMIRJkiQ1YAiTJElqwBAmSZLUgCFMkiSpAUOYJElSA4YwSZKkBgxhkiRJDRjCJEmSGjCESZIkNWAIkyRJasAQJkmS1IAhTJIkqQFDmCRJUgOGMEmSpAYMYZIkSQ0YwiRJkhowhEmSJDVgCJMkSWrAECZJktSAIUySJKkBQ5gkSVIDhjBJkqQGDGGSJEkNGMIkSZIaMIRJkiQ1YAiTJElqwBAmSZLUgCFMkiSpAUOYJElSA4YwSZKkBgxhkiRJDRjCJEmSGjCESZIkNWAIkyRJasAQJkmS1IAhTJIkqQFDmCRJUgOGMEmSpAYMYZIkSQ0YwiRJkhowhEmSJDVgCJMkSWrAECZJktTA0EJYkuOSXJvkomn2H5TkgiQXJjkzyR7DqkWSJGncDLMn7Hhgnxn2fx94YlU9FHgjcOwQa5EkSRorC4Z14Ko6I8niGfafObB6NrDDsGqRJEkaN+MyJ+wFwOem25nk8CTLkixbuXLlCMuSJEkajuYhLMnedCHsb6drU1XHVtWSqlqyaNGi0RUnSZI0JEMbjpyNJLsDHwKeVlWrWtYiSZI0Ss16wpLsBHwaOLiqvtuqDkmSpBaG1hOW5ARgKbAwyQrgdcBmAFV1DPBaYFvgfUkAVlfVkmHVI0mSNE6G+enIA9ay/4XAC4d1fkmSpHHWfGK+JEnSxsgQJkmS1IAhTJIkqQFDmCRJUgOGMEmSpAYMYZIkSQ0YwiRJkhowhEmSJDVgCJMkSWrAECZJktSAIUySJKmBod07UuNn8ZGn3uFjLD9q3zmoRJIk2RMmSZLUgCFMkiSpAUOYJElSA4YwSZKkBgxhkiRJDRjCJEmSGjCESZIkNWAIkyRJasAQJkmS1IAhTJIkqQFDmCRJUgOGMEmSpAYMYZIkSQ0YwiRJkhowhEmSJDVgCJMkSWrAECZJktSAIUySJKkBQ5gkSVIDhjBJkqQGDGGSJEkNGMIkSZIaMIRJkiQ1YAiTJElqwBAmSZLUgCFMkiSpAUOYJElSA4YwSZKkBgxhkiRJDRjCJEmSGjCESZIkNWAIkyRJasAQJkmS1IAhTJIkqQFDmCRJUgOGMEmSpAYMYZIkSQ0YwiRJkhowhEmSJDVgCJMkSWrAECZJktSAIUySJKmBoYWwJMcluTbJRdPsT5J3Jbk8yQVJHj6sWiRJksbNMHvCjgf2mWH/04Bd+q/DgfcPsRZJkqSxMrQQVlVnANfP0GR/4CPVORu4W5J7D6seSZKkcdJyTtj2wJUD6yv6bb8lyeFJliVZtnLlypEUJ0mSNEwbxMT8qjq2qpZU1ZJFixa1LkeSJOkOaxnCrgJ2HFjfod8mSZI07601hCW5X5LN++WlSY5Icrc5OPcpwPP7T0k+CvhJVV0zB8eVJEkae7PpCfsUcGuS+wPH0vVefXxtD0pyAnAW8IAkK5K8IMmfJ/nzvslpwBXA5cAHgRevzxOQJEnaEC2YRZs1VbU6yR8D766qdyc5f20PqqoD1rK/gL+cZZ2SJEnzymx6wm5JcgBwCPDZfttmwytJkiRp/ptNCDsMeDTwT1X1/SQ7Ax8dblmSJEnz21pDWFVdArwCuDjJQ4GrquotQ69MkiRpHlvrnLAk+wLHAP8HBNg5yZ9V1eeGXZwkSdJ8NZuJ+W8D9q6qy6G7ZAVwKmAIkyRJWk+zmRN200QA610B3DSkeiRJkjYKs+kJW5bkNOAkoIBnA+ckeQZAVX16iPVJkiTNS7MJYVsAPwae2K+vBO4M/CFdKDOESZIkraO1hrCqOmwUhUiSJG1Mpg1hSV5VVf+S5N10PV63U1VHDLUySZKkeWymnrBL+3+XjaIQSZKkjcm0Iayq/qv/999GV44kSdLGYabhyP9iimHICVW131AqkiRJ2gjMNBz5/0ZWhSRJ0kZmphB2CbCov3fkbZLsRneZCkmSJK2nma6Y/25g4RTbtwXeOZxyJEmSNg4zhbD7V9UZkzdW1deA3YdXkiRJ0vw3UwjbaoZ9m811IZIkSRuTmULY5UmePnljkqfR3cRbkiRJ62mmifl/DZya5DnAuf22JcCjgT8Ycl2SJEnz2rQ9YVX1PeChwFeBxf3XV4Hdq+q7oyhOkiRpvprxBt5V9SvgwyOqRZIkaaMx05wwSZIkDYkhTJIkqYEZhyMnJLkTsGu/ellV3TK8kiRJkua/tYawJEuBfwOWAwF2THLIVBdylSRJ0uzMpifsbcBTq+oygCS7AicAjxhmYZIkSfPZbOaEbTYRwAD6y1N4xXxJkqQ7YDY9YcuSfAj49379IGDZ8EqSJEma/2YTwv4C+EvgiH79a8D7hlaRJEnSRmCtIay/YOvb+y9JkiTNgWlDWJKTquo5SS4EavL+qtp9qJVJkiTNYzP1hP1V/68365YkSZpj04awqrqm//cHoytHkiRp4zDTcORNTDEMOaGqth5KRdooLD7y1Dt8jOVH7TsHlUiS1MZMPWFbASR5I3AN8FG6K+YfBNx7JNVJkiTNU7O5WOt+VfW+qrqpqn5aVe8H9h92YZIkSfPZbELYz5MclGTTJJskOQj4+bALkyRJms9mE8IOBJ4D/Lj/ena/TZIkSetpNhdrXY7Dj5IkSXNqrSEsyYeZ+mKtfzqUiiRJkjYCs7l35GcHlrcA/hi4ejjlSJIkbRxmMxz5qcH1JCcAXx9aRZIkSRuB2UzMn2wX4J5zXYgkSdLGZDZzwiZfOf9HwN8OrSJJkqSNwGyGI7caRSGSJEkbk3UajkxyvyT/kOTiYRUkSZK0MVhrCEuyXZKXJzkHuLh/zPOGXpkkSdI8Nm0IS3J4ktOBrwD3AF4AXFNVr6+qC0dUnyRJ0rw005yw9wBnAQdW1TKAJL910VZJkiStu5lC2L3p7hP5tiT3Ak4CNhtJVZIkSfPctMORVbWqqo6pqicCTwZuBH6c5NIk/zyqAiVJkuajWX06sqpWVNXbqmoJ3c28bx5uWZIkSfPbOl8xv6q+W1VvmE3bJPskuSzJ5UmOnGL/TklOT3J+kguSPH1d65EkSdoQrc9ti2YlyabAe4GnAbsBByTZbVKzvwdOqqqH0V324n3DqkeSJGmcDC2EAXsBl1fVFVX1a+BEuqHMQQVs3S9vA1w9xHokSZLGxrSfjkzy8JkeWFXnreXY2wNXDqyvAB45qc0/Al9M8lLgrsBT1nJMSZKkeWGmS1S8bYZ9BTxpDs5/AHB8Vb0tyaOBjyZ5SFWtGWyU5HDgcICddtppDk4rSZLU1rQhrKr2voPHvgrYcWB9h37boBcA+/TnOyvJFsBC4NpJtRwLHAuwZMkSLxgrSZI2eDP1hN0myUPoJtdvMbGtqj6yloedA+ySZGe68PU84MBJbX5Idw2y45M8qD/+ytmVLkmStOFaawhL8jpgKV0IO43u045fB2YMYVW1OslLgC8AmwLHVdXFSd4ALKuqU4C/AT6Y5GV0Q5yHVpU9XZIkad6bTU/Ys4A9gPOr6rAkvwP8+2wOXlWn0QW3wW2vHVi+BHjs7MuVJEmaH2ZziYpf9hPlVyfZmm6+1o5reYwkSZJmMJuesGVJ7gZ8EDgX+Blw1jCLkiRJmu/WGsKq6sX94jFJPg9sXVUXDLcsSZKk+W2tw5FJ/mdiuaqWV9UFg9skSZK07ma6Yv4WwF2AhUnuDqTftTXd1fAlSZK0nmYajvwz4K+B7YDBWxT9FHjPEGuSJEma92a6Yv47gXcmeWlVvXuENUmSJM17s/l05AeSHAE8oV//CvCBqrplaFVJkiTNc7MJYe8DNuv/BTgYeD/wwmEVJUmSNN/NNDF/QVWtBn63qvYY2PXlJN8efmmSJEnz10yXqPjf/t9bk9xvYmOS+wK3DrUqSZKkeW6m4ciJS1K8Ajg9yRX9+mLgsGEWJUmSNN/NFMIWJXl5v/wBYNN++VbgYcDpwyxMkiRpPpsphG0KbMlvesQGH7PV0CqSRmjxkafOyXGWH7XvnBxHkrTxmCmEXVNVbxhZJZIkSRuRmSbmT+4BkyRJ0hyZKYQ9eWRVSJIkbWSmDWFVdf0oC5EkSdqYzNQTJkmSpCExhEmSJDVgCJMkSWrAECZJktSAIUySJKkBQ5gkSVIDhjBJkqQGDGGSJEkNGMIkSZIaMIRJkiQ1YAiTJElqwBAmSZLUgCFMkiSpAUOYJElSA4YwSZKkBgxhkiRJDRjCJEmSGjCESZIkNWAIkyRJasAQJkmS1IAhTJIkqQFDmCRJUgOGMEmSpAYMYZIkSQ0YwiRJkhowhEmSJDVgCJMkSWrAECZJktSAIUySJKkBQ5gkSVIDhjBJkqQGDGGSJEkNGMIkSZIaMIRJkiQ1YAiTJElqwBAmSZLUwFBDWJJ9klyW5PIkR07T5jlJLklycZKPD7MeSZKkcbFgWAdOsinwXuD3gBXAOUlOqapLBtrsArwaeGxV3ZDknsOqR5IkaZwMsydsL+Dyqrqiqn4NnAjsP6nNi4D3VtUNAFV17RDrkSRJGhvDDGHbA1cOrK/otw3aFdg1yTeSnJ1knyHWI0mSNDaGNhy5DuffBVgK7ACckeShVXXjYKMkhwOHA+y0004jLlGSJGnuDbMn7Cpgx4H1Hfptg1YAp1TVLVX1feC7dKHsdqrq2KpaUlVLFi1aNLSCJUmSRmWYIewcYJckOye5E/A84JRJbU6m6wUjyUK64ckrhliTJEnSWBhaCKuq1cBLgC8AlwInVdXFSd6QZL++2ReAVUkuAU4HXllVq4ZVkyRJ0rgY6pywqjoNOG3SttcOLBfw8v5LkiRpo+EV8yVJkhowhEmSJDVgCJMkSWrAECZJktSAIUySJKkBQ5gkSVIDhjBJkqQGDGGSJEkNGMIkSZIaMIRJkiQ1YAiTJElqwBAmSZLUgCFMkiSpAUOYJElSA4YwSZKkBgxhkiRJDRjCJEmSGjCESZIkNWAIkyRJasAQJkmS1IAhTJIkqQFDmCRJUgMLWhcgqbP4yFPn5DjLj9p3To4jSRoue8IkSZIaMIRJkiQ1YAiTJElqwBAmSZLUgCFMkiSpAUOYJElSA4YwSZKkBgxhkiRJDRjCJEmSGjCESZIkNWAIkyRJasAQJkmS1IAhTJIkqQFDmCRJUgOGMEmSpAYMYZIkSQ0YwiRJkhowhEmSJDVgCJMkSWrAECZJktSAIUySJKkBQ5gkSVIDhjBJkqQGDGGSJEkNGMIkSZIaMIRJkiQ1YAiTJElqwBAmSZLUgCFMkiSpAUOYJElSA4YwSZKkBoYawpLsk+SyJJcnOXKGds9MUkmWDLMeSZKkcTG0EJZkU+C9wNOA3YADkuw2RbutgL8CvjmsWiRJksbNMHvC9gIur6orqurXwInA/lO0eyPwFuDmIdYiSZI0VoYZwrYHrhxYX9Fvu02ShwM7VtWpMx0oyeFJliVZtnLlyrmvVJIkacSaTcxPsgnwduBv1ta2qo6tqiVVtWTRokXDL06SJGnIhhnCrgJ2HFjfod82YSvgIcBXkiwHHgWc4uR8SZK0MRhmCDsH2CXJzknuBDwPOGViZ1X9pKoWVtXiqloMnA3sV1XLhliTJEnSWBhaCKuq1cBLgC8AlwInVdXFSd6QZL9hnVeSJGlDsGCYB6+q04DTJm177TRtlw6zFkmSpHHiFfMlSZIaMIRJkiQ1YAiTJElqwBAmSZLUgCFMkiSpAUOYJElSA4YwSZKkBgxhkiRJDRjCJEmSGjCESZIkNWAIkyRJasAQJkmS1IAhTJIkqYEFrQuQNH4WH3nqnBxn+VH7zslxJGk+sidMkiSpAUOYJElSA4YwSZKkBgxhkiRJDRjCJEmSGjCESZIkNWAIkyRJasAQJkmS1IAhTJIkqQFDmCRJUgOGMEmSpAYMYZIkSQ0YwiRJkhowhEmSJDVgCJMkSWrAECZJktSAIUySJKkBQ5gkSVIDhjBJkqQGDGGSJEkNGMIkSZIaMIRJkiQ1YAiTJElqwBAmSZLUgCFMkiSpAUOYJElSA4YwSZKkBgxhkiRJDRjCJEmSGjCESZIkNWAIkyRJasAQJkmS1IAhTJIkqQFDmCRJUgOGMEmSpAYMYZIkSQ0YwiRJkhowhEmSJDVgCJMkSWrAECZJktTAUENYkn2SXJbk8iRHTrH/5UkuSXJBkv9Jcp9h1iNJkjQuhhbCkmwKvBd4GrAbcECS3SY1Ox9YUlW7A58E/mVY9UiSJI2TBUM89l7A5VV1BUCSE4H9gUsmGlTV6QPtzwb+ZIj1SNoALT7y1Dt8jOVH7TsHlUjS3BrmcOT2wJUD6yv6bdN5AfC5qXYkOTzJsiTLVq5cOYclSpIktTEWE/OT/AmwBHjrVPur6tiqWlJVSxYtWjTa4iRJkoZgmMORVwE7Dqzv0G+7nSRPAV4DPLGqfjXEeiRJksbGMHvCzgF2SbJzkjsBzwNOGWyQ5GHAB4D9quraIdYiSZI0VoYWwqpqNfAS4AvApcBJVXVxkjck2a9v9lZgS+ATSb6V5JRpDidJkjSvDHM4kqo6DTht0rbXDiw/ZZjnlyRJGldjMTFfkiRpY2MIkyRJasAQJkmS1IAhTJIkqQFDmCRJUgOGMEmSpAYMYZIkSQ0YwiRJkhowhEmSJDVgCJMkSWrAECZJktSAIUySJKkBQ5gkSVIDhjBJkqQGDGGSJEkNGMIkSZIaMIRJkiQ1YAiTJElqwBAmSZLUgCFMkiSpAUOYJElSA4YwSZKkBgxhkiRJDRjCJEmSGjCESZIkNbCgdQGStKFYfOSpd/gYy4/adw4qkTQf2BMmSZLUgCFMkiSpAUOYJElSA4YwSZKkBgxhkiRJDRjCJEmSGjCESZIkNWAIkyRJasAQJkmS1IAhTJIkqQFDmCRJUgOGMEmSpAYMYZIkSQ0saF2AJGndLT7y1Dt8jOVH7TsHlUhaX/aESZIkNWAIkyRJasAQJkmS1IAhTJIkqQFDmCRJUgOGMEmSpAYMYZIkSQ0YwiRJkhowhEmSJDXgFfMlSXeIV++X1o89YZIkSQ0YwiRJkhowhEmSJDVgCJMkSWpgqBPzk+wDvBPYFPhQVR01af/mwEeARwCrgOdW1fJh1iRJmr/8kIA2JEPrCUuyKfBe4GnAbsABSXab1OwFwA1VdX/gHcBbhlWPJEnSOBlmT9hewOVVdQVAkhOB/YFLBtrsD/xjv/xJ4D1JUlU1xLokSRqqueiRA3vl5rsMK+8keRawT1W9sF8/GHhkVb1koM1FfZsV/fr/9W2um3Ssw4HD+9UHAJfNQYkLgevW2mo0xqWWcakDrGU61jI1a5nauNQyLnWAtUzHWqY2F7Xcp6oWTbVjg7hYa1UdCxw7l8dMsqyqlszlMdfXuNQyLnWAtUzHWqZmLVMbl1rGpQ6wlulYy9SGXcswPx15FbDjwPoO/bYp2yRZAGxDN0FfkiRpXhtmCDsH2CXJzknuBDwPOGVSm1OAQ/rlZwFfdj6YJEnaGAxtOLKqVid5CfAFuktUHFdVFyd5A7Csqk4B/hX4aJLLgevpgtqozOnw5h00LrWMSx1gLdOxlqlZy9TGpZZxqQOsZTrWMrWh1jK0ifmSJEmanlfMlyRJasAQJkmS1IAhTJIkqYEN4jphd1SSvYCqqnP6WyftA3ynqk5rXBpJPlJVzx+DOh5Hd5eDi6rqiyM+9yOBS6vqp0nuDBwJPJzu7gr/XFU/GWEtRwD/WVVXjuqcM9Qy8aniq6vqv5McCDwGuBQ4tqpuGXE99wWeQXdZmVuB7wIfr6qfjrIOSZov5v3E/CSvo7t/5QLgS8AjgdOB3wO+UFX/NMJaJl+iI8DewJcBqmq/Edbyv1W1V7/8IuAvgf8Engr81+SbrQ+5louBPfpP1B4L/ILuNlZP7rc/Y4S1/AT4OfB/wAnAJ6pq5ajOP6mWj9G9b+8C3AhsCXya7vuSqjpk+kfPeS1HAH8AnAE8HTi/r+mPgRdX1VdGVYt0RyS5Z1Vd27oOCTaOEHYhsCewOfAjYIeBHpdvVtXuI6zlPLrenQ8BRRfCTqC/NEdVfXWEtZxfVQ/rl88Bnl5VK5PcFTi7qh46wlouraoH9cvnVdXDB/Z9q6r2HGEt5wOPAJ4CPBfYDziX7nX6dFXdNMJaLqiq3fsLGV8FbFdVtyYJ8O0Rv3cvBPbsz38X4LSqWppkJ+AzE++lEdWyDfBq4I+Ae9L9X7oW+AxwVFXdOKpaNLUk9wJeB6wBXgu8FHgmXS/uX1XVNSOq4x6TN9H9f34Y3e+/60dRx4YgybZVtVFfLD3JEuCtdD9vXw0cRzdC9F3g8Ko6f67PuTHMCVtdVbdW1S+A/5sYOqmqX9L9gBilJXQ/AF4D/KTvPfhlVX11lAGst0mSuyfZlu6H0UqAqvo5sHrEtVyU5LB++dv9fwSS7AqMdMiNbth6TVV9sapeAGwHvI9uCPuKEdeyST8kuRVdb9g2/fbNgc1GXAv8ZvrC5nS9clTVDxvUchJwA7C0qu5RVdvS9Sjf0O8bC0k+N+LzbZ3kzUk+2g9dD+573yhrAY6n+4PzSrqRh1/S9aB+DThmhHVcR/czd+JrGbA9cF6/PDJJ9hlY3ibJvya5IMnHk/zOiGs5KsnCfnlJkiuAbyb5QZInjriW85L8fZL7jfK803gf8C/AqcCZwAeqa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\n"},"metadata":{"needs_background":"light"}}],"source":"for l in tqdm(languages):\n plot_saves = \"plots/wordlengths_0806/\"\n main_data[main_data['language']==l].groupby('wl').sum().drop('index', axis=1).plot(kind='bar', figsize=(10,10), xlabel='Word Length', ylabel='Total Audio Clips', title=f'Total Audio Clips v/s Word Length in {l}')\n save_path = plot_saves + f\"{l}.png\"\n plt.savefig(save_path)"},{"cell_type":"code","execution_count":51,"metadata":{},"outputs":[],"source":"# for l in tqdm(languages):\n# plot_saves = \"plots/wordlengths_0806/\"\n# main_data[main_data['language']==l].groupby('wl').sum().drop('index', axis=1).plot(kind='bar', figsize=(10,10), xlabel='Word Length', ylabel='Total Audio Clips', title=f'Total Audio Clips v/s Word Length in {l}')\n# save_path = plot_saves + f\"{l}.png\"\n# plt.savefig(save_path)"},{"cell_type":"code","execution_count":52,"metadata":{},"outputs":[{"output_type":"stream","name":"stderr","text":["/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/frame.py:3607: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n self._set_item(key, value)\n"]},{"output_type":"execute_result","data":{"text/plain":[" index word counts language wl fraction\n","0 0 che 9624 it 3 4.023746e-04\n","1 1 per 8938 it 3 3.736933e-04\n","2 2 del 8419 it 3 3.519942e-04\n","3 3 non 7403 it 3 3.095157e-04\n","4 4 della 7323 it 5 3.061710e-04\n","... ... ... ... ... .. ...\n","354102 15901 нептунием 5 ru 9 2.090475e-07\n","354103 15902 поддерживается 5 ru 14 2.090475e-07\n","354104 15903 барнаулом 5 ru 9 2.090475e-07\n","354105 15904 березы 5 ru 6 2.090475e-07\n","354106 15905 окончена 5 ru 8 2.090475e-07\n","\n","[347772 rows x 6 columns]"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
indexwordcountslanguagewlfraction
00che9624it34.023746e-04
11per8938it33.736933e-04
22del8419it33.519942e-04
33non7403it33.095157e-04
44della7323it53.061710e-04
.....................
35410215901нептунием5ru92.090475e-07
35410315902поддерживается5ru142.090475e-07
35410415903барнаулом5ru92.090475e-07
35410515904березы5ru62.090475e-07
35410615905окончена5ru82.090475e-07
\n

347772 rows × 6 columns

\n
"},"metadata":{},"execution_count":52}],"source":"# main_data[main_data['language']==l].groupby('wl').sum().drop('index', axis=1).plot(kind='bar', figsize=(10,10), xlabel='Word Length', ylabel='Total Audio Clips', title=f'Total Audio Clips v/s Word Length in {l}', stacked=True)\n# main_data.groupby('language')\n# main_data[main_data['language']==l].groupby('wl').sum().drop('index', axis=1).plot(kind='bar', figsize=(10,10), xlabel='Word Length', ylabel='Total Audio Clips', title=f'Total Audio Clips v/s Word Length in {l}', stacked=True)\nmain_data['fraction'] = main_data['counts']/sum(main_data['counts'])\nmain_data"},{"cell_type":"code","execution_count":53,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" index counts fraction\n","wl \n","3 62205071 5193055 2.171190e-01\n","4 199472492 4404932 1.841680e-01\n","5 378661455 3724133 1.557041e-01\n","6 544677848 3062614 1.280464e-01\n","7 638910737 2382744 9.962133e-02\n","8 651333324 1812456 7.577788e-02\n","9 583569135 1295605 5.416860e-02\n","10 465574922 855526 3.576911e-02\n","11 331511485 510045 2.132473e-02\n","12 214747187 309740 1.295007e-02\n","13 134242735 166888 6.977504e-03\n","14 84051385 95573 3.995859e-03\n","15 49228475 47919 2.003469e-03\n","16 28921865 23017 9.623292e-04\n","17 18466890 13388 5.597456e-04\n","18 12178667 8285 3.463917e-04\n","19 6972563 4441 1.856760e-04\n","20 5009749 2864 1.197424e-04\n","21 3884082 1580 6.605901e-05\n","22 1955961 874 3.654150e-05\n","23 1468851 964 4.030436e-05\n","24 1114412 424 1.772723e-05\n","25 520231 305 1.275190e-05\n","26 302788 188 7.860186e-06\n","27 215243 119 4.975330e-06\n","28 61679 58 2.424951e-06\n","29 213551 176 7.358472e-06\n","30 33106 7 2.926665e-07\n","31 27618 54 2.257713e-06\n","33 81996 29 1.212475e-06\n","34 32203 7 2.926665e-07"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
indexcountsfraction
wl
36220507151930552.171190e-01
419947249244049321.841680e-01
537866145537241331.557041e-01
654467784830626141.280464e-01
763891073723827449.962133e-02
865133332418124567.577788e-02
958356913512956055.416860e-02
104655749228555263.576911e-02
113315114855100452.132473e-02
122147471873097401.295007e-02
131342427351668886.977504e-03
1484051385955733.995859e-03
1549228475479192.003469e-03
1628921865230179.623292e-04
1718466890133885.597456e-04
181217866782853.463917e-04
19697256344411.856760e-04
20500974928641.197424e-04
21388408215806.605901e-05
2219559618743.654150e-05
2314688519644.030436e-05
2411144124241.772723e-05
255202313051.275190e-05
263027881887.860186e-06
272152431194.975330e-06
2861679582.424951e-06
292135511767.358472e-06
303310672.926665e-07
3127618542.257713e-06
3381996291.212475e-06
343220372.926665e-07
\n
"},"metadata":{},"execution_count":53}],"source":"main_data.groupby('wl').sum()"},{"cell_type":"code","execution_count":54,"metadata":{},"outputs":[{"output_type":"error","ename":"KeyError","evalue":"'wl'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'counts'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroupby\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'wl'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36mgroupby\u001b[0;34m(self, by, axis, level, as_index, sort, group_keys, squeeze, observed, dropna)\u001b[0m\n\u001b[1;32m 7624\u001b[0m \u001b[0;31m# error: Argument \"squeeze\" to \"DataFrameGroupBy\" has incompatible type\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7625\u001b[0m \u001b[0;31m# \"Union[bool, NoDefault]\"; expected \"bool\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 7626\u001b[0;31m return DataFrameGroupBy(\n\u001b[0m\u001b[1;32m 7627\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7628\u001b[0m \u001b[0mkeys\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mby\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/groupby/groupby.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, obj, keys, axis, level, grouper, exclusions, selection, as_index, sort, group_keys, squeeze, observed, mutated, dropna)\u001b[0m\n\u001b[1;32m 886\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mpandas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcore\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroupby\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgrouper\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mget_grouper\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 887\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 888\u001b[0;31m grouper, exclusions, obj = get_grouper(\n\u001b[0m\u001b[1;32m 889\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 890\u001b[0m \u001b[0mkeys\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/groupby/grouper.py\u001b[0m in \u001b[0;36mget_grouper\u001b[0;34m(obj, key, axis, level, sort, observed, mutated, validate, dropna)\u001b[0m\n\u001b[1;32m 858\u001b[0m \u001b[0min_axis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgpr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgpr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 859\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 860\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgpr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 861\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgpr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mGrouper\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mgpr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkey\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 862\u001b[0m \u001b[0;31m# Add key to exclusions\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: 'wl'"]}],"source":"main_data[['counts']].groupby('wl').sum()"},{"cell_type":"code","execution_count":55,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" counts\n","wl \n","3 5193055\n","4 4404932\n","5 3724133\n","6 3062614\n","7 2382744\n","8 1812456\n","9 1295605\n","10 855526\n","11 510045\n","12 309740\n","13 166888\n","14 95573\n","15 47919\n","16 23017\n","17 13388\n","18 8285\n","19 4441\n","20 2864\n","21 1580\n","22 874\n","23 964\n","24 424\n","25 305\n","26 188\n","27 119\n","28 58\n","29 176\n","30 7\n","31 54\n","33 29\n","34 7"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
counts
wl
35193055
44404932
53724133
63062614
72382744
81812456
91295605
10855526
11510045
12309740
13166888
1495573
1547919
1623017
1713388
188285
194441
202864
211580
22874
23964
24424
25305
26188
27119
2858
29176
307
3154
3329
347
\n
"},"metadata":{},"execution_count":55}],"source":"main_data[['counts','wl']].groupby('wl').sum()"},{"cell_type":"code","execution_count":56,"metadata":{},"outputs":[{"output_type":"error","ename":"ValueError","evalue":"dictionary update sequence element #0 has length 1; 2 is required","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'counts'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'wl'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroupby\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'wl'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;31mValueError\u001b[0m: dictionary update sequence element #0 has length 1; 2 is required"]}],"source":"dict(zip(main_data[['counts','wl']].groupby('wl').sum().values))"},{"cell_type":"code","execution_count":57,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([[5193055],\n"," [4404932],\n"," [3724133],\n"," [3062614],\n"," [2382744],\n"," [1812456],\n"," [1295605],\n"," [ 855526],\n"," [ 510045],\n"," [ 309740],\n"," [ 166888],\n"," [ 95573],\n"," [ 47919],\n"," [ 23017],\n"," [ 13388],\n"," [ 8285],\n"," [ 4441],\n"," [ 2864],\n"," [ 1580],\n"," [ 874],\n"," [ 964],\n"," [ 424],\n"," [ 305],\n"," [ 188],\n"," [ 119],\n"," [ 58],\n"," [ 176],\n"," [ 7],\n"," [ 54],\n"," [ 29],\n"," [ 7]])"]},"metadata":{},"execution_count":57}],"source":"main_data[['counts','wl']].groupby('wl').sum().values"},{"cell_type":"code","execution_count":58,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" wl counts\n","0 3 5193055\n","1 4 4404932\n","2 5 3724133\n","3 6 3062614\n","4 7 2382744\n","5 8 1812456\n","6 9 1295605\n","7 10 855526\n","8 11 510045\n","9 12 309740\n","10 13 166888\n","11 14 95573\n","12 15 47919\n","13 16 23017\n","14 17 13388\n","15 18 8285\n","16 19 4441\n","17 20 2864\n","18 21 1580\n","19 22 874\n","20 23 964\n","21 24 424\n","22 25 305\n","23 26 188\n","24 27 119\n","25 28 58\n","26 29 176\n","27 30 7\n","28 31 54\n","29 33 29\n","30 34 7"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
wlcounts
035193055
144404932
253724133
363062614
472382744
581812456
691295605
710855526
811510045
912309740
1013166888
111495573
121547919
131623017
141713388
15188285
16194441
17202864
18211580
1922874
2023964
2124424
2225305
2326188
2427119
252858
2629176
27307
283154
293329
30347
\n
"},"metadata":{},"execution_count":58}],"source":"main_data[['counts','wl']].groupby('wl').sum().reset_index()"},{"cell_type":"code","execution_count":59,"metadata":{},"outputs":[{"output_type":"error","ename":"ValueError","evalue":"dictionary update sequence element #0 has length 1; 2 is required","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'counts'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'wl'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroupby\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'wl'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreset_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;31mValueError\u001b[0m: dictionary update sequence element #0 has length 1; 2 is required"]}],"source":"dict(zip(main_data[['counts','wl']].groupby('wl').sum().reset_index().values))"},{"cell_type":"code","execution_count":60,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([[ 3, 5193055],\n"," [ 4, 4404932],\n"," [ 5, 3724133],\n"," [ 6, 3062614],\n"," [ 7, 2382744],\n"," [ 8, 1812456],\n"," [ 9, 1295605],\n"," [ 10, 855526],\n"," [ 11, 510045],\n"," [ 12, 309740],\n"," [ 13, 166888],\n"," [ 14, 95573],\n"," [ 15, 47919],\n"," [ 16, 23017],\n"," [ 17, 13388],\n"," [ 18, 8285],\n"," [ 19, 4441],\n"," [ 20, 2864],\n"," [ 21, 1580],\n"," [ 22, 874],\n"," [ 23, 964],\n"," [ 24, 424],\n"," [ 25, 305],\n"," [ 26, 188],\n"," [ 27, 119],\n"," [ 28, 58],\n"," [ 29, 176],\n"," [ 30, 7],\n"," [ 31, 54],\n"," [ 33, 29],\n"," [ 34, 7]])"]},"metadata":{},"execution_count":60}],"source":"main_data[['counts','wl']].groupby('wl').sum().reset_index().values"},{"cell_type":"code","execution_count":61,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":61}],"source":"zip(main_data[['counts','wl']].groupby('wl').sum().reset_index().values)"},{"cell_type":"code","execution_count":62,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["[(array([ 3, 5193055]),),\n"," (array([ 4, 4404932]),),\n"," (array([ 5, 3724133]),),\n"," (array([ 6, 3062614]),),\n"," (array([ 7, 2382744]),),\n"," (array([ 8, 1812456]),),\n"," (array([ 9, 1295605]),),\n"," (array([ 10, 855526]),),\n"," (array([ 11, 510045]),),\n"," (array([ 12, 309740]),),\n"," (array([ 13, 166888]),),\n"," (array([ 14, 95573]),),\n"," (array([ 15, 47919]),),\n"," (array([ 16, 23017]),),\n"," (array([ 17, 13388]),),\n"," (array([ 18, 8285]),),\n"," (array([ 19, 4441]),),\n"," (array([ 20, 2864]),),\n"," (array([ 21, 1580]),),\n"," (array([ 22, 874]),),\n"," (array([ 23, 964]),),\n"," (array([ 24, 424]),),\n"," (array([ 25, 305]),),\n"," (array([ 26, 188]),),\n"," (array([ 27, 119]),),\n"," (array([28, 58]),),\n"," (array([ 29, 176]),),\n"," (array([30, 7]),),\n"," (array([31, 54]),),\n"," (array([33, 29]),),\n"," (array([34, 7]),)]"]},"metadata":{},"execution_count":62}],"source":"list(zip(main_data[['counts','wl']].groupby('wl').sum().reset_index().values))"},{"cell_type":"code","execution_count":63,"metadata":{},"outputs":[{"output_type":"error","ename":"ValueError","evalue":"dictionary update sequence element #0 has length 1; 2 is required","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'counts'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'wl'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroupby\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'wl'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreset_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;31mValueError\u001b[0m: dictionary update sequence element #0 has length 1; 2 is required"]}],"source":"dict(zip(main_data[['counts','wl']].groupby('wl').sum().reset_index().values))"},{"cell_type":"code","execution_count":64,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([[ 3, 5193055],\n"," [ 4, 4404932],\n"," [ 5, 3724133],\n"," [ 6, 3062614],\n"," [ 7, 2382744],\n"," [ 8, 1812456],\n"," [ 9, 1295605],\n"," [ 10, 855526],\n"," [ 11, 510045],\n"," [ 12, 309740],\n"," [ 13, 166888],\n"," [ 14, 95573],\n"," [ 15, 47919],\n"," [ 16, 23017],\n"," [ 17, 13388],\n"," [ 18, 8285],\n"," [ 19, 4441],\n"," [ 20, 2864],\n"," [ 21, 1580],\n"," [ 22, 874],\n"," [ 23, 964],\n"," [ 24, 424],\n"," [ 25, 305],\n"," [ 26, 188],\n"," [ 27, 119],\n"," [ 28, 58],\n"," [ 29, 176],\n"," [ 30, 7],\n"," [ 31, 54],\n"," [ 33, 29],\n"," [ 34, 7]])"]},"metadata":{},"execution_count":64}],"source":"main_data[['counts','wl']].groupby('wl').sum().reset_index().values"},{"cell_type":"code","execution_count":65,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["[[3, 5193055],\n"," [4, 4404932],\n"," [5, 3724133],\n"," [6, 3062614],\n"," [7, 2382744],\n"," [8, 1812456],\n"," [9, 1295605],\n"," [10, 855526],\n"," [11, 510045],\n"," [12, 309740],\n"," [13, 166888],\n"," [14, 95573],\n"," [15, 47919],\n"," [16, 23017],\n"," [17, 13388],\n"," [18, 8285],\n"," [19, 4441],\n"," [20, 2864],\n"," [21, 1580],\n"," [22, 874],\n"," [23, 964],\n"," [24, 424],\n"," [25, 305],\n"," [26, 188],\n"," [27, 119],\n"," [28, 58],\n"," [29, 176],\n"," [30, 7],\n"," [31, 54],\n"," [33, 29],\n"," [34, 7]]"]},"metadata":{},"execution_count":65}],"source":"main_data[['counts','wl']].groupby('wl').sum().reset_index().values.tolist()"},{"cell_type":"code","execution_count":66,"metadata":{},"outputs":[{"output_type":"error","ename":"ValueError","evalue":"dictionary update sequence element #0 has length 1; 2 is required","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'counts'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'wl'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroupby\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'wl'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreset_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtolist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;31mValueError\u001b[0m: dictionary update sequence element #0 has length 1; 2 is required"]}],"source":"dict(zip(main_data[['counts','wl']].groupby('wl').sum().reset_index().values.tolist()))"},{"cell_type":"code","execution_count":67,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["[([3, 5193055],),\n"," ([4, 4404932],),\n"," ([5, 3724133],),\n"," ([6, 3062614],),\n"," ([7, 2382744],),\n"," ([8, 1812456],),\n"," ([9, 1295605],),\n"," ([10, 855526],),\n"," ([11, 510045],),\n"," ([12, 309740],),\n"," ([13, 166888],),\n"," ([14, 95573],),\n"," ([15, 47919],),\n"," ([16, 23017],),\n"," ([17, 13388],),\n"," ([18, 8285],),\n"," ([19, 4441],),\n"," ([20, 2864],),\n"," ([21, 1580],),\n"," ([22, 874],),\n"," ([23, 964],),\n"," ([24, 424],),\n"," ([25, 305],),\n"," ([26, 188],),\n"," ([27, 119],),\n"," ([28, 58],),\n"," ([29, 176],),\n"," ([30, 7],),\n"," ([31, 54],),\n"," ([33, 29],),\n"," ([34, 7],)]"]},"metadata":{},"execution_count":67}],"source":"list(zip(main_data[['counts','wl']].groupby('wl').sum().reset_index().values.tolist()))"},{"cell_type":"code","execution_count":68,"metadata":{},"outputs":[{"output_type":"error","ename":"SyntaxError","evalue":"unmatched ')' (3518756500.py, line 1)","traceback":["\u001b[0;36m File \u001b[0;32m\"/tmp/ipykernel_11406/3518756500.py\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m dict(main_data[['counts','wl']].groupby('wl').sum().reset_index().values.tolist()))\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m unmatched ')'\n"]}],"source":"dict(main_data[['counts','wl']].groupby('wl').sum().reset_index().values.tolist()))"},{"cell_type":"code","execution_count":69,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["{3: 5193055,\n"," 4: 4404932,\n"," 5: 3724133,\n"," 6: 3062614,\n"," 7: 2382744,\n"," 8: 1812456,\n"," 9: 1295605,\n"," 10: 855526,\n"," 11: 510045,\n"," 12: 309740,\n"," 13: 166888,\n"," 14: 95573,\n"," 15: 47919,\n"," 16: 23017,\n"," 17: 13388,\n"," 18: 8285,\n"," 19: 4441,\n"," 20: 2864,\n"," 21: 1580,\n"," 22: 874,\n"," 23: 964,\n"," 24: 424,\n"," 25: 305,\n"," 26: 188,\n"," 27: 119,\n"," 28: 58,\n"," 29: 176,\n"," 30: 7,\n"," 31: 54,\n"," 33: 29,\n"," 34: 7}"]},"metadata":{},"execution_count":69}],"source":"dict(main_data[['counts','wl']].groupby('wl').sum().reset_index().values.tolist())"},{"cell_type":"code","execution_count":70,"metadata":{},"outputs":[],"source":"# wordlengths_counts = dict(main_data[['counts','wl']].groupby('wl').sum().reset_index().values.tolist())\n# for l in tqdm(languages):\n# language_fractions[l] = main_data[main_data['language']==l].groupby('wl')['counts'].sum()"},{"cell_type":"code","execution_count":71,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["wl\n","3 1388789\n","4 1647976\n","5 1145729\n","6 872236\n","7 741493\n","8 511727\n","9 339622\n","10 204458\n","11 103044\n","12 56223\n","13 25893\n","14 9492\n","15 2513\n","16 362\n","17 53\n","18 5\n","Name: counts, dtype: int64"]},"metadata":{},"execution_count":71}],"source":"main_data[main_data['language']=='en'].groupby('wl')['counts'].sum()"},{"cell_type":"code","execution_count":72,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([[ 3, 1388789],\n"," [ 4, 1647976],\n"," [ 5, 1145729],\n"," [ 6, 872236],\n"," [ 7, 741493],\n"," [ 8, 511727],\n"," [ 9, 339622],\n"," [ 10, 204458],\n"," [ 11, 103044],\n"," [ 12, 56223],\n"," [ 13, 25893],\n"," [ 14, 9492],\n"," [ 15, 2513],\n"," [ 16, 362],\n"," [ 17, 53],\n"," [ 18, 5]])"]},"metadata":{},"execution_count":72}],"source":"main_data[main_data['language']=='en'].groupby('wl')['counts'].sum().reset_index().values"},{"cell_type":"code","execution_count":73,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["{3: 1388789,\n"," 4: 1647976,\n"," 5: 1145729,\n"," 6: 872236,\n"," 7: 741493,\n"," 8: 511727,\n"," 9: 339622,\n"," 10: 204458,\n"," 11: 103044,\n"," 12: 56223,\n"," 13: 25893,\n"," 14: 9492,\n"," 15: 2513,\n"," 16: 362,\n"," 17: 53,\n"," 18: 5}"]},"metadata":{},"execution_count":73}],"source":"dict(main_data[main_data['language']=='en'].groupby('wl')['counts'].sum().reset_index().values)"},{"cell_type":"code","execution_count":74,"metadata":{},"outputs":[{"output_type":"stream","name":"stderr","text":[" 0%| | 0/48 [00:00\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mwordlengths_counts\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'counts'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'wl'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroupby\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'wl'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreset_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtolist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0ml\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtqdm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlanguages\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mlanguage_fractions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0ml\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'language'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0ml\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroupby\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'wl'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'counts'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreset_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;31mNameError\u001b[0m: name 'language_fractions' is not defined"]}],"source":"wordlengths_counts = dict(main_data[['counts','wl']].groupby('wl').sum().reset_index().values.tolist())\nfor l in tqdm(languages):\n language_fractions[l] = dict(main_data[main_data['language']==l].groupby('wl')['counts'].sum().reset_index().values)"},{"cell_type":"code","execution_count":75,"metadata":{},"outputs":[{"output_type":"stream","name":"stderr","text":["100%|██████████| 48/48 [00:00<00:00, 53.51it/s]\n"]}],"source":"wordlengths_counts = dict(main_data[['counts','wl']].groupby('wl').sum().reset_index().values.tolist())\nlanguage_fractions = {}\nfor l in tqdm(languages):\n language_fractions[l] = dict(main_data[main_data['language']==l].groupby('wl')['counts'].sum().reset_index().values)"},{"cell_type":"code","execution_count":76,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["{'it': {3: 98098,\n"," 4: 60035,\n"," 5: 107270,\n"," 6: 81082,\n"," 7: 65570,\n"," 8: 54892,\n"," 9: 34074,\n"," 10: 26622,\n"," 11: 16161,\n"," 12: 7548,\n"," 13: 4481,\n"," 14: 3186,\n"," 15: 1959,\n"," 16: 408,\n"," 17: 180,\n"," 18: 103,\n"," 19: 61,\n"," 20: 16,\n"," 21: 5},\n"," 'mt': {3: 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'rm-vallader': {3: 1731,\n"," 4: 922,\n"," 5: 573,\n"," 6: 477,\n"," 7: 243,\n"," 8: 88,\n"," 9: 69,\n"," 10: 27,\n"," 11: 10,\n"," 12: 13,\n"," 13: 5},\n"," 'mn': {3: 9198,\n"," 4: 7453,\n"," 5: 9803,\n"," 6: 9278,\n"," 7: 3461,\n"," 8: 2337,\n"," 9: 1143,\n"," 10: 304,\n"," 11: 193,\n"," 12: 96,\n"," 13: 19,\n"," 14: 12,\n"," 15: 5},\n"," 'ro': {3: 2124,\n"," 4: 4252,\n"," 5: 2639,\n"," 6: 2697,\n"," 7: 2081,\n"," 8: 1100,\n"," 9: 764,\n"," 10: 337,\n"," 11: 80,\n"," 12: 27,\n"," 13: 34,\n"," 17: 6},\n"," 'es': {3: 245765,\n"," 4: 149234,\n"," 5: 193815,\n"," 6: 163536,\n"," 7: 158812,\n"," 8: 118989,\n"," 9: 88250,\n"," 10: 60122,\n"," 11: 36264,\n"," 12: 17623,\n"," 13: 11746,\n"," 14: 7415,\n"," 15: 3039,\n"," 16: 849,\n"," 17: 156,\n"," 18: 176,\n"," 19: 121},\n"," 'eo': {3: 63249,\n"," 4: 39706,\n"," 5: 61925,\n"," 6: 37970,\n"," 7: 33165,\n"," 8: 22098,\n"," 9: 11272,\n"," 10: 5572,\n"," 11: 2460,\n"," 12: 874,\n"," 13: 590,\n"," 14: 177,\n"," 15: 38,\n"," 16: 10},\n"," 'sah': 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122726,\n"," 7: 56283,\n"," 8: 27342,\n"," 9: 9520,\n"," 10: 3450,\n"," 11: 1665,\n"," 12: 1144,\n"," 13: 392,\n"," 14: 273,\n"," 15: 116,\n"," 16: 53,\n"," 17: 21,\n"," 19: 37},\n"," 'en': {3: 1388789,\n"," 4: 1647976,\n"," 5: 1145729,\n"," 6: 872236,\n"," 7: 741493,\n"," 8: 511727,\n"," 9: 339622,\n"," 10: 204458,\n"," 11: 103044,\n"," 12: 56223,\n"," 13: 25893,\n"," 14: 9492,\n"," 15: 2513,\n"," 16: 362,\n"," 17: 53,\n"," 18: 5},\n"," 'br': {3: 6056,\n"," 4: 5324,\n"," 5: 3525,\n"," 6: 2639,\n"," 7: 1607,\n"," 8: 761,\n"," 9: 233,\n"," 10: 171,\n"," 11: 27,\n"," 12: 21,\n"," 13: 5},\n"," 'cv': {3: 1497,\n"," 4: 1355,\n"," 5: 2150,\n"," 6: 829,\n"," 7: 659,\n"," 8: 545,\n"," 9: 258,\n"," 10: 213,\n"," 11: 80,\n"," 12: 26,\n"," 13: 12,\n"," 14: 15,\n"," 15: 9},\n"," 'ca': {3: 558959,\n"," 4: 300366,\n"," 5: 317731,\n"," 6: 298827,\n"," 7: 255145,\n"," 8: 213997,\n"," 9: 171156,\n"," 10: 107368,\n"," 11: 63211,\n"," 12: 38509,\n"," 13: 20046,\n"," 14: 9306,\n"," 15: 4319,\n"," 16: 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[00:00\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0ml\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtqdm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlanguage_fractions\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mj\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mwordlengths_counts\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0mj\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mlanguage_fractions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0ml\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0mlanguage_fractions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0ml\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mTypeError\u001b[0m: argument of type 'int' is not iterable"]}],"source":"for l in tqdm(language_fractions):\n for j in wordlengths_counts:\n if j not in language_fractions[l]:\n language_fractions[l] = 0"},{"cell_type":"code","execution_count":78,"metadata":{},"outputs":[{"output_type":"stream","name":"stderr","text":[" 0%| | 0/48 [00:00\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0ml\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtqdm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlanguage_fractions\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mj\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mwordlengths_counts\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0mj\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mlanguage_fractions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0ml\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0mlanguage_fractions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0ml\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mTypeError\u001b[0m: argument of type 'int' is not iterable"]}],"source":"for l in tqdm(language_fractions):\n for j in wordlengths_counts:\n if j not in language_fractions[l]:\n language_fractions[l] = 0"},{"cell_type":"code","execution_count":79,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["'it'"]},"metadata":{},"execution_count":79}],"source":"l"},{"cell_type":"code","execution_count":80,"metadata":{},"outputs":[{"output_type":"stream","name":"stderr","text":[" 0%| | 0/48 [00:00\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0ml\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtqdm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlanguage_fractions\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mj\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mwordlengths_counts\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0mj\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mlanguage_fractions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0ml\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0mlanguage_fractions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0ml\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mTypeError\u001b[0m: argument of type 'int' is not iterable"]}],"source":"for l in tqdm(language_fractions):\n for j in wordlengths_counts:\n if j not in language_fractions[l]:\n language_fractions[l] = 0"},{"cell_type":"code","execution_count":81,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["0"]},"metadata":{},"execution_count":81}],"source":"language_fractions[l]"},{"cell_type":"code","execution_count":82,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["{'it': 0,\n"," 'mt': {3: 5383,\n"," 4: 7849,\n"," 5: 4599,\n"," 6: 3424,\n"," 7: 2205,\n"," 8: 1810,\n"," 9: 670,\n"," 10: 453,\n"," 11: 180,\n"," 12: 123,\n"," 13: 86,\n"," 14: 13,\n"," 15: 35,\n"," 16: 12,\n"," 17: 5,\n"," 19: 6},\n"," 'pl': {3: 93486,\n"," 4: 64831,\n"," 5: 74697,\n"," 6: 67352,\n"," 7: 52483,\n"," 8: 43169,\n"," 9: 31409,\n"," 10: 18960,\n"," 11: 11082,\n"," 12: 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dict(main_data[main_data['language']==l].groupby('wl')['counts'].sum().reset_index().values)"},{"cell_type":"code","execution_count":84,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["{3: 55168,\n"," 4: 44716,\n"," 5: 67622,\n"," 6: 64864,\n"," 7: 55053,\n"," 8: 49666,\n"," 9: 43873,\n"," 10: 32573,\n"," 11: 29620,\n"," 12: 22595,\n"," 13: 12592,\n"," 14: 8209,\n"," 15: 4318,\n"," 16: 1496,\n"," 17: 1138,\n"," 18: 470,\n"," 19: 92,\n"," 20: 49,\n"," 21: 32,\n"," 22: 17}"]},"metadata":{},"execution_count":84}],"source":"language_fractions[l]"},{"cell_type":"code","execution_count":85,"metadata":{},"outputs":[{"output_type":"stream","name":"stderr","text":["100%|██████████| 48/48 [00:00<00:00, 73800.07it/s]\n"]}],"source":"for l in tqdm(language_fractions):\n for j in wordlengths_counts:\n if j not in language_fractions[l]:\n language_fractions[l][j] = 0"},{"cell_type":"code","execution_count":86,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["{'it': {3: 98098,\n"," 4: 60035,\n"," 5: 107270,\n"," 6: 81082,\n"," 7: 65570,\n"," 8: 54892,\n"," 9: 34074,\n"," 10: 26622,\n"," 11: 16161,\n"," 12: 7548,\n"," 13: 4481,\n"," 14: 3186,\n"," 15: 1959,\n"," 16: 408,\n"," 17: 180,\n"," 18: 103,\n"," 19: 61,\n"," 20: 16,\n"," 21: 5,\n"," 22: 0,\n"," 23: 0,\n"," 24: 0,\n"," 25: 0,\n"," 26: 0,\n"," 27: 0,\n"," 28: 0,\n"," 29: 0,\n"," 30: 0,\n"," 31: 0,\n"," 33: 0,\n"," 34: 0},\n"," 'mt': {3: 5383,\n"," 4: 7849,\n"," 5: 4599,\n"," 6: 3424,\n"," 7: 2205,\n"," 8: 1810,\n"," 9: 670,\n"," 10: 453,\n"," 11: 180,\n"," 12: 123,\n"," 13: 86,\n"," 14: 13,\n"," 15: 35,\n"," 16: 12,\n"," 17: 5,\n"," 19: 6,\n"," 18: 0,\n"," 20: 0,\n"," 21: 0,\n"," 22: 0,\n"," 23: 0,\n"," 24: 0,\n"," 25: 0,\n"," 26: 0,\n"," 27: 0,\n"," 28: 0,\n"," 29: 0,\n"," 30: 0,\n"," 31: 0,\n"," 33: 0,\n"," 34: 0},\n"," 'pl': {3: 93486,\n"," 4: 64831,\n"," 5: 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"},"metadata":{},"execution_count":87}],"source":"pd.DataFrame(language_fractions)"},{"cell_type":"code","execution_count":88,"metadata":{},"outputs":[{"output_type":"stream","name":"stderr","text":["100%|██████████| 48/48 [00:00<00:00, 78428.75it/s]\n"]}],"source":"for l in tqdm(language_fractions):\n for j in language_fractions[l]:\n language_fractions[l][j] /= wordlengths_counts[j]\n # for j in wordlengths_counts:\n # if j not in language_fractions[l]:\n # language_fractions[l][j] = 0"},{"cell_type":"code","execution_count":89,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" it mt pl sl ka rm-sursilv rm-vallader \\\n","3 0.018890 0.001037 0.018002 0.000493 0.000130 0.001200 0.000333 \n","4 0.013629 0.001782 0.014718 0.000614 0.000173 0.000878 0.000209 \n","5 0.028804 0.001235 0.020058 0.000727 0.000176 0.000672 0.000154 \n","6 0.026475 0.001118 0.021992 0.000464 0.000203 0.000696 0.000156 \n","7 0.027519 0.000925 0.022026 0.000276 0.000309 0.000462 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itmtplslkarm-sursilvrm-valladermnroes...pttafaenbrcvcatttrru
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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df = pd.DataFrame(language_fractions)\nlanguage_fractions_df.plot(use_index=True, y=language_fractions_df.columns, kind='bar',stacked=True)"},{"cell_type":"code","execution_count":91,"metadata":{},"outputs":[{"output_type":"error","ename":"KeyError","evalue":"\"['mt', 'sl', 'ka', 'rm-sursilv', 'rm-vallader', 'mn', 'ro', 'eo', 'sah', 'lv', 'cnh', 'pa-IN', 'dv', 'ar', 'vi', 'as', 'cy', 'ab', 'or', 'cs', 'fy-NL', 'sv-SE', 'id', 'ky', 'ia', 'et', 'el', 'ga-IE', 'ja', 'nl', 'uk', 'pt', 'ta', 'br', 'cv', 'ca', 'tt', 'tr', 'ru'] not in index\"","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mlanguage_fractions_df_major\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlanguage_fractions_major\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0;31m# language_fractions_df_major = language_fractions[]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mlanguage_fractions_df_major\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0muse_index\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlanguage_fractions_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'bar'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mstacked\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 956\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 957\u001b[0m \u001b[0;31m# don't overwrite\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 958\u001b[0;31m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 959\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 960\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mABCSeries\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3459\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_iterator\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3460\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3461\u001b[0;31m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_listlike_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3462\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3463\u001b[0m \u001b[0;31m# take() does not accept boolean indexers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_get_listlike_indexer\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1312\u001b[0m \u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnew_indexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reindex_non_unique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1313\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1314\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_read_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1315\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1316\u001b[0m if needs_i8_conversion(ax.dtype) or isinstance(\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_validate_read_indexer\u001b[0;34m(self, key, indexer, axis)\u001b[0m\n\u001b[1;32m 1375\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1376\u001b[0m \u001b[0mnot_found\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mensure_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mmissing_mask\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnonzero\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1377\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"{not_found} not in index\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1378\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1379\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: \"['mt', 'sl', 'ka', 'rm-sursilv', 'rm-vallader', 'mn', 'ro', 'eo', 'sah', 'lv', 'cnh', 'pa-IN', 'dv', 'ar', 'vi', 'as', 'cy', 'ab', 'or', 'cs', 'fy-NL', 'sv-SE', 'id', 'ky', 'ia', 'et', 'el', 'ga-IE', 'ja', 'nl', 'uk', 'pt', 'ta', 'br', 'cv', 'ca', 'tt', 'tr', 'ru'] not in index\""]}],"source":"language_fractions_major_keys = ['de','en','fr','it','rw','es','pl','eu','fa']\nlanguage_fractions_major = {}\nfor l in language_fractions:\n if l in language_fractions_major_keys:\n language_fractions_major[l] = language_fractions[l]\n\nlanguage_fractions_df_major = pd.DataFrame(language_fractions_major)\n# language_fractions_df_major = language_fractions[]\nlanguage_fractions_df_major.plot(use_index=True, y=language_fractions_df.columns, kind='bar',stacked=True)"},{"cell_type":"code","execution_count":92,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":92},{"output_type":"display_data","data":{"text/plain":"
","image/svg+xml":"\n\n\n \n \n \n \n 2021-08-06T18:19:40.516167\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_major_keys = ['de','en','fr','it','rw','es','pl','eu','fa']\nlanguage_fractions_major = {}\nfor l in language_fractions:\n if l in language_fractions_major_keys:\n language_fractions_major[l] = language_fractions[l]\n\nlanguage_fractions_df_major = pd.DataFrame(language_fractions_major)\n# language_fractions_df_major = language_fractions[]\nlanguage_fractions_df_major.plot(use_index=True, y=language_fractions_df_major.columns, kind='bar',stacked=True)"},{"cell_type":"code","execution_count":93,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":93},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_minor_keys = ['de','en','fr','it','rw','es','pl','eu','fa']\nlanguage_fractions_minor = {}\nfor l in language_fractions:\n if l in language_fractions_minor_keys:\n language_fractions_minor[l] = language_fractions[l]\n\nlanguage_fractions_df_minor = pd.DataFrame(language_fractions_minor)\n# language_fractions_df_major = language_fractions[]\nlanguage_fractions_df_minor.plot(use_index=True, y=language_fractions_df_minor.columns, kind='bar',stacked=True)"},{"cell_type":"code","execution_count":94,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":94},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_major_keys = ['de','en','fr','it','rw','es','pl','eu','fa']\nlanguage_fractions_major = {}\nfor l in language_fractions:\n if l in language_fractions_major_keys:\n language_fractions_major[l] = language_fractions[l]\n\nlanguage_fractions_df_major = pd.DataFrame(language_fractions_major)\n# language_fractions_df_major = language_fractions[]\nlanguage_fractions_df_major.plot(use_index=True, y=language_fractions_df_major.columns, kind='bar',stacked=True)"},{"cell_type":"code","execution_count":95,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":95},{"output_type":"display_data","data":{"text/plain":"
","image/svg+xml":"\n\n\n \n \n \n \n 2021-08-06T18:20:55.064940\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_major_keys = ['de','en','fr','it','rw','es','pl','eu','fa']\nlanguage_fractions_major = {}\nfor l in language_fractions:\n if l not in language_fractions_major_keys:\n language_fractions_major[l] = language_fractions[l]\n\nlanguage_fractions_df_major = pd.DataFrame(language_fractions_major)\n# language_fractions_df_major = language_fractions[]\nlanguage_fractions_df_major.plot(use_index=True, y=language_fractions_df_major.columns, kind='bar',stacked=True)"},{"cell_type":"code","execution_count":96,"metadata":{},"outputs":[],"source":"last = ['br','rm-sursilv','ro','sl','sah','lv','ia']"},{"cell_type":"code","execution_count":97,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":97},{"output_type":"display_data","data":{"text/plain":"
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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_major_keys = ['de','en','fr','it','rw','es','pl','eu','fa']\nlanguage_fractions_major = {}\nfor l in language_fractions:\n if l not in language_fractions_major_keys:\n language_fractions_major[l] = language_fractions[l]\n\nlanguage_fractions_df_major = pd.DataFrame(language_fractions_major)\n# language_fractions_df_major = language_fractions[]\nlanguage_fractions_df_major.plot(use_index=True, y=language_fractions_df_major.columns, kind='bar',stacked=True, figsize=(10,10))"},{"cell_type":"code","execution_count":98,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":98},{"output_type":"display_data","data":{"text/plain":"
","image/svg+xml":"\n\n\n \n \n \n \n 2021-08-06T18:30:35.568432\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_major_keys = ['de','en','fr','it','rw','es','pl','eu','fa']\nlanguage_fractions_major = {}\nfor l in language_fractions:\n if l not in language_fractions_major_keys:\n language_fractions_major[l] = language_fractions[l]\n\nlanguage_fractions_df_major = pd.DataFrame(language_fractions_major)\n# language_fractions_df_major = language_fractions[]\nlanguage_fractions_df_major.max().nlargest(10).plot(use_index=True, y=language_fractions_df_major.columns, kind='bar',stacked=True, figsize=(10,10))"},{"cell_type":"code","execution_count":99,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":99},{"output_type":"display_data","data":{"text/plain":"
","image/svg+xml":"\n\n\n \n \n \n \n 2021-08-06T18:30:45.238628\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n","image/png":"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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_major_keys = ['de','en','fr','it','rw','es','pl','eu','fa']\nlanguage_fractions_major = {}\nfor l in language_fractions:\n if l not in language_fractions_major_keys:\n language_fractions_major[l] = language_fractions[l]\n\nlanguage_fractions_df_major = pd.DataFrame(language_fractions_major)\n# language_fractions_df_major = language_fractions[]\nlanguage_fractions_df_major.max().nlargest(10).plot(use_index=True, y=language_fractions_df_major.columns, kind='bar',stacked=True, figsize=(10,10))"},{"cell_type":"code","execution_count":100,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["ca 0.132105\n","ru 0.090110\n","nl 0.073864\n","cy 0.022402\n","eo 0.016628\n","tr 0.011522\n","pt 0.010645\n","tt 0.007792\n","cs 0.005007\n","sv-SE 0.004517\n","dtype: float64"]},"metadata":{},"execution_count":100}],"source":"language_fractions_df_major.max().nlargest(10)"},{"cell_type":"code","execution_count":101,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["9 0.132105\n","10 0.125499\n","12 0.124327\n","11 0.123932\n","13 0.120116\n","8 0.118070\n","3 0.107636\n","7 0.107080\n","6 0.097573\n","14 0.097371\n","dtype: float64"]},"metadata":{},"execution_count":101}],"source":"language_fractions_df_major.max(axis=1).nlargest(10)"},{"cell_type":"code","execution_count":102,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["ca 0.132105\n","ru 0.090110\n","nl 0.073864\n","cy 0.022402\n","eo 0.016628\n","tr 0.011522\n","pt 0.010645\n","tt 0.007792\n","cs 0.005007\n","sv-SE 0.004517\n","dtype: float64"]},"metadata":{},"execution_count":102}],"source":"language_fractions_df_major.max(axis=0).nlargest(10)"},{"cell_type":"code","execution_count":103,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["mt 1.781866e-03\n","sl 7.271491e-04\n","ka 4.494032e-04\n","rm-sursilv 1.200449e-03\n","rm-vallader 3.333298e-04\n","mn 3.029438e-03\n","ro 9.652816e-04\n","eo 1.662803e-02\n","sah 7.738487e-04\n","lv 1.016134e-03\n","cnh 8.037658e-04\n","pa-IN 9.628244e-07\n","dv 3.777158e-05\n","ar 1.778144e-03\n","vi 5.045200e-05\n","as 4.063119e-05\n","cy 2.240193e-02\n","ab 2.098421e-06\n","or 3.485424e-05\n","cs 5.007071e-03\n","fy-NL 2.409179e-03\n","sv-SE 4.517379e-03\n","id 2.516290e-03\n","ky 2.624503e-03\n","ia 7.782186e-04\n","et 3.866135e-03\n","el 1.911977e-03\n","ga-IE 7.469376e-04\n","ja 8.280290e-06\n","nl 7.386364e-02\n","uk 3.475692e-03\n","pt 1.064543e-02\n","ta 1.720798e-04\n","br 1.208645e-03\n","cv 5.773156e-04\n","ca 1.321051e-01\n","tt 7.791612e-03\n","tr 1.152235e-02\n","ru 9.011039e-02\n","dtype: float64"]},"metadata":{},"execution_count":103}],"source":"language_fractions_df_major.max()"},{"cell_type":"code","execution_count":104,"metadata":{},"outputs":[{"output_type":"error","ename":"SyntaxError","evalue":"positional argument follows keyword argument (2626947293.py, line 1)","traceback":["\u001b[0;36m File \u001b[0;32m\"/tmp/ipykernel_11406/2626947293.py\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m language_fractions_df_major.max(axis=1,10)\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m positional argument follows keyword argument\n"]}],"source":"language_fractions_df_major.max(axis=1,10)"},{"cell_type":"code","execution_count":105,"metadata":{},"outputs":[],"source":"# language_fractions_major_keys = ['de','en','fr','it','rw','es','pl','eu','fa']\n# language_fractions_major = {}\n# for l in language_fractions:\n# if l not in language_fractions_major_keys:\n# language_fractions_major[l] = language_fractions[l]\n\n# language_fractions_df_major = pd.DataFrame(language_fractions_major)\n# # language_fractions_df_major = language_fractions[]\n# language_fractions_df_major.sort_values('').plot(use_index=True, y=language_fractions_df_major.columns, kind='bar',stacked=True, figsize=(10,10))"},{"cell_type":"code","execution_count":106,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" mt sl ka rm-sursilv rm-vallader mn ro \\\n","3 0.001037 0.000493 0.000130 0.001200 0.000333 0.001771 0.000409 \n","4 0.001782 0.000614 0.000173 0.000878 0.000209 0.001692 0.000965 \n","5 0.001235 0.000727 0.000176 0.000672 0.000154 0.002632 0.000709 \n","6 0.001118 0.000464 0.000203 0.000696 0.000156 0.003029 0.000881 \n","7 0.000925 0.000276 0.000309 0.000462 0.000102 0.001453 0.000873 \n","8 0.000999 0.000173 0.000246 0.000363 0.000049 0.001289 0.000607 \n","9 0.000517 0.000140 0.000186 0.000310 0.000053 0.000882 0.000590 \n","10 0.000529 0.000062 0.000334 0.000296 0.000032 0.000355 0.000394 \n","11 0.000353 0.000037 0.000410 0.000280 0.000020 0.000378 0.000157 \n","12 0.000397 0.000000 0.000307 0.000310 0.000042 0.000310 0.000087 \n","13 0.000515 0.000072 0.000449 0.000138 0.000030 0.000114 0.000204 \n","14 0.000136 0.000000 0.000293 0.000052 0.000000 0.000126 0.000000 \n","15 0.000730 0.000000 0.000334 0.000000 0.000000 0.000104 0.000000 \n","16 0.000521 0.000000 0.000000 0.000217 0.000000 0.000000 0.000000 \n","17 0.000373 0.000000 0.000000 0.000000 0.000000 0.000000 0.000448 \n","19 0.001351 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n","18 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n","20 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n","21 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n","22 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n","23 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n","24 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0.009686 0.003064 0.009230 0.000068 \n","7 0.013919 0.000512 0.000368 ... 0.008101 0.002811 0.009081 0.000073 \n","8 0.012192 0.000408 0.000215 ... 0.008820 0.002662 0.008341 0.000033 \n","9 0.008700 0.000323 0.000189 ... 0.009163 0.002714 0.005426 0.000021 \n","10 0.006513 0.000113 0.000067 ... 0.009561 0.003071 0.005441 0.000047 \n","11 0.004823 0.000169 0.000049 ... 0.011417 0.002657 0.004900 0.000010 \n","12 0.002822 0.000042 0.000016 ... 0.012113 0.002767 0.003768 0.000000 \n","13 0.003535 0.000000 0.000000 ... 0.012416 0.001582 0.003811 0.000000 \n","14 0.001852 0.000000 0.000000 ... 0.011258 0.001507 0.002815 0.000000 \n","15 0.000793 0.000000 0.000000 ... 0.015422 0.001231 0.002129 0.000000 \n","16 0.000434 0.000000 0.000000 ... 0.020376 0.003476 0.000739 0.000000 \n","17 0.000000 0.000000 0.000000 ... 0.025545 0.000523 0.000448 0.000000 \n","19 0.000000 0.000000 0.000000 ... 0.030849 0.000000 0.000000 0.000000 \n","18 0.000000 0.000000 0.000000 ... 0.021967 0.000000 0.001207 0.000000 \n","20 0.000000 0.000000 0.000000 ... 0.036662 0.000000 0.000000 0.000000 \n","21 0.000000 0.000000 0.000000 ... 0.015823 0.000000 0.000000 0.000000 \n","22 0.000000 0.000000 0.000000 ... 0.033181 0.000000 0.000000 0.000000 \n","23 0.000000 0.000000 0.000000 ... 0.013485 0.000000 0.000000 0.000000 \n","24 0.000000 0.000000 0.000000 ... 0.051887 0.000000 0.000000 0.000000 \n","25 0.000000 0.000000 0.000000 ... 0.042623 0.000000 0.000000 0.000000 \n","26 0.000000 0.000000 0.000000 ... 0.037234 0.000000 0.000000 0.000000 \n","27 0.000000 0.000000 0.000000 ... 0.000000 0.000000 0.000000 0.000000 \n","28 0.000000 0.000000 0.000000 ... 0.000000 0.000000 0.000000 0.000000 \n","29 0.000000 0.000000 0.000000 ... 0.073864 0.000000 0.000000 0.000000 \n","30 0.000000 0.000000 0.000000 ... 0.000000 0.000000 0.000000 0.000000 \n","31 0.000000 0.000000 0.000000 ... 0.000000 0.000000 0.000000 0.000000 \n","33 0.000000 0.000000 0.000000 ... 0.000000 0.000000 0.000000 0.000000 \n","34 0.000000 0.000000 0.000000 ... 0.000000 0.000000 0.000000 0.000000 \n","\n"," br cv ca tt tr ru \n","3 0.001166 0.000288 0.107636 0.003743 0.002406 0.010623 \n","4 0.001209 0.000308 0.068189 0.005188 0.002670 0.010151 \n","5 0.000947 0.000577 0.085317 0.007792 0.004333 0.018158 \n","6 0.000862 0.000271 0.097573 0.005129 0.003737 0.021179 \n","7 0.000674 0.000277 0.107080 0.004302 0.003881 0.023105 \n","8 0.000420 0.000301 0.118070 0.003388 0.003294 0.027403 \n","9 0.000180 0.000199 0.132105 0.001760 0.003743 0.033863 \n","10 0.000200 0.000249 0.125499 0.001191 0.003344 0.038074 \n","11 0.000053 0.000157 0.123932 0.000794 0.002327 0.058073 \n","12 0.000068 0.000084 0.124327 0.000549 0.002986 0.072948 \n","13 0.000030 0.000072 0.120116 0.000336 0.001983 0.075452 \n","14 0.000000 0.000157 0.097371 0.000230 0.001590 0.085892 \n","15 0.000000 0.000188 0.090131 0.000334 0.001148 0.090110 \n","16 0.000000 0.000000 0.065691 0.000000 0.000521 0.064995 \n","17 0.000000 0.000000 0.025545 0.000000 0.001046 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"},"metadata":{},"execution_count":106}],"source":"language_fractions_df_major"},{"cell_type":"code","execution_count":107,"metadata":{},"outputs":[],"source":"# language_fractions_major_keys = ['de','en','fr','it','rw','es','pl','eu','fa']\n# language_fractions_major = {}\n# for l in language_fractions:\n# if l not in language_fractions_major_keys:\n# language_fractions_major[l] = language_fractions[l]\n\n# language_fractions_df_major = pd.DataFrame(language_fractions_major)\n# # language_fractions_df_major = language_fractions[]\n# language_fractions_df_major.sort_values('').plot(use_index=True, y=language_fractions_df_major.columns, kind='bar',stacked=True, figsize=(10,10))"},{"cell_type":"code","execution_count":108,"metadata":{},"outputs":[{"output_type":"error","ename":"TypeError","evalue":"nlargest() missing 1 required positional argument: 'columns'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlanguage_fractions_df_major\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlargest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;31mTypeError\u001b[0m: nlargest() missing 1 required positional argument: 'columns'"]}],"source":"language_fractions_df_major.nlargest(10)"},{"cell_type":"code","execution_count":109,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" it mt pl sl ka rm-sursilv rm-vallader \\\n","3 0.018890 0.001037 0.018002 0.000493 0.000130 0.001200 0.000333 \n","4 0.013629 0.001782 0.014718 0.000614 0.000173 0.000878 0.000209 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48 rows × 31 columns

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"},"metadata":{},"execution_count":110}],"source":"language_fractions_df.transpose()"},{"cell_type":"code","execution_count":111,"metadata":{},"outputs":[{"output_type":"error","ename":"TypeError","evalue":"sort_values() missing 1 required positional argument: 'by'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlanguage_fractions_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msort_values\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtail\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/util/_decorators.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 309\u001b[0m \u001b[0mstacklevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstacklevel\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 310\u001b[0m )\n\u001b[0;32m--> 311\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 312\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 313\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mTypeError\u001b[0m: sort_values() missing 1 required positional argument: 'by'"]}],"source":"language_fractions_df.sort_values(axis=1).tail"},{"cell_type":"code","execution_count":112,"metadata":{},"outputs":[{"output_type":"error","ename":"TypeError","evalue":"sort_values() missing 1 required positional argument: 'by'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlanguage_fractions_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msort_values\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtail\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/util/_decorators.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 309\u001b[0m \u001b[0mstacklevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstacklevel\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 310\u001b[0m )\n\u001b[0;32m--> 311\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 312\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 313\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mTypeError\u001b[0m: sort_values() missing 1 required positional argument: 'by'"]}],"source":"language_fractions_df.sort_values(axis=1).tail()"},{"cell_type":"code","execution_count":113,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" it mt pl sl ka rm-sursilv rm-vallader \\\n","3 0.018890 0.001037 0.018002 0.000493 0.000130 0.001200 0.000333 \n","4 0.013629 0.001782 0.014718 0.000614 0.000173 0.000878 0.000209 \n","5 0.028804 0.001235 0.020058 0.000727 0.000176 0.000672 0.000154 \n","6 0.026475 0.001118 0.021992 0.000464 0.000203 0.000696 0.000156 \n","7 0.027519 0.000925 0.022026 0.000276 0.000309 0.000462 0.000102 \n","8 0.030286 0.000999 0.023818 0.000173 0.000246 0.000363 0.000049 \n","9 0.026300 0.000517 0.024243 0.000140 0.000186 0.000310 0.000053 \n","10 0.031118 0.000529 0.022162 0.000062 0.000334 0.000296 0.000032 \n","11 0.031685 0.000353 0.021727 0.000037 0.000410 0.000280 0.000020 \n","12 0.024369 0.000397 0.020821 0.000000 0.000307 0.000310 0.000042 \n","13 0.026850 0.000515 0.016436 0.000072 0.000449 0.000138 0.000030 \n","14 0.033336 0.000136 0.012441 0.000000 0.000293 0.000052 0.000000 \n","15 0.040881 0.000730 0.011144 0.000000 0.000334 0.000000 0.000000 \n","16 0.017726 0.000521 0.008038 0.000000 0.000000 0.000217 0.000000 \n","17 0.013445 0.000373 0.012324 0.000000 0.000000 0.000000 0.000000 \n","18 0.012432 0.000000 0.011949 0.000000 0.000000 0.000000 0.000000 \n","19 0.013736 0.001351 0.002252 0.000000 0.000000 0.000000 0.000000 \n","20 0.005587 0.000000 0.003492 0.000000 0.000000 0.000000 0.000000 \n","21 0.003165 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n","22 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"},"metadata":{},"execution_count":114}],"source":"language_fractions_df.transpose()"},{"cell_type":"code","execution_count":115,"metadata":{},"outputs":[{"output_type":"error","ename":"TypeError","evalue":"nlargest() missing 1 required positional argument: 'columns'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlanguage_fractions_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtranspose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlargest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;31mTypeError\u001b[0m: nlargest() missing 1 required positional argument: 'columns'"]}],"source":"language_fractions_df.transpose().nlargest(10)"},{"cell_type":"code","execution_count":116,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" 3 4 5 6 7 8 9 \\\n","en 0.267432 0.374121 0.307650 0.284801 0.311193 0.282339 0.262134 \n","de 0.231581 0.129696 0.136772 0.140211 0.118437 0.123826 0.144515 \n","ca 0.107636 0.068189 0.085317 0.097573 0.107080 0.118070 0.132105 \n","fr 0.102434 0.114762 0.107785 0.111844 0.116888 0.132967 0.133882 \n","fa 0.065989 0.085083 0.067020 0.040072 0.023621 0.015086 0.007348 \n","es 0.047326 0.033879 0.052043 0.053398 0.066651 0.065651 0.068115 \n","rw 0.031675 0.046783 0.060898 0.095430 0.084748 0.090948 0.090703 \n","it 0.018890 0.013629 0.028804 0.026475 0.027519 0.030286 0.026300 \n","pl 0.018002 0.014718 0.020058 0.021992 0.022026 0.023818 0.024243 \n","cy 0.017852 0.022402 0.019665 0.017337 0.012771 0.010374 0.007908 \n","\n"," 10 11 12 ... 24 25 26 27 28 \\\n","en 0.238985 0.202029 0.181517 ... 0.000000 0.000000 0.000000 0.0 0.0 \n","de 0.187480 0.227747 0.240980 ... 0.948113 0.957377 0.962766 1.0 1.0 \n","ca 0.125499 0.123932 0.124327 ... 0.000000 0.000000 0.000000 0.0 0.0 \n","fr 0.127631 0.118533 0.128818 ... 0.000000 0.000000 0.000000 0.0 0.0 \n","fa 0.004033 0.003264 0.003693 ... 0.000000 0.000000 0.000000 0.0 0.0 \n","es 0.070275 0.071100 0.056896 ... 0.000000 0.000000 0.000000 0.0 0.0 \n","rw 0.081564 0.069370 0.078282 ... 0.000000 0.000000 0.000000 0.0 0.0 \n","it 0.031118 0.031685 0.024369 ... 0.000000 0.000000 0.000000 0.0 0.0 \n","pl 0.022162 0.021727 0.020821 ... 0.000000 0.000000 0.000000 0.0 0.0 \n","cy 0.007558 0.007101 0.006802 ... 0.000000 0.000000 0.000000 0.0 0.0 \n","\n"," 29 30 31 33 34 \n","en 0.000000 0.0 0.0 0.0 0.0 \n","de 0.926136 1.0 1.0 1.0 1.0 \n","ca 0.000000 0.0 0.0 0.0 0.0 \n","fr 0.000000 0.0 0.0 0.0 0.0 \n","fa 0.000000 0.0 0.0 0.0 0.0 \n","es 0.000000 0.0 0.0 0.0 0.0 \n","rw 0.000000 0.0 0.0 0.0 0.0 \n","it 0.000000 0.0 0.0 0.0 0.0 \n","pl 0.000000 0.0 0.0 0.0 0.0 \n","cy 0.000000 0.0 0.0 0.0 0.0 \n","\n","[10 rows x 31 columns]"],"text/html":"
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"},"metadata":{},"execution_count":116}],"source":"language_fractions_df.transpose().nlargest(10, 3)"},{"cell_type":"code","execution_count":117,"metadata":{},"outputs":[{"output_type":"error","ename":"NameError","evalue":"name 'language_fractions_df_T' is not defined","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlanguage_fractions_df_T\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlanguage_fractions_df_T\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mlanguage_fractions_df_T\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlargest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0muse_index\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'bar'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mstacked\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mNameError\u001b[0m: name 'language_fractions_df_T' is not defined"]}],"source":"language_fractions_df_T = language_fractions_df_T\nlanguage_fractions_df_T.nlargest(10, 3).plot(use_index=True,kind='bar',stacked=True)"},{"cell_type":"code","execution_count":118,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":118},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_df.transpose()\nlanguage_fractions_df_T.nlargest(10, 3).plot(use_index=True,kind='bar',stacked=True, figsize=(10,10))"},{"cell_type":"code","execution_count":119,"metadata":{},"outputs":[{"output_type":"error","ename":"AttributeError","evalue":"'DataFrame' object has no attribute 'tranpose'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mlanguage_fractions_df_T\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlanguage_fractions_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtranspose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mlanguage_fractions_df_T\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlargest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtranpose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0muse_index\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'bar'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mstacked\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfigsize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m 5476\u001b[0m ):\n\u001b[1;32m 5477\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5478\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mobject\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__getattribute__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 5479\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5480\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mAttributeError\u001b[0m: 'DataFrame' object has no attribute 'tranpose'"]}],"source":"language_fractions_df_T = language_fractions_df.transpose()\nlanguage_fractions_df_T.nlargest(10, 3).tranpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10))"},{"cell_type":"code","execution_count":120,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":120},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_df.transpose()\nlanguage_fractions_df_T.nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10))"},{"cell_type":"code","execution_count":121,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":121},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_df.transpose()\nlanguage_fractions_df_T.nsmallest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10))"},{"cell_type":"code","execution_count":122,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":122},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_df.transpose()\nlanguage_fractions_df_T.nlargest(20, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10))"},{"cell_type":"code","execution_count":123,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":123},{"output_type":"display_data","data":{"text/plain":"
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5IkqayIaPfXMzwcKUmSVABDmCRJUgEMYZIkSQXodmPCJElSc3r33XeZM2cOCxcuLLqUqvXt25chQ4bQp0+fiu9jCJMkSQ1hzpw59O/fn6FDh5L9hnr3kFLi1VdfZc6cOay99toV38/DkZIkqSEsXLiQAQMGdKsABhARDBgwoOoePEOYJElqGN0tgLXoTN2GMEmSpAI4JkySJDWkocf9pabtzTp1j5q2t7TsCZMkSSqAIUySJCl36aWXstVWW7HZZpvxrW99i/fee49+/fpxwgknMGzYMLbZZhteeumlmqzLECZJkgRMnz6dq666invuuYepU6fSq1cvLrvsMt5880222WYbHnnkEXbYYQfOP//8mqzPMWGSJEnAbbfdxuTJk9lyyy0BePvtt1lttdVYdtll+fznPw/AFltswS233FKT9RnCJEmSyE66OmbMGE455ZQlpp9++unvn4KiV69eLFq0qCbr83CkJEkSMHLkSK699lrmzp0LwLx583jmmWfqtj57wiRJUkPq6lNKbLzxxowfP55dd92VxYsX06dPH84666y6rS9SSnVrvB5GjBiRHnrooaLLkCRJNTZ9+nQ22mijosvotLbqj4jJKaURbS3v4UhJkqQCGMIkSZIKYAiTJEkqgCFMkiSpAHULYRFxQUTMjYhH25kfEXFmRDwVEX+PiM3rVYskSVKjqWdP2EXAqA7m7wasl1/GAufUsRZJkqSGUrfzhKWU7oyIoR0sshdwScrOkXFfRKwcER9PKb1Qr5okSVI3Mm6lGrc3v7rFx42jX79+/Od//mdt68gVebLW1YHZJbfn5NM+FMIiYixZbxlrrrlmlxQnSVLdVRIyKgkOtWqnVhqtnhbPT2l/3uDhS3d/gNfnApWf56xbDMxPKZ2XUhqRUhoxaNCgosuRJElN6ic/+Qnrr78+2223HU888QQATz/9NKNGjWKLUQey/d5f5/GnZtZkXUX2hD0HrFFye0g+TZIkqctNnjyZK6+8kqlTp7Jo0SI233xztthiC8aOHcu5557Leiu8wf0PT+Pw409h4jXnLfX6igxh1wNHRsSVwNbAfMeDSZKkotx1113svffeLL/88gCMHj2ahQsXMmnSJPbdd194920A/v3OOzVZX91CWERcAewEDIyIOcCPgD4AKaVzgRuA3YGngLeAr9WrFkmSpM5YvHgxK6+8MlOnTi0/JqxKdRsTllI6IKX08ZRSn5TSkJTS71JK5+YBjJQ5IqW0Tkrpkyklf5VbkiQVZocdduC6667j7bffZsGCBUyYMIHll1+etddem2uuuQaAlBKPPPbPmqyvyMORkiRJ7Rt7R/llavGtxtzmm2/Ofvvtx7Bhw1httdXYcsstAbjssss47LDDGP+jGby7aBH77/U5hm2yfkVtdsQQJkmqn0Y9VYHUjhNOOIETTjjhQ9NvvPHG7nM4UpIkSe0zhEmSJBXAECZJklQAQ5gkSVIBDGGSJEkFMIRJkiQVwFNUSJKkhvTJW75a0/amffaSmra3tOwJkyRJKoAhTJIkKXfJJZew6aabMmzYMA4++GAmTJjA1ltvzfDhw9llv2/z0suv1mxdHo6UJEkCHnvsMcaPH8+kSZMYOHAg8+bNIyK47777iAh+e/pJ/M/ZF/PzHx1Tk/UZwiRJkoCJEyey7777MnDgQABWXXVVpk2bxn777ccLL7zAO28tYO01B9dsfYYwSWoi48aNq8kykjJHHXUUxxxzDKNHj+aOa89n3C9+U7O2DWGSJFXLHyZvSjvvvDN77703xxxzDAMGDGDevHnMnz+f1VdfHYCLr5lQ0/UZwiSpiYzjlxUtJXUHFZ1SYvDw8ss8P6Wi9W2yySaccMIJ7LjjjvTq1Yvhw4czbtw49t13X1ZZZRV23moTZs5+vqK2KmEIkyT1HPZgqYwxY8YwZsyYJabttdde2ZUKw1ylPEWFJElSAQxhkiRJBTCESZIkFcAQJkmSVAAH5kuSGp8D6tWE7AmTJEkqgD1hkiSpIU3f+cCatrfRxMvLLnPmmWdyzjnnsPnmm3PZZZfVdP2tGcIkSZJyZ599NrfeeitDhgx5f9qiRYvo3bv2kcnDkZIkScC3v/1tZsyYwW677cZKK63EwQcfzLbbbsvBBx9cl/XZEyZJkgSce+653Hjjjdx+++38+te/ZsKECdx9990st9xydVmfIUyS9CHTN9yo7DIbPT69CyqRijN69Oi6BTDwcKQkSVKbVlhhhbq2bwiTJEkqgIcjJUlSQ6rklBIMHl5+meenLH0xdWAIk6SlcNvEdcouM3Lnp7ugEkm1MGvWLADGjRtX93UZwiRpKdx1Z/mvro/cuQsKkdTtGMIkSVLG3+jsUoYwSWoAHtaUeh5DmCTpQzba//miS5CaniFMkhqAY8uknsfzhEmSJBXAnjBJktSQzjr5tQqWmlhxe0ectErZZc4880zOOeccNt98cy677LKK2+4MQ5gkLYVDF45sqHYkLZ2zzz6bW2+9lSFDhtR9XYYwSZIk4Nvf/jYzZsxgt91246CDDuK6665j4cKFLLfcclx44YVs0L+263NMmCRJEnDuuecyePBgbr/9dg477DDuuusupkyZwsknn8wPfvCDmq+vKXrCPnb71LLLvPiZzepehyRJag7z589nzJgxPPnkk0QE7777bs3XYU+YJElSKz/84Q/5zGc+w6OPPsqECRNYuHBhzdfRFD1htWKPmtRzNNoZ6of0/XwFS/lzMVJXmT9/PquvvjoAF110UV3WYQiTJEkNqZJTSjB4ePllnp9S9bq///3vM2bMGMaPH88ee+xR9f0rYQiTJEnKzZo1C4CBAwfyz3/+8/3p48eP71SY64hjwiRJkgpgT5i6XK3G3jmGT5LUndkTJkmSVAB7wlQxe54kSaqdpghhl6UvVbBU133VvNEYnqQPu+vOg8suM3LnLihEUo/VFCGsWTVreKpVaDZ8S5K6M0NYHTRreJIkqSv9/Ls/rGl7x/7yv2va3tJyYL4kSVIB7AlTxTz8J0lqdpdeeilnnnkm77zzDltvvTVnn3023/jGN3jooYeI9/7N1/cbzXfHHlSTdRnCShgyJFXrqpmnlV3mWLbvgkokLa3p06dz1VVXcc8999CnTx8OP/xwxo8fz3PPPcejjz4Kz0/h9fkLarY+Q1gPYLiUPuzQhSOLLkFSg7ntttuYPHkyW265JQBvv/02o0aNYsaMGRx11FHssc0G7Lrjp2q2PkOYejy/SCFJAkgpMWbMGE455ZQlpv/kJz/hpptu4tzzf83VE27hgl+Mq8n6HJgvSZIEjBw5kmuvvZa5c+cCMG/ePJ555hkWL17Ml770JcZ//3AenvZ4zdbXFD1hnnRRkqTmU9EpJQYPL7/M81MqWt/GG2/M+PHj2XXXXVm8eDF9+vThF7/4BXvvvTeLFy+Gd9/mlOOPqqitSjRFCGtWjuWSJKlr7bfffuy3335LTHv44YezKxWGuUoZwtTjGXZ7Jr/VKKlohjB1W412GNoB/h27beI6ZZcZubNhV1LPYQgrUauduj0rHWu08CRJUhEMYVKDsUdNknoGQ5jUpAxzktTYDGGqmIcRO1arw9CN1o4kqT4MYZK6RK1CvAP8pZ5jzplvVLDUXRW3N+Tofp0vpg4MYT2APViSJFUnpURKiWWWqd+PCzVFCPOHeCUVpe8qxxRdgqQamTVrFp/73OfYeuutmTx5MltttRUXXnghZ5xxBmeccQYz7v4/Zjwzh4OP/iH3/OnCpV5fU4SwWjHMSZLUsz355JNcfPHFDB06lD333BOAu+66iwEDBvDcC3O56/4p7LDN5jVZlyGsgXkYUZKkrrXWWmuxzTbbAPDGG2+wYMECZs+ezYEHHsid9z/MXQ9M4Yu71WbnawhTj2fY7VizDoTf/ZHuV7Ok+lthhRXev/7pT3+aCy+8kA022IDtt9+eC371P9w7+e/8/KTv1mRdhrA6cKeuRtCsr8NGe1w733FEBUtNr3sdkmpv++2356STTuKkk05i+PDh3D7pQZbr25eVVuxfk/YNYVKDabSQIUlFqeiUEoOHl1/m+SmdWv/222/P7Nmz2WGHHejVqxdrDP4YG647tFNttcUQJkmSBAwdOpRHH330/dvrrLMOKaX3b998xdk1XZ8hTFKX8NvHkrQkQ5i6XLPujD2MKEmqhiFMUocMl5JUH4YwdVvN2qMmSeoZDGGSupVGC99fPr78x+i0LqhDUvdTv1+llCRJUrvsCesBatVz0Gg9EJKk5jbuvD9VsFQly+Ttjd2r7DKf/vSnmTRpErNmzWLSpEkceOCBFbdfLXvCJEmScpMmTQJg1qxZXH755XVdlz1hkrQUps18tugSJNVQv379eOONNzjuuOOYPn06m222GWPGjOG7363N70WWaooQdtXM08oucyzbd0ElteXhP0mSinHqqady+umn8+c//7lu6/BwpCRJUgEMYZIkSQVoisORjcbDiFoavn4kqXj9+/dnwYIFdV2HIUw9nqfwkKTGVMkpJRg8vPwyz0+pet2bbropvXr1YtiwYRxyyCEOzJdUOUOhJFXvjTfeAKBPnz5MnDixrutyTJgkSVIBDGGSJEkFMIRJkiQVoK5jwiJiFHAG0Av4bUrp1Fbz1wQuBlbOlzkupXRDPWvqSLOe9FWSJDWeuvWERUQv4CxgN2Bj4ICI2LjVYicCV6eUhgP7A2fXqx5JkqRGUs/DkVsBT6WUZqSU3gGuBFp/1zQBK+bXVwKer2M9kiRJDaOehyNXB2aX3J4DbN1qmXHAzRFxFLACsEtbDUXEWGAswJprrlnzQiX1PF8+vvzH37QuqENS+257fJ/yCz1eeXsjN7y2U3XstNNOnH766YwY3KtT929P0QPzDwAuSikNAXYHfh8RH6oppXReSmlESmnEoEGDurxISZKkWqtnT9hzwBolt4fk00p9AxgFkFK6NyL6AgOBuXWsS1IVPOmrpJ5i1qxZjBo1ii222IKHH36YTTbZhEsuuaRu66tnT9iDwHoRsXZELEs28P76Vss8C4wEiIiNgL7Ay3WsSZIkqV1PPPEEhx9+ONOnT2fFFVfk7LPr953BuoWwlNIi4EjgJmA62bcgH4uIkyNidL7YscA3I+IR4ArgkJRSqldNkiRJHVljjTXYdtttATjooIO4++6767auup4nLD/n1w2tpp1Ucv0fwLb1rEGSJKlSEdHh7VoqemC+JElSw3j22We59957Abj88svZbrvt6rauuvaESZIkdVZFp5QYPLz8Ms9PqXidG2ywAWeddRZf//rX2XjjjTnssMOYMGFCxfevhiFMkiQp17t3by699NIlpt1xxx3ZlSrCXCU8HClJklQAQ5gkSRIwdOhQHn300S5bn4cjJfVI02Y+W3QJkno4e8IkSZIK0BQ9YX1XOaboEiSVcdXM08oucyzbd0ElktQYmiKE1YphTmp8hjlJzcIQJkmSGtLHnqjgbPVPTK2gpaydFzdorF9GdEyYJElSAQxhkiRJuUsuuYRNN92UYcOGsffee7P22mvz7rvvAvCvBW+w9jaff//20jKESZIkAY899hjjx49n4sSJPPLII/zud79jp5124i9/+QsAV/7pJr6428706dOnJuszhEmSJAETJ05k3333ZeDAgQCsuuqqHHrooVx44YUAXHjV9Xxtv9E1W58D8yV1K36LWVJX2nbbbZk1axZ33HEH7y1ezH9suG7N2jaESepWdr7jiAqWml73OiQ1n5133pm9996bY445hgEDBjBv3jxWXXVVvvrVr3LggQfyw6MOqen6DGF14HmMJElaehWdUmLw8PLLPD+lovVtsskmnHDCCey444706tWL4cOHc9FFF/GVr3yFE088kQO+MKqidiplCJMkScqNGTOGMWPGLDHt7rvvZp999mHllfrXdF2GMHVbzdrj2KyPS5K6o6OOOoq//vWv3HDDDcCbNW3bECZJktSOX/3qVx/cqPCwZqU8RYUkSWoYKTXWTwtVKqu7utrtCVOX83CbJKktffv25dVXX2XAgAFEVPC7kQ0ipcSrby6i7/wZVd3PEKYez1AoSY1hyJAhzJkzh5dffjmb8Prc8neaX8EpaereTqLv/BkMefg0GHV4+XZyhrAewJAhSeoO+vTpw9prr/3BhHHblL/TuPkVLNOF7VTBMWGSJEkFsCdMUofsSZWk+jCEqWLujLU0/M1HSVqSIUyqEUNqx/zNR0lakiFMalKGQklqbA7MlyRJKoAhTJIkqQAejmxgHk6SJKl52RMmSZJUAEOYJElSAQxhkiRJBXBMmKRu5cvHl//YmtYFdUjS0rInTJIkqQCGMEmSpAIYwiRJkgpgCJMkSSqAIUySJKkATfHtyJ3vOKKCpabXvQ5JkqRK2RMmSZJUgKboCWs0fVc5pugSJElSg7MnTJIkqQCGMEmSpAIYwiRJkgpgCJMkSSqAIUySJKkAfjtSUrcybeazRZcgSTVhT5gkSVIBDGGSJEkFMIRJkiQVwDFhJfwNSkmS1FUMYeq2mvXnoZr1cUmSlmQIkxqMPbKS1DMYwtTlatXT02hhxR4sSVI1DGE9gOFAkqTGYwhTj9esPXO1YoiXpPowhDUwd35qBM0aLiWpaIYwVaxZe4warR5JUs/gyVolSZIKYAiTJEkqgCFMkiSpAIYwSZKkAhjCJEmSCmAIkyRJKoAhTJIkqQCeJ0wV83xa3Ysn+5WkxmZPmCRJUgHsCesB7MHqmXzeJamx2RMmSZJUAEOYJElSAQxhkiRJBTCESZIkFcAQJkmSVABDmCRJUgEMYZIkSQXwPGF14PmZJElSOfaESZIkFcCesAZmj5okSc3LnjBJkqQCGMIkSZIKYAiTJEkqgCFMkiSpAIYwSZKkAhjCJEmSCmAIkyRJKoAhTJIkqQCerFVSl/jy8eU/bqZ1QR2S1CjsCZMkSSqAIUySJKkAhjBJkqQCGMIkSZIKUNeB+RExCjgD6AX8NqV0ahvLfBkYByTgkZTSgdWuxwG/kiSpu6lbCIuIXsBZwGeBOcCDEXF9SukfJcusBxwPbJtSei0iVqtXPZIkSY2k7OHIiPhORKwYmd9FxMMRsWsFbW8FPJVSmpFSege4Etir1TLfBM5KKb0GkFKaW+0DkCRJ6o4qGRP29ZTSv4BdgVWAg4EPHVZsw+rA7JLbc/JppdYH1o+IeyLivvzw5YdExNiIeCgiHnr55ZcrWLUkSVJjqySERf53d+D3KaXHSqYtrd7AesBOwAHA+RGxcuuFUkrnpZRGpJRGDBo0qEarliRJKk4lIWxyRNxMFsJuioj+wOIK7vccsEbJ7SH5tFJzgOtTSu+mlGYC/yQLZZIkSU2tkhD2DeA4YMuU0lvAssDXKrjfg8B6EbF2RCwL7A9c32qZ68h6wYiIgWSHJ2dUVLkkSVI3VvbbkSmlxRExFDgoIhJwd0rpjxXcb1FEHAncRHaKigtSSo9FxMnAQyml6/N5u0bEP4D3gO+llF5discjSZLULZQNYRFxNrAucEU+6VsRsUtK6Yhy900p3QDc0GraSSXXE3BMfpEkSeoxKjlP2M7ARnlgIiIuBv7R8V0kSZLUkUrGhD0FrFlyew3gyfqUI0mS1DNU0hPWH5geEQ+Q/bTQVsBDEXE9QEppdB3rkyRJakqVhLCTyi8iSZKkalTy7ci/dUUhkiRJPUm7ISwi7k4pbRcRC8gOQ74/i+yLjSvWvTpJkqQm1W4ISyltl//t33XlSGo0Xz6+/KiFaV1QhyQ1m456wlbt6I4ppXm1L0eSJKln6Ohf3MlkhyHb+rHuBHyiLhVJkiT1AB0djly7KwtpBB52USPwdShJPUO7J2uNiM9FxD5tTP9SRHy2vmVJkiQ1t47OmH8S0NbpKf4GnFyfciRJknqGjkLYR1JKL7eemFJ6BVihfiVJkiQ1v45C2IoR8aHBKRHRB1iufiVJkiQ1v45C2B+A8yPi/V6viOgHnJvPkyRJUid1FMJOBF4CnomIyRExGZgJvJzPkyRJUid1dIqKRcBxEfFjYN188lMppbe7pDJJkqQmVskPeL+NpyWSJEmqqfJnhZSanCdHlSQVwRCmbsvwJEnqzioKYRExGtghv/m3lNKE+pUkqRlNm/ls0SVIUkPp6NuRAETEKcB3gH/kl6Mj4qf1LkySJKmZVdITtgewWUppMUBEXAxMAX5Qz8Kk7sbDo5KkapTtCcutXHJ9pTrUIUmS1KNU0hN2CjAlIm4Hgmxs2HF1rUqSJKnJVXKesCsi4g5gy3zSf6WUXqxrVZIkSU2u3RAWERumlB6PiM3zSXPyv4MjYnBK6eH6l6dm5NipruF2lqTG1tGn9LHAN4GftzEvATvXpSLVnDtjSZIaT0e/HfnN/O9nuq4cSZKknqGjw5Ff7OiOKaU/1L4cSZKknqGj41R75n9XAz4NTMxvfwaYBBjCJEmSOqmjw5FfA4iIm4GNU0ov5Lc/DlzUJdV1U47BkiRJ5VRystY1WgJY7iVgzTrVI0mS1CNUcrLW2yLiJuCK/PZ+wK31K0mSJKn5VXKy1iPzQfrb55POSyn9sb5lqRF5mFWSpNqppCes5ZuQDsTvYoYeSZKaV9m9fEQsIDs5K8CyQB/gzZTSivUsTJIkqZlVcjiyf8v1iAhgL2CbehYlSZLU7Cr5duT7UuY64HP1KUeSJKlnqORwZOmZ85cBRgAL61aRJElSD1DJwPw9S64vAmaRHZKUJElSJ1UyJuxrradFxJbA3LpUJEmS1ANUdIoKgIjYGDggv7xOdlhSkiRJndBhCIuIoXwQvN4F1gJGpJRm1b0ySZKkJtZuCIuIe4EVgSuBL6WUnoyImc0cwKbNfLboEiRJUg/R0SkqXgL6Ax8FBuXTUvuLS5IkqVLthrCU0heATwKTgXERMRNYJSK26qLaJEmSmlaHY8JSSvOBC4ELI2I14MvALyNizZTSGl1RYCU8jChJkrqbis+Yn1Kam1L6dUppW2C7OtYkSZLU9Kr62aIWKaVnal2IJElST9KpECZJkqSl024Ii4jT8r/7dl05kiRJPUNHA/N3j4jjgOOBa7qoHkkNxi++SFJ9dBTCbgReA/pFxL+AIDtPWAAppbRiF9QnSZLUlDo6T9j3UkorA39JKa2YUupf+rfrSpQkSWo+ZX/AO6W0V0R8FNgyn3R/Sunl+pYlSZLU3Mp+OzIfmP8AsC/ZyVofiIh96l2YJElSMyvbEwacCGyZUpoLEBGDgFuBa+tZmCRJUjOr5Dxhy7QEsNyrFd5PkiRJ7aikJ+zGiLgJuCK/vR9wQ/1KkiRJan6VDMz/XkR8kQ9+L/K8lNIf61uWJElSc6ukJ4yU0h+AP9S5FkmSpB7DsV2SJEkFMIRJkiQVoKoQFhHrRMQn61WMJElST1HRmDCAiPgBsC6wOCI+klI6uH5lSZIkNbd2Q1hEHA2clVJ6L580LKW0Xz7v711RnCRJUrPq6HDkq2TnCBud3745Im6MiJuBm+pfmiRJUvNqN4SllC4D9gQ2jYjrgcnAF4F9U0rf66L6JEmSmlK5gfnrAFcDY4EjgDOA5epdlCRJUrPraEzYRcC7wPLAcymlb0bEcOD8iHgwpXRyF9UoSZLUdDr6duTwlNIwgIiYApBSmgLsGRF7dUVxUk80beazRZcgSeoCHYWwv+Y/3N0HuLx0RkrpT3WtSpIkqcm1G8JSSsdFxIrA4pTSG6XzIiKAbVJK99a7QEmSpGbU4claU0r/arkeER8DRgG7AesD9+YXSZIkVamjgfm9gG3JQtdngNfIzg/2o5TS411TXvfkmB5JklRORz1hDwD3ADcCJ6eU3u6akiTVgv8MSFJj62hM2BZdWYgkSVJPUu5krZIkSaoDQ5gkSVIBDGGSJEkFMIRJkiQVwBAmSZJUgA5P1qrm4KkKOub2kSQVwRCmbsvwJEnqzgxhDcyQIUlS8zKESTViaJYkVcOB+ZIkSQUwhEmSJBXAECZJklQAQ5gkSVIBDGGSJEkFMIRJkiQVwBAmSZJUAEOYJElSAep6staIGAWcAfQCfptSOrWd5b4EXAtsmVJ6qJ41qfNqdTJST2oqSVIde8IiohdwFrAbsDFwQERs3MZy/YHvAPfXqxZJkqRGU8/DkVsBT6WUZqSU3gGuBPZqY7n/Bk4DFtaxFkmSpIZSzxC2OjC75PacfNr7ImJzYI2U0l86aigixkbEQxHx0Msvv1z7SiVJkrpYYQPzI2IZ4BfAseWWTSmdl1IakVIaMWjQoPoXJ0mSVGf1DGHPAWuU3B6ST2vRH/gP4I6ImAVsA1wfESPqWJMkSVJDqGcIexBYLyLWjohlgf2B61tmppTmp5QGppSGppSGAvcBo/12pCRJ6gnqFsJSSouAI4GbgOnA1SmlxyLi5IgYXa/1SpIkdQd1PU9YSukG4IZW005qZ9md6lmLJElSI/GM+ZIkSQUwhEmSJBXAECZJklQAQ5gkSVIBDGGSJEkFMIRJkiQVwBAmSZJUgLqeJ6y7Gbrw8rLLzKp/GZIkqQewJ0ySJKkAhjBJkqQCGMIkSZIKYAiTJEkqgCFMkiSpAIYwSZKkAhjCJEmSCmAIkyRJKoAhTJIkqQCGMEmSpAIYwiRJkgpgCJMkSSqAIUySJKkAhjBJkqQCGMIkSZIKYAiTJEkqgCFMkiSpAIYwSZKkAhjCJEmSCmAIkyRJKoAhTJIkqQCGMEmSpAIYwiRJkgpgCJMkSSqAIUySJKkAhjBJkqQCGMIkSZIKYAiTJEkqgCFMkiSpAIYwSZKkAhjCJEmSCmAIkyRJKkDvogtQ/Q1deHnZZWbVvwxJklTCnjBJkqQC2BNWB/Y8SZKkcuwJkyRJKoAhTJIkqQCGMEmSpAIYwiRJkgpgCJMkSSqAIUySJKkAhjBJkqQCGMIkSZIKYAiTJEkqgCFMkiSpAIYwSZKkAvjbkQ3M36CUJKl5GcJUMUOhJEm14+FISZKkAhjCJEmSCmAIkyRJKoAhTJIkqQCGMEmSpAIYwiRJkgpgCJMkSSpAU5wnzPNXSZKk7saeMEmSpAI0RU+Yuhd7LiVJsidMkiSpEIYwSZKkAhjCJEmSCmAIkyRJKoAhTJIkqQCGMEmSpAIYwiRJkgpgCJMkSSqAIUySJKkAhjBJkqQCGMIkSZIK4G9HqtvyNyglSd2ZPWGSJEkFMIRJkiQVwBAmSZJUAEOYJElSAQxhkiRJBTCESZIkFcAQJkmSVABDmCRJUgEMYZIkSQUwhEmSJBXAECZJklQAQ5gkSVIBDGGSJEkFMIRJkiQVwBAmSZJUAEOYJElSAeoawiJiVEQ8ERFPRcRxbcw/JiL+ERF/j4jbImKtetYjSZLUKOoWwiKiF3AWsBuwMXBARGzcarEpwIiU0qbAtcD/1KseSZKkRtK7jm1vBTyVUpoBEBFXAnsB/2hZIKV0e8ny9wEH1bEeqU1DF15edplZ9S9DktTD1PNw5OrA7JLbc/Jp7fkG8Nc61iNJktQw6tkTVrGIOAgYAezYzvyxwFiANddcswsrkyRJqo969oQ9B6xRcntIPm0JEbELcAIwOqX077YaSimdl1IakVIaMWjQoLoUK0mS1JXqGcIeBNaLiLUjYllgf+D60gUiYjjwG7IANreOtUiSJDWUuoWwlNIi4EjgJmA6cHVK6bGIODkiRueL/QzoB1wTEVMj4vp2mpMkSWoqdR0TllK6Abih1bSTSq7vUs/1S5IkNSrPmC9JklQAQ5gkSVIBDGGSJEkFMIRJkiQVoCFO1io1A3/+SJJUDXvCJEmSCmAIkyRJKoAhTJIkqQCGMEmSpAIYwiRJkgpgCJMkSSqAIUySJKkAhjBJkqQCGMIkSZIKYAiTJEkqgCFMkiSpAIYwSZKkAhjCJEmSCtC76AIkLWnowsvLLjOr/mVIkurMnjBJkqQCGMIkSZIKYAiTJEkqgCFMkiSpAIYwSZKkAhjCJEmSCmAIkyRJKoAhTJIkqQCGMEmSpAIYwiRJkgpgCJMkSSqAIUySJKkAhjBJkqQCGMIkSZIKYAiTJEkqgCFMkiSpAIYwSZKkAhjCJEmSCmAIkyRJKoAhTJIkqQCGMEmSpAIYwiRJkgpgCJMkSSqAIUySJKkAhjBJkqQCGMIkSZIKYAiTJEkqgCFMkiSpAL2LLkBSfQxdeHnZZWbVvwxJUjvsCZMkSSqAIUySJKkAhjBJkqQCGMIkSZIKYAiTJEkqgCFMkiSpAIYwSZKkAhjCJEmSCmAIkyRJKoAhTJIkqQCGMEmSpAIYwiRJkgpgCJMkSSqAIUySJKkAhjBJkqQCGMIkSZIKYAiTJEkqgCFMkiSpAIYwSZKkAhjCJEmSCmAIkyRJKoAhTJIkqQCGMEmSpAL0LroASY1t6MLLyy4zq/5lSFLTsSdMkiSpAIYwSZKkAhjCJEmSCmAIkyRJKoAhTJIkqQCGMEmSpAIYwiRJkgpgCJMkSSqAIUySJKkAhjBJkqQCGMIkSZIKYAiTJEkqgCFMkiSpAIYwSZKkAhjCJEmSCmAIkyRJKoAhTJIkqQCGMEmSpAL0LroAST3D0IWXl11mVv3LkKSGYU+YJElSAQxhkiRJBTCESZIkFcAQJkmSVIC6hrCIGBURT0TEUxFxXBvzPxIRV+Xz74+IofWsR5IkqVHU7duREdELOAv4LDAHeDAirk8p/aNksW8Ar6WU1o2I/YHTgP3qVZOk7s9vWUpqFvXsCdsKeCqlNCOl9A5wJbBXq2X2Ai7Or18LjIyIqGNNkiRJDSFSSvVpOGIfYFRK6dD89sHA1imlI0uWeTRfZk5+++l8mVdatTUWGJvf3AB4oszqBwKvlFmmErZjO7ZjO7ZjO7ZjO0vTzloppUFtzegWJ2tNKZ0HnFfp8hHxUEppxNKu13Zsx3Zsx3Zsx3Zsp17t1PNw5HPAGiW3h+TT2lwmInoDKwGv1rEmSZKkhlDPEPYgsF5ErB0RywL7A9e3WuZ6YEx+fR9gYqrX8VFJkqQGUrfDkSmlRRFxJHAT0Au4IKX0WEScDDyUUroe+B3w+4h4CphHFtRqoeJDl7ZjO7ZjO7ZjO7ZjO0W0U7eB+ZIkSWqfZ8yXJEkqgCFMkiSpAIYwSZKkAjRFCIuIrSJiy/z6xhFxTETsXoN2L6lBG9vl9exa5f22jogV8+vLRcSPI2JCRJwWEStV0c7REbFG+SXLtrNsRHw1InbJbx8YEb+OiCMiok+VbX0iIv4zIs6IiF9ExLdbHqskVSIiViu6BmlpdfuB+RHxI2A3sm963gJsDdxO9puVN6WUflJhO61PnxHAZ4CJACml0RW280BKaav8+jeBI4A/ArsCE1JKp1bYzmPAsPxbpucBb5H/tFM+/YsVtjMfeBN4GrgCuCal9HIl923VzmVk23h54HWgH/CHvJ5IKY1p/95LtHM08HngTmB3YEre3t7A4SmlO6qtTZWJiNVSSnOLrkMflv9jdTzwBWA1IAFzgT8Bp6aUXi+suKUQER8DfgQsBk4CjgK+BEwHvpNSeqHCdlZtPQmYDAwn+/yZV7OiOykiBqSUCjnPZUSMAH5Gdu7N44ELyH468J/A2JTSlC6upzfZb0PvDQzOJz9H9nr+XUrp3Rqs47yU0tjyS0JELA8cSfa++hXZmRi+CDwOnJxSemMp6vhnSmn9zt6flFK3vgDTyE6BsTzwL2DFfPpywN+raOdh4FJgJ2DH/O8L+fUdq2hnSsn1B4FB+fUVgGlVtDO9tLZW86ZWUw9Zj+euZKcEeRm4kez8bP2raOfv+d/ewEtAr/x2VLmdp5Xcd3ngjvz6mqXbroJ2VgJOJXsTzSM7ye/0fNrKRb8uO3sBPgacA5wFDADG5dvsauDjVbSzaqvLALLftV4FWLXox5nXOKDAdY8g+2ftUrITRt8CzM/fs8MLqOcm4L+Aj7V6LfwXcHON1vHXKpZdETgF+D1wYKt5Z1fRzo1kwes44O/541kjn/anKtpZDMxsdXk3/zujinZGlVxfKf9M/DtwOfDRKto5FRhY8lqaATwFPEN1+4uHgROBdZbyuX2ArDPiAGA2sE8+fSRwbxXt9ANOBh7L3w8vA/cBh1RZzxX559g2ZCdqH5JfPwe4qop2Wn+OlX6ezaminauBnwNnA7cBvwa2Jwuuv6+inQVkOeNf+fUFwHst0zv13C3NE98IF5YMPVNazZtaRTvLAN/NP4w3y6dV/OYuaecRsh3dALLzobVZawXtXAN8Lb9+ITAiv74+8GAV7bQOcH2A0fmb5OUq2nkUWDZ/bAvId+RAX0oCYwXtTAM+kl9fpXQbAY9W0Y47rY7bcafVcTuNttN6ojPz2lh283YuWwAvVNHO/+XP2RfITqr9fyXv24eraGdKyfVnW82bWkU7x+bvjU+WTJvZief94ZLrvwXGA2uRffZfV0U700qu3w5smV9fn1af+2XamQmcDjybvya/CwzuxOPqaDtPqaKdPwGHkIWmY4AfAusBFwM/raKdf3ZmXhvLvpd/VpR+jrXcfqeKdqbmfwN4kQ+OAlbbiXAmcAkln32deR0u0ebS3LkRLsD9wPL59WVKpq9UzYdFyf2GkAWgX7d+MVd4/1klL5IZ5L0XZB/WU6toZyXgIrLDiPeT7UBnAH8jOxxZaTtTOpi3fBXtfDdf/zPA0WT/TZxPFqp+VEU73yHbiZ9P1ovVEjQHAXdW0Y47rY7bcafV+e08pYp2arXTuhn4Pkt+uH+ULITfWkU775ENobi9jcvbVbQztdXtE4B7yP65rOb1/EjJ9fHtvSYqbKvls/kXQH86909y6eu59WOcWkU704He+fX7Ovu4WtWzPVlPzYv58zW2inbuJTvasS/ZZ/QX8uk7Vvn+eqTV7Qfzv8sAj1fRzn15LaX75GWA/YD7q2jnSWDNdubNrqKdqSXXL+joMVfQ1hb5e+zo/DFV/Tpcor2luXMjXMh3dG1MH0jJDqgT7e5RzYdoBe0tD6zdifutCAzLn/iKex5K7r9+DR/DYPIdHrAy2U9NbdWJdjbJ77vhUtTiTqt8W+602m+n0XZaqwCnkf1j8hrZIfbp+bSKDx+T9Viv1868anZa0ynZgebTDiHr8XuminZOBvq1MX1d4NpqX4/5fUeT7eRf7MR955CF5WPJ/qmMknnV9IgclX8G7Uw2ZOCM/LXzY6o7vPWhzway4TWjgAuraGcY2dGBvwIb5vW8nj9fn66inUnAdiXb+aaSedX8czsUuIpsXOM/88vcfFrF+0GyMdXD2nsOqmjnt+28DtcB7u7E62gZshB2F/B8Z17H77e1NHf24qWoS6ud1rxWO61VqmjHnVbH93Wn1XE7Ndlp5ctvCOzS+vmn5JBwBW3sA2zQzrwvVNHO/wC7tDF9FPBkJx7XyKV5XK3bIRvz+x+d2D4/anVpGbP7MeCSKuvZiSxUTCE7InADMBboU0UbV1azzjJtbbS02zl/XzxA9o/A3S2vJbIjFUdXWc/WZF8OGABsC/wnsHsnHtdWfNBzvnH+eVSrdvYo/UzrRDvbk33hpOp63m+vVi8AL14a5UJ+iLPCZRtup1WLx9XGfUt3WtVsn67YafWuoo2a7bRq9PrZtNVOa/18elU7LbL/qp8AriMb0rBXybyqhlVQh9DTavpuVbRxVC0eVzfbPl3eTr59Hq/R9tmIpf9n4Edk//g9RDZW9jayQ/V3AicsRTsTG6ydTj2uJdrszJ28eGnkC50Yy9dOO50OPXVqp1aPq1m3T6Nt52rC3LSWnR7ZoZyHyE7hANWNUatJWKF24alWj6tW7TRUKGzA7VyTMEftzlrQlO2UXnojdUMR8ff2ZpGNDauFH5N9M7XL2qnV42rW7VOrdhpw+yyT8nMVpZRmRcROwLURsVZeU6W+CWyRUnojIobmbQxNKZ1RZTtja9ROrR5Xrdqp1eNq1u38TbJv4i9tPYtSSu8Bb0XE0ymlf+W1vR0Ri23nA4YwdVcfBT5HdhioVJCN06lIA4aemjyuWrXTaNun0bZzDet5KSI2SylNBch3gp8nO+nmJ6top9FCT60eV7Nun0bbzrWq552IWD6l9BbZl8qA909KXE1YadZ23mcIU3f1Z7Lu96mtZ0TEHVW001Chh9o9rmbdPo22nWtVz1eBRaUTUkqLgK9GxG+qaKfRQk+tHlezbp9G2861qmeHlNK/8zZKw0kfshOF9/R23tftf7ZIWhoR8Tuyb9Xd3ca8y1NKB3ZlO42m0bZPo23nBqxnCNkhkxfbmLdtSumermyn0TTa9mm07dxo9fQEhjBJkqQCLFN0AZIkST2RIUySJKkAhjBJDSEifhkR/6/k9k0R8duS2z+PiGM62fZOEfHnSqfXSkSsHBGHd9X6JHUvhjBJjeIe4NMAEbEM2e+/blIy/9NU+I3DiOhV8+o6Z2Xg8HILSeqZDGGSGsUk4FP59U3IftdzQUSsEhEfIfs5lYcjYmRETImIaRFxQT6PiJgVEadFxMPAvhExKiIez29/sZpCImLXiLg3Ih6OiGsiol/JOn6cT58WERvm0wdFxC0R8VhE/DYinomIgcCpwDoRMTUifpY33y8irs1ruywiqjn/kqQmYgiT1BBSSs8DiyJiTbJer3uB+8mC2QiynwxZBrgI2C+l9Emycx0eVtLMqymlzcl+duV8YE+ykyp+rNI68vB0ItlvgW5O9hMwpYdBX8mnn0P2o8SQ/abcxJTSJsC1wJr59OOAp1NKm6WUvpdPGw78P7IfEf4E2Y8bS+qBDGGSGskksgDWEsLuLbl9D7ABMDOl9M98+YuBHUruf1X+d8N8uSdTdh6eS6uoYRuygHRPREwlOwnjWiXz/5D/nUz2O30A2wFXAqSUbuTDJ28t9UBKaU5+ssepJW1I6mE8Y76kRtIyLuyTZIcjZwPHkv1YbiW/w/hmDWoI4JaU0gHtzP93/vc9OvcZ+u+S651tQ1ITsCdMUiOZBHwemJdSei+lNI9scPun8nlPAEMjYt18+YOBv7XRzuP5cuvkt9sLVG25D9i2ZR0RsUJErF/mPvcAX86X3xVYJZ++AOhfxbol9SCGMEmNZBrZtyLvazVtfkrplZTSQuBrwDURMY3sR3PPbd1IvtxY4C/5wPy5HaxzZETMabkA6wKHAFdE9gPd95Id3uzIj4FdI+JRYF/gRWBBSulVssOaj5YMzJckwJ8tkqSlln9D872U0qKI+BRwTkpps4LLktTgHIsgSUtvTeDq/Pxm7wDfLLgeSd2APWGSJEkFcEyYJElSAQxhkiRJBTCESZIkFcAQJkmSVABDmCRJUgH+P89tB3/MLGN9AAAAAElFTkSuQmCC\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_df.transpose()\nlanguage_fractions_df_T.nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"\\% of Audio Clips\", xlabel='Word Length', title='Percentage of Audio Clips by Word Length for each Language')\n# plt.savefig('plots/stacked/stack_number_audio_clips_vs_word_length_top10.png')"},{"cell_type":"code","execution_count":124,"metadata":{},"outputs":[],"source":"wl15 = [3,4,5,6,7,8,9,10,11,12,13,14,15]"},{"cell_type":"code","execution_count":125,"metadata":{},"outputs":[{"output_type":"error","ename":"KeyError","evalue":"\"None of [Int64Index([3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15], dtype='int64')] are in the [columns]\"","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlanguage_fractions_df_T\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlanguage_fractions_df\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mwl15\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtranspose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mlanguage_fractions_df_T\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlargest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtranspose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0muse_index\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'bar'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mstacked\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfigsize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mylabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"\\% of Audio Clips\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mxlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Word Length'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtitle\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Percentage of Audio Clips by Word Length for each Language'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;31m# plt.savefig('plots/stacked/stack_number_audio_clips_vs_word_length_top10.png')\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3459\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_iterator\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3460\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3461\u001b[0;31m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_listlike_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3462\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3463\u001b[0m \u001b[0;31m# take() does not accept boolean indexers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_get_listlike_indexer\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1312\u001b[0m \u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnew_indexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reindex_non_unique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1313\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1314\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_read_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1315\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1316\u001b[0m if needs_i8_conversion(ax.dtype) or isinstance(\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_validate_read_indexer\u001b[0;34m(self, key, indexer, axis)\u001b[0m\n\u001b[1;32m 1372\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0muse_interval_msg\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1373\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1374\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"None of [{key}] are in the [{axis_name}]\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1375\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1376\u001b[0m \u001b[0mnot_found\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mensure_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mmissing_mask\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnonzero\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: \"None of [Int64Index([3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15], dtype='int64')] are in the [columns]\""]}],"source":"language_fractions_df_T = language_fractions_df[wl15].transpose()\nlanguage_fractions_df_T.nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"\\% of Audio Clips\", xlabel='Word Length', title='Percentage of Audio Clips by Word Length for each Language')\n# plt.savefig('plots/stacked/stack_number_audio_clips_vs_word_length_top10.png')"},{"cell_type":"code","execution_count":126,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":126},{"output_type":"display_data","data":{"text/plain":"
","image/svg+xml":"\n\n\n \n \n \n \n 2021-08-06T18:46:12.583508\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_df.transpose()[wl15]\nlanguage_fractions_df_T.nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"\\% of Audio Clips\", xlabel='Word Length', title='Percentage of Audio Clips by Word Length for each Language')\n# plt.savefig('plots/stacked/stack_number_audio_clips_vs_word_length_top10.png')"},{"cell_type":"code","execution_count":127,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":127},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_df.transpose()[wl15]\nlanguage_fractions_df_T.nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Percentage of Audio Clips\", xlabel='Word Length', title='Percentage of Audio Clips by Word Length (limited upto 15) for each Language ')\n# plt.savefig('plots/stacked/stack_number_audio_clips_vs_word_length_top10.png')"},{"cell_type":"code","execution_count":128,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":128},{"output_type":"display_data","data":{"text/plain":"
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b2upKNK8/6udD473OmCvd215PHYaJ+iCxE4B1FEzFC62OELSm/+GUpvwF5/DxHxrNKA6/crdavcpxQCpNSFNEWpq/VZpfF12/e2nV703Oh4tu2bi9eZpPSHeI6k/VXqbo2I30v6gdIFKdOK15JSAJPSH+xpkq536jb5k1Io7M0vJP1aKbA8qDRW8NNN1n2gpB9FxGPlL6Xw0dOt/mWlE94cSccrXZTS83PcpXQ1+dlK/13PUQqrrxIR9yoFsx8qtdi8X+lWVy/WqW2SpP+TdIpSN979SuHu4iZ/trMl/VHSA8W6PVdqbqq0P59TOkH/KCKuarCd30m6SSksXKo0xrLnZ5oh6WalP35/7W3lkuskjVQKj1Gs/6TScftEEbIVEX9S2ue/UdqnG0vat95Gi2Ppf5XGUU5TnSt+a/xYqRW95+uXEfFbpSvnzy2OuTslvbeJbUnpD9kflVoib1Fq7VmkV66G/r6kDzpdMf6DJrf5skj3gbxS6b2e23GSznDqctw7IqZKOkTpWJyjtI8PKup6UenCjIOUhiDsoxQmehURVyj9w3K70jF1SS+L/VppfPJjSmN/JxXrzpf0DUl/K2p7s1p/79+r9PteV2mcY8+wJCkdY9MkPav0z9OJEXFGad3/UjovNGtpzkvqY7/fLek7Su/fxyVtpfTPW8+65yvtq7OLn+cipQuE+uMtWvK90vNV9/zehMOVzgWPKe2jc/TKuV9KP/dRSkNpttSS/5Qfr3RB4Vyl89HLx1vpePyY0jnzAKVjbEExv+4+RXfquYAAaJrT7YHuVLpasOX72GFJtqcrDbL/0yC81i8kPRIRLd0XtsqKFp9TI6K/rUq9bXMLpSEM20VFT7K2r1a68CbLp3P1l1NPyzWS3tjHsBH0g+0TJa0VEc2OnW9l2/9Qei/+cqC3jfajhRNNcfrIyWG2V1NqWbqYsNldbI9TalH4eR+LVprTxxruVnTjravUrf/bgXyN4qKWbasaNjtZRDwREZsTNgeG7dfZfn1p+MLHNEDvF9vvtL1W8V48UNLrlS46RQURONGsTyjdKuN+pa7H/25vOWiF7a8ptUqfHBEPtrueNrNSV98cpS71e5RumQXg1VZR6gqfpzTE4jtacrzs0nit0oVdTyuNk/9gRDw6QNtGh6FLHQAAAFnRwgkAAICshva9SGdZY401Yty4ce0uAwAAoE833XTTkxFR78NQlhldFzjHjRunqVOntrsMAACAPtle2k/0qgS61AEAAJBV17VwAgAAoG8333zzHkOGDPmOpCGD8HKLFy9efOQ222xzUW8zCZwAAAAVNHTo0GM23njj51deeeXs96WdN2/eivfff/8xSp+W9Sp0qQMAAFRQRKw1fPjwQfkQhOHDh78QEa+pN58WTgAAgIqyrXHHXPqmVtaZfsKEm/rzOkofrNErAicAAAAa+sMf/jDi8ssvX3X+/PnL3XfffSvusccec2bMmLHCySef3NSnQ9GlDgAAgIYmT5682rhx4xasueaaC+fNm7fcpEmTZs+dO7fpi5EInAAAAGhor732mjNjxowVVl555ZfGjRu3oNX16VIHAACosP6Myaw1YcKE5yZMmPBcedppp502s9n1aeEEAABAVgROAAAAZEXgBAAAQFaM4QQAAKiy40a2dB9OHTe37pjPH/zgB6vvsMMO87bddtuWbihP4AQAAEBDF1xwwao33HDDynfddddKzzzzzJBLL7105Jw5c4Z8//vff6SZ9elSBwAAQEOXXXbZyG9961uPbrvttvP+8pe/rDJ69OhFCxcu9AsvvFD304XKCJwAAABoaNddd5178sknj7n55puHv/3tb3929uzZQzfZZJMFK664YjSzPl3qAAAAVdZgTGaz9t5772eKh7P6sz4tnAAAAMiKwAkAAICsCJwAAADIijGcAAAAFbbVGVu1dB/OOw68Y6nHfNYicAIAAKChSy+9dMQ111yzygYbbLDg6aefHvqvf/1r2PHHH//YuHHjFjazPl3qAAAAaGjKlCmjTjrppEcnTJjw7MKFCz1q1KjF11133fBm16eFEwAAAA1NnDjx6aOPPnpt2zFkyBBFhBYvXtzUTd+ligfOta66dcC3+di7th7wbQIAAOQyEGMyJ0yY8NyECROe6+/6dKkDAAAgKwInAAAAsiJwAgAAIKtKj+HsJow3BQAAOdzzus1bug/n5v+851VjPi+55JJVLr/88lWPPfbYx9ZYY43FrdZA4AQAAEBDF1544ahf/epXY8aOHfvibrvt9sxWW221oJX1CZwAAABoaOutt57/yCOPPH3IIYfMHj169Eutrk/gBFBZOYaqSHmGq3RTrQCWXUOGDOnXegROAACACuttTGarJk2aNHvSpEmz+7s+gRNAS2iJAwC0itsiAQAAIKtKt3CeFXtl2Or9GbaJZR2thnnkOQdInAcAdJNTPnllS7dF+tSpOy11F3ytSgdOgPubolsQjgF0Mu7DiUFHiAMAYNly4YUXjlpttdUW/eQnP1n9/vvvH/aLX/xiRivrM4YTAAAADW299dbzd9ppp2eHDBkSjz766PJz5sxpKUPSwgmgJXT9AsCy6ZZbbhk+evToRS+99JIXL17sVtYlcHYILnACAAA5DMRFQOV7cB522GFPtbo+XeoAAADIihZOoAPQTQ0AqDICJwCgJdw3Fugu39nnfS3dh/PI8y4Z8Ptw0qUOAACArCrdwvnXv3x4wLe5804DvklkxMVYAAAsvT/84Q8jLr/88lXnz5+/3HPPPbfc61//+uf333//Oeutt96iZtavdOAEAADA0ps8efJqb3jDG+Y/+eSTQ8eMGaM5c+YMiYim1ydwAgBawkVuQHcZiDGZe+2115yrrrpqldVXX33Rk08+OfTFF19c7sEHH1xh/fXXp4UTALpFjiFAEsOAuMAJGBgTJkx4bsKECc/1d30CZ4fopvGmjItEtyDEAUBnIHACANABcrTG0hKLTkHgBAAALSEcd5eZx/y1pftwjj3h7QN+H04CJwCgsrrpAieGK6HKCJwAWsK4SACE42XPEUccsc6QIUNizTXXXHjNNdesevzxxz9yxhlnjP7BD37wSDPrEziBDkCIAwB0umOOOeaJY489dq2tt9563plnnjl6rbXWWtjsugROAACAChuoMZlDhw6NBx54YNiXv/zlp774xS+u+73vfW9G0+sORAGd6uMv7NzuEprWTbUCAIBly3e/+91HJOmyyy57QJKuvPLKaa2sv1yOogAAAIAelW7hBLrphvoAAFQVgRMA0BIuckM3+fOVGw/4NnfeqbuuqD/uuONaug/ncccdx3040X60GgLAso2/A8ues846a+SVV1656s9//vOmLxQqYwwnAAAAGrr00ktH3nnnnStdeOGFq/ZnfVo4AQDoALQaopOttdZai0aMGDF/zz33fKY/6xM4AQAAKmygxmRGhM4555yR++2339xW1yVwAqgs7m8LLnACBkbPfTj7izGcAAAAyIoWTgDoALTGAnkwNrYzEDgBAAAq7M9XbtzSfTh33un+Ab8PJ13qAAAAaNqhhx46ttV1aOEEAABAQ0ccccQ6a6yxxsKHHnpo2OLFi93q+gROoAN00/i9bqoVADBw9tlnn6evvfbalU888cS1W12XwAkAAFBhAzUm84wzzhj9wAMPDNthhx2ea3VdAicAAAD6dOSRR84aOXLkS/1Zl8CJSqP7FwCApbe0N36vdOA878ETB3ybR+rtA75NAACAKqt04AQAAFjWrXXVrS3dh/Oxd2094PfhJHCiZXRTAwCAVhA4AQAt4Z/OPNiv6GSXXnrpiGuuuWaV9dZb78Xx48fPf/jhh5dffvnlY/fdd3+2mfUJnACAyiLEAQNjypQpo37yk5/MXLBggY8++ui1FyxYsNypp546s9n1CZwAAKAlBPnuMhBjMidOnPj00UcfvfZGG220YOTIkYtXX331Ba2sz2epAwAAoKEJEyY8d9JJJz26yy67PPvQQw+tcMghhzzVyvq0cAIAAFRURMhu+aPP69pkk00Wnn766TN6ex1JUW89WjgBAAAqyPZj8+fPX3EwXmv+/Pkr2n683vysLZy2d5X0fUlDJP0sIk6omb++pDMkjSqWOSYiLstZU6fiJvUAAGAgLVq06IRp06Z9R9KIQXi5xYsXL/5SvZnZAqftIZJOkfRuSTMl3Wh7SkTcXVrsS5ImR8SPbW8h6TJJ43LVBAAAsKzYZpttLpJ0UZvLkJS3S307SdMi4oGIeFHSuZJ2r1kmJK1aPB4paak+pxMAAACdJ2fgXFdSeVDpzGJa2XGSDrA9U6l189O9bcj2oban2p46a9asHLUCAAAgk3ZfNLSfpNMjYqyk3ST92varaoqI0yJifESMHzNmzKAXCQAAgP7LGTgflrRe6fnYYlrZxyRNlqSI+LukFSWtkbEmAAAADLKcV6nfKGlT2xsqBc19Je1fs8xDknaWdLrtzZUCJ33mAABgQPCpSJ0hWwtnRCySdLikyyXdo3Q1+l22v2p7YrHYkZIOsX2bpHMkHRTFnUMBAABQDVnvw1ncU/OymmlfKT2+W9Jbc9YAAACA9mr3RUMAAACoOAInAAAAsiJwAgAAICsCJwAAALIicAIAACArAicAAACyInACAAAgKwInAAAAsiJwAgAAIKusnzTUbiuudkS7SwAAAFjmVTpwdhPCMQAAqCq61AEAAJAVgRMAAABZETgBAACQFYETAAAAWRE4AQAAkBWBEwAAAFkROAEAAJAVgRMAAABZceN3tOy8B08c8G0eqbcP+DYBAEBnoIUTAAAAWdHCCQAdIEfPgUTvQTeh9whVRgsnAAAAsiJwAgAAICu61AFUFt3UANAZCJwAgJYQ5AG0isAJdAD+gAMAqowxnAAAAMiKwAkAAICs6FIHAACVxf1NOwOBE0BLGG8KAGgVgRMAUFn8gwR0BgInAABoCd3UaBUXDQEAACArAicAAACyoksdlUa3DwAA7UcLJwAAALIicAIAACArAicAAACyInACAAAgKwInAAAAsiJwAgAAICsCJwAAALIicAIAACArAicAAACyInACAAAgq0p/tOVOV38qw1bvybBNAACA6qKFEwAAAFkROAEAAJBVpbvUkceKqx3R7hIAAEAXoYUTAAAAWRE4AQAAkBWBEwAAAFkROAEAAJAVgRMAAABZETgBAACQFYETAAAAWRE4AQAAkBWBEwAAAFnxSUMdYqerP5Vhq/dk2CYAAEBraOEEAABAVrRwAkAHWHG1I9pdAtqMYwBVRuAEAKADMLQKVUbgBFBZ3dRilCdsSMt64OimYwCoMgIn0AH4owgAqDICJwCgJd30DxItx+im47XKCJyoNE40ALBsY2xsZyBwAmhJN4V4WrfyYL8CaBX34QQAAEBWBE4AAABkReAEAABAVgROAAAAZEXgBAAAQFYETgAAAGRF4AQAAEBWBE4AAABkxY3fAbSEm34D6KYPgEBnoIUTAAAAWdHCCXQAWg0BdBM+nxytooUTAAAAWRE4AQAAkBWBEwAAAFkROAEAAJAVgRMAAABZETgBAACQFYETAAAAWRE4AQAAkBU3fkfLuOEvAABoBS2cAAAAyIoWTlQarbEAALQfLZwAAADIisAJAACArAicAAAAyIrACQAAgKwInAAAAMiKwAkAAICsCJwAAADIisAJAACArAicAAAAyIrACQAAgKwInAAAAMiKwAkAAICsCJwAAADIisAJAACArIa2u4Cc9v78wP94dwz4FgEAAKotawun7V1t32t7mu1j6iyzt+27bd9l++yc9QAAAGDwZWvhtD1E0imS3i1ppqQbbU+JiLtLy2wq6fOS3hoRc2yvmaseAAAAtEfOFs7tJE2LiAci4kVJ50ravWaZQySdEhFzJCkinshYDwAAANogZ+BcV9KM0vOZxbSyzSRtZvtvtq+3vWtvG7J9qO2ptqfOmjUrU7kAAADIod1XqQ+VtKmkHSXtJ+mntkfVLhQRp0XE+IgYP2bMmMGtEAAAAEslZ+B8WNJ6pedji2llMyVNiYiFEfGgpH8pBVAAAABURM7AeaOkTW1vaHsFSftKmlKzzEVKrZuyvYZSF/sDGWsCAADAIMsWOCNikaTDJV0u6R5JkyPiLttftT2xWOxySbNt3y3pKklHRcTsXDUBAABg8GW98XtEXCbpspppXyk9DklHFF8AAACooHZfNAQAAICKI3ACAAAgq5YCp+3VbL8+VzEAAAConj4Dp+2rba9qe7Skm5Xulfnd/KUBAACgCppp4RwZEc9I2lPSryJie0m75C0LAAAAVdFM4Bxqe21Je0u6JHM9AAAAqJhmbov0VaX7Zf4tIm60vZGk+/KWBQAAsPT2/vzA3wHyjgHfYvX1+VuIiPMlnV96/oCkvXIWBQAAgOpo5qKhjWxfbHuW7Sds/65o5QQAAAD61MwYzrMlTZa0tqR1lFo7z8lZFAAAAKqjmYENwyPi16XnZ9o+KldByyrGmADAso2/A6iyZo7u39s+RtK5kkLSPpIuK+7LqYh4KmN9AAAA6HLNBM69i++fqJm+r1IAZTwnAAAA6mrmKvUNB6MQAAAAVFPdwGl7p4i40vaevc2PiAvzlQUAAICqaNTC+U5JV0p6fy/zQhKBEwAAAH2qGzgj4tji+8GDVw4AAACqplGX+hGNVoyI7w58OQAAAKiaRl3qqwxaFQAAAKisRl3qxw9mIQAAAKimuh9taftk27X33pTtT9g+IW9ZAAAAqIpGXeo7STq6l+k/lXS7pGOyVAQA6Gg5PoJR4mMYgSprdNYYFhFROzEiXrLtjDUBwDKHEAegyup2qUt63vamtROLac/nKwkAAABV0uhf6q9I+r3tr0u6qZg2XtLnJX02c10AAACoiEZXqf/e9h6SjpL06WLynZL2igh6aQAAHY+hCkBnaPhOjIg7JR04SLUAAACgghqN4QQAAACWGoETAAAAWeUZ3AIAHYDxe0AeOd5bvK+qrc8jxvZYST+U9DZJIemvkj4TETMz1wYsMwhGAIAqa6ZL/ZeSpkhaW9I6ki4upgEAAAB9aiZwjomIX0bEouLrdEljMtcFAACAimgmcM62fYDtIcXXAZJm5y4MAAAA1dDMwLGPKo3h/J7SGM7rJB2csyh0NgaLAwCAVvSZHCLi35ImDkItAAAAqKC6gdP20RFxku0fKrVsLiEiJmWtDAAAAJXQqIXznuL71MEoBEB34BZOAIBW1f3LEREXF9/PGLxygIHFeFMAANqvUZf6xeqlK71HRDCuEwAAAH1q1Pzz7eL7npLWknRm8Xw/SY/nLAoAAADV0ahL/RpJsv2diBhfmnWxbcZ1AgAAoCnN3Ph9Zdsb9TyxvaGklfOVBAAAgCpp5oqKz0m62vYDkixpA0mfyFoVAAAAKqOZG7//wfamkl5XTPpnRCzIWxYAAACqos/AafsjNZPeYFsR8atMNQEAAKBCmulS37b0eEVJO0u6WRKBEwAAAH1qpkv90+XntkdJOjdXQQAAAKiWZq5SrzVP0oYDXQgAAACqqZkxnOVPHFpO0haSzs9Z1LLojgcfancJAAAAWTQzhvPbpceLJP07ImZmqgcAAAAV08wYzmvKz22/zfbnI+JT+coCAABAVTTTwinbb5S0v6QPSXpQ0oU5ixoodFMDAAC0X93AaXszSfsVX09KOk+SI+Jdg1QbAAAAKqBRC+c/Jf1V0vsiYpok2f7coFQFAACAymh0W6Q9JT0q6SrbP7W9s9JnqQMAAABNqxs4I+KiiNhX6TPUr5L0WUlr2v6x7fcMUn0AAADocn3e+D0i5kXE2RHxfkljJd0i6X+yVwYAAIBKaOoq9R4RMUfSacUXAABAR+OONZ2hPx9tCQAAADStbuC0PWwwCwEAAEA1NWrh/Lsk2f71INUCAACACmo0hnMF2/tLeovtPWtnRkRXfNoQAAAA2qtR4PykpP+SNErS+2vmhbrk4y0BAADQXnUDZ0RcK+la21Mj4ueDWBMAAAAqpJnbIv3a9iRJ7yieXyPp1IhYmK8sAAAAVEUzgfNHkpYvvkvShyX9WNLHcxUFAACA6mgmcG4bEW8oPb/S9m25CgIAAEC1NHPj98W2N+55YnsjSYvzlQQAAIAqaaaF8yhJV9l+QJIlbSDp4KxVAQAAoDL6DJwR8Wfbm0p6bTHp3ohYkLcsAAAAVEUzLZwqAubtmWsBAABABTUzhhMAAADoNwInAAAAsuozcDo5wPZXiufr294uf2kAAACogmZaOH8kaQdJ+xXPn5V0SraKAAAAUCnNXDS0fURsY/sWSYqIObZXyFwXAAAAKqKZFs6FtodICkmyPUbSS1mrAgAAQGU0Ezh/IOm3kta0/Q1J10r6ZtaqAAAAUBnN3Pj9LNs3SdpZ6ZOG9oiIe7JXBgDAMuSOBx9qdwlANn0GTtujJT0h6ZzStOUjYmHOwgAAAFANzXSp3yxplqR/SbqveDzd9s2235SzOAAAAHS/ZgLnFZJ2i4g1ImJ1Se+VdImkw5RumQQAAADU1cxtkd4cEYf0PImIP9r+dkR8wvawjLWhQzHOCAAAtKKZwPmo7f+RdG7xfB9Jjxe3SuL2SAAALGNoeECrmulS31/SWEkXFV/rF9OGSNo7V2EAAACohmZui/SkpE/XmT1tYMsBAABA1TRzW6Qxko6WtKWkFXumR8ROGesCAABARTTTpX6WpH9K2lDS8ZKmS7oxY00AAACokGYC5+oR8XNJCyPimoj4qCRaNwEAANCUZq5S7/lEoUdtT5D0iKTR+UoCAABAlTQTOL9ue6SkIyX9UNKqkj6bsyhgWcMtRtBNOF4BtKqZwDknIuZKmivpXZJk+61ZqwIAAEBlNBM4fyhpmyamAQD6iVZDAFVWN3Da3kHSWySNsX1EadaqSjd9Bzoef8QBAGi/Ri2cK0gaUSyzSmn6M5I+mLMoAAAGAv90Ap2hbuCMiGskXWP79Ij49yDWBAAAgAppZgznMNunSRpXXp5PGgIAAEAzmgmc50s6VdLPJC3OWw4AAACqppnAuSgifpy9EgAAAFRSMx9tebHtw2yvbXt0z1f2ygAAAFAJzbRwHlh8P6o0LSRtNPDlAAAAoGr6DJwRseFgFAIAAIBq6rNL3fZw218qrlSX7U1tvy9/aQAAAKiCZrrUfynpJqVPHZKkh5WuXL8kV1EAMBC46TcAdIZmAufGEbGP7f0kKSLm23YzG7e9q6TvK30U5s8i4oQ6y+0l6QJJ20bE1OZKB9AOhDgAQKuauUr9RdsrKV0oJNsbS1rQ10q2h0g6RdJ7JW0haT/bW/Sy3CqSPiPpHy3UDQAAgC7RTOA8VtIfJK1n+yxJf5Z0dBPrbSdpWkQ8EBEvSjpX0u69LPc1SSdKeqG5kgEAANBN+gycEXGFpD0lHSTpHEnjI+LqJra9rqQZpeczi2kvs72NpPUi4tJGG7J9qO2ptqfOmjWriZcGAABAp2jmKvUPKH3a0KURcYmkRbb3WNoXtr2cpO9KOrKvZSPitIgYHxHjx4wZs7QvDQAAgEHUVJd6RMzteRIRTyt1s/flYUnrlZ6PLab1WEXSf0i62vZ0SW+WNMX2+Ca2DQAAgC7RTODsbZlmrm6/UdKmtje0vYKkfSVN6ZkZEXMjYo2IGBcR4yRdL2kiV6kDAABUSzOBc6rt79reuPj6rtJ9ORuKiEWSDpd0uaR7JE2OiLtsf9X2xKUrGwAAAN2imZbKT0v6sqTzlG6NdIWkTzWz8Yi4TNJlNdO+UmfZHZvZJgAAALpLw8BZ3Evzkoh41yDVAwAAgIpp2KUeEYslvWR75CDVAwAAgIpppkv9OUl32L5C0ryeiRExKVtVAAAAqIxmAueFxRcAAADQsj4DZ0ScUXyW+voRce8g1AQAAIAKaeaTht4v6Valz1OX7a1tT2m4EgAAAFBo5j6cx0naTtLTkhQRt0raKFtFAAAAqJRmAufC8kdbFl7KUQwAAACqp5mLhu6yvb+kIbY3lTRJ0nV5ywIAAEBVNPtJQ1+UtEDS2UofVfn1nEUti8a9cPaAb3P6gG8RAACgdXUDp+0VJX1S0iaS7pC0Q/H56AAAAEDTGo3hPEPSeKWw+V5J3x6UigAAAFApjbrUt4iIrSTJ9s8l3TA4JQEAAKBKGrVwLux5QFc6AAAA+qtRC+cbbD9TPLaklYrnlhQRsWr26gAAAND16gbOiBgymIUAAACgmpq58TsAAADQbwROAAAAZEXgBAAAQFYETgAAAGRF4AQAAEBWBE4AAABkReAEAABAVgROAAAAZEXgBAAAQFYETgAAAGRF4AQAAEBWBE4AAABkReAEAABAVgROAAAAZEXgBAAAQFYETgAAAGRF4AQAAEBWBE4AAABkReAEAABAVgROAAAAZEXgBAAAQFYETgAAAGRF4AQAAEBWBE4AAABkReAEAABAVgROAAAAZEXgBAAAQFYETgAAAGRF4AQAAEBWQ9tdAABp3AtnZ9nu9CxbBQCgNbRwAgAAICtaONGyHK1x0wd8iwAAoFPQwgkAAICsCJwAAADIisAJAACArAicAAAAyIrACQAAgKwInAAAAMiKwAkAAICsCJwAAADIisAJAACArAicAAAAyIrACQAAgKwInAAAAMhqaLsLAHIa98LZA77N6QO+RQAAqo3ACaAlOUK8RJAHgCqjSx0AAABZETgBAACQFYETAAAAWRE4AQAAkBWBEwAAAFkROAEAAJAVgRMAAABZETgBAACQVaVv/M6nzAAAALQfLZwAAADIisAJAACArCrdpQ5g2cbnvgNAZ6CFEwAAAFkROAEAAJAVgRMAAABZETgBAACQFYETAAAAWRE4AQAAkBWBEwAAAFkROAEAAJAVgRMAAABZETgBAACQFYETAAAAWRE4AQAAkNXQdhcAAJDGvXB2lu1Oz7JVAGgNLZwAAADIisAJAACArAicAAAAyIrACQAAgKwInAAAAMiKwAkAAICsCJwAAADIisAJAACArAicAAAAyIrACQAAgKwInAAAAMiKwAkAAICsCJwAAADIisAJAACArAicAAAAyIrACQAAgKwInAAAAMiKwAkAAICssgZO27vavtf2NNvH9DL/CNt3277d9p9tb5CzHgAAAAy+bIHT9hBJp0h6r6QtJO1ne4uaxW6RND4iXi/pAkkn5aoHAAAA7TE047a3kzQtIh6QJNvnStpd0t09C0TEVaXlr5d0QMZ6AAADYNwLZ2fZ7vQsWwXQCXJ2qa8raUbp+cxiWj0fk/T73mbYPtT2VNtTZ82aNYAlAgAAILeOuGjI9gGSxks6ubf5EXFaRIyPiPFjxowZ3OIAAACwVHJ2qT8sab3S87HFtCXY3kXSFyW9MyIWZKwHAAAAbZCzhfNGSZva3tD2CpL2lTSlvIDtN0r6iaSJEfFExloAAADQJtkCZ0QsknS4pMsl3SNpckTcZfurticWi50saYSk823fantKnc0BAACgS+XsUldEXCbpspppXyk93iXn6wMAAKD9OuKiIQAAAFQXgRMAAABZETgBAACQFYETAAAAWRE4AQAAkFXWq9QBAGgnPvcd6Ay0cAIAACArAicAAACyInACAAAgKwInAAAAsiJwAgAAICsCJwAAALIicAIAACArAicAAACyInACAAAgKwInAAAAsiJwAgAAICsCJwAAALIicAIAACArAicAAACyGtruAgAAgDTuhbMHfJvTB3yLQP/QwgkAAICsCJwAAADIisAJAACArAicAAAAyIrACQAAgKwInAAAAMiKwAkAAICsCJwAAADIisAJAACArAicAAAAyIrACQAAgKwInAAAAMiKwAkAAICsCJwAAADIisAJAACArAicAAAAyIrACQAAgKwInAAAAMiKwAkAAICsCJwAAADIisAJAACArAicAAAAyIrACQAAgKwInAAAAMiKwAkAAICsCJwAAADIisAJAACArAicAAAAyIrACQAAgKwInAAAAMhqaLsLAAAA3WXcC2cP+DanD/gW0Ulo4QQAAEBWBE4AAABkReAEAABAVgROAAAAZEXgBAAAQFYETgAAAGRF4AQAAEBWBE4AAABkReAEAABAVgROAAAAZEXgBAAAQFYETgAAAGRF4AQAAEBWBE4AAABkReAEAABAVgROAAAAZEXgBAAAQFYETgAAAGRF4AQAAEBWBE4AAABkReAEAABAVgROAAAAZEXgBAAAQFYETgAAAGRF4AQAAEBWBE4AAABkNbTdBQAAAOQy7oWzB3yb0wd8i9VHCycAAACyInACAAAgKwInAAAAsiJwAgAAICsCJwAAALIicAIAACArAicAAACyInACAAAgKwInAAAAsiJwAgAAICsCJwAAALIicAIAACArAicAAACyInACAAAgKwInAAAAsiJwAgAAICsCJwAAALIicAIAACArAicAAACyInACAAAgKwInAAAAsiJwAgAAICsCJwAAALIicAIAACArAicAAACyInACAAAgq6yB0/autu+1Pc32Mb3MH2b7vGL+P2yPy1kPAAAABl+2wGl7iKRTJL1X0haS9rO9Rc1iH5M0JyI2kfQ9SSfmqgcAAADtkbOFcztJ0yLigYh4UdK5knavWWZ3SWcUjy+QtLNtZ6wJAAAAg8wRkWfD9gcl7RoRHy+ef1jS9hFxeGmZO4tlZhbP7y+WebJmW4dKOrR4+lpJ92YoeQ1JT/a5VPt1S50SteZCrXlQax7Umge15pGj1g0iYswAb7PrDG13Ac2IiNMknZbzNWxPjYjxOV9jIHRLnRK15kKteVBrHtSaB7Xm0U21dpucXeoPS1qv9HxsMa3XZWwPlTRS0uyMNQEAAGCQ5QycN0ra1PaGtleQtK+kKTXLTJF0YPH4g5KujFx9/AAAAGiLbF3qEbHI9uGSLpc0RNIvIuIu21+VNDUipkj6uaRf254m6SmlUNouWbvsB1C31ClRay7Umge15kGteVBrHt1Ua1fJdtEQAAAAIPFJQwAAAMiMwAkAAICsCJwAAADIqivuwznQbG8nKSLixuLjNneV9M+IuKzNpfXJ9q8i4iPtrqMvtt+m9GlTd0bEH9tdT5nt7SXdExHP2F5J0jGStpF0t6RvRsTcthZYYnuSpN9GxIx219KX0t0oHomIP9neX9JbJN0j6bSIWNjWAmvY3kjSnkq3Zlss6V+Szo6IZ9paGABU0DJ30ZDtY5U+332opCskbS/pKknvlnR5RHyjjeUtwXbtbaQs6V2SrpSkiJg46EXVYfuGiNiueHyIpE9J+q2k90i6OCJOaGd9ZbbvkvSG4k4Kp0mar+KjVYvpe7a1wBLbcyXNk3S/pHMknR8Rs9pbVe9sn6X0vhou6WlJIyRdqLRfHREH1l97cBVB/n2S/iJpN0m3KNX8AUmHRcTVbSsOqBjba0bEE+2uA+21LAbOOyRtLWmYpMckjS21dP0jIl7fzvrKbN+s1Or2M0mhFDjPUXH7qIi4pn3VLcn2LRHxxuLxjZJ2i4hZtleWdH1EbNXeCl9h+56I2Lx4fHNEbFOad2tEbN224mrYvkXSmyTtImkfSRMl3aR0HFwYEc+2sbwl2L49Il5ffIjDw5LWiYjFti3ptg57b90haeuivuGSLouIHW2vL+l3PcdyJ7A9UtLnJe0haU2lc8ETkn4n6YSIeLptxWFQ2F5L0rGSXpL0FUmflrSXUu/BZyLi0TaWtwTbo2snKZ2z3qiUOZ4a/KrQCZbFMZyLImJxRMyXdH9P91lEPK/0Zu4k45XeqF+UNLdodXk+Iq7ppLBZWM72arZXVzqpzJKkiJgnaVF7S3uVO20fXDy+zfZ4SbK9maSO6vZVGvrxUkT8MSI+JmkdST9SGgbyQHtLe5Xlim71VZRaOUcW04dJWr5tVdXXM6RomFJrrCLiIXVerZMlzZG0Y0SMjojVlXo65hTzuoLt37e7hjLbq9r+lu1fF8M/yvN+1K666jhdqfFhhlKP3PNKLfN/lXRq+8rq1ZNKf7d6vqZKWlfSzcXjjmF719LjkbZ/bvt222fbfk07a6uiZbGF8x+S3hUR820vFxEvFdNHSrqq3NrVKWyPlfQ9SY9LmhgR67e5pFexPV0psFupBeatEfGo7RGSru2wVsORkr4v6e1KJ8dtlE7kMyRNiojb2ljeEsotx73MG17849QRbH9OqeVliKTvSNpdKRS/WdIFEXF8G8tbgu3PSPqYpH8oHQcnRsQvbY+R9JuIeEdbCyyxfW9EvLbVee1gu97505IuiYi1B7OeRmz/RtJ9kq6X9FGlfzb3j4gFtT0f7VbTg/RQ+W9AB/bKHKk0RO2oiLijmPZgRGzY3sperfx7tv0zpV7PnyqN7X5nROzRxvIqZ1kMnMMiYkEv09eQtHbPG6QT2Z6gFOS+0O5amlV0V74mIh5sdy21bK8qaUOllq6ZEfF4m0t6FdubRcS/2l1Hs2yvI0kR8YjtUUpDAR6KiBvaWlgvbG8paXOlC9v+2e566rH9R0l/knRGzzFatL4cJOndEbFLG8tbgu3Fkq5RCpi13hwRKw1ySXXVBjXbX1RqNZwo6YoOC5y3RcQbisdfj4gvlebd0UlDlqQlGklmKA0FuC0iNmpvVa9WEzhrj4eOCvJVsMwFTgDoJrZXU7qTwu5KYzil1NsxRWkM55x21VbL9p2SPhAR9/Uyb0ZErNeGsnpl+x5JW/b0chXTDpJ0lKQREbFBu2qrVXwk9EkR8VzN9E2UjoEPtqeyxmxPlPQFSeMiYq1211PL9kxJ31X6B+lTkjaOIhT1jElvZ31VsyyO4QSArhERcyLifyLidcUYztERsXlE/I/ShUSd5DjV/7vy6UGsoxkXS9qpPCEiTpd0pKQX21FQPRHxldqwWUyfJunSNpTUlIiYojTeeBdJKo2d7xQ/VRpzPkLSGZLWkF6+SOvW9pVVTbRwAkCXqh3P18lsHxwRv2x3Hc3oslq76Rjoplq75hjoFgROAOhgtm+vN0vSZhExbDDr6a8uCxsdVWs3HQPdVGsjnXYMVMEy+UlDANBFXiPpP5Vug1RmSdcNfjn19RE2Ouo2M91Uq7roGFAX1dplx0DXI3ACQGe7ROkilltrZ9i+etCraaxrwoa6q9ZuOga6qdZuOga6HoETADpYccP/evP2rzevTbopbHRNrd10DHRTreqiY6AKGMMJAACArLgtEgAAALIicAIAACArAieAjmD7e7Y/W3p+efH5xj3Pv2P7iH5ue0fblzQ7faDYHmX7sMF6PQDoVAROAJ3ib5LeIkm2l1P61I8tS/PfoiavHLU9ZMCr659Rkg7rayEAqDoCJ4BOcZ2kHYrHW0q6U9KztlezPUzS5pJutr2z7Vts32H7F8U82Z5u+0TbN0v6kO1dbf+zeL5nK4XYfo/tv9u+2fb5tkeUXuP4Yvodtl9XTB9j+wrbd9n+me1/215D0gmSNrZ9q+2Ti82PsH1BUdtZtr2U+w0AOh6BE0BHiIhHJC2yvb5Sa+bfJf1DKYSOl3SH0jnrdEn7RMRWSrd2++/SZmZHxDaSLlL6nOT3S3qTpLWaraMIil+StEuxramSyl35TxbTfyzp/xXTjpV0ZURsKekCST2fUHKMpPsjYuuIOKqY9kZJn5W0haSNJL212doAoFsROAF0kuuUwmZP4Px76fnfJL1W0oMR8a9i+TMkvaO0/nnF99cVy90X6d5vZ7ZQw5uVwuDfbN8q6UBJG5TmX1h8v0nSuOLx2ySdK0kR8Qe9+kbSZTdExMyIeEnSraVtAEBlceN3AJ2kZxznVkpd6jMkHSnpGUm/bGL9eQNQgyVdERH71Zm/oPi+WP07hy4oPe7vNgCgq9DCCaCTXCfpfZKeiojFEfGU0oU3OxTz7pU0zvYmxfIflnRNL9v5Z7HcxsXzeuGxN9dLemvPa9he2fZmfazzN0l7F8u/R9JqxfRnJa3SwmsDQCUROAF0kjuUrk6/vmba3Ih4MiJekHSwpPNt3yHpJUmn1m6kWO5QSZcWFw090eA1d7Y9s+dL0iaSDpJ0ju3blbr1X9dH3cdLeo/tOyV9SNJjkp6NiNlKXfN3li4aAoBlDh9tCQBLqbhSfnFELLK9g6QfR8TWbS4LADoGY4cAYOmtL2lycf/QFyUd0uZ6AKCj0MIJAACArBjDCQAAgKwInAAAAMiKwAkAAICsCJwAAADIisAJAACArP4/ViImpZ4K73UAAAAASUVORK5CYII=\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_df.transpose()[wl15]\nlanguage_fractions_df_T.nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Percentage of Audio Clips\", xlabel='Word Length', title='Percentage of Audio Clips by Word Length (limited upto 15) for each Language ')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='xx-small')\n\n# plt.savefig('plots/stacked/stack_number_audio_clips_vs_word_length_top10.png')"},{"cell_type":"code","execution_count":129,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":129},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_df.transpose()[wl15]\nlanguage_fractions_df_T.nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Percentage of Audio Clips\", xlabel='Word Length', title='Percentage of Audio Clips by Word Length (limited upto 15) for each Language ')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\n# plt.savefig('plots/stacked/stack_number_audio_clips_vs_word_length_top10.png')"},{"cell_type":"code","execution_count":130,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":130},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_df.transpose()[wl15]\nlanguage_fractions_df_T.nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Percentage of Audio Clips\", xlabel='Word Length', title='Percentage of Audio Clips by Word Length (limited upto 15) for top 10 languages')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\n# plt.savefig('plots/stacked/percent_audio_clips_by_word_length_vs_word_length_top10.png')"},{"cell_type":"code","execution_count":131,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":131},{"output_type":"display_data","data":{"text/plain":"
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= language_fractions_df.transpose()[wl15]\nlanguage_fractions_df_T.nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Percentage of Audio Clips\", xlabel='Word Length', title='Percentage of Audio Clips by Word Length (limited upto 15) for top 10 languages')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\n# plt.savefig('plots/stacked/percent_audio_clips_by_word_length_vs_word_length_top10.png')"},{"cell_type":"code","execution_count":132,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" it mt pl sl ka rm-sursilv rm-vallader \\\n","3 0.018890 0.001037 0.018002 0.000493 0.000130 0.001200 0.000333 \n","4 0.013629 0.001782 0.014718 0.000614 0.000173 0.000878 0.000209 \n","5 0.028804 0.001235 0.020058 0.000727 0.000176 0.000672 0.000154 \n","6 0.026475 0.001118 0.021992 0.000464 0.000203 0.000696 0.000156 \n","7 0.027519 0.000925 0.022026 0.000276 0.000309 0.000462 0.000102 \n","8 0.030286 0.000999 0.023818 0.000173 0.000246 0.000363 0.000049 \n","9 0.026300 0.000517 0.024243 0.000140 0.000186 0.000310 0.000053 \n","10 0.031118 0.000529 0.022162 0.000062 0.000334 0.000296 0.000032 \n","11 0.031685 0.000353 0.021727 0.000037 0.000410 0.000280 0.000020 \n","12 0.024369 0.000397 0.020821 0.000000 0.000307 0.000310 0.000042 \n","13 0.026850 0.000515 0.016436 0.000072 0.000449 0.000138 0.000030 \n","14 0.033336 0.000136 0.012441 0.000000 0.000293 0.000052 0.000000 \n","15 0.040881 0.000730 0.011144 0.000000 0.000334 0.000000 0.000000 \n","16 0.017726 0.000521 0.008038 0.000000 0.000000 0.000217 0.000000 \n","17 0.013445 0.000373 0.012324 0.000000 0.000000 0.000000 0.000000 \n","18 0.012432 0.000000 0.011949 0.000000 0.000000 0.000000 0.000000 \n","19 0.013736 0.001351 0.002252 0.000000 0.000000 0.000000 0.000000 \n","20 0.005587 0.000000 0.003492 0.000000 0.000000 0.000000 0.000000 \n","21 0.003165 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n","22 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31 rows × 48 columns

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"},"metadata":{},"execution_count":133}],"source":"language_fractions_df.rename({'ab':'Abkhaz',\n\t'ar':'Arabic',\n\t'as':'Assamese',\n\t'br':'Breton',\n\t'cnh':'Hakha Chin',\n\t'ca':'Catalan',\n\t'cs':'Czech',\n\t'cv':'Chuvash',\n\t'cy':'Welsh',\n\t'de':'German',\n\t'dv':'Divehi',\n\t'el':'Greek',\n\t'en':'English',\n\t'es':'Spanish',\n\t'eo':'Esperanto',\n\t'eu':'Basque',\n\t'et':'Estonian',\n\t'fa':'Persian',\n\t'fr':'French',\n\t'fy-NL':'Frisian',\n\t'ga-IE':'Irish',\n\t'ia':'Interlingua',\n\t'id':'Indonesian',\n\t'it':'Italian',\n\t'ja':'Japanese',\n\t'ka':'Georgian',\n\t'ky':'Kyrgyz',\n\t'lv':'Latvian',\n\t'mn':'Mongolian',\n\t'mt':'Maltese',\n\t'nl':'Dutch',\n\t'or':'Oriya',\n\t'pa-IN':'Punjabi',\n\t'pl':'Polish',\n\t'pt':'Portuguese',\n\t'rm-sursilv':'Sursilvan',\n\t'rm-vallader':'Vallader',\n\t'ro':'Romanian',\n\t'ru':'Russian',\n\t'rw':'Kinyarwanda',\n\t'sah':'Sakha',\n\t'sl':'Slovenian',\n\t'sv-SE':'Swedish',\n\t'ta':'Tamil',\n\t'tr':'Turkish',\n\t'tt':'Tatar',\n\t'uk':'Ukrainian',\n\t'vi':'Vietnamese',\n\t'zh-CN':'Chinese',\n\t'zh-TW':'Chinese'})\n "},{"cell_type":"code","execution_count":134,"metadata":{},"outputs":[],"source":"isocode_to_lang = {'ab':'Abkhaz',\n\t'ar':'Arabic',\n\t'as':'Assamese',\n\t'br':'Breton',\n\t'cnh':'Hakha Chin',\n\t'ca':'Catalan',\n\t'cs':'Czech',\n\t'cv':'Chuvash',\n\t'cy':'Welsh',\n\t'de':'German',\n\t'dv':'Divehi',\n\t'el':'Greek',\n\t'en':'English',\n\t'es':'Spanish',\n\t'eo':'Esperanto',\n\t'eu':'Basque',\n\t'et':'Estonian',\n\t'fa':'Persian',\n\t'fr':'French',\n\t'fy-NL':'Frisian',\n\t'ga-IE':'Irish',\n\t'ia':'Interlingua',\n\t'id':'Indonesian',\n\t'it':'Italian',\n\t'ja':'Japanese',\n\t'ka':'Georgian',\n\t'ky':'Kyrgyz',\n\t'lv':'Latvian',\n\t'mn':'Mongolian',\n\t'mt':'Maltese',\n\t'nl':'Dutch',\n\t'or':'Oriya',\n\t'pa-IN':'Punjabi',\n\t'pl':'Polish',\n\t'pt':'Portuguese',\n\t'rm-sursilv':'Sursilvan',\n\t'rm-vallader':'Vallader',\n\t'ro':'Romanian',\n\t'ru':'Russian',\n\t'rw':'Kinyarwanda',\n\t'sah':'Sakha',\n\t'sl':'Slovenian',\n\t'sv-SE':'Swedish',\n\t'ta':'Tamil',\n\t'tr':'Turkish',\n\t'tt':'Tatar',\n\t'uk':'Ukrainian',\n\t'vi':'Vietnamese',\n\t'zh-CN':'Chinese',\n\t'zh-TW':'Chinese'}"},{"cell_type":"code","execution_count":135,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" 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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df = language_fractions_df.rename(isocode_to_lang, axis=1)\n\nlanguage_fractions_df_T = language_fractions_df.transpose()[wl15]\nlanguage_fractions_df_T.nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Percentage of Audio Clips\", xlabel='Word Length', title='Percentage of Audio Clips by Word Length (limited upto 15) for top 10 languages')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\n# plt.savefig('plots/stacked/percent_audio_clips_by_word_length_vs_word_length_top10.png')"},{"cell_type":"code","execution_count":138,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":138},{"output_type":"display_data","data":{"text/plain":"
","image/svg+xml":"\n\n\n \n \n \n \n 2021-08-06T18:52:44.991817\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df = language_fractions_df.rename(isocode_to_lang, axis=1)\n\nlanguage_fractions_df_T = language_fractions_df.transpose()[wl15]\nlanguage_fractions_df_T.nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Percentage of Audio Clips\", xlabel='Word Length', title='Percentage of Audio Clips by Word Length (1-15) for top 1-10 languages')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\n# plt.savefig('plots/stacked/percent_audio_clips_by_word_length_vs_word_length_top1-10.png')"},{"cell_type":"code","execution_count":139,"metadata":{},"outputs":[{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_df.transpose()[wl15]\nlanguage_fractions_df_T.nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Percentage of Audio Clips\", xlabel='Word Length', title='Percentage of Audio Clips by Word Length (1 to 15) for top (1 to 10) languages')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\nplt.savefig('plots/stacked/percent_audio_clips_by_word_length_vs_word_length_top1-10.png')"},{"cell_type":"code","execution_count":140,"metadata":{},"outputs":[{"output_type":"error","ename":"SyntaxError","evalue":"invalid syntax (1083522907.py, line 2)","traceback":["\u001b[0;36m File \u001b[0;32m\"/tmp/ipykernel_11406/1083522907.py\"\u001b[0;36m, line \u001b[0;32m2\u001b[0m\n\u001b[0;31m language_fractions_df_T.nsmallest(40,3).nlargest(10, 3)..transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Percentage of Audio Clips\", xlabel='Word Length', title='Percentage of Audio Clips by Word Length (1 to 15) for top (11 to 20) languages')\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"]}],"source":"language_fractions_df_T = language_fractions_df.transpose()[wl15]\nlanguage_fractions_df_T.nsmallest(40,3).nlargest(10, 3)..transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Percentage of Audio Clips\", xlabel='Word Length', title='Percentage of Audio Clips by Word Length (1 to 15) for top (11 to 20) languages')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\n# plt.savefig('plots/stacked/percent_audio_clips_by_word_length_vs_word_length_top1-10.png')"},{"cell_type":"code","execution_count":141,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":141},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_df.transpose()[wl15]\nlanguage_fractions_df_T.nsmallest(40,3).nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Percentage of Audio Clips\", xlabel='Word Length', title='Percentage of Audio Clips by Word Length (1 to 15) for top (11 to 20) languages')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\n# plt.savefig('plots/stacked/percent_audio_clips_by_word_length_vs_word_length_top1-10.png')"},{"cell_type":"code","execution_count":142,"metadata":{},"outputs":[{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_df.transpose()[wl15]\nlanguage_fractions_df_T.nsmallest(40,3).nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Percentage of Audio Clips\", xlabel='Word Length', title='Percentage of Audio Clips by Word Length (1 to 15) for top (11 to 20) languages')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\nplt.savefig('plots/stacked/percent_audio_clips_by_word_length_vs_word_length_top11-20.png')"},{"cell_type":"code","execution_count":143,"metadata":{},"outputs":[{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_df.transpose()[wl15]\nlanguage_fractions_df_T.nsmallest(30,3).nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Percentage of Audio Clips\", xlabel='Word Length', title='Percentage of Audio Clips by Word Length (1 to 15) for top (21 to 30) languages')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\nplt.savefig('plots/stacked/percent_audio_clips_by_word_length_vs_word_length_top21-30.png')"},{"cell_type":"code","execution_count":144,"metadata":{},"outputs":[{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_df.transpose()[wl15]\nlanguage_fractions_df_T.nsmallest(20,3).nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Percentage of Audio Clips\", xlabel='Word Length', title='Percentage of Audio Clips by Word Length (1 to 15) for top (31 to 40) languages')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\nplt.savefig('plots/stacked/percent_audio_clips_by_word_length_vs_word_length_top31-40.png')"},{"cell_type":"code","execution_count":145,"metadata":{},"outputs":[{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_df.transpose()[wl15]\nlanguage_fractions_df_T.nsmallest(10,3).nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Percentage of Audio Clips\", xlabel='Word Length', title='Percentage of Audio Clips by Word Length (1 to 15) for top (41 to 50) languages')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\nplt.savefig('plots/stacked/percent_audio_clips_by_word_length_vs_word_length_top41-50.png')"},{"cell_type":"code","execution_count":146,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["{3: 936,\n"," 4: 2786,\n"," 5: 4616,\n"," 6: 6156,\n"," 7: 6585,\n"," 9: 4882,\n"," 10: 3402,\n"," 8: 5952,\n"," 13: 640,\n"," 11: 2066,\n"," 12: 1157,\n"," 14: 251,\n"," 15: 120,\n"," 16: 14,\n"," 17: 3,\n"," 18: 1}"]},"metadata":{},"execution_count":146}],"source":"wordlengths"},{"cell_type":"code","execution_count":147,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0.5, 1.0, \"Number of Keywords v/s Word Length for 'en\")"]},"metadata":{},"execution_count":147},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"sub_df = main_data[main_data['language']=='en']\nwords = sub_df['word'].unique().tolist()\n\nwordlengths_2 = {}\nfor w in words:\n if type(w) == str:\n if len(w) in wordlengths_2:\n wordlengths_2[len(w)] += 1\n else:\n wordlengths_2[len(w)] = 1\n\nfig, ax = plt.subplots(figsize=(8,8))\nax.bar(wordlengths_2.keys(), wordlengths_2.values())\nax.set_xlabel(\"Word Length\")\nax.set_ylabel(\"Number of Keywords\")\nax.set_title(f\"Number of Keywords v/s Word Length for 'en\")"},{"cell_type":"code","execution_count":148,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" word\n","counts \n","5 3794\n","6 2700\n","7 2502\n","8 2049\n","9 1668\n","... ...\n","69139 1\n","80814 1\n","100463 1\n","131469 1\n","150846 1\n","\n","[1787 rows x 1 columns]"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
word
counts
53794
62700
72502
82049
91668
......
691391
808141
1004631
1314691
1508461
\n

1787 rows × 1 columns

\n
"},"metadata":{},"execution_count":148}],"source":"main_data[main_data['language']=='en'][['counts','word']].groupby('counts').count()"},{"cell_type":"code","execution_count":149,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":149},{"output_type":"stream","name":"stdout","text":["Error in callback (for post_execute):\n"]},{"output_type":"error","ename":"KeyboardInterrupt","evalue":"","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/matplotlib_inline/backend_inline.py\u001b[0m in \u001b[0;36mflush_figures\u001b[0;34m()\u001b[0m\n\u001b[1;32m 119\u001b[0m \u001b[0;31m# ignore the tracking, just draw and close all figures\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 120\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 121\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 122\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 123\u001b[0m \u001b[0;31m# safely show traceback if in IPython, else raise\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/matplotlib_inline/backend_inline.py\u001b[0m in \u001b[0;36mshow\u001b[0;34m(close, block)\u001b[0m\n\u001b[1;32m 39\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 40\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mfigure_manager\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mGcf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_all_fig_managers\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 41\u001b[0;31m display(\n\u001b[0m\u001b[1;32m 42\u001b[0m \u001b[0mfigure_manager\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 43\u001b[0m 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over)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/IPython/core/formatters.py\u001b[0m in \u001b[0;36mformat\u001b[0;34m(self, obj, include, exclude)\u001b[0m\n\u001b[1;32m 178\u001b[0m \u001b[0mmd\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 179\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 180\u001b[0;31m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mformatter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 181\u001b[0m \u001b[0;32mexcept\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 182\u001b[0m \u001b[0;31m# FIXME: log the 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call\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 223\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 224\u001b[0;31m \u001b[0mr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 225\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mNotImplementedError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 226\u001b[0m \u001b[0;31m# don't warn on NotImplementedErrors\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/IPython/core/formatters.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m 339\u001b[0m \u001b[0;32mpass\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 340\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 341\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mprinter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 342\u001b[0m \u001b[0;31m# Finally look for special method names\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 343\u001b[0m \u001b[0mmethod\u001b[0m \u001b[0;34m=\u001b[0m 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for_layout_only=for_layout_only)\n\u001b[1;32m 4439\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/matplotlib/axis.py\u001b[0m in \u001b[0;36mget_tightbbox\u001b[0;34m(self, renderer, for_layout_only)\u001b[0m\n\u001b[1;32m 1081\u001b[0m \u001b[0mticks_to_draw\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_update_ticks\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1082\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1083\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_update_label_position\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1084\u001b[0m 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label1's and label2's.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1063\u001b[0;31m return ([tick.label1.get_window_extent(renderer)\n\u001b[0m\u001b[1;32m 1064\u001b[0m for tick in ticks if tick.label1.get_visible()],\n\u001b[1;32m 1065\u001b[0m [tick.label2.get_window_extent(renderer)\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/matplotlib/axis.py\u001b[0m in \u001b[0;36m\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 1061\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_get_tick_bboxes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mticks\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1062\u001b[0m \u001b[0;34m\"\"\"Return lists of bboxes for ticks' label1's and label2's.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1063\u001b[0;31m return ([tick.label1.get_window_extent(renderer)\n\u001b[0m\u001b[1;32m 1064\u001b[0m for tick in ticks if tick.label1.get_visible()],\n\u001b[1;32m 1065\u001b[0m [tick.label2.get_window_extent(renderer)\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/matplotlib/text.py\u001b[0m in \u001b[0;36mget_window_extent\u001b[0;34m(self, renderer, dpi)\u001b[0m\n\u001b[1;32m 901\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 902\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mcbook\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_setattr_cm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdpi\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdpi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 903\u001b[0;31m \u001b[0mbbox\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minfo\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdescent\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_layout\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_renderer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 904\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_unitless_position\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 905\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_transform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtransform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/matplotlib/text.py\u001b[0m in \u001b[0;36m_get_layout\u001b[0;34m(self, renderer)\u001b[0m\n\u001b[1;32m 304\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 305\u001b[0m \u001b[0;31m# Full vertical extent of font, including ascenders and descenders:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 306\u001b[0;31m _, lp_h, lp_d = renderer.get_text_width_height_descent(\n\u001b[0m\u001b[1;32m 307\u001b[0m \u001b[0;34m\"lp\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_fontproperties\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 308\u001b[0m ismath=\"TeX\" if self.get_usetex() else False)\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/matplotlib/backends/backend_agg.py\u001b[0m in \u001b[0;36mget_text_width_height_descent\u001b[0;34m(self, s, prop, ismath)\u001b[0m\n\u001b[1;32m 238\u001b[0m \u001b[0mflags\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_hinting_flag\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 239\u001b[0m \u001b[0mfont\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_agg_font\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprop\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 240\u001b[0;31m \u001b[0mfont\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_text\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflags\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mflags\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 241\u001b[0m \u001b[0mw\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mh\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfont\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_width_height\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# width and height of unrotated string\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 242\u001b[0m \u001b[0md\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfont\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_descent\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mKeyboardInterrupt\u001b[0m: "]}],"source":"main_data[main_data['language']=='en'][['counts','word']].groupby('counts').count().plot(kind='bar')"},{"cell_type":"code","execution_count":150,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" word\n","counts \n","5 3794\n","6 2700\n","7 2502\n","8 2049\n","9 1668\n","... ...\n","69139 1\n","80814 1\n","100463 1\n","131469 1\n","150846 1\n","\n","[1787 rows x 1 columns]"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
word
counts
53794
62700
72502
82049
91668
......
691391
808141
1004631
1314691
1508461
\n

1787 rows × 1 columns

\n
"},"metadata":{},"execution_count":150}],"source":"main_data[main_data['language']=='en'][['counts','word']].groupby('counts').count()"},{"cell_type":"code","execution_count":151,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" counts word\n","0 5 3794\n","1 6 2700\n","2 7 2502\n","3 8 2049\n","4 9 1668\n","... ... ...\n","1782 69139 1\n","1783 80814 1\n","1784 100463 1\n","1785 131469 1\n","1786 150846 1\n","\n","[1787 rows x 2 columns]"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
countsword
053794
162700
272502
382049
491668
.........
1782691391
1783808141
17841004631
17851314691
17861508461
\n

1787 rows × 2 columns

\n
"},"metadata":{},"execution_count":151}],"source":"main_data[main_data['language']=='en'][['counts','word']].groupby('counts').count().reset_index()"},{"cell_type":"code","execution_count":152,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" counts word\n","0 5 3794\n","1 6 2700\n","2 7 2502\n","3 8 2049\n","4 9 1668\n","... ... ...\n","1782 69139 1\n","1783 80814 1\n","1784 100463 1\n","1785 131469 1\n","1786 150846 1\n","\n","[1787 rows x 2 columns]"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
countsword
053794
162700
272502
382049
491668
.........
1782691391
1783808141
17841004631
17851314691
17861508461
\n

1787 rows × 2 columns

\n
"},"metadata":{},"execution_count":152}],"source":"main_data[main_data['language']=='en'][['counts','word']].groupby('counts').count().reset_index().rename({'counts':'Number Of Extractions','word':'Number of Keywords'})"},{"cell_type":"code","execution_count":153,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" Number Of Extractions Number of Keywords\n","0 5 3794\n","1 6 2700\n","2 7 2502\n","3 8 2049\n","4 9 1668\n","... ... ...\n","1782 69139 1\n","1783 80814 1\n","1784 100463 1\n","1785 131469 1\n","1786 150846 1\n","\n","[1787 rows x 2 columns]"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Number Of ExtractionsNumber of Keywords
053794
162700
272502
382049
491668
.........
1782691391
1783808141
17841004631
17851314691
17861508461
\n

1787 rows × 2 columns

\n
"},"metadata":{},"execution_count":153}],"source":"main_data[main_data['language']=='en'][['counts','word']].groupby('counts').count().reset_index().rename({'counts':'Number Of Extractions','word':'Number of Keywords'}, axis=1)"},{"cell_type":"code","execution_count":154,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":154},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"main_data[main_data['language']=='en'][['counts','word']].groupby('counts').count().reset_index().rename({'counts':'Number Of Extractions','word':'Number of Keywords'}, axis=1).plot.hist(bins=20)"},{"cell_type":"code","execution_count":155,"metadata":{},"outputs":[],"source":"# main_data[main_data['language']=='en'][['counts','word']].groupby('counts').count().reset_index().rename({'counts':'Number Of Extractions','word':'Number of Keywords'}, axis=1).plot(kind='bar',)"},{"cell_type":"code","execution_count":156,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":156},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"main_data[main_data['language']=='en'][['counts','word']].plot.hist(bins=20)"},{"cell_type":"code","execution_count":157,"metadata":{},"outputs":[{"output_type":"error","ename":"TypeError","evalue":"no numeric data to plot","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mmain_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'language'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;34m'en'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'word'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbins\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m20\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36mhist\u001b[0;34m(self, by, bins, **kwargs)\u001b[0m\n\u001b[1;32m 1311\u001b[0m \u001b[0;34m>>\u001b[0m\u001b[0;34m>\u001b[0m \u001b[0max\u001b[0m \u001b[0;34m=\u001b[0m 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\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_compute_plot_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 287\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_setup_subplots\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 288\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_plot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/plotting/_matplotlib/core.py\u001b[0m in \u001b[0;36m_compute_plot_data\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 451\u001b[0m \u001b[0;31m# no non-numeric frames or series allowed\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 452\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_empty\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 453\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"no numeric data to plot\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 454\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 455\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnumeric_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_convert_to_ndarray\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mTypeError\u001b[0m: no numeric data to plot"]}],"source":"main_data[main_data['language']=='en'][['word']].plot.hist(bins=20)"},{"cell_type":"code","execution_count":158,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":158},{"output_type":"display_data","data":{"text/plain":"
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Number Of Extractions Number of Keywords\n","0 5 3794\n","1 6 2700\n","2 7 2502\n","3 8 2049\n","4 9 1668\n","... ... ...\n","1782 69139 1\n","1783 80814 1\n","1784 100463 1\n","1785 131469 1\n","1786 150846 1\n","\n","[1787 rows x 2 columns]"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Number Of ExtractionsNumber of Keywords
053794
162700
272502
382049
491668
.........
1782691391
1783808141
17841004631
17851314691
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1787 rows × 2 columns

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"},"metadata":{},"execution_count":159}],"source":"main_data[main_data['language']=='en'][['counts','word']].groupby('counts').count().reset_index().rename({'counts':'Number Of Extractions','word':'Number of Keywords'}, axis=1)"},{"cell_type":"code","execution_count":160,"metadata":{},"outputs":[],"source":"plot1_df = main_data[main_data['language']=='en'][['counts','word']].groupby('counts').count().reset_index().rename({'counts':'Number Of Extractions','word':'Number of Keywords'}, axis=1)"},{"cell_type":"code","execution_count":161,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":161},{"output_type":"display_data","data":{"text/plain":"
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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n"},"metadata":{"needs_background":"light"}}],"source":"# plot1_df['Number of Keywords'] = np.log(plot1_df['Number of Keywords'])\nplot1_df.plot(x='Number of Keywords',y='Number Of Extractions',kind='bar')"},{"cell_type":"code","execution_count":162,"metadata":{},"outputs":[{"output_type":"error","ename":"KeyError","evalue":"'Number of Extractions'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3360\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3361\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3362\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n","\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n","\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: 'Number of Extractions'","\nThe above exception was the direct cause of the following exception:\n","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mplot1_df_1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Number of Extractions'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mplot1_df\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Number of Extractions'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mplot1_df_1\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Number of Keywords'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Number Of Extractions'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'bar'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3453\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlevels\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3454\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3455\u001b[0;31m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3456\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3457\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3361\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3362\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3363\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3364\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3365\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_scalar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0misna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhasnans\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: 'Number of Extractions'"]}],"source":"plot1_df_1['Number of Extractions'] = np.log(plot1_df['Number of Extractions'])\nplot1_df_1.plot(x='Number of Keywords',y='Number Of Extractions',kind='bar')"},{"cell_type":"code","execution_count":163,"metadata":{},"outputs":[{"output_type":"error","ename":"KeyError","evalue":"'Number of Extractions'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3360\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3361\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3362\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n","\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n","\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: 'Number of Extractions'","\nThe above exception was the direct cause of the following exception:\n","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mplot1_df_1\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplot1_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mplot1_df_1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Number of Extractions'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mplot1_df\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Number of Extractions'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0mplot1_df_1\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Number of Keywords'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Number Of Extractions'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'bar'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3453\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlevels\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3454\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3455\u001b[0;31m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3456\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3457\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3361\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3362\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3363\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3364\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3365\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_scalar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0misna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhasnans\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: 'Number of Extractions'"]}],"source":"plot1_df_1 = plot1_df.copy()\nplot1_df_1['Number of Extractions'] = np.log(plot1_df['Number of Extractions'])\nplot1_df_1.plot(x='Number of Keywords',y='Number Of Extractions',kind='bar')"},{"cell_type":"code","execution_count":164,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" Number Of Extractions Number of Keywords\n","0 5 3794\n","1 6 2700\n","2 7 2502\n","3 8 2049\n","4 9 1668\n","... ... ...\n","1782 69139 1\n","1783 80814 1\n","1784 100463 1\n","1785 131469 1\n","1786 150846 1\n","\n","[1787 rows x 2 columns]"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Number Of ExtractionsNumber of Keywords
053794
162700
272502
382049
491668
.........
1782691391
1783808141
17841004631
17851314691
17861508461
\n

1787 rows × 2 columns

\n
"},"metadata":{},"execution_count":164}],"source":"plot1_df"},{"cell_type":"code","execution_count":165,"metadata":{},"outputs":[{"output_type":"error","ename":"KeyError","evalue":"'Number of Extractions'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3360\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3361\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3362\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n","\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n","\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: 'Number of Extractions'","\nThe above exception was the direct cause of the following exception:\n","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mplot1_df_1\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplot1_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mplot1_df_1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Number of Extractions'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mplot1_df_1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Number of Extractions'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0mplot1_df_1\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Number of Keywords'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Number Of Extractions'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'bar'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3453\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlevels\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3454\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3455\u001b[0;31m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3456\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3457\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3361\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3362\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3363\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3364\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3365\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_scalar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0misna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhasnans\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: 'Number of Extractions'"]}],"source":"plot1_df_1 = plot1_df.copy()\nplot1_df_1['Number of Extractions'] = np.log(plot1_df_1['Number of Extractions'])\nplot1_df_1.plot(x='Number of Keywords',y='Number Of Extractions',kind='bar')"},{"cell_type":"code","execution_count":166,"metadata":{},"outputs":[{"output_type":"error","ename":"KeyError","evalue":"'Number of Extractions'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3360\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3361\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3362\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n","\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n","\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: 'Number of Extractions'","\nThe above exception was the direct cause of the following exception:\n","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mplot1_df_1\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplot1_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mplot1_df_1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Number of Extractions'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mplot1_df_1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Number of Extractions'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0mplot1_df_1\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Number of Keywords'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Number Of Extractions'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'bar'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3453\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlevels\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3454\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3455\u001b[0;31m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3456\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3457\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3361\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3362\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3363\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3364\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3365\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_scalar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0misna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhasnans\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: 'Number of Extractions'"]}],"source":"plot1_df_1 = plot1_df.copy()\nplot1_df_1['Number of Extractions'] = np.log(plot1_df_1['Number of Extractions'])\nplot1_df_1.plot(x='Number of Keywords',y='Number Of Extractions',kind='bar')"},{"cell_type":"code","execution_count":167,"metadata":{},"outputs":[{"output_type":"error","ename":"KeyError","evalue":"'Number of Extractions'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3360\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3361\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3362\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n","\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n","\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: 'Number of Extractions'","\nThe above exception was the direct cause of the following exception:\n","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mplot1_df_1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Number of Extractions'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3453\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlevels\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3454\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3455\u001b[0;31m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3456\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3457\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3361\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3362\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3363\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3364\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3365\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_scalar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0misna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhasnans\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: 'Number of Extractions'"]}],"source":"plot1_df_1['Number of Extractions']"},{"cell_type":"code","execution_count":168,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["Index(['Number Of Extractions', 'Number of Keywords'], dtype='object')"]},"metadata":{},"execution_count":168}],"source":"plot1_df_1.columns"},{"cell_type":"code","execution_count":169,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":169},{"output_type":"display_data","data":{"text/plain":"
","image/svg+xml":"\n\n\n \n \n \n \n 2021-08-06T19:18:48.776511\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n"},"metadata":{"needs_background":"light"}}],"source":"plot1_df_1 = plot1_df.copy()\nplot1_df_1['Number Of Extractions'] = np.log(plot1_df_1['Number Of Extractions'])\nplot1_df_1.plot(x='Number of Keywords',y='Number Of Extractions',kind='bar')"},{"cell_type":"code","execution_count":170,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" Number Of Extractions Number of Keywords\n","0 5 3794\n","1 6 2700\n","2 7 2502\n","3 8 2049\n","4 9 1668\n","... ... ...\n","1782 69139 1\n","1783 80814 1\n","1784 100463 1\n","1785 131469 1\n","1786 150846 1\n","\n","[1787 rows x 2 columns]"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Number Of ExtractionsNumber of Keywords
053794
162700
272502
382049
491668
.........
1782691391
1783808141
17841004631
17851314691
17861508461
\n

1787 rows × 2 columns

\n
"},"metadata":{},"execution_count":170}],"source":"plot1_df"},{"cell_type":"code","execution_count":171,"metadata":{},"outputs":[{"output_type":"error","ename":"AttributeError","evalue":"'Series' object has no attribute 'log'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mplot1_df\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Number Of Extractions'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m 5476\u001b[0m ):\n\u001b[1;32m 5477\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5478\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mobject\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__getattribute__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 5479\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5480\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mAttributeError\u001b[0m: 'Series' object has no attribute 'log'"]}],"source":"plot1_df['Number Of Extractions'].log()"},{"cell_type":"code","execution_count":172,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["0 5\n","1 6\n","2 7\n","3 8\n","4 9\n"," ... \n","1782 69139\n","1783 80814\n","1784 100463\n","1785 131469\n","1786 150846\n","Name: Number Of Extractions, Length: 1787, dtype: int64"]},"metadata":{},"execution_count":172}],"source":"plot1_df['Number Of Extractions']"},{"cell_type":"code","execution_count":173,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["0 1.609438\n","1 1.791759\n","2 1.945910\n","3 2.079442\n","4 2.197225\n"," ... \n","1782 11.143874\n","1783 11.299905\n","1784 11.517545\n","1785 11.786526\n","1786 11.924015\n","Name: Number Of Extractions, Length: 1787, dtype: float64"]},"metadata":{},"execution_count":173}],"source":"np.log(plot1_df['Number Of Extractions'])"},{"cell_type":"code","execution_count":174,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([ 1.60943791, 1.79175947, 1.94591015, ..., 11.51754478,\n"," 11.78652636, 11.92401473])"]},"metadata":{},"execution_count":174}],"source":"np.log(plot1_df['Number Of Extractions']).values"},{"cell_type":"code","execution_count":175,"metadata":{},"outputs":[{"output_type":"error","ename":"SyntaxError","evalue":"unmatched ')' (1486778956.py, line 1)","traceback":["\u001b[0;36m File \u001b[0;32m\"/tmp/ipykernel_11406/1486778956.py\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m plt.bar(plot1_df['Number Of Keywords']).values, np.log(plot1_df['Number Of Extractions']).values)\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m unmatched ')'\n"]}],"source":"plt.bar(plot1_df['Number Of Keywords']).values, np.log(plot1_df['Number Of Extractions']).values)"},{"cell_type":"code","execution_count":176,"metadata":{},"outputs":[{"output_type":"error","ename":"SyntaxError","evalue":"unexpected EOF while parsing (963881844.py, line 1)","traceback":["\u001b[0;36m File \u001b[0;32m\"/tmp/ipykernel_11406/963881844.py\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m plt.bar(plot1_df['Number Of Keywords'].values, np.log(plot1_df['Number Of Extractions'].values)\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m unexpected EOF while parsing\n"]}],"source":"plt.bar(plot1_df['Number Of Keywords'].values, np.log(plot1_df['Number Of Extractions'].values)"},{"cell_type":"code","execution_count":177,"metadata":{},"outputs":[{"output_type":"error","ename":"KeyError","evalue":"'Number Of Keywords'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3360\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3361\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3362\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n","\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n","\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: 'Number Of Keywords'","\nThe above exception was the direct cause of the following exception:\n","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mplot1_df\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Number Of Keywords'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mplot1_df\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Number Of Extractions'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3453\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlevels\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3454\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3455\u001b[0;31m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3456\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3457\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3361\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3362\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3363\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3364\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3365\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_scalar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0misna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhasnans\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: 'Number Of Keywords'"]}],"source":"plt.bar(plot1_df['Number Of Keywords'].values, np.log(plot1_df['Number Of Extractions']).values)"},{"cell_type":"code","execution_count":178,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":178},{"output_type":"display_data","data":{"text/plain":"
","image/svg+xml":"\n\n\n \n \n \n \n 2021-08-06T19:27:54.447965\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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e":"plt.bar(plot1_df['Number of Keywords'].values, np.log(plot1_df['Number Of Extractions']).values)"},{"cell_type":"code","execution_count":179,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":179},{"output_type":"display_data","data":{"text/plain":"
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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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of Keywords'].values, np.log(plot1_df['Number Of Extractions']).values, width=100)"},{"cell_type":"code","execution_count":180,"metadata":{},"outputs":[{"output_type":"error","ename":"AttributeError","evalue":"'Line2D' object has no property 'width'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mplot1_df_1\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Number of Keywords'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Number Of Extractions'\u001b[0m\u001b[0;34m,\u001b[0m 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\u001b[0mkw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 354\u001b[0;31m \u001b[0mseg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmlines\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mLine2D\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 355\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mseg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkw\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 356\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/matplotlib/lines.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, xdata, ydata, linewidth, linestyle, color, marker, markersize, markeredgewidth, markeredgecolor, markerfacecolor, markerfacecoloralt, fillstyle, antialiased, dash_capstyle, solid_capstyle, dash_joinstyle, solid_joinstyle, pickradius, drawstyle, markevery, **kwargs)\u001b[0m\n\u001b[1;32m 395\u001b[0m \u001b[0;31m# update kwargs before updating data to give the caller a\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 396\u001b[0m \u001b[0;31m# chance to init axes (and hence unit support)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 397\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 398\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpickradius\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpickradius\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 399\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mind_offset\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/matplotlib/artist.py\u001b[0m in \u001b[0;36mupdate\u001b[0;34m(self, props)\u001b[0m\n\u001b[1;32m 1060\u001b[0m \u001b[0mfunc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34mf\"set_{k}\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1061\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mcallable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfunc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1062\u001b[0;31m raise AttributeError(f\"{type(self).__name__!r} object \"\n\u001b[0m\u001b[1;32m 1063\u001b[0m f\"has no property {k!r}\")\n\u001b[1;32m 1064\u001b[0m \u001b[0mret\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mAttributeError\u001b[0m: 'Line2D' object has no property 'width'"]}],"source":"plot1_df_1.plot(x='Number of Keywords', y='Number Of Extractions', width=100)"},{"cell_type":"code","execution_count":181,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":181},{"output_type":"display_data","data":{"text/plain":"
","image/svg+xml":"\n\n\n \n \n \n \n 2021-08-06T19:29:39.981170\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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of Keywords', y='Number Of Extractions', kind='bar',width=100)"},{"cell_type":"code","execution_count":182,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" Number Of Extractions Number of Keywords\n","0 1.609438 3794\n","1 1.791759 2700\n","2 1.945910 2502\n","3 2.079442 2049\n","4 2.197225 1668\n","... ... ...\n","1782 11.143874 1\n","1783 11.299905 1\n","1784 11.517545 1\n","1785 11.786526 1\n","1786 11.924015 1\n","\n","[1787 rows x 2 columns]"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Number Of ExtractionsNumber of Keywords
01.6094383794
11.7917592700
21.9459102502
32.0794422049
42.1972251668
.........
178211.1438741
178311.2999051
178411.5175451
178511.7865261
178611.9240151
\n

1787 rows × 2 columns

\n
"},"metadata":{},"execution_count":182}],"source":"plot1_df_1"},{"cell_type":"code","execution_count":183,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":183},{"output_type":"display_data","data":{"text/plain":"
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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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of Keywords'].values, np.log(plot1_df['Number Of Extractions']).values, width=150)"},{"cell_type":"code","execution_count":185,"metadata":{},"outputs":[{"output_type":"error","ename":"SyntaxError","evalue":"positional argument follows keyword argument (3869988660.py, line 3)","traceback":["\u001b[0;36m File \u001b[0;32m\"/tmp/ipykernel_11406/3869988660.py\"\u001b[0;36m, line \u001b[0;32m3\u001b[0m\n\u001b[0;31m ax.bar(plot1_df['Number of Keywords'].values, plot1_df['Number Of Extractions'].values, width=150, yticks)\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m positional argument follows keyword argument\n"]}],"source":"fig, ax = plt.subplots(figsize=(10,10))\n\nax.bar(plot1_df['Number of Keywords'].values, plot1_df['Number Of Extractions'].values, width=150, yticks)\nax.set_yscale('log')"},{"cell_type":"code","execution_count":186,"metadata":{},"outputs":[{"output_type":"display_data","data":{"text/plain":"
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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n"},"metadata":{"needs_background":"light"}}],"source":"fig, ax = plt.subplots(figsize=(10,10))\n\nax.bar(plot1_df['Number of Keywords'].values, plot1_df['Number Of Extractions'].values, width=150)\nax.set_yscale('log')"},{"cell_type":"code","execution_count":187,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0, 0.5, 'Number of Extractions')"]},"metadata":{},"execution_count":187},{"output_type":"display_data","data":{"text/plain":"
","image/svg+xml":"\n\n\n \n \n \n \n 2021-08-06T19:37:36.880826\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n"},"metadata":{"needs_background":"light"}}],"source":"fig, ax = plt.subplots(figsize=(10,10))\n\nax.bar(plot1_df['Number of Keywords'].values, plot1_df['Number Of Extractions'].values, width=500)\nax.set_yscale('log')\nax.set_xlabel(\"Number of Keywords\")\nax.set_ylabel(\"Number of Extractions\")"},{"cell_type":"code","execution_count":188,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0, 0.5, 'Number of Extractions')"]},"metadata":{},"execution_count":188},{"output_type":"display_data","data":{"text/plain":"
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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n"},"metadata":{"needs_background":"light"}}],"source":"fig, ax = plt.subplots(figsize=(10,10))\n\nax.bar(plot1_df['Number of Keywords'].values, plot1_df['Number Of Extractions'].values)\nax.set_yscale('log')\nax.set_xlabel(\"Number of Keywords\")\nax.set_ylabel(\"Number of Extractions\")"},{"cell_type":"code","execution_count":189,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" Number Of Extractions Number of Keywords\n","0 5 3794\n","1 6 2700\n","2 7 2502\n","3 8 2049\n","4 9 1668\n","... ... ...\n","1782 69139 1\n","1783 80814 1\n","1784 100463 1\n","1785 131469 1\n","1786 150846 1\n","\n","[1787 rows x 2 columns]"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Number Of ExtractionsNumber of Keywords
053794
162700
272502
382049
491668
.........
1782691391
1783808141
17841004631
17851314691
17861508461
\n

1787 rows × 2 columns

\n
"},"metadata":{},"execution_count":189}],"source":"plot1_df"},{"cell_type":"code","execution_count":190,"metadata":{},"outputs":[{"output_type":"error","ename":"TypeError","evalue":"'int' object is not iterable","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0msomething\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mplot1_df\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0msomething\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mextend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mplot1_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0miloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'Number of Keywords'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mplot1_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0miloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'Number Of Extractions'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mTypeError\u001b[0m: 'int' object is not iterable"]}],"source":"something = []\nfor i in len(plot1_df):\n something.extend([plot1_df.iloc[i,'Number of Keywords']]*plot1_df.iloc[i,'Number Of Extractions'])"},{"cell_type":"code","execution_count":191,"metadata":{},"outputs":[{"output_type":"error","ename":"ValueError","evalue":"Location based indexing can only have [integer, integer slice (START point is INCLUDED, END point is EXCLUDED), listlike of integers, boolean array] types","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_has_valid_tuple\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 753\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 754\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_key\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 755\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_validate_key\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1425\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1426\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"Can only index by location with a [{self._valid_types}]\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1427\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mValueError\u001b[0m: Can only index by location with a [integer, integer slice (START point is INCLUDED, END point is EXCLUDED), listlike of integers, boolean array]","\nThe above exception was the direct cause of the following exception:\n","\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0msomething\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mplot1_df\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0msomething\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mextend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mplot1_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0miloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'Number of Keywords'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mplot1_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0miloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'Number Of Extractions'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 923\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0msuppress\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mKeyError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mIndexError\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 924\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_value\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtakeable\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_takeable\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 925\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 926\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 927\u001b[0m \u001b[0;31m# we by definition only have the 0th axis\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1504\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtup\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mtuple\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1505\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1506\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_has_valid_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtup\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1507\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0msuppress\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mIndexingError\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1508\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_lowerdim\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtup\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_has_valid_tuple\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 754\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_key\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 755\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 756\u001b[0;31m raise ValueError(\n\u001b[0m\u001b[1;32m 757\u001b[0m \u001b[0;34m\"Location based indexing can only have \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 758\u001b[0m \u001b[0;34mf\"[{self._valid_types}] types\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mValueError\u001b[0m: Location based indexing can only have [integer, integer slice (START point is INCLUDED, END point is EXCLUDED), listlike of integers, boolean array] types"]}],"source":"something = []\nfor i in range(len(plot1_df)):\n something.extend([plot1_df.iloc[i,'Number of Keywords']]*plot1_df.iloc[i,'Number Of Extractions'])"},{"cell_type":"code","execution_count":192,"metadata":{},"outputs":[{"output_type":"error","ename":"ValueError","evalue":"Location based indexing can only have [integer, integer slice (START point is INCLUDED, END point is EXCLUDED), listlike of integers, boolean array] types","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_has_valid_tuple\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 753\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 754\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_key\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 755\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_validate_key\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1425\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1426\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"Can only index by location with a [{self._valid_types}]\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1427\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mValueError\u001b[0m: Can only index by location with a [integer, integer slice (START point is INCLUDED, END point is EXCLUDED), listlike of integers, boolean array]","\nThe above exception was the direct cause of the following exception:\n","\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0msomething\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mplot1_df\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0msomething\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mextend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mplot1_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'Number of Keywords'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mplot1_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0miloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'Number Of Extractions'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 923\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0msuppress\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mKeyError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mIndexError\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 924\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_value\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtakeable\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_takeable\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 925\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 926\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 927\u001b[0m \u001b[0;31m# we by definition only have the 0th axis\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1504\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtup\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mtuple\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1505\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1506\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_has_valid_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtup\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1507\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0msuppress\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mIndexingError\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1508\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_lowerdim\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtup\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_has_valid_tuple\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 754\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_key\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 755\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 756\u001b[0;31m raise ValueError(\n\u001b[0m\u001b[1;32m 757\u001b[0m \u001b[0;34m\"Location based indexing can only have \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 758\u001b[0m \u001b[0;34mf\"[{self._valid_types}] types\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mValueError\u001b[0m: Location based indexing can only have [integer, integer slice (START point is INCLUDED, END point is EXCLUDED), listlike of integers, boolean array] types"]}],"source":"something = []\nfor i in range(len(plot1_df)):\n something.extend([plot1_df.loc[i,'Number of Keywords']]*plot1_df.iloc[i,'Number Of Extractions'])"},{"cell_type":"code","execution_count":193,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" Number Of Extractions Number of Keywords\n","0 5 3794\n","1 6 2700\n","2 7 2502\n","3 8 2049\n","4 9 1668\n","... ... ...\n","1782 69139 1\n","1783 80814 1\n","1784 100463 1\n","1785 131469 1\n","1786 150846 1\n","\n","[1787 rows x 2 columns]"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Number Of ExtractionsNumber of Keywords
053794
162700
272502
382049
491668
.........
1782691391
1783808141
17841004631
17851314691
17861508461
\n

1787 rows × 2 columns

\n
"},"metadata":{},"execution_count":193}],"source":"plot1_df"},{"cell_type":"code","execution_count":194,"metadata":{},"outputs":[],"source":"something = []\nfor i in range(len(plot1_df)):\n something.extend([plot1_df.loc[i,'Number of Keywords']]*plot1_df.loc[i,'Number Of Extractions'])"},{"cell_type":"code","execution_count":195,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["4584131"]},"metadata":{},"execution_count":195}],"source":"len(something)"},{"cell_type":"code","execution_count":196,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["(array([4.583931e+06, 1.190000e+02, 2.500000e+01, 2.100000e+01,\n"," 9.000000e+00, 8.000000e+00, 7.000000e+00, 6.000000e+00,\n"," 0.000000e+00, 5.000000e+00]),\n"," array([1.0000e+00, 3.8030e+02, 7.5960e+02, 1.1389e+03, 1.5182e+03,\n"," 1.8975e+03, 2.2768e+03, 2.6561e+03, 3.0354e+03, 3.4147e+03,\n"," 3.7940e+03]),\n"," )"]},"metadata":{},"execution_count":196},{"output_type":"display_data","data":{"text/plain":"
","image/svg+xml":"\n\n\n \n \n \n \n 2021-08-06T19:43:28.449287\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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1.755430e+05, 5.531300e+04, 2.438200e+04,\n"," 8.208000e+03, 3.179000e+03, 9.460000e+02, 1.740000e+02,\n"," 6.000000e+01, 3.500000e+01]),\n"," array([0. , 0.82411762, 1.64823523, 2.47235285, 3.29647046,\n"," 4.12058808, 4.94470569, 5.76882331, 6.59294092, 7.41705854,\n"," 8.24117615]),\n"," )"]},"metadata":{},"execution_count":197},{"output_type":"display_data","data":{"text/plain":"
","image/svg+xml":"\n\n\n \n \n \n \n 2021-08-06T19:43:45.384379\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n","image/png":"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\n"},"metadata":{"needs_background":"light"}}],"source":"plt.hist(np.log(something))"},{"cell_type":"code","execution_count":198,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["(array([4.583931e+06, 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\n"},"metadata":{"needs_background":"light"}}],"source":"fig, ax = plt.subplots(figsize=(10,10))\nax.hist(something, log=True, bins=20)"},{"cell_type":"code","execution_count":201,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["(array([4.582308e+06, 1.049000e+03, 4.330000e+02, 1.410000e+02,\n"," 3.900000e+01, 1.800000e+01, 4.800000e+01, 1.400000e+01,\n"," 0.000000e+00, 1.300000e+01, 1.200000e+01, 0.000000e+00,\n"," 1.100000e+01, 1.000000e+01, 0.000000e+00, 0.000000e+00,\n"," 0.000000e+00, 9.000000e+00, 0.000000e+00, 0.000000e+00,\n"," 0.000000e+00, 8.000000e+00, 0.000000e+00, 0.000000e+00,\n"," 0.000000e+00, 0.000000e+00, 7.000000e+00, 0.000000e+00,\n"," 6.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n"," 0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n"," 0.000000e+00, 0.000000e+00, 0.000000e+00, 5.000000e+00]),\n"," array([1.000000e+00, 9.582500e+01, 1.906500e+02, 2.854750e+02,\n"," 3.803000e+02, 4.751250e+02, 5.699500e+02, 6.647750e+02,\n"," 7.596000e+02, 8.544250e+02, 9.492500e+02, 1.044075e+03,\n"," 1.138900e+03, 1.233725e+03, 1.328550e+03, 1.423375e+03,\n"," 1.518200e+03, 1.613025e+03, 1.707850e+03, 1.802675e+03,\n"," 1.897500e+03, 1.992325e+03, 2.087150e+03, 2.181975e+03,\n"," 2.276800e+03, 2.371625e+03, 2.466450e+03, 2.561275e+03,\n"," 2.656100e+03, 2.750925e+03, 2.845750e+03, 2.940575e+03,\n"," 3.035400e+03, 3.130225e+03, 3.225050e+03, 3.319875e+03,\n"," 3.414700e+03, 3.509525e+03, 3.604350e+03, 3.699175e+03,\n"," 3.794000e+03]),\n"," )"]},"metadata":{},"execution_count":201},{"output_type":"display_data","data":{"text/plain":"
","image/svg+xml":"\n\n\n \n \n \n \n 2021-08-06T19:47:17.352217\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n"},"metadata":{"needs_background":"light"}}],"source":"fig, ax = plt.subplots(figsize=(10,10))\nax.hist(something, log=True, bins=40)"},{"cell_type":"code","execution_count":202,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0, 0.5, 'Extractions')"]},"metadata":{},"execution_count":202},{"output_type":"display_data","data":{"text/plain":"
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ax = plt.subplots(figsize=(10,10))\nax.hist(something, log=True, bins=40)\nax.set_xlabel(\"Keywords\")\nax.set_ylabel(\"Extractions\")"},{"cell_type":"code","execution_count":203,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" Number Of Extractions Number of Keywords\n","0 5 3794\n","1 6 2700\n","2 7 2502\n","3 8 2049\n","4 9 1668\n","... ... ...\n","1782 69139 1\n","1783 80814 1\n","1784 100463 1\n","1785 131469 1\n","1786 150846 1\n","\n","[1787 rows x 2 columns]"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Number Of ExtractionsNumber of Keywords
053794
162700
272502
382049
491668
.........
1782691391
1783808141
17841004631
17851314691
17861508461
\n

1787 rows × 2 columns

\n
"},"metadata":{},"execution_count":203}],"source":"# something = []\n# for i in range(len(plot1_df)):\n# something.extend([plot1_df.loc[i,'Number of Keywords']]*plot1_df.loc[i,'Number Of Extractions'])\n\n# fig, ax = plt.subplots(figsize=(10,10))\n# ax.hist(something, log=True, bins=40)\n# ax.set_xlabel(\"Keywords\")\n# ax.set_ylabel(\"Extractions\")\nplot1_df"},{"cell_type":"code","execution_count":204,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" counts word\n","0 5 3794\n","1 6 2700\n","2 7 2502\n","3 8 2049\n","4 9 1668\n","... ... ...\n","1782 69139 1\n","1783 80814 1\n","1784 100463 1\n","1785 131469 1\n","1786 150846 1\n","\n","[1787 rows x 2 columns]"],"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
countsword
053794
162700
272502
382049
491668
.........
1782691391
1783808141
17841004631
17851314691
17861508461
\n

1787 rows × 2 columns

\n
"},"metadata":{},"execution_count":204}],"source":"# tdf = main_data[main_data['language']=='en'][['word','counts']].groupby('counts').count().reset_index()\n# something = []\n# for i in range(len(tdf)):\n# something.extend([tdf.loc[i,'Number of Keywords']]*tdf.loc[i,'Number Of Extractions'])\n\n# fig, ax = plt.subplots(figsize=(10,10))\n# ax.hist(something, log=True, bins=40)\n# ax.set_xlabel(\"Keywords\")\n# ax.set_ylabel(\"Extractions\")\n# plot1_df\nmain_data[main_data['language']=='en'][['word','counts']].groupby('counts').count().reset_index()"},{"cell_type":"code","execution_count":205,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0, 0.5, 'Extractions')"]},"metadata":{},"execution_count":205},{"output_type":"display_data","data":{"text/plain":"
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3FV3VVVz62qL07yr5I8Y41zAQDsGzs67UV3f0tVvTLJ+7I6D9m3dPevrXUyAIB9YkdbyKrq6iR/I8nPJ/lgkv+iqv7MOgcDANgvdvqR5ZEk/3N3/1dJ/kqSDyS5Z21TAQDsIzs9U/+13f2xZPV9SUl+qKqOrG8sAID940znIfvbSdLdH6uqbzrh7m9f11AAAPvJmT6yvGHb9dedcN+BczwLAMC+dKYgq1NcP9ltAACehDMFWZ/i+sluAwDwJJxpp/4vraqPZbU17HOn65luP22tkwEA7BOnDbLuvuB8DQIAsF/t9DxkAACsySyDrKoOVtXhra2t0aMAAOzaLIOsu49096GNjY3RowAA7NosgwwAYEkEGQDAYIIMAGAwQQYAMJggAwAYTJABAAwmyAAABhNkAACDCTIAgMEEGQDAYIIMAGAwQQYAMJggAwAYTJABAAwmyAAABhNkAACDCTIAgMEEGQDAYIIMAGCwPRNkVfUXqupNVfVzVfWdo+cBADhf1hpkVXVrVT1WVfefsPxAVT1YVUer6pYk6e4Huvs1Sb45yVeucy4AgL1k3VvIbktyYPuCqrogyRuTXJfkmiQ3VtU1033fkOTOJHeteS4AgD3jwnU+eXffXVVXnLD42iRHu/uhJKmqtyS5PslvdvcdSe6oqjuT/F/rnG2drrjlzrP+mYdf/7I1TAIAzMFag+wULknyoW23H0nywqp6UZKXJ3lqTrOFrKoOJTmUJJdffvnahgQAOF9GBNlJdfevJvnVHTzucJLDSbK5udnrnQoAYP1GHGX5aJLLtt2+dFoGALAvjQiye5JcXVVXVtVFSW5IcseAOQAA9oR1n/bizUnekeT5VfVIVd3U3U8keW2StyV5IMnt3f3+s3zeg1V1eGtr69wPDQBwnq37KMsbT7H8ruzi1BbdfSTJkc3NzZuf7HMAAOwVe+ZM/QAA+5UgAwAYbJZBZh8yAGBJZhlk3X2kuw9tbGyMHgUAYNdmGWQAAEsiyAAABhNkAACDzTLI7NQPACzJLIPMTv0AwJLMMsgAAJZEkAEADCbIAAAGE2QAAIPNMsgcZQkALMksg8xRlgDAkswyyAAAlkSQAQAMJsgAAAYTZAAAg80yyBxlCQAsySyDzFGWAMCSzDLIAACWRJABAAwmyAAABrtw9ACsXHHLnWf1+Idf/7I1TQIAnG+2kAEADCbIAAAGm2WQOQ8ZALAkswwy5yEDAJZklkEGALAkggwAYDBBBgAwmCADABhMkAEADCbIAAAGE2QAAIMJMgCAwQQZAMBgswwyX50EACzJLIPMVycBAEsyyyADAFgSQQYAMJggAwAYTJABAAwmyAAABhNkAACDCTIAgMEEGQDAYIIMAGAwQQYAMJggAwAYTJABAAw2yyCrqoNVdXhra2v0KAAAuzbLIOvuI919aGNjY/QoAAC7NssgAwBYEkEGADCYIAMAGEyQAQAMJsgAAAYTZAAAgwkyAIDBBBkAwGCCDABgMEEGADCYIAMAGOzC0QPw5Fxxy51n/TMPv/5la5gEANgtW8gAAAYTZAAAgwkyAIDBBBkAwGCCDABgMEEGADCYIAMAGGxPnYesqr4xycuSPDPJj3f3L46dCABg/da+hayqbq2qx6rq/hOWH6iqB6vqaFXdkiTd/U+6++Ykr0nyynXPBgCwF5yPjyxvS3Jg+4KquiDJG5Ncl+SaJDdW1TXbHvJ3p/sBABZv7UHW3Xcn+egJi69NcrS7H+ruTyV5S5Lra+X7k/zz7v6Ndc8GALAXjNqp/5IkH9p2+5Fp2X+b5D9L8oqqes3JfrCqDlXVvVV17+OPP77+SQEA1mxP7dTf3W9I8oYzPOZwksNJsrm52edjLgCAdRq1hezRJJdtu33ptAwAYN8ZFWT3JLm6qq6sqouS3JDkjkGzAAAMdT5Oe/HmJO9I8vyqeqSqburuJ5K8NsnbkjyQ5Pbufv9ZPOfBqjq8tbW1nqEBAM6jte9D1t03nmL5XUnuepLPeSTJkc3NzZt3MxsAwF7gq5MAAAYTZAAAg80yyOxDBgAsySyDrLuPdPehjY2N0aMAAOzaLIMMAGBJBBkAwGCCDABgsFkGmZ36AYAlmWWQ2akfAFiSWQYZAMCSCDIAgMEEGQDAYIIMAGCwWQaZoywBgCWZZZA5yhIAWJJZBhkAwJIIMgCAwQQZAMBgggwAYLBZBpmjLAGAJZllkDnKEgBYkgtHD8CyXHHLnWf9Mw+//mVrmAQA5mOWW8gAAJZEkAEADCbIAAAGE2QAAIMJMgCAwWYZZM5DBgAsySxPe9HdR5Ic2dzcvHn0LHPilBQAsDfNcgsZAMCSCDIAgMEEGQDAYIIMAGAwQQYAMJggAwAYTJABAAwmyAAABhNkAACDzTLIfHUSALAkswyy7j7S3Yc2NjZGjwIAsGuzDDIAgCURZAAAgwkyAIDBBBkAwGCCDABgMEEGADCYIAMAGEyQAQAMJsgAAAYTZAAAgwkyAIDBBBkAwGCzDLKqOlhVh7e2tkaPAgCwa7MMsu4+0t2HNjY2Ro8CALBrswwyAIAlEWQAAINdOHoA9rYrbrlz9AgAsHi2kAEADCbIAAAGE2QAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABjMiWEZ7smcfPbh179sDZMAwBi2kAEADCbIAAAG85El+8bZfjTqY1EAzhdbyAAABhNkAACD+cgSTsHRnwCcL7aQAQAMtmeCrKqeV1U/XlU/N3oWAIDzaa0fWVbVrUm+Pslj3f3F25YfSPK/JbkgyT/u7td390NJbhJk7DeO/gRg3VvIbktyYPuCqrogyRuTXJfkmiQ3VtU1a54DAGDPWmuQdffdST56wuJrkxzt7oe6+1NJ3pLk+nXOAQCwl404yvKSJB/advuRJC+sqmcn+QdJ/mJVva67v+9kP1xVh5IcSpLLL7983bPCnuPoT4Dl2TOnveju30/ymh087nCSw0myubnZ654LAGDdRhxl+WiSy7bdvnRaBgCwL40IsnuSXF1VV1bVRUluSHLHgDkAAPaEdZ/24s1JXpTkOVX1SJK/190/XlWvTfK2rE57cWt3v/8sn/dgkoNXXXXVuR4ZOI/sDwewstYg6+4bT7H8riR37eJ5jyQ5srm5efOTfQ4AgL1iz5ypHwBgvxJkAACD7ZnTXpwN+5ABe42vwAJ2Y5ZbyLr7SHcf2tjYGD0KAMCuzTLIAACWRJABAAwmyAAABrNTPwC74gS/sHuz3EJmp34AYElmGWQAAEsiyAAABhNkAACDCTIAgMEcZQnAnudITpZullvIHGUJACzJLIMMAGBJBBkAwGCCDABgMEEGADCYoywBgEWZ41G5s9xC5ihLAGBJZhlkAABLIsgAAAYTZAAAgwkyAIDBBBkAwGCCDABgsFkGWVUdrKrDW1tbo0cBANi1WQaZ85ABAEsyyyADAFgSQQYAMJggAwAYTJABAAwmyAAABhNkAACDCTIAgMEEGQDAYLMMMmfqBwCWZJZB5kz9AMCSzDLIAACWRJABAAwmyAAABhNkAACDCTIAgMGqu0fP8KRV1eNJPrjmv+Y5SX5vzX/HXFgXx1kXx1kXx1kXx1kXK9bDcdZF8oXdffHJ7ph1kJ0PVXVvd2+OnmMvsC6Osy6Osy6Osy6Osy5WrIfjrIvT85ElAMBgggwAYDBBdmaHRw+wh1gXx1kXx1kXx1kXx1kXK9bDcdbFadiHDABgMFvIAAAGE2SnUVUHqurBqjpaVbeMnud8qKqHq+p9VfWeqrp3WvYFVfVLVfWB6c/Pn5ZXVb1hWj/vraoXjJ1+d6rq1qp6rKru37bsrF97VX3b9PgPVNW3jXgtu3GK9fA9VfXo9L54T1W9dNt9r5vWw4NV9ZJty2f/+1NVl1XVr1TVb1bV+6vqb0zL9+P74lTrYt+9N6rqaVX1rqq6b1oX3zstv7Kq3jm9rp+pqoum5U+dbh+d7r9i23OddB3NxWnWxW1V9Tvb3hdfNi1f7O/IrnW3y0kuSS5I8ttJnpfkoiT3Jblm9Fzn4XU/nOQ5Jyz7gSS3TNdvSfL90/WXJvnnSSrJX0ryztHz7/K1f02SFyS5/8m+9iRfkOSh6c/Pn65//ujXdg7Ww/ck+Vsneew10+/GU5NcOf3OXLCU358kz03ygun6M5L81vSa9+P74lTrYt+9N6b/vp83XX9KkndO/71vT3LDtPxNSb5zuv5fJ3nTdP2GJD9zunU0+vWdo3VxW5JXnOTxi/0d2e3FFrJTuzbJ0e5+qLs/leQtSa4fPNMo1yf5yen6Tyb5xm3Lf6pX/lWSZ1XVcwfMd050991JPnrC4rN97S9J8kvd/dHu/oMkv5TkwNqHP4dOsR5O5fokb+nuP+nu30lyNKvfnUX8/nT3h7v7N6brH0/yQJJLsj/fF6daF6ey2PfG9N/3E9PNp0yXTvK1SX5uWn7i++LY++Xnkry4qiqnXkezcZp1cSqL/R3ZLUF2apck+dC224/k9P/4LEUn+cWqendVHZqW/dnu/vB0/SNJ/ux0fT+so7N97UteJ6+dPmK49dhHdNlH62H6mOkvZrUFYF+/L05YF8k+fG9U1QVV9Z4kj2UVD7+d5A+7+4npIdtf179/zdP9W0menYWui+4+9r74B9P74keq6qnTskW/L3ZDkHGir+ruFyS5Lsl/U1Vfs/3OXm1b3peH5u7n157kHyX580m+LMmHk/zQ0GnOs6r6vCQ/n+RvdvfHtt+3394XJ1kX+/K90d2f6e4vS3JpVlu1vmjsROOcuC6q6ouTvC6rdfIVWX0M+V3jJpwHQXZqjya5bNvtS6dli9bdj05/PpbkF7L6h+Z3j30UOf352PTw/bCOzva1L3KddPfvTv/ofjbJj+X4xyqLXw9V9ZSsAuSnu/ut0+J9+b442brYz++NJOnuP0zyK0n+clYfv1043bX9df371zzdv5Hk97PcdXFg+oi7u/tPkvxE9tn74skQZKd2T5Krp6NmLspqR8w7Bs+0VlX19Kp6xrHrSb4uyf1Zve5jR7x8W5J/Ol2/I8l/OR0185eSbG37GGcpzva1vy3J11XV508f3XzdtGzWTtg38D/P6n2RrNbDDdNRZFcmuTrJu7KQ359pP58fT/JAd//wtrv23fviVOtiP743quriqnrWdP1zk/y1rPap+5Ukr5geduL74tj75RVJfnnasnqqdTQbp1gX/2bb/7BUVvvSbX9fLPJ3ZNfO5xEEc7tkdTTIb2W1b8DfGT3PeXi9z8vqiJ/7krz/2GvOal+Hf5nkA0n+RZIvmJZXkjdO6+d9STZHv4Zdvv43Z/WRy6ez2n/hpifz2pN8R1Y75x5N8urRr+scrYf/Y3qd783qH9Tnbnv835nWw4NJrtu2fPa/P0m+KquPI9+b5D3T5aX79H1xqnWx794bSb4kyb+eXvP9Sb57Wv68rILqaJKfTfLUafnTpttHp/ufd6Z1NJfLadbFL0/vi/uT/J85fiTmYn9Hdntxpn4AgMF8ZAkAMJggAwAYTJABAAwmyAAABhNkAACDCTJglqrqE9uuv7SqfquqvnDkTMdU1bdX1Y+OngOYD0EGzFpVvTjJG7I6h9MHB81wwYi/F1gOQQbM1vRdqz+W5Ou7+7enZa+qqndV1Xuq6n+fvvj4O6rqf932czdPX3j8P1bVX5+W/UhV/fJ0/Wur6qen6zdW1fuq6v6q+v5tz/GJqvqhqrovyV+uqldPW+neleQrtz3um6afva+q7j4PqwWYIUEGzNVTk/yTJN/Y3f8mSarqLyR5ZZKv7NWXHX8mybcmuT3Jwem7GJPk1UluTfL2JF89LdtM8nnTY746yd1V9eeSfH+Sr83qy7O/oqq+cXr805O8s7u/NKuzjn9vViH2VUmu2Tbndyd5yfS4bzh3Lx9YEkEGzNWnk/x6Vl/tdMyLk3x5knuq6j3T7ed19yey+iqXr6+qL0rylO5+X5J3J/nyqnpmkj9J8o6swuyrs4q1r0jyq939eHc/keSnk3zN9Hd9Jqsv2k6SF2573KeS/My2mX4tyW1VdXMSH20CJyXIgLn6bJJvTnJtVf1P07JK8pPd/WXT5fnd/T3Tff84ybdntXXsJ5Kkuz+d5Hem5b+eVYT91SRXZfVl0afz77r7M2casrtfk+TvJrksybur6tk7fYHA/iHIgNnq7k8meVmSb62qm7L6wu9XVNV/lCRV9QXHjrzs7ndmFUXfktUXqB/z9iR/K8nd0/XXJPnXvfqi33cl+StV9Zxpx/0bk/w/JxnlndPjnj195PlNx+6oqj/f3e/s7u9O8vg0A8CfIsiAWevujyY5kNVWqKumP3+xqt6b5JeSPHfbw29P8mvd/Qfblr19esw7uvt3k/y7aVm6+8NJbknyK0nuS/Lu7v6nJ5nhw0m+J6uPPH8tf3rr2g8eOyggq61w9+32NQPLU6v/CQRYvqr6Z0l+pLv/5ehZALazhQxYvKp6VlX9VpI/FmPAXmQLGQDAYLaQAQAMJsgAAAYTZAAAgwkyAIDBBBkAwGCCDABgsP8fkTCLyKMfMtYAAAAASUVORK5CYII=\n"},"metadata":{"needs_background":"light"}}],"source":"tdf = main_data[main_data['language']=='en'][['word','counts']].groupby('counts').count().reset_index()\nsomething = []\nfor i in range(len(tdf)):\n something.extend([tdf.loc[i,'word']]*tdf.loc[i,'counts'])\n\nfig, ax = plt.subplots(figsize=(10,10))\nax.hist(something, log=True, bins=40)\nax.set_xlabel(\"Keywords\")\nax.set_ylabel(\"Extractions\")\n# plot1_df\n# main_data[main_data['language']=='en'][['word','counts']].groupby('counts').count().reset_index()"},{"cell_type":"code","execution_count":206,"metadata":{},"outputs":[{"output_type":"stream","name":"stderr","text":[" 42%|████▏ | 20/48 [00:10<00:10, 2.67it/s]/tmp/ipykernel_11406/885795361.py:8: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n"," fig, ax = plt.subplots(figsize=(10,10))\n","100%|██████████| 48/48 [00:39<00:00, 1.23it/s]\n"]},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}},{"output_type":"display_data","data":{"text/plain":"
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DBsX532oqqemORxSc5J8tPd/arZiQAAlm/pe8iq6sVVdVtV3XjM8kuq6m1VdXNVXZkk3f0r3f0dSZ6V5CnLng0AYD84E29ZXpXkkt0LquqsJC9McmmSi5JcXlUX7XrK9y8eBwBYe0sPsu5+dZIPHbP44Ulu7u53dfcnkrwsyWW143lJfr2737js2QAA9oOpY8jul+Q9u+7fmuQRSf5Fkq9PslVVF3b3iyaGAwA4k/bVQf3d/YIkL7iz51TVoSSHkuSCCy44E2MBACzV1Gkv3pvk/F33z1ssO6nuPtzdF3f3xeeee+5ShgMAOJOmguwNSR5UVQ+oqrsleWqSq4dmAQAYdSZOe/HSJK9N8uCqurWqruju25M8O8krk9yU5OXd/dZlzwIAsB8t/Riy7r78BMuvTXLtsv9+AID9zqWTAACGrWSQVdXBqjq8vb09PQoAwClbySDr7iPdfWhra2t6FACAU7aSQQYAsE4EGQDAMEEGADBMkAEADBNkAADDVjLInPYCAFgnKxlkTnsBAKyTlQwyAIB1svRrWbJ/HLjymrv8e2557uOWMAkAsJs9ZAAAwwQZAMAwQQYAMEyQAQAMW8kgcx4yAGCdrGSQOQ8ZALBOVjLIAADWifOQrajP5JxiAMD+ZA8ZAMAwQQYAMEyQAQAME2QAAMMEGQDAMEEGADBsJYPMmfoBgHWykkHmTP0AwDpZySADAFgnggwAYJggAwAYJsgAAIYJMgCAYYIMAGCYIAMAGCbIAACGCTIAgGErGWQunQQArJOVDDKXTgIA1slKBhkAwDoRZAAAwwQZAMAwQQYAMEyQAQAME2QAAMMEGQDAMEEGADBMkAEADBNkAADDBBkAwLCVDDIXFwcA1slKBpmLiwMA62QlgwwAYJ0IMgCAYYIMAGCYIAMAGCbIAACGCTIAgGGCDABgmCADABgmyAAAhgkyAIBhggwAYJggAwAYJsgAAIYJMgCAYWdPD8D+duDKa+7S82957uOWNAkArC97yAAAhq1kkFXVwao6vL29PT0KAMApW8kg6+4j3X1oa2trehQAgFO2kkEGALBOBBkAwDBBBgAwTJABAAwTZAAAwwQZAMAwQQYAMEyQAQAME2QAAMNcXJxxd/UC5omLmAOwXuwhAwAYJsgAAIYJMgCAYYIMAGCYIAMAGCbIAACGCTIAgGGCDABgmCADABgmyAAAhgkyAIBhggwAYJggAwAYtpJBVlUHq+rw9vb29CgAAKdsJYOsu49096Gtra3pUQAATtlKBhkAwDoRZAAAwwQZAMAwQQYAMEyQAQAME2QAAMMEGQDAMEEGADBMkAEADBNkAADDBBkAwDBBBgAwTJABAAwTZAAAwwQZAMAwQQYAMEyQAQAME2QAAMMEGQDAsLOnB2C9HLjymukRAGDl2EMGADBMkAEADBNkAADDBBkAwDBBBgAwTJABAAwTZAAAwwQZAMAwQQYAMEyQAQAME2QAAMMEGQDAMEEGADBMkAEADDt7egA4Uw5cec1dev4tz33ckiYBgDuyhwwAYNi+CbKqemBV/XRV/eL0LAAAZ9JSg6yqXlxVt1XVjccsv6Sq3lZVN1fVlUnS3e/q7iuWOQ8AwH607D1kVyW5ZPeCqjoryQuTXJrkoiSXV9VFS54DAGDfWmqQdferk3zomMUPT3LzYo/YJ5K8LMlly5wDAGA/m/iU5f2SvGfX/VuTPKKq7p3kPyX5iqp6Tnf/8PF+c1UdSnIoSS644IJlzwpL59OfAOyb01509weTPGsPzzuc5HCSXHzxxb3suQAAlm3iU5bvTXL+rvvnLZYBAGykiSB7Q5IHVdUDqupuSZ6a5OqBOQAA9oVln/bipUlem+TBVXVrVV3R3bcneXaSVya5KcnLu/uty5wDAGA/W+oxZN19+QmWX5vk2mX+3QAAq2LfHNR/V1TVwSQHL7zwwulRgFNwVz9hmviUKbCe9s2lk+6K7j7S3Ye2tramRwEAOGUrGWQAAOtEkAEADBNkAADDBBkAwDBBBgAwzGkvgLXm1BrAKljJPWROewEArJOVDDIAgHUiyAAAhgkyAIBhggwAYJggAwAYJsgAAIYJMgCAYU4MC7DG7uqJcZ0UF2as5B4yJ4YFANbJSgYZAMA6EWQAAMMEGQDAMEEGADBMkAEADBNkAADDBBkAwDAnhgVgLd3Vk+ImTozLnJXcQ+bEsADAOlnJIAMAWCeCDABgmCADABgmyAAAhgkyAIBhggwAYJggAwAYJsgAAIYJMgCAYS6dBACslVW8bNZK7iFz6SQAYJ2sZJABAKwTQQYAMEyQAQAME2QAAMMEGQDAMEEGADBMkAEADBNkAADDBBkAwDBBBgAwTJABAAwTZAAAw1YyyKrqYFUd3t7enh4FAOCUrWSQdfeR7j60tbU1PQoAwClbySADAFgnggwAYJggAwAYJsgAAIYJMgCAYYIMAGCYIAMAGCbIAACGCTIAgGHV3dMzfMaq6s+TvHtJf/x9kvzFkv7s/WxT1zvZ3HXf1PVONnfdN3W9k81d901d72R/rfv9u/vc4z2w0kG2TFV1XXdfPD3Hmbap651s7rpv6nonm7vum7reyeau+6aud7I66+4tSwCAYYIMAGCYIDuxw9MDDNnU9U42d903db2TzV33TV3vZHPXfVPXO1mRdXcMGQDAMHvIAACGCbJjVNUlVfW2qrq5qq6cnmeZqur8qvqdqvrjqnprVX3XYvkPVtV7q+pNi6/HTs96ulXVLVX1lsX6XbdY9gVV9RtV9Y7Fr39jes7TraoevGu7vqmqPlxV372O27yqXlxVt1XVjbuWHXcb144XLF73b66qh85NfupOsO7Pr6o/WazfK6rqXovlB6rq47u2/YvGBj9FJ1jvE35vV9VzFtv8bVX1jTNTnx4nWPef37Xet1TVmxbL12mbn+jn2Oq91rvb1+IryVlJ3pnkgUnuluSGJBdNz7XE9b1vkocubt8zyduTXJTkB5N8z/R8S173W5Lc55hlP5LkysXtK5M8b3rOJf83OCvJ+5Pcfx23eZJHJ3lokhtPto2TPDbJryepJF+V5HXT8y9h3b8hydmL28/bte4Hdj9vlb9OsN7H/d5e/L/uhiR3T/KAxf/7z5peh9O57sc8/qNJfmANt/mJfo6t3GvdHrI7eniSm7v7Xd39iSQvS3LZ8ExL093v6+43Lm5/JMlNSe43O9Woy5L87OL2zyZ54twoZ8Rjkryzu5d1cuVR3f3qJB86ZvGJtvFlSX6ud/xhkntV1X3PyKBLcLx17+5Xdffti7t/mOS8Mz7Ykp1gm5/IZUle1t1/3d1/muTm7PwMWEl3tu5VVUmenOSlZ3SoM+BOfo6t3GtdkN3R/ZK8Z9f9W7MhgVJVB5J8RZLXLRY9e7E798Xr+NZdkk7yqqq6vqoOLZZ9YXe/b3H7/Um+cGa0M+apueP/oNd9mycn3sab9tr/9uzsJTjqAVX1R1X1e1X1qKmhluh439ubtM0fleQD3f2OXcvWbpsf83Ns5V7rgoxU1ecn+aUk393dH07yk0m+OMmXJ3lfdnZ1r5uv7u6HJrk0yT+vqkfvfrB39m2v7UeQq+puSZ6Q5BcWizZhm9/Bum/jE6mq70tye5KXLBa9L8kF3f0VSf5Vkv9RVedMzbcEG/e9fRyX547/+Fq7bX6cn2P/36q81gXZHb03yfm77p+3WLa2quqzs/NN/JLu/uUk6e4PdPenuvvTSX4qK7wb/0S6+72LX29L8orsrOMHju66Xvx629yES3dpkjd29weSzdjmCyfaxhvx2q+qZyR5fJKnLX5IZfGW3QcXt6/PzrFUf3tsyNPsTr63N2Wbn53km5P8/NFl67bNj/dzLCv4Whdkd/SGJA+qqgcs9iA8NcnVwzMtzeK4gp9OclN3/9iu5bvfT/+mJDce+3tXWVXdo6ruefR2dg52vjE72/rbFk/7tiS/OjPhGXGHfzGv+zbf5UTb+Ook/2TxCayvSrK96+2OtVBVlyT53iRP6O6P7Vp+blWdtbj9wCQPSvKumSlPvzv53r46yVOr6u5V9YDsrPfrz/R8Z8DXJ/mT7r716IJ12uYn+jmWVXytT3+qYL99ZecTGG/Pzr8Yvm96niWv61dnZzfum5O8afH12CT/PclbFsuvTnLf6VlP83o/MDufrrohyVuPbuck907yW0nekeQ3k3zB9KxLWv97JPlgkq1dy9Zum2cnON+X5JPZOU7kihNt4+x84uqFi9f9W5JcPD3/Etb95uwcO3P0tf6ixXP/0eJ18KYkb0xycHr+07zeJ/zeTvJ9i23+tiSXTs9/utd9sfyqJM865rnrtM1P9HNs5V7rztQPADDMW5YAAMMEGQDAMEEGADBMkAEADBNkAADDBBmwkqrqo7tuP7aq3l5V95+c6aiqekZV/cT0HMDqEGTASquqxyR5QXbOIzVyofSjJ9kE+EwJMmBlLa5B+lNJHt/d71wse3pVvb6q3lRV/7Wqzqqqb6+q/7zr931HVf14Vf2bqvrOxbIfr6rfXtz+uqp6yeL25VX1lqq6saqet+vP+GhV/WhV3ZDk71fVMxd76V6f5JG7nvekxe+9oapefQb+swArSJABq+ruSX4lyRO7+0+SpKq+NMlTkjyyu788yaeSPC3Jy5McXFzzLkmemeTFSX4/yaMWyy5O8vmL5zwqyaur6ouSPC/J12Xn4tRfWVVPXDz/Hkle190Pyc5Zv/9jdkLsq5NctGvOH0jyjYvnPeH0rT6wTgQZsKo+meQPsnN5nKMek+RhSd5QVW9a3H9gd380yW8neXxVfUmSz+7utyS5PsnDquqcJH+d5LXZCbNHZSfWvjLJ73b3n3f37UlekuTRi7/rU9m5oHGSPGLX8z6RXRdyTvKaJFdV1Xck8dYmcFyCDFhVn07y5CQPr6p/t1hWSX62u7988fXg7v7BxWP/LckzsrN37GeSpLs/meRPF8v/IDsR9g+SXJjkppP8/X/V3Z862ZDd/awk35/k/CTXV9W997qCw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\n"},"metadata":{"needs_background":"light"}}],"source":"save_path = \"plots/wordfrequency_0806/\"\nfor l in tqdm(languages):\n tdf = main_data[main_data['language']==l][['word','counts']].groupby('counts').count().reset_index()\n something = []\n for i in range(len(tdf)):\n something.extend([tdf.loc[i,'word']]*tdf.loc[i,'counts'])\n\n fig, ax = plt.subplots(figsize=(10,10))\n ax.hist(something, log=True, bins=40)\n ax.set_xlabel(\"Keywords\")\n ax.set_ylabel(\"Extractions\")\n plt.savefig(save_path + l + \".png\")\n# plot1_df\n# main_data[main_data['language']=='en'][['word','counts']].groupby('counts').count().reset_index()"},{"cell_type":"code","execution_count":207,"metadata":{},"outputs":[{"output_type":"stream","name":"stderr","text":[" 42%|████▏ | 20/48 [00:10<00:10, 2.76it/s]/tmp/ipykernel_11406/4082147859.py:8: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n"," fig, ax = plt.subplots(figsize=(10,10))\n","100%|██████████| 48/48 [00:38<00:00, 1.25it/s]\n"]},{"output_type":"display_data","data":{"text/plain":"
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ixlkPkuSwBgPVnKIAMAWE8EGQDAYIIMAGAwQQYAMJggAwAYTJABAAwmyAAABhNkAACDCTIAgMEEGQDAYIIMAGCwpQwyXy4OAKwnSxlkvlwcAFhPljLIAADWE0EGADCYIAMAGEyQAQAMJsgAAAYTZAAAgwkyAIDBBBkAwGCCDABgMEEGADCYIAMAGEyQAQAMJsgAAAYTZAAAgy1lkFXVlqo6eevWraOHAgCw15YyyLr71O4+cWVlZfRQAAD22lIGGQDAeiLIAAAGE2QAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhMkAEADCbIAAAGE2QAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhMkAEADCbIAAAGW8ogq6otVXXy1q1bRw8FAGCvLWWQdfep3X3iysrK6KEAAOy1pQwyAID1RJABAAwmyAAABhNkAACDCTIAgMEEGQDAYIIMAGAwQQYAMJggAwAYTJABAAwmyAAABhNkAACDCTIAgMEEGQDAYIIMAGAwQQYAMJggAwAYTJABAAwmyAAABhNkAACDCTIAgMEEGQDAYIIMAGCwpQyyqtpSVSdv3bp19FAAAPbaUgZZd5/a3SeurKyMHgoAwF5byiADAFhPBBkAwGCCDABgMEEGADCYIAMAGEyQAQAMJsgAAAYTZAAAgwkyAIDBBBkAwGCCDABgMEEGADCYIAMAGEyQAQAMJsgAAAYTZAAAgwkyAIDBBBkAwGCCDABgMEEGADCYIAMAGEyQAQAMJsgAAAYTZAAAgwkyAIDBBBkAwGCCDABgMEEGADCYIAMAGEyQAQAMJsgAAAYTZAAAgwkyAIDBljLIqmpLVZ28devW0UMBANhrSxlk3X1qd5+4srIyeigAAHttKYMMAGA9EWQAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhMkAEADCbIAAAGE2QAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhMkAEADCbIAAAGE2QAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhMkAEADCbIAAAGE2QAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhMkAEADCbIAAAGE2QAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhMkAEADCbIAAAGE2QAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhMkAEADLaqIKuqe1XVjafpJ1TV86vqdosdGgDAxrDaPWQvSvL1qrprkl9L8pkkr1rYqAAANpDVBtnV3d1JHpbkT7v7hUkOWtywAAA2jgNXeb0rq+rpSZ6Q5L5VdZ0k113csAAANo7V7iF7TJJvJjmhu7+Q5NAkv7+wUQEAbCCr2kM2Rdjz5+Y/G+eQAQCsidW+y/IRVfXpqtpaVVdU1ZVVdcWiBwcAsBGs9hyy5yXZ0t3nLnIwAAAb0WqD7NJFx1hVPTzJsUkOTvLS7n7HIh8PAGB/sdqT+s+qqtdX1XHT4ctHVNUjdnejqnpZVV1WVR/bbvnRVfWpqjqvqk5Kku7+6+5+cpKnZPYmAgCADWG1QXZwkq8n+ekkW6bLQ1Zxu1ckOXp+QVUdkOSFSY5JcniS46rq8Lmr/Ma0HgBgQ1jtuyyftCd33t2nV9Wm7RYfleS87j4/SarqdUkeVlXnJnlOkr/r7g/v7D6r6sQkJybJbW972z0ZFgDAfmW177I8tKrePB1+vKyq3lRVh+7hY94myUVz8xdPy/5zkp9K8siqesrObtzdJ3f3kd195CGHHLKHQwAA2H+s9qT+lyd5bZJHTfNPmJY9aK0G0t1/nOSP1+r+AACWxWrPITuku1/e3VdPl1ck2dPdU59Lctjc/KHTMgCADWm1e8i+VFVPSHLKNH9cki/t4WN+KMkdq+r2mYXYY5M8bg/va93YdNJpC3+MC55z7MIfAwC49la7h+znkjw6yReSXJLkkUl2e6J/VZ2S5Iwkd6qqi6vqhO6+OskvJ3l7knOTvKG7P74ngwcAWA9W+y7LC5M89NreeXcft5Plb03y1mt7fwAA69Eug6yqntbdz6uqP0nS26/v7l9Z2MgAADaI3e0h2/Z1SWcteiAAABvVLoOsu0+dJr/e3X85v66qHrWDm+wTVbUlyZbNmzePGgIAwJpZ7Un9T1/lsn2iu0/t7hNXVlZGDQEAYM3s7hyyY5I8OMltqmr+Q1sPTnL1IgcGALBR7O4css9ndv7YQ5OcPbf8yiT/ZVGDAgDYSHZ3Dtk5Sc6pqjcn+Vp3fydJquqAJNffB+MDAFj3VnsO2TuS3HBu/oZJ/vfaDwcAYONZbZDdoLuv2jYzTd9oMUMCANhYVhtkX6uqu22bqaq7J/nGYoYEALCxrPbLxZ+a5C+r6vNJKskPJHnMogYFALCRrPa7LD9UVXdOcqdp0ae6+9uLGxYAwMax2j1kySzGDk9ygyR3q6p096sWM6xd80n9AMB6sqpzyKrqt5P8yXS5f5LnZfbZZEP4pH4AYD1Z7Un9j0zywCRf6O4nJblrEjUEALAGVhtk3+juf0tydVUdnOSyJIctblgAABvHas8hO6uqbprkxZl9hdJVSc5Y1KAAADaS3QZZVVWS3+vuryb5s6p6W5KDu/ufFj04AICNYLdB1t1dVW9N8iPT/AWLHhQAwEay2nPIPlxVP77QkQAAbFCrPYfsHkkeX1UXJvlaZp/W3939owsbGQDABrHaIPuZhY4CAGADW+0hy2d394XzlyTPXuTAAAA2itUG2V3mZ6rqgCR3X/vhAABsPLsMsqp6elVdmeRHq+qK6XJlZh8M+5Z9MsIdj2tLVZ28devWUUMAAFgzuwyy7v697j4oye9398HT5aDuvnl3n7SPxrijcfkuSwBg3VjtIcvz5meq6oDpC8cBANhLqw2yB1bVW6vqVlX175L8Q5KDFjguAIANY1Ufe9Hdj6uqxyT5aGafQ/a47n7/QkcGALBBrGoPWVXdMcmvJnlTkguT/GxV3WiRAwMA2ChWe8jy1CS/2d2/kOQnk3w6yYcWNioAgA1ktZ/Uf1R3X5HMvi8pyR9U1amLGxYAwMaxu88he1qSdPcVVfWo7VYfv6hBAQBsJLs7ZPnYuemnb7fu6DUeCwDAhrS7IKudTO9oHgCAPbC7IOudTO9oHgCAPbC7k/rvWlVXZLY37IbTdKb5Gyx0ZAAAG8Qug6y7D9hXA7k2qmpLki2bN28ePRQAgL222s8h26/4cnEAYD1ZyiADAFhPBBkAwGCCDABgMEEGADCYIAMAGEyQAQAMJsgAAAYTZAAAgwkyAIDBBBkAwGCCDABgMEEGADCYIAMAGEyQAQAMtpRBVlVbqurkrVu3jh4KAMBeW8og6+5Tu/vElZWV0UMBANhrSxlkAADriSADABhMkAEADCbIAAAGE2QAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhMkAEADCbIAAAGE2QAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhsKYOsqrZU1clbt24dPRQAgL22lEHW3ad294krKyujhwIAsNeWMsgAANYTQQYAMJggAwAYTJABAAwmyAAABhNkAACDCTIAgMEEGQDAYIIMAGAwQQYAMJggAwAYTJABAAwmyAAABhNkAACDCTIAgMEEGQDAYIIMAGAwQQYAMJggAwAYTJABAAwmyAAABhNkAACDCTIAgMGWMsiqaktVnbx169bRQwEA2GtLGWTdfWp3n7iysjJ6KAAAe20pgwwAYD0RZAAAgwkyAIDBBBkAwGCCDABgMEEGADCYIAMAGEyQAQAMJsgAAAYTZAAAgwkyAIDBBBkAwGCCDABgMEEGADCYIAMAGEyQAQAMJsgAAAYTZAAAgwkyAIDBBBkAwGCCDABgMEEGADCYIAMAGEyQAQAMJsgAAAYTZAAAgwkyAIDBBBkAwGCCDABgsANHDwD2xKaTTlv4Y1zwnGMX/hgAkNhDBgAwnCADABhMkAEADLaUQVZVW6rq5K1bt44eCgDAXlvKIOvuU7v7xJWVldFDAQDYa0sZZAAA64kgAwAYTJABAAwmyAAABhNkAACDCTIAgMEEGQDAYIIMAGAwQQYAMJggAwAYTJABAAwmyAAABhNkAACDCTIAgMEEGQDAYIIMAGAwQQYAMJggAwAYTJABAAwmyAAABhNkAACDCTIAgMEEGQDAYAeOHgD7zqaTTlv4Y1zwnGMX/hjsn/bF6yvxGgPWJ3vIAAAGE2QAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhMkAEADCbIAAAGE2QAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhMkAEADCbIAAAGE2QAAIMJMgCAwQ4cPQDWl00nnTZ6CACwdOwhAwAYTJABAAwmyAAABhNkAACDCTIAgMEEGQDAYIIMAGAwQQYAMJggAwAYTJABAAwmyAAABttvgqyq7lBVL62qN44eCwDAvrTQIKuql1XVZVX1se2WH11Vn6qq86rqpCTp7vO7+4RFjgcAYH+06D1kr0hy9PyCqjogyQuTHJPk8CTHVdXhCx4HAMB+a6FB1t2nJ/nydouPSnLetEfsW0lel+RhixwHAMD+bMQ5ZLdJctHc/MVJblNVN6+qP0vyY1X19J3duKpOrKqzquqsyy+/fNFjBQBYuANHD2Cb7v5Skqes4nonJzk5SY488she9LgAABZtxB6yzyU5bG7+0GkZAMCGNCLIPpTkjlV1+6q6XpLHJnnLgHEAAOwXFv2xF6ckOSPJnarq4qo6obuvTvLLSd6e5Nwkb+jujy9yHAAA+7OFnkPW3cftZPlbk7x1kY8NALAs9ptP6gcA2KgEGQDAYIIMAGCw/eZzyK6NqtqSZMvmzZtHDwX2yqaTTtsnj3PBc47dJ48DwJ5Zyj1k3X1qd5+4srIyeigAAHttKYMMAGA9EWQAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhMkAEADLaUQVZVW6rq5K1bt44eCgDAXlvKIPNJ/QDAerKUQQYAs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iasAQAMTFgDABiYsAYAMDBhDQBgYMIaAMDAhDUAgIEJawAAAxPWAAAGJqwBAAxMWAMAGJiwBgAwMGENAGBgwhoAwMCENQCAgQlrAAADE9YAAAYmrAEADGyosFZVt6+qi6vqUcuuBQBgBAsNa1V1blVdX1WXbWo/rareXVVXVtU5cy/9pySvXmRNAACrZNEjay9Octp8Q1Udk+QFSU5PckqSs6rqlKr63iTvTHL9gmsCAFgZxy5y4d19QVWdvKn51CRXdvdVSVJVr0xyRpI7JLl9ZgHuk1V1fnd/fvMyq2pHkh1Jco973GOB1QMALN9Cw9o+nJjkmrnpa5M8sLufniRV9aQkH9pbUEuS7t6ZZGeSbNu2rRdbKgDAci0jrO1Xd7942TUAAIxiGWeDvi/J3eemT5raAADYZBlh7aIk962qe1XVbZOcmeS8JdQBADC8RV+64xVJLkxyv6q6tqrO7u6bkzw9yeuSXJ7k1d39joNc7vaq2rl79+7DXzQAwEAWfTboWftoPz/J+V/Ecncl2bVt27anHOoyAABWwVB3MAAA4NaENQCAgQlrAAADE9YAAAa2kmHN2aAAwLpYybDW3bu6e8fGxsaySwEAWKiVDGsAAOtCWAMAGJiwBgAwMGENAGBgKxnWnA0KAKyLlQxrzgYFANbFSoY1AIB1IawBAAxMWAMAGJiwBgAwMGENAGBgwhoAwMBWMqy5zhoAsC5WMqy5zhoAsC5WMqwBAKwLYQ0AYGDCGgDAwIQ1AICBCWsAAAMT1gAABiasAQAMbCXDmoviAgDrYiXDmoviAgDrYiXDGgDAuhDWAAAGJqwBAAxMWAMAGJiwBgAwMGENAGBgwhoAwMCENQCAga1kWHMHAwBgXaxkWHMHAwBgXaxkWAMAWBfCGgDAwIQ1AICBCWsAAAMT1gAABiasAQAMTFgDABiYsAYAMDBhDQBgYMIaAMDAhDUAgIEJawAAA1vJsFZV26tq5+7du5ddCgDAQq1kWOvuXd29Y2NjY9mlAAAs1EqGNQCAdSGsAQAMTFgDABiYsAYAMDBhDQBgYMIaAMDAhDUAgIEJawAAAxPWAAAGJqwBAAxMWAMAGJiwBgAwMGENAGBgwhoAwMCENQCAgQlrAAADE9YAAAYmrAEADGwlw1pVba+qnbt37152KQAAC7WSYa27d3X3jo2NjWWXAgCwUCsZ1gAA1oWwBgAwMGENAGBgwhoAwMCENQCAgQlrAAAD21JYq6rvqKrbT8+fUFXPrap7LrY0AAC2OrL2wiSfqKpvSvIfkrwnyUsXVhUAAEm2HtZu7u5OckaS53f3C5LccXFlAQCQJMducb6PVdUzkjwhyYOr6kuS3GZxZQEAkGx9ZO1xST6d5Ozu/kCSk5L82sKqAgAgyRZH1qaA9ty56X+MY9YAABZuq2eDfn9VXVFVu6vqxqr6WFXduOjiAADW3VaPWfvVJNu7+/JFFgMAwK1t9Zi1DwpqAABH3lZH1i6uqlcl+ePMTjRIknT3Hy6iKAAAZrYa1o5L8okk3zfX1kmENQCABdrq2aBPXnQhAAB8oa2eDXpSVf1RVV0/PV5TVSctujgAgHW31RMMfifJeUnuNj12TW0AACzQVsPaCd39O9198/R4cZITFlgXAADZelj7cFU9oaqOmR5PSPLhRRYGAMDWw9qPJvnBJB9Icl2SxyZx0gEAwIJt9WzQ9yZ59IJrAQBgk/2Gtar6me7+1ar6/zO7rtqtdPdPLKwyAAAOOLK25xZTFy+6EAAAvtB+w1p375qefqK7f3/+tar6gYVVBQBAkq2fYPCMLbYBAHAYHeiYtdOTPCLJiVX1vLmXjkty8+EspKq+PslPJjk+yV909wsP5/IBAFbRgUbW3p/Z8WqfSnLJ3OO8JA8/0MKr6tzp9lSXbWo/rareXVVXVtU5SdLdl3f3UzO7RMh3HPyqAAAcfQ50zNqlSS6tqj9K8vHu/lySVNUxSW63heW/OMnzk7x0T8P03hck+d4k1ya5qKrO6+53VtWjkzwtycsOYV0AAI46Wz1m7fVJvmxu+suS/PmB3tTdFyT5yKbmU5Nc2d1XdfdnkrwyyRnT/Od19+lJHr+vZVbVjqq6uKouvuGGG7ZYPgDAatrSRXGTfGl337RnortvqqovP8TPPDHJNXPT1yZ5YFU9NMn3ZzZid/6+3tzdO5PsTJJt27Z9wbXfAACOJlsNax+vqgd091uTpKq+JcknD2ch3f1XSf7qcC4TAGDVbTWs/VSS36+q9yepJF+d5HGH+JnvS3L3uemTpjYAADbZ6r1BL6qqr0tyv6np3d392UP8zIuS3Leq7pVZSDszyQ8d4rIAAI5qWz3BIJkFtVOSPCDJWVX1Iwd6Q1W9IsmFSe5XVddW1dndfXOSpyd5XWa3s3p1d7/jYIququ1VtXP37t0H8zYAgJWzpZG1qvrPSR6aWVg7P8npSf5X5i7JsTfdfdY+2s/Pfk4iOJDpNli7tm3b9pRDXQYAwCrY6sjaY5M8LMkHuvvJSb4pycbCqgIAIMnWw9onu/vzSW6uquOSXJ9bnyQAAMACbPVs0Iur6k5JXpTZ7aZuyuxYNAAAFuiAYa2qKskvd/c/JfmNqvqzJMd1998tujgAgHV3wN2g3d2ZOxmgu69edlBzNigAsC62eszaW6vqWxdayUHo7l3dvWNjwzkOAMDRbavHrD0wyeOr6r1JPp7ZXQy6u//lwioDAGDLYe3hC60CAIC92upu0F/q7vfOP5L80iILAwBg62HtG+YnquqYJN9y+MsBAGDefsNaVT2jqj6W5F9W1Y3T42OZXRT3vCNS4d7rcjYoALAW9hvWuvuXu/uOSX6tu4+bHnfs7rt09zlHqMa91eVsUABgLWx1N+iV8xNVdcx0c3cAABZoq2HtYVV1flXdtar+RZI3J7njAusCACBbvHRHd/9QVT0uydszu87aD3X3Xy+0MgAAtjayVlX3TfKTSV6T5L1JfriqvnyRhQEAsPXdoLuS/EJ3/9skD0lyRZKLFlYVAABJtn4Hg1O7+8bkn2/s/pyq2rW4sgAASA58nbWfSZLuvrGqfmDTy09aVFEH4jprAMC6ONBu0DPnnj9j02unHeZatsx11gCAdXGgsFb7eL63aQAADrMDhbXex/O9TQMAcJgd6ASDb6qqGzMbRfuy6Xmm6S9daGUAAOw/rHX3MUeqEAAAvtBWr7MGAMASCGsAAAMT1gAABraSYc1FcQGAdbGSYc1FcQGAdbGSYQ0AYF0IawAAAxPWAAAGJqwBAAxMWAMAGJiwBgAwMGENAGBgwhoAwMBWMqy5gwEAsC5WMqy5gwEAsC5WMqwBAKwLYQ0AYGDCGgDAwIQ1AICBCWsAAAMT1gAABiasAQAMTFgDABiYsAYAMDBhDQBgYMIaAMDAhDUAgIGtZFirqu1VtXP37t3LLgUAYKFWMqx1967u3rGxsbHsUgAAFmolwxoAwLoQ1gAABiasAQAMTFgDABiYsAYAMDBhDQBgYMIaAMDAhDUAgIEJawAAAxPWAAAGJqwBAAzs2GUXwMzJ57x24Z9x9a88cuGfAQAcXkbWAAAGJqwBAAxMWAMAGJiwBgAwMGENAGBgwhoAwMBWMqxV1faq2rl79+5llwIAsFArGda6e1d379jY2Fh2KQAAC7WSYQ0AYF0IawAAAxPWAAAGJqwBAAxMWAMAGJiwBgAwMGENAGBgwhoAwMCENQCAgQlrAAADE9YAAAYmrAEADExYAwAYmLAGADAwYQ0AYGDCGgDAwIQ1AICBCWsAAAMT1gAABiasAQAMTFgDABiYsAYAMDBhDQBgYMIaAMDAhDUAgIEJawAAAxPWAAAGJqwBAAzs2GUXMK+qHpPkkUmOS/Lb3f365VYEALBcCx9Zq6pzq+r6qrpsU/tpVfXuqrqyqs5Jku7+4+5+SpKnJnncomsDABjdkdgN+uIkp803VNUxSV6Q5PQkpyQ5q6pOmZvl56fXAQDW2sLDWndfkOQjm5pPTXJld1/V3Z9J8sokZ9TMs5P8aXe/dW/Lq6odVXVxVV18ww03LLZ4AIAlW9YJBicmuWZu+tqp7ceTfE+Sx1bVU/f2xu7e2d3bunvbCSecsPhKAQCWaKgTDLr7eUmet+w6AABGsayRtfclufvc9ElTGwAAc5YV1i5Kct+quldV3TbJmUnOW1ItAADDOhKX7nhFkguT3K+qrq2qs7v75iRPT/K6JJcneXV3v+Mglrm9qnbu3r17MUUDAAxi4cesdfdZ+2g/P8n5h7jMXUl2bdu27SlfTG0AAKNzuykAgIEJawAAAxPWAAAGJqwBAAxsJcOas0EBgHWxkmGtu3d1946NjY1llwIAsFArGdYAANaFsAYAMDBhDQBgYMIaAMDAhDUAgIGtZFhz6Q4AYF2sZFhz6Q4AYF2sZFgDAFgXxy67AI6ck8957cI/4+pfeeTCPwMA1omRNQCAgQlrAAADE9YAAAa2kmHNpTsAgHWxkmHNpTsAgHWxkmENAGBdCGsAAAMT1gAABiasAQAMTFgDABiYsAYAMDD3BuWwOhL3H03cgxSA9bGSI2suigsArIuVDGsuigsArIuVDGsAAOtCWAMAGJiwBgAwMGENAGBgwhoAwMCENQCAgQlrAAADE9YAAAYmrAEADGwlw5rbTQEA62Ilw5rbTQEA62IlwxoAwLoQ1gAABiasAQAMTFgDABiYsAYAMDBhDQBgYMIaAMDAhDUAgIEJawAAAxPWAAAGJqwBAAxsJcOaG7kDAOtiJcOaG7kDAOtiJcMaAMC6ENYAAAYmrAEADExYAwAYmLAGADAwYQ0AYGDCGgDAwIQ1AICBCWsAAAMT1gAABiasAQAMTFgDABiYsAYAMDBhDQBgYMIaAMDAhDUAgIEJawAAAxPWAAAGtpJhraq2V9XO3bt3L7sUAICFWsmw1t27unvHxsbGsksBAFiolQxrAADrQlgDABiYsAYAMDBhDQBgYMIaAMDAhDUAgIEJawAAAxPWAAAGJqwBAAxMW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MEEGQDAYIIMAGAwQQYAMJggAwAYTJABAAwmyAAABhNkAACDCTIAgMEEGQDAYIIMAGCwpQyyqtpeVWetr6+PHgUAYL8tZZB1987u3rG2tjZ6FACA/baUQQYAsEoEGQDAYIIMAGAwQQYAMJggAwAYTJABAAwmyAAABhNkAACDCTIAgMEEGQDAYIIMAGAwQQYAMJggAwAYTJABAAwmyAAABhNkAACDCTIAgMEEGQDAYIIMAGAwQQYAMJggAwAYTJABAAwmyAAABhNkAACDCTIAgMEEGQDAYIIMAGAwQQYAMJggAwAYTJABAAwmyAAABhNkAACDCTIAgMEEGQDAYIIMAGAwQQYAMJggAwAYbNMEWVV9e1X9XlW9qqoeN3oeAICDZaFBVlUvrKorq+o9u60/sao+UFUXV9WZSdLdF3X3Y5M8NMl9FjkXAMBmsug9ZC9KcuL8iqo6JMlzkpyU5Ngkp1fVsdNjD0rymiTnLnguAIBNY6FB1t3nJfn0bquPT3Jxd1/S3V9O8ookp07PP6e7T0ry8L29ZlXtqKoLquqCq666alGjAwAcNIcOeM87JvnI3PLlSe5dVQ9I8uNJbp7r2UPW3WclOStJjjvuuF7YlAAAB8mIINuj7n5TkjcNHgMA4KAb8VeWH01y9NzyUdM6AIAtaUSQvSPJ3arqLlV1sySnJTlnwBwAAJvCoi978fIk5ye5e1VdXlVndPe1SR6f5HVJLkpydne/d5FzAABsZgs9h6y7T9/L+nPj0hYAAEk20ZX6b4iq2l5VZ62vr48eBQBgvy1lkHX3zu7esba2NnoUAID9tpRBBgCwSgQZAMBgggwAYDBBBgAwmCADABhsKYPMZS8AgFWylEHmshcAwCpZyiADAFglggwAYDBBBgAwmCADABhMkAEADCbIAAAGW8ogcx0yAGCVLGWQuQ4ZALBKljLIAABWiSADABhMkAEADCbIAAAGE2QAAIMJMgCAwQQZAMBgSxlkLgwLAKySpQwyF4YFAFbJUgYZAMAqEWQAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhMkAEADCbIAAAGE2QAAIMtZZD5LksAYJUsZZD5LksAYJUsZZABAKwSQQYAMJggAwAYTJABAAwmyAAABhNkAACDbSjIquo+VXWr6f4jquoZVXXnxY4GALA1bHQP2XOTfL6q7pHkl5J8KMlLFjYVAMAWstEgu7a7O8mpSZ7d3c9JcpvFjQUAsHUcusHnfa6qnpTkEUl+oKpukuSmixsLAGDr2Ogesocl+VKSM7r740mOSvLbC5sKAGAL2dAesinCnjG3/OEMPIesqrYn2X7MMceMGgEA4IDZ6F9Z/nhVfbCq1qvq6qr6XFVdvejh9saXiwMAq2Sj55D9VpLt3X3RIocBANiKNnoO2SfEGADAYmx0D9kFVfXKJH+S2cn9SZLu/qNFDAUAsJVsNMgOS/L5JD8yt66TCDIAgP200b+yfPSiBwEA2Ko2+leWR1XVH1fVldPt1VV11KKHAwDYCjZ6Uv/vJzknyR2m285pHQAA+2mjQXZkd/9+d1873V6U5MgFzgUAsGVsNMg+VVWPqKpDptsjknxqkYMBAGwVGw2yn0ny0CQfT3JFkockcaI/AMABsNG/srwsyYMWPAsAwJZ0vUFWVU/s7t+qqv8vs+uOXUd3//zCJgMA2CL2tYds19clXbDoQQAAtqrrDbLu3jnd/Xx3/+H8Y1X1kwubCgBgC9noSf1P2uA6AABuoH2dQ3ZSkh9LcseqetbcQ4cluXaRgwEAbBX7OofsY5mdP/agJO+cW/+5JL+4qKH2paq2J9l+zDHHjBoBAOCA2dc5ZBcmubCq/jjJP3X3V5Okqg5JcvODMN/e5tqZZOdxxx33mFEzAAAcKBs9h+wvktxybvmWSf7qwI8DALD1bDTIbtHd1+xamO5/w2JGAgDYWjYaZP9UVffatVBV35PkC4sZCQBga9nQVycleUKSP6yqjyWpJN+c5GGLGgoAYCvZ6HdZvqOqvi3J3adVH+juryxuLACArWOje8iSWYwdm+QWSe5VVenulyxmLACArWNDQVZVv5bkAZkF2blJTkryN0kEGQDAftroSf0PSXJCko9396OT3CPJ2sKmAgDYQjYaZF/o7q8lubaqDktyZZKjFzcWAMDWsdFzyC6oqtsmeV5mX6F0TZLzFzUUAMBWss8gq6pK8hvd/dkkv1dVr01yWHf//aKHAwDYCvYZZN3dVXVuku+cli9d9FAAAFvJRs8he1dVfe9CJwEA2KI2eg7ZvZM8vKouS/JPmV2tv7v7uxY2GQDAFrHRIPvRhU4BALCFbfSQ5a9392XztyS/vsjBAAC2io0G2XfML1TVIUm+58CPAwCw9VxvkFXVk6rqc0m+q6qunm6fy+zCsOcclAkBAFbc9QZZd/9Gd98myW9392HT7TbdfXh3n3mQZgQAWGkbPWR58fxCVR0yfeE4AAD7aaNBdkJVnVtVt6+qf53kb5PcZoFzAQBsGRu67EV3/1RVPSzJP2R2HbKf6u63LHQyAIAtYkN7yKrqbkl+Icmrk1yW5Ker6hsWOdg+5tleVWetr6+PGgEA4IDZ6CHLnUl+pbv/fZL7J/lgkncsbKp96O6d3b1jbW1t1AgAAAfMRq/Uf3x3X53Mvi8pye9U1c7FjQUAsHXs6zpkT0yS7r66qn5yt4cftaihAAC2kn0dsjxt7v6TdnvsxAM8CwDAlrSvIKu93N/TMgAAN8K+gqz3cn9PywAA3Aj7Oqn/HlV1dWZ7w2453c+0fIuFTgYAsEVcb5B19yEHaxAAgK1qo9chAwBgQQQZAMBgggwAYDBBBgAwmCADABhMkAEADCbIAAAGE2QAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhMkAEADCbIAAAGE2QAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhMkAEADCbIAAAGE2QAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhMkAEADCbIAAAGO3T0APOq6sFJTk5yWJIXdPdfjJ0IAGDxFr6HrKpeWFVXVtV7dlt/YlV9oKourqozk6S7/6S7H5PksUketujZAAA2g4NxyPJFSU6cX1FVhyR5TpKTkhyb5PSqOnbuKU+ZHgcAWHkLD7LuPi/Jp3dbfXySi7v7ku7+cpJXJDm1Zp6e5M+7+117er2q2lFVF1TVBVddddVihwcAOAhGndR/xyQfmVu+fFr3H5P8UJKHVNVj9/SD3X1Wdx/X3ccdeeSRi58UAGDBNtVJ/d39rCTPGj0HAMDBNGoP2UeTHD23fNS0DgBgyxkVZO9IcrequktV3SzJaUnOGTQLAMBQB+OyFy9Pcn6Su1fV5VV1Rndfm+TxSV6X5KIkZ3f3exc9CwDAZrTwc8i6+/S9rD83ybk35jWranuS7cccc8z+jAYAsCks5VcndffO7t6xtrY2ehQAgP22lEEGALBKBBkAwGCb6jpkW9m2M1+z8Pe49DdPXvh7AAA3nD1kAACDCTIAgMGWMsiqantVnbW+vj56FACA/baUQeayFwDAKlnKIAMAWCWCDABgMEEGADCYIAMAGEyQAQAMJsgAAAZbyiBzHTIAYJUsZZC5DhkAsEqWMsgAAFaJIAMAGEyQAQAMJsgAAAYTZAAAgwkyAIDBBBkAwGCCDABgsKUMMlfqBwBWyVIGmSv1AwCrZCmDDABglQgyAIDBBBkAwGCCDABgMEEGADCYIAMAGEyQAQAMJsgAAAYTZAAAgy1lkPnqJABglSxlkPnqJABglSxlkAEArBJBBgAwmCADABhMkAEADCbIAAAGE2QAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhsKYPMl4sDAKtkKYPMl4sDAKtkKYMMAGCVCDIAgMEEGQDAYIIMAGAwQQYAMJggAwAYTJABAAwmyAAABhNkAACDCTIAgMEEGQDAYIIMAGAwQQYAMJggAwAYTJABAAwmyAAABlvKIKuq7VV11vr6+uhRAAD221IGWXfv7O4da2tro0cBANhvSxlkAACrRJABAAwmyAAABhNkAACDHTp6AA6ebWe+ZuHvcelvnrzw9wCAVWMPGQDAYIIMAGAwQQYAMJggAwAYTJABAAwmyAAABhNkAACDCTIAgMEEGQDAYK7UzwF1ML4NIPGNAACsFnvIAAAGE2QAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhMkAEADLaUQVZV26vqrPX19dGjAADst6UMsu7e2d071tbWRo8CALDfljLIAABWiSADABhMkAEADCbIAAAGE2QAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhMkAEADCbIAAAGE2QAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhMkAEADCbIAAAGE2QAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhMkAEADCbIAAAGE2QAAIMJMgCAwQQZAMBgggwAYDBBBgAwmCADABhMkAEADCbIAAAGE2QAAINtmiCrqrtW1Quq6lWjZwEAOJgWGmRV9cKqurKq3rPb+hOr6gNVdXFVnZkk3X1Jd5+xyHkAADajRe8he1GSE+dXVNUhSZ6T5KQkxyY5vaqOXfAcAACb1qGLfPHuPq+qtu22+vgkF3f3JUlSVa9IcmqS923kNatqR5IdSXKnO93pwA3LUtl25msW/h6X/ubJC38PAEjGnEN2xyQfmVu+PMkdq+rwqvq9JN9dVU/a2w9391ndfVx3H3fkkUcuelYAgIVb6B6yG6K7P5XksaPnAAA42EbsIftokqPnlo+a1gEAbEkjguwdSe5WVXepqpslOS3JOQPmAADYFBZ92YuXJzk/yd2r6vKqOqO7r03y+CSvS3JRkrO7+72LnAMAYDNb9F9Znr6X9ecmOffGvm5VbU+y/ZhjjrmxLwH7dDD+kjPx15wAbKIr9d8Q3b2zu3esra2NHgUAYL8tZZABAKwSQQYAMJggAwAYTJABA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\n"},"metadata":{"needs_background":"light"}},{"output_type":"display_data","data":{"text/plain":"
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A4AgE1h0ctevDTJxUnuVVXXVNVZ3X1jkqckeW2Sy5Oc391vP8T97qyqc/fs2bP+RQMAbLCFziHr7jMP0H5hkguPYL+7kuzasWPHEw93HwAAm8WmWakfAGCrEsgAAAYTyAAABlvKQGZSPwCwSpYykHX3ru4+e9u2baNLAQA4YksZyAAAVolABgAwmEAGADDYUgYyk/oBgFWylIHMpH4AYJUsZSADAFglAhkAwGACGQDAYAIZAMBgAhkAwGBLGcgsewEArJKlDGSWvQAAVslSBjIAgFUikAEADCaQAQAMJpABAAwmkAEADCaQAQAMtpSBzDpkAMAqWcpAZh0yAGCVLGUgAwBYJQIZAMBgAhkAwGACGQDAYAIZAMBgAhkAwGACGQDAYAIZAMBgSxnIrNQPAKySpQxkVuoHAFbJUgYyAIBVIpABAAwmkAEADCaQAQAMJpABAAwmkAEADCaQAQAMJpABAAwmkAEADCaQAQAMtpSBzL0sAYBVspSBzL0sAYBVspSBDABglQhkAACDCWQAAIMJZAAAgwlkAACDCWQAAIMJZAAAgwlkAACDCWQAAIMJZAAAgwlkAACDCWQAAIMJZAAAgwlkAACDCWQAAIMJZAAAgy1lIKuqnVV17p49e0aXAgBwxJYykHX3ru4+e9u2baNLAQA4YksZyAAAVolABgAwmEAGADCYQAYAMJhABgAwmEAGADCYQAYAMJhABgAwmEAGADCYQAYAMJhABgAwmEAGADCYQAYAMJhABgAwmEAGADCYQAYAMJhABgAwmEAGADCYQAYAMJhABgAwmEAGADCYQAYAMJhABgAwmEAGADCYQAYAMNimCmRVdduquqSqHja6FgCAjbLQQFZVL6yq66rqsn3aT6mqd1XVFVV1ztxL/yXJ+YusCQBgs1n0CNl5SU6Zb6iqo5I8J8mpSU5KcmZVnVRV35vkHUmuW3BNAACbytGL3Hl3X1RVJ+7TfHKSK7r7yiSpqpclOT3J7ZLcNrOQ9umqurC7v7DvPqvq7CRnJ8lXfdVXLbB6AICNsdBAdgDHJbl6bvuaJPfv7qckSVU9PslH9hfGkqS7z01ybpLs2LGjF1sqAMDijQhkt6i7zxtdAwDARhpxleUHkpwwt3381AYAsCWNCGRvTnLPqrp7VR2T5IwkFwyoAwBgU1j0shcvTXJxkntV1TVVdVZ335jkKUlem+TyJOd399sPcb87q+rcPXv2rH/RAAAbbNFXWZ55gPYLk1x4BPvdlWTXjh07nni4+wAA2Cw21Ur9AABbkUAGADCYQAYAMNhSBjKT+gGAVbKUgay7d3X32du2bRtdCgDAEVvKQAYAsEoEMgCAwQQyAIDBBDIAgMGWMpC5yhIAWCVLGchcZQkArJKlDGQAAKtEIAMAGEwgAwAYTCADABhsKQOZqywBgFWylIHMVZYAwCpZykAGALBKBDIAgMEEMgCAwQQyAIDBBDIAgMEEMgCAwZYykFmHDABYJUsZyKxDBgCskqUMZAAAq0QgAwAYTCADABhMIAMAGEwgAwAYTCADABhMIAMAGEwgAwAYbCkDmZX6AYBVspSBzEr9AMAqWcpABgCwSgQyAIDB1hTIqurbq+q20/PHVtUzq+puiy0NAGBrWOsI2XOTfKqq7pvkZ5K8J8mLF1YVAMAWstZAdmN3d5LTk/xOdz8nye0XVxYAwNZx9Brf94mqemqSxyZ5YFV9UZJbLa4sAICtY60jZI9O8pkkZ3X3h5Icn+TXF1YVAMAWsqYRsimEPXNu+/0xhwwAYF2s9SrLR1bVu6tqT1VdX1WfqKrrF10cAMBWsNY5ZL+WZGd3X77IYgAAtqK1ziH78GYKY+5lCQCskrUGskuq6uVVdeZ0+vKRVfXIhVZ2C9zLEgBYJWs9ZXmHJJ9K8n1zbZ3kVeteEQDAFrPWqyyfsOhCAAC2qrVeZXl8Vf1xVV03PV5ZVccvujgAgK1grXPIfj/JBUnuOj12TW0AAByhtQayY7v797v7xulxXpJjF1gXAMCWsdZA9tGqemxVHTU9Hpvko4ssDABgq1hrIPvRJD+Y5ENJrk3yqCQm+gMArIO1XmX5viQPX3AtAABb0i0Gsqr62e7+tar6H5mtO3Yz3f0TC6sMAGCLONgI2d7bJV2y6EIAALaqWwxk3b1revqp7v6j+deq6gcWVhUAwBay1kn9T11jGwAAh+hgc8hOTfLQJMdV1bPnXrpDkhsXWRgAwFZxsDlkH8xs/tjDk7xlrv0TSX56UUUBAGwlB5tDdmmSS6vqj5N8srs/nyRVdVSSW29AfQAAK2+tc8j+PMkXz21/cZK/XP9yAAC2nrUGstt09w17N6bnX7KYkg6uqnZW1bl79uwZVQIAwLpZayD7ZFV9096NqvrmJJ9eTEkH1927uvvsbdu2jSoBAGDdrOnWSUl+KskfVdUHk1SSr0zy6EUVBQCwlaz1XpZvrqqvTXKvqeld3f25xZUFALB1rHWELJmFsZOS3CbJN1VVuvvFiykLAGDrWFMgq6pfSvKgzALZhUlOTfL/JxHIAACO0Fon9T8qyYOTfKi7n5DkvknMqAcAWAdrDWSf7u4vJLmxqu6Q5LokJyyuLACArWOtc8guqao7Jvm9zG6hdEOSixdVFADAVnLQQFZVleRXu/tfkjyvql6T5A7d/Y+LLg4AYCs4aCDr7q6qC5PcZ9q+atFFAQBsJWudQ/bWqvqWhVYCALBFrXUO2f2TPKaq3pfkk5mt1t/d/Q0LqwwAYItYayB7yEKrAADYwtZ6yvJXuvt9848kv7LIwgAAtoq1BrKvn9+oqqOSfPP6lwMAsPXcYiCrqqdW1SeSfENVXT89PpHZwrAXbEiFAAAr7hYDWXf/anffPsmvd/cdpsftu/tO3X3OBtUIALDS1nrK8or5jao6arrhOAAAR2itgezBVXVhVd2lqu6d5I1Jbr/AugAAtow1LXvR3T9UVY9O8k+ZrUP2Q939twutDABgi1jTCFlV3TPJTyZ5ZZL3JfnhqvqSRRYGALBVrPWU5a4kv9jd/zHJdyZ5d5I3L6wqAIAtZK0r9Z/c3dcns/slJfnNqtq1uLIAALaOg61D9rNJ0t3XV9UP7PPy4xdVFADAVnKwU5ZnzD1/6j6vnbLOtQAAbEkHC2R1gOf72wYA4DAcLJD1AZ7vb/uIVNXXVdXzquoVVfXk9dw3AMBmdrBAdt+5+1fuez/L+xxs51X1wqq6rqou26f9lKp6V1VdUVXnJEl3X97dT0ryg0m+/TA/DwDA0jnYvSyPmrt/5dH73M/yVmvY/3nZZ65ZVR2V5DlJTk1yUpIzq+qk6bWHJ3l1kgsP47MAACylta5Ddli6+6IkH9un+eQkV3T3ld392SQvS3L69P4LuvvUJI850D6r6uyquqSqLtm9e/eiSgcA2DBrXYdsPR2X5Oq57WuS3L+qHpTkkUlunVsYIevuc5OcmyQ7duxY13lsAAAjjAhk+9Xdf5PkbwaXAQCw4RZ6yvIAPpDkhLnt46c2AIAtaUQge3OSe1bV3avqmMwWn71gQB0AAJvCQgNZVb00ycVJ7lVV11TVWd19Y5KnJHltksuTnN/dbz/E/e6sqnP37Nmz/kUDAGywhc4h6+4zD9B+YY5gaYvu3pVk144dO554uPsAANgsRpyyBABgjkAGADCYQAYAMNhSBjKT+gGAVbKUgay7d3X32du2bRtdCgDAEVvKQAYAsEoEMgCAwQQyAIDBBDIAgMGWMpC5yhIAWCVLGchcZQkArJKlDGQAAKtEIAMAGEwgAwAYTCADABhsKQOZqywBgFWylIHMVZYAwCpZykAGALBKBDIAgMEEMgCAwQQyAIDBBDIAgMEEMgCAwY4eXcDhqKqdSXZu3759dCnr5sRzXr3wY1z19NMWfgwA4NAt5QiZdcgAgFWylIEMAGCVCGQAAIMJZAAAgwlkAACDCWQAAIMJZAAAgwlkAACDCWQAAIMtZSCrqp1Vde6ePXtGlwIAcMSWMpBZqR8AWCVLGcgAAFaJQAYAMJhABgAwmEAGADCYQAYAMJhABgAwmEAGADCYQAYAMJhABgAwmEAGADCYQAYAMNhSBjI3FwcAVslSBjI3FwcAVslSBjIAgFUikAEADCaQAQAMJpABAAwmkAEADCaQAQAMJpABAAwmkAEADCaQAQAMJpABAAwmkAEADCaQAQAMJpABAAwmkAEADCaQAQAMdvToAg5HVe1MsnP79u2jS1kqJ57z6oUf46qnn7bwYwDAqlnKEbLu3tXdZ2/btm10KQAAR2wpAxkAwCoRyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAY7enQB86rqEUlOS3KHJC/o7j8fWxEAwOItfISsql5YVddV1WX7tJ9SVe+qqiuq6pwk6e4/6e4nJnlSkkcvujYAgM1gI05ZnpfklPmGqjoqyXOSnJrkpCRnVtVJc2/5hel1AICVt/BA1t0XJfnYPs0nJ7miu6/s7s8meVmS02vmGUn+rLvfur/9VdXZVXVJVV2ye/fuxRYPALABRs0hOy7J1XPb1yS5f5IfT/I9SbZV1fbuft6+P9jd5yY5N0l27NjRG1Arh+DEc169Ice56umnbchxAGAjbKpJ/d397CTPHl0HAMBGGrXsxQeSnDC3ffzUBgCw5YwKZG9Ocs+quntVHZPkjCQXDKoFAGCojVj24qVJLk5yr6q6pqrO6u4bkzwlyWuTXJ7k/O5++yHsc2dVnbtnz57FFA0AsIEWPoesu888QPuFSS48zH3uSrJrx44dTzyS2gAANgO3TgIAGEwgAwAYTCADABhsKQOZSf0AwCpZykDW3bu6++xt27aNLgUA4IgtZSADAFglAhkAwGACGQDAYAIZAMBgSxnIXGUJAKySpQxkr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\n"},"metadata":{"needs_background":"light"}}],"source":"save_path = \"plots/wordfrequency_0806/\"\nfor l in tqdm(languages):\n tdf = main_data[main_data['language']==l][['word','counts']].groupby('counts').count().reset_index()\n something = []\n for i in range(len(tdf)):\n something.extend([tdf.loc[i,'word']]*tdf.loc[i,'counts'])\n\n fig, ax = plt.subplots(figsize=(10,10))\n ax.hist(something, log=True, bins=20)\n ax.set_xlabel(\"Keywords\")\n ax.set_ylabel(\"Extractions\")\n ax.set_title(f\"Extractions v/s Keywords for {l}\")\n plt.savefig(save_path + l + \".png\")\n# plot1_df\n# main_data[main_data['language']=='en'][['word','counts']].groupby('counts').count().reset_index()"},{"cell_type":"code","execution_count":208,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":208},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_df.transpose()[wl15]\nlanguage_fractions_df_T.nsmallest(40,3).nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Percentage of Audio Clips\", xlabel='Word Length', title='Percentage of Audio Clips by Word Length (1 to 15) for top (11 to 20) languages')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\n# plt.savefig('plots/stacked/percent_audio_clips_by_word_length_vs_word_length_top11-20.png')"},{"cell_type":"code","execution_count":209,"metadata":{},"outputs":[],"source":"# language_fractions_df_T = language_fractions_df.transpose()[wl15]\n# language_fractions_df_T.nsmallest(40,3).nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Percentage of Audio Clips\", xlabel='Word Length', title='Percentage of Audio Clips by Word Length (1 to 15) for top (11 to 20) languages')\n# plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\n# plt.savefig('plots/stacked/percent_audio_clips_by_word_length_vs_word_length_top11-20.png')"},{"cell_type":"code","execution_count":210,"metadata":{},"outputs":[],"source":"# for l in tqdm(language_fractions):\n# for j in language_fractions[l]:\n# language_fractions[l][j] /= wordlengths_counts[j]\n # for j in wordlengths_counts:\n # if j not in language_fractions[l]:\n # language_fractions[l][j] = 0"},{"cell_type":"code","execution_count":211,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":["337330067,\n"," 5: 0.000774408432781536,\n"," 6: 0.00046822746843056294,\n"," 7: 0.0003684827241197544,\n"," 8: 0.00021517763741574968,\n"," 9: 0.00018910084477908004,\n"," 10: 6.662567823771574e-05,\n"," 11: 4.901528296522856e-05,\n"," 12: 1.6142571188738942e-05,\n"," 13: 0.0,\n"," 14: 0.0,\n"," 15: 0.0,\n"," 16: 0.0,\n"," 17: 0.0,\n"," 18: 0.0,\n"," 19: 0.0,\n"," 20: 0.0,\n"," 21: 0.0,\n"," 22: 0.0,\n"," 23: 0.0,\n"," 24: 0.0,\n"," 25: 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31 rows × 48 columns

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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_og.transpose()[wl15]\nlanguage_fractions_df_T.nsmallest(40,3).nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Percentage of Audio Clips\", xlabel='Word Length', title='Percentage of Audio Clips by Word Length (1 to 15) for top (11 to 20) languages')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\n# plt.savefig('plots/stacked/percent_audio_clips_by_word_length_vs_word_length_top11-20.png')"},{"cell_type":"code","execution_count":218,"metadata":{},"outputs":[{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_og.transpose()[wl15]\nlanguage_fractions_df_T.nsmallest(40,3).nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Number of Audio Clips\", xlabel='Word Length', title='Audio Clips v/s Word Length (1 to 15) for top (11 to 20) languages')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\nplt.savefig('plots/stacked/audio_clips_vs_word_length_top11-20.png')"},{"cell_type":"code","execution_count":219,"metadata":{},"outputs":[],"source":"# language_fractions_df_T = language_fractions_og.transpose()[wl15]\n# language_fractions_df_T.nsmallest(40,3).nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Number of Audio Clips\", xlabel='Word Length', title='Audio Clips v/s Word Length (1 to 15) for top (11 to 20) languages')\n# plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\n# plt.savefig('plots/stacked/audio_clips_vs_word_length_top11-20.png')"},{"cell_type":"code","execution_count":220,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" Italian Maltese Polish Slovenian Georgian Sursilvan Vallader \\\n","3 98098 5383 93486 2561 673 6234 1731 \n","4 60035 7849 64831 2703 763 3866 922 \n","5 107270 4599 74697 2708 656 2504 573 \n","6 81082 3424 67352 1422 621 2131 477 \n","7 65570 2205 52483 658 737 1102 243 \n","8 54892 1810 43169 314 445 658 88 \n","9 34074 670 31409 182 241 401 69 \n","10 26622 452 18960 53 286 253 27 \n","11 16161 180 11082 19 209 143 10 \n","12 7548 123 6449 0 95 96 12 \n","13 4481 86 2742 12 75 23 5 \n","14 3186 13 1189 0 28 5 0 \n","15 1959 35 534 0 16 0 0 \n","16 408 12 185 0 0 5 0 \n","17 180 5 165 0 0 0 0 \n","18 103 0 99 0 0 0 0 \n","19 61 6 10 0 0 0 0 \n","20 16 0 10 0 0 0 0 \n","21 5 0 0 0 0 0 0 \n","22 0 0 0 0 0 0 0 \n","23 0 0 0 0 0 0 0 \n","24 0 0 0 0 0 0 0 \n","25 0 0 0 0 0 0 0 \n","26 0 0 0 0 0 0 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"},"metadata":{},"execution_count":220}],"source":"language_fractions_og = language_fractions_og.rename(isocode_to_lang, axis=1)\nlanguage_fractions_og"},{"cell_type":"code","execution_count":221,"metadata":{},"outputs":[{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_og.transpose()[wl15]\nlanguage_fractions_df_T.nsmallest(40,3).nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Number of Audio Clips\", xlabel='Word Length', title='Audio Clips v/s Word Length (1 to 15) for top (11 to 20) languages')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\nplt.savefig('plots/stacked/audio_clips_vs_word_length_top11-20.png')"},{"cell_type":"code","execution_count":222,"metadata":{},"outputs":[{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_og.transpose()[wl15]\nlanguage_fractions_df_T.nsmallest(30,3).nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Number of Audio Clips\", xlabel='Word Length', title='Audio Clips v/s Word Length (1 to 15) for top (21 to 30) languages')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\nplt.savefig('plots/stacked/audio_clips_vs_word_length_top21-30.png')"},{"cell_type":"code","execution_count":223,"metadata":{},"outputs":[{"output_type":"display_data","data":{"text/plain":"
","image/svg+xml":"\n\n\n \n \n \n \n 2021-08-06T20:04:56.207583\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_og.transpose()[wl15]\nlanguage_fractions_df_T.nsmallest(20,3).nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Number of Audio Clips\", xlabel='Word Length', title='Audio Clips v/s Word Length (1 to 15) for top (31 to 40) languages')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\nplt.savefig('plots/stacked/audio_clips_vs_word_length_top31-40.png')"},{"cell_type":"code","execution_count":224,"metadata":{},"outputs":[{"output_type":"display_data","data":{"text/plain":"
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nD90SJux4XFHHugohc1ayV9HLc1VvSCb018W39dwrmPKeJck+Nthykacd8Y3wdvSMpKOLayog/y1S+h/4WSjk+4XmxtSvgbKKG/VopeLK+T9HxCnQWP1y8knV7od/mgpEmKAtw7kpqX0H9fSa8Us62o+7Y876un4vvhO0XvMl1eaHtnRc9DmxV9HqNzob/pxZIqlua2KfpbWxH/np9Q9MLltoTHzOLi7mdF00deUvT3P1XRyPEbCfuerOjveZ2ke/X959jD4tvwXXw/D088l6J3GGbE2/+jKNRfn7C9T3zOdYpGwP+jKLwfruj5c0P8u56oaEpJ0v6/4oefffnH3Pf23VogdZjZZEUB5J+B+v+bpM/d/W8h+t+fWLTSw9nufvRudy59nydK+o27n1ZWfZYHM/utpEPc/QfL3u0rzOxRRUHtj3twzPuSLvMivrQmVZnZvYpeIJb737hF3x7awN1L+1mZPen7I0kPuvsjZd038FP2k/giC6AczVA0So5CzKyhoqkKHyoaTR2uHy5JuFfc/XVF77KkFHcv85U49gXuXuSSnqnM3YeX17ni6SIVJX0mqZui6TCXlHhQ6fs+WtE7U98qeofwcEXvZAIoQwRtoAx5tD4xilZR0Xq8zRW9Hf20opUoABStuqJpLo0UTT+5V/+bS763MhV9bqKaoi9ZOsOjb70EUIaYOgIAAAAEwKojAAAAQAD75dSRunXrerNmzZJdBgAAwG5Nnz79W3evl+w6UPb2y6DdrFkzTZs2LdllAAAA7JaZ/dhv68U+jqkjAAAAQAAEbQAAACAAgjYAAAAQwH45RxsAAAClN2PGjD+Y2a8lWbJrSTVmtjw/P/+uLl26PF94G0EbAADgJ87Mfn3YYYety8jI2JHsWlKJu2vTpk0HzJs3715JzxfeztQRAAAAGCF7z5mZqlWrtkVSelHbCdoAAABAAEwdAQAAwC7NRrzUdW/7WHhX3+klbZ80aVK16667rrG7Kz093U888cS8ypUr77z22mtX7e25i5Obm1vxiiuuaPzqq68uCHWOwgjaAAAAKDcrVqxIv+yyy5q+/vrrc5s2bbp99erV6f/v//2/usmuKwSmjgAAAKDcjBs3ruYpp5yyrmnTptsl6cADD9xRp06d/LfffrtG7969W7Zv377t119/XUGS2rdv37bguPbt27fdunWrdenSpU1B22mnndb8k08+qfzAAw/Uyc7OzmzXrl3bBx54oI4k3XPPPfU6dOjQtkePHq0ff/zxWpK0cuXKin379j20devW7SZMmFA99G0laAMAAKDcLF26tGKjRo22FW6vUaPGjjfffHPeBRdc8O0TTzxRu6hjK1Wq5K1atdr84YcfVtm0aZMtXry4YufOnbcMGjRoXU5OTm5OTs6XDzzwQH1Jeu6552q//fbbuVOmTJlz3nnnrZOkNWvWZDz//PMLnn766QWjRo06KOgNFVNHAAAAUI4aNWq0be7cuZULt3fq1GmTJDVp0mTbtGnTqhbe7u6SpHPOOWfNk08+WWfu3LkbTzzxxDxJGj9+fI1Ro0bVd3d98803lSXpzjvvXDxkyJAm7q4bbrhhWeXKlT0zM3NzhQoV1KJFi215eXlFrhRSlhjRBgAAQLk544wz8l555ZVaBdND1qxZk7ZmzZoMM/OCfdzdJGnr1q1p+fn5mjt3bsW8vLwMSerXr9+G999/v/p//vOf2oMHD14jSXfffXfD//73v3PffPPNuZUrV94pSd26dds8bty4hb/+9a9X3XbbbQ0lqahzhMSINgAAAHbZ3Yohe6t+/fo7Ro0a9fUvfvGLQwtWHTnppJPyitr3jDPOWN25c+e2RxxxxIYaNWrkS1JGRoY6dOiwadasWVUyMzO3SVK/fv3W9ujRI7NDhw6bCvYbPHhw00WLFlXatm2b3XLLLUtC3qbiWMEw/P4kKyvLp02bluwyAAAAdsvMprt7VjJrmDlz5sKOHTt+m8waUtnMmTPrduzYsVnhdqaOAAAAAAEQtAEAAIAACNoAAABAAARtAAAAIACCNgAAABAAy/sBAADgf26q2XXv+8grcYnA119/vdr1119/sLubu2vo0KErLrzwwnV7fd7Ytdde22DQoEFr2rRp84NvoCxPwYK2mVWW9I6kSvF5xrn7jWb2qKSjJRWsl3ihu88wM5P0V0mnSNoUt38c9zVY0h/j/W9z98dC1Q0AAIBwli9fnv7b3/626euvvz63adOm27du3WrvvvvuD74JsjR27Nih9PQffsHjHXfcsXyvCy0DIaeObJXU2907SuokqY+Z9Yi3/d7dO8U/M+K2kyW1in+GSPq7JJlZHUk3SuouKVvSjWZWO2DdAAAACOTZZ5+t2bdv33VNmzbdLkmVKlXy448/fuM777xTtXv37q27du2aecMNN9SXpPnz51fo2bNn66ysrMxBgwY1kaSRI0ce2K9fv0N79+7dcty4cTVHjBjRoFOnTm0uvPDCQ9q1a9dWkgYOHNhs6tSplRctWpRR0GefPn0Ozc/PV25ubsUuXbq06du376GtW7duN2HChOqhbmuwoO2R7+KrFeKfkr4dZ4Ckx+PjpkiqZWYNJZ0kaZK7r3H3tZImSeoTqm4AAACEs3Tp0ooNGzbcJkkTJkyonp2dndm7d++WI0aMaDxx4sT506dPz33vvfeqL1q0KOPmm29uOGzYsOXTpk3L3bJli73yyisHSFJGRoa/+eab84444oiNb7zxRs2PP/74y2HDhq0s+Jr2AvXq1dvx3nvvzZk+fXpuw4YNt7/44os1JGnNmjUZzz///IKnn356wahRow4KdVuDztE2s3RJ0yW1lPSAu39kZv8n6XYzu0HSG5JGuPtWSQdLWpRw+OK4rbj2wucaomgkXE2aNAlwa7AnGrw1o8z7XH5spzLvEwAAlK9GjRptmzt3bmVJ6t+//4b+/fvntm/fvu3SpUsr9u3bt6Uk5eXlpX/11VcVv/rqq0q9evXaKElZWVmbvvzyy8rp6emelZW1UZLmzp1bqV27dpvS0tJ0+OGHb61WrdqOxHOtWLEi4+KLL26Sl5eXsXLlygpdunTZ1K5duy2ZmZmbK1SooBYtWmzLy8v74dyTMhI0aLv7DkmdzKyWpPFm1l7SNZKWS6oo6WFJf5B0Sxmc6+G4P2VlZe1/3yufYp70gQF6nR+gTwAAUJ4GDhyYd9RRRzW48sorVzVr1mz79u3bJUlt2rTZ9OKLLy448MADd+Tn5ystLU3Nmzff+s4771Q788wz10+bNq3qRRddtHru3LmV0tLSXJJatWq19csvv6yyc+dOzZo1q9LGjRu/F5pHjx5d55RTTskbNmzYt4MHDz7EPYqIZrYrK7q7hbqt5bLqiLuvM7O3JPVx9z/HzVvN7BFJV8XXl0g6JOGwxnHbEknHFGqfHLRgAACAn6rdrBiytxo0aLBj1KhRX5955pmHmpmnpaXpN7/5zYoOHTps6devX4udO3eqYsWK/sorr8y74YYblp1//vnN77777oZt2rTZfPLJJ383d+7cSgV9NWnSJP/YY49d37lz5zaHH374plq1auUnnuukk05af+GFFzZ/6aWXalapUqXcB2KtINmXecdm9SRtj0N2FUmvS7pb0nR3XxavMnKfpC3uPsLM+kq6TNGqI90ljXT37PjDkNMldYm7/lhSV3dfU9y5s7KyfNq0aUFuF0rnjTdblHmfx/VmRBsAsP8xs+nunpXMGmbOnLmwY8eO3yazhh9r69atVqlSJf/0008r/fa3vz3k7bffnlfeNcycObNux44dmxVuDzmi3VDSY/E87TRJz7j7RDN7Mw7hJmmGpF/H+7+sKGTPU7S830WS5O5rzOxWSVPj/W4pKWRj3zDjobZl3udxvcu8SwAAkOKGDx/e6KOPPjpgy5YtaQ888MDXya4nUbCg7e6fSupcRHuRccmjofWhxWwbLWl0mRYIAACAlDdq1Kglya6hOHwFOwAAABAAQRsAAAAIgKANAAAABFAuy/sBAAAgNXR4rEPXve3js8GfFblEYNeuXTPHjx8/v0mTJvmSNGrUqAO//vrrihdffPHqNm3abCvqmD//+c91r7rqqpRcEYURbQAAAJSLAQMGrB0zZkztguvPPfdc7fPPP39NcSFbkh599NF65VNd2SNoAwAAoFycd955aydMmFBbktasWZO2cuXKCrfcckvDqVOnVt65c6cGDx58SPfu3Vv37Nmz9fz58yvcfffd9b766qvK2dnZmRMmTKienZ2deckllzTOysrKHDRoUBNJysnJqdKtW7fMTp06tSlomzhxYvVevXq1OuGEE1pkZma2+8c//lG7V69erTp06NB2+fLl6ZI0YsSIBt26dcvMysrKzMnJqbJ161br3bt3y+zs7Mzs7OzMTZs22bJlyzKOP/74Fj169Gjdv3//5vn5+cXfuCIQtAEAAFAuWrRosX3r1q22dOnSjLFjx9Y6+eST1xVsGzt2bM3atWvv+Oijj+bcdtttS26++eaGf/jDH1Y1b958S05OTm7//v03SNLAgQPXTZs2LffTTz+tunr16vR27dpt+eijj3JnzJjx5ZIlSyp89tlnlSRp586dmjRp0vxLL7105TPPPFPnvffem3vmmWeufvrpp2tNnTq18pw5cypPnTo1d9y4cQuuueaaRvPmzatYpUqVnTk5OblTpkzJrVq1qt94440NLr/88pVTpkyZ06FDh81PPPFE7WJuWpGYow0AAIBy079//7Vjxoyp9dprr9W85557ltx2220NJGnWrFmVX3755VoffPBBdXdXo0aNipxO0qNHj02S1KBBg22rV69O37BhQ4Xf/e53h2zevDlt0aJFlb755psKknTYYYdtlqSDDz54e/v27TdLUuPGjbcvXLiw4syZM6tMnz79gOzs7ExJSk9P98MOO2xrjx49vhswYEDzJk2abLvvvvuW5ObmVp4+fXq12267TVu2bLGzzz579Z7cVoI2AAAAys1555239swzz2yxfft269y585aC9rZt224ZMGDA2j/96U/LpOir1Ys6Pi3tfxMy3F0jR46sN2zYsOWnnXbaht69e7d0d5Mks/8dnnjZ3dWhQ4ctPXr02DB27NivC861efNmu/baa1emp6frnHPOaTpp0qQDWrVqteWMM85Y16dPn+9Kqqk4BG0AAADsUtyKIWWlZcuW23fu3KmTTjppXWL7Oeeck/fGG2/U6N69e2sz01lnnbXmd7/73bctWrTYctJJJ7UYPnz48qL6GzBgQN5VV13V5O9///uW6IvGd6979+6bW7ZsubVbt26ZaWlpfuyxx64/99xz11500UXN0tPTVbVq1R09e/bc1Llz582DBg1qdtNNNzWSpHvuuWfxUUcdtam0t9VKW1AqycrK8mnTpiW7jJ+0e8/qV+Z9Dh87scz7BAAg2cxsurtnJbOGmTNnLuzYsWNKLqG3L5g5c2bdjh07NivczochAQAAgAAI2gAAAEAABG0AAAAgAII2AAAAEABBGwAAAAiAoA0AAIBy1blz5zZXXXVVw2TXERrraAMAAGCX2W3adt3bPtp+ObvYtbjnzZtXoWHDhtvee++96pKW7e259mWMaAMAAKDcPPnkk7XPPffcNS1bttzyySefVL7nnnvqdejQoW2PHj1aP/7447VmzZpVqXPnzm26d+/e+txzz20qSddff3397OzszHbt2rUdP358DUkaOHBgs3PPPbdp9+7dW5911llNf//73zfs1KlTmyFDhjSWpGXLlmUcf/zxLXr06NG6f//+zfPz8/XGG29UO/zww9t079699bBhwxpJ0rhx42p07do1s3Pnzm0eeuihOmV5WxnRBgAAQLl54403al599dXz6tatmz9mzJja7777bvW33347t06dOjt37NihkSNH1j3rrLNWjxgxYtWOHTskSVdfffWqW2+9dcWSJUsyTjvttBann376ekk68sgjN4wZM+brzp07tzn11FPz/vSnPy1r3759261bt9qNN97Y4PLLL1/Zv3//Ddddd12DJ554ovaMGTOqXHfddcvOOuusvB07dmjnzp264447Gn3wwQe5GRkZnp2d3ebiiy9ek5FRNhGZoA0AAIByMX/+/Apz5sypcuKJJ7Z0d23YsCH9/vvv/2bIkCFN3F033HDDsgsvvHDNiBEjGvXv37/5iSeeuP6yyy5b/eCDD9YZO3bsgWlpaVq1alWFgv66du26WZLq16+/LSsra5Mk1atXb/vatWvTcnNzK0+fPr3abbfdpi1bttjZZ5+9evjw4Sv/+Mc/NnryySfrnHfeeWt69eq18auvvqp01FFHtZak9evXpy9dujSjSZMm+WVxewnaAAAAKBdPPvlk7TvvvHPRRRddtFaSzj///CaVK1f2cePGLZw0aVK12267reEjjzzy9UMPPbRYklq2bHnY//3f/61++OGH68+ePXvWsmXLMnr16tWmoD8z84TLu87j7taqVastZ5xxxro+ffp8J0lbt2617du36/HHH/9my5Ytdvjhh7edPXv2F4ceeuiWd955Z07lypV969atVqlSpV197i2CNgAAAHYp6YOMe+uFF16o/dJLL80ruN67d+8NvXr1ate1a9fvtm3bZrfccsuSp556qtaDDz54kCQdc8wxeenp6erWrduGrKysNl27dt1YtWrVnaU512233bZs0KBBzW666aZGknTPPfcsnjx58gETJkyovWPHDjvnnHNWp6en69prr1125JFHtk5LS/MDDzww/+WXX15QVrfX3MsstO8zsrKyfNq0acku4yft3rP6lXmfw8dOLPM+AQBINjOb7u5Zyaxh5syZCzt27PhtMmtIZTNnzqzbsWPHZoXbWXUEAAAACICgDQAAAARA0AYAAAACIGgDAAAAARC0AQAAgAAI2gAAAChXEydOrN61a9fMbt26Zfbr1+/QVatWpSdu/+abbzJ+97vfNUpWfWWFdbQBAACwywO/frPr3vYx9MHexa7FvWLFivRhw4YdMnny5DmNGjXKf+ihh+pccsklTV544YWvJGnnzp1q3Lhx/n333bd0b+tINka0AQAAUG7GjRtXs2/fvusaNWqUL0m/+tWv1nzyySfVTj/99GYXXHBBk169erV69913q/bp0+fQpUuXZhxzzDEtC4494ogjWq9Zsybt+uuvr5+dnZ3Zrl27tuPHj6+RvFtTMoI2AAAAys3SpUsrNmrUaFtiW506dfJXr15doUuXLps++OCDuQ0aNMiXpEaNGuVXqFDBv/766wpffPFFxbp1626vU6fOzquvvnpVTk5O7qRJk+becccdDZNzS3aPqSMAAAAoNw0bNtw+f/78Soltq1evzmjWrNnWnj17biy8/3nnnbf6kUceqbNx48a0c889d40kPfjgg3XGjh17YFpamlatWlWhvGrfU4xoAwAAoNycccYZ61566aVaS5cuzZCkhx56qE7nzp03pqene1pamhfe/+yzz8577bXXar711ls1zjjjjDxJevjhh+tPmTIl99lnn53v/oND9hmMaAMAAKDcNGjQYMef//znRaeeemoLM9NBBx20ffTo0V8PHTr0kKL2r1y5srds2XJLWlqaV6gQDV5369ZtQ1ZWVpuuXbturFq16s5yvQF7gKANAACAXUpaMaSs9O/ff0P//v1zE9ueffbZhQWXMzMzt7366qsLCq6npaX5xRdfvLrg+pgxY74JXWNZIGgDAABgn3X++ec3Wb9+ffpRRx21Kdm17CmCNgAAAPZZ//73v1Ni9LoofBgSAAAACICgDQAAAARA0AYAAAACIGgDAAAAAfBhSAAAAOxy71n9uu5tH8PHTixyicDvvvvOevfu3VqSZs2aVfWwww7bJEkvvvjivPr16+8oTd/jxo2rsWnTprRBgwata9++fdvPP/989t7WGwpBGwAAAOXigAMO8JycnFxJat++fduCy3vijDPOWF/2lYVB0AYAAEBSPPDAA3Uee+yxet99913a0KFDVwwdOnTNsGHDGs2fP7/S2rVrMySpb9++65599tk69erV2/7SSy8tGDly5IHfffdd2rXXXrsq2fXvDnO0AQAAkBSDBg1al5OTk5uTk/PlAw88UL+gvU2bNpvfeeeduTVr1szftm2b5eTk5G7bts2++OKLismsd08xog0AAICkGD9+fI1Ro0bVd3d98803lQvaO3bsuFmSGjZsuL1Tp067Lq9evTqlsmtKFQsAAID9x913393www8/zDUzNW/evENBu5mpqMvuXr4F7iWCNgAAAHYpbsWQEPr167e2R48emR06dNhUo0aN/PI6b3mxVHtlUBpZWVk+bdq0ZJfxk3bvWf3KvM/hYyeWeZ8AACSbmU1396xk1jBz5syFHTt2/DaZNaSymTNn1u3YsWOzwu18GBIAAAAIgKANAAAABEDQBgAAAAIgaAMAAAABELQBAACAAFjeDwAAALssHvFu173to/FdRxa7RGBubm7FK664ovGrr766YG/Ps69jRBsAAAAIgKANAACAcnf99dfXz87OzmzXrl3b8ePH15CkgQMHNjvzzDOb9uzZs3Xfvn0Pzc/P16JFizK6d+/eumvXrpl9+vQ5ND8/X7m5uRW7dOnSpm/fvoe2bt263YQJE6pL0jvvvFO1YN8bbrihviTdc8899Tp06NC2R48erR9//PFakjRixIgG3bp1y8zKysrMycmpEuo2ErQBAABQ7q6++upVOTk5uZMmTZp7xx13NCxoz87O3vjBBx/Madq06dYnn3yyVr169Xa89957c6ZPn57bsGHD7S+++GINSVqzZk3G888/v+Dpp59eMGrUqIMkacSIEY0nTpw4f/r06bnvvfde9UWLFmU899xztd9+++3cKVOmzDnvvPPWTZ06tfKcOXMqT506NXfcuHELrrnmmkahbiNztAEAAFDuHnzwwTpjx449MC0tTatWrapQ0N69e/dNUhS458yZU3nFihUbL7744iZ5eXkZK1eurNClS5dN7dq125KZmbm5QoUKatGixba8vLx0Sfryyy+r9O3bt6Uk5eXlpX/11VcV77zzzsVDhgxp4u664YYbls2cObPK9OnTD8jOzs6UpPT09GBfk07QBgAAQLl7+OGH68+ePXvWsmXLMnr16tWmoH3q1KlVjzzyyE1Tp06t1q1bt42jR4+uc8opp+QNGzbs28GDBx/iHuViM9sVkN3dJKlNmzabXnzxxQUHHnjgjvz8fKWlpWnTpk02bty4hZMmTap22223NbzqqqtW9OjRY8PYsWO/lqStW7daqNv4kw/ai0e8G6TfxncdGaRfAACAkEpaMaQsuLvS09PVrVu3DVlZWW26du26sWrVqjsLtk+fPr3qEUcc0bp27dr5999//5KpU6dWufDCC5u/9NJLNatUqVLi6PPdd9+9pF+/fi127typihUr+iuvvDJv8ODBTRctWlRp27Ztdssttyzp3r375pYtW27t1q1bZlpamh977LHr77rrruUhbutPPmgDAACg/MyfP79i/fr1t48ePXpRUduvvPLKld26ddtScL1nz56b58yZ80Xh/QqWB6xZs+bOnJycXEk68sgjN3344YdzEvd79tlnFxY+9vbbb19+++23BwnXiQjaAAAAKBfjxo2rcfPNNx/86KOPfpXsWspDsFVHzKyymeWY2Uwzm2VmN8ftzc3sIzObZ2Zjzaxi3F4pvj4v3t4soa9r4vZcMzspVM0AAAAI54wzzlj/2Wefze7ateuWorY/++yzCxNHs1NdyOX9tkrq7e4dJXWS1MfMeki6W9J97t5S0lpJF8f7Xyxpbdx+X7yfzKydpLMlHSapj6S/mVl6wLoBAACAvRYsaHvku/hqhfjHJfWWNC5uf0zSafHlAfF1xduPMzOL2592963u/pWkeZKyQ9UNAAAAlIWgX1hjZulmNkPSSkmTJM2XtM7d8+NdFks6OL58sKRFkhRvz5N0YGJ7EccknmuImU0zs2mrVq0KcGsAAACA0gv6YUh33yGpk5nVkjReUpuSj9ircz0s6WFJysrKKvXC42O/ujtIPcPF8n4AACD13HTTTV3LoI9ilwjMzc2t2KNHj7atWrXasnnz5rRRo0Z9ffTRR28qTb8jR448sF27dluOP/74jUVtb9++fdvPP/98dmLbtdde22DQoEFr2rRps23PbsXeK5dVR9x9nZm9JekISbXMLCMetW4saUm82xJJh0habGYZkmpKWp3QXiDxmJ+Ue8/qF6Tf4WMnBukXAACgKN27d9/w6quvLnjzzTerXXvttQe///77c0tz3OWXX756T891xx13BF/GrzghVx2pF49ky8yqSDpB0mxJb0k6I95tsKQX4ssT4uuKt7/p0Vf/TJB0drwqSXNJrSTlhKobAAAA5eOII47YtGzZsopDhgxpLElTp06tPHDgwGaS1K5du7aDBg1qcvjhh7e57rrrGkjSsGHDGj311FM1d+zYoZ49e7bu1q1bZs+ePVutWbMmTZI2btyYduqppzZv37592wcffLCOJA0cOLDZ1KlTKyfj9oWco91Q0ltm9qmkqZImuftESX+QNMzM5imag/2veP9/STowbh8maYQkufssSc9I+kLSq5KGxlNSAAAAkMJeeeWV6t9++22ForatX78+449//OPyjz/++MtnnnnmwMRt6enpeu211+ZNnTo196STTsp75JFH6kjSihUrKv7zn//8ZurUqV/ef//9DfLz84vqutwEmzri7p9K6lxE+wIVsWqIu2+R9Iti+rpd0u1lXSMAAADK30cffVQ9Ozs7s1q1ajueeuqpeS+88EItSXJ3K9inZs2a+a1bt94mSZUqVdqZeHxeXl7aBRdc0HTZsmUV8/Ly0k899dS1ktS4ceOt9evX3yFJjRo12rZs2bKkfjlj0FVHAAAAgMK6d+++IScnJ/ett96aV7du3R1Lly6tKEnTpk2rUrBPtMpz0caPH1+jWbNmW6dOnZp7zjnnrC4I6EuWLKm0atWq9M2bN9vSpUsrNmzYMKlD2nwFOwAAAHYpacWQELp167Z506ZNaT179mzVtm3bUn0r5NFHH73xT3/6U8Njjjmmar169fIPOeSQbZLUoEGDbZdeemmTefPmVb788suXZ2QkN+oStAEAAFBuMjMzt7366qsLCq6npaXpzTffnFd4v8Rl+goub9261apVq7azefPm22fNmjW78DHz58+fVbjt2WefXVhmxe8hgjaCqFx7WLJLAAAA+5ExY8bUnDZtWrU77rhjWbJrKS3maAMAAGCfd+655+Z99NFHc2rWrLlz93vvGwjaAAAAQAAEbQAAACAAgjYAAAAQAB+GBAAAwC5vvNmi6972cVzv+cUuEZibm1uxR48ebTMzMzfn5+db586dN/7lL39ZesUVVxw8cuTIxQcccICX5hy5ubkVr7jiisaJK5hI0i9/+ctD9qSfkBjRBgAAQLnq3r37hilTpszJycnJrVq16s6rrrqq0ejRoxeVRTguq37KAiPaCKL35KEBev3BcpkAACCFpaWl6e67717Wpk2bw7Kzs6tNmjRp7s9//vPmo0eP/qZp06bb77vvvrrbt2+3yy677Ntzzjmn2YoVKypUrVp157hx4xZI0sqVKyv27dv30Llz51b+85//vKh///4bsrOzMydNmjR3X1idhBFtAAAAJE3lypV9+/btu75vfeDAgWsff/zx2pL0/PPP17rgggvW3n///XWPPfbY9VOmTJlzzjnnrL7//vvrSdKaNWsynn/++QVPP/30glGjRh2UrNtQHEa0AQAAkDSbN2+2ihUr7hp9Puecc9adcsopLS+55JI1aWlpatiwYf4XX3xRZcaMGdXGjBlTNz8/33r06LFBkjIzMzdXqFBBLVq02JaXl5eevFtRNII2AAAAkua6665rePLJJ6+bNm3aAZJUu3btnbVr186//fbb659++ulrJalNmzZbjjjiiO+GDh26Roq+in3hwoUVzGzXXGx3t6LPkDwEbQAAAOxS0oohZeWjjz6q3r1799Y7duywrl27brz33nuX9O7du3XB9l/84hdrf/Ob3zRbvHjxp5I0bNiwVeedd17TJ554oq4kXXnllSs6d+68OXSde4ugjSDOvKbsH1qflXmPAACgvGVmZm5bu3btzMLtOTk5uQWXL7roorUXXXTR2oLrVatW9fHjxy8sfEzB0n41a9bcWXB8Yj/JxochAQAAgAAI2gAAAEAABG0AAAAgAII2AAAAEMBP/sOQlWsPS3YJAAAA2A8xog0AAIBy1blz5zZXXXVVQ0kaNmxYo6eeeqpm4vbc3NyKffr0OTSxbeLEidWHDBnSuDzr3Fs/+RFtAAAA/E+Dt2Z03ds+lh/bqdi1uOfNm1ehYcOG2957773qkpbt7bn2ZQRtBPHZV98kuwQAALAPevLJJ2ufe+65a1599dUan3zySWVJGjNmTJ2//e1vB0nShAkT5hfsu2PHDg0aNKjJEUccsbFZs2bbZs+eXeWEE05o8c0331T697//vaBbt25bLrnkksYzZ86stmXLlrSHHnpoYXZ29uaePXtmStKqVasyjj/++Lx//OMfi5NxW5k6AgAAgHLzxhtv1Bw4cGDe+eefv2bMmDG1Jalp06bb3n333bmnnnrqur/+9a/1JGnHjh129tlnNzvmmGM2XHbZZaslKT8/3yZNmjT/1ltvXfzQQw/VlaT77rtv6dSpU3MffPDBhXfddVeDjIwM5eTk5L788svzDjrooO0jRoxYkazbyog2AAAAysX8+fMrzJkzp8qJJ57Y0t21YcOG9OOOO259VlbWRkk64ogjNj744IN1JWnmzJnV2rZtu+nSSy/d9Q2R7du33yRJzZs337Zu3boMSbrpppvqT548uYYkZWRkuCTl5+frrLPOanbXXXctbtGixfbyvp0FGNEGAABAuXjyySdr33nnnYvefffdue+9997cDh06bJo7d26ljz/+uKokTZkypWrLli23SlKXLl2+O/7449dfeumluz4AaWa7+nJ3LV++PH3y5Mk1pk+fnnv//fcvcneTpIsvvviQM888c+2xxx67qZxv4vcwog0AAIBdSvog49564YUXar/00kvzCq737t17w6WXXnrogAEDVv/sZz9rZWaaMGHC/FWrVmVI0vXXX79yxIgRDa688spGxx9//IbC/dWrV29HzZo1d2RnZ2dmZWV9J0UftvzPf/5Td/bs2VX/9a9/1TvttNPWXHvttatC3aaSmLsn47xBZWVl+bRp00q17wO/fjNIDUMf7F3mfd57Vr8y71OSho+dWPad3lRz9/vscZ95Zd8nAABJZmbT3T0rmTXMnDlzYceOHb9NZg2pbObMmXU7duzYrHA7U0cAAACAAAjaAAAAQAAEbQAAAGh/nE5cHnbu3GmSdha1jaANAADwE2dmyzdt2lQ52XWkmp07d9qqVatqSvq8qO2sOgIAAPATl5+ff9e8efPulXRAsmtJMTslfZ6fn39JURsJ2gAAAD9xXbp0eV7S80kuY7/D1BEAAAAgAII2AAAAEABBGwAAAAiAoA0AAAAEQNAGAAAAAiBoAwAAAAEQtAEAAIAACNoAAABAAARtAAAAIACCNgAAABAAQRsAAAAIgKANAAAABJCR7AKSrffkoYF6nh2oXwAAAKQCRrQBAACAAAjaAAAAQAAEbQAAACAAgjYAAAAQAEEbAAAACICgDQAAAARA0AYAAAACIGgDAAAAARC0AQAAgAAI2gAAAEAABG0AAAAgAII2AAAAEABBGwAAAAiAoA0AAAAEQNAGAAAAAiBoAwAAAAEQtAEAAIAAggVtMzvEzN4ysy/MbJaZXRG332RmS8xsRvxzSsIx15jZPDPLNbOTEtr7xG3zzGxEqJoBAACAspIRsO98ScPd/WMzqy5puplNirfd5+5/TtzZzNpJOlvSYZIaSfqvmbWONz8g6QRJiyVNNbMJ7v5FwNoBAACAvRIsaLv7MknL4ssbzGy2pINLOGSApKfdfaukr8xsnqTseNs8d18gSWb2dLwvQRsAAAD7rHKZo21mzSR1lvRR3HSZmX1qZqPNrHbcdrCkRQmHLY7bimsvfI4hZjbNzKatWrWqrG8CAAAAsEeCB20zO0DSs5KudPf1kv4uqYWkTopGvO8ti/O4+8PunuXuWfXq1SuLLgEAAIAfLeQcbZlZBUUh+0l3f06S3H1FwvZ/SJoYX10i6ZCEwxvHbSqhHQAAANgnhVx1xCT9S9Jsd/9LQnvDhN1Ol/R5fHmCpLPNrJKZNZfUSlKOpKmSWplZczOrqOgDkxNC1Q0AAACUhZAj2j+TdIGkz8xsRtx2raRzzKyTJJe0UNKvJMndZ5nZM4o+5Jgvaai775AkM7tM0muS0iWNdvdZAesGAAAA9lrIVUfek2RFbHq5hGNul3R7Ee0vl3QcAAAAsK/hmyEBAACAAAjaAAAAQAAEbQAAACAAgjYAAAAQQNB1tFPBmdeE+RV8FqRXAAAApApGtAEAAIAACNoAAABAAARtAAAAIACCNgAAABAAQRsAAAAIgKANAAAABEDQBgAAAAIgaAMAAAABELQBAACAAAjaAAAAQAAEbQAAACAAgjYAAAAQAEEbAAAACICgDQAAAARA0AYAAAACIGgDAAAAARC0AQAAgAAI2gAAAEAABG0AAAAgAII2AAAAEABBGwAAAAiAoA0AAAAEQNAGAAAAAiBoAwAAAAEQtAEAAIAACNoAAABAAARtAAAAIACCNgAAABAAQRsAAAAIICPZBaD0KtceluwSAAAAUEoE7RTSe/LQQD3PDtQvAADATxdTRwAAAIAACNoAAABAAHsUtM0szcxqhCoGAAAA2F/sNmib2Rgzq2Fm1SR9LukLM/t9+NIAAACA1FWaEe127r5e0mmSXpHUXNIFIYsCAAAAUl1pVh2pYGYVFAXtUe6+3cw8bFkoypnXhFkk5rMgvQIAAPy0lWZE+yFJCyVVk/SOmTWVtD5kUQAAAECq2+0QqbuPlDQyoelrMzs2XEnl67Ovvkl2CQAAANgPlebDkAea2Ugz+9jMppvZXyXVLIfaAAAAgJRVmqkjT0taJWmgpDPiy2NDFgUAAACkutJ8uq6hu9+acP02MzsrVEHYPzTbMqbM+1xY5j0CAACEU5oR7dfN7Oz4y2rSzOxMSa+FLgwAAABIZaUJ2pdKGiNpq6RtiqaS/MrMNpgZq48AAAAARSjNqiPVy6MQAAAAYH9SbNA2szbu/qWZdSlqu7t/HK4sAAAAILWVNKI9XNG0kXuL2OaSegepCMVizW8AAIDUUWzQdvdL43/3my+nAQAAAMpLSVNHfl7Sge7+XNmXAwAAAOwfSpo6cmoJ21wSQRsAAAAoRklTRy4qz0IAAACA/Umx62ib2TAzu7iI9ovN7MqgVQEAAAAprqQvrDlP0uNFtD8h6ZdhygEAAAD2DyUF7Qx331640d23SbJwJQEAAACpr6SgnWZm9Qs3FtUGAAAA4PtKCtp/kvSSmR1tZtXjn2MkTZT05/IoDgAAAEhVJa068riZrZJ0i6T2ipb0myXpBnd/pZzqAwAAAFJSSetoKw7UhGoAAABgD5U0dQQAAADAj0TQBgAAAAIIFrTN7BAze8vMvjCzWWZ2Rdxex8wmmdnc+N/acbuZ2Ugzm2dmn5pZl4S+Bsf7zzWzwaFqBgAAAMrKboO2mdU0s/vMbFr8c6+Z1SxF3/mShrt7O0k9JA01s3aSRkh6w91bSXojvi5JJ0tqFf8MkfT3+Px1JN0oqbukbEk3FoRzAAAAYF9VmhHt0ZLWSzoz/lkv6ZHdHeTuy9z94/jyBkmzJR0saYCkx+LdHpN0Wnx5gKTHPTJFUi0zayjpJEmT3H2Nu6+VNElSn9LdPAAAACA5Slx1JNbC3QcmXL/ZzGbsyUnMrJmkzpI+klTf3ZfFm5ZLKvgCnIMlLUo4bHHcVlx74XMMUTQSriZNmuxJeQAAAECZK82I9mYz61Vwxcx+JmlzaU9gZgdIelbSle6+PnGbu7ui9bn3mrs/7O5Z7p5Vr169sugSAAAA+NFKM6L9f5Iei+dlm6Q1ki4sTedmVkFRyH7S3Z+Lm1eYWUN3XxZPDVkZty+RdEjC4Y3jtiWSjinUPrk05wcAAACSZbcj2u4+w907SjpcUgd37+zuM3d3nJmZpH9Jmu3uf0nYNEFSwcohgyW9kNA+KF59pIekvHiKyWuSTjSz2vGHIE+M2wAAAIB9VrEj2mZ2vrv/28yGFWqXJBUKz0X5maQLJH2WMKf7Wkl3SXrGzC6W9LWiD1hK0suSTpE0T9ImSRfF51ljZrdKmhrvd4u7rynVrQMAAACSpKSpI9Xif6v/mI7d/T1FU02KclwR+7ukocX0NVrR6icAAABASig2aLv7Q/G/N5dfOQAAAMD+oaSpIyNLOtDdLy/7cgAAAID9Q0kfhpwe/1SW1EXS3Pink6SKwSsDAAAAUlhJU0cekyQz+z9Jvdw9P77+oKR3y6c8AAAAIDWV5gtrakuqkXD9gLgNAAAAQDFK84U1d0n6xMzeUrSKyFGSbgpZFAAAAJDqdhu03f0RM3tFUve46Q/uvjxsWQAAAEBq223QNrOj4otr439bm1lrd38nXFkAAABAaivN1JHfJ1yuLClb0WokvYNUBAAAAOwHSjN15NTE62Z2iKT7QxUEAAAA7A9Ks+pIYYsltS3rQgAAAID9SWnmaP8/SR5fTVP0hTUfB6wJAAAASHmlmaM9LeFyvqSn3P39QPUAAAAA+4XSzNF+LPG6mR1iZr939z+FKwsAAABIbaWao21m9czsN2b2rqTJkuoHrQoAAABIccWOaJtZdUk/l3SupNaSnpPU3N0bl1NtAAAAQMoqaerISkk5kv4o6T13dzM7vXzKAgAAAFJbSVNHrpFUSdLfJF1jZi3KpyQAAAAg9RUbtN39fnfvIWlA3PS8pEZm9gcza10exQEAAACparcfhnT3Be5+h7t3kJQlqYakl4NXBgAAAKSwPfpmSHf/3N2vc/eWoQoCAAAA9gc/5ivYAQAAAOwGQRsAAAAIoNigbWZvxP/eXX7lAAAAAPuHktbRbmhmPSX1N7OnJVniRnf/OGhlAAAAQAorKWjfIOl6SY0l/aXQNpfUO1RRAAAAQKorNmi7+zhJ48zsene/tRxrAgAAAFJeSSPakiR3v9XM+ks6Km6a7O4Tw5YFAAAApLbdrjpiZndKukLSF/HPFWZ2R+jCAAAAgFS22xFtSX0ldXL3nZJkZo9J+kTStSELAwAAAFJZadfRrpVwuWaAOgAAAID9SmlGtO+U9ImZvaVoib+jJI0IWhUAAACQ4krzYcinzGyypG5x0x/cfXnQqgAAAIAUV5oRbbn7MkkTAtcCAAAA7DdKO0cbAAAAwB4gaAMAAAABlBi0zSzdzL4sr2IAAACA/UWJQdvdd0jKNbMm5VQPAAAAsF8ozYcha0uaZWY5kjYWNLp7/2BVAQAAACmuNEH7+uBVAAAAAPuZ0qyj/baZNZXUyt3/a2ZVJaWHLw0AAABIXbtddcTMLpU0TtJDcdPBkp4PWBMAAACQ8kozdWSopGxJH0mSu881s4OCVgWUo3vP6lfmfQ4fO7HM+5SkBm/NKPM+lx/bqcz7BAAApQvaW919m5lJkswsQ5IHrQpAkZ70gQF6nR+gTwAAUJovrHnbzK6VVMXMTpD0H0kvhi0LAAAASG2lCdojJK2S9JmkX0l6WdIfQxYFAAAApLrSrDqy08weUzRH2yXlujtTRwAAAIAS7DZom1lfSQ8qmshpkpqb2a/c/ZXQxQEAAACpqjQfhrxX0rHuPk+SzKyFpJckEbQBAACAYpRmjvaGgpAdWyBpQ6B6AAAAgP1CsSPaZvbz+OI0M3tZ0jOK5mj/QtLUcqgNAAAASFklTR05NeHyCklHx5dXSaoSrCIAAABgP1Bs0Hb3i8qzEAAAAGB/UppVR5pL+q2kZon7u3v/cGUBAAAAqa00q448L+lfir4NcmfQagAAAID9RGmC9hZ3Hxm8EgAAAGA/Upqg/Vczu1HS65K2FjS6+8fBqgJQpBkPtS3zPo/rXeZdAgAAlS5od5B0gaTe+t/UEY+vAwAAAChCaYL2LyQd6u7bQhcDAAAA7C9K882Qn0uqFbgOAAAAYL9SmhHtWpK+NLOp+v4cbZb3AwAAAIpRmqB9Y/AqAAAAgP3MboO2u79dHoUAAAAA+5PSfDPkBkWrjEhSRUkVJG109xohCwMAAABSWWlGtKsXXDYzkzRAUo+QRQEAAACprjSrjuzikeclnbS7fc1stJmtNLPPE9puMrMlZjYj/jklYds1ZjbPzHLN7KSE9j5x2zwzG7En9QIAAADJUpqpIz9PuJomKUvSllL0/aikUZIeL9R+n7v/udA52kk6W9JhkhpJ+q+ZtY43PyDpBEmLJU01swnu/kUpzg8AAAAkTWlWHTk14XK+pIWKpo+UyN3fMbNmpaxjgKSn3X2rpK/MbJ6k7HjbPHdfIElm9nS8L0EbAAAA+7TSzNG+qIzPeZmZDZI0TdJwd18r6WBJUxL2WRy3SdKiQu3di+rUzIZIGiJJTZo0KeOSAQAAgD1TbNA2sxtKOM7d/dYfcb6/S7pV0Somt0q6V9Ivf0Q/RRX0sKSHJSkrK8t3s/suzbaMKYvT/8DCIL0CAAAgVZQ0or2xiLZqki6WdKCioLxH3H1FwWUz+4ekifHVJZIOSdi1cdymEtoBAACAfVaxQdvd7y24bGbVJV0h6SJJTysaid5jZtbQ3ZfFV0+XVLAiyQRJY8zsL4o+DNlKUo4kk9TKzJorCthnSzr3x5wbAAAAKE8lztE2szqShkk6T9JjkrrEc6p3y8yeknSMpLpmtljRV7kfY2adFE0dWSjpV5Lk7rPM7BlFH3LMlzTU3XfE/Vwm6TVJ6ZJGu/usPbuJAAAAQPkraY72nyT9XNG85w7u/t2edOzu5xTR/K8S9r9d0u1FtL8s6eU9OTewJ06ZOT/ZJQAAgP1QSV9YM1zRNI4/SlpqZuvjnw1mtr58ygMAAABSU0lztPfoWyOBVHXmNaVZTn7PfFbmPQIAgFRT9gkDSDGfffVNsksAAAD7IUatAQAAgAAI2gAAAEAABG0AAAAgAII2AAAAEABBGwAAAAiAVUeAFMKX6wAAkDoY0QYAAAACYEQbSCFtz16a7BIAAEApMaINAAAABEDQBgAAAAIgaAMAAAABELQBAACAAAjaAAAAQACsOpJCmm0ZE6TfhUF6BQAA+GljRBsAAAAIgKANAAAABEDQBgAAAAIgaAMAAAABELQBAACAAAjaAAAAQAAEbQAAACAAgjYAAAAQAEEbAAAACICgDQAAAARA0AYAAAACIGgDAAAAARC0AQAAgAAI2gAAAEAABG0AAAAgAII2AAAAEABBGwAAAAiAoA0AAAAEQNAGAAAAAiBoAwAAAAEQtAEAAIAACNoAAABAAARtAAAAIACCNgAAABAAQRsAAAAIgKANAAAABEDQBgAAAAIgaAMAAAABELQBAACAAAjaAAAAQAAEbQAAACAAgjYAAAAQAEEbAAAACICgDQAAAARA0AYAAAACIGgDAAAAARC0AQAAgAAI2gAAAEAABG0AAAAgAII2AAAAEABBGwAAAAiAoA0AAAAEQNAGAAAAAiBoAwAAAAFkJLsAAPune8/qV+Z9Dh87scz7BAAgFEa0AQAAgAAI2gAAAEAABG0AAAAggGBB28xGm9lKM/s8oa2OmU0ys7nxv7XjdjOzkWY2z8w+NbMuCccMjvefa2aDQ9ULAAAAlKWQI9qPSupTqG2EpDfcvZWkN+LrknSypFbxzxBJf5eiYC7pRkndJWVLurEgnAMAAAD7smBB293fkbSmUPMASY/Flx+TdFpC++MemSKplpk1lHSSpEnuvsbd10qapB+GdwAAAGCfU95ztOu7+7L48nJJ9ePLB0talLDf4rituPYfMLMhZjbNzKatWrWqbKsGAAAA9lDSPgzp7i7Jy7C/h909y92z6tWrV1bdAgAAAD9KeX9hzQoza+juy+KpISvj9iWSDknYr3HctkTSMYXaJ5dDnQD20vC27ya7BAAAkqq8R7QnSCpYOWSwpBcS2gfFq4/0kJQXTzF5TdKJZlY7/hDkiXEbAAAAsE8LNqJtZk8pGo2ua2aLFa0ecpekZ8zsYklfSzoz3v1lSadImidpk6SLJMnd15jZrZKmxvvd4u6FP2AJAAAA7HOCBW13P6eYTccVsa9LGlpMP6MljS7D0gAAAIDg+GZIAAAAIACCNgAAABAAQRsAAAAIgKANAAAABEDQBgAAAAIgaAMAAAABELQBAACAAAjaAAAAQAAEbQAAACAAgjYAAAAQAEEbAAAACICgDQAAAARA0AYAAAACIGgDAAAAARC0AQAAgAAI2gAAAEAABG0AAAAgAII2AAAAEABBGwAAAAggI9kFAMnWbMuYMu9zYZn3CAAAUg0j2gAAAEAABG0AAAAgAII2AAAAEABBGwAAAAiAoA0AAAAEQNAGAAAAAiBoAwAAAAEQtAEAAIAACNoAAABAAARtAAAAIACCNgAAABAAQRsAAAAIgKANAAAABEDQBgAAAAIgaAMAAAABELQBAACAAAjaAAAAQAAEbQAAACAAgjYAAAAQAEEbAAAACICgDQAAAARA0AYAAAACIGgDAAAAARC0AQAAgAAI2gAAAEAAGckuAEDpNdsypsz7XFjmPQIAAIkRbQAAACAIgjYAAAAQAEEbAAAACICgDQAAAARA0AYAAAACIGgDAAAAARC0AQAAgAAI2gAAAEAABG0AAAAgAII2AAAAEABBGwAAAAiAoA0AAAAEQNAGAAAAAiBoAwAAAAEQtAEAAIAAMpJdAID9U7MtY8q8z4Vl3mPqufesfmXe5/CxE8u8TwAAI9oAAABAEARtAAAAIACmjgD4yWM6BgAghKSMaJvZQjP7zMxmmNm0uK2OmU0ys7nxv7XjdjOzkWY2z8w+NbMuyagZAAAA2BPJnDpyrLt3cves+PoISW+4eytJb8TXJelkSa3inyGS/l7ulQIAAAB7aF+aOjJA0jHx5cckTZb0h7j9cXd3SVPMrJaZNXT3ZUmpEgCSqHLtYckuAQBQSskK2i7pdTNzSQ+5+8OS6ieE5+WS6seXD5a0KOHYxXHb94K2mQ1RNOKtJk2aBCwdwP5meNt3k11CqQ1tcHqAXvMC9AkASFbQ7uXuS8zsIEmTzOzLxI3u7nEIL7U4rD8sSVlZWXt0LAAAAFDWkjJH292XxP+ulDReUrakFWbWUJLif1fGuy+RdEjC4Y3jNgAAAGCfVe5B28yqmVn1gsuSTpT0uaQJkgbHuw2W9EJ8eYKkQfHqIz0k5TE/GwAAAPu6ZEwdqS9pvJkVnH+Mu79qZlMlPWNmF0v6WtKZ8f4vSzpF0jxJmyRdVP4lAwAAAHum3IO2uy+Q1LGI9tWSjiui3SUNLYfSAAAAgDLDV7ADAAAAARC0AQAAgAAI2gAAAEAABG0AAAAgAII2AAAAEABBGwAAAAiAoA0AAAAEQNAGAAAAAiBoAwAAAAEQtAEAAIAACNoAAABAAARtAAAAIACCNgAAABAAQRsAAAAIgKANAAAABEDQBgAAAAIgaAMAAAABELQBAACAAAjaAAAAQAAEbQAAACAAgjYAAAAQAEEbAAAACCAj2QUAAPZPb7zZosz7PK73/DLvEwBCYUQbAAAACICgDQAAAATA1BEAQBDHvfNt2Xfau+y7BIBQGNEGAAAAAiBoAwAAAAEQtAEAAIAACNoAAABAAHwYEsBPXrMtY8q8z4Vl3iMAINUwog0AAAAEQNAGAAAAAiBoAwAAAAEQtAEAAIAACNoAAABAAARtAAAAIACW9wOAFMJShACQOhjRBgAAAAIgaAMAAAABELQBAACAAAjaAAAAQAAEbQAAACAAgjYAAAAQAEEbAAAACICgDQAAAARA0AYAAAACIGgDAAAAARC0AQAAgAAI2gAAAEAAGckuAACApLqpZqB+88L0CyBlMKINAAAABEDQBgAAAAIgaAMAAAABELQBAACAAPgwJAAAqYIPbgIphaANAAii2ZYxZd7nwjLvEQDCYeoIAAAAEABBGwAAAAiAoA0AAAAEQNAGAAAAAiBoAwAAAAGw6ggAACh7LEUIMKINAAAAhMCINgDgJy3Eet8Sa36nFEbfEUjKjGibWR8zyzWzeWY2Itn1AAAAACVJiRFtM0uX9ICkEyQtljTVzCa4+xfJrQwAgPKTSqPvqVQrEEpKBG1J2ZLmufsCSTKzpyUNkETQBgAAe4UXBQjF3D3ZNeyWmZ0hqY+7XxJfv0BSd3e/LGGfIZKGxFczJeUGKKWupG8D9BsCtYZBrWGkSq2pUqdEraFQaxg/9Vqbunu9Mu4T+4BUGdHeLXd/WNLDIc9hZtPcPSvkOcoKtYZBrWGkSq2pUqdEraFQaxjUiv1VqnwYcomkQxKuN47bAAAAgH1SqgTtqZJamVlzM6so6WxJE5JcEwAAAFCslJg64u75ZnaZpNckpUsa7e6zklBK0KkpZYxaw6DWMFKl1lSpU6LWUKg1DGrFfiklPgwJAAAApJpUmToCAAAApBSCNgAAABAAQRsAAAAIICU+DJksZpYtyd19qpm1k9RH0pfu/nKSSyuRmT3u7oOSXUdpmFkvRd/8+bm7v57segqYWXdJs919vZlVkTRCUhdF30Z6h7vnJbXABGZ2uaTx7r4o2bXsTsKqQUvd/b9mdq6knpJmS3rY3bcntcBCzOxQST9XtLzoDklzJI1x9/VJLQwAkBL4MGQxzOxGSScrejEySVJ3SW9JOkHSa+5+exLL28XMCi9zaJKOlfSmJLl7/3IvqgRmluPu2fHlSyUNlTRe0omSXnT3u5JZXwEzmyWpY7zizcOSNkkaJ+m4uP3nSS0wgZnlSdooab6kpyT9x91XJbeqopnZk4r+pqpKWifpAEnPKfq9mrsPTl513xe/gOkn6R1Jp0j6RFHNp0v6jbtPTlpxwH7GzA5y95XJrgMoawTtYpjZZ5I6Saokabmkxgmjmx+5++HJrK+AmX2saJT1n5JcUdB+StGoodz97eRV90Nm9om7d44vT5V0iruvMrNqkqa4e4fkVhgxs9nu3ja+/LG7d0nYNsPdOyWtuELM7BNJXSUdL+ksSf0lTVf0OHjO3TcksbzvMbNP3f1wM8tQ9KVTjdx9h5mZpJn7yt+V9L/ngLi+qpJedvdjzKyJpBcKHsf7AjOrKekaSadJOkjRc8FKSS9Iusvd1yWtOJQLM2sg6UZJOyXdIOm3kgYqerfoCndflsTyvsfM6hRuUvSc1VlRLllT/lUBYTBHu3j57r7D3TdJml/wVrG7b1b0RLavyFL0BHWdpLx4lG2zu7+9r4XsWJqZ1TazAxU9oa6SJHffKCk/uaV9z+dmdlF8eaaZZUmSmbWWtE9Nb1A0vWmnu7/u7hdLaiTpb4qmOi1Ibmk/kBZPH6muaFS7ZtxeSVKFpFVVvILpdZUUjb7L3b/RvlfrM5LWSjrG3eu4+4GK3tlaG29LCWb2SrJrSGRmNczsTjN7Ip7mlLjtb8mqqxiPKhp0WaTo3dfNit6JeVfSg8krq0jfKvp/q+BnmqSDJX0cX95nmFmfhMs1zexfZvapmY0xs/rJrA2pgRHtYpjZR5KOdfdNZpbm7jvj9pqS3koc4dwXmFljSfdJWiGpv7s3SXJJRTKzhYpeqJiiUbefufsyMztA0nv7ykhxfD//VdKRiv5T6KLoP7BFki5395lJLO97Et8lKGJb1fjF4j7BzH6naKQtXdK9kgYoejHQQ9I4d785ieV9j5ldIeliSR8pehzc7e6PmFk9Sc+6+1FJLTCBmeW6e+aebksGMyvuudMkTXT3huVZT0nM7FlJcyVNkfRLRS+yz3X3rYXf6Uq2Qu8WfpP4f8A++C7ccEXTMH/v7p/FbV+5e/PkVvZDifezmf1T0Tvc/1D02Y2j3f20JJaHFEDQLoaZVXL3rUW015XUsODJYV9jZn0Vhddrk13Lnojfmq/v7l8lu5ZEZlZDUnNFI5uL3X1Fkkv6ATNr7e5zkl1HaZlZI0ly96VmVkvRlJdv3D0nqYUVwcwOk9RW0Yd1v0x2PcUxs9cl/VfSYwWP0Xi07UJJJ7j78Uks73vMbIektxUF68J6uHuVci6pWIUDqpldp2iUuL+kSftY0J7p7h3jy7e5+x8Ttn22r0zLK5AwOLRI0ZSXme5+aHKr+qFCQbvw42GfegGDfRNBGwBSnJnVVrQyzgBFc7Sl6N2tCYrmaK9NVm2Fmdnnkk5397lFbFvk7ockoawimdlsSYcVvKMZt10o6feSDnD3psmqrTAzu0XSPe7+XaH2looeA2ckp7KSmVl/SddKaubuDZJdT2FmtljSXxS9MBwqqYXHwangMyfJrA/7PuZoA0CKc/e17v4Hd28Tz9Gu4+5t3f0Pij4guS+5ScX/3/PbcqyjNF6U1Duxwd0flTRc0rZkFFQcd7+hcMiO2+dJeikJJZWKu09Q9HmC4yUp4bMx+4p/KPpMyQGSHpNUV9r14dMZySsLqYIRbQDYjxWer7svM7OL3P2RZNdRGilWayo9BlKp1pR5DCB5CNoAkOLM7NPiNklq7e6VyrOeHyvFQtY+VWsqPQZSqdaS7GuPAeyb+GZIAEh99SWdpGg5v0Qm6YPyL6d4uwlZ+9RyaalUq1LoMaAUqjXFHgPYBxG0ASD1TVT04bwZhTeY2eRyr6ZkKROylFq1ptJjIJVqTaXHAPZBBG0ASHHxFxUVt+3c4rYlSSqFrJSpNZUeA6lUq1LoMYB9E3O0AQAAgABY3g8AAAAIgKANAAAABEDQBpBSzOw+M7sy4fprZvbPhOv3mtmwH9n3MWY2sbTtZcXMapnZb8rrfACA8kHQBpBq3pfUU5LMLE3RN7UdlrC9p0q5GoCZpZd5dT9OLUm/2d1OAIDUQtAGkGo+kHREfPkwSZ9L2mBmtc2skqS2kj42s+PM7BMz+8zMRsfbZGYLzexuM/tY0i/MrI+ZfRlf//meFGJmJ5rZh2b2sZn9x8wOSDjHzXH7Z2bWJm6vZ2aTzGyWmf3TzL42s7qS7pLUwsxmmNmf4u4PMLNxcW1Pmpnt5e8NAFDOCNoAUoq7L5WUb2ZNFI1efyjpI0XhO0vSZ4qe2x6VdJa7d1C0lOn/JXSz2t27SHpe0j8knSqpq6QGpa0jDsh/lHR83Nc0SYlTVr6N2/8u6aq47UZJb7r7YZLGSSr4VrkRkua7eyd3/33c1lnSlZLaSTpU0s9KWxsAYN9A0AaQij5QFLILgvaHCdffl5Qp6St3nxPv/5ikoxKOHxv/2ybeb65Ha53+ew9q6KEoBL9vZjMkDZbUNGH7c/G/0yU1iy/3kvS0JLn7q/rhl2AkynH3xe6+U9KMhD4AACmCL6wBkIoK5ml3UDR1ZJGk4ZLWS3qkFMdvLIMaTNIkdz+nmO1b43936Mc9125NuPxj+wAAJBEj2gBS0QeS+kla4+473H2Nog8UHhFvy5XUzMxaxvtfIOntIvr5Mt6vRXy9uNBclCmSflZwDjOrZmatd3PM+5LOjPc/UVLtuH2DpOp7cG4AQAogaANIRZ8pWm1kSqG2PHf/1t23SLpI0n/M7DNJOyU9WLiTeL8hkl6KPwy5soRzHmdmiwt+JLWUdKGkp8zsU0XTV9rspu6bJZ1oZp9L+oWk5ZI2uPtqRVNQPk/4MCQAIMXxFewAUE7ilU92uHu+mR0h6e/u3inJZQEAAmHOHwCUnyaSnonX/94m6dIk1wMACIgRbQAAACAA5mgDAAAAARC0AQAAgAAI2gAAAEAABG0AAAAgAII2AAAAEMD/BwVzU8bZSDZcAAAAAElFTkSuQmCC\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_og.transpose()[wl15]\nlanguage_fractions_df_T.nsmallest(10,3).nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Number of Audio Clips\", xlabel='Word Length', title='Audio Clips v/s Word Length (1 to 15) for top (41 to 50) languages')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\nplt.savefig('plots/stacked/audio_clips_vs_word_length_top41-50.png')"},{"cell_type":"code","execution_count":225,"metadata":{},"outputs":[{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}],"source":"language_fractions_df_T = language_fractions_og.transpose()[wl15]\nlanguage_fractions_df_T.nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Number of Audio Clips\", xlabel='Word Length', title='Audio Clips v/s Word Length (1 to 15) for top (1 to 10) languages')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small')\n\nplt.savefig('plots/stacked/audio_clips_vs_word_length_top1-10.png')"}],"nbformat":4,"nbformat_minor":2,"metadata":{"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":3},"orig_nbformat":4}} \ No newline at end of file diff --git a/eda/plot2_violin2.ipynb b/eda/plot2_violin2.ipynb new file mode 100644 index 0000000..008e3ce --- /dev/null +++ b/eda/plot2_violin2.ipynb @@ -0,0 +1 @@ +{"cells":[{"cell_type":"code","execution_count":33,"source":["import matplotlib.pyplot as plt\n","import seaborn as sns\n","import pickle\n","import pandas as pd\n","import numpy as np\n","from pathlib import Path\n","import collections\n","from collections import Counter\n","from tqdm import tqdm\n","# import plotly.express as px\n","base = Path(\"/mnt/disks/std750\")\n","data = pd.read_csv(base / \"data\" / \"csvs\" / \"new4.csv\")\n","main_data = pd.read_csv(base / \"data\" / \"csvs\" / \"new3.csv\")\n","main_data = main_data[main_data[\"counts\"] >= 5]"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":34,"source":["iso_code_to_name = {'ab':'Abkhaz',\n","'ar':'Arabic',\n","'as':'Assamese',\n","'br':'Breton',\n","'cnh':'Hakha Chin',\n","'ca':'Catalan',\n","'cs':'Czech',\n","'cv':'Chuvash',\n","'cy':'Welsh',\n","'de':'German',\n","'dv':'Divehi',\n","'el':'Greek',\n","'en':'English',\n","'es':'Spanish',\n","'eo':'Esperanto',\n","'eu':'Basque',\n","'et':'Estonian',\n","'fa':'Persian',\n","'fr':'French',\n","'fy-NL':'Frisian',\n","'ga-IE':'Irish',\n","'ia':'Interlingua',\n","'id':'Indonesian',\n","'it':'Italian',\n","'ja':'Japanese',\n","'ka':'Georgian',\n","'ky':'Kyrgyz',\n","'lv':'Latvian',\n","'mn':'Mongolian',\n","'mt':'Maltese',\n","'nl':'Dutch',\n","'or':'Oriya',\n","'pa-IN':'Punjabi',\n","'pl':'Polish',\n","'pt':'Portuguese',\n","'rm-sursilv':'Sursilvan',\n","'rm-vallader':'Vallader',\n","'ro':'Romanian',\n","'ru':'Russian',\n","'rw':'Kinyarwanda',\n","'sah':'Sakha',\n","'sl':'Slovenian',\n","'sv-SE':'Swedish',\n","'ta':'Tamil',\n","'tr':'Turkish',\n","'tt':'Tatar',\n","'uk':'Ukrainian',\n","'vi':'Vietnamese',\n","'zh-CN':'Chinese'}"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":35,"source":["data = pd.read_csv(base / \"data\" / \"csvs\" / \"final_short-v2.csv\")\n","main_data = pd.read_csv(base / \"data\" / \"csvs\" / \"final-v2.csv\")\n","main_data = main_data[main_data[\"counts\"] >= 5]"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":36,"source":["main_data.shape"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["(350789, 4)"]},"metadata":{},"execution_count":36}],"metadata":{}},{"cell_type":"code","execution_count":37,"source":["languages = main_data['language'].unique()\n","main_data['wl'] = main_data['word'].str.len()\n","wordlengths_counts = dict(main_data[['counts','wl']].groupby('wl').sum().reset_index().values.tolist())\n","language_fractions = {}\n","for l in tqdm(languages):\n","\tlanguage_fractions[l] = dict(main_data[main_data['language']==l].groupby('wl')['counts'].sum().reset_index().values)\n","\n","for l in tqdm(language_fractions):\n","\tfor j in wordlengths_counts:\n","\t\tif j not in language_fractions[l]:\n","\t\t\tlanguage_fractions[l][j] = 0\n","language_fractions_df = pd.DataFrame(language_fractions)\n","language_fractions_df = language_fractions_df.rename(iso_code_to_name, axis=1)"],"outputs":[{"output_type":"stream","name":"stderr","text":["100%|██████████| 53/53 [00:01<00:00, 48.05it/s]\n","100%|██████████| 53/53 [00:00<00:00, 114882.75it/s]\n"]}],"metadata":{}},{"cell_type":"code","execution_count":38,"source":["low = [\"mt\",\"br\",\"rm-sursilv\",\"sl\",\"sah\",\"lv\",\"cv\",\"ga-IE\",\"ka\",\"cnh\",\"ha\",\"rm-vallader\",\"vi\",\"as\",\"gn\",\"ab\",\"or\"]\n","medium = [\"eu\",\"nl\",\"pt\",\"tt\",\"cs\",\"uk\",\"et\",\"tr\",\"mn\",\"ky\",\"ar\",\"fy-NL\",\"sv-SE\",\"id\",\"el\",\"ro\",\"ia\",\"sk\",\"zh-CN\",\"dv\"]\n","high = [\"de\",\"en\",\"fr\",\"ca\",\"rw\",'es',\"ru\",\"it\",\"pl\",\"fa\",\"eo\",\"cy\",\"ta\"]"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":39,"source":["iso_code_to_name['gn'] = \"Gaurian\"\n","iso_code_to_name['ha'] = \"Hausa\"\n","iso_code_to_name['sk'] = \"Slovak\"\n","high_lang = [iso_code_to_name[i] for i in high]\n","low_lang = [iso_code_to_name[i] for i in low]\n","main_data_lang = main_data.replace({'language':iso_code_to_name})"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":40,"source":["medium_lang = [iso_code_to_name[i] for i in medium]"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":41,"source":["## Unique keywords\n","\n","fig, ax = plt.subplots(figsize=(15,10))\n","sns.violinplot(x=\"language\",y=\"wl\",data=main_data_lang.loc[main_data_lang['language'].isin(low_lang),:],bw=1, ax=ax)\n","ax.tick_params(axis='x', rotation=30)"],"outputs":[{"output_type":"display_data","data":{"text/plain":["
"],"image/svg+xml":"\n\n\n \n \n \n \n 2021-08-21T19:47:07.620274\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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CFEQ5Zh/kcuhisXgEKI9wohfkoI8RUhRE8I8ekJx7wuhJBjf96+6rYuOyZPdpfNAWSnTC6K559/vuomEELIRDjWVQtzAInCqeD//P0Avg/A5wC4M477ZwB+YuhxdJmNImaxbA7gMnTG/A6EEEKIvjAHkCiqEIC/LKX8JQAQQnwUwI0px92XUn7u6ppVjmWYKJr8HbgPoH4sw4CyDN+BEEJ0ZRnGOpPh708UVx4CKqU0P14PZk8UTW67gvsAEkIIIWbBsa5aGAJKFDoXgfm/CSEiIcSxEOKjQojHq24Q0QfmAOrHMnwHQgghZNlZBiOAnI8qQkCL8EvIcgTfAvBNAH4cwG8JIb5FSnk8frAQ4ocB/DAAPPbYY1fZTlIRy5YDuAwsw4BCEUsIIZcH+9hq4e9PFFo6gFLK/0xK+c+llL8lpfwwgD8F4BEA/9cpx39YSvl+KeX7b968eaVtJdWwbAJwGVzMZWAZRCwhhOgKBUi18PcnCi0F4DhSymcBvADgO6pui4I3UbUsmwBchutpGb4DIYQQsqxwnCYKIwRgH9n/owW8iaqFAlA/lsE9W4bzQAghusI+tlr4+xOFEQJQCPHNAJ4E8LtVt0XBm6halk0AMgRUD5ZBxBJCiK5w7lQt/P2J4sqLwAgh6sg2ggeARwGsCSF+oP/43wL4owD+PIB/DeAeMuH3YwDeAPCzV9rYCbCErh4Mi74kSSpsycVg8vVkctsJIYRcHRwvqoW/P1FUUQX0IQC/OPacevwuAG/2j/lHADYA7AP4BIC/IaU8uZomzsfkm8jktiuWzQFchnOyDPA8EEIIWXZMH+sODg5gWRY2NjaqboqxXLkAlFK+DmBenNUfv4KmnAvTbx7A7HA3bgRPLgOT7wlCCNGdZRjrTB4n1HzJ5O8AAB/6Sx9Co9HA//Qz/1PVTTEWXfcB1J5l6MRMZtkcQJNFrOkDCSGEkKthGeZOy/AdTOfw6BCHR4dVN8NojCgCoyMmT9iXgeG8P+YA6gG/AyGEkFmwj60Wzl2JggKwJMrtWIZOzOTvsGxFYJahU14GJ3AZvgMhhOiKyfOOZYCFDImCArAk6qYxecK+DJPcZQsBZWdMCCFk2eFYVy3q91+GeSA5HxSAJVkmB9BkkiSB6r9MFuMKXk96wPNACCFkWeEYRxQUgCWhfa4HvV4Pnp0pQIaA6sEy3BNcFSWEkMtjGcYJk+HvTxQUgAuyDBN2k0mSBO4SCcBl6JQpngghhMyCc6dqUb//Msw5yPmgACwJQ0D1IEkSeP1NTJYhB9Dk78B7gRBCCNEf5gASBQXggpi8irUME/ZerwdniRxAogfLcG8QQoiumDx3Wgb4+xMFBeCCLMNNZPIKUJIkcCxAiOUQgLye9GAZvgMhhOgKF9mqhb8/UVAAloRFYPQgSRLYQsK2hNHhk4plEIC8JwghhMyC40S1MAeQKCgAS7JMAtDk79Dr9WBZgG0JOoAVs0yumcn3BCGE6A772GphDiBRUACWRE3UTZ6wK0zuAAYOIENAdWEZBnaT7wlCCNGdZYjYMZllmGuQi4ECsCTLJABNJo5j2HQAtUAJP8tid0IIIWS5MXmh0OS5BrlYOGMryTIJQJMdm14SwxaCDqBGmHw9KZbhOxBCiK5wrKuWZfj9ycVAAViSZcoBNHkVK0mSLAdQZG6g6SxDp8x7ghBCyCyWYZwwGf7+REEBWBI1UWcce7XEiQoBXY5zQQFYLcu0sEMIIbqyDOO1yfD3JwoKwJKom2cZJuwmk8TZPoC2tRwOIDvlaqHwI4QQsuxwrCMKCsCSLJNTYPJ3SHpJ5gAKuRTiyeRzocIml2FRhCGghBByeSzDOGEyg30AK24IqRwKwJIsUxEYkye7SZzAEmY7gMOibxmuJ5NF7DL8/oQQojsmjxPLAMc6oqAALAlzAPUgSRI4toAtpLFVQIc74mXolE0e2JfJ2SeEEF1ZhrHO5MXzZfj9ycVAAViSZcoBNHmymyRJXgTGVAdw+BpahgUFk68ndS5MHtgJIUR3lmHuZDKD39/c8ZpcDBSAJWEIqB7ESQJHAI4lkMRR1c1ZiGHRtwzXk8kC0OS2E0KIKSxDX2vyd1iGuQa5GCgAS7JMDqCppGmKXi+lA6gJyxA+yfuZEEIuDzU8sK+tFv7+REEBWJJlcgBNnbCrnD/HBhwKQG0w9XoChiujmfsdCCFEd5ZhrDMZ/v5EQQFYknSJHEBTQ0CV4FMOoKlFYBgCqg+q7abeE4QQYgLLMNaZTP77mztckwuCArAkatLOVZTqyB1ASxgdAjp8DS3D9WSyAOSkhBBCLh+Tx4llYBnmGuRioAAsyTJtA2FqRzzsAC5LCOgyCBBTrydgcD+b/B0IIcvJCy+8gGeffbbqZpyTrG9dhrHOZPLfn8Eu1x6n6gaYBovAVM9oCKhAvAQhoMuwoGDyPcFtIAghuvKX//JfBgB88pOfrLgl52cZxjqT4e9PFHQAS5L2zHcATZ/kKgHo9B3AZcgBNPl6UpjsnpksXgkhxBTY11YLf3+ioAAsCXMAq2dYANo20OulRnZqFID6wCqghBBy+SzDWGcyy/D7c5y+GCgAS7IMAtD0m2c8BxAw0wVkFVB9WIYQUJN/f0LI9WAZxjqTMXnuquBYdzFQAJakl/YFoIGCQ2H6zZM7gHZWBXT4OZMY7ohNFLDjmDywm9x2hen3NSFk+VmGvtZklqGOBce6i4ECsCTq5lmGCbupjOYAZo5NFEVVNmkhlsUBVK6Zyd9hGaqAmtx2Qsj1YBkcKJNR43SapsaOGSbPNXSCArAkSviZ3ImZetMrRgSgPfqcSSyLA6iuJ5OvK3UuGAJKCCGXh8lzp2VgGeYdHOsuBgrAkixDFVB185g62Z2UA2i6ADT5elKYvCq3DEVgTP79CSHLjepa2U9Vy7DoM/VcmDxO6wQFYEmSXt8BTMydsJt+8wxyAAcC0MQQ0OGO2GQBuEwhoCZj+n1NCFle1HqzyePEMjA87zDVAeQ1dDFQAJakly6PA2jqhFGJPccSRoeALkNHPIyp1xOwHFVAOSgSQnRFjQ8mz52WgWWIPDJ5rqETFIAlUdU/lRNoMqZOdicVgTFRAA5P2E3tiAHzFxQAFoEhhJDLQkrJAnqasGw5gBz3FocCsARpmiLtX2ym3jiA+U5B7gDagyIwpoeAmnw9KUy+rlgamxBCLodlWexcBpYh9WT4euK4tzgUgCVYhhtnGFNvHOX2uTbgGlwEZtmuJ5PF02B12rzrSLEM1xAhZPlYhrDDZYEOIFFQAJZgGW4cwPwqoMrtsy3kG8Gb6AAuy/WkMFkAqt/f5PPAgZAQoiMUgPqwDAvPdAAvBgrAEiiXyRLC6ImiyRN1IBN7tiVgCQF3CYrAWJa5HfEwJnfEuQNo8Hkw/b4mhCwnyyYATR7rliH1ZPj357i3OBSAJVAdl2c7Rk8UTS/aEUURHDtzL9XfJjqAqvN1bXM7YmDgJJs8sC9DgQJT72dCyHKzDKIDWI5c8WUQ4xzrLgYKwBKojitwHPR6PWMvQtNDQOM4hqsEoMEhoLkAdMx2lBUmD4rq9+8ZfB5M/v0JIcvLMogOYNDHmtzXDkdLmRg5BYwKQJOvp6qhACxBLgBtB1JKYzsBU4WrIo7jXPipKqBhGFbXoAVR15NjuAOoMPV+AJYjB9Dk358QsrwsiwO4DAJwGc6F6XNYXaAALIFaLfEdZ+SxaSxHCGj2b5OrgKqVK9eRxnbEwHIMissQAsqVUEKIjixD4RFgOca6JE7g2h4AM+dNwOjvb/K5qBoKwBIMQkDdkcemYXoIaBiGufCzDRaA+XYWjpntVyzDoKh+/6Rn5j0NmP37E0KWl2WpeL0UY12SwLd9AOaKcRaBuRgoAEugOi7THUDTb5goiuBYAxHr2mIJcgDNvJaA5UqM7yVmDoiA2b8/IWR5WYawQ2A5xrokjuE7AYDlmMOaGsmmAxSAJVA3S21JHEBTb5woinDcSfHxLw8ElKkC0BKZixkb2H5FmvbFk6GricDg3jZ1QATMnpQQQpaXZRGAqo81eaxLkgS+HeT/JtXxpS99CR/+8Icr+/8pAEugJocqBNTUyaLqxEwNAY3CEHEPuH+cfQ/HEkYWgYnjGJYtYFtmd8S5e2b4oAiY/R0oAAlZbkxdtF0WAbgMY10cJ/Adv/9vs+ew4/82jb/9t/82PvrRj1b2/1MAlmDcATT15jF1EFFEUYhh7erY5m4D4VgCtp3F5ZvKUuRFqBzAxNztXUz+/Qkh8zH1HleiTwgLccyxrkriOEbg1ACYLcYVpo7XANButyv9/ykASzC8D+DwY9MwufMCsiIww96la6gAjOMYtg1YlrmLCcBy5EUM//6m3tcmr0oTQuZj6mQ33/LIDZZirDO5r43jCEE/B9DEeRPAHMCLggKwBOMhoKbfPKbeOFEUjTqAljTyXCRJAstSIaAcFKskjgfXDwUgIURHTF1kU3Mnx/WNrrS8FGNdksDvO4CmivHhuaup81gdoAAsgRIZddfsPVRM3wZiXAC6lpkbwUdRBNvqF4FhWEylREP3sqn3tcm/PyFkPqYKj4EADJAYPNYtQ7RLEse5A2jqWEcBeDFQAJZA3Sx112wH0NRBRBFG0UgIqGNLIwVgkiSwLckiMBqQLIEANPn3J4QsLyMhoEsw1pk6Xvd6PaQyRc2tAzB3rFs2AVjVd6AALMGyFYEx9caJohjWiAMoEEXmCcA4jjMH0DbbAVwGARhTABJCNGQZNr1elhxA06tFK9PCt30ICGPPBQXgxUABWAJ189QMDwE1eRuIJEmQpumZKqBh2K2uUQsSxzEsS8K2BKSUxg4qyyIAHW/wbxMx+fcnhExmGQRgHgLq1UaiLUzDdAcwPw+2C9d2jY1iowC8GCgAS6BunsaSCEATUaGeIzmANhCF5nVkmQOYhYAC5ocUmyxA4jiG3ReApp6H4UnJMgyKhJDl2PNMzZVcN2DBswrJBaDlwrFdY+ewyyYAq4ICsARRP/dMbQNh6kRRdV4m3jjqNx/fBiI08FxkRWCyfQABcxcUTB8UgSwE11kiAWjyuSCEDFgGAaj6VMetGTvOAeaPdeo8uH0BaOpYN4yJ89hx6AAaQBRFcB0Hnp0JQFM7MpNDQCc7gMJQBzCCbSN3AE29nkwfFHu9Hnq9Hhw/e2z6eQDMDVEihIyyDAJwJAQ0SYydtKt+1dT+NReAtgvXogOoC1Xd1xSAJYiiCK5lw7Xs/LGJmDqIAIPf3BrbBiKKzTsXURjm20AA5l5PpgvAfHXacAdw+Pc39VwQQkZZhk2vh0NAhx+bhukCcDgE1LXMdQCX4Z7QAQrAEkRRBNe24fZj9kzcegAweyP43AEces6xgV4vNa5THq4Cqh6bSK+X9v82U3QMVqezx6be18PXv2n3AiFkMstSBMayHdiO2fUT1B6GplbtHnYAHcs1dqxbNugAGkAYhvBsG7YQEEIYv3piYghongM41HYvi8g1rjOL4xiOnQlY9dg0hquXmio61HXj9kNATb2vGQJKyPKxDM5+FEWwbReWbfYeyvk2EIb2r/lYZ3twWQRGG5gDaAAqBFQIAc92jBMcClMHEWBKDmA/HtS0QSWKIzj2wAE0rf3A6MqVqdXd8hBQwwXg8GBOAUjIcrAsDqDtuLBts/dQVpvYm7qZ/XARGNdgB3DZBGBVUACWIIoieP3Zumfbxk4UlyEEdCQHsO8Adrtm7QUYRTFsG3AMLgKzDGGH6ppiCCghRDdMFX3DZHveOrBswyuoqxxA40NAPbiWZ2TxPGD5BCBDQA0gDEN4/QIwvmO+A2heAOjkHEDXUActjpO+A2imgwksh+jIw2KC0cemsQznYphlmPgScl6G7wNTo3eiKILteMbnACrnL+mZ2b/mY53lwrU9Y8e6ZYMhoAYQhWFeAMY12AE0dRABpm8EP/yaCSRJgjRNYVsizwE0qf2K0bwzMwf13AH0Rx+bxvCkytQJ1jDLsLJLyHlZhhBQlQNoL0kOoKkLbCMOoO0Zex7oAF4MFIAlCMMQfj+EwbNsYyeKyyAArbF9AIdfM4E872yoCIyJnfFo3pmZ15W6bmwXsCyzrqNhhiclFICELAfLUPI+iiJYQ0VgTO1jVb9q+mKnZ3vw7OXIAVwGqvo+TiX/q6GE3RCenYUwLIMANPEmWhYHUIm91+6l2D8xNwR0mRxA2wFs1zLqOhpm2RxAU90OQi6SZdgIPooitJuHePVrv5E/NhE1xpnav45UAbXMdQCHMXEeO05V9zUFYAm6YRf+ah0A4NuOcUVHFAOnwLwbZ5IA9AwWgK0u0Euz82BS+xVqILRtcx1AdR9bbiYCTTwPwPIJwGUY2Ak5L8sQ7haGEXpJhNbJAwBmCkAp5UgIqJTSuK20hquAekuSA2jqPTGMlgJQCFEv82FSyvb5mqM341VAjw29eZRrk/bMW00MwxCOJSYWgTFJkA93vGoMMXFQVAOi45orOtR1YzuA5Zh1HQ2zbNtAmOp2EHKRLIMDGIYhhBAQwsofm4bqXz0nQJR0kSQJXNetuFXlCMMQnuP3tzLzkfQS9Ho92GovKkNYBtE3jK4hoE2Us4nMuopKkm0E388BtB10O2ZOFPONuw2sZBWGIVxHYPiydA2sojnY0H5Q0dTEQTEXgI65pbGXUQCadC9Mw9TJLiEXyTIUgQmjEBAid8xM7J9yAehmAjCOYzMFYD+Nye3/HYYh6vVSXk/lLIMrPoyWDiCAvwAT4wQvgV6vhyiO4TvZT+Y7DrqnJxW3ajEGYQzmhexlK1jjAjD726SJ+0goq8iK2pg8KLou0O2Ydz0BQyGgDmDZKTqdTsUtWozh68dUN3aYZRjYCTkvy1EEJs7cvyUQgL5XR7NzZGQfqxxAALkQNF0ALgNVFWacKQCllD+r/i2E+K8A/BaAz0gpm5fcLu1QE3ZVBdS3zS8CY2KYWLfbzQWfwutfxSadj/FcRscRRrVfoQZBx8muqzRNYVlmFRfudruwHQEhANuV6HbNFIBxHAOuAGJp5ARrHFPdDkIukmVwO6IlCgH13RoAM0Vst9uFa2WupWf7+XMmY+o9MYwJ20D8hwCeBnAohPiCEOIfCiH+90KIm5fUNq1QN8lAAJpfBMbE7SCiKDojAB1r8JopjG9o79jCqPYrhh1AwNxFBdvNzoTlAO2OmanMcRxDeOausI9DAUjIMuUAWnkIqIkCUPWpvlcfeWwS3W43F36eM3AATWMZRN8w2gtAKeW3ArgB4P8A4DcA/CEAvwDgbSHE14UQP305TdSD3AHMQ0BdJL2ekRPePATU1BxAa/TmF0LAc4RRglwNHmo/Q9dwB1AJQBPDYjIBmP3bds1dEY2iCNLPLigTz8M4pk52CblITHcApZSIorAv/gQsQ7fQygWga7gAtPpbmdEB1AbtBSAASCkPpZQfl1L+FwD+fQD/EbKw0G9Ali+4tKibxBtyAIefNwmTcwA7nQ5c++wN7xomAFVb8xBQ28yVuOEQ0OHHJtFut0cEYKdtZghoGIaATweQkGXCdAEYx3HW7n74p+2Yuf2AGtsCvzHy2CS6nSEH0GABaOJ9MAtdi8DkCCHWAHw3gO/p/3k/siqhzwD4L5AJwaVFFYYIhorAANnNs7KyUlm7FkEJQCmlcSWAw24Hri0QJaMdgGeb5aCdyQG0pVHtV+QOoDf62CQ6nQ4sOwUgYDtAx8ABEQC6YQh45oZYjUMBSIj5RWAGi51Z3+Q4npGiQy2qBV5j5LFJdLtdbNirAADfYAE4jIn3xDhaFoEZ4wBACOCXAPwcgL8kpXzuUlqlIeomCfrOX+CY6wCO7xdmkgDshl1s2kA0Fr3qGuagjQtA25JGX0smh4COO4BJbObeSGHYhfAF4FhGTk7GMTFHmZCLxnQHcDDWDRxAE/unPA2onwNo0nxD0e124XkqB9BcAWj6PTGOCSGgn0cmGP8EgP8AwJ8UQny7UMs6S45yAPMcwL4QNLFk/HDeomkT9rAbnikCAwCubZaAOhMCauj+c2og99zRxybRbrdyAei46jnzCsGEYQg4AsIxs6DQOHQACTF/sntGALq+0WNdzV8ZeWwS3W43d/5MDgFdNqqqJVKmCMwfArAB4D8G8BUAfwZZ2OehEOLfCiF+9FJaqAm5A9ifIS6LA2icAAxDeJMEoGVWCGUYhrCtwdpJ5mCat5gwHgJq4qA44gB6g+dMI4wiwAaEa1Y49DToABKyTAIwG+9s2zeyf1JtViGgJn6HbrcLv+/8+XQAtUH7HEAAkFJ2kFUA/Y1+TuAfBfBXAHwvgD8F4P9z4S3UhNwBtAdVQIefNwmTN4wOo+jMRvBAX0AZ1JF1u124Q9/DdYBWx5z2K3IH0PAcwM1++22DHcAoDLN9AA2tKDsOBSAhoxNcE13xXGDkIaC+0fMmVQTGtMXONE0RRmHu/Ckn0MRzsWwCUHsHUAjxsBDiB4UQ/70Q4ksA9gF8FJkr+P8F8J8U/Jz3CiF+SgjxFSFETwjx6QnHCCHE3xBCvCmE6AghflMI8W1F23oZLJcDaKYAlFIiDM/uAwigvw2EOR1ZGIZwnIED6Nj9Ih6GoQZB19AQUCklOp3RbSAA8wSglBJxFAOOgHTMXJ0GlmPPM0LIACUwhnMATZw3qT615q+OPDaFwVZmAQDAsVxYwjLyXFAAXgxlHMB7ACIAXwTwKwB+DMAzUsqjkv/n7wfwfQA+B8CdcsxfB/A3kVUX/TqA/xzArwkhvllK+XbJ/+9CUBNClQOohKBpE0UA2URR/dsgAZi7TZMEoA3sG9SRZQ7g4LFr6KQ9iiJYtoDtZJ2wad+h2+1CSml8DmAcx0jTFMIBpGH5sMNQABIyiumT3UG+eyYAHddHp7NbZZMWYiAAV0Yem8Igii1z/oQQ8N3AyLHC9HtiHBNCQP8YgN/uh4Geh1+WUv4SAAghPopsc/kcIUSATAD+N1LK/6H/3GcBvA7gR5AJzysni512YfXj2AODi8DEcQTXEohTaZRjk+/F6JytO2RaFdButzuyn6HrAN1uCCklTKqrFIYhHFvAtrLvYtL1BAyEnsr9MzUHMB/EXQHpCGO3shgO+6xqVZQQnTB9spsLwH7Ou+MGODk0r39S38NUB3BQyDDIn/OdwMg5rOn3xDhVGTFlisB8+gLEH6SU86TuHwawBuB/GXpPC8AvA/jAef//Rel0OnnYJwDU+jFvJq6eRFGMhpd9F5McQNXhTq4CalbeU7fbhTMkAB1bZGF8Bp0PoF/MxgH66yFGnQMAaLVaAAbOn+ONPm8K+e/uCMCFUeHQwwyLPjqAhJjPGQfQ8RGG5s2bssJtNlzHg23Zxs39VHuVA6j+baIAXDaqyncvsw3EVfEkgB6Al8aef77/WiW02+087BMAHMuGY9nGOQUAEEcRak6mokxybFQHNjEH0O5XQTSETqcDZywEFDBvQSGKIjg2oLbMM1YAjhWBMU0ADjuAwhHGDurDAyGLwBBivsMxLgBN3QYiDEO4buaeuY55lUwHaUxDDqBNB1AHtC8Cc4VsAmhKKcdH/0MAdSGEV0Gb0G63UXNcfOQrn8dHvvJ5AJkLaKIAjOIIdddcATgxB9ABer3UmLCxbrczImSVADStMw7DEJadFbEBzLqegIHQe/sl4JXPDXIBm81mha0qT15owRWAK4ycYAEMASVkHNMnu2cdwAC9Xs+4aJcsbz+bfroGilg1Rnzmjf8VH3325wCYKwCXLVfchCIw2iKE+GEAPwwAjz322KX8H51OB4Ht4M7xQf5c4LhG3jxhFKOxal4p4zwEdEoOIJB10isrK1fZrIXodDrYrgHd/s9vsgNo29LYEFAl9LqnQNzJEuNdXxi3sDPsAJosAIcHQgpAQkYxUQC22204zmDd3nEH2w+47rQ6gPqRCcCs7a5trgDca+3gNDwGAAROgHb7pMpmEdABHOYQwIoQYtzn2QTQllKeUSxSyg9LKd8vpXz/zZs3L6VR7VZrJAcQyLaCMG2imKaZS9Yw0AFU4mLiRvC2GDlGd7rd7lKEgHa7Xdi2hNXvSUz5/RXKARyuu+P4BoeAOgBcgSiMjFwZHR4IGQJKyHI4gI43CDt0+mGUJo51bj9/znXME4BqrmqJwbTfdwJ02uaZGMvgAA63W/siMFfI1wHYAN479vyT/dcqodPu5IVfFIFtngBUgq/RVxwmCcCZOYCGCahut5u3GTA3BDQTgJmAcgx0nnIBONQT2q65IaDwMgcw2zPTLDEOMASUXCxSSiRJwsWECsny3QeFR5QANG3u1Ol04DqDHEDTxmrV3nEB2DZQAA4vhJgqAIfHNwrAAZ8BcALgB9UTQog6gO8H8HRVjWq3W6g5owLQxBxAJfhW+urDpEli7gBOCFz2DCpC0uv1EEXxiAOotrYwbVDpdgfFbBxHGLWgAGRCT1ijDqDtpcYJwLwf6oeAAuZdSwBDQMnF8qM/+tfxfd/3ffi+7/s+/OZv/mbVzbmWtNvtXPQBoyGgJtHtDIWAGrh9wiQHMHACdDpmzWGBUdFnoisOjIq+ayMAhRB1IcQPCCF+AMCjAG6qx0KIupSyC+C/BfA3hBD/DyHEHwfwi/22/sRVt1fR7nTOCkDHRdvQULGGgQJw4ABOygEUI8fozKT9DE0NAQ3Dbl4B1HHMa3+z2YTrj3aDjgecNs3KixjJAfQoAAkBgBdfegnWrUchIfDKK69U3ZxrSafTgT0iAGsAzBsrOp0OvL549Vwf3Y557Xdtd2SfYd8JEEahcQ75MoSA6iAAqygC8xAyQTeMevwuZBu+/7fIBN9/CWAbwBcA/Ekp5YMrauMISZIgjCLU3NECpDXHRfvErImiEnyNvmVmUic8MwfQoCIkuZBdkhDQlWxfXDi2WdcTkAlAZ6yusOMBpwdmOYB5zqInIFwBCfNCrIDRgZACkJyHXq+HTrsF5xv/AMTJEU4MG6uXhXan06/8md3bygE0rX9qdzpYX8/Eq+fUcHBs1ljXbrcR9MW3ouZkjzudjhHF8xSm58UCo+lX16YKqJTydQBnLZzRYySA/7r/p3JUR3U2BNQzrhNTAimwbXi2bYRgUgyqgJ59zRuqAqo7SuR5Q5eTZ6wADPMQUNuWRvz+w2QCcHQAcXzgyMAQUOEICEtALokDaFqZeKIXp6enkFJC1OpAUMPx8XHVTbqWtNsdON4aeh0lAAeiwyS6nQ7cG/0cQNe80MlsK7NRARj0H7fbbaME4DLsFzs8vlWVOqNjDqB2KJE3XgW05jjohmbZ52qC7jsWfMc2asLe7XZhCWBCBGheGMYEQauuJ9MdQCnlSC6j7ZgnAE9OTmCPC0APCMPIKAHS6XQgvH533heAplUyBegAkotDCT4R1CH9Go4oACuhM5YD6HrmFYGRUqLT7cDr5wD6boBOt2OU+9Rut0c2gQcAf0gAmsRw2KdJ8+9hhkXftckBNBF1c9THQkDVY5Mm7YPN1C14jmXUhD3bh8caiWFXqHw6E77PIAdw8JxlCTiOMOpaCsMQUsqhIjAwblX05PQEQwXqAAD9CCWjCsG0Wq0zAtC0QR1gDiC5OI6OjgAAolaHqNVxeHhYbYOuKdl+fwPnyUQHMIoi9Ho9+F4/BNQ1bzP7bC/rMQfQwHMBjIq+ZcgBpAOoMWolve6eLQIz/LoJKPERODYC2ywBGIbhSOGUYZQDaEIVyoEDOPpdPMMEoGqryQKw2Tw9IwDV49PT06tv0IK0221ItT5lsAAcvn9NuJeJvijBJ2oNiHoDh4dH1TboGiKlzLaB8AbCw3Y8CCGM6p9UWz23NvK3Sd+h1WqdcQBr/ccmzWGB5XMAKQA1Rt0ctbFqEaoojEmdgJq0+44F30ABOGkPQMD8HMDssVmDovqtVWqs4wAdA35/RZqmaDXbueOnMFEANptNpG4/HGlJQkBNWl0n+nFwcAAAEPUGRH0F7VaTiwpXTLfbhZTpiAMohIDr1Y0a6wZjtrkCsN1qo+bUR54LDA0BXQYHcDhdiQJQY/IiMFMcQJNuntwBtG0EtlmCIwzDiRVAgawCpTpGd/LVxLFiNq4jzXYAXRhVGrvdbmchrGNVQF0TBWCrmQs/2ICwBAUgudYcHBxA2Dbg1yDqK/lz5OpQY53jjTpPrhcYNfdQbfX7ws83UAC2Wq0zVUCVADRtrFiGIjBK9AmIyuatFIAFyB3AMQGoQkJNunnUpD3oF4HpGNSBdbtduPbkpGtLCLh2dTdSGdQ5GK9m6trSqAElF4BDDmC3GxqTGK8E3lhUjJkOYKsF0d/PUAgB4VtG9UsKHfIiyHKwv78Pq76S3Q99Abi/v19xq86HKX2rIk93GBMejlczaqwbF4BGOoCds1VAa27mCJo2ViyDAMy3ZHMDOoA6k+cAjlkFqgiMSTdPu92GEFkRmMCxjBKAURTCtaYPgK4jjAgBnVQFFMhCQttts64lYPA9XCeboJhwDoCBwFuGENB2qzVwAAHAUAGYD4S2RQeQnIvd3V2gkW1SavX/Nl0AmkbuAPqjoYeOWzOqf1Jt9cYcQFO+QxRFSJIkr/qpUDmBJglZYDmKhamxbtWrIezSAdSWVqsF27Lg2aPxhzVDHcDAcSCEQODYaBsUcpg5gNO3kPQMcQDb7TZcR8CyRr+L6/Qn8oYwKQR0+HndURtDnykC4wFCwJiNo3u9XhZ66w9dT55ZVUwVSvRZvksHkJyLBzsDAShW1gAAOzs7VTZpIUxz/YaZ6gC6ZjmAao7ne/WRv02Z+w2i2EbPgyUs+E5gzPdQLIMAVHPVFa+GMKxm0ZwCsACtVgt1zzuz/YByBE26edrtNoJ+JZWaa6PTNWOyDgBhtzu1CAyQVQI1QQB2Oh147qStLLIwDVPIV3f7ws81VACOO4BCCLi+ZYwAzPufIQGY+sCJQQ6mIhd9nmPEvUz0JE1T7O3twlpZz57wfFieb6QANBnVN53NAayjadC8KReAhjqAeR2LsSIwAFAzrCAPsFwhoKteDV06gPrSarXOhH8CgGfbsC2zQq2y79IXgI6NOE6MWWnvdrtnCqcM4xgiANvt9mQB6ALtthniCRjKZRwTgKbcD9McQABwA3NCQHOnb0gACk/g9NQMATtMGIYQlgW4NkNAK+bw8BB/7+/9Pbz11ltVN6U0h4eH6CUJxGrm/AkhIFbW8ODBg4pbdr3IHUBvVHi4Xg3tljmiY1kdQACoOWaF4wLL4QCqVJlVv84iMDrTbrfzip/DCCFQdz2jQq3a7TYCJzvttb4QNGX1JwxDODOuWNcyI/+s3W7Dc86G9XguEIaRMStag/Ce7LGpIaDjDiAA2F6K4+PjK27RYqj+RxWBAQAEwqh+SRFFEYRjQdrCmIWpZeXzn/88Pv3pT+NjH/tY1U0pzdtvvw0AEKvrgydX1nG//7xJDIeAmhYOqoSF65ldBKbVasGxXTh2Nsipf5vSx6rzEDhnBWDg1Iz5Hoo4juH1z4WpC4XZtmYOarZX2byVArAAzdNTNNyzAhDICsGYtHrSbrVw1Inw8195A7V+PKUp7Q+jaOpG8ADg2bKyWOoytFqtiQLQ77uCJohYoD8oOgK/90Xgi18w0wF0fQvCOntNOQFwfHx09Y1aACVk0xdCpL81CAdtNVvGTRijKMqsfNtC1wA3f5lR+2uZKMTv378PALBWN/LnxNo63n77bePuCZPJBeCY8+R6NURRaIx702w2EfgN/NrvfAS/9jsfAQAEfsOYsW7gAE4IAXXqaBnkxgKZ6+fZHixhbrGwTqcD33HhOy7CsFtJv0QBWIBWq3VmE3hFzXGNWslqNk8R9VK8cdxG3TABGEXRnBxAU4rANDFpPUFV0zTlfLTbbbiuwOEhcHg4EICm3A8nJydwg8mvub45RWDy1dvTHuRef0LlW1lxGEMWExRhGEI4NuDYRizmXAfGc99NIBOAAmJIAFprm+h2OsY4+wqTHcB2uw3H8WDZo7kbKiTUlLGi1WrB9+p4cHAHDw7uAMjCQE0Zq2cLwBpaTTO+hyKOY7i2A9d2jVlEGKfb7cKzXfi2i1TKSoQsBWABms3mVAew4bpoGpIrBACtZgtWf0A3SQAmSYJeL50pALMcQP0nje1We2Iuo2eYgGq1WiNC1kQH0PEnT6hMygHMherwRD3I/m3Kd1CEYQg4FuBYlSXGk1FMEx0AcO/ePdgrqxDOoKMVa5v5a+RqaLVacP2zokM5gqaEHp6ensIfE0+B2zCmf80F4IQiMIFbN2r7KSAzAxzLgWs5xjqA3W4XgeMh6JtLVaTOUAAWoNVqo+ZOcwDNCgFttltQOynU+5aTCe1Xzt4sAejZqGw/lTK02234E9YTTBSAjjuYHJrmAB4dH00XgD4QRbERDlouAId6c9EXgKa4mIooiiBtC3BsdA1YzCF68tZbbwF9waew1rPHd+/eraJJC2OiAFc0m80zBWAA5KLQhLkHADSbLQReY+Q536ujaYhzpoR2MKEITN2to2WYAIzjGK5w4NqOkSHqQH9Ltr4DqB5fNRSAc+j1euh0O6jPcgANWcUKwxBxnOT7zykH0IRVLHWTz9oH0LX1z1eRUqLd6eZibxiVA2iKgMocwMHkxLYByxbGDOonx8dTQ0D7++MaIaBOT08hPAsYvjWCrGs3of3DdLtdSFsAjqX9vXxdMC0EVEqJN+/ehdjYGnlerG4AwjKuqqnJIaCtVguOd1Z0uIZV0Tw9PT0jAAPPLAcwcGuwxNkpf+DUEcexUf1tGIZwLReuZe5+sZ1OB4Hl0gHUGTUZr09zAF3PmARaJVTt/oDe6DuAJghY5cTMDgEVCEO9O4MwDJGm6dR9AAFzBGCzeXoml9H3DBKAp6fTcwANEoAnJyewgrGu3DfTAex0O9lN7thGuPnXAdNEx/HxMdrNJqz1MQFo27DXN/Dmm29W1LLFMFkANlutJXEAmxMFoAlzJ6BfyX5C/h+QOYCAOecCyBb6vX4IqAl1HybRabcZAqo76gafJgDrrodOt2NE6X61WqUEYOBYsIQwYhVr4ABOP0Y5gDoPkkrcTXIAPcNy6FqtFsZvC9czo/3dbhdRGE3cAxAYCMCjo6Mra9OinJycQAZjCwo1Ux3AMEvmdWzEUZRXoiTVYZoDqASe2Ng+++L6Fu68YZYAHEbnsW0SreYUAWiQA5imaeag+WMC0F9Bq9Uyoo9qNpuoTdgCAhiEhZpwLhRRGMG1XXgGO4BtJQBtL3981VAAzmGeA9hwqzt5ZckFYD8EVAiBFd+MENY8B3DGFevZQCql1lWh1HXiTygC4xuWQ9dqtc4IWdeVRlxP+R6AM6qADh+nM8cnx0jHhWzfATSt4mGnkzmAor/SY+rq7jKgxIZpouONN94AAFibN868Zm3cwL17d41YsFUM//4miI1hpjmAnkECsNVqQcoUNX9l5PnAa0DK1IjxutlsIphQAAYA6m4jP8YUut0uPCsTgCbk6U8i21/cy+uL0AHUkIEDODkHsNZ/3oSbR01m7aEV3YZrGzHJVas8zowcwP6+9lqvCKkBz5uwnmDSNhC9Xg9hGJ11AF1phKOshNG8EFATBNTR8VFe9EUhbAHLN+PeHqbb7WY3cl8Amjq4LwMmiaRh3njjDQjXhVhZO/Oa2NxGL0mMqgRqmugbpt1qwR1zzgDkeYEmzJvUeBaMCcBa/3uZMN61mq081HMctTm8CfMORbfbhW/78CrcRP28tDsd1BwftX4YEh1ADckF4JR9AJUDaMLNkwtAy1wBODMEtP+9dBaAuQM4IQfQsgQ81zJmRRE4G8rqulluoO7ME4COn+2qYIIAPDk+yUM+hxE1y4j2DxOG3TwHEKAArBIlPEwLAX399ddhbdyY2G7lCt65c+eqm7UwwwLQJFEeRRHiOII7oQiMZdlwvcAIAajmR7XxHMC+IDRh/pSFgC5PDmAYhvBtD77tGZkrHscx4jhG4Hj5HuNV/P4UgHNQJ6UxybLBIDTUhJtnPAcQAFY8BycGTBKLbAOhHECdw8ZyB3BCCCiQCUMTriU1cI87gJ5nxqpuLgCn5AAKIeAGlvaDexRF6Ha6QO3sZDcNpBE5jIo0TRGF0YgDWEVYDMlQofSmhYC+9vrrEBPCP4GBAHz99devsEXnY1gAmnQuBtEuk4WH69WNGCvUvKnmr448r0JCjXAAW62pRWBqpoaA2i582zNyjFD3Rt318yIwdAA1ZLCB5uQQ0LpBIaDHx8dwbWtkv+g1zzHCJVCbfTpzisAAejuA+aA4+XKC55qxmJA7gFOKwOg+UckF4OS8+Oy1QP8iMPm9O8EBlIHA4fHR1TboHKiBXHgUgDqgcy71NE5OTnB0eAhr6+bE14XrwV7fNEoAmpoDOFgknCIA/boRY51aBBwvAlMzxAGUUqLVniUAs+dNmMMqut0uak4A3/aNjBJRYq/m+HAsG77j0gHUkSJVQAEzJu0nJydY9V2IoQ3DVnwHJ6cn2k/YB0VgZu8DCOgtAAchoJNf9xwzksrVque4APQ8IEl6WruwQCachACmRHYDABw/1X5xRLVPTHAARc3CseYCdph8IHftTASCArBKlAA0KQT0tddeAwCIKQIQALB5A6+8+uoVtej8mBoCmgvACTmAAOC6ZjiAeQjoFAdQdwHY7XaRpunUHEDf9mEJy4g5LJDN75JeAt/2UHP8bOsgwxh2ALO/AzqAOpJtoOnCtib/VCoH0ISO7OjoCCtjsYernoM4TrQXHUVyAB0DcgALOYAGXEu5ABwLoVSCUPf74fj4GG5gzZzcZg7g4RW2qjy5QznBAUQtC2HVfXFHkfdBrpPf6Lr3S8uMEoAmuU6v9oWdtfXQ1GOsrYdw7+5drceJYYZFn0nnQo11as+/cVy/gWZTf9FxenoKATFxH0ABob0AVGPxNAdQCIGaZ4YbCwwWCgPbR+D4iOPYuGiFQW0RJQD9SuZMFIBzaLVaU90/YFAF1ISb5/joCGveqIJa61tRujsdgyqg048xpQqo6whYU5xMzwWaLb3FEzA9BFQ91j0v4uTkZGoBGIXjZ1ss6MxMAVgXSHup9mJckbt9np2XxKUDWB1qUmWS6/Tqq6/CrtUh6pNdJwCwth+ClNKYMNDh39+kiW4+RkxzAH0zNlI/OTlBEDRgjZkAlmUj8OvGC0D1mgnnAhhKy3ID1OxsEDdtofCMA+j4lcyZKADnME8AWsJCzfWMEIBHh4dYG7OeVvsb0ume65TnAM64Yk0QgO12G96ECqAK3/AcQFME4PHxERx/9mq6GwDNU703+h0IwAnXVF8UHh7q7WIq1CAuPCevkmTawL5MqD5X/W0Cr7zyKrD10Exn39rO3MFXDQkDHRZ9OvdF48zLAfQMKQJzfHx8Zg9ARS1Y1X7xfFDHYoYAdMxxAAf5cwFqjpkCUM2PGv1V6Lrjo3lKB1A7ms0mavaUko19am41CZxlOTo+zgWfQjmAuk8SiziAapN4nQVgq9Wamv8HZPNeE1yP09NTOI6APXY+VEio7gP70dHRXAfQDbIJl87f5ejoCMIWgDcpB1Dkx5jAIAR0UATGhH51WTFNAPZ6Pbx+53WI7enhnwAg1jZhuZ6RAnDZHMBOp629qD05OUHgTRGAnjkCUG34PomaY4YYBwbfJwsBDUaeM4XBOcna33Cr2RKFAnAOrWZzpgMIZIVgdL8AO50OumGI9WBUfaz31Yjuk8QoimAJwJqxsqvEoc4TllarBc+dnpPleQJhGGk/0J+ensL3z54LcxzA40ICENA7yf/w8BCibk92POpZ9677va3I+1DPgbAtCMc2bmV3mTBNAL711ltI4jh3+KYhhIDYuomXX3nlilp2PoZDQE0Kx221WrBsB5Y9ecXT9eqQUmp/jx8fHaPur018reavZvuwakyRENC6W6/EgVqEgXiqoeGat4k9kM2PLGHlewA23ABNhoDqR7PZzLd6mEbdcbVfPVEO3/qY/bTWdwR1dwDjOIZjz65Gp4rA6DxhabVaU/cABAbVQXUfFE9OTs6EfwKA33cAdRaAaZri9LQJZ8oegAolAHVe4T04OICcFP4JGBsCqm4Q4Tna3wfLjOpHdY6oGOaVvqCzt2/NPVZsP4RXXnnFiAJJpjqA2SJhY2o4rtcvDqPzWAH0Q0CD1YmvGRUCOmPPo8AgB1C1s+HUUDfUATw9PUXDC/J7o+EGaHXaV77AQwE4h3k5gEAmAHWv3KgmgWtjAtCxLDQ8V/tJYhzHcPsC8ONfTnDvSOLekcRP/WaEj385GxQdE0JAm6dTK4ACg+qgundop6encNyzoTuOA1iW3q5Zs9mElLKwA6jzAH9weAA5bWE3EIAwRwAOO4AAIHxH+/tgmVH9qM796TCvvPIKhG1DbGzPPdbavoVOu4233377Clp2PkwVgK1Wa2oFUGBQHVRn4SGlxMnpCepTcgDr/gqOT461XkhQv28wIwew7pqTAzjYmq2Gel/U6r6IMM7p6SlWvMEEZMULsv0ar/gcUADOQIUn1KdsAq8wIQfw4OAAALARnP0uG4H+AjCKotwBvH+copsA3QR4dU/i/nEmREwIAW232zNzAE1xAI+Pj3K3bxghAN+3tBaAqm1zBaA/eryOHBweQkyqAApAWAJW3dH+3lY0m00Ix0b62ZfR+3cvInVt7fvVZUYJv67me3oqXn7lFVhbNyHGE5MnoMJEXzEgDFSNZ8J2jBHjQDbJdb3peWfqNZ3v8U6ngziOUQ8mh4DWgzUkSaJ13n6r1YJne3CnhOICWXhoN+waEWI82EKhhoaBm9gD2aLyijNwZFcqErIUgDPINpzsobYEOYBKAI6HgALAumdjf3//qptUijiOYc+5WpUDqLMAbLXbS+EAnpycnNkDUOH5eosm5eiZngPY6/VwenwCNGbcGHVhjABstVqwfBdy/xRy/xTwHZwaNrAvEyY5gFJKvPzyKxAz9v8bxtp6CBDCiEIwcRwDwoLl+lqPbeM0m004UyqAAoPiMDpP3tVYMSsEdPg4HWk2m6jNOA/AID9Q93kHkImkuluDbdmoOQEEhJEOYMMddgAzAXjVcw0KwBkoF6ZIDmBLc8fm4OAAlhBnqoACwHrg4mB/r4JWFSdJkplbQADIBaKug2Sv10O3G84WgE7mcurcEUsp0Wy24E9ZF/HcVFvRBAw5gHNyAC0HsB2hbRGVk5OTrILetBxAAGkN2D/Qe3FH0Ww2IYcTZD3HuIF9mVAbLocGCMCDgwOcnhzDujE//w8AhOvC3tg2xgG0HAfCdo0Q44rT02ae5zcJ1wABqPr+WQ7g8HE60mq1Zm4BAQy2iNB53qHI8uey9lrCQsOrGzdOnB6f5KIPAFYpAPVjUG1otgNYcz0kSaJ153xwcID1mjexiuZm4OHg8FDrOPYoiuY6gFaW8qStAFRhIv6sfQD7l5rOHXG7nSUrTwoBBZQDeHSlbSpDUQdQCAHX13d1UTl7oj79xhB1S3t3X3F6egrpD4Xv+S5Om3r+9tcBFfoZGRACqoScVaAATM7WTbz48suX1KKLIwxDCMcFHLNCQJvN5swQUM/TP3xPjRXTqoCq53V3AANnegEYYOAA6nwuFCcnJ1gZErQrXl3r338SxycnWBsRgNn3uervQQE4g8EGmvNCQN2R43Vkb28PGxPcPyDLAYzjRNuJLtB3AMVsgSqEgGMLbRPllaM82wEcPVZH1CqVqSGgRXMAAcAJ9B3cVVj3vBDQ4yO9ixQoTk6zsM8c30G72TKi7ctIqASgAaIjF4BbNwu/x7pxC/u7u1qPe0D2+wvbAwxyALOCFs2ZRWAcrwYh9F1gA4YdwMkhoHUDQkBbzQIOoEEhoMfHx1gd2tOw4dS1nm+ME4YhwijEijcsYjMxSAGoEWoSXpsTAqoEos6T9v29PWxMqT6yUcvar7NTUCQHEABsS2jrAKrO1fQiMGrAnuYA+l4W/qPrxP3k5ASWLWDN2I5D4fgpjo+PLr1Ni5ALwBkOIOpWliuo8SRLcXp6OnJzCN/th013K2zV9UU5gHEUaXsvK1599VXYaxsQfoFVnT5WP1/wtddeu6xmXQhhGAK2A9iuMfdCt9tFmqbwZjiAQgh4fl3rsS53AOeEgOosALOtzIoJQCMcwKNjrAxdV6tuAyca//7jqGtlzR84gDXHg23ZDAHViYEDOL8K6PDxOrK/v4/N2uTvsdmvDKqzAEySBLY1fxJi2/qWyi7iANp2to2CCYPiVAHoA3GcaDtZyTaBF1P3pxrG9fUd3IsKQEDve1sxLgDR75dMEK/LSNi/f6WUuRuoKy+9/ApQwv0DBuGiuucBdrtdwPEBx9P+PCiUkFB5ftNwPb33nzs+PobrePCmhIt4bgDX8TTPAWwjmCcA+yGiOs87FMcnJyMO4Kq3gqMjPcfoSahrZXXIARRCYM2vX/l1RAE4g8JFYPqv63rzhGGI02YTW8HkUNbN/vO7u7tX2axSJHGMOfvAA8g2g9dVAKoFAlXoZRJCCPiupe21BBQLAQX0nbifnp7OLQCjcHx9v8fBwQEs34KYkVMq+uGhuVjUlCRJ0O10IILREFBA399/2Qm73WxFCtBaeHS7Xdy/dzd39Ioi6g3YtYb2lUAzAegBjodOR89FtXGUqJtVBAbIBKLOAvDo6Aj12mT3T1GvrWktANvtVi7wpmFKCGgYhuh0O1jzBiG5a57+ezEOo66VtbHKrGseBaBWFHYAHb0dwL29rMLnZm2KAKzp7wDGSQzbmq8ALaFvEZgiDmD2utD2WgIGAnCWAwjo65ydnJzA9s5uYj8JxweazVZWbVMzDg4OgPqcPc8McQBzkTccAtp3AE3K71gWer1e1o/WsomjzvucvfHGG5BS5nv7FUUIAWzewKuah4B2Ol3A9SBcHx1NoyrGUeOXO2f7Acer4/RUcwE4pQCMou7rKwCjKEIUR7nAm4YqEqPzvAMYDp9cyZ9b81aQJInWi+bDqGtlfcwdX/NqODo8utK2UADOoGgOYNAXgLoOkrkAnLAJPAA4loW1wNPfASyUA2h2CGj2utS6M8uLqEz5HvoLwGM4BR1AN1AFDfQbGPf395HW5qx6GuIA5gIwOBsCSgF49ajwbVGrjzzWkddffx1AuQIwCrH9EO7cuaPlAo+i3elAuEEmADWdY4xTNATU8xpa9q2Ko8OCAvCKJ+5FUb/tvBBQ27LhO77WbiwwqHy95o0KwOHXdEe1c9UfdWXXvMaVfwcKwBl0Oh24tg3Hmr3KXtM8BFQJu60pDiAAbAVuLhR1JEkSWNdEALq2/gIwCKyp58PXPAT05PSkVAgooGdy/N7+Xh7iOQ3hCliepb0AzFfQh/uovgDUdSFhFl/60pfwo3/9rxszYR8nF4D1bOKo8/d4/fXXIRwHYm2z9HutrZuIwhD379+/hJZdDO1OG8L1jRSA80NA9c4BPDo+nloARlEP1nCkaR+VmxhzQkCBLAxUZzEODMTT+pAoV/82SQD6jova2Cr0ej8H8CpDWSkAZ9ButxHMcf+AQQiorpN2JezmCcDdnZ2ralJpkiQplANoiSx8SUdyATin+qTnAq2WvoPiycnJ1Pw/QG8HUG1iX9gB1FTMSin7IaAFuvCGrb0AVC6fGHYAfXMF4E/91E/hS1/8InY07lNnkY9ldf2LQ7z22muwNm5AFFkhHMPavAEgCyPVlU67DeEFEG6AbqdjRK7TIAR0fhEYXUWHlBLHx8VyAI+Pr3biXpTcASwgAAOnpu25UAwcwEEO4Lq/OvKa7hweHmJtgjO+5jcQxdGV9rUUgDNot9tz8/8AwLVsWEJouzq3u7uLhufCd6Y7mZs1vUNAe2kPBVIAYQuptQD03PnVJzMBqG9HfHx8DG9GDp3bX2fQMXQvDEMkcVJYAKrjdPsu7XYbcRTP3gOwj6xDa3cfGHIAhwSgsC1YgWekAFRFU3Tti+ahxjLRWBl5rCOv37kDbGwv9F4lAFUYqW5IKdFp90NAvRqkTLUOx1XkIaDebOHh+nV0ux0to3ba7TbiOJ4fAhqsIY5jLRdJBmlMs51YIBOAOt/nwCCXfTgEVDmAui9yKg4PD7E+ITd2oy8Kr1LIUgDOoNPpILDnC0AhBGqup2UHAGQCcGvKFhCK7ZqHVrut7XfoJb1COYCW0DsE1HPnfwnPyVZ9deXo6HBqARgg28YiCCwtE+OVk1c4BNQbfZ8u5EVdCghA1AX2DvQWgLnIG4tSEDXXSAGo3ACdc8tmocYB0aiPPNaNdruN/b29XMiVRXg+7JU1bR3AbrcLKdPMAfSyrQh0DplUtFotOK4Py54d7qKKxOh4fanxqzHHAWz0Q0R1HO/U71rcAdTvPAxzcHCAFa8Bb2hevuLWYQv90xwUB/sH2BgqYqNYDzIBeJXfgwJwBp1OB4FTYLdoZIVgdF2Z23nwAFtTCsAoVHiori5gr2e+A9jpdOaGfwJ9AajptQQAxyfHMwUgkIWB6iaagMHkqawDqNukSwlAUSgE1MLhwaGWIUqKo6MjWL4LMbbKk/quMaE9k9B1MWoeAwGYTUp0jUh46623AADW5mIOIADIjS288eabF9WkC0X1O8KvQ/hmlOoHsjbOc/+AgUOo43dSgq5IDiCgZ6j6wAEskAPo1NDW8DwMc3BwMJL/BwCWsLAerBkjAA8PD7ARnA0BVaLwKit2UwDOoNNuI5izgqUIHEdb+zxzAKfn/wHAdj17XdeclV4vhVVAAQqNcwBbrRZcZ/4k3HWBMIy0/B5SSpyenM4VgK6XajkgKlHqzL4dclQ4q24CMB/sCjmAFuIo1nKSpTg6OoKY1EfVXOwfmjGwT0LHe7gI+bWykk1KdHRogEHunrVgCCgAWOvbePPNN7VcIMkFoFeD6Isl3fqiSWQCcH7YoTpGx+9UVgDq7QBO3sh+mMDVPwfwYP8AG0P5f4oNb037rY6AbFuO02ZzogO4EVx9NVMKwBl0Oh34BR1A39ZTAHY6HZw2m7hRnz1j39bcAUzTtJADaFlAmuo56Wq324UEoNooXkdHudPpIEl6hRzAoyP9Ju5qgCvqAFqOgO0I7SYoAwFY4KYwYCuIg8MDpJOiFOqetiXWi2CqA6juExEEEI6j7cTw7t27gBAQaxsLf4a1sYVup6Pl/aEWrITfgAjqI8/pTLPZLCUAdby+lkEAli0Co+Mcdpi9vT1s+utnnt/017G3q3eaAzAYgzeDswJwxQ3gWDYdQF3odDqFisAAQM1xtFwlVYJue44DuBF4EEJjBzDtFa8CmugpADvtVrEQ0P4lp+P1pFw9f86Cou/rVzgFGAoBLegAZsfqJwD39/chXAtwC7jiDf03g88qmp49KaLuodVsGiuk4jiuugkLkV/vngfL13d/sLt378JeXYcoGKkzCbV9xL179y6qWRfGoDpuHaJfJMIIAdhqwSkQduj6+jqAaqwzOQS00+nAtmw41vx5bODU0OnqW2W21+vh4PAAm8EEARisa1/oDBiMwRsTqoAKIbBZW6UA1IVxB/AjX/k87hwd4M7RAf7ub/0KPvKVz+ev+baDroarJ0rQzQsBtS2BrVqgrQBMeynmFM8EAFhCoNfTc7LY6XRG9gD89Bd72D0Cdo+AX/z1BJ/+YiZcXWdwvG6oCUkRB/Dk5FS7wWSSAHzlcxLNfaC5D3z530i88rnRNjuefhOUg4MDiLo1t6IsgHyrCJ0F4OHh0UQBqIrCmJoHaKpwbTabsFwPwrIBz9Pu+lfcvXcP8hzuHwBY6/oKwGEH0OpPGnVcWBun3WqP5AD+3jMfwdH+HRzt38Gnf+nv4vee+QgAwHX13Wbk6OgIvleDM6cQoGO78L2alg5gtpVZLR8nPvrsz+Gt4zt46/gO/tEz/zU++uzP5cf6TgAppZaRR0B2PtI0nSgAN/w1tNotbduuUCJ1s3Y2jBXIhOFVClkKwBmEUQR/aGXxzvEB2kmMdhLj+b0HuHM8CBnxHUfLi08JuhuTJldjbNUcfQXgUAhoN5YIggAf/OAHEQQBuvFgwm4JINVMdCg63U4u7gBg90giioEoBu7uZo+BwT6BOl5PuQNYQAAmSU87EatCYuyh26G5D/Ti7M/x29njYWxPaheitH+wDzk/wiqjHyaqY4gbkOVFtFstiEl9VD903VQBaLIDKPzsfEiNBeD9+/dhrU7fAD585lcRPvOrMz9DrKwDwtJyM3jV31rBCuAFEJZthAAczwE82ruDJOogiTrYu/91HO3dAaB3FdDj42PUg8kT9XHqwZq+AnAo/++t4zvoJB10kg5e2v863jq+k7+mjtPxXACDBcytYOPMa+o5nRc5gSEBOOW62vRXsH+FoawUgFPo9XqI47hUDqCOE/adnR0IkYV4zmO75mHnwYMraFV5UilzB7ATAx/4wAfwoQ99CN/7vd+LztAcSwBINS280Ol0C4WAuhqHgKrJx6yN4Idf1y0spt1uw3ZEoYJCCsvRTwDu7e8V2wQeAFwB4epbJjtv14Q8ZdHIntN9YJ9GFEVVN2EhTk9PB6s8vo8TDcMO2+02mqenM/P/0v0dpPuzFzWFbcNeWcXbb799wS08PycnJxCOB+F6EELArjW061Mn0W634fhFcgD1dgBrc/YAVNT8VS0FYLfbhW/PLwADZA4goGfkETBIZ5olAHWtYaHY39+HaztYcSefk63aKvb2968scmrxwPklR4k5v2BugWc7+ea/OrGzs4OtWgC7wIR3u+bhC/d30ev1YNvTN42/atReWkoA1lzg6aefhpQSn/jEJ7A1NG8UAtqFHQLZgkIUxXCc+efB7Sc76tgRl3EAgWwCc/v27UtuVXFarRYcTwAofo04HtBs6eWAHB4cAu8rJgCFEEBdXwGYi7uJDqA3eoxhmCoAT05OkKpVHD/A8ZF+DuyD/mKltVJskj6TlTUtBeDR0RHs2lDBiGBFS6ExTK/XQxh28/DOWVi2A9txtVtgA4CjwyPU/enu8jB1fw1HGkYptNvt4gLQpgC8bPb29rBVW5uaurEVrCKMQrRaLaysnC0Uc9HQAZyCEnNFBaDvOOhqKgC352wCr9iu+0h6Pe0GGCXolIYNXIFut4unnnoK3W4XwVAhDCH03HxZXU9eAQGo8gR1dJRPTk4gxMClnMawANSJdrtdqgAMkIWLttv6TFA6nQ66nW5xBxCArOsbAprvadiYsKrQzwHUte3z0HFRsAhHJycQQXY+RODjVLP7GBikN4gLEIBiZR0PNJw8Hh4eAsP5QsGq9uHQSkAU2QdQHaej6DgqFQK6iiMNndlOpwPfLlby2gQH0LUcrLpnC6hs9fMCdReAuzs72JxQAEax1b/Xr+p7UABOIZ+wFxWAtoMkSbTb92nnwdvFBWBNz70AcwewwLG6CkAl5opEFDv26Ht04vj4GEFgzS3Io3MIqFVgK45hHDcL39WFfAJYZAuIPrJuZWGjGpK7exMEoLAtWI3AOAdQLVrpeA8X4eT4GAj6E/ighigMtROzapJ0MQJwDYcHB9qN34dHRxBDJeOt2ir2NReAKpzTmRLmNo6r4f5zUkqcnJzMrQCqqAdrODk50S76qNPu5MJuHoEBAnCrtjnRPfNsD6v+igECcBfbM64p9RoFYMUMBGCxUEh1nE6DZJqm2Nvbn1sBVKEE4APN8gBVp1qk4KGAniGg+apogcvJ1bgIzMnJydz8P0BvB9Byy10ftguE3VCb60oJQFHCARSah4AKywIm7QMIAHXPiBLfw/T6i1A6jQdFSdM0y60Lsgmh+lu3xZxsUUBA1M8fKiUaK0g1jH7Z3z+AqA+qHop6FmqoS180ibIC0NHQAWy32+j1EtQKOoC1YBW9XqJdLmNWd6DYefD6TqGO8w6gn840YQ9AxZa/oZ15MUyv18PewX7u8k1CvXZV34MCcAoqd6OoAHQ1FICHh4dIej1sz9kEXqE2i9dtFSUXgAWOFaJMdtfVoa4Lt0gRGN0FoDvfYfW87FxoJwA7bcyp6n0G24VW5bEHRVNKdN91gW6nq2VO2t7eHqzVYGpehGx42NGsT5qHut91uWbKcHra376l1p841vQUgAcHB7DrjWzx4JyI+mr+mbrQ6/VwcnwMqz5wDKz6GuIo0k5oDJMLwIIhoLYTaPd98j0A/YIhoP3jdLtHwrBbIgRUbwG4+2B3Yv6fYjvYwM4DfQXg4eEh0jTFdm26A7jhr0AIQQewako7gFZ2nE4TLLWKMG8TeEXNtVFz9dsKIg/pLOoAahwCWkQA2lYmnnTsiI+Pjwo5gEIAvm9pJwA7nTbK7hltaybI8xDQWhkBaI2+VyN2dneRztqmpuEb5wAqR0O3iW0RlAsm+iGg6m/d3LHDw0OgPj2fpgyiVh98piYcHR1ByhRiSAAqN1DnkGh17TtuMeHhuAFaLb3uEyXkijqAum4G3+12c2dvHjo7gL1eD/sH+7hR25p6zHawqZ15MYxq2ywBaFsWtmqrFIBVkzs2JaqADr9PB8oKQADYrnvaCUBF0YwnHcNj1HXh2PO/hRACrmNpdS0pTk6LhYACWR7gqWbl47udbmkBaPUdQ13ClAYCsHgOoAoX1cnhUOzs7kzM/1OIlQCtZlPLickker0eov69q8s1U4ZBiHFt5G+dxBEAHBweAkHRzTBnI2qZkNRJ5CqRZzU28ueshjkCsEgVUCATgLrd22rhsl5iG4jh9+mAlBJhFMIrWPXM11gA7u3tIZUptoPpVVm3a5tod9ra7lk6mI/PXlTYDtauzMmkAJyC2sBXOXvzUCGgOm38m5fNLSMAAxc7O3rlAJahSJ5gFZRxANVxuglAKSWap034BS8nz031WxENw/IhoJo5gEdHR7DqDkSJvQyVW6jTBBfI3P39vX1gZUaeyko2MTHFBRwWfSY6gIMFhvrI37oJwMOjo5kCMHzmV5HuP0C6/wCdj//8zA3hlQOoU3+VC8ChHEDLAAcwL3hWuAhMoN1CSe4A+sXyS9VxOl0/URRBSlk4BNTpD4y6zTuAYfG0MfWY7X54qG41LBSqXTdq0/MYs9fXrmwOTgE4BSXkHLvYT+T28xB0CwENXAeNIruP99mqedjd0ddGN5WBA1jseMcW2nXE3W4XcZzM3QNQkTmA+qyIAkAcRbAWDAHV5XxkpeFLrnT0j9dNAB4dHaGXJBArsx1AQL/qxNMYrmh4qulq9CzybTnqmSgSrgvL87QTHVmhmukuU7q/A0QhEIVI778xe0N41wMsS6uIBbWAO+oAboy8piODENBiAtDW2AGsBQUFYKCfAziIYiu2YmsJC57taTPODZOLp2B6CKgKD9X13tjd3UXN9VGfExq9XVvD3t7elVQkpgCcghJybkEH0LH0dADLhH8CmQA8OT3VshMwGXU9FReAUrtzoCZHhUNAPb1WRLNtWtLyIaC6CcCjQ6RByTBnTXMA88F6pgOYvabryu44wyFIOgmKohwcHEA4TnYD9xH1hlYCsNfrodNuQxTtjOYghIDt17Q6X7u7uxCWnReoAQDh+rCDuraTXGCRHEAfnU5Hq9SN09NTWMKC7xYLMfbdGiyh1wLCoI5F8Tmg5+gpANXi31YBB1DXhcIHDx7MzP9T3KitIen1rmSspgCcghJyRQWgcgD1EoA72ArKzXZVuKgp4VamUNYBtG293GRgSAAWDQH1odX+TuocFLylc3R0AMtsAQEAwhEQnqWVIAcGok6szhCADT2rE08jnwSurWg1ISzK3t4erEZjpCprWq9hTyMBqEJrhV/MZSqC8H2t+qvd3V3YKxsQYvReF40tbSe5wCAE1C6Ye+Y4PqRMtZo7nZycoBasTK1MPI4QArVgRSsHcGBiFBeArqYO4M7ODlb9FfgzxOyavwrXcrRdKHzw9gPcLCAAlUi8iu9BATiFPAS0YIlplQOo06R9b3cXmws4gICeArDI+qBGi4gjlHYALanVtQQs5gB2Ol0kSXKJrSqO+j3LhoAqwajL+Tg+PgaC8l23qOknAPOJ7AwBKGwL9kqg7cA+jpoEivUVNJtNrZyNIuzt7UHWR50PUW9oJcDz3MoLcgABQLqeVjmbDx48ABpni16IlQ080FwAOo53RrhOw3b1Kz5ycnKCoGD+nyLwGnoKwBIOoGt72oxzwzx48GBmARggC2Hdqm1quziys/Ngbv4fANzoV/29iu9BATgFNWktKgDt/nFXEbdbhDiOcXh0jK1gMQGo02Cfr8IVnEcVXbW7SsqHgGZ7+OhEWQdQFYvRxQXJBWBJB1AnARjHMTrtTvkcQAAy0CskF8gGOctzgDl5yumKr+3APs5AAK6ilyRaTWyL8GBnB2iMbq8gVho4ODjQZnxTv6lwSlZ0moF0XK2Kkbz9YAfW6tmcJ2tlCw803u8sDEPYbvF5h9N3CnVynk5PTxF45bYYCTy9HP+BACx+jzjC0cqJVew+2MGNOQIQUHsB6rdQ2Gq10Gq3c3E3CyUS6QBWiBKAdlEB2F/t0sXtODg4gJSytAO4GWSdhY4CsJADCH0FoABQdM9i20ZeSl4XygpAd0kEoNBIAOYrzGX2AOwjA5FVTtSIBw8eADM2gc9ZDXDv7ftX06hzokS22MwGe90K78yi1+vhYH8fYmXU/RArK0h7PW2+Sy4WLlAACsdFp6OHWE+SBAf7+7BWJgjA1W10O21t+tVxMgewuDNra7gB+UIC0G9odU7yRWerhAC0XC3GuWGklNjZ3c1z/GaxHWxquThStAIoAASOhxW/TgewSso6gOo4XQSgStjfrJUbIH3HRt1ztdovrJSgyxTgpbVlUeI4hm2Lwt/FtoBIs5U4VdyicA5g/zhd8mrUymbByKQcJRh1WBnNBaBf/hoXgYWTE70cwHv370POKgCjWK1hf29fGwdqFsfHx7A8F6KRhVHqIpqKcHh4iF6vd0YAov9YlzBcNUkVTsl47lk4LqJYj8nv7u4upExhrW6feU09p8u5GCeKosL5f8AgV1An4XF62lzAAWzg9FSfqr8DAVj8HnEtVysnFsjEeDfsYnvGJvCKG7VNHBweaHUtAcMCsNi+kjdqa3j77bcvs0kAKACnkjuARePYhV4hoCqHb7NkCGj2HlerHMDcASxgAaYALI0FYFFsC4g1mYwoms0mhACKzrlUeo4uq6Lqni7tAPa7AB3ubfVbigVyABEInJzocS6AbGX3wYMHwNp8AShWA6S9nlaVKKeRFempAfXse5kkAHNRsTK6WbHoP9ZFdOSLMWVv5llYljYTRzX5myUA79/X0xEPwxBWibwzW8MQ0GazCX8BAajTJuR5IcMyIaCWiyTWw8RQDMRTkRDQ7Bid5q/A0Heoz3cAAeBmsIadtxkCWhm9Xg+WKOPY6OkAbgSjN//Pf+UN3Dlu485xG//Nb30dP/+VN868d8N3sK/RDWT1f9u0gACUcnC8TkRRVDj/D1BVQKt3nIZpNpvwfWvEYP3iF4Cjw+zPp341e6xQDqAug6K6N0s7gP3jtXIAg9F+Kf2tFrCXAHsJev/qOHs8TiAQhaEW3wPIrotup5Pv8zeTfpGYq1gVPS/7BwdIaz5ELWuzTtEU81C/r1gdE4D9x7r8/vk4e4F9vbBtJEn1izzAQNxZazfOvGatZQJQl3MxThRFsEuIDluzDcjTNEWn0z7jAP7a73wEOwd3sHNwBz//ib+LX/udj4y87nsNdDptpGl6lc2dSh7FJoo7gLZlI070GB8U+SbwBXIA1V6AuuWLP3jwAJ7tYs0rtq3Ijfo6Huw8uPQCYvrNlDUhTVNYYzPFdhwhCAJ88IMfRBAEaA85NMp10uXmPzw8hG0JrIwVV3jjuI1O0kMn6eHr+6d44/hs1bONQK8QUCXoilYB1VEAJkkCyxqdtIcxRq6ncKjfzRxAvTriVquF8dz+w0MgjrM/uzvZY4XrDt6nA8rBG1/TSaLR85CMmQA6OYC5mB4LAZV7CRAh+3MvyR6P41ujn1Ex+QR2bfpm3gqxWht9j8bs7e9B1AOgLwBNcC0VSnicEYCuC6te1+b3z8fZGX29jMKR+1pGcwSGsJBKPcbv+/fvQ1j2yCbwCsuvww4ay+MA2nqFgKo9CYOxyfqDgzsI4zbCuI03HzyPBwd3Rl4PvDqklNoUElLzB3soBLQTd0buiU482lbHchBrtvCcC8AhB/Dnnv9X+Lnn/9WZY3XdC/DBgwe4UV87Yyh95Nlfw0ee/bUzx9+orSGMoksv2naBAfTLhXIAh2nHMT7wgQ/gQx/6EKSUeOaTgxOnowBcD7yFwiHXAxeHb+9BSqlFQZUyIaC6CsA4jmGPNSuKMXI9/fqvPpW/Zlt6CI5hWq0WXLf4ipQSgLoIjlwAjp2HJAK+b+g8PP1rT428rm4BHc5HHk4bLHBf9kXj6ekpNjfnr6ZeNgO3ab4ANMUBlFJif28f+MYnIGwLVr1mnAC0G43JuXWrq7h3797VN2oC+cr4rPEp6o70r7/0qd+Y/7lFwkyugPv378Ne24aYMpaJtRvanItxoiiGbRe4p/tY/UI+ughANV75Bd0ahTq+2Wyi0SgXPnoZDLYyGxKASXvknvitTz4z8h7bcrSJYlPs7u7CtV2suoPf9I2TuxOP3dRVAL79ANvB2fy/OyeT26lCRR88eICNjY1LaxcF4BSklGccm7rr4umnn4aUEp/4xCdwyx90croJwIODA6z7i53edd9FHCdoNptYHVsJrgpLiGI5gBJTB80qyRYURp/zXIxcT8ORcJbQJ5xY0Ww24TjFJ0i2DVi20M8BHLs8HG/0PDjj437/vOlwb7daraw97gJFYDwBCX0c2YEDWCAH0LZgrdS0F4Cnp6eIowj2Sv8iatS0m4zM4u7du5BrUwoVrK3hzbuTJ16VMWtQ8IKR+xqNYvk3OvDW3bvA2s2pr4u1G9kxGhLFESy7+LzBtrN5ii4RL2ovSN8tLmKHj9dlL0k13tlDebI1pz5yT9zwbo28xxa2Fgudw+zu7mK7tlHIjPBsF2v+qlZV7IFMyH3n5rsKHz+8FcQ3fuM3XlazGAI6jTRNITAuAD10u1089dRT6Ha7qA/FwykBqMvNc3hwgLU5e2tNY93PVuR0Kl5g2VbhHEDbvsDCABdEFgI6+gV8FyPXkz+UNmHZ+lxLilarWbgCKJAtznuu0GZAVAJufBhxvNHzMF7ATggBIfQ4H61WC5ZnL+bM9x1AnQSgFXgQfrF8Ibnq477mAlBNPERfAMpGDW/v6FE4pQiZ8JgslMTaOg729rTI1SoS5SE8f+S+FvM2jZcS1niYRgVIKXHv3j3YE/L/FPbaTezu7GgjmoZJ4gSWXXzuYfUdKl0WPJdNAFpiSAC6tZF7ojb2HW1ha3MeFDs7O9jyNgofvx1saLXo1ul0cHJ6gpsFC8AAV7cZfPW9naZkOYDFJ1m6OYBHR4dYKzixGmet7xzqJABt2y4kAHtSjqx46UKSJGccwFnYAtoUJFC0Wq3S2265rj6CYxA2tsCbBS49IbsIrVZroS0gAACeXgLw/v37eWhnIdZquHdfz7A3xaCKZiYAxWoDuzu7Wlw782i1Wjg5PoZYnyIA+8/rEHqYC8ALHG+lTLVIHzg8PES304G1Pt0BtNZvQspUS0c8jmNYJYrAqGN1CQFVAs4rKQA9bQVg8WvasiwtFjqH2d3ZxVaBPQAVW/4G9nb1KWKoRFyRPQAVDTdAzfUvvepy9b2dxuiQ/7YIUkocHZ9gdcEQ0FUdHUBhtgPY6/VKFawTll4LCkC2kuWWFICOq09SvJqEL3JbCyG0mMS32+1cyJWm/z5dJij37t+HXC2+YbRYDXB0cKjNRHESgyIq2b55Yq2BKAy16kun8eabbwIAxJScE/W8Oq5KHJWjmF7gZLWXDj63Qu72QzvttYemHmP3w0PvahgGGicJrBKLsJamIaCeW2Jxauh4XfrXPARUFD8XtnC0EoC9Xg8HhwfYqm0Ufs9msK7VNhCDIjbF9gBU3KitUwBWhQ6TvUVpt9tIkgSrC4aAKgfwsisQlcG2LaQFFGAqAUtTASgK1THNUG6hLp1xVt2sC7fkJeU4UhvH6bz3tA59Qrvdhlx0jtrPG9RBkKdp2t8DsMQq+1ptsHegpty/fx+W5wH9/VeVENS1YuMwb7yRbQk0XQCujxxXJV4/Fl1eZP+YJvDLxLhfEm+99RYAzHYANx4aOVYnekmSh3UWQYlFXca6brcLoLwAdPvHq/dXTZ7yUMIBFEJoteh8cHCANE2x5W8Ufs92sIFWu6WNEM8dwHpZAbiKnQcMAa2MMuvs4/mCVaL2ChvfAqIo6n35nmMaUDQENJVCSwcwTdNyDqBGhUeALDwnTdPSIaCOA3Q6enTE50WHiIBOpwO5WGS3Vg7g/v4+ekkCUUIAqmN1FlP37t0D1lfya0Wsrwye15w33ngDwrIgphSBEY4Le21NCwfQ9/vO8QXmK8kkhj8vT/AKeOuttyBsZ+Im8AorWIEdNPQUgL1yDqDoO1S6jHVqgcx1SjqA/eN1WGADhiNeyqQyWVosdCqUk7cVFA+fVJVAdXEBd3Z2YAkLm8FKqfdt19awQweQlEWVil/1FpspOpaFwLW1E4C9AuNDL4UWYTzj9Hq9UqGHujmAalAr+9O6rj4D4jLQ6XYWqgAKZGHFwhZaFPHIc5eKbAGhWNN/L8A7b74JrA2VgF9tAEJoOVEf5/XXX4fY2JhZRVmub+DV1167wlZNZiAALzAcOE5Qq5Wb9F8Gb775Juz1m3OrWYv1h/Dmm/pdV71eClEmBLR/rC7FR5SD5zrlFgPU8bqMd0rIWSXMCQG9HEC1hc5miRzATX995L1Vs7u7i63aaqlcTADYCtbQbLcu9XqiAJzBIusgOqyeKOHW8BZ3whqeq5UAdBwHvUJFYPR1AEs5yv2DdbiegMUFoOPo4TgBQ/tJLvJmTc5DN+xCnGN9Q7iWFgIwz5UrEwJa9yAcW1sBGEUR9nZ2gI2BgyZsG/b6qhau2Txee/11YM7+kGJrE2+99Vblk/VaLbtuZHxxAtBKovxzq+SNN9+CmJH/p7DWH8IbGl5XvV5SSgAqoavLYmcYhhAQcEoUsgGQH69LjnIu5EqsPOsWAqpcvE2/ePjkZt8t1MYBfLCDraD8dmo3+jmDl7mlBQXgFMoWfZD9aaUOVcRUzlW9bMLWEHXH1iZ3CwBsxylU8K0nAbdspZIrQEq5UPERXTpjtSq6iACMouoFBzAUCrOAlpNSj3s77IaAs3goqn4OYHHHRQgBsarvXoBvvvlmdp9vjE5W0vUVvHbn9WoaVZB2u43dnR2Ira2Zx4mtLfSSpHJHs17vb7NxkX1LHFW+gXeSJHj77fuwN27NPdbefBjHR4dajdNAf7GzlOiwAAitBKDjeKVD/oUQcB1Pi/4VGAoBLekA6sT+/j5sYWHFK35fbvTF4sHBwWU1qxQ7O4sJwK3aav7+y6L6GY2mlL350wXirS+LZrMJAKi7izthdcdCq9W8qCadG8e2kRTQQmmqZxVQKWWppFLdHMBFBaBtA92uHiuiSsAt8pPqIgDjOM72CFkUR48V6rfffhv2Sg2i5L5rctXHXU3z6V5//XUAgNgaFYBicx337t7TpsrhJF7rh3WKrel5Z8Ovv1ZxGGgQBFmxrwucbKdht3IBeP/+faS9Xl7kZRbWenaMbu5ymspShUcAfaosA5kAdMc3gy2I6/jaCMBl4ODgAOvBWqnwycDxUXMDLQSglBJ7+3vYri0uAC/Tyax+RqMpQohc1BVBHarDJHHgAC4uhGqujeapPgLQ9byC+wBq6gCWDQFV79NoUASAEvv7AsgEY6/XqzxkDBgsDMiSpmqeS6HBvZ0JwMXfL22hhRB5++23kZbYAiJnNcCDB3o6gK+//npWRGV9TABuryPt9bSbqA/zyiuvAACs7TkCcGMDwrbx6quvXkWzprdDCKysrECGF5MfI9MUadjF2pQCOFeFukbsjYfnHqtcwqrd2HGkTI0WgFEUwS4Z/qmwbVeLBbZl4eDgABte+Xty3V/TQgAeHx8jSZKFHMBNPysawxDQCrAsKw/rLII6VgcHsNPpQADwS66uD1NzLK2qN7qOi6SAAtS1CExpNHMAlQB0SooPJRh1WBXNBWDJn1QJRh2uq17SO58DaOmx39a9t0tuAt9HrNXQbrXzKAedePnllyG21s+4mtb2BoCByNKRV155BVZQA+Y4YMK2ITY38dLLL19Ry6azurYG2Z0uAK3thwDPBzwf1u3HssfT6AvJ1dXyE7WLZCAA54eAWms3ISxbi205FItUnsyO16f6ZBzHcMqudPZxbEeL/nVRysx5r4LDg0OseeWqZwLAuruihQAcFLEp36+4toM1v3GpxWwoAKcghECvRP5VqpFL0Ol04LvOucRo4NjodvTYzwYAHNctVAU0SaUWE/Vz0++HdVhQAAZhg2Wja9XxOqyKquuitAPYP77q0OI0TbOc0PN0MRoIwDiOcbh/UK4CqKIvGnXbC1BKiRdfegnYmlCufH0VwnHwsgaiaRovvvQSsL1VrL/Z3saLL71U+YR9c2MDsjt9kdL/7j8Ja/sWrO1bqP3ZPwf/u//k1GOVkFxfL15u/jJ48803YTfWIPz594awbdhrN7QSgIOc9fL5c7rkAMZxDNta0AG03Mr7V8Wg6FmZSDapxRxWcXh4iHW/vHha81ZxdHB08Q0qiRJvW7XyIhYANoOV6ycAhRD/FyGEnPDnL11VGxzHKRUC2uvPEqueJAJ9AVjWqhnDdyy0NSlnDGRhnb10/qDS6+kZAgpRZhv4QZ0S3QRgieJuAJZDAKaaOID55Oocvba0qi8stLu7mxVLWVvAAVzVcyuI3d1dnJ6cQNw8W0RFWBbE9gZeeOGFClo2nziO8fprr0HcuFHoeOvGTTRPTi41NKkIW5ubsGYIwDLIdpY2sTmnCuplc+eNNyDW54d/KsTGLS0rgS5SS0SXsS4puZH9MJaljwM4yHkv3t9L6CMA0zTF8ckx1rzyAnDdX8Xh0eEltKocSrxt+IsJwA2/gf29yxOAulslfwzAsAq5ssQD27ZLTZTSfniiDgIwiqJzhX8CgGdZiOO4X72y+o7Zdd1C20AkqdRSAOrwG56HRR1ANZboEAKqrou05EKzLiGgi5T1PoOQlQvA3L1bWWDPtb4DeJmV0Rbh61//OgBAPDSliuZDW3jphZeRJEnl19E4r732Gnq9Hpyb8wuPAIC4eRMA8OKLL+Khh4q95zLY3NxE2r6YCpiynYUUb82pgnqZSCkzB/Dx7yj8HnvjFu599Tn9rquyYfYahR4mSQK77EpnH9uytXEycwFYygEsV8H1Mmk2m0jTdKEQ0DVvBc1Ws/L7QoWhrvuLFZfa8Bt46+DuRTZpBD2k/nQ+L6X83NCfKxv1bduGBJAWXD3RyQEMwxDuefKEAHi2hVRKLYp3ANnkPenN/k5SSiQ9XQUgFtyATg/UdVB2XUHdDjoMiosKwLR/C3jeYpXhLoqBAFz8MySqzytV4k0skAOIwIVwbO1CQL/2ta9l+XH9fL9xxEPbiKOo8uIpk1Di1eoLu3mIrS0Iy6rc0dze3kYadi9kL0AlALfnFMG5TA4PD9FutWBtzs//U1ibDyPt9fJ9NavmPOJBF+HR6/VgicXmcZbQRwCq37PoHDY7Vh8H8Pj4GACwuoAAVNtGVL2X9eHhIRpeDe6COaXr/goOj48u7ZrS40xriBJyvSKlJ4eO02EVLo5juOfsTN3+TF+H0D2gLwDn9GPKIdRTAFqlio+oY3VYUAAGArDs2KCO1yEsRl0Xi4aA6nhdlUaDOVbu3i3gAKq9AHVzAL/67LMQD21BTLlfrYez8Mpnn332KptViBdeeAFWrQasFJtoCceB2N7G833hWBU3+iGrsnV67s9KW6fwgyDfX7AKyhSAUahj9aswW9oC1IZer1e6iqlCCEsbAajmDqUi2WQP1oLu50WjxNtqiT0AFco1VCKyKg4PD7EeLL61zEbQQJqmOD09fx83Cd0F4CtCiEQI8YIQ4i9e5X+shFxS8OZJZG/kfVUSxzEc63wzPbv/fq0cwHkCsDc4VjeUo1wUnbYVAQYCruzYoJMAVA5eWvKSVo5h1Q7gsrC7uwurEUzcA7D3714E9k6BvVMkv/S72eMxZMPDzq4+ArDdbuOVl18GHp7uoImVOqy1FXzlK1+5wpYV47mvfQ24+VA5B+bmQ3jhhRcqneze7DuWsnn+yZFsnuDGjRuVulDTtoBoP/NRnH78H+V/2s98NH9NCUBdCsHkhUdKRhnoFHqYpb0sLgCrjrBQqLloTxa/R3uyB+ec9SMuCiXeVtxRAfVzz/8r3Dm9izund/H3fvt/wM89/6/OvFe9p2oH8OjoCGvu5IJOH3n213DneAd3jnfwdz/zz/CRZ3/tzDFrXrYgdVlCVo/Z5VnuA/ibAH4IwPcD+ByAnxRC/JWraoASEUnBeDElFHUQH0mSYJr+68Q9BEGAD37wgwiCAJ148vezhV4C0PO8uQIwTgfH6oZllRsYUs2qgKrrYLw5cYyR62lc5ykBqMOqqO9n+86VbYoSjOr9WhLJkfOAaMq1psHcZHd3F2hMvkfl/ikQ9bI/946yx+Os+NjZqbYAyTBf/epXkaYprEcH+XDJM19E8swXRw+8fRO/95Uva3EvKE5OTnDv7l2IW2dz+ZLPPIPkM89MfJ916yGE3S5ef/31S27hdFT+Ydq8gMlR8xgP3yruvF0Gb775JizXh2hsjDzf238Lyf2X8z+9/cG+f8KrwWlsaLMXoBCiL4JGB+s46oyOE9FogTkpU20WO9N0shgNo/bIdwijswWIhBCV51grcgewjABMe9pEHamtflbcUVf+jZO76CRddJIuvn74Ct44OZsj1+i/57Kcs6IcHR7mIm6cOyc76CQhOkmIr++/iTsnZxc1V/3svUdHR5fSvurtqglIKX8FwK8MPfW0ECIA8GNCiP9OjvUuQogfBvDDAPDYY49dSBtKO4D9PQp0cAB7vR6cKcKhnST4wAf+ND70oQ9BSolnPvlvJx6nBKAukxXf95HMqQKTaOzUWJaFVBYXc7o5gOo6GG9OHAEf+MAH8uvpV3/1qZHX1WWow3WkBFxZB7DXPz4IFshZu0Dya2FSWHooR87DU5/6+MTPELL6a+rtnQeQjXOI6ZUAxy+8XXmCv+KLX/wihGND3BpU0ZT7R2eOE++4hfYLr+Gll17Ck08+eYUtnM7zzz8PALBuna08mc4oP66O/9rXvob3vOc9l9O4Ody8eTPbQPz0aOoxM/f+G6Z5gocf/s6LadiCvPHGG7A2bpVf9Ft/CHfu6OEAAmqxc1wAtkf6p09+arCwIKWElFIb4ZGmEmJCrHwYj36H3/i1s4sjOgrAXomk957URwAq8VZ3y4dlN/quW9X7xZ6cnOB9m8WqK09ipf89LsvJrH70LM5HAfwfATyBsWqgUsoPA/gwALz//e+/kDVuJSLiog5gf5VFBwdwVuXOuuPg6aefhpQSn/jEJ3DLm3wJqLfr0pl5noc4mX1q475A1FEA2rZdKgcw1SwHUF0H45eV62HkegrGoh10EoC2bcNxbKRJubboUgQmvxYmXUe+GDkPWJkyiZSi8mtqf28feO/ixTZEw0cqJQ4ODiqtQqn47d/5HeD2TYg5oVPWow+jB+ALX/iCNgLwueeeAywrr+xZmNVVWPU6nnvuOXz/93//5TRuDo7jYPvGTRyeTHcAZ+39p5BRiF6njYcfLr79wmVw5403Ya2XX8C2N27hzTtf1KZit2VZkGPzBterj/RPfmPIbdVoD+WcCT+j745+h7XaBMdYTnlzBQyi2IqvePbSBG5Q/RwWyMSbgEDNKb9YqBzAKgWgyt1bvbXAfrd9Vr3svdctBHQScuzvS2Vw8ww6ssfXt1B3XNQdF9904xYeXx+UjI57+oSAzqLm2uh2u3jqqafQ7XZRcydPWiatgFVJlgMokUqJ2+sWAgcIHODdNwRur2eXcaJxCGi2rUjx3zRNs8G86sm6otfrTSwA47oYuZ7GL//ctNJkIcH3/dzRU6xsA7ab/Vl/OHs8jDq+Vlu8I78IBg7ghBc9MXIe4E2+1qp2ADudDrqdDkT9HA5g3z28zA1yi3L37l3cu3sX1mO35x4raj6sW9v4zGc/ewUtK8ZXn30W1vYNiJLjlhACuHULX6m4qM2jj9wGZjiARUhPsv3Cbt+efw4vizAMsb+3C6tEARiFtfEQ2q3WpYWJlSVzAEcX2VyvNjpOeIO+VLmFWgnACbNM36uPfAd/QmifhDzXLj0XSZ4DOCQA37H+OGpODTWnhvdtP4l3rD8+8p4kTeBoModtt9sIXB/WAvmYvu1BQKDdvph9Qheh0+kglRINd/HIoRUve+9lCVmTHMAfALAH4M5V/GdKyEVDzsUPfesfxJ3jbF+PH/uePzVyvHIKdRQfy4D6XZMe8Gf/gIP7x9mg8Rf//cHvHWscAuo4zsTIvWmkKWCfcy/Hi0RKea69LHRJjA9qAXrx6KDwnn9PoLmfte8P/Omzo3evn9dYtQBUCwJpmQtpnF61i1RqXyScIwRUice9vb2LaNK5eOaZLAzMevzRQseLxx/By7/zVezs7FTuXkZRhBdeeAHiyW9a6P3i4dvY++xnKv0ujzzyCL764kvn+gx5nAnARx8tdg4vg7t372ZhkOvlf0d7PRONb731VuUb2QP9sa5E2GHaFyg6hHMD2TC3+L6EixeQuWgmOYA/8M1/Hm8dZ1Po/+d3/7/OvCdJE3iaCMBWq4X6lAIq87CEhcD10WpdzD6hi6BE23kEoGs5cCz70r6HHlfqGEKIfymE+FEhxAeEEH9GCPERAP8xgL8znv93Wah8obhg6FrUtwl0KRRx3um26gB1CCkBhs/H9GPUa7qcg2GyiXvx41OpT/gn0A8rXuSNYvB+HajVarmgK0raP77qHEAAcFwHOE80rS4CsH6ORZr+ew8PDy+gRefjN3/zN2Hd3IJYLVbq23rXOwAMhGOVvPDCC0jiGOL2YqGPVt8x++pXv3qRzSrFO97xDqSdNmTYmX/wFNK+AHzkkUcuqlmlUUVcrI3yAlC9R5dCMI7rQpYSgPpUUAfKF2wbRmq0j57q5+O0+IDXS5NsjNGAdruNwF58Lhc4QaUOoBKAdfcci51CoOHVrt02EC8A+AsA/iWAXwTw+wD8n6SUP3FVDVAiIioYP62cQh1CQG3bRnrOCbduOWjFBKAcOVYnMgewTAioPgPieVDfWBcB2KivlBaASf/4KvcIU7ieO9jwcgFET1Z6XSnRJmrnEIC1rI+tOuTt/v37ePHFFyHe/Y7C7xEba7C2N/GpX//1S2xZMZRwsx5eLPRRbG3B8v1Kt7Z4xzuy3z49Olj4M+TxPja3tit1+O/ezSoZLuIAWitbEJaNe/fuXXSzFsKxbaTjcfYz0M0BdBznTAhrUaRMtZkz5VFTJQRgnMbazJ+63S58e/FxIrC9LB2iIpT4XCSHcZjA8dDpLL7ANQstBaCU8m9IKb9RSlmXUtaklN8ppfzIVbZB3TxRQQdQOYU63DyO4xTewH4a6v36dWbTv5fOVUBd1y21/UDSA1xNBsRlotFooBeX8zJ7MeB5rhYTFN/3gXPszCJ7slInMxdt53AAhWXBqnmVO4Cf+tSnAADWe8oV7hDvfSdefOGFfNJfFV/+yldgbW1DLHg9CMsCbt3ClysUgO985zsBAOnR4vmg8ugAjz/2zotq0kLcu3cPTmMdYgG3QFgW7PUb+jiAjpOLuiIosahD/wqoBfTFBGCqURXNwaJ5VPg9cRppM3/qdDrwrcXb4lnVCkAl2gLnfL9nzXYvzcnUUgDqQO4AFlzJijQSgLZtn8ckAAD0+pG2unRmatIazTgdkcYhoK7rlhLlaQptQjGALBRhkUtKvUeXUOJ6vb6QAAxq1Yd/AoDv+cCcarizkHG1AjCvZuafM1Ki5l1aZbQipGmKT/zKr8B69KHC4Z8K632PA0Lgk5/85CW1bj5xHOO5556DOGfhE3H7Edy7e7eygjy3b9/OKiwvKACllJBH+xe2fdSivHX3LrC2eLl4sXoTd+/q4QB6nodeGQewf6wuwiNL11hQAKb67Gc4MDFKOIA9fQRg2A3P5QD6tquFAPTt8411vu1eLwdQB5SICAuWjA81ygH0PA/JOUPu4lSvLRXy1awZeXQqPFSHXK1xMgFY/Pheqkc4sUIIgVL7WCg0288wcwDLvSeJgJXGyuU0qCRBUIOMF89PkXFaaR91cnICy3chzlngSHrOpe2NVIQvfelL2HnwAOIb3136vaJRh/XOh/H0Jz6BJDmHnXsOXnzxRURhCHHOvDer//6qwkBt28aj73gH0oPFCgLJ1inSKKxcAN69ew/W6uIC0Fq/iXv372kRau95HtISnWyvf6wuc40sgmoxAdhLE23G7cUcQH1CQKMogmst/lt6losoKv7dL5owDAGcXwB6toOo/1kXjR6zMg1R+QBhwY4sTGI4jqNFGIPneYjKqI0JqPfr0innndmM+ZLOOYCe5yEp4dxkAlCP3x7oO4CL6z9taDQaSMJyrUoiYGVFDwHYaNSBBQUgNMhlPDk5gbiIfaZqLo4qdAA//su/DKsW5EVdymL9vvfi6PAQn/nMZy64ZcX4vd/7vawd53UAt7dh+X7+eVXwrieeAI4WE4DpYfa+J5544uIaVJJut4ujwwNY6yX3YhzCWruBKAwrz4sFAN/30EuKC0AlFnURTq7rlgphHaaXxtp8jzxqqldcPERJqM0CehRFcO3F59OO5SAKqxOASnye5zsAmZDtdikArxR1E4QFV2jDXoJAE+HheV4uhhYl7qVwHEcb52bQmU3/Xio8VFcB2Etl4RXapKfX91Ab2ZcVgapmry6hxCsrK0hiCVkiHLcXASsrq5fYquLUa3VYJUNYc/rCscpiF81mE9K7gEUyz6lsk9/79+/jc5/9LPCN75q7+fs0xDsfhrW2gn/5sX95wa0rxu99+cuwthfP/1NkeYAP40sVCsAnnngCvZMjyLj8ZE8e7AIAHn/88TlHXh4PHjwAANir23OOnI567/379y+kTechcwCLnwslFnVZbM72HC4ZJtKn19PPASwqAKWUCDUSgHEcw7UWHyvcih3AOO4vbFjnm/s4to2kxIJKGfSY3WtIHgJaMJY9TBLUgmr3CVPUajV0C4auTiNMUtQCfQRI3pnNdAAzp0qXDngY1f6ipyUTgHp0xMAghLOsANStmmyjkeVrJSXGhV5kaeMA1ut1YNExLZKDz6iIZqsF6V3AteA5aLer2ePpYx/7GCAE7G9+78KfISwL4pvfh+e/9jyef/75C2zdfKIowteeew7i9sVseyAeeQRv37+P3d3dC/m8sij3Trl5ZUgPdrG+sYn19fULblVx3n77bQCAdQ4BaK1tj3xWlWQ5gCUEYP9YXRY8s/YvNuFOevo4gIM5bDEBmKQJUplqIwCTJIEtFheAtmWjd8558HlQ4f3OeQWgsJFc0vegAJyCZVnwPQ/dgg5gt5doUygiCAJ0k+Rc+QDdpIdAE0ELFNsGIupl4Se6FBwZJt+UteB93NPQAQRQai9DQD8HcHU1c/KSEhEVOoWArqysAOGC4d3991X5XZrNJnBBDmC300WvTGndC+Dw8BD/9umnId77GETjfELaevJdsAIf//yf//MLal0xvv71ryOO43Pn/ylUHuCXv/zlC/m8srzrXe8CAKT7O6XfKw938Z73lM/jvEiUA3guAbiyNfJZVRIEQTkHMA7z9+mA53mIy6wQDpH0Im3Gbdu24bkewoKDncoV1OU89Ho92GJxiWILa+FczotACUDrHN8BAGzLogNYBZmTVlAAJglqGuwTBvQrHaYyL+SyCN0krTRUbBzVKc0UgInUJgx3nNIOYCq0CYkBBiW6SzuA6ej7q0YJwKLRYlJKxN00f1/VrKysIA17iy3u9HMfqxSAnU4HcM+/GCD6LmJ4Scnx0/jYxz6GOIpgf9s3nfuzhOtC/P734nOf+xxeeeWVC2hdMZRQO2/+n0Jsb8MKgsoE4MMPPwzfD5AelBOAMk2RHuzh3X0BWRU7OzsQtgNRX7yPEa4Pu9bAzk55EXzR+L6PpEQ4btIXKLoIpyAIEMeL9StxrE8IJZB9lzApVgmzm3Ty9+hAr9c7l3iyhIX0nLUwzkPan/xY5zQkhBClUlbKQAE4g0wAFlPe3STWRjCpMLfzhIG2kx5WNJn0AsPbQEy/EeKePp3XOLmALZhbniRCq++iHMyyC2pKAOoSFpM7gAWrQ6dJ9h10EYCrq6tZZZ0FCsFIDQRgGIbAgnlzIzhXLwAPDw/x1FNPwXrPYxCbaxfymda3fAMsz8P//JGr2+b2y1/+MqwbNyAuaMIthAAefhi/V5EAtCwLT7zrCciSDqA8PoDsJXj3u6t1AHd3d2GvbECc0ykQjS1tBGCvRIhFTzMB6Ps+UpkiKRkG2utlIZQ6LdzWavUSAjA7rsoUgWHSND2XeLKEWHg7j4tALdKeVwBaELmYvGgoAGdQr9eLC8Beos2NowRga1bC3BzacU+bsDdgeE+b6cdEib4CsKwDqJuYVQKu7IKa6n91E4BFF3jj7uj7qiZvR3eBFcFudvLW1i5GvCxCGIYX4gAqAXiV+zz9wi/8AsIogv2dv//CPlP4HsS3fgM++5nP4IUXXriwz51GFEX42vPPn3v/v3HE7Ufw4O23KxMg73vveyEPdks54+l+Fi6pgwBEfePcnyMa69jdXawa6kUSBAGSEg5aolkIqFrIj+NyfUsUZw6aLvNAAKjXa+j2in0PJRR1MTIyziOe9EsFWphLSmuiAJxBrV5Hp6AA7CSJNjeOmiS2Z8VLzqGdpFoJQMuyEPjenI3gJYKaPp3vMGUdwDipdsPucRZ1AHuahYAq8VN0gVrNY6oUTcPk7egsIgCz91QpZuMoAs65ByAAwMk+46qqvD148CDb+uEbnrgw909hfcs3wKoF+B//f//jpe/j9uKLLyKJ4wsrAKOwbj8MAPjqV796oZ9blHe/+91Iwy5ks/jekOn+Dmzbxjvf+c5LbNl8dnb3IBrnL0JjNTaxu1e9AKzVakiSCLKga6EEoC7zJ9WOqGiYSJ9IQwFVr9cRJsU2EQ97+rXfZFThvPScfbqEPLeLOA0KwBk0Gg10CucAxtqs/KgJXvMcDmAzirVxPRR+EMzeBqIntO28BgJwfmcgpURU8Ybd46i2lK25oY7XRcyurKxACFHYAUx0FYDdBUJCuinqjXplBXnSNIWUEsK6gMGs/xlXVQTmZ3/2Z5FCwn7/N889Nnnmi5D7R5D7R4g//utInvnizOOF50J8+zfhy7/3ZXz+85+/qCZPRAk06+FbM49LPvMM5P4+5P4+ol/+OJLPPDPzeLG1Dcvz8Nxzz11YW8vwnve8B8DA1StCuvcAjz3+eKXRCVJKHB4ewKqfXwCK+hpazdO8/HxVqDE4KSigkqQL23a0iRLJBWBpB1A/AVVv1PPQznl0+g6miiDTg/OIp2p3IVbFCM8rANOLGjMnQAE4g3q9jm7BOPB2FGlz46iS1qcLCsAkTdGOkkpLY0+iFgRzHED9BWCRENBemhVb0em7qBDcRQWgLnkRtm2jsVJH0bFdHafLvbCxsQEAkIs4gG2Zv78KcrE2azCLEgRBgA9+8IPZPTPthu8PrknBBbrz8OKLL+JTn/oUxDd/A8TK/EU+uX8ERDEQxZD3d7PHc7B+33tgra/ipz784UsVtc899xzszU2IORWe0/19IIqAKIK8fz97PANhWcBDD+ErFTmATzzxBIQQSPdKVME82MX73rv4Vh4XQafTQRxFsOrnX2CyatmCbdWbwecCMCooAKOuVmOdWsgP42LOmSLUMAS00Wig2yv2PVQRGF3msZZlIZVnFzo7SXdkjOhMEbiplLDOuQXDecjTZuTk/rzTLxiUf48pq9JJ2oPjXM7iCAXgDBqNBtoFVtOiXg9J2tPmxs8FYLjY5Eg5h7pMehXBXAGoj9M0jro2ogLrCSpMVKdBMc9hLHlJqW00dXIz19fWjReA6JR3AGUnxdbm1sU2qAR5IvuscJYwwQc+8AF86EMfwvd+7/cC0/qwK3IApZT4yZ/8SVi1APa3n7/y5zSEbcP6rm/Bm2+8gaeffvpS/g8pJZ772tcgH3roUj5f3LqFN994A63W1e/PWKvVcPuRRwtvBZG2m+i1m5Xn/x0eHgIARO380TaiLyLVZ1aFGuuK5tAlcUersU6lvoRRu9T71PE6pc7U63V04mLfQx2nyzw2E4BnFzrbcWdkjGhPEeqpTGFdRLrBgqhIm2RKKHQ7CUe/x5S8lEwAXo6Q1SMxR1Oym2d+jok6RpeVk3q9DsdxcFJEbUzgJNRTANbqdYQznA+di8CUyQGMNBSAqv1l59tJkoVC6BLeAwAbG5t46+BeoWPjbtZ+XQb1er0Ox3XQa5cXgFZXVOoAFsJ38PTTT0NKiU984hPAyuwh6rL3/Px3/+7f4dlnn4X9Pd8J4V3uNSze9Q5Yt2/iZ372Z/FH/+gfvfDx5N69e2g1m3Aemh3+uSjWQ7fQkxIvvvgivv3bv/1S/o9ZvO+978GDLxWrRKqcQhU6WhUnJ1nOohWcv3+xgsbIZ1aFEhBJQQctjruon3NPzYtE3XeLOoC6zAOBfhpTwe/RSfQSgLZtozfBAay7tZEx4pY7ef/MVKZ5Hl4VqKinuDd50ld3/NHv4U2OAojTHvza5Syg0wGcQaPRQNzrIZ4z61UuoS43jhACmxvrOOmeFYCPrddRc2zUHBtPbq/isfWzbT4Os/dtbVXnFkyiVqsjTqZP+MJYanMOxskdwKG+4OaGgOcCngs8ejN7DADKdNZJAA7yOkaf39wEXDf7c/Oh7PEwSQIEgX/pE/UybGxsIOkW6/riLrC6uqLNRvZC9EXcmAAUNxzAQ/bnESd7PE4rrfSeLnQNeA663S6eeuqprMLnnE3jL/O6iqIIH/7pn4a1tQHryct3ioQQsP7Qt+H09ORSNod/8cUXs//n5s0L/+zhz1X/z1Xznve8B72TI8hwvvOknMKqBeDx8TEAQATnFw2iLyLVZ1ZF7gBGA+GxceNxOF4NjlfDjdtPYuPG4/lrcdRGo66XaAKAbjjqZN/aehy+W4fv1vHOW9+EW1uPj7weRq2R9+vAysoKkl6cb/I+i27cQS2oaTPWuY4zMXyy5gQjY0TNmbzon6S9SheeVdRTlE4WgE9uvxNp3MO//vgv45a3hie3JxejinsxvEuKoKIDOAN1I7eTCOv29Ml4O9HLAQSAza0tHB+dzYf4c9/6GN44zlZ6/svveXLie4/7wnFzfDZfMbVaDVFv8oQvlRJRkmrrAHqeB8uyRorA/JHvsLF7lHUOP/jHBreiEok6idk8h3GsL/uO9wMq4uiP/8mz70sSIKjpdU7W19eLVwHt6ueEb2/fwF5zdJJnfU8Dvb3s5NgfPNtemUikYU+PRZ2LyM3vhwZdpgD8+Mc/jgdvvw3n+/53WY7bFWDd3IL1vifwLz/2MfzpP/2ncfsCt2t4+eWXIWwbYuty+nURBLDX1vDyyy9fyufPY1AIZgf2I4/NPDbdf4AbDz1UubPfbDYBAMI/f1+vPkN9ZlWoeVA8FEL5bd/9QzjauwMA+CP/4Y+NHJ9EHaysXM6ixCKo4nfdaFQA/onv+iE8OMi+w5/73h87875OXzDqVDxPnYtO3IFrz87Db8dtrDT0iHQBshy6ZIp4KkKSJnDd6iSOEoDhlJ0Efuib/wTunGQLUT/2h//TqZ8T9hI0LkkA0gGcQS4A54RStvshoFUPJsNsbW3jaMEcQOUA6igAwylmrNrxQifXbBghBOq1oFAOYNTf5FsnATjYG6nc+5IkK96jExsbG4g6aaGS+3E3CxnViRvb27DKpafkjmGV97TaCqRoefiZ9KsBX9b2IicnJ/i5n/95WO+8DeudD1/K/zEN+7u+BSmAn/mZn7nQz3311VchNjchLrEwgtzcwsuvvHJpnz8Llc9XqBLo/g7eV7H7ByDPlxTe+cct4QUjn1kVeQhoVCz0MIk7Wo11nufB8/wzAnAe3agFz/O1KXgGDOakKrxzFp24jcaKPiaG63qIzyEA4zSB61Z3LtScKSzgvs6im17eDgMUgDNQN097Th6gjgJwe3sbR93Fbp7DToRaEGjVKQOZCxVO2UZBuWa6OoBAX8AWEYAa5gAO8jrKvS+OgYZGq4pAJgClLLYXYNK19HDNhtje3gZaJUVU//jt7cn5EleBZVmwbHuwOeR56IvIyxKAv/ALv4B2qwXrf/Otl/L5sxCNOsS3fAM+/elP46WXXrqwz33t9dfPxmhfMGJrE/fv3atkK4KtrS2srq3PLQQj4xi944PKwz+BYQF4/nFL2C6E7VQuANXCeRQWW6WKo7ZW0VMAsLqygk5Yzknthk2t5oDA0By2gJhtxy2tBKDne4gLVuGfRJzG8PzqBKCaM3WScwrAJKIArAJ187TmbBrWivQUgKdhhHiBydZhN8aNG9VNFKdRr9dzd2wcJQx1Ek3j1BuNgg5g9rdOg6LneXAcu7QDqKsABIAiC9RRB9oVTtne3kYa9iCn3AsT6QvAGzduXFKriuE4DpBeQAxov1+7jByP/f19/NIv/RKs9z0Oa3vjwj+/CPYf+EZYgY+f+dmfvZDP63Q6ONjfh7hkN1tsbCBNU9y7V6zI0oX+30Lgve99D+TBbAGYHu4CUlZeARQAwjAEhAVYF7OQYbl+9pkV0mg0sr1WC1TRlFIi6ra0mjsBwNr6Ojrhaan3tMNT7dIFBibGfAHYSVra7HcL9Bf808XFU5TGlRoCg/Db892P7Ti8tLkgBeAM1I/eMtABVBO9w275G+iwG2P7hj4x+YogCBD3JHoTJpChhq7ZOI3GSikBqJsDW6vVFggBtbQ7J0rQzSuOlvYk4jDVTgDmIq6ECyg1EYB+4A/itc9Df0PNyxjgf/EXfxFxkhTa9P2yEL4H8a3fiC98/vP4+te/fu7PU4JMrF/uBE/0J8BVCEAAeM+73430YG9mmLEuBWAAoNvtwnIvrkiWcL2seFKFWJaVFWwL54uOXhIhTXtazZ0AYH19Dd2SDmAnPMX6Jd9fZSkjAFuxXkLc871zhU9GaVzp9lMDA2nx+zGVEu2oe2nnhQJwBoMTOPsibMURLMvSKvzwZr8i20GnvIV+0I3x0CXtFXUelJCYtBegGQKwgWhGFVNFGOvpZq6sNBZyAHVKigeKO4Cq39ZWADZLuPvNFK7rVn4uarXaxQjA/mdc9D1ycnKCf/1v/g2s9z4GsVbtZMj6/e+F5Xv4F//iX5z7s3Z2MtEjVi73/KvPV//fVfPud78bspdAHh9MPSY92IEfBLh163K2wyhDFEUQFxnGbLuIovOFnF0EjUajkAOojtEp2gXICn+VdQA7YVM7B1D190UEYDtuVT4+DFOr1RCdwwHs9sJK51Dqt2yeQwB2khASkgKwCtQJbM3pUFtxhJV+2IMuKAG43ylnPydpiqNOlL9fJ5QjNqm2TWRACOjKygqiuIAAjIBaLdCmHLNiZWUVZecWUSi1G9xVTt88B1AJRN2KIal7U5bJA2ym2L65XXkfVQtqxTbDnIOMehBCXPgK7yc+8QlEYQjrD0yukHyVCM8Fvund+MxnPoMHDwoUNpnB3t5e9pmXfS/WahCWlf9/V8273vUuAJiZByj3d/HEE09UukeYIkkSiAsK/wQAYdlIxks1V8Dq6iqiAg6gOkYn5wnIBGC7rADsnugrAOfkAPbSBGF8eU7TItTrdXTPkT/XSbqVzgc9z0PgB2gWLIY0idP+ey8rNLf6HlBjfN+H67rzHcAowuolr6yWZeAAlruBjroxpJRaCkDlsE4qBGOKAxgWyNuKYqCh0ca4ipWVVcy5FUZIUyCOL2/1alFWVlZg2xaiOQtzsaYCMHcAT0s4aU2JWzerdzxWV1cnr+CUJUpQq9cvVNBKKfFvn34a1sM3K8v9G8f+fe+FlBKf/OQnz/U5R0dH2T8ueUsWIQSsWm3w/10x73znO2FZFtKD3YmvSykhD3fxHg3y/wCg1+sBFyhEpTYCcKVQCGis4dYJQBb10ek20StYhbLXS9AJW9pFiziOg1pQQyueHc7a6gtEnXIAa7UaOr3F3DMpJbpxtQ4gkP2ep+cQgM2+Q35ZCwsUgHNYaTTQiuYUgYlDrGjWgdVqNaytrmK/XU4A7vWP1yE8ZpxJm6kr1JxSt7y5YRqNBrqRnLv9QKhh4RQgE05xXLzLUOGiuglAy7Kwvr6OeRFKqt/WbVAPggArqyulQkCtltQirHttdRUiuoAQ0DC+8Enjyy+/jHt370J8w+PzD74ixGoD1qMP4VO//uvn+pxmswnL8y51C4gc38fpaTn35KLwPA+PPPpoVuhlArLdQtrt4Iknnrjahk1BSglcpCsvRKHtbS6b1dVVxAUqT0b9PDsdBSAAdLrFrmPlFuo2VgDZb9uKZgvAdqzfeWg0GuhEnYWu5yiNkcq08vngxsY6TgoshEzjOKQArJTVldUCOYAxVtf0uXEUt27dygVdUfbbYf5e3cj3VZkoAM0IAU1Tid6c+W8YA6ur+qzEKdbW1kqFgKpidDqtKio2N7eMDQEFgIceegiyoACUqUSvmWghAFdXVyGK7IUyj25y4ZOVz33ucwAA64l3XOjnnhfxxDtw7+5d3L17d+HPaLfbEJdQMXUS0nUrLUTyrieeAI72J74m+8Lw8cf1EfnLSOEQ0K6+DiAAtLrHhY5vdY5H3qcTa2trc3MAlQOo03lYWVlBT6aI0vLjRbs/uFe9+Ly5tYWTArmw01Di8bLmIBSAc1hdW52bA9hOosovtEncevhh7JUMAVWCUYfJ4jgDATghBDQePUZHVC5cd05/FsVCy+tpdXUVYZii6IKcum10GlQUW1tbiLuzV97jDhDUAq2KOyluPXQLVtEida0UkNAirHt9fR1pJzq3SyG6MTYveLL1la9+FdaNTYhadZXjJmG9I1uM+8pXvrLwZyRJAlxRTrG0rErDEB9//HH0jg8hJ2xamh7u5cfogBAChTvUIkhZeZ4v0B8rus2597muDqCacLc6J4WOb/eFoo6Lhdkcdk4IaN8B1GmxVs2X2vNWaifQTvQQgBsbGzgq4IRPQzmAl7WwQAE4h9W1NbTmJKI2o0irG0fx8MMPY68dlpps7bZDbG1uwPOq20BzGjOLwPQA13UubWPoi0B1RuEcTR5qKgDX1taQpkDRuZ2KnNZtcAf6ArAze6IUtfVc0QX6DuBpr9i9fZrm76majY0NyF46OY67BKITX/hk6+WXXwZu6DeBw/oqLM/Fq6++uvBHXHio4UwE0hnbMFw2jz32GCAl0gmVQNPDfTRWVrSZqNu2nSVLXxAi7WkxBq6uriLtJegls9NnorAFIazKQ/XGGQjAo0LHKwdQl+tqmLW1NbSSeTmA+gnxQRX+8g6aek/V86jt7W0cd1tI5WL3+GG3ibWV1Uubj1MAzmF1dXYIaColWmFXqxtH8fDDDyPupTguEXK12w5x+/Yjl9iqxRkUgTn7WhhL1DR0aoYpKgC7kX6VM4HB6mDRfYb1DgHdRNSZnY8ZdYEb29XumzeNW7duQUYpEM0XgFIjAZhPkEqGpg8jpUTaCS90stXpdNBqNiHW9Vt4EUIAq41zVQK9aKExC5GmlYqQxx57DAAgD8+GgcqjfTz22GNauGQA4LouZMFCI0WQmghA1edH3dnCI+o2sbK6okVF1mEGArBcCKi2AnCOA9iMshxGnaqYqmuoeQ4BWPXcY3t7G1LK3Mkry1G3ia3t7Qtu1QC97joNWV1dRXNGEZhOHEFCr5UTxcMPPwwA2GkV3wpitxPj4du3L6tJ52LgAE6uAqpz+CcwuEa6MyqBpqlEGKVaXk+LCkAdXbTNzU2kqcSsBeqkY2k5oANDYu60wKS+Xy1UBwGotuCQ7XLb04zQjSF7af5ZF0Gr1Q/T0TDyAQCk5w7auABBEEBeUVim6CWVbsD86KOPQgiBdFIe4PEBHnvnO6++UVNwXXdiqOrCJFGlv71iMFbME4CnWNMw371WqyEIamgWdACbnSMEQU3LOcja2hra4WwXqhU14diOVu0f7KNXvt9T1TOrnkepit0HBYsJjXMQnmL7BgVgZayurqIbx0jSyZU7mv1Ep6qt5knc7gu53YICMElTHLTDXDjqRhAEEEJgkqEZJnpXAAWKOYBR/7tV3XFNQq0OhgXrO4QhYNv6hfcAg5XaWfnZUUfPFV1gqEhTIQGYYm19TYtcxjwPscSi1Bn67823w7hQqq+gOJVzuFYrKytIu92rqRAZRZVGMPi+j+0bN8+EgMqwi167iXdqJACDIEAanz8nViGTSIv7vKgDGIZNrK/rJwCBbLGq2TksdGyzc3ihC1IXydraGiTkzL0AW1EzK9CliTMODDmACxRRUaKx6nlULgA7iwnAw7B5qQu3FIBzmLcZvHIHq7aaJ3Hr1i0IIbBTcLV9r50NRLc1dQCFEAh8f2oV0Hpdv7DJYXIHcIYAVK/puKCwiAOo26CiUIP1tL0A00QiDi/WZbpI1KAgT+ZvqSBPU22q+m6rcJbm4gJQXoIAzCcKnXMI0z4yihEEAT74wQ9mzlt0fofH6kZYP8cYs7GxkRUbKXjzyiga+w7FQnaz8NxO5Qsn73zHo8Dx6OQ9PckeP/KIPikOQRAAMgV6091ZGXXGzsXkohhSSqRRaJQAjMOmlnMnANje3irlAG5v6zlWqN931l6ArehUq/BPYNDu0znhq5M46TuaVafSDARgsWJCwyRpD8ed1iUtdGZUHyyuOWpicBqFWA9qeHx99CZvxvoKQM/zcGN764wD+Nj6ZEdGHafTADlOrRYgTCLcXh9du4gSgU0NnaZh8iqgQ3lbNzdGxVFX48qZKpRz3AGcNtcLu3qGfwJnHcCVsSgLnbeAALLf1fVcJEMOoLgxuTu3msDtd+mxqFOr1dBYWUG7eY5tAk6z915kVVPf97G1vY2jo/ID9RmiGB/4wAfwoQ99CFJKPPWpXz3Xx8leD+nJ6bn6ZSW8ZbMJUUQgRNHYd/hUsf8oiiDjeCD0K+LRRx/Fl7/2PORQVUzZF4SPPvpolU0bQS30yagD4UzepkNGnZFz8fFP/ebkD+vFkGmv8kkvMCwAB87Hxo2zlVejblM74aHY3t7G3TtfH3nu1tbk6rHtzjHeu/3kVTSrNOr3bYanuLVyG+9YP/sdmtEp1h7Saw4bBAF8z8fJAgLwNGphbW2t8sXnjY0NeK6L/SkC8PG16e7efucEEpe7fy8F4Bzy1ZO+0/dD3/oHR15XDqCOE3YAuH37Eezce23kuT/3rY9NPFblCurqAAJZmGeYnOAHv3P00g17QstQw2Fs20a9XkM4ZDv9ke8YLc0e9vMDdbye6vU6XNdBd8yC/Y73Tz4+7AI336GngFLOnqow/Z5/b3Sg0F0ACiHw0EMP4W5zsOG19T1nJ35SSshTPfYAVDz88C28enq08PvlaRe241y4O/tNTz6Jz37l90ZEw0J4Lp5++mlIKfGJT3wCaJzPkZE7B5C9FE8+ufgEU4X1y9MToMiKsueNfYdiokKenIz8f1XxyCOPIA27QNgBgmxc0NEBHBaAqE+egAuvNnIuRGOyuJahHqXvgaFokSEH8Nu++4dGjpFSIuyearl4DmQC8LR9ONIf/Inv+qEzx0kpcdo+rHzRYxrjDuAPfPOfP3NMK2nikXU9okSG2djYwOkM53Iap5EeCwtCCNy8+RD2pgjAH/rmPzH1veo9DAGtkEEiqnkhoABw+5FHsNMuFoK00+rC9zxtw94AoFavT6wgHxlQBAYAVldXCoWA6igAhRBYX18rngMYWdo6gJmYdTElmioXhjrfC7cfvg3rdE7uUFtCJrLyCfkwtx++DTElBFRsrwKPbOR/xPaE++C0g5sP3bzwyoHf9V3fhfS0Bbl/dK7PsW7fRLcR4KlP/Sq6jQDW7fM5lenrd2HZNr7t275t4c94xzuyze3l0VGh4+3bt9FtNPDUpz6FbqMBu+CioDzKRFbVeXZK5KUnR/lz8uQIG5ubWhRJUeQCsDs9P8u5/T7EjW18/FO/ibixDef2+yYeJ0M9St8D2WJno7Ey4gCO00tC9JJY27nT9vY24iREOGcfujDuIE5CbQXgwAGcHt3QivQMxd3Y2MBJOHoNPbb2KGpOgJoT4MnN9+CxtbOO/nF8is0tPRZvbz18a6oAnMVeO6sse5npG3QA55ALwCmVQNXzOnS6k3jkkUdw3AkRJj34zuyNgHdaWQGYqm3zWdRqdZyc3d4JYSINEYBr6Lb2pr7e1XjvPADY2NhEqz3hBEyg25FaO2gbm+uIOpPPRWSAAHz44YeB5740+6B+BVBdcgCBrN3yc52JTpv9v/2Gue8Xp1088s7Jk+Dz8N3f/d3473/iJ5C+8Bqsc+wH6Hz3d1xYm2QvBV5+A3/wD77/XGNMvV7H9s2bODwodu86f/i7F5ocyIMD2LZdeZjlwPE8Bh56pP/vI+2iW9QCWTojV67+3T9Q6LPSfqEJXRbdss3gp098lTuoo/AABmHTzfYBAm96dFGznS16/P/bO+8wSapycb9ncg47szmxKzksiCSRKGAABVQUFFEEMXIVEbMi5nD9mXPOCYzo5ZrBq4iCAUFBQJLEZXdndndmOtf5/fGdM1Vd07M7MzvdXdXzvc/Tz0xVV3efU3XCl853kjpXhFFsldtYYAPGcslbAwgwuGiQ+x+6t+zcc/d5Gvduux+ANx5+YcXPbcuPsW5w/ueIubBs2TLu+Me/Zv25TZmtNBkzr0sd4qgHcCeEmYimUwDz9HR1yz5LCcRPeA/PIOvexkyeFQlaH1GJrq4ucqVyodFaS7YQpEIB7Ovr32EW0CQngQFYtGiIXG7nBoJiEQoFmxhhpBKLBoemzQLqFcAkl3/JkiUEmRJ2B3sBJmkPQM+KFSuwxdLcM4Fuy7KyCmF8fX19HHfssdh/3Y3N7noymPkguOMegokMT33KU3f5u/baYw/MpumNT/OB3bSJ3datq/tedN7gEWyP7OM2to3lCfKEQ+idsRO7vvbUZpK1l1t/f39ZCGgc7x1MSnnjTCqAO0kE4xXAaibr2BU6Ojpoa22b3OsvTqYwgbU2kc9hcHCQbdOUezpk373tiTE+L126lG25cbLF2e19+8jEVoYWDdHaWnlt8HygCuBO6Orqorm5eVoFcLyQo6c3mcI6hKEwO9sL0FrLxrFc4iykcTo7O6eEgBZKkuAu6WsAwW8rMn23y+Yt7e1tVe30u8LAwAC57M4VwGw2vD6pLFq0iGK28rPIT0BPT3fdBdkdEW4FsYNMoE4BTJIHcHKM2bbj0KpK2GyBIJuv2jj1rGc9C1ssUrpx9hbb+caWSti//JPd1q3j0EMP3fkHdsLee+9NaetWbHb2930m2CDAbtzIPruwVnG+6O7upqu7GzsmipUNAkpj2xJlCIFwjXEwxzTxUQKnRCYlFHFgoJ/CDvYBzKVEAdw+seOtILa7iJik3Pc4xhj6+voYm8YD6BXDJHpiBwcH2ZYb2+EehnEyxSyFUiExHtnJ7dgmtu7kynI2Tmxl+YrqyuOqAO4EYwy9PT2T+/3F2Z7PJbLjeHzj2zi+44Vbo9kC+VIpUQvkKyFJYMrP+eM0eAB7e3vJ7cBjk81DX0LDP0EG5EwmYGfbVvl1gkmxwlVicHCQwjTdopBNdtlhhnsBbi/R3dOdKOOIH2Ps6Oz3d2KrfKZaIYbr1q3jhMc/Hnvzbdhts08+MJ8EN99OsG2MF55//ryE5e+///7yvQ89tMvfVQm7ZTO2UGC//faryvfPliWLl2DHROiymXEIgsQpgK2trfT29ROMj+7ydwUTW2lpbU3M8oH+/v4drgHMJ8xjGScaArojvIKYVAUQoK+/n7F8ZS/zeIIVwEWLFmGtnbIOcEeMurWOSVMAN06Mzupzj2S2srzK8rgqgDOgt7d3eg9gPk9vAjuOp7e3l96enp16AB9OwRYQIEperlgu8KZNAczkgmk3/s3lSXR7GhwcJAhgZ9uCZVKwhm5wcJB8JsAGU59FPiPhrknGK4B2Bwqg3ZacPQA9S5YsoaW1ZU4KoP9MNdeYnX/++bS1tFL63V9qs3F6Bez2ceyf/8lhhx3GYYcdNi/fueeee9La1oa9/4F5+b44wf2yLmdXktXMJ0uWLIZxUeK9J7Ca62nmyuLFw9j5UADHRxhctCgxa/j7+vrIZrZNP9dlk6t4gIRO9nT3sH18xx7AsYkt9HT3JGL/xeno7++bdh9A7xlMoiLu5YfRHSSwieOvTYoBN3TCjM74M/lSgZHM9qrP3aoAzgBxn0+jABbzibG4TcfyFct3qgB6D2HSQ0C7urooFC2liNCeK8r/aVEArYXcNIlZM3lZJ5hU/KCa3UkmUP9+0hVAa6FQoWsUs02JmUCmY3BwkOaWlh2GgDaNwbKlyVr31NzczPLlKya9ebPBjk7Q1NRU1XFqeHiY8887j+A/DxL8666df2CesdZSuuZ6WpuauPDCykkO5kJbWxsbDjgAe/998/adUex997Fq9erEeEKGhoZgQpQM6xTBJK7TWrpkCXZsx0rGTLBjIyxPkLGnv7+fUrFAqVhZ9shlt2NMU2LXuwMMDQ/PIAR0hKEEtqso/f39O1AAk+uJ9WPJXBTApIxDvb29dHV2zcoD6K+ttkNGFcAZ0NvXx/g0Czi355IdAgqwYsVKHsns2GXzyHiOJmMS5y2I45W8fETm9WsCkxTmNh2+rUy3FUSuYBJtUPAKXWYny4jSsAbQl63SVhD5BGcw9TQ1NTE8PDRtCKjsAVhKZJ9eu2YNZnQOa9FGJ1i6bGnV18ieeuqpHLBhA8G1f8NurW0oaHDTbQT3P8yLX/zied++47DDDiMYHcVum916lJ1hCwXsQw9xxOGHz+v37gpDQ0OUJiZkLaVTBJNokFqyZAnB2JZd9zaPjSQqxNUrFLlp1jfmMtvo6+ub9+1c5pPh4SHGMjsOAR3LjMg4nGD6+/sZmyaMcjyXXE+sV+JGUqwAGmNYsWIFD+/EkxzlYectVAUwAYgHcKrEHtiAiYSvAQTx6m0az1EMpg8V2ziRY/Hi4UQnvYBQAYx60NLmAQSmzQSayydzIPZMegB3pgBmZM/DJLcnrwDGt3kqFS3FfLIzmHqWL1s+/RrAnMUWkrfuCWSfuGDrhGxzMAvM6ARr16ytUqlCmpqaeN1rX0tnWxulX/8BW9pBop15JHhkC8GfbuKwww/nlFNOmffvP+KIIwAo3X3PvH5v8J//YEslDk+QAijKnsVmxrET4zQ1NSXSy7Fs2TKCfBabm34vwJ1hSwWKY6OJ2u9zUgGcZh1gPpvMveeiDA8PM5bZeQhoEj3LUfr6+pjIj1MKpo5jY/nttLa2JjKENQwBnbnBaiS7lY72jkQ5BFasXMHGzMzrsFEVwOQw3RrAiUIBS3L3bPOsWLGCwFq27MAL+MhEnuUrkr0FBEQUwGI0BLT8vSTjJ7xMbqq111pLJhckuj15q9rOQkAzmWRa26N4ZTbuASykYAsIz9KlSzHTyY0JzADqWbNmjaTunUUYqA0C7OgEa9dWXwEE8cxc8upXE2zcQum6G6v+ezaXJ/jlHxgcGOA1l1xSlbVcy5cvZ+1uu2Hvnt/Q1uDuu+jp7Z1MNJME/PgjCuAYfQMDifQ2hZvWz32LjmD7FsAmag3/zhTAXHYbA4MDNSzR7BkeHmZsYpSgguIEEAQlxjJbE68A+mcxUSEMdCw/Rn9ff2LWjkZpaWlhoH+AkewsFMDcVoYStBYWpI8/Mj5KaQdOmCgbJ0bp6equuiyYvNEwgfT29pIrFijErMBeKUyywA6RNLQ7WAf4yET1UqvPJ96qE90KIpeiEFDfViqFgOaLEATJ9gB2dXXR2to6gxBQw9BQsidFrwDGM4EWUpDB1LN48WKCsSK2VCF8LIF7AHrWrFkDgB2ZhddjawYbBKxevbpKpZrKUUcdxdOe9jSCm2+ndMe9O//AHLHWUrr6TzCe4S1vfnNVPVXHHnMMwUMPYSfm7nGKYotFuPdejnrc4xK1H67vvzYzjs2MM5hQg46fd4Otj8z5O7zymKQ53LfhfKZy+F4+u53+BM91IAZPa+20ewGOZUax1iYm3HA6wv2spyqA4/nt9CXQM+4ZGh5iZDYewNxWhhYnS/ZYvnw5JRuwaYZewIfGR1i+YnnVlVhVAGfAdJvBp00B3DhRWQHMFEpsy+YTZT2cjtADGJ7LO29gEkMY4uxIAUz6JvAg8eyLFg3sNAQ0lzWJ9wB2d3fT3Nw8rQKYxHCxOJPK3fhUy6IdE4NVEjMfrl69Wia3WSiAXlmslQfQ88IXvpB99t2X4LfXY0fmd+2cJ/jbrQR338+LX/Siqm+jcMwxxwBQuvPOefm+4D//IcjnJ783KUxusp6ZgGyGRQk16KxYsQJjDKVdUABLoxsBWLVq1XwVa5cJPYCV19Dmc2OJj7Lwnr2xaRLBJH0TeE8ow071xo4VttPXl1wZdvHixWyZpQKYtDnPZ62eaSbQhydGWVHFTNceVQBngBfaxwvlUrtfF5hkjw2IFaulpWXaTKCPOMUwSesHpmMyCUxKQ0B3tAYw5x5P0tvTokVDO/QAWgsTGZt4BdAYQ19/75QQ0HyKQkAnJ7qxCqElYwHNLS2JVGQ7OjpYvHQJdsssvFBOAfTew1rR2trKpW95C33dPZR+fi02P00K3zkS3Pcwpetv4tjjjuP000+f1++uxJo1a9ht3Trsv/89L98X/PsOevv6ePSjHz0v3zdfTLb7bAaTyySyH4BkZx1evITS1ofn/B2lrQ/T1d2TqLmju7ubpqaminsBWhuQy2xPVHkr4RW76TKBbk+JAujb/niFRDDj+bHE9g2QezvTENDABoxkkxeS6xXAh2aQCKYYlNg0sbUmDhlVAGeA98jEPYDjhXR4AJuamli6ePG0IaD+fJLCR6Zj0gMYywLa0tJc9cyA80FLSwudnR0V1wBm3AbxSW9PQ0PD5HLTDx35PASl5CuAAAP9A9N6ANOkAFbcC3AsYGh4USLXPQGs320dZmQWawC3jLN4yZK6GHqGhoZ4y5vfDNvGKF7zp3nbH9COTRD8+jpWr17Fxa96Vc3WrZx4wgkEDz+8y9lAbT6Pvfdejjv22ESFf4KEqzc3N2OzEwSZiUQrG2tWr8I6L95cCEYfZvWqVYla92SMobevv+IawHxuHGttohUPCNe8b59mM3h/PukhoKETo0IIaCHZyXiGh4cZy4+TL+1k82Fgu0t0kzQP4KJFi2hva+fhnWwpArBpYiuBDaq6160nmZJBwvCdJ60hoADLVqxg0zRJYNLpAQzP5YqWzhSEf3p6e3sqegB9CGiSB2OQwWxHHkAfHpqGNXQDA4MUs+VCUyFLYrOixdmZB3DpkuQlgPGsXbsWOzrzTKBmZIJ1u+1W3ULtgA0bNnDeeedh77yP4Obbd/n7bCmg9Ks/0GrhrZe+taaK7XHHHSdhh7fvWj2Cu+7CFouccMIJ81Sy+cMYQ09vL8Vb/kaQzyV6nl6zZg2l0YexdnZZcT129GF22622odEzob+vj1yFNYD5hG8C7+nv76e5uWWHIaDNzcmMsoji7/N4bA1gYAMmcuOJfg7emzcTL+CW7GjZZ5KCMYbly5dPbu+wI/x2EaoAJoSdhYAmec2WZ9myZTwyUVkB3DSRo7OjI9ETpMcL5dEsoPkitHe016tIs6avt2+HawCT/hwGBwfJ5wKmy4zvlcOkW0VBvHyVFMC+/t5EWdOno7Ozk67uLhif+jCaxmHxcLIsoVHWrl2LDYIZZQKVDKDjNV//F+eZz3wmRxxxBMF1NxJs3LxL31W6/iaChzZx8ateVfOw1iVLlnDAhg3YO+7YJW9mcPttLFu+nH322WceSzd/nPPc53LMEYfz+Mc/PnFrFKOsXbsWW8y7bJ6zI8hNUJrYVtPkSDNlYKCffG6q1ymXkXNJV5yamppYNLho2iQw2ydGWDSY3CgLT0dHB21t7VPWAE7kx7HYRCuA3si52Sl3OyKpCiDAylUrZ+QBfLhGm8CDKoAzYjoP4HghR1dnZ+JCXyqxZMkSxnIFssWpguKmibykk0+BwOsVwHgW0K7O5GcA9fT29VdUAHMpSAIDO98M3p9PQwhof38/hVhkdCEroaFpYXh4GBvzAFprCcaSFwoTZTfnzZtRJtCtGWwpmPxMvTDGcMkll7Bo0SKCX/9xzusBg/seIrjxVk4++WSOP/74eS7lzHjCSScRbN2K3Ti3tWd2bDvBAw9w0oknJnbuOPXUU3nTm97E61//+robD3aEL1sw8tCsPxtseRCg7n2jEn19fRQqhYCmxAMIkoVyuhDQscwIQwnfBN7T19s7xQPoQ0KT/BxCD+DoTq/1CmAS572VK1eycXyUYCde/ofGR+js6KzJEhRVAGdAV1cXxpgpHsDxfD7xwrrHh3duquAF3JwtsDQF4Z8Azc3NtLW1limA+aKlM0UKYF9fH7nC1K6XzVna29toa2urQ6lmzuRegNMogH6PwDQogH19fRRyAUEQekGKOcPAQPLDVz1LFi+hKa5DZSw2SHZ6cp8JdCaJYPw1SRDi+/r6eOMb3oDdNkbpD3+b9edtLk9wzfWsWr2al7zkJfNfwBly1FFH0drWRum2uYWBlm6/A4ATTzxxPou1IPHtujTy4Kw/Wxp5AEimAtjf30+ukgfQKYBJ9wACDA8PTbsZ/FhmhOG0KIB9fYwXysdarxAmWQH0ytyWGYaAtiQ08dmKFSsoBiW2ZCpnxfU8PD7CipUramJUUwVwBjQ1NdHd1cV4PqYAFvKJD9fz+HTxmypsBeE9gGmho729PAS0ZOhMwR6Ant7eXrL5qWFX2bysD0w6XrGbbjP4bAba29tSsS+jnyiKkboUcybRE2KcoaEhmIi1J7ctRBJDYTzt7e1ieJpJJtCRMYwxNQ+VnI4DDjiAZz7zmQS33knwn9l5bUrX/hUmsrz+da+r6zrTrq4ujnrc4+DOO7HTxXNPg7UWe8ft7LvffqlIHpZ0enp6WDQ0TGnzA7P+bGnLg3R0dibS69HX10cuMzZlbWM+m3zFwzM0NMS4C8uLMzYxkmgjW5TevgoeQHecZDm2o6OD3p7eshDQNX0rWdM3dY3cluwow4uGEhmS68fJh8Z3HOa9MTNasy3ZkneXEkpPT89k1k/PeCFPT4I7ThSv4G2JJYLJFEpM5AuJ3Cx6Ojo7O8v3ASyZVCTs8PT29pLNBVPW3ogCmPwJcSYhoGlIAAOhABLNBFrIpkMw8QwNDRGMF7ERL6ZXAJMunOy2du2MMoHaLeMML1mcqH7+vOc9j5WrVhH87s/YQnHnH8CFft52N2eeeSZ77rlnlUu4c0488USCXJbg3ntm9Tm7aRPByAgnqfdv3njU+nUEI3NRAO9n/bp1iQzD7evrw9qAQmyvnVx2e2oSbS1atIhsfoJCsVz+KxRz5PKZVES6gDyLiWK5AjjhPIJJn++Gh4fZkg29sM/d52k8d5+nTbluS3aUxUuTKct6pW7jNMYEkKQ8G8drswUEqAI4Y8R9nl4P4ODgIM3NTWyOKYD+OInWw+no6OggH90GopSOPQA9PT09BLZ8HSNArpAOBbC/vx9jzA5DQIeGkut5ijKpALq53QaWQi5I/IQYZWhoCCyQCRVAmxYFcLfdCLaO7zQTqBmdYP1u62pUqpnR1tbGqy66iGDbGKW/3bLT620pIPj9X1m6fBlnn312DUq4cw4++GD6BwYIZpkNNLj9NppbWhKdWCVtrFu3jtLIQ7PyxlprCbY8yPr166tYsrnjx9H4XoD53Bg9vX2JVFrj+DF0LCa4++Okj7Ge3kprAF1SmKTLsUuWLpnRZvBbcqOJlWWHh4dpaWmZzPJZiS2Z7ZSCUs2iKlQBnCE9vb0VFcC0rAFsbm5maNEQm2MhoJszcpwuD2BX2Ubw+SKpsCR6fJuJbwWRK5jED8Qgbam/v29aD2Au25Q6D6A37npFME0K4KQFeiKiRLn/k/4c1q5dC4HdYSZQGwTYkYlErnHasGEDxx13HPbv/8KO7diTGfzzDoLRbbz8pS9LzDrf5uZmHn/88dj//Aebq7xPbBwbBNg77+Twww9PxXiVFtatW4cNSgSz2BDejo0Q5CZYty5ZxhGPD7HPZcsVj1x2O/0pGWP9+BpfB+gzg6bFA9jb28uE23/RM1GYwBhDd3d3HUu2cxYvXjyZ4GU6AhuwJbs1sQpgc3MzS5cs3aEH0GcAVQUwYfT09JAplrtsJlKUBAZg8ZIljGTKs9ZtSaMHsLOTQim0HOaKNlUKoBea4plAs/l0KIDgwmKmWQOYyabLKgphCGgxzQrgeLkC2NPbQ2tra30KNUN88osdZgLdmsEGQWLW/8U5//zzacJQ+vM/pr3GFgrYv97CgQcdyOGHH17D0u2c448/HlsqEdx114yutw8+QDAxwePrlL20UfFevOLm+2f8meKW+8s+mzT8+DrFA5gdo78/HWOsn8vGM+UeqHGnAKZprivZErlSOHGP58fo6e5J5Jq5KIsXL2YsP05uB5vBb8uPJXIT+CgrVq7gkYnpPZkbnXdQQ0ATRnd3N+ORbSAKpRL5UjFdCuDixYzkypXYkUyBJmNSY8UCCffMOwXQWku+GKRSAczl42sAg9S0p0WLhshlp4bvlEqQzwWJ9zx5/LMounnFewDToohDqADaiAfQjqfjGaxatUrCwHaQCMYrh0lVAJcuXcpTTjkFe9vd2O2V6xH8898EmSwvOPcFiQt722uvvVi6bBnBnf+e0fWlf/+b9o6OxCmyaWf16tU0t7RQmoUC6K9NonccoiGg5R7AQm4sNUY2P47G9wL0x2kYZyGyn3U+HKMmCuOpmOt8MrMdeQGTvAegZ/ny5Tw8MTrt3qsbJ7bS3NxcszqoAjhDent7mYiEgE4U07MJvGd4eJgtmVxZ4xvJ5BkY6KelpaWOJZsd0TWAxQCsTWcIaNQDWCxZikWbisEYvAdwqiDr1wWmZVLs6Oigubl50vPn/6apX0/e64gCaDKWoUXJt0x3dHQwvGQxdnQHHsCEK4AgG8QboHTz1LV0NgiwN9/OARs2sO+++9a+cDvBGMNxxx5LcP/92Onc+g4bBHD33Tz2iCNob2+vUQkXBi0tLaxdu5bS5vtm/JnS5vtZsmxZYkP4JhXAXHn/zqdIAezr66O5uXnS4+cZz4iwnpZ6eNliohAq4+P5MXpSkHnce/VGdrAVRJL3APQsW7aMTCHHeKHyOLtxYpSlS5bUbG9xVQBnSHd396TXD5jcEiKpA28lhoaGKJQCxgvhIvORbJ7h4eR2mEp0dHRMJlDxf9OkAIYewPBcWjaB9wwODpLJBMQNWV5+TIsCaIyhp7d70vNXTKEHsK2tjY7OjrKtIEyKMrHutmYtZnSaBaWAHZ1g0dBQohM9LVmyhKOOOgr+dRc2tlTA3vMAwdgEz3j60+tUup1z9NFHg7UE99y9w+vsgw8SZLOa/KVK7P6oR2G3zDwTqN1yP3s86lFVLNGu0d3djTGGfGQvQGst+Ww6PE8g24D19w9UDAHt7x9IfPikx8sWExEPYKaYjufglbrN2R0lUBkFku8BhOkzgT4ysZVlNdxWJx0tNwF4RW+iUHB/06kAAoxmw3WAo7kSQwnuMJUQBVCEXe8JTJMCOOkBjCzHzKZMARwYGCAIIB9fx5iiTeA9Pd09kyGgxZQ9B8/A4ABkIiGgmYCBgYG6lWc2rFmzBjs6MW1YjBmZYLcEbAC/M0455RSCXJ7g7nIBPvjXXQwuWpTokMk99tiDoeFhgrt3vB1EcPfdtLa1ccghh9SoZAuLdevWUZrYRjCxbafX2kKO4ugjiU0AA24P5e4e8tlQ6SgWsgRBKRWKh2dwcIDxmPdpPLuVwcGB+hRoDoQewDBZ1URxIhVznVfqdugBzMkm8Eme95YtWwbApmnWAW7KbqvpvqqqAM6QUAHMu78ivaeh83hCBTCU2kezhdQsYva0t7eTLwZu/Z8IjWlSADs7O2lqaipbA5hGDyBM3QzeHyd5EI7T29sbhoCm7Dl4BgcGsU4BtEWLzadHAVy1ahW2WILtU8NirLXYrROsXr26DiWbHRs2bGBwaBGlX/2B/Ge+M/kK7nmAEx7/+JqF9cwFYwyPO/JI7P33TfFgeqy12P/cy8EHH5yq8TZN+GQuM1kHWNryIGATmwDG09vbW+YB9OGg6VIAB5nIlivlE9ltqTJ0+vudKUTWAObT4QFsb2+nr6d3J2sAtzI8NJy4NdZR/H7cj2SmKoDZYp5t2fHJa2pBehZ+1RmvAGac4pcpps8D6Acr7wEsBgHbc/nUhIp5Ojo6CCyUAiik0AMoaZe7yEZCMXIFUQbTonhMKoAZcJm+J48hXQpgT08vpc0yaRRz0NHRnmhhvRID/QM0bXQTn1ME0/IMvHJnt05g+mJhnhN5bL7IqlWr6lCy2dHc3MwbX/8GbrzxxrLzTU1NnHLKKXUq1cw5/PDD+fGPf0zwwAM0V1hvaUdHCbZt44gEezLTzqNcOGdp8/20rt5nh9eWXAbQRyU4BBSgt6+XreNRBVD+T4Pi4RkcHOS2W8uz5I5ntzIwkOx7H2UyBNQpgNZaMvmJ1Miww4sXs3lsdNr3R7KjLF6V7OVMPT099HR1s6mCh3+TUwpVAUwgk52nWO4BTEvngVBo35YruL/FsvNpwSt7hVI6FUCAnp5u8hFLnPcApmVS9MpFfOuwbBa6u7sSs8/ZTOjp6aGUN4ClmIeuFPVpz8DAQLgRfFb+piU5waRyNzoBq8ujEeyohCutXLmy1sWaEwceeCAHHnhgvYsxJw488EBaW1sJ7vsPVFAAg//8B4BDDz201kVbMPT19TE4NMT4DNYBljbfT0dnZ00FxrnQ19vLppEtk8c+I2ha5jqQ/QwnMtuw1mKMwVrLRGZbaoxs4CKPTBOZolhp86UcJZueUNzFSxbz0A4SJG3Jb2X/4eQvFViydGnFEFCvFNayP2sI6AyZGgKaPg9gZ2cn7e1tbHUewK1OEUxTGAMwmX0uXwqTwKQtI11PTy+5yBpA/39a2tOOQkD7oy7BFNDd3U3J3f9SAXpS8gyi9PX1YTMlWUfnPIBpeQ6Dg4O0d3RgK20G786lwQOYdtra2jhgwwbs/ZXDD+3997Fy1SqWLFlS45ItLHZfv55gJgrglgdYt25d4pOQ9PT0UIhkAS3kJibPp4WBgQGKpQL5okx4+WKWYqmQKgXQGENXVxcZtwbQ/02LzDE8PMxIrvLaOWstI5nkbgIfZemypWzKbJ9yflNGFcDE0tXVBURDQOVvkjPTxTHGMNg/MKn4eU9g2jyAXtkrlCyFUvrWAIJTAKNZQFOmAPb29mKMmQz59GSzMDiYLoOCCCjSjoq5dAkmnr6+PmxgoQA2ZR5AY4xsfLt1aiZQuzVDc0tLKib2RuDRBx1EMDKCnShXxm1Qwj70EI85+OA6lWzhsH79ekojD2JLpWmvsdYSbHmA9QlOAOPp6ekhH1nu4NcApmmc9YrehBPS/d+0GNk83d09k0lgvCcwLTLH0NAQ23JjFIKpa5S3F8YpBsVU5LNYsmQJmzNTQ0A3Z7bR0txcU3lcFcAZMrkG0Cl+2UKBzo7OxFvf4gwMDrLduc22uxDQNFmxIFT28sUwC2j6PIA95Ith28kVLG1trakJnZT9j3qmhIDm802pMyh0dXURlCxByVIqGrq70yOYeCaVvWwgL9IVYrV61SrMtgp7I22dYOnSpalbk5lWNmzYAEDw4INl5+2mTdhCYfJ9pXrstttu2KBEsHXjtNfY8VGC3ESiM4B6ent7yWfDLL+FfPoUQK/oZXLby/6mTXbq7umeTALj/6ZFAfSZQEcrZAL12UGTvAWEZ/HixUwUskwUyoWnzZltDA0N1VSnSJf2Uke8p88rgJliga6u9Hj/PP0DA2xzWpP3AKbNihV6ANO7BrC7u3sy8QvIGsCuFHmTAfr7B6YogLkUhoB6734xD0HBTB6niUllL2flRboUwOXLl2O3ZcSLGcFsz7IqJev/GoE99tiD1rY27MMPlZ0PHnoYgP33378exVpQeKXOJ3mpRMmFiKZBAezu7sbagJJLtVzITdDU1JSq6ClvYJtwip//m5YoC09PTzdZ5/nLFDLuXDoU8cmtICqEgY7m0qUAAmyJZZXdnNnG4hqH16sCOEOam5vpaG8vCwHt7kqH5STKwMBA6AHMF2ltbUnVQAxxBVAExrR4zjzd3d3l20AU0mOJ8wwMDJKLOG2CALLZILUKYKkgSmAaFcDJSTwrCmB7RzstLenJ8bVs2TJsEMB4aFGw1sK2bE33RVrotLS0sNdee2E3lnuf7MaHWbJ0aerWi6eR1atX09Tc7LZ5qIxXAHfbbbcalWru+LHJh34W8hN0d/ckOl1/nMkQUCe0Z7LpVAC7uyMKYFFCQdMy3/nwzkp7AW5x59IQAjqpAMbWAW7JjdV8qYMqgLOgs7Mz9AAWCnSm0APY29vLmPP8jeWL9PX0pmoghvgawPJzaaGrq4tC0RI4j0e+AN0pscR5BgYGyOXDIcTlRUqdAugNIKU8FPM2NRNilNADGEDOpq4teSXPbousA8wVCfKFyc1zldqw9157YTdvxgbhGjSzaRP77L13HUu1cGhtbWXFihWURnagAI48yOCiRanw8nsFsJAXhSOfS8/WAx6v6GXcFhbeA5i2ua6rq2tSAcwW0rcGEGAkN3X9nPcApsFA5b2UW7KhAihJbLarAphkujq7yHoFsFSgM4WCYl9fH4VSQK5YYixXpDdlFiyYmgXUGENra2udSzU7/KDrs5jmC6Ru7VlfXx/5SAioDwdN46QIUCxAqWhT5xGHsD3ZvMXmAnpTpgBOZj6Lbga/PVP+nlIT9thjD2yphN0yAoDNZilt28Yee+xR55ItHNbttht2BwpgMPIQ61Lg/YPIXBfxAKYl7NDT1dVFU1MTWVeHbG6cpqam1BkLu7u7J5O/+L9pqUNvby+tLa1sragAbqO/rz8VUS+hJzPcG3Msn6EYlGruwVQFcBZ0dnWSLYrEni0WU9NxonhL1li+yFihRF9/ehXAYgkKAbS1tabOi+knRZ/9s1AyqbHEefr7+8lmAwLJOTKpAKYtLMYrfHnnfEpjv54UqNwawN6e5HsGokxaPsdCD6B1yqAqgLXFbyxut2wp+7t+/fq6lWmhsXbtWorbNmGLhSnvWRsQjD7E2rXJ3/MMwrmu6AZYCQFN1xhrjKGnp7csCUxPCqOnOjs7Jz1/uWIWY0xq8icYY1i0aFHFENDR7LZUeP9APPx9vX1lCuAW978qgAmmsyv0AGaLxVR6CrygOF4oMV4o0dubLmEdwvV+hRIUSzZ16/8gVDLcklLyhfQpgF7R86GfqVcAXeb7tEyIUTo7O0UYyVmaUtiW2tra6B8YwG6PuJTHRAHUfedqy8qVK2lpbcVu2QyECmAaEo40CqtXrwZrK2YCDcZGCQp5uSYFTM51TgEsFTKpG59APFBRD2Aawm/jdHV1UQpKFEoFssUMHe0dqcpkv2hoEaP5Ch7A/DaGhpO//s8zPDxUpgCOunBQVQATTFdXFxnvASwVUqkA+kFrolBkolBKXSgGTF0D2J5CBXBS6XAKYK6QvtBDr+jlYgpg2kJA/X0vZMuP04QxRtYk5y0mn551HVGWLl0yqfQB2LEcrW1tqTMopJ3m5mZWrlxJcP/9FP/+d0p33UVnV1dqLOyNwJo1awAojT485b1g5KGya5KOH4sKkx7AFCuAbguLbD69CiBAtpghW8ykLtpl0aJFbM1P3UR9NL89VePT4KJFbM2Fe2OOuv9rXQdVAGdBZ2cn2ZJTAAvpVAAnPYD5EhOFYioHMe/xKwbiBUyjB3AyBLRosdaSzwepG4y9YO7XAebz5efTwuS+kpny47TR2dUJBYtNYVsCWDy8GDORD0+MZxkaGkpdmFUjsOGAA7CbN1O67g/YBx9g//331+dQQ1a6rU8qKYAl5xVMmwewGFEA0zg+9fb2xBTA9BnPvcyaK2bJFrN0dabrOSxatIjR2BrAwAZsS1EIKIinb2s+VAC31kkBTP6KyQTR0dFBrlikFAQUSqVUK4Db80VyxVIqLXGtrbLmz+8D2JayDKBQ7gEsFMGSvrVn3njgPX/5nNsuJWUKlC9vIeUKYFdXN5vz2yGlCuDw8HDZNhCM51myOB1ejkbjwgsv5Lzzzps8TuNcl2Y6OjoYWryY7aMVQkBHH6azqzs1m5B3dEiYYSEvm8EX8hOpHJ96enrIFe4BIFdIXyIbCGWMXDFLrpilcyBd/XpwcJDx/ASFoEhrk6gvY4UJSjZgcHCwzqWbOYODg4xmx7HWYoxhNDdOV2dXzbPZqwdwFnR0dJArFcg5L2AaBUWv8G3J5MuO04Rk/Wyh6NYAtrelTwGMrgEsuEygaROyvALoPX+5vGw0mzZPQVtbmxgUXPRhGvs1QHdXF2QDbCmdW1kMDw8T5ApYt7dL03g+Ffs6NSLGyDpS/0rTOqFGYfXKlQTbpiqApW2PsHLlitSMs8YYOjs7KRaylIo5rLWplDt6enrIOS9mLoWZTCGc23KlLLliLnUyh1fytuXCMFD/f5oUwIGBAUpBiYmCGDy35cYZrINBR0f1WdDZ2UmuWJzMBJpGQdELhpudAphGQRGgrbWVQiBhoO0pfA6THsBiuBVE2gbjuAJYyJPKsBhjDG1tralXALs6u2BC9pVMW1uCyAQ+IUJiMJFTBVBZsKxatQq7bdPUN7Y9wupVq2pfoF2gs7OLQiFD0Q2yaRyfuru7yTovZjY3nkolNgwBzZEPsql7Dn6OiK4D9P+nTQGEMPRzW26CgcGBmpdDFcBZ0NHRQSkIGHdaexoFxZaWFtpaWyc9gKlVANvaJAlMYFK5BnAy8UgxzASatsF4cn8npwDm89Dbm64EMJ729vZJBbDWYRjzRWdnJ0zInhxpHJsm1z9M5CFfwhZLqVrXoSjzyYoVKyhlxwlyE5PnbKlIcfsWVqxYUceSzR7vASzk060ABkGJTG47gQ1SqQD6eSHr1gCmbZ6o5AHcmlIPIMA2l3p8WyFDv3oAk43vLNty2bLjtNHZ2cloNt0KYGtrq4SABunbBB5EEW9tbSFftJMewLQ9i+bmZjo7Oya3gSjkTSqTCgG0tbdRcop4Gg0K4MajvA3/Txle2bMTOZgQI1ta1jkpynyzfPlyAIJtmyfPBWMjYO3ke2mhu7ubQj5D0S20TqsCCLBtfEvZcZqYTHhWypEv5VI3T/j5YHskgcq2/FjZe2kgrEdm8m89sqerAjgLfGfZnkuvBxC8AliY/D+NtLW1UQxkM/g0C+yFIhSK6RXau7u7J7eyKKRw/zlP1OuXxucA6a/D5ASeKYCLUEiTVVdR5pNQAXxk8lzgQkLTpgB2dnZQKuYouuiptBk7ISzz9oktZcdpYnINYDFLvpheBXBbJAR0e36M5ubmVK3J9MredhdSvD03oQpg0vEC1vZ8+j2AEy7RQmoVwPZ25wEklR5AiCqAcpzGZ9HT0zPpAcznSdUgHKW9PezLaTYoVPo/LUxuH5LJY52BKk1WXUWZT5YuXQpAsH3L5Llg++ay99JCZ2cnpUJucg1gGscnPz+POQUwjfN11AOYS6EC2NnZSXtb26TXD8QD2Nfbl6pEVT5SaiyfYaKYI7BBXbbPSs8dSwBeMNzuNj5L61qhjsjAlbYBwNPa2kYxsJSC9ArsnTEFMI3Pore3l0IBrIV8PkitAtgR6ctpbU/R8SiNY1NLSwtd3d2i/DkPoCqAykKlu7ubru5ugrGIAji2haamptQlR+ro6KBYzKY+CQzA9okRIN0ewInCBIENUilz9PX1l4WAbs+P1cV7tiu0t7fT3tbGWD7DmAsDVQUw4cRDQNMoZEH6PQXgQkBLUCjZ1HoAOzu7Uu8B7O7uoVAwlEqiBKZxUgRoc1uJtLQ0p8qSGCWquKZ1bOrr64VsAbLSKdK6plRR5oMlS5aUewDHRlg0NExzc3MdSzV7fBKYYjE3eZw2vKw0nhkF0lmH5uZmWlpaGHcetDTOE/39/WwvRBTAwjj9A+lSAEHmtrFCljFnFFEFMOHEQ0DT2HmggRRAaygG6VUAOzo7RQGUaNxUtqeuri6KRTOZyTStawC98pTWtgTl7SetXsz+vn7IFrC5Am3t7amth6LMB0uXLMFOjE4eB2MjLF2yuH4FmiMdHR0UCzlKKc6gPhkCmtladpw22tvaGXNr6NIoc/QP9LO9EIaAjhXGU+cBBOjp6WW8kGXC6RP1MHYmVgE0xuxrjPmVMWbCGPOAMebtxpi6mr28MDLuFj2lVTiJDr5pHADAZQENDMUUewA7OjqkDkWLMSaVz6Krq4tCnsl1gGn1APo2lNa2BI3hAezv78fkipAtpDacWFHmi+HhYez4aHhiYiuLF6dVAcxTLKZ3DWDoAUy5AtjewbhTANP4HPr6+hgrhFujbC+M18V7tqv09fcxns8y5jLj1mO+a6n5L84AY8wg8Evgn8BpwKOA/4corG+uV7kmFUC38VlahSxfj7bWVowxdS7N3GhtbaXgwg7TKrR3dHRQLBkKJUtbWzqfhWQBtZMewLQrgC0pbUtQrgCmtU/09PRg8kVsrqDhn8qCZ2hoiFJmDFsqQFMLpfFRhoeH612sWSOykiWfHcOYdO7dO7l+Lru17DhttLe3MT4uHrQ0Poe+vj7GnQIY2IDx/EQqFcDu7m5GSw8x4aznqgCGvAToBJ5urd0G/MIY0wdcZox5vztXc7zCN572JDBu4Epj5/e0traSK8j2CWmtR3t7O0W3BjCtbamzs5OgZHHLYlOvALalVHGC8n6Q1j7R09ODzRchX6R3SBVAZWHjk70EE9sxbR3YYmFyv8w0Mbn9QGY7bW3tqTR2hgpgesMnQco9Orp18v+00dvby0Q+Q2ADMsUs1tpUGgu7u7slBNR5xeuxfCapIaBPBn4WU/S+jSiFx9anSBEFsJCnqakpdQuxPV7YbU+pkAhSh6xTAFtakmrH2DHt7e0USpZiKb3PwofBZLPlx2kj9ACmsy1BudcvrR7A7u5ugmwBky/Rk9L1pIoyX3hlz46PYidEaE9bBlAIZadcdjtt7emc61pbW2lubqZYytPc3JzaMbatvY0Jl0QljYbC3t5eLJbxQmYyFDStCmCmkGeikKO5ubkuynhSFcC9gVujJ6y19wIT7r26EF0D2AiegrQOYCBKX6EkCmBa6yEeQKcAdqTPEgehwpfJlB+njXANYPomRE+jKIBYCxP51CYUUpT5YnBwEIAgs51gYnvZuTThhdt8brxsz9W00e6yRadRcfK0tbWRL6U3j4UPlZwoTEyGgqZXAcyRKebo6uysi1c8qQrgIDBa4fyIe68MY8yLjDE3GGNueOSRR6pWKC9UBdamsuN4fNmbUurBhHIBN60ewLa2NgpF60JA0zkp+pDPRvEAtjWIApjGECsI208wkUttW1KU+cIrezazHZsRBTCNe2N6mSOf3Z7aaBcItwtqb0vnfA3pzxbtlb3xYoaJOiZQ2VW6urqwWEaz43VbOpNUBXBWWGs/a609xFp7SDUzZDWChR3CsqdVSITGeBaTVtGCTWUsPoTrIrKZ8uO04Y0IaTUmQHr7QZToRKgeQGWh45W9ILOdIJteBbDcA5jOuQ6YDF9NaxgrlM8TaVQAQw9gholiuhVAgJHsdjo766MAJlXaGQEqbewx6N6rC83NzTQ3N1MqlVLZcTxpFnI90TqktT5+Iszm0+sBnFQAs+XHacO3oTQrUWntB1H23XdfNmzYQKFY4NBDD613cRSlrrS2ttLR2YXNjkMQYIxJZbhbqACO0d6+qs6lmTu+HqlWYlOeLMwbBieKGcZT7AH0stJobpyl3fUJ606qxHArsbV+xpjVQBextYG1prWlhVKplGpBcdID2JReD2AjKIB+8M3l05kWGyLZ3bLQ2tqS2sRIvtxp9oqntR9EWb58OR/4wAfqXQxFSQx9fX08cscNmKYmunt6UjnGTs5vNr379kKYrC3NYaxpj57yyt54g3gAt+bG2a1Oyx2SKjFcBbzGGNNrrd3uzp0JZIBr6lcsl30yl6M1xQPAhg0bOPjggzn66KPrXZQ5ExV20ziIQUQBLKR3TemkAphLpzXR49uQtbbOJZk7jaAAKopSzumnncr1118PwAEHHFDn0syN6NyQau9Zg4WAplF2inoAM4UsTaYplZFHvszFoFS39e5JlRg+DbwC+L4x5n3AeuAy4IP12gPQ0wj7ha1Zs4b3vve99S7GLtEIHkDfloql9CpPk0psDrq70zuxNzWlfzl0Gj0DiqLsmDPOOIMzzjij3sXYJdIedugJs0WnV/5LuwLY0dGBMYZMMUummKWzThk0d5Wo0lovBTaRkrO1dsQYcwLwceBKJCPohxAlsK5MJotIYcdpJBpBAWyESTFqzU2zZde3oTROJJ609gNFURqbtCce8agCWH+ampro7Ogk6xTAemXQ3FVUAdwB1tp/Ao+vdzniNMIA0Ag0ggKY9oEYGkcB9N6zNIeADg4OsmhoEfvtt1+9i6IoijJJVOlL61wHjSH/NcIWWl1dXWSKOTKlLN3d6VQAk7AdRzqffh3xnSetHadRiIa7pTX0rfE8gOmLw/c0ggewq6uLb3/r2/UuhqIoShmNYOyEcJ5O63wNERm2uSW1811nZyfZQpZsMUdnA3gA62U8T//ClxrTCOniGwH1ACaD5ubmyfVzjeABVBRFUeaXRkjaBo3hAJg0dqY4C7z3AGZLubolUNlVov1AFcCU0AgbRjcC0fufVuG9ERRAgLY2lxgpxVbRRkgCoyiKkkQaZa7zskaa5T9f9jQvd+js6iRbypEt5VOrACYhBFSlnlnik7+kVeloFKL3P62DcaNMipOZcVOsADbCGkBFUZQkEo0USet8DY2xBjDN99/T2dlJLsiTaxAPoCqAKUFDQJNBIyiA0U6f1jpAY0yKXjhJ65oIRVGUJOPH2DTPEwMDA2V/00iaZQ1PR0cHuVKeXCmfyj0AoTzqqF59Iv0tocb4zqMewPrSCCGgjbIuwiuyaa6DhoAqiqJUnzQrIGeffTbHHnssq1atqndR5oyXl9Js7Ozo6CBfypMr5lKrAEZRBTAl6BrAZNAIWUAbIZENNEYI6ODgIAB77713nUuiKIrSuKR5rmtubmbt2rX1LsYukeb77+no6CBbzJEvFRpCAdRtIFKCVzbSqnQ0Co2gADbCfjzQGCGg+++/P9/61rdYtGhRvYuiKIrScPjV1Wme6xqBtMpLUbwC6P9PO/XqE9oTZ4kqgMmgERTARljHCNDSkn4FEGBoaKjeRVAURWlIfMBhmue6RiDMAlrnguwCScigOZ/US3bShS+zRBXAZNAICmCjhID6kJg0r4tQFEVRqk9a5+tGIVwDWOeC7AJRpS/N+w971AOYElQBTAbRpB1pfRaNogBecsklXHTRRan3ACqKoijVQjSONM91jUBa5aUoUQWwETyA9eoT6gGcJY2wl00jEB3E0prBMVruNLcnY4wqf4qiKMpOSfNc1wg0ggIY9fqpB3DupFNyTgCN0InSTCMogNE0zNqeFEVRlEZH57r6klZ5KYp6AOfpd+vyqw1AI3SiNNMIIaBRGqEOiqIoirIjdK6rL41w/6MRR2lWAC+66CL+9re/sXr16rr8viqAc6QROlGaabT7r2ExiqIoSqPiA14abe5OG43gvGgUD+DJJ5/MySefXLffT39LqBON0InSTKPdf50UFUVRlEZH57r60giyU6PsoVxv0t8S6kQjdKI002iTiLYnRVEUpVHxyTp0rqsvixYtAuDwww+vc0nmTtTrpwno5o6qznNEB7H60mj3X61YiqIoSqPyspe9jOuuu4499tij3kVZ0KxatYrLL7+cnp6eehdlzjTKGsB6o1LnHGk0BSRtNNr9b7T6KIqiKIrnxBNP5MQTT6x3MRSgv7+/3kXYJTQEdH5QqXOW+NT9jRaCmDYaTWHS9qQoiqIoirJjovKSKoBzp7Gk6Bqw//77A7B8+fI6l2Rh0ygK4G5r1wLQ29tb55IoiqIoiqIkm6gHUNcAzh1VnWfJE5/4RE466aSGUUDSSqN4zD7+iU+Qz+dTHY+vKIqiKIpSC6LyX6PIgvVAFcA5oMpf/fGhuGmnra1NFzEriqIoiqLMgGjYp4aAzh3VZJRUokq4oiiKoijKwkIVwPlBpWgllagCqCiKoiiKsrCIrvtTWXDuqOqspBLt9IqiKIqiKAuLzs5OXvGKV9DW1tYwy4HqgSqASirRTq8oiqIoirLweMpTnlLvIqQedaMoqUQ9gIqiKIqiKIoye1SKVlKJegAVRVEURVEUZfaoAqikEvUAKoqiKIqiKMrsUSlaSSXqAVQURVEURVGU2aMKoKIoiqIoiqIoygJBFUBFURRFURRFUZQFgiqAiqIoiqIoiqIoCwTdB1BJLU960pNYsWJFvYuhKIqiKIqiKKlBFUAltVx88cX1LoKiKIqiKIqipAoNAVUURVEURVEURVkgqAKoKIqiKIqiKIqyQFAFUFEURVEURVEUZYGgCqCiKIqiKIqiKMoCQRVARVEURVEURVGUBYIqgIqiKIqiKIqiKAsEVQAVRVEURVEURVEWCKoAKoqiKIqiKIqiLBBUAVQURVEURVEURVkgqAKoKIqiKIqiKIqyQFAFUFEURVEURVEUZYGgCqCiKIqiKIqiKMoCQRVARVEURVEURVGUBYIqgIqiKIqiKIqiKAsEVQAVRVEURVEURVEWCKoAKoqiKIqiKIqiLBBUAVQURVEURVEURVkgqAKoKIqiKIqiKIqyQFAFUFEURVEURVEUZYGgCqCiKIqiKIqiKMoCQRVARVEURVEURVGUBYIqgIqiKIqiKIqiKAsEY62tdxnmFWPMI8A9Vf6ZYWBTlX+j2mgdkkMj1EPrkAwaoQ7QGPXQOiSDRqgDNEY9tA7JQOuQHKpdj7XW2sWV3mg4BbAWGGNusNYeUu9y7Apah+TQCPXQOiSDRqgDNEY9tA7JoBHqAI1RD61DMtA6JId61kNDQBVFURRFURRFURYIqgAqiqIoiqIoiqIsEFQBnBufrXcB5gGtQ3JohHpoHZJBI9QBGqMeWodk0Ah1gMaoh9YhGWgdkkPd6qFrABVFURRFURRFURYI6gFUFEVRFEVRFEVZIKgCqCiKoiiKoiiKskBQBVBRFEVRFEVRFGWBoAqgoiiKoiiKoijKAkEVQKVqGGNMvcswV9Jc9kbAGNMU+b+5nmXZEb6daHtpDPQ51h7f15N+740xLbHjRJdXUZSZsxD7syqASlUwxjTbWIrZtHSwSmVPI0lWnKbDC4PW2sAdvwp4clQhTALGmCZjTJNvJ43QXjxpbDfzgTGmJa1jVhTfNmPnElePSB8KoLwPJam/e8XPWlt0x6e748T1+bQ8ewBjTKv725bUMs4njWhAiDzDpvi8kZb6GSFVMt983dvEDLILjfhg0GhYa0vGmH5jzAuMMSeloYP5ThUp+2uMMecaY1bWu2yzxRhjrLUl9/+Bxpi1kcE6sQNzRPHrNsa8CXg3MAB01rNcUbzQaq0NjDH7G2NebYw5xxhzQL3Ltiu4ibDJt5tGZbr2b60tOkHmecaYJxtjepI+ZsVx46xvm8PGmLWQTGUlUs6DjTGfNMZcaow51b9X7/JFFFSv+L3UGPMw8D1jzNF1Lt4UYs9+jTHmAGNMV5KevRtj1hpjfgw8G8Bam7fWWmPMPsaYPaJKRV0LO89E2tGGSsamtBCJevkg8Ho3TgZObmr182Ba6meFkjFmlTHmDGPMgfUu03TEDc+7SkN1sDThhA1jjDnbGHOCMWbYv5dkAX2mGGPOAe4G3gv8DPi2MWbPuhZqJ/hOZYw5GbgTeAXwSeBqY8yx9SzbTPFWODehrjTGXAP8Gvgd8EljTKt7L5FtzBjTYYx5P/A94GjgFOBb1trx+pYsxAlYXcaYzwB/RMr4PuArxphnQLqEl4jiZ13dHmeMudwY81FjzDPrXb4q0AeTk+lkPzDGPAG4H/gg8CPgf5IsDFTCCTJNxpiPAX8DfmWM+Z4x5vg6F20KxphmY8x7gWuBdcBZwNeNMe82xnS7a+o2TkWUqWOMMf8ALgN+BWwF7qlXuabDPfseY8yXgauRNny1MeZcSIZc4ebYEeBw4CnGmOXGmHZjzE+ROeoa4IvGmEXu3te9zLuCKV/KcLox5k7gp8AvjDHPcudTVceI8rEWuBDYH8RAAtwFXGWM+ZEbT1MxFxpjLgX+BXwa+Isx5g1+DEoKptzwvI9TVo8yxrTN9TsT/2AaFSdYbQTeA1wB/MYY8zJIj+WkEsaYJxljjgP2RibM44AzgJOBlxljButVtp3hFPFXAo8CPgA8DjgI6SevMcbsU8fizYiIFe4xwAuBh4HnAVcCTwU+4i6t+6RjKocaFoFlyKTSaa39ddI8UsaYfuBDwAHAM621j0faShPwEWNMexI8GDMlovi1GmNOQtpKF/Bk4JvGmDPrW8L5wRgzZIz5CfB2mBTwrTHmUGPMacA+wOeAY4AnAvsh/X5N3Qo9S5zQ8i3gROANSH1agB8YYw6qY7kqyRr7I2PSK4FnAYe5v5cAL3X9qG5zoesPH0WUqWuBxwL/C+SATL0F9/g9NcYciZR1T+Bi4GzgF8CnjTH7J0GucJ6vbcAbEQPfacDLgRLwfODb7vxn61bIecSNq8uMMUcAL0Pq9y6gB3iPMeZwNwalRhaPzNvPQ+aJs4wxpwDPAT7qXuuADxpjViRZkTfGPMMZ+dYB5wGnIs/n7cDTppFR6oK7j93GmM8B1wGvA34LfMoYczDMQdm21uqrxi9EsLgZeAeiKO0HfBy4HTjNXdNU73LOoV6DyIQTIBPmish770I8gmfXu5yuPCZ23A78tyv7v4H9I++djihSb07DcwH+D/gncAPwOHeuFXi9q98hle5BLe999LeBNUCzPwccCdwI3Dnd86pF23BlmvK8gSHg1cDx7vgpiEfgfqAAfNSdT3xbidTpecA3EQHlFYgyux74AmKoWlvvMs5DHZsRoXhZ5Fyvq2MA/APYL/Lei4EHgf+qd9kr1MVM0zaPdM/raUBr5Pz9bmxeV+NyNgHN0XJH/n8rsAloj5w70T2LzwNLatk2pjn/IkTx63DHlwG31Pv5x8o44P4+B/g6MOiOT3ZzbgD8GGirYxmb4mM44vH7o5unTo6cf4kr85PjbSZtL8RIGCBRUF8G+tz5Q5F5+rf1LuMs69Mc+/taYBz4CfB+35cR4+E/gK8n9RkCB7p5OwNcjhic/Xu/BP4ObKhj+eL9ZTXwfUS2PtmdewISrfbdOf1GvR9CI7+AlkoPFLF+3QfsE3nvaMQK9pd6l3u29Yq99yREgfpx9FpEwboZ+CHwqISW/UAkXPIWxLIVFVauAP4CHFvv++/bEjEBMHKvzwQmgBtj7z8K+D1wbT3ueYUB7UjgT26g/T0RQRvxXjwCnOeOq65MIQaMbyDhSU2R88PAyshxE7DY/f9OJCTs/e7+vsf14z0q1bneLyoIYu78+4AHkDCYwcj5PYF7gc/Uu+y7WO9423tm5P+jgOvdqzX27K9GwtIOrncdImVqifzfC+zm6wi8wD1HL2iuQzy6AWJw7K1lW4u1o3cDz46U9cPANe54f3f/J1wfGq5Vu4iVc3fEO+MF2dbY9T8GvhGvXx3agEHm1I8Bn3Ln1rhXPzLPTiBLMM53Y9Iz61TOqAFgiX+2wPHAGHBv7DMrEYXiX/W6v3OoZ0UDgnvvJ67/vSp2X14MjALn1rs9zbZ+wFDk/5td/U6NnOtEDObbgaPrWT+mkfmANsSLtg14rS+3+7ve1entQHeNy1vRaAY8GnFS7OuOn4qE3I4iBr4LZnuf696wGvEVfwDAMxBPX5M7/hJwdeRhfwAJffsJcEy9y7+DesWFqDOQhdyPxQkWiLD8QTf5LHPn2tzf5wEPAa+sZ7kjZbkYUZZWunPtbrKMWh+9ILAvIlh9GCdc1fE5xCfUx0QHZHf++4j34vjofUBCrEpEBLFq3XM3wH4JOCfS9v3fU11b+CpwLvAdxHPxXvf+OuAqxNrVH/1sFe/rAJB3ZfYW/0+5QfYWZLKIerX3RizsLwe63LmzXfv5ZjXv7zy0m7hxynvvs8CekWfYhIQuFYAj612HubTDCude7sanF7vjXuA17rk9xp3zY9bxiPf/7dTRgzJN3d4B3IQoAX4Mu9CNU3si4d4l91wPrVMZW4FPuPv9P4ihYZF772LEePJTd+8vx3lgXbs7mRqNtUio/6+RyIObgC/G3m9CQmmvAT4Sf2+6tjZPZSsTCGPv/Rn4fKwc73DnT3B9eD3iJfgjVVas4+NK5PyQG1evRhQf70H6NCLAnha7/kmuzVxczXs7X88n8v9jEGNGNMrAKxOfjbZnRFm/3D2b1qTX05Xv+cic/CZgvTv3eFe/N1Puzd+AhCjW1OAc+f0pRj9kSdK6SF/Z35Xx1sh1/ll8FDFCH1untvQoJGrLe/tagN2QMfWTiHL9biR0/reIMd17/2fUjureoBr5hSxqv8N18NfjQlqAV7mGdTEi9P4bUaT8oLgvEXd0Hct/JHBYhfNHI1af+5FEA/cR8RAg4Q13A19xx1HB8ypkkn1clct+HPD0aer0d0RI+hki3F0J7O7e94rHPyKf8c/lfe55nVPvZ+PK8/+QEIY7XLkuIlREDkUUrP9HxIKFKIxfd89uWqvlPJbxVkTweFTs/PeRJAXDkXPx0J/zgduAy9xx1SZHQivb8xEl8DjEU38tEhL5HUSh/kTkM+e5fnxk5Nxzgf+4ekxpf3VqJ1FPdi9icPoWojjsTjgZPgdRdt8V+/xidx9+RsKUoAp1XRN5ltMJo3sgnpxrCZWRfRAP1G8q3LMvIWP0qdUo8xzqeAgSXvVPZA45Behx760Ctrj2dwti8PFGrCXA16hhWJNrazchYdLLo+0HibK4EwkhOyNyvgV4OhIVsH+Vy9fk+vcDSJTHyW4M+A/w8di1na6/nx85Pgl4WxXK9SLg0grn/VzkDRRvB26LvN+PzK/fiH3u765NXFbFe3kZ8BliSjti4NsC/Ab4L0R+8FEha929/izlXqUBxICx1ffRJL8QwfxqYLNrI1sQb/yQe//TiKxxTOxzpyOy0n/79ljvukxTv3WuPz6IKEZnUx4p8jPXzw+Ife6FiGzyUndczTn8GCKKd+T805B57U7X1m4BLoy8/wIkMdHL3bHvW81IiPoVwNIa3usWZG4eA36OKNv9kfdPROS+swgN1R9y/ftNs7nPdW9YjfhCJpVL3EDwNuAIImtokEnmFvfAXk1Ea0cszl8HHlvnOqxDlIRnxs6fiCh9n8atJ3ENdAK4xB13I0pugLM8RzrVcUgoZdUmdtdx/4Z4LqIWlYORuPvPAWvcuechlpRvRa57CuIJ+a9Y2fuRQf7wWrcn3z7c333cwHAjIrTvA1yACFLPjZT3U4gCdVrs+05yz+aMKpbZl+Eg91uXRAarNa5cr4lc/wJkorgdOMqdG0DWTfwdN7HMdGCbYRkn1/rFzvtwwJ8Cp0TOf8iV+8xIWx4DXop4vlcBP0AsoW8gsp6sxu3ljcCLKpw/193jaxFB7Y+Igh6t43dd3Y+KffZk9xwTYfyYpt6HuDI+LXJuAPGKPZdygeV8JNz1He64hdB7+4xYG94dUbhqHp1Rqb0jVt/fuH4U9+S2I4J4CTgxcn4p4sG+AThpvsvI1KiXJsRw8AfgjbH3Bgmt7N7g8jZkvdQh7v97kXXxA/NYzimeOtc+vkj5WPQ61w6KwBMj5/dH5ooTkXX733bXfZLIGuZ5KOcAojh7gbQJ8ej+EHhh7NrXIuOjN2AuRgT1z0Tqexpi1Pw6VTTiIHPQubFzixDP6geQ+TO6LtWPv29DBNrnxj57BDKnXViN8s6hjXe7/70S7svfi8gFv0aUkCcg66kfxBkHkGiYba6tRY2eA8gc9xARIT9pL+AtiPd7A+Vr5Xwbqxgyiaxb+wXika6acosk7coAB0XOtSDj/K3ImLnS9dPvIQY9b2he4/rGfwgNad5odjEiSy6uUrnj46ZBZOubkSip3Yh4Vd01n0XkkGg7ejcyZj6Mi2KZ0e/Xu2Gl/UUFLwqyhuAGnDYeOe8nvQ5EmNyIWG8NEiJxKjJhXkFkzVEd6uQHtlXx866Mr3WdqwVZ+1RyjW+T/wwyYf2eyCJnahDeEBmcByu8dySiiPS5geD/uUHrZkSBPd1dt8R1wkcIQ1tbq132GdTND05PRrLReSX2KDfABq79HOzOL3UD3VeB5ZHv6QJWV/sZRI4/iXgpj3DHLUjYz/mIgngjIli9hdAY4gfgpyHW+XfMU9mWAI+vcH4l8Cz3/9HuXt5ORABFBMBfIuEWfq3AFa4u1yMKxV+BvevYRtoRYev5Fdr+L1z79/3bK3WX49YjI+E8/0CScEQ99z1IFMP6eveDHdS9FzGMXI8YoZ6BWOLvRYT5qwkT9wwCX0EMcRvcuVWIcHB75Du9p6Lq3vJYXabzXhoiXnF3bjkSyu7r0eba4d8Qz/VliNHtIeZZgY+1kSHKDZ1N7t6/F1mvcqZ7PtchhpKoAfGviPfkVkQQe+48lO1gwtDYiuM34sV7bOTvvxDD54WIkv0nwjngSEQh+SrimfojcOA830/fN73xYcD9XeTunY8c8udPRLKSro58x3sRj8cPEO/mjcjSha4qtdW4ELsK5zFBFIaASAQIEjp/om8ryJh1E6Lgro9c10YCkk+5PncOotz0V3j/CYjyETU8tSPe9ltxIYSI9zMfvc6d3506Lytx5YjP21FDyV9wyc0i545HMnZ7ueSTrn3GvZz7xL+7SuX38pDvQx2Ig8WvjRtElKcAkSl+STi+n4p4Yj/ojqfNFVGlsnvdYL0bg86Pvd9DqGy/FDE874mMW+uQuf3DSLj92hn/br0bXVpfFQa9qKdpETLJvRMRRPZGlKbPI/HvS11j/AxiFboFsR5lXQOte/hnpC6nIMqQj/de4TrWXoiAcZu75inIxPlFd10zEnMdEBNGa/hMjkXWVR7njntc2Vchyum/XLkPQib6v0Q++1hkYv1Shd+ptTDYhHiUro6cOxhRpD7l2s3HkTUfAWJRHXDXvQoXHlrjMvcgoXPfRhKrBEgIrU8A8GVEKC+69/eMfPYMwpAYwzyuPXP9ctIDTZhM4Q4iSqbrmyO4jKmR8y93177BHS9GPGtfBt5Sy3u8o/bi/i6KnFuBeCYNYlW8BhFa/sfV89WRaz/s+vZz6l2XndTzSa6s7yf0yh7l+u35SDKR1yFhZscgE/z3cMKy6/t/w4Wqu3M+C+W7al2faer4QkTgP5ow8dD7EEXkcmTiLyLKXR74rLtmJRIB8T/IGPgRqjivuOdwn+sbPyC0rj8PUUbuQAyElyOGt/uAX/v2injQ9yPitdzF8hzI1MQbe7vffiMRT4F7z3vOvoFbI0QYku4TUZ1FmCV63vsG5TKEcW15O+EaoAFkPN+EjE+9iEHrXiICIzL2vhPxDN4FfCD2O3MWbpm6ripa5g7EmxK4cra6etyEKKGfQpTmHOIdu58w6/nzEOXhrfXoZzOo9+muXscjETRjhBFPpyJGcO8hjK4fvhmnVLhzNyNG2t3rXadYW4tHSq0hsvYeWVc6ihgXvuL+34iEVX7EtyvEiFOzkElinnfEcPPqyLPYw5X/BMSwdANiyHkT4i17mbtuABlXA8ozwFd12QmiwH2QMBKlyfX5VyFbS52KLJX5ORK51ofoFDe5+38FYrD9GbE8EDMqQ70bX9pf7gFdjVha347T1BFLex4RMLYig/Q1ruN8jVBIeyoS7/9GXHafOtVjurTir3GD3Uti5z+IKE1+0X4rolAFhJ6eNchEVNMMeoRWnaMRQel9RKyfyFq5O5B1ct5a9H1X9gvdcT8SnnREjcs+3WL/ryMWq6hQfzYijDyLcO3fVa5u0fCvPxOzKFW5DkuQif7vyDq5tyNemS24kCpkQL6byFoVxOJ7NGIJ/gjzaBUl9Aw/FRE+3xw59xhE+IhuAbAbMhC/Bxe6GqnbtxCPxR47e241vOdxwex4RCg5NHZ+N8Tg9BPg0e7cje5ZHemO90QExyuidU/KC1kc/xtkLP0Osjn3KxHDWyuyRiVw9Yp6FC5ELPJvjpz7AOLpPcUdDyPGlifWsk4V6niE68f3EU72P4u8/27EoPhVRLk9ADEyFolZgKmu4teFKE3/QsbL1yAK4PZI+1qEGNSiY9fLEAPEvIdWEY7pP0EE7gORSIKtyJy1zd3Tp0c+cyqS6Oi4yDlvwLwDl/wJZ2iY5/KWZeZ1bflc90yvBX4Xu/5Frl5XIaFv1yNGgnjGzSHK1w7tcggeoWAdD0t7NWHiq/9xfc+H7e+HzF8/QJTARyPRB1cBf4h8xzXuexKZCAWR8zYhBtfoEpgnIvKdTyoVfQa/ReYz7+F5EqL8JkYBjJR1g3sGd7nXvwgjQwYQ58SVyHh7HjLufBqRQfxSn1dTxZDJSFnj892xiPzwTcSg+djY+z9F5jNv/Fvn+vZfCaMEjkM8aKuqVOZK0YItyLKkP+CWFrm+PIaMO9uQcewr7v/vuGv2Qua5XwLvnnOZ6t3o0vKifID2GQ4/gAghX3IPaLsb1Lx34Qmuozwh8tkPuw6SmFAqyq0/7Uz1pF2DeCgPdMdLkAnoc7Hr/s91vjtqWPZoSvRm9xzOiQy4n0SEvqe641YkfPIXlCck+B7hnknxjJrVtAI9AXjndM+E0Jr4QsS65sMtjKvH72Of+5Grw9cig11NPcpIiOo45etn1iHWwisRa3sLIugEOO8ZsvB5xNWhKoOwK8vlyMD/eHf8X8CfK1x3KSI0xieTMxHr4WtreV9nWLfTEePFEJIk5HuUCySXIhPLAZTvbea3svDbBzyRBIQlVajf3sj+YVciint/hWv2RayiN1AewtvqPnctLrkVsubs/xCvcCIET8Qq/D3Ee743EjHyeETQ+mJkbIgL4S9DBNF9alUXZMuUjYjXPjqe3oMIzLvHrm9HwsZ+SMTzOo/laaY8wYjPTvh5xKregyijVyHzgjecnYdEs5zojrvdePQNRPB6Xg3u5QDhmvQ3E2alHsGFsbnrvBf/n4RbDHzA17/C91bc+mWWZetCEif9NHa+D1FW70bG0TZXtgAx/vrxpJnytWHNri9+n1CpTIyxianr/HZ3dQoQGS66lnElIoj/lDDRn++jP8EpubXqk7OsX5NrT89DxpfvIp5nn/TlV4SGHENsTS7iJX+AyJZmNa5HtyvzQ4hnttv1n08SLid5NGJsinrJ1yBK7oNUYRzaSZl94jH/DJ7o+nI0wdyjECOub0/NiBf2QcqTJe3Set66N8Qkv5DJbV8qrB9wg9y/kXhcP4nsgwgnUzb3dA+wBQnd+Hm96+bLFDu+DPHcfAO3d4s7/yRE4L2MUCH5NTLBPwoRrM5ErPKvxi36r+WAh0yU+yNe158QeiaXIYrH1wjXJ74TEVqOQoTlE119XoJ4CUwtyu7um084cFikvF8kDC/xE9DBiPXxKe64HbGm3hT5voMQj8hXEQts1axwVAgjipT1aciayuHotUhmvwDxFPhzz0eE3Z8hgvi8Jqah3LjhB9x9kEnr44RKgd+8PTqxdyPK0reYqkjU1DM8w7qeigirPvzOezCi+zN9hsj+WohA/CvEkPVAtN8n6UUoUL3LPZNHx94v2+ICMS4UCKMR/OdPQTygH45c/yb3vW216PeVyhw77wWW50bO9SFGi62Uhyg1uzHjJCS8+SvTfe8ulHNHff0cRCjxwtZaQiPUuwkVgG5kfL0AMYD+m8gWNbtQNv/9caOlH3s+SGjpjwpOpyNK6kci5b4FEXovRAwlNyOKd/883cchxLt8ibsXGyLvXYp4zn7n7qlfY7zKjT/3EBps/Bz8aEQoDNyzr8oaP/+8kaUFI4T7ur0FiZz4EWKgbIr0sw8h89Xxse/pQdasnot4mC6oVpnnWM/JOlR473DE4/Ugka1y3N+XETGKI0acwxDF+MX1rtcM6v1RIp4kZPwsIlEkk/048v4i1/6uRBSwmirv7jm9FjGg/wTxAPox6HWI/HGqO25G5ja/JKsVWc/+I0RRPK9GZW5Gwjj/yNT9RT+DROGc5usXea8NGeN/Tiwz8S6Xqd4NL6kv97De5wZWLzheRPlWDpsp39flEtdpfkb5fmEHIhPJlxHF4/nufCIsQq6u73YD8hcRy+hmItniEGv0jYQhfIcisfx3uA641dW/qmni4/fMleMeV+bPICFTecSN7r1lr3Xn/WLgdkQpHHHPdwzZYLPqg5ibGD4SaVNLEKHj5+54GRKqkEOEBD+obUAs1PH0xfcgQsPrXV2+X+XyRwemVmRdTFn6ZcSa+B/KQ6yaECvyP5CwmHi66HndoJqdCMGIt+tORCC7F5f5Mf55xLBRdPVMTH+t9EwQS3QOeJI7HkSs9jcSCsrnIorRi5H1Eee49rY/kWygSXy5vnMbM1hr6frRnxGhOp4p89Pu2fukPzVP8ER5REln7L3TkHBp/8xejyiEf8KtB3PnV7lnd5Ubw7423/0oVq7nI4l1otnnXooYB/dE1tcVEWPaEbHPrkfCLv+BKGW7lGTBjT3vR+allsi5NsQA9oXItfcjQvvayLk+JIJnmopWtQAANd5JREFUhDBi5yxX9geQcXXeEua4cWYM8Ur/FTG4jCEG02bgrYhs8M8Knz0NGU8revmQ0Lwbqf4ef0uQsfv37vhId2+3EoZ7TnrOXBv+KmFCmBMQZeEaJELkTdUs7y7W9bFIyOoXEW+sH2OXu/b+CcqXBnQg4c95RCa60l33W6qYcG0X6rcMiYTwMtHuiFJ3IKKI3I8Ycj+GKPLeM74SUaS+7c5fjQuFrXH590bmsYDYvpzu/TsRj6xPDOOz0v8WUfxGkDDkqizdmO57EXmigDN0R9rVAUgUyncIk071IMt8nu/eu415NtDWvSEm6YWEFEUTQeyNWEA+Rbi+za8Veb7rAE2Icnc3MoC/nPI0uachCtLdiIBe0y0EdlLfbkRo+A0SO30oYj1vQyaUq3EZDZGY4/sQ4clbV5+OTKI/wnkdqlzesgXn7u+nXOfY2w3C+yBC393Re42sk/gZ4US1AbH0foHYeh+qG/L5NFeO6Pqxp7p29hx33Ip4Wx8mYvFxz+STsef3bNeu/uXqMq9WYGQtUn/8viCW/IcQq/lmJIb9XPdeDzKBfJZyxbALsX4VEMt19zyX1VQo52mIEPJuIokbkAQKtxLuj3Wla0tPZGpo3Z8RA0Fd9mhCPAdTvNJElGjXb5sQJeFzkfNHUr5Fy2pXz8A9owwJFsSizxYJhbwPt4aPnSv5T3P9Kj7ZHowoTXUdi5F5449uvLo0cn6Z6yMfRTxlDyMeBh9psh/hmrRXu+sOmsdyxdek7Ysob1sQYf9mXFi0K+tm155uc+ORz+A7jHgkD3HH+zOPUQlufPkncFbk3BCxVOiIQSoAnh37/GMRZexHkXMtzH9mzwvdvbkAUSBakQiir7m++RHXvq9B1pd575JfxtCPKNcjuHnDldMrW4e5+lVd0XDPd5RwrH83ovQcQzj++nJfgBgE/LYqByNRF++dz3YwD3Xy5W5yrzcjyvn3kBDVLBKy7Nvxq9y5KdvCIJ6o9yBe2ylb8dSpfpVyO+yFGBVeFr0PiEHpZ4Rr//Z0bfTzrm+tQTzB38Utq6lhPY4kHMs7kTExAF4Xuca3vae6914Y6SeXINFtP6VKETzxe+3uc3OkDP3IEpRbmBpO+z7Xx1/gjo8iVPw+RhUMlXVvnEl5uQE1Ho43jEx4Oddw1kWuP809mDvdAPhxwjVX7ci+U4cjwvBTiCwur1f9KpzrRuLZtwA/ib13hLsXFxMKHu9GEibscoruWZY9no7+84j3qxMRAOJrEVciA/hHCDPnPR0ReCeteRV+p5r71JSl93b/eyV2ALGo3UZ5ooTXIQLvt5F1c291A0dcEehnDhmgZlDm81wbOC1yrhPxSNyKWDwXufL/BhEM/WLw1yCCmM+WaRCB63LEyv5j5kFZdc96yp6ZSEjXVYhw+h33ewHiVR2I1G87Ioi9BRHGM8jE+H3CzFx1WwuHhCx+hvIENb2IcHIvbrLw7QlJtvDDSB3bCcOx/PjUhIQ9n0ckUiHpL9cH7nP1aZ/B9V3uOd7IPO4nN8eyx72Q+7r+8hVEmPIhk/3uOX6RcL3R0sjnHuWe/asrfe88lDM61vpx/xnImLsnEvZ1D2Iw8YrKpa6s0TW/S9wYcAPOIz3fZUSUqD+4vu29TOciSnML5eHcf0Os/7tHv4fQM/D0+Sxj5DeGEOPcZ3FZMWO//wnC7JKPJ7blDeG8caS7l1dV+I0zEYPnAdWoQ+y3ulx7vcvVZ4Ubh74QL7P7/y+IAc3vU5ikDOfRcnov8hLES/1Gwgii9e7e/8TVv83V6UpCY/i+JHQT91g7itb5BsqNhfu4thgNPT8IUUoeIcyGW7VQ48jvxhWpHkSpDgjDo1cjhv1fUGE+QNZl/pnIcgHmf7w8gXBZTjQfxbOQeedGxCgb7dOHIvKpXyrlx7PdEWX755H+cigVNreft/LXu2Em6eU6+tXAde54L0SIHEFihdsj1/YgloSHgbPdOZ9S/mzEijKvG+7OsU5xZWFvnLfAHR/hOtHfI3XwDfI7yEDvrb2drr4/pQoKxwzq0oMIRP9ALG2rkHVjX47Ux5f93e65RUOmrkaErkfFvrfqAzdMSbTzMcqz+h2CrN+KZihsQ4SCEcQA8VVkvVbVJnrE6BH1YN+JhML49ZMDiCLqw+fWIkJ2CRFevhv57NcRBez3iDJ+CyIIzUs2OkR4uhmZnI6LvNfn2sTllG8MezviyYi2id+5Pu63OVmPePd/QGRrhHq9CJMPvMa1hUcQC+z+ri/kiWxyjqxlu5NyQX4P14+/VO/67MJ98P37u67/r5nmOi/o+D3x/Obwl1a7jDOog0GMgSuQhBnvJFzPdRFiaHyaOz4GCVv8gnt+KxFh45fIeD1vW6O434sKL97I9lvEu3glkfBgRCHciAjJBlFYb0CEne+68eEGd80L5rOcFZ7zKxEF63Xu+Argcvd/1PJ+pGsHF1FuhNsPGYsPrFI5T0TG9XhIbFPk96/FhX4ixr7rieyZGqnL25Coi7WR71mNjKt/okaGKiRT8/3Ae9zxfyEe68fF25Nrsw8T2eanni/XXuPbHpyBGM32IAzRG469H7i+9yh37gnu3HcJlfiX1LIuO6tj5Pg0V04/Jvq2907EkOv7yF7IHPkWd9zunu0nEaPKm6hidNQM6nUkYgD06/VbqLzO3be9Pdx7b6Ua3jORP/+EGJd8IqNF7n49iEQNnYxEAASEekIr4u3bQiTzP2JYvweZ419Rk3ta78aapJfrOGcgwuw57lyz6wRZwsXP0Y2Ur3WN4HQk5OiziND7/5jnELddrNtTXGe/DZlgLou8dyEiSHqh3ofwLEIsEh8kXPv4RGqcwhhZy/RTxNv3c8otOl9FQiDjg9tTXKf7EmG65vV1KHtUsPLtph1RULcSZqLsQkJHRgmtP/76ZxImVgioUsYtRJjI4CxT7tzp7jfPJ5wofFjws11b/yXiGfgQIqA83b2/xPWnq5BB8v3zVM7TkQH2OiTM6PnErJKIwuT768WuXtcRbh3g1wac6L6rLCSVOk50kTL4++33Cy0giu1evq0jwse/cRnEEC9rhsj+he6617tnk5jQqznek2OQseoiQuUpbi0+EBF4HoUICa8gtp9jjcoaFcJOQRSiCcQIcQ9OIIhcczNipFoT+cy/3LO/1v39IVXcY8u1le+53/seYkzI4qzcket+gFjXj3PHy5D1gFchCuPH2cX5j8h6RqbfyL3L/ebvkBDDq4EXxuvk/n4XmQMP3ZVyzbIOJyHj55HRssSuuQhZE/cEZBnKrcCnI+97gXYpsXXqrj+8nyqu/axQ3mZEJhhB5tRmZGz9DeXKdSI8Yu6+raxwvg9RKu5ClKHdgOcg80Ev4tX7q3s2byPM3ujb02uRue86Ypu7J+FFGPFxlqvHvyk3iL4WMab5hHl9iPy6DZlXPoAYdU9hnj1nMyj7k11Zotv4dCGROiXCOdCvc/875fk4fJ95AU52nYcyTZEJkIiiWwgjnQ4gYjBDZL0vuzHgzsgzWY7Is9cistWTkKUAJ1JDx1HdG2m9Xky/790SZD3cA4QCWC8y2V3F1LjdxyDp+P+NTOA34IT6pLwQBeJhREA/E7HqbsdtP4BYMq4Ebol8xgtXb3eN97galbVSGusuxGLyCC5UlVA58pk/30G5wPA6wjVOT4p9piYTE+UC4PMRq7qPrT8ACYX8U+Sa9a4dTUlLTJiW+SdUKYwGseR/ErGyrYmcvwaZQKLZB/16vk8SGge8lf0XlC+Qb2OewkaQELn/dW14BeWersm1S5G++1HXDv7LHb8E8bQ8j3Ai/77r74+ZjzLuYv18mbylugMRwANkglhWoW29Bpm0348o3H9g6r6d3ZX6VlJeMy0bEoXweTcWTFmDgkys38V5ger9QgwjpyDW8zchHpGPuOdZFsaJRDUEiMHRG+F2Q5SI51BFJRYRpG5A5rivIJ79TmQZwzgiIEf79AGuz3yYWJbM+RifEM/3OPDK2PmzEePeysi5ZyKC7K8j928DU9fyLnHvfyT+XhXv65Mq1cO95/v6vogx0AuRH0UMZmdFr4t8bnLza+pkqHLP5ybgCnf8ZGRcrdl+szMoo/dk34Yo1V/EKUCIV6yAeIzfRbgc4ymIoP5X11a+SWjwbEIyLR8T+Y3BetdzmrqfhShKB7vjYVenP/lnhBhMSpQrhbsjyv1fEcXm3CqXczo5/JVImOTLYuf3RiIN/jfy+SPdta+MXDfvMh6hly/a/4YRg/LNiMGxidDwfD7h3qMvQAywH4t838GIgW+TK/+XqHFCsro31Hq8KBcaO4hZKpENIUdwIQ7u3Mmuszw7/j3uOzqo014oO6mr3/fu29HBCrGKB4QLtJ/lGqhPsBBdP1H10AbKQzKaXUdvJxSODkWsJbdFrvPvvRtZt/VFJKT1KYjSchzi7fxi/DdqeP+PQISTe5HJ5NzIe+cjYQAvc8dtyKLlIuWTTMV9v6pU3j0RhekTkd/1awMuJYy/PxlRvJ8c+exh7rMbgbdXqXyPd797crQNTHPtAYgy+4pIuQ9FBLLvE+5vtIbIXp31eLHj9OPrEaE2T/l6zOg4dibiVfohLrtgtO0k9QVTMhruNIswEoZ8CyLYvRIR9HZHQtOuRLLwVT0p1QzKOUS49vRGwjDjAcI1v0PunBcofuDGi6p5qeL3PFImv2XCF2LvvQvx9B8SO//frn/N+5pwRFn7OqJktiGK9N2IB3+b+/+iyPVfdWPPvcjYP4ZY2C9DjLT7uuvOIhJCWaN2cL8bb5ZHn7X7389h9xFuSbGf68uf2tH4Vu8X4rncCpzgjn/u+l/dy4xkXc0gRsoXIYln7nTPoZ1w/dikDBT5rN8W5+WRc82IXPFL5nlN6y7Ws6IBAIneug8JIR9w5/ZAlIwsYijcDXFsvK3C56u+Npzy6KhKY9KvXV8uW8OHyEgBoWG/CzGaBFRh/2Bie2ASjtW+756IGGyi+/g9DlHuLkPG1i7EsDZOeYKqYURuqmlk2uTv1+NHa15Jsaz2Rx+e+/9SxOr5O8Td7QXCAcLsVj4cp4Uwe8/xiHD5A2o8mcywvi8gzCi5Eonrvjjy/uuQSfQ6QgvRECL0P0S43qvmAzkSjnqP6zx/pzw73osRq93z3bG3krcjguAjiDWliCiD3Ujo6DW1qEt8EEO8EX9CBuG9iVkLkUnom4jQ4hMuLEEmmT9SBU8fTFkTamJ/m5CJPY9LhuTOf8a1jWMi5Zxwz6QbMYB8yNXn08DpVbrH+zJ1i5JmxNJ+LJG1UUg4ZED5BHIB4g0PkKxgSRBWosaP/ZDw8UuJCdaIVfY3wG7TPMvnI2uPA+DL9a7XLO/Bmcg4/GPEq1zRmEb52qkvuzY4ighzGxHhbX2tyu3b3w7eeyYyZ0xarN3fgxHh+dJYvZa75/cB5nlLHaZ6y+N7ex2CeHX+N3o94nW/FxFgomFWg4iyusvZAKkQpoVY9h9BQuNf7MaVA5C1St9FjH4vdtce4frHl5Bw1MPdePRXZK77JXXaaByZm/JI1IG/p9FnsRKZty6KnDuslmWcY70WufHoXt8eElCmbmQOCpAlCoORPvd6RK44CPEcne2u81sheIH+8YRZ0E9Alr28C5n/vkgd8h/MoN5PxHnFKQ9/LCDeWT++9CFy3l2IgeGnyBpYL0vVYv/j+Lx1CSJLfwKJdvBlPRGZq99BuUPiAMTAc13k3F7ImuRqeP6ie2Ae5c7FoyHud6/j3bn/RoxXiyPXeSX1h/Uai6bUrd4FqHJD2weJ534IeGbk/GMQAft2JA769Yjg9PtIRzgICRv4fuRzqxGPzV2I0PFPJAytXmEY01l/riXcV67XlfUCxIJ1FyIoXUjoFfHhnk9ChOuapoV3HazJdWCfXOBcxEoeEIaqrkQseHcQTqRRK9JaROj38eH7IkJCVZN5MFXxezsiTD0BCemMJwCIZvV7qivjh/13uXMF5jG1e+T3vKI5rXCJCFB/QjzHPjSmHQkb/jxh5rP/557Pz13/eZgaCC6uff/VDbL/D7F0ZgjXSH7I9cs9kNCM77u+exAy0RxNJHFKLdv5Dt5rR0LTJpBQz2sQofAdkWdwnKvfyymfECeVeMSqW5XEG1W6J8uRMKyNyLqx1yPK3C8JQ692pGAdilizz6FCNtgalD+qvJ+ICFsHR8anRcjEX6Q8i3QLEla5lUhqf/f3uVQxpb9rP392bezzhEJNF+JpDggTf/l6PN/1sVOIJJnY0Tgyg3L473gXYcbpaGhnN5LAIUAUwRMj7+2GKHubCce09yFe1efEfmf/uZZxnu53M2FI3VNj77W5et/h23v8s/Us+wzq9gzXjsu2DqljeSoJ6z507xluTPWZwfsRg9EfmbqG/CRkHH7YPbfbiW0jUsf6xRWo41w5P1vh2msRJX157L13I0pugDP4VLHMj0MMfM+MnT/W3VufJfdHiKwazTfwdcQREE3ctj/htmw73RN2nurg98D8Q+RcF2LcLyFj6d+AK917H0AcLN6Zshoxbn4F8cBO6et1aU/1LkCVH9perpGMIxPdWnf+dUjIiF+QuR5R9gLgve5cJ2J1LFv/higVZ1PnbR0q1NVbTVoQAfj/CPeK+oqrRwYRsrylyCCKoU9330EkK1EVy1ppMW0PolB/ItL52xEFPUe4EenTEcuKVwrjyleHG3DOQUI+/lKLOrnf7nUD1kZEAXw6YiF/HZK45P3IRHId4uXocu3s/Yggc0CkDv3zXLYliLf7k7HzT0ZSoT+dMMNZM7JGokS54eSViCX7aZFzb0U845dTo0xvyKL+37o2/QCybum/kTDmT7t27rMCvhwRsu9xf6+jQkKAGpV7cg1B7HyLu4+/JyIgIsrqCGIQ8MrB5chY5aMV9iQcx+ougMXqVdHbHKv3+Uiykajn9lfIJPmlmX53neu5HzLePoIIAWOI4u4zsx7rxoErYp9biwhAPmtlVeuErFH5GWIweZvrz1e6MntBZQ/Xt/4U+6xx191EZKuaeSrXF1xfvh2xjkeNegchxoCNxMKkCA1svq+vdM/hD0yTJbaObeRAxPg6goQkHo4Yol/rxrB3uf6QmHY9w3olrryEwvq1kXN9iKHSGw59ojK/pOBF8fq45zFAJIKkDnXpJ4xCm25z8Q5ErrsFl4mVcL44xvWtC2L9qgeZ4zfjPKBVKPsBrj/e7caNDCKbGTf2XYGsIfYK+XLEAPo7XIQPoWz+EyQMfNj1lQ8iSztqlm+DcA/Ms5EtlMbdmPhk9/4bETnjqUhEwv2IEeE5iOf4/5BcDlXfRmPGdap3Aar4sIxrLJe7h3QvLjsY4unaA1kf9xnXQa5A9gMbJdzfaD3iBbm53vXZQT0nEwZEzr3KdTq/5uBQxEL0RUJvXydisf6560y12NtlR5b8fRBP2AWRc9EU4z905xa7QWMz4Zqa6KC92A0g9wEfqGLbaor95jcQgf2nlG/Q/UnEC3UHouC+E7EOBbhFy8ggfR/woSre+yFEIfbZIndHLIOb3d/7iAhOyMTnQ56jexPe6ga16Eb28xqqNsP6tCGCdz+RlN3uveuQ8J0mxIhwKCLsVmWvrxmUteIagtg1ZxKGNj/B9d/73N/fESp5Swkzmvqx6331qNcM6t2/s/aBeJS80HIRovj9EfH+302YTS2RnhBEoLkeCUn0SvmbcXuOuuN2ZE3SNkLBxif5uRCZc+bVKBG/X66/nOfK6Q1N/a7PB8DX3LkmxKNajLTH6DrsZ81jGb0H8PmuTV+BROz8kHBpQocrd4kwS7Xf7LkPEeg/HCnjRUho8PB8lXMe63s4YiDc5NrCP1w7SUzilEZ5MVVY3+7u93sQr1gGMcx2Id6n+4jtt0adlVvXZ+9GIliiodcvdmPMYYRGxePcuBmNWGtGZNxfIN6+vSPvVS0hnhvXXkm4B+9xiDNmOZEkisgyh6Wuj3/JjUM/c/3jE4QGtPMQ2WkUkUcewoVa1vh5dBHuRbgJyXoczauxDjFGX+fu+8sQ2e9BxBFR80zUO61TvQswjw/n+cRCPZDwm/91D+IPiCAV7QQfQdzLPhGK3zrgG5GG/Cx37qg6129KiAVhSvTfUJ40ZC93/thIPf4LmXSucoPg1xFL9VeZZ4vuDOpyFpIR7yzCcMJeZJCejOOODFKvRixD/toTEYX+lfF75P4eQg3S3RMKIqtdO9uIS6AQKUsHonw9OvbZPxJmUGsmstH3PJQr3k58WS53/WANssD6Ctz+V8hahyzlE8ih/plEzvm05i+M/069X4RC4PcRb0JNM2rt6HkwNSwpLqD7tvQSJMz8w8jkeCIi/L6UMNTtWcg6l98TC3dLwguZKH/AVC/ScYg19KDIOe/tfwUi7LzKHR+GCBD/G7mmnntQTWd9fzqy0N8LYhe7fvQgEqbklcINiGfzutjnO5nH5E4V2tWBkf9PjPT3dyBK3s8Rr/kY4ZY0KxAl6qFa9CHE+PEg4hk7GRHO/x65d8uReetfTN0G4S7gU/VqF3Os7/6I4eCJsfOJTtiUpheVhXUvP/QgUTfbkLlwT2IZGutc9oMQb9cyREbKIE6LPZHQ7QcR+Wcj8PrI596GGHnja8f9msj3UhtD/16IUexSYlnz3fteHmlCFKWfIQqSN/Z9DlH2vMHHuD7zWsSQVrMtTyqU/RjEmP+ZaF0i778AMZL7vRT7qeK+zbtcn3oXYB4eSLSj34Ks74l6Z76OWBf2QVy2b0KE8hWIwPHeyLXNbrAo4DaWRBYRVz0j0k7qGF0wPkj5AtR9EGXiJsLNY9e74zfHvuep7n5cgXhxqmJFQTxiwxU6x26IEj6CeGgK7q9PLPJ5RHBfSrlX7w1ImIz3zLZQpzC+SJnOQaxbfgsEvznyVe54uoyO3Ygg9k9iMfHzWLbWSmVAhNNtiIfpYsL9ES9GFOzbKc8M24msq9mICw91519KlbaimENdo+3EuAH6ViIZ3JLwokJYUoVrFiHRCh/EWXyRSIWNiNX6wMi1ibj/09SjmTBh01PcuR8jitFDro2dQ7gGedCNYd8EeiLf83dECfRKYb3WWkfnk0HK118ucedWu+f7AOJ1eDoijH0pcu0LEGX+NTUo8wsQj8cvcBluCQWv1yNr5Xw6+CNwY3Lk8yciCmLVDAyEBr4hN/74zLXPdePj3YTZfk9y13yJMBTsTNc3zqh3m59NfSucr3siqkZ8MVVYj8pRByKKlU8i9B7EmNBfx/IegMhDt7py/w9i/LgWMai9FIni2h1RDr/trvXz9b5IBNJfCSO99nbj6o+RSKq+Kpbf9+cPIwrqish7TZSHoK50556MyNynEq5190agrxKJNErCi3APzC2ES2ZaInXvR9Yy3kLMo5zEV90LMA8PxFvX70MsI9+NTrCEewQ1I1bNW5FQjNWIQHJ25NpzEcXpJpwgX4/6THN+CFHe/oQIGq/EJRNBJvAfImtQfGz7DYRppVtj31WV7QSQSfkzSKzzfUioY3TQfb8r+8GIx+8QRHm/izCkb4v7Dr/f2aAb6CouVKaKVlPCMK1K+9S8ExFQ/P5y7YRZVKd4eRDDxEvcNSOu3gPzXN4hZDHyNyu1KcRLvhF4GqKI9rjB6kFkjcBeiMD4r8hn1yMD9BXVvNe7WO/1rg+8GonB/zFVSAc9D+V8tnv2XvCOe2v2cu3nZZFzx7j+ESDrPGoebjvLOnov7Cpk3cZNiPfrciRB035IuPQ9uEyxru88Qrk1+3g3hvwVUQ576lUX9/8eiEB2HWL4WRm79q2IwnpI5NyNiAfdKzHrkaRFJ1SxzEOurz6EJKN6KmFYdxPhfn9fpVyRvc21sQvdcS9VTEQT+V2DGHGvBX7mzjUjRsCbXX8517WRD7ky3oPM8xOuHok1huirfi/KhfXd3Tk/Pp3i2o/3MlVNMZpBOQ1ihB11Y8sTEHlhNWKEPd61+824vSHd5w5EogquJkxeeBZieLodMd7+3o29NZs3EBnkq+7/uOy5ryvzXxCv3rOAIHbNR12/z+DC0JP0QhTwvwM/iJ33BraDmKfN56tel3oXYJ4eyDJkMfvtSFKBCcRa0o2EHd2EWBxWI8Lsp9znrkQ09ZcjFsZfIJsq71WnerwKsc76zhwNabzddeY3IS7zR4Bfxj5/JTKRX4CEJd1Uw7JfjHhYf4vE1r8e8Yr1uAFuKWLV+mDsc99wg9tp7vg5iNB0qxsIrkK8VpPhAFWux0oqZBMk3K/LP5N+9xx+Q7jH1LGIsPq9yOe88vUKN2hcg/OKVKHsTYjQl0MSK+zvznuP4GL33jnu+BxEmDqBMMzuU5QLgm3umZxajz4xgzqvd+3leiQhxCvrXaYdlLULmeDvIrTQRr1LaxHjyY8RZXCVex6vQxbs132j+lnW9wmI8LWNcuWuy/Xv7xFaUT+FeM+ej6T//4pry4+lviE/TUjEyJ/cc/m4q8/vcXv1IfPMP4GvxD77G9e/bqQKXh4qhKUiwuK/kOQWldaaDjFV2X6SK/8fkLmyph4pJAzse+63ByL1eAgRegvIHP0URHD8IxL5cnC927i+kv0iFNa/Hzv3dURxqmt0lyvPPkho5xunG+uQXAIBMdkBkSvuwDk9EEPJEYjc9FfEY14z45kb239CxIFCKANd5OrwKyQS4q2It8/vO7yHG7euQrz887beuAr1vAhR2P2a7lR68etegHl8IGe7yeIZiBXkr65RGST7n39Q70a8IE9GwkD/7ibEMcRyWk9h47OIMHtQ7PzbEAVwfeTcOYgHM+rtXAm8xXUyX6+qxx+7e38z4pUcrNQZXNnGCRM+nOfKdzsS8hMVhJ+EhIP+HFnPVfXskogQ9wlXj0coz/x6MiKE7OeOvRL4bETYioYRX4ZY4M52x1Ere8W9zapQl3MQYfrPlKdVX4pLsOGOP0ksqx8i4G52bSgdViwJHzmDhHvHXFmPRjxb73PHzZSHsV6IeJYfRJSHu4Gj613uCvXYFzHerIudP8T12fVISOv7Kd+01xu3zkcE/Fe44yFEuN/ixom/1qLfu9/e3Y+5sXFod8QS/SVEQfVGoL3cGPHRyLnvI16sQUSheSIiYH4QUWTbmSfjFVM9x9EMqu9xfXwIUV77kfH1SYT7R37eta9XI4rWD9zn9o1/dw3uvR9L3+T6xSmIgFhA1gIdjkTubEOMPBeQgHT8+krPi1BYfzqyF+NGZJ4/tM7l8m3/g0jIZHyrhui8sN71gfcR8Xgjzo/L3di5NnK+k3mOMJpFvb6NGJT2j5wziGzu54GPuv5+GjLnBe44jyRjTPRcTrgH5n/qXZZdqke9CzCPD6TLdYTb3cT3RCSr5DcQC+x/u+sMYn3+gXuIbUg65ppsFRArc5m3yQkP97oJuted60QsKj+KfbYbibV+hKlZQC9xHeqPVNnChWSLvNnd5+j6nWbKlZ9OwvDVaxEh722EAtRSpi6K74t9X1W8f8gWDQ8i4V0XIF6Irsj76xHv0lcrfPabiKLlNwDdFwkV+7/IM6x56CSiEN3qyuZD0FqRpBq/cMevR6xvp7j+czgitJ6HKLI91brnC/VFeVhSNJOqcX366e7+v5nIxtBJe7kxM0CUiGg//yDwk8jxYYjH8yvuOBpW+Rs3Hhzijhe7761Zhjf3PM5H5g2/JvEkxPPYjYTWB8T2EiVcM3SWO34sYpC7GQlP3IhYuKsWnoiET/0DMeI83517NGEq9Z+6cXYLosjeiYTpdyNj8MOIwfE31H+d+0mI8Be4MeoEyte6vw24tN7tXl/peyFy3i8ItwSr6r7Acyjfb4Cvu/+nTbrk5uQRYnvtIorVHVSQT+pUn8e5e30hEUWO2B6GiJHnC4js8Vgk1Ds1US7uvr+DhOyBOac61LsA8/xAjsbtqeOOD3KTYwnJgNTjzp/jGui5dSpn3Nt0fOS9F7qJ8ImEFqIfA//n/o+uKzveTfbPdcdR63VNUs4iYY9bKM/sF+3kA4hX8hwkmct2ZF+n4cg1y5A1dZ8kluUtXucqlL/fCRwfRTzCzZV+F1EKS4T7Efpnc5wblD9PGGr5SndPzq5WuWdYt/VIiPO9uEQJ7hk84uvg2uBmRPHbhCjyNd0gfaG9EM/SjbhQYTceHEmYre3l1Wzz81iPD7nxdoM7bkU8ltE1jB1IWH1AmIHSh78egyghH6VK65JnWI+9EW/kl5DwowCnfCORIluA97tj78Hsdn3r+4SetachXqurmYe5hQoeeMI1c59E5o73ujLuQxhq9WxEMPkyYlBYiYSFbSXcemYQMVYlQuBy7f8BV+b+aH3d38T3B30l94XkgngzFeSLOperE1m68/MZXNuDGJ3K8gcg0QUfw+1lmIQX4ZKsSvkQWt3YcyPw2nqXdRfqmEqlr6wO9S7APD+QqHV9L3fuENfx496lc+tUxtPZsbepCfHc/YpwI/czEOXDW8q98rEHEhZwVi3rEKvPiYjCenC0bO7/tyJrzgLEO3s6YlG/GxGCd0e8Tt92g0VVsmLupPx+I1jvJasYy41Yzn+FrJPpolzJ/Suy9vJcd7yo3oIV5etHv42EOJ+PeA0eJswMeCCyjuCbwPPqWeaF9CIMS3ohoWHkX7gQmTS8EI/dRiQ8shPx9o0Sy9zm+vmfgN9GznnB/nJkY+a6hfw4geSPSNbLa5EkVd6YM4iERW8nXJ/m3zsfiTJ55TyWxd+Xd7lx82JcGDfhOt09XFs5K/bZHe2zuh8SUvyy+SprFZ7DPcAno/dBX/qaj1eS2xOi0N1CbBuzyPu+3zcjXqc8suzBxK9JygvZXmMrst3UoZHzPYix5yokUspnIk/s82nkV90LMO8VChf9/jByLmp9qFsmQ2bubTrOTf5+4/qVSEjPHwm3HWhCLL2PEAsJqHGdvIX8hbHzRyFJUp6NWKGLSGr4PZCwr4eR8CWvDNdlrxTEErUZt0bUPwtkzcyxRPZ/RJTFHC5Bijt3OBJ+cT8SVlzzbIUzqGMz4d54NyBbDSTGWrgQX4iR4Oeun4+R7HBPExcwCA0MFyLZ2o5CEm/9osI1fqwqEmYp9p60mip+VN5PdXckyuIeYom13PuHIIre59xxNIz1z4gBaN08l/MLrm3cjhjNor95NjLHHYqkIB9CwqfOJbJViLt2OaKYf9v1+/XzWc55rvN3gTvrXQ596auWLzd2loVMxscod+6VwKOQkNF/EYmiSuIL2ablz4gi+CVk3+2vI1FrVxJb86iv2r+8tbGhMMZchMRLP8ta+3NjTIu1tmiMMbaOFTbGPB5RAE+31v6PL9c0134TmeCfaK290xhzMNLx/4Eogw8g1uE/IGnlx2pSicplfQDJbvkKa+0j7lwrIuSNueMfIckTTkGUv32QrKxbrLVXu2uaAFvrZ2SMuRbxYPwSERDPRISqdnfJR5Dspf8xxnwE2WPrvYi34LnIM7kZ2fh6ay3LvjOMMU3W2sAYM4R4m96EWOHebK19d31Lt7AxxjwT6RMfsNZm610egPgYaYxpttaW3P89iNfvbn+NMaYNSc6xCdk6wO/9NxL73pWIJ+1ka207dcD3Bff/nsj673uttdtc3Z6IeCTPsNZ+P9J3OoD/QhIwHGSt/bsxpt1amzPGPAZRdK+fpzIaa601xjwf2aD9p8iamj8Cb7fW/sUYsxqxnjcjiRMOAyyiiPciiRV+g9zv/ZANpO9GjHT/nI9yVgNjzFuQMfctIBNBfUukKLXBGPMTZC44z1r7f7FxtwmRMy5FQlmbkCiLb9etwDPEjVUXIOH+I0gk26estb+qa8EUgIZVABchaaV3t9aurnd5PMaYfZHkIGdZa3/hzjUjC+AzQNFa+3t33m/m/mHgndbajDHmOKQzPRoJW/qOtfbNNa7GFIwxr0SEo3OQdU1BXLk1xrwE8XweY629rsJ3TA54tcYYsxQR/I5C1gLdiCh01yNev+ch60rf5a7/CeIV6EZi8p9lrb21DkWfNcaYCxBL4gvmS2hV5ka9DVKViBjLJpUld/4yxDASIH3kc14AMcY8ATFsbUMm+T4kC9zPgZ86paUJEQJOQELDq2roMcZ0WmszFc4PIOv0TkQ8rwUkadaPEIXwm0hUwKOttRORz+2ObE2BtfZx1Sp35PfORMb+tyJK3vcQb+ALrLV/NsYciazrW4dEVPwS8Qb+DtnQ/cXO4Hg6sofq/1S7zLtKvM0pykLBGLMW8er/FVkX9yd3vhNxBFyG9P8LrbWFepVzV5huTFbqR0MqgADGmGcgSWCqLmzMhhl4mz4MfMxae5cx5h2I5fkJfkBw37EMGKun1y+KE+7+glihL4lad9x7hyCep38Bb6iXorcjnCdjD0TYarXWboq8dx2SPex0a+12Y0wXkrhmpbX2/+pSYEWZR5wA8kXgOmvtmyKeqH0QT9IawqQvRyGJah7tDR/GmK8h4+0LkTWyZyGGrcWIcesca+3PalSXlyIJWS6KerxcH/8mst/iGxBP+JORqIQ3WGu/Zox5LJIx8F3W2vfEvvcFSGjmgdbam6pUdn/fh5Cw07dYa/+fMea5yD5h3cBL4wqdMcYg88hVwDXW2kuqUT5FUaqDMeZZwGsRj/33kaUpw8i6/auAF/sIqzShhp3k0sgKYOKs6zBjb9O7rbXvNMZ0I+s2bkbCPLfUpdAzwBhzEGKlbkWUvdsRQfBxiBL7FyQBwZ31KuNsiXhDvg8cgGwVUkhq25oJaS67Uj2MMYuRTLZrgWdYa//tjDenI2PSxS4UfV9kPcehyNq0s6y1eWPM3shY9V5r7WXuO7uRNStD1trf1KAOS4GvIl6xl1hrfx17/0gkpPJFyLY6eXf+TsTAcxZipHo3EmnxVMQg9CJEqfqZMWaJtXZjlethCI2E2621T3SRIj4R1XLgjdbaz7jr1yDb6LwYmUOeUynKQlGUZONC5S9A8g9sQ4zqH7fW/rKuBVMakoZVAJPMDLxNE8g6mgljzAsR9//h1tr761HemWKMORxR9k5AEt7chljZ32et/Vw9yzZTogqSE8SOBj6LeGU/UdfCKUoViHidTkO2Y/m9tfYl7r11yLqyfyAewJciBqw/IhmXz7TWXuGufbd7/xRr7bW1NjYYY4Zduf7XWvtypxgti4RTnYokQ+l29T0S+ACSCffNwGetteORNXbDuL2rXD2vrmFdWl1Z9wSOttaOGmOORzIGtiDj60VIuOpuiPf1YUTx/VOFr1QUJUUYY7qiYeiKMt+oApgQpvM21btcc8EYsxdiwe6x1v4ucr5u6/xmg1t/uQTxXr4C8dK+zFp7X10LpijzgDMq/dMpac1A4BSiDuD9SFjki621v46MSxchHqa3IZ7+5cgav61IYpfNbu317ci2CF+vch3iyWp8wpbvAqsQ790fkM3Pn+lCty8AXge8HkmnfiaiZF1mrb3NKV1d1tqtxhj/HWPW2q9Vsy4V6ubr8iZEoX4xkvDrGGSfvM+7809wH/kY8A9r7Y9rWU5FUeYfDZlUaoUqgHWk0bxN01n806L4waTydyNwK5Kq/6PW2o/Ut1SKMj8YyX75QyBjrX2MO9eMbPOQd8abHwK3Wmuf5t734Ygj1tqnRL7reuAxyDo1nyBpwFo7WoN6tLpw7HiymouBtyMhkS9H9ln9mLX208aYJUhUQh+SnvxVwB+stSXn9Xs9UvdfJiFM2hhzEhKy2oIo2/+NeGez7v23AwVr7TvqV0pFURQljTTVuwALGWd1X2+MOQKx8H4NEVB+VN+SzY3phKa0KH8Abo3i2UhW031U+VMaCWvtbUjo5lrnCcRaW4qs4/sssi/eY40x57mP9SHZMh/232OM8WtU/hc4yyVGotrKnzFmyBhzDWFGTr+tg3GXbEIylR6IJGzZBDzDGLOHW7v3fmQvzy+76IQWFyp6IZJVs5QE5c8xjpT/q0gI6q+stdlIXd+myp+iKIoyF1QBrCMRb9PHgJche82dqqGG9cVa+2Nr7RU+SYSiNBg/Q5KJvMmfMMZ8Adm64WFkH7k/Ay82xgxZax92x8caY77kstVdimyc/mxr7QE1XKsyguw5+gxjzBeMMfu78y3u71VIRuU9rLWbkY2H1yBb1GBl78urgIuNMf+H7LX3ayQc9NJ44ph6Yq29FlG8J1xYqnHnrfubGsOaoiiKkiw0BLTOuMQEbcCPVeFQFKUWGGNOR7Z3uBPxlt2NbDPwC+cNfAESEnmFlW0hBpFkVKci63t/B1xgYxu+1wpjzDmIl/5B4FSfIMtlAr0SuMtae6ZTmq5A1gVeYmWT5WFk8/RTkG0V/mGt/e961GNnuDWNh1hr19e7LIqiKErjoAqgoijKAsPIhuhvQbL2/reN7P0Xef8jyBq/Z1trb3JJUpYimYvvqk/JQ4wxZyBZS8eRdYj/48p4JZK582xr7SZjzAlIlMXVwMsrJY+pfelnhjHmLYhH8y0wfZi9oiiKoswGDQFVFEVZYLi1ej8EbgH2due88tfk3v8Woki9071fsNbelwTlD8BtP3Eyst/op40xZ7jMydcgXs0xd92vkM3dnww8J/YdiVX+HO+y1r7ZOupdGEVRFKUxUAVQURRlYfIH4BvAScaYJ8Jkxt4AwFr7v8h6uapv4j4XnKJ6J7K+71rgy8aY84F/I4rrYyOXfw7Z5P2emhd0F0iBgqooiqKkEA0BVRRFWaAYY/YBPgosimwLYZC5IfD7ANa1kDPAbWVxObKH6lYkKcwnrLWfq/WG9IqiKIqSdNQDqCiKskCx1t6CZMpcaYx5tTttIl7ANCh/TS4j5gXIJul7AhuAxaDr5hRFURQljnoAFUVRFjDGmBXI/n/rgIPcOrrUYoy5AHgl8AJr7fX1Lo+iKIqiJA1VABVFURY4LhT037oVjaIoiqI0PqoAKoqiKA2DrvlTFEVRlB2jCqCiKIqiKIqiKMoCQZPAKIqiKIqiKIqiLBBUAVQURVEURVEURVkgqAKoKIqiKIqiKIqyQFAFUFEURVEURVEUZYGgCqCiKIqiKIqiKMoCQRVARVEUpWEwxnzZGHNDvcuhKIqiKElFFUBFURRFURRFUZQFgiqAiqIoiqIoiqIoCwRVABVFUZSGxBiz3BjzRWPMncaYjDHmNmPMO40xbZFrdjPGWGPMs4wxnzHGbDXG3GeMeZsxpin2fc80xtzuvus3xphHu8+eG7nGGmMujH3uMmPMptmUy123xhhzlbvmLmPMucaYK4wxV8eu298Y81NjzHb3utwYs2x+7qKiKIrSaLTUuwCKoiiKUiWGgS3AxcAIsCdwGbAYeHHs2vcD3wPOAE4ALgX+AXwXwBhzCPBt4Argv4B9gO9Uq1zGGAP8GBgAzgOywFvcNf/2X2SM2R34PXAD8FxkXn8HcKUx5jBrrZ1jGRVFUZQGRRVARVEUpSGx1t4EXOKPjTG/B8aBLxpj/stam49c/ltr7avd/78wxjwJeDpOAQReB9wCnOWUqv81xrQC76tSuU4GDgQOs9Ze7677E3A3EQUQe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Unique keywords\n","\n","fig, ax = plt.subplots(figsize=(15,10))\n","sns.violinplot(x=\"language\",y=\"wl\",data=main_data_lang.loc[main_data_lang['language'].isin(low_lang),:],bw=1, ax=ax)\n","ax.axhline(3)\n","ax.tick_params(axis='x', rotation=30)"],"outputs":[{"output_type":"display_data","data":{"text/plain":["
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"},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":43,"source":["## Unique keywords\n","\n","fig, ax = plt.subplots(figsize=(15,10))\n","sns.violinplot(x=\"language\",y=\"wl\",data=main_data_lang.loc[main_data_lang['language'].isin(low_lang),:],bw=1, ax=ax)\n","ax.axhline(3, c='red',ls=':')\n","ax.tick_params(axis='x', rotation=30)"],"outputs":[{"output_type":"display_data","data":{"text/plain":["
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"},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":44,"source":["## Unique keywords\n","\n","fig, ax = plt.subplots(figsize=(15,10))\n","sns.violinplot(x=\"language\",y=\"wl\",data=main_data_lang.loc[main_data_lang['language'].isin(low_lang),:],bw=1, ax=ax)\n","ax.axhline(3, c='red',ls='-')\n","ax.tick_params(axis='x', rotation=30)"],"outputs":[{"output_type":"display_data","data":{"text/plain":["
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XDpAlAI8agQ4qeEEF8WQiRCiE+OueZlIYQc+XP3stu66Ji82F00B5CDMjkvnn766aqbQAghY+FcVy3MASQKp4L/8xsAvAvAZwC4U677dwD++cDX4UU2ipjFojmAizAY8z0QQggh+sIcQKKoQgD+ipTywwAghPgAgGsTrrsjpfzM5TWrHIuwUDT5PfAcQP1YhAllEd4DIYToyiLMdSbDz58oLj0EVEppfrwezF4omtx2Bc8BJIQQQsyCc121MASUKHQuAvN/E0KEQogjIcQHhBAPVd0gog/MAdSPRXgPhBBCyKKzCEYAORtVhIAW4cPIcgRfA/B1AH4UwG8LIb5JSnk0erEQ4vsBfD8APPjgg5fZTlIRi5YDuAgswoRCEUsIIRcHx9hq4edPFFo6gFLKvyml/AUp5W9LKd8L4E8DeB2Avzrh+vdKKd8hpXzH9evXL7WtpBoWTQAugou5CCyCiCWEEF2hAKkWfv5EoaUAHEVK+SSAZwD8warbomAnqpZFE4CL8DwtwnsghBBCFhXO00RhhADsIXt/tICdqFooAPVjEdyzRbgPhBCiKxxjq4WfP1EYIQCFEN8I4O0Afr/qtijYiapl0QQgQ0D1YBFELCGE6ArXTtXCz58oLr0IjBCijuwgeAB4PYBVIcT39L7+NQB/HMBfAfCrAG4jE34/DOAVAD97qY0dA0vo6sGg6IvjuMKWnA8mP08mt50QQsjlwfmiWvj5E0UVVUDvA/D+ke+pr98E4NXeNf8MwDqAPQCPA/gHUsrjy2nibEzuRCa3XbFoDuAi3JNFgPeBEELIomP6XLe/vw/LsrC+vl51U4zl0gWglPJlALPirP7kJTTlTJjeeQCzw914EDy5CEzuE4QQojuLMNeZPE+o9ZLJ7wEA3vPX3oOlpSX865/511U3xVh0PQdQexZhEDOZRXMATRaxpk8khBBCLodFWDstwnswnYPDAxwcHlTdDKMxogiMjpi8YF8EBvP+mAOoB3wPhBBCpsExtlq4diUKCsCSKLdjEQYxk9/DohWBWYRBeRGcwEV4D4QQoismrzsWARYyJAoKwJKoTmPygn0RFrmLFgLKwZgQQsiiw7muWtTnvwjrQHI2KABLskgOoMnEcQw1fpksxhV8nvSA94EQQsiiwjmOKCgAS0L7XA+SJIFnZwqQIaB6sAh9gruihBBycSzCPGEy/PyJggJwThZhwW4ycRzDXSABuAiDMsUTIYSQaXDtVC3q81+ENQc5GxSAJWEIqB7EcQyvd4jJIuQAmvwe2BcIIYQQ/WEOIFFQAM6JybtYi7BgT5IEzgI5gEQPFqFvEEKIrpi8dloE+PkTBQXgnCxCJzJ5ByiOYzgWIMRiCEA+T3qwCO+BEEJ0hZts1cLPnygoAEvCIjB6EMcxbCFhW8Lo8EnFIghA9glCCCHT4DxRLcwBJAoKwJIskgA0+T0kSQLLAmxL0AGsmEVyzUzuE4QQojscY6uFOYBEQQFYErVQN3nBrjB5AOg7gAwB1YVFmNhN7hOEEKI7ixCxYzKLsNYg5wMFYEkWSQCaTBRFsOkAaoESfpbF4YQQQshiY/JGoclrDXK+cMVWkkUSgCY7NkkcwRaCDqBGmPw8KRbhPRBCiK5wrquWRfj8yflAAViSRcoBNHkXK47jLAdQZG6g6SzCoMw+QQghZBqLME+YDD9/oqAALIlaqDOOvVqiWIWALsa9oACslkXa2CGEEF1ZhPnaZPj5EwUFYElU51mEBbvJxFF2DqBtLYYDyEG5Wij8CCGELDqc64iCArAki+QUmPwe4iTOHEAhF0I8mXwvVNjkImyKMASUEEIujkWYJ0ymfw5gxQ0hlUMBWJJFKgJj8mI3jmJYwmwHcFD0LcLzZLKIXYTPnxBCdMfkeWIR4FxHFBSAJWEOoB7EcQzHFrCFNLYK6OBAvAiDsskT+yI5+4QQoiuLMNeZvHm+CJ8/OR8oAEuySDmAJi924zjOi8CY6gAOPkOLsKFg8vOk7oXJEzshhOjOIqydTKb/+Zs7X5PzgQKwJAwB1YMojuEIwLEE4iisujlzMSj6FuF5MlkAmtx2QggxhUUYa01+D4uw1iDnAwVgSRbJATSVNE2RJCkdQE1YhPBJ9mdCCLk41PTAsbZa+PkTBQVgSRbJATR1wa5y/hwbcCgAtcHU5wkYrIxm7nsghBDdWYS5zmT4+RMFBWBJ0gVyAE0NAVWCTzmAphaBYQioPqi2m9onCCHEBBZhrjOZ/PM3d7om5wQFYEnUop27KNWRO4CWMDoEdPAZWoTnyWQByEUJIYRcPCbPE4vAIqw1yPlAAViSRToGwtSBeNABXJQQ0EUQIKY+T0C/P5v8Hgghi8kzzzyDJ598supmnJFsbF2Euc5k8s+fwS5XHqfqBpgGi8BUz3AIqEC0ACGgi7ChYHKf4DEQhBBd+Rt/428AAD760Y9W3JKzswhzncnw8ycKOoAlSRPzHUDTF7lKADo9B3ARcgBNfp4UJrtnJotXQggxBY611cLPnygoAEvCHMDqGRSAtg0kSWrkoEYBqA+sAkoIIRfPIsx1JrMInz/n6fOBArAkiyAATe88ozmAgJkuIKuA6sMihICa/PkTQq4GizDXmYzJa1cF57rzgQKwJEnaE4AGCg6F6Z0ndwDtrAro4PdMYnAgNlHAjmLyxG5y2xWm92tCyOKzCGOtySxCHQvOdecDBWBJVOdZhAW7qQznAGaOTRiGVTZpLhbFAVSumcnvYRGqgJrcdkLI1WARHCiTUfN0mqbGzhkmrzV0ggKwJEr4mTyImdrpFUMC0B7+nkksigOonieTnyt1LxgCSgghF4fJa6dFYBHWHZzrzgcKwJIsQhVQ1XlMXeyOywE0XQCa/DwpTN6VW4QiMCZ//oSQxUYNrRynqmVQ9Jl6L0yep3WCArAkcdJzAGNzF+ymd55+DmBfAJoYAjo4EJssABcpBNRkTO/XhJDFRe03mzxPLAKD6w5THUA+Q+cDBWBJknRxHEBTF4xK7DmWMDoEdBEG4kFMfZ6AxagCykmREKIran4wee20CCxC5JHJaw2doAAsiar+qZxAkzF1sTuuCIyJAnBwwW7qQAyYv6EAsAgMIYRcFFJKFtDThEXLAeS8Nz8UgCVI0xRp72EzteMA5jsFuQNo94vAmB4CavLzpDD5uWJpbEIIuRgWZbNzEViE1JPB54nz3vxQAJZgETrOIKZ2HOX2uTbgGlwEZtGeJ5PFU3932rznSLEIzxAhZPFYhLDDRYEOIFFQAJZgEToOYH4VUOX22Rbyg+BNdAAX5XlSmCwA1edv8n3gREgI0REKQH1YhI1nOoDnAwVgCZTLZAlh9ELR5IU6kIk92xKwhIC7AEVgLMvcgXgQkwfi3AE0+D6Y3q8JIYvJoglAk+e6RUg9Gfz8Oe/NDwVgCdTA5dmO0QtF04t2hGEIx87cS/W3iQ6gGnxd29yBGOg7ySZP7ItQoMDU/kwIWWwWQXQAi5ErvghinHPd+UABWAI1cAWOgyRJjH0ITQ8BjaIIrhKABoeA5gLQMdtRVpg8KarPPzH4Ppj8+RNCFpdFEB1Af4w1eawdjJYyMXIKGBaAJj9PVUMBWIJcANoOpJTGDgKmCldFFEW58FNVQLvdbnUNmhP1PDmGO4AKU/sDsBg5gCZ//oSQxWVRHMBFEICLcC9MX8PqAgVgCdRuie84Q1+bxmKEgGb/NrkKqNq5ch1p7EAMLMakuAghoNwJJYToyCIUHgEWY66Loxiu7QEwc90EDH/+Jt+LqqEALEE/BNQd+to0TA8B7Xa7ufCzDRaA+XEWjpntVyzCpKg+/zgxs08DZn/+hJDFZVEqXi/EXBfH8G0fgLlinEVgzgcKwBKogct0B9D0DhOGIRyrL2JdWyxADqCZzxKwWInxSWzmhAiY/fkTQhaXRQg7BBZjroujCL4TAFiMNaypkWw6QAFYAtVZagviAJraccIwxFE7xUe+1BdQpgpAS2QuZmRg+xVp2hNPhu4mAv2+beqECJi9KCGELC6LIgDVGGvyXBfHMXw7yP9NquMLX/gC3vve91b2/1MAlkAtDlUIqKmLRTWImRoCGna7iBLgzlH2PhxLGFkEJooiWLaAbZk9EOfumeGTImD2e6AAJGSxMXXTdlEE4CLMdVEUw3f83r/NXsOO/ts0/tE/+kf4wAc+UNn/TwFYglEH0NTOY+okogjDLga1q2ObewyEYwnYdhaXbyoLkRehcgBjc493MfnzJ4TMxtQ+rkSfEBaiiHNdlURRhMCpATBbjCtMna8BoNVqVfr/UwCWYPAcwMGvTcPkwQvIisAMepeuoQIwiiLYNmBZ5m4mAIuRFzH4+Zvar03elSaEzMbUxW5+5JEbLMRcZ/JYG0Uhgl4OoInrJoA5gOcFBWAJRkNATe88pnacMAyHHUBLGnkv4jiGZakQUE6KVRJF/eeHApAQoiOmbrKptZPj+kZXWl6IuS6O4fccQFPF+ODa1dR1rA5QAJZAiYy6a/YZKqYfAzEqAF3LzIPgwzCEbfWKwDAsplLCgb5sar82+fMnhMzGVOHRF4ABYoPnukWIdomjKHcATZ3rKADPBwrAEqjOUnfNdgBNnUQU3TAcCgF1bGmkAIzjGLYlWQRGA+IFEIAmf/6EkMVlKAR0AeY6U+frJEmQyhQ1tw7A3Llu0QRgVe+BArAEi1YExtSOE4YRrCEHUCAMzROAURRlDqBttgO4CAIwogAkhGjIIhx6vSg5gKZXi1amhW/7EBDG3gsKwPOBArAEqvPUDA8BNfkYiDiOkabpqSqg3W6nukbNSRRFsCwJ2xKQUho7qSyKAHS8/r9NxOTPnxAynkUQgHkIqFcbirYwDdMdwPw+2C5c2zU2io0C8HygACyB6jxLCyIATUSFeg7lANpA2DVvIMscwCwEFDA/pNhkARJFEeyeADT1PgwuShZhUiSELMaZZ2qt5LoBC55VSC4ALReO7Rq7hl00AVgVFIAlCHu5Z+oYCFMXimrwMrHjqM989BiIroH3IisCk50DCJi7oWD6pAhkIbjOAglAk+8FIaTPIghANaY6bs3YeQ4wf65T98HtCUBT57pBTFzHjkIH0ADCMITrOPDsTACaOpCZHAI63gEUhjqAIWwbuQNo6vNk+qSYJAmSJIHjZ1+bfh8Ac0OUCCHDLIIAHAoBjWNjF+1qXDV1fM0FoO3CtegA6kJV/ZoCsARhGMK1bLiWnX9tIqZOIkD/M7dGjoEII/PuRdjt5sdAAOY+T6YLwHx32nAHcPDzN/VeEEKGWYRDrwdDQAe/Ng3TBeBgCKhrmesALkKf0AEKwBKEYQjXtuH2YvZMPHoAMPsg+NwBHPieYwNJkho3KA9WAVVfm0iSpL2/zRQd/d3p7GtT+/Xg829aXyCEjGdRisBYtgPbMbt+gjrD0NSq3YMOoGO5xs51iwYdQAPodrvwbBu2EBBCGL97YmIIaJ4DONB2L4vINW4wi6IIjp0JWPW1aQxWLzVVdKjnxu2FgJrarxkCSsjisQjOfhiGsG0Xlm32Gcr5MRCGjq/5XGd7cFkERhuYA2gAKgRUCAHPdowTHApTJxFgQg5gLx7UtEkljEI4dt8BNK39wPDOlanV3fIQUMMF4OBkTgFIyGKwKA6g7biwbbPPUFaH2Jt6mP1gERjXYAdw0QRgVVAAliAMQ3i91bpn28YuFBchBHQoB7DnAHY6Zp0FGIYRbBtwDC4Cswhhh+qZYggoIUQ3TBV9g2Rn3jqwbMMrqKscQONDQD24lmdk8Txg8QQgQ0ANoNvtwusVgPEd8x1A8wJAx+cAuoY6aFEU9xxAMx1MYDFERx4WEwx/bRqLcC8GWYSFLyFnZbAfmBq9E4YhbMczPgdQOX9xYub4ms91lgvX9oyd6xYNhoAaQNjt5gVgXIMdQFMnEWDyQfCDPzOBOI6RpilsS+Q5gCa1XzGcd2bmpJ47gP7w16YxuKgydYE1yCLs7BJyVhYhBFTlANoLkgNo6gbbkANoe8beBzqA5wMFYAm63S78XgiDZ9nGLhQXQQBaI+cADv7MBPK8s4EiMCYOxsN5Z2Y+V+q5sV3Assx6jgYZXJRQABKyGCxCyfswDGENFIExdYxV46rpm52e7cGzFyMHcBGo6v04lfyvhtLtdOHZWQjDIghAEzvRojiASuy9dDvF3rG5IaCL5ADaDmC7llHP0SCL5gCa6nYQcp4swkHwYRii1TjAi1/9zfxrE1FznKnj61AVUMtcB3AQE9exo1TVrykAS9DpduCv1AEAvu0YV3RE0XcKzOs44wSgZ7AAbHaAJM3ug0ntV6iJ0LbNdQBVP7bcTASaeB+AxROAizCxE3JWFiHcrdsNkcQhmsf3AJgpAKWUQyGgUkrjjtIarALqLUgOoKl9YhAtBaAQol7ml0kpW2drjt6MVgE9MrTzKNcmTczbTex2u3AsMbYIjEmCfHDgVXOIiZOimhAd11zRoZ4b2wEsx6znaJBFOwbCVLeDkPNkERzAbrcLIQSEsPKvTUONr54TIIw7iOMYrutW3KpydLtdeI7fO8rMR5zESJIEtjqLyhAWQfQNomsIaAPlbCKznqKSZAfB93IAbQedtpkLxfzgbgMrWXW7XbiOwOBj6RpYRbN/oH2/oqmJk2IuAB1zS2MvogA0qS9MwtTFLiHnySIUgemGXUCI3DEzcXzKBaCbCcAoiswUgL00Jrf3d7fbRb1eyuupnEVwxQfR0gEE8H0wMU7wAkiSBGEUwXeyj8x3HHROjitu1Xz0wxjMC9nLdrBGBWD2t0kL96FQVpEVtTF5UnRdoNM273kCBkJAHcCyU7Tb7YpbNB+Dz4+pbuwgizCxE3JWFqMITJS5fwsgAH2vjkb70MgxVjmAAHIhaLoAXASqKsw4VQBKKX9W/VsI8T8A+G0An5JSNi64XdqhFuyqCqhvm18ExsQwsU6nkws+hdd7ik26H6O5jI4jjGq/Qk2CjpM9V2mawrLMKi7c6XRgOwJCALYr0emYKQCjKAJcAUTSyAXWKKa6HYScJ4vgdoQLFALquzUAZorYTqcD18pcS8/28++ZjKl9YhATjoH4cwAeA3AghPicEOInhBD/FyHE9Qtqm1aoTtIXgOYXgTHxOIgwDE8JQMfq/8wURg+0d2xhVPsVgw4gYO6mgu1md8JygFbbzFTmKIogPHN32EehACRkkXIArTwE1EQBqMZU36sPfW0SnU4nF36e03cATWMRRN8g2gtAKeU3A7gG4C8A+E0AfwTALwK4K4T4mhDipy+miXqQO4B5CKiLOEmMXPDmIaCm5gBaw51fCAHPEUYJcjV5qPMMXcMdQCUATQyLyQRg9m/bNXdHNAxDSD97oEy8D6OYutgl5Dwx3QGUUiIMuz3xJ2AZeoRWLgBdwwWg1TvKjA6gNmgvAAFASnkgpfyIlPLvAPjPAfx5ZGGhb0WWL7iwqE7iDTiAg983CZNzANvtNlz7dId3DROAqq15CKht5k7cYAjo4Ncm0Wq1hgRgu2VmCGi32wV8OoCELBKmC8AoirJ298I/bcfM4wfU3Bb4S0Nfm0SnPeAAGiwATewH09C1CEyOEGIVwB8F8O29P+9AViX0CQB/B5kQXFhUYYhgoAgMkHWe5eXlyto1D0oASimNKwHc7bTh2gJhPDwAeLZZDtqpHEBbGtV+Re4AesNfm0S73YZlpwAEbAdoGzghAkCn2wU8c0OsRqEAJMT8IjD9zc5sbHIcz0jRoTbVAm9p6GuT6HQ6WLdXAAC+wQJwEBP7xChaFoEZYR9AF8CHAfwcgL8mpXzqQlqlIaqTBD3nL3DMdQBHzwszSQB2uh1s2EA4Er3qGuagjQpA25JGP0smh4COOoBxZObZSN1uB8IXgGMZuTgZxcQcZULOG9MdwP5c13cATRyf8jSgXg6gSesNRafTgeepHEBzBaDpfWIUE0JAP4tMMP4pAP8FgO8QQnyrUNs6C45yAPMcwJ4QNLFk/GDeomkL9m6ne6oIDAC4tlkC6lQIqKHnz6mJ3HOHvzaJVquZC0DHVd8zrxBMt9sFHAHhmFlQaBQ6gISYv9g9JQBd3+i5ruYvD31tEp1OJ3f+TA4BXTSqqiVSpgjMHwGwDuC/BPBlAH8GWdjngRDi14QQP3QhLdSE3AHsrRAXxQE0TgB2u/DGCUDLrBDKbrcL2+rvnWQOpnmbCaMhoCZOikMOoNf/nml0wxCwAeGaFQ49CTqAhCySAMzmO9v2jRyfVJtVCKiJ76HT6cDvOX8+HUBt0D4HEACklG1kFUB/s5cT+McB/C0A3wngTwP4/5x7CzUhdwDtfhXQwe+bhMkHRnfD8NRB8EBPQBk0kHU6HbgD78N1gGbbnPYrcgfQ8BzAjV77bYMdwLDbzc4BNLSi7CgUgIQML3BNdMVzgZGHgPpGr5tUERjTNjvTNEU37ObOn3ICTbwXiyYAtXcAhRD3CyH+ohDi/yeE+AKAPQAfQOYK/m8A/lLB3/OoEOKnhBBfFkIkQohPjrlGCCH+gRDiVSFEWwjxW0KIbyna1otgsRxAMwWglBLd7ulzAAH0joEwZyDrdrtwnL4D6Ni9Ih6GoSZB19AQUCkl2u3hYyAA8wSglBJRGAGOgHTM3J0GFuPMM0JIHyUwBnMATVw3qTG15q8MfW0K/aPMAgCAY7mwhGXkvaAAPB/KOIC3AYQAPg/g1wH8MIAnpJSHJf/PbwDwLgCfAeBOuObvAfiHyKqLfg3AfwfgY0KIb5RS3i35/50LakGocgCVEDRtoQggWyiqfxskAHO3aZwAtIE9gwayzAHsf+0aumgPwxCWLWA72SBs2nvodDqQUhqfAxhFEdI0hXAAaVg+7CAUgIQMY/pit5/vnglAx/XRbu9U2aS56AvA5aGvTaEfxZY5f0II+G5g5Fxhep8YxYQQ0D8B4Hd7YaBn4VeklB8GACHEB5AdLp8jhAiQCcD/SUr5v/a+92kALwP4QWTC89LJYqddWL049sDgIjBRFMK1BKJUGuXY5GcxOqfrDplWBbTT6QydZ+g6QKfThZQSJtVV6na7cGwB28rei0nPE9AXeir3z9QcwHwSdwWkI4w9ymIw7LOqXVFCdML0xW4uAHs5744b4PjAvPFJvQ9THcB+IcMg/57vBEauYU3vE6NUZcSUKQLzyXMQf5BSzpK6/ymAVQD/x8BrmgB+BcA7z/r/z0u73c7DPgGg1ot5M3H3JAwjLHnZezHJAVQD7vgqoGblPXU6HTgDAtCxRRbGZ9D9AHrFbBygtx9i1D0AgGazCaDv/Dne8PdNIf/cHQG4MCocepBB0UcHkBDzOeUAOj66XfPWTVnhNhuu48G2bOPWfqq9ygFU/zZRAC4aVeW7lzkG4rJ4O4AEwHMj33+697NKaLVaedgnADiWDceyjXMKACAKQ9ScTEWZ5NioAWxsDqDdq4JoCO12G85ICChg3oZCGIZwbEAdmWesABwpAmOaABx0AIUjjJ3UBydCFoEhxHyHY1QAmnoMRLfbhetm7pnrmFfJtJ/GNOAA2nQAdUD7IjCXyAaAhpRydPY/AFAXQngVtAmtVgs1x8X7vvxZvO/LnwWQuYAmCsAwClF3zRWAY3MAHSBJUmPCxjqd9pCQVQLQtMG42+3CsrMiNoBZzxPQF3p3nwNe+Ew/F7DRaFTYqvLkhRZcAbjCyAUWwBBQQkYxfbF72gEMkCSJcdEuWd5+tvx0DRSxao741Cv/ER948ucAmCsAFy1X3IQiMNoihPh+AN8PAA8++OCF/B/tdhuB7eDm0X7+vcBxjew83TDC0op5pYzzENAJOYBANkgvLy9fZrPmot1uY6sGdHofv8kOoG1LY0NAldDrnABRO0uMd31h3MbOoANosgAcnAgpAAkZxkQB2Gq14Dj9fXvH7R8/4LqT6gDqRyYAs7a7trkCcLe5jZPuEQAgcAK0WsdVNouADuAgBwCWhRCjPs8GgJaU8pRikVK+V0r5DinlO65fv34hjWo1m0M5gEB2FIRpC8U0zVyyJQMdQCUuxh4Eb4uha3Sn0+ksRAhop9OBbUtYvZHElM9foRzAwbo7jm9wCKgDwBUIu6GRO6ODEyFDQAlZDAfQ8fphh04vjNLEuc7t5c+5jnkCUK1VLdFf9vtOgHbLPBNjERzAwXZrXwTmEvkaABvAoyPff3vvZ5XQbrXzwi+KwDZPACrBt9RTHCYJwKk5gIYJqE6nk7cZMDcENBOAmYByDHSecgE4MBLarrkhoPAyBzA7M9MsMQ4wBJScL1JKxHHMzYQKyfLd+4VHlAA0be3UbrfhOv0cQNPmatXeUQHYMlAADm6EmCoAB+c3CsA+nwJwDOAvqm8IIeoAvhvAY1U1qtVqouYMC0ATcwCV4FvuqQ+TFom5AzgmcNkzqAhJkiQIw2jIAVRHW5g2qXQ6/WI2jiOM2lAAMqEnrGEH0PZS4wRgPg71QkAB854lgCGg5Hz5oR/6e3jXu96Fd73rXfit3/qtqptzJWm1WrnoA4ZDQE2i0x4IATXw+IRxDmDgBGi3zVrDAsOiz0RXHBgWfVdGAAoh6kKI7xFCfA+A1wO4rr4WQtSllB0A/zOAfyCE+H8IIf4kgPf32vrPL7u9ila7fVoAOi5ahoaKLRkoAPsO4LgcQDF0jc6MO8/Q1BDQbreTVwB1HPPa32g04PrDw6DjAScNs/IihnIAPQpAQgDg2eeeg3Xj9ZAQeOGFF6puzpWk3W7DHhKANQDmzRXtdhteT7x6ro9O27z2u7Y7dM6w7wTohl3jHPJFCAHVQQBWUQTmPmSCbhD19ZuQHfj+PyMTfH8fwBaAzwH4DinlvUtq4xBxHKMbhqi5wwVIa46L1rFZC0Ul+JZ6lplJg/DUHECDipDkQnZBQkCXs3Nx4dhmPU9AJgCdkbrCjgec7JvlAOY5i56AcAUkzAuxAoYnQgpAchaSJEG71YTztj8AcXyIY8Pm6kWh1W73Kn9mfVs5gKaNT612G2trmXj1nBr2j8ya61qtFoKe+FbUnOzrdrttRPE8hel5scBw+tWVqQIqpXwZwGkLZ/gaCeB/7P2pHDVQnQ4B9YwbxJRACmwbnm0bIZgU/Sqgp3/mDVQB1R0l8ryBx8kzVgB28xBQ25ZGfP6DZAJweAJxfODQwBBQ4QgIS0AuiANoWpl4ohcnJyeQUkLU6kBQw9HRUdVNupK0Wm043iqSthKAfdFhEp12G+61Xg6ga17oZHaU2bAADHpft1otowTgIpwXOzi/VZU6o2MOoHYokTdaBbTmOOh0zbLP1QLddyz4jm3Ugr3T6cASwJgI0LwwjAmCVj1PpjuAUsqhXEbbMU8AHh8fwx4VgB7Q7YZGCZB2uw3h9YbzngA0rZIpQAeQnB9K8ImgDunXcEgBWAntkRxA1zOvCIyUEu1OG14vB9B3A7Q7baPcp1arNXQIPAD4AwLQJAbDPk1afw8yKPquTA6giajOUR8JAVVfm7Ro7x+mbsFzLKMW7Nk5PNZQDLtC5dOZ8H76OYD971mWgOMIo56lbrcLKeVAERgYtyt6fHKMgQJ1AIBehJJRhWCazeYpAWjapA4wB5CcH4eHhwAAUatD1Oo4ODiotkFXlOy8v77zZKIDGIYhkiSB7/VCQF3zDrPPzrIecQANvBfAsOhbhBxAOoAao3bS6+7pIjCDPzcBJT4Cx0ZgmyUAu93uUOGUQZQDaEIVyr4DOPxePMMEoGqryQKw0Tg5JQDV1ycnJ5ffoDlptVqQan/KYAE42H9N6MtEX5TgE7UliPoSDg4Oq23QFURKmR0D4fWFh+14EEIYNT6ptnpubehvk95Ds9k85QDWel+btIYFFs8BpADUGNU5aiPVIlRRGJMGAbVo9x0LvoECcNwZgID5OYDZ12ZNiuqzVqmxjgO0Dfj8FWmaotlo5Y6fwkQB2Gg0kLq9cKQFCQE1aXed6Mf+/j4AQNSXIOrLaDUb3FS4ZDqdDqRMhxxAIQRcr27UXNefs80VgK1mCzWnPvS9wNAQ0EVwAAfTlSgANSYvAjPBATSp8+QOoG0jsM0SHN1ud2wFUCCrQKmu0Z18N3GkmI3rSLMdQBdGlcZutVpZCOtIFVDXRAHYbOTCDzYgLEEBSK40+/v7ELYN+DWI+nL+PXJ5qLnO8YadJ9cLjFp7qLb6PeHnGygAm83mqSqgSgCaNlcsQhEYJfoERGXrVgrAAuQO4IgAVCGhJnUetWgPekVg2gYNYJ1OB649PunaEgKuXV1HKoO6B6PVTF1bGjWh5AJwwAHsdLrGJMYrgTcSFWOmA9hsQvTOMxRCQPiWUeOSQoe8CLIY7O3twaovZ/2hJwD39vYqbtXZMGVsVeTpDiPCw/FqRs11owLQSAewfboKaM3NHEHT5opFEID5kWxuQAdQZ/IcwBGrQBWBManztFotCJEVgQkcyygBGIZduNbkCdB1hBEhoOOqgAJZSGirZdazBPTfh+tkCxQT7gHQF3iLEALaajb7DiAAGCoA84nQtugAkjOxs7MDLGWHlFq9v00XgKaRO4D+cOih49aMGp9UW70RB9CU9xCGIeI4zqt+KlROoElCFliMYmFqrlvxauh26ABqS7PZhG1Z8Ozh+MOaoQ5g4DgQQiBwbLQMCjnMHMDJR0h6hjiArVYLriNgWcPvxXV6C3lDGBcCOvh93VEHQ58qAuMBQsCYg6OTJMlCb/2B58kzq4qpQok+y3fpAJIzcW+7LwDF8ioAYHt7u8omzYVprt8gEx1A1ywHUK3xfK8+9Lcpa79+FNvwfbCEBd8JjHkfikUQgGqtuuzV0O1Ws2lOAViAZrOJuuedOn5AOYImdZ5Wq4WgV0ml5tpod8xYrANAt9OZWAQGyCqBmiAA2+02PHfcURZZmIYp5Lu7PeHnGioARx1AIQRc3zJGAObjz4AATH3g2CAHU5GLPs8xoi8TPUnTFLu7O7CW17JveD4szzdSAJqMGptO5wDW0TBo3ZQLQEMdwLyOxUgRGACoGVaQB1isENAVr4YOHUB9aTabp8I/AcCzbdiWWaFW2XvpCUDHRhTFxuy0dzqdU4VTBnEMEYCtVmu8AHSBVssM8QQM5DKOCEBT+sMkBxAA3MCcENDc6RsQgMITODkxQ8AO0u12ISwLcG2GgFbMwcEB/sk/+Sd47bXXqm5KaQ4ODpDEMcRK5vwJISCWV3Hv3r2KW3a1yB1Ab1h4uF4NraY5omNRHUAAqDlmheMCi+EAqlSZFb/OIjA602q18oqfgwghUHc9o0KtWq0WAie77bWeEDRl96fb7cKZ8sS6lhn5Z61WC55zOqzHc4FuNzRmR6sf3pN9bWoI6KgDCAC2l+Lo6OiSWzQfavxRRWAAAIEwalxShGEI4ViQtjBmY2pR+exnP4tPfvKT+OAHP1h1U0pz9+5dAIBYWet/c3kNd3rfN4nBEFDTwkGVsHA9s4vANJtNOLYLx84mOfVvU8ZYdR8C57QADJyaMe9DEUURvN69MHWjMDvWzEHN9ipbt1IAFqBxcoIl97QABLJCMCbtnrSaTRy2Q/z8l19BrRdPaUr7u2E48SB4APBsWVksdRmazeZYAej3XEETRCzQmxQdgS9+Hvj858x0AF3fgrBOP1NOABwdHV5+o+ZACdn0mS7S3+6HgzYbTeMWjGEYZla+baFjgJu/yKjztUwU4nfu3AEAWCvr+ffE6hru3r1rXJ8wmVwAjjhPrldDGHaNcW8ajQYCfwkf+7334WO/9z4AQOAvGTPX9R3AMSGgTh1Ng9xYIHP9PNuDJcwtFtZut+E7LnzHRbfbqWRcogAsQLPZPHUIvKLmuEbtZDUaJwiTFK8ctVA3TACGYTgjB9CUIjANjNtPUNU0TbkfrVYLritwcAAcHPQFoCn94fj4GG4w/meub04RmHz39iSB3O0tqHwrKw5jyGaCotvtQjg24NhGbOZcBUZz300gE4ACYkAAWqsb6LTbxjj7CpMdwFarBcfxYNnDuRsqJNSUuaLZbML36ri3fxP39m8CyMJATZmrpwvAGpoNM96HIooiuLYD13aN2UQYpdPpwLNd+LaLVMpKhCwFYAEajcZEB3DJddEwJFcIAJqNJqzehG6SAIzjGEmSThWAWQ6g/ovGVrM1NpfRM0xANZvNISFrogPo+OMXVCblAOZCdXChHmT/NuU9KLrdLuBYgGNVlhhPhjFNdADA7du3YS+vQDj9gVasbuQ/I5dDs9mE658WHcoRNCX08OTkBP6IeArcJWPG11wAjikCE7h1o46fAjIzwLEcuJZjrAPY6XQQOB6CnrlUReoMBWABms0Wau4kB9CsENBGqwl1kkK9ZzmZ0H7l7E0TgJ6Nys5TKUOr1YI/Zj/BRAHouP3FoWkO4OHR4WQB6ANhGBnhoOUCcGA0Fz0BaIqLqQjDENK2AMdGx4DNHKInr732GtATfAprLfv61q1bVTRpbkwU4IpGo3GqAAyAXBSasPYAgEajicBbGvqe79XRMMQ5U0I7GFMEpu7W0TRMAEZRBFc4cG3HyBB1oHckW88BVF9fNhSAM0iSBO1OG/VpDqAhu1jdbhdRFOfnzykH0IRdLNXJp50D6Nr656tIKdFqd3KxN4jKATRFQGUOYH9xYtuAZQtjJvXjo6OJIaC983GNEFAnJycQngUMdo0gG9pNaP8gnU4H0haAY2nfl68KpoWASinx6q1bEOubQ98XK+uAsIyrampyCGiz2YTjnRYdrmFVNE9OTk4JwMAzywEM3BoscXrJHzh1RFFk1Hjb7XbhWi5cy9zzYtvtNgLLpQOoM2oxXp/kALqeMQm0SqjavQl9qecAmiBglRMzPQRUoNvVezDodrtI03TiOYCAOQKw0Tg5lcvoewYJwJOTyTmABgnA4+NjWMHIUO6b6QC2O+2skzu2EW7+VcA00XF0dIRWowFrbUQA2jbstXW8+uqrFbVsPkwWgI1mc0EcwMZYAWjC2gnoVbIfk/8HZA4gYM69ALKNfq8XAmpC3YdxtFsthoDqjurgkwRg3fXQ7rSNKN2vdquUAAwcC5YQRuxi9R3AydcoB1DnSVKJu3EOoGdYDl2z2cRot3A9M9rf6XQQdsOxZwACfQF4eHh4aW2al+PjY8hgZEOhZqoD2M2SeR0bURjmlShJdZjmACqBJ9a3Tv9wbRM3XzFLAA6i89w2jmZjggA0yAFM0zRz0PwRAegvo9lsGjFGNRoN1MYcAQH0w0JNuBeKsBvCtV14BjuALSUAbS//+rKhAJzBLAdwya3u5pUlF4C9EFAhBJZ9M0JY8xzAKU+sZwOplFpXhVLPiT+mCIxvWA5ds9k8JWRdVxrxPOVnAE6pAjp4nc4cHR8hHRWyPQfQtIqH7XbmAIreTo+pu7uLgBIbpomOV155BQBgbVw79TNr/Rpu375lxIatYvDzN0FsDDLJAfQMEoDNZhNSpqj5y0PfD7wlSJkaMV83Gg0EYwrAAEDdXcqvMYVOpwPPygSgCXn648jOF/fy+iJ0ADWk7wCOzwGs9b5vQudRi1l7YEd3ybWNWOSqXR5nSg5g71x7rXeE1ITnjdlPMOkYiCRJ0O2Gpx1AVxrhKCthNCsE1AQBdXh0mBd9UQhbwPLN6NuDdDqdrCP3BKCpk/siYJJIGuSVV16BcF2I5dVTPxMbW0ji2KhKoKaJvkFazSbcEecMQJ4XaMK6Sc1nwYgArPXelwnzXbPRzEM9R1GHw5uw7lB0Oh34tg+vwkPUz0qr3UbN8VHrhSHRAdSQXABOOAdQOYAmdJ5cAFrmCsCpIaC996WzAMwdwDE5gJYl4LmWMTuKwOlQVtfNcgN1Z5YAdPzsVAUTBODx0XEe8jmIqFlGtH+QbreT5wACFIBVooSHaSGgL7/8Mqz1a2PbrVzBmzdvXnaz5mZQAJokysMwRBSFcMcUgbEsG64XGCEA1fqoNpoD2BOEJqyfshDQxckB7Ha78G0Pvu0ZmSseRRGiKELgePkZ41V8/hSAM1A3ZWmcZYN+aKgJnWc0BxAAlj0HxwYsEoscA6EcQJ3DxnIHcEwIKJAJQxOeJTVxjzqAnmfGrm4uACfkAAoh4AaW9pN7GIbotDtA7fRiNw2kETmMijRNEXbDIQewirAYkqFC6U0LAX3p5ZchxoR/An0B+PLLL19ii87GoAA06V70o13GCw/XqxsxV6h1U81fGfq+Cgk1wgFsNicWgamZGgJqu/Btz8g5QvWNuuvnRWDoAGpI/wDN8SGgdYNCQI+OjuDa1tB50aueY4RLoA77dGYUgQH0dgDzSXH84wTPNWMzIXcAJxSB0X2hkgvA8Xnx2c8C/YvA5H13jAMoA4GDo8PLbdAZUBO58CgAdUDnXOpJHB8f4/DgANbm9bE/F64He23DKAFoag5gf5NwggD060bMdWoTcLQITM0QB1BKiWZrmgDMvm/CGlbR6XRQcwL4tm9klIgSezXHh2PZ8B2XDqCOFKkCCpixaD8+PsaK70IMHBi27Ds4PjnWfsHeLwIz/RxAQG8B2A8BHf9zzzEjqVzteo4KQM8D4jjR2oUFMuEkBDAhshsA4Pip9psjqn1ijAMoahaONBewg+QTuWtnIhAUgFWiBKBJIaAvvfQSAEBMEIAAgI1reOHFFy+pRWfH1BDQXACOyQEEANc1wwHMQ0AnOIC6C8BOp4M0TSfmAPq2D0tYRqxhgWx9FycxfNtDzfGzo4MMY9ABzP4O6ADqSHaApgvbGv9RqRxAEwayw8NDLI/EHq54DqIo1l50FMkBdAzIASzkABrwLOUCcCSEUglC3fvD0dER3MCaurjNHMCDS2xVeXKHcowDiFoWwqr75o4iH4NcJ+/ouo9Li4wSgCa5Ti/2hJ21ed/Ea6zN+3D71i2t54lBBkWfSfdCzXXqzL9RXH8JjYb+ouPk5AQCYuw5gAJCewGo5uJJDqAQAjXPDDcW6G8UBraPwPERRZFx0Qr92iJKAPqVrJkoAGfQbDYnun9AvwqoCZ3n6PAQq96wglrtWVG6Ox39KqCTrzGlCqjrCFgTnEzPBRpNvcUTMDkEVH2te17E8fHxxAIwCsfPjljQmakCsC6QJqn2YlyRu32enZfEpQNYHWpRZZLr9OKLL8Ku1SHq410nALC27oOU0pgw0MHP36SFbj5HTHIAfTMOUj8+PkYQLMEaMQEsy0bg140XgOpnJtwLYCAtyw1Qs7NJ3LSNwlMOoONXsmaiAJzBLAFoCQs11zNCAB4eHGB1xHpa6R1Ip3uuU54DOOWJNUEAtloteGMqgCp8w3MATRGAR0eHcPzpu+luADRO9D7oty8AxzxTPVF4cKC3i6lQk7jwnLxKkmkT+yKhxlz1twm88MKLwOZ9U519aytzB180JAx0UPTpPBaNMisH0DOkCMzR0dGpMwAVtWBF+83zfh2LKQLQMccB7OfPBag5ZgpAtT5a6u1C1x0fjRM6gNrRaDRQsyeUbOxRc6tJ4CzL4dFRLvgUygHUfZFYxAFUh8TrLACbzebE/D8gW/ea4HqcnJzAcQTskfuhQkJ1n9gPDw9nOoBukC24dH4vh4eHELYAvHE5gCK/xgT6IaD9IjAmjKuLimkCMEkSvHzzZYityeGfACBWN2C5npECcNEcwHa7pb2oPT4+RuBNEICeOQJQHfg+jppjhhgH+u8nCwENhr5nCv17krV/ya3mSBQKwBk0G42pDiCQFYLR/QFst9vodLtYC4bVx1pPjei+SAzDEJYArCk7u0oc6rxgaTab8NzJOVmeJ9DthtpP9CcnJ/D90/fCHAfwqJAABPRO8j84OICo2+Mdj3o2vOvetxX5GOo5ELYF4djG7ewuEqYJwNdeew1xFOUO3ySEEBCb1/H8Cy9cUsvOxmAIqEnhuM1mE5btwLLH73i6Xh1SSu37+NHhEer+6tif1fyV7BxWjSkSAlp365U4UPPQF081LLnmHWIPZOsjS1j5GYBLboAGQ0D1o9Fo5Ec9TKLuuNrvniiHb23EflrtOYK6O4BRFMGxp1ejU0VgdF6wNJvNiWcAAv3qoLpPisfHx6fCPwHA7zmAOgvANE1xctKAM+EMQIUSgDrv8O7v70OOC/8EjA0BVR1EeI72/WCRUeOozhEVg7zQE3T21o2Z14qt+/DCCy8YUSDJVAcw2yRcmhiO6/WKw+g8VwC9ENBgZezPjAoBnXLmUWCQA6jaueTUUDfUATw5OcGSF+R9Y8kN0Gy3Ln2DhwJwBrNyAIFMAOpeuVEtAldHBKBjWVjyXO0XiVEUwe0JwI98KcbtQ4nbhxI/9VshPvKlbFJ0TAgBbZxMrAAK9KuD6j6gnZycwHFPh+44DmBZertmjUYDUsrCDqDOE/z+wT7kpI3dQADCHAE46AACgPAd7fvBIqPGUZ3H00FeeOEFCNuGWN+aea21dQPtVgt37969hJadDVMFYLPZnFgBFOhXB9VZeEgpcXxyjPqEHMC6v4yj4yOtNxLU5xtMyQGsu+bkAPaPZquh3hO1um8ijHJycoJlr78AWfaC7LzGS74HFIBTUOEJ9QmHwCtMyAHc398HAKwHp9/LeqC/AAzDMHcA7xyl6MRAJwZe3JW4c5QJERNCQFut1tQcQFMcwKOjw9ztG0QIwPctrQWgattMAegPX68j+wcHEOMqgAIQloBVd7Tv24pGowHh2Eg//TyS33kWqWtrP64uMkr4dTQ/01Px/AsvwNq8DjGamDwGFSb6ggFhoGo+E7ZjjBgHskWu603OO1M/07mPt9ttRFGEejA+BLQerCKOY63z9pvNJjzbgzshFBfIwkM73Y4RIcb9IxRqWDLwEHsg21RedvqO7HJFQpYCcArZgZMJaguQA6gE4GgIKACseTb29vYuu0mliKII9oynVTmAOgvAZqu1EA7g8fHxqTMAFZ6vt2hSjp7pOYBJkuDk6BhYmtIx6sIYAdhsNmH5LuTeCeTeCeA7ODFsYl8kTHIApZR4/vkXIKac/zeItXkfIIQRhWCiKAKEBcv1tZ7bRmk0GnAmVAAF+sVhdF68q7liWgjo4HU60mg0UJtyH4B+fqDu6w4gE0l1twbbslFzAggIIx3AJXfQAcwE4GWvNSgAp6BcmCI5gE3NHZv9/X1YQpyqAgoAa4GL/b3dClpVnDiOpx4BASAXiLpOkkmSoNPpTheATuZy6jwQSynRaDThT9gX8dxUW9EEDDiAM3IALQewHaFtEZXj4+Osgt6kHEAAaQ3Y29d7c0fRaDQgBxNkPce4iX2RUAcudw0QgPv7+zg5PoJ1bXb+HwAI14W9vmWMA2g5DoTtGiHGFScnjTzPbxyuAQJQjf3THMDB63Sk2WxOPQIC6B8RofO6Q5Hlz2XttYSFJa9u3DxxcnSciz4AWKEA1I9+taHpDmDN9RDHsdaD8/7+PtZq3tgqmhuBh/2DA63j2MMwnOkAWlnKk7YCUIWJ+NPOAew9ajoPxK1Wlqw8LgQUUA7g4aW2qQxFHUAhBFxf391F5eyJ+uSOIeqW9u6+4uTkBNIfCN/zXZw09PzsrwIq9DM0IARUCTmrQAGYnM3rePb55y+oRedHt9uFcFzAMSsEtNFoTA0B9Tz9w/fUXDGpCqj6vu4OYOBMLgAD9B1Ane+F4vj4GMsDgnbZq2v9+Y/j6PgYq0MCMHs/l/0+KACn0D9Ac1YIqDt0vY7s7u5ifYz7B2Q5gFEUa7vQBXoOoJguUIUQcGyhbaK8cpSnO4DD1+qI2qUyNQS0aA4gADiBvpO7CuueFQJ6dKh3kQLF8UkW9pnjO2g1mka0fRHpKgFogOjIBeDm9cKvsa7dwN7OjtbzHpB9/sL2AIMcwKygRWNqERjHq0EIfTfYgEEHcHwIaN2AENBmo4ADaFAI6NHREVYGzjRccuparzdG6Xa76IZdLHuDIjYTgxSAGqEW4bUZIaBKIOq8aN/b3cX6hOoj67Ws/To7BUVyAAHAtoS2DqAaXE0vAqMm7EkOoO9l4T+6LtyPj49h2QLWlOM4FI6f4ujo8MLbNA+5AJziAKJuZbmCGi+yFCcnJ0OdQ/huL2y6U2Grri7KAYzCUNu+rHjxxRdhr65D+AV2dXpYvXzBl1566aKadS50u13AdgDbNaYvdDodpGkKb4oDKISA59e1nutyB3BGCKjOAjA7yqyYADTCATw8wvLAc7XiLuFY489/FPWsrPp9B7DmeLAtmyGgOtF3AGdXAR28Xkf29vawURv/PjZ6lUF1FoBxHMO2Zi9CbFvfUtlFHEDbzo5RMGFSnCgAfSCKYm0XK9kh8GLi+VSDuL6+k3tRAQjo3bcVowIQvXHJBPG6iHR7/VdKmbuBuvLc8y8AJdw/oB8uqnseYKfTARwfcDzt74NCCQmV5zcJ19P7/LmjoyO4jgdvQriI5wZwHU/zHMAWglkCsBciqvO6Q3F0fDzkAK54yzg81HOOHod6VlYGHEAhBFb9+qU/RxSAUyhcBKb3c107T7fbxUmjgc1gfCjrRu/7Ozs7l9msUsRRhBnnwAPIDoPXVQCqDQJV6GUcQgj4rqXtswQUCwEF9F24n5yczCwAo3B8fd/H/v4+LN+CmJJTKnrhoblY1JQ4jtFptyGC4RBQQN/Pf9HpdjrZjhSgtfDodDq4c/tW7ugVRdSXYNeWtK8EmglAD3A8tNt6bqqNokTdtCIwQCYQdRaAh4eHqNfGu3+Kem1VawHYajVzgTcJU0JAu90u2p02Vr1+SO6qp/9ZjIOoZ2V1pDLrqkcBqBWFHUBHbwdwdzer8LlRmyAAa/o7gFEcwbZmK0BL6FsEpogDmP1caPssAX0BOM0BBPR1zo6Pj2F7pw+xH4fjA41GM6u2qRn7+/tAfcaZZ4Y4gLnIGwwB7TmAJuV3LApJkmTjaC1bOOp8ztkrr7wCKWV+tl9RhBDAxjW8qHkIaLvdAVwPwvXR1jSqYhQ1f7kzjh9wvDpOTjQXgBMKwCjqvr4CMAxDhFGYC7xJqCIxOq87gMHwyeX8e6veMuI41nrTfBD1rKyNuOOrXg2HB4eX2hYKwCkUzQEMegJQ10kyF4BjDoEHAMeysBp4+juAhXIAzQ4BzX4utR7M8iIqE96H/gLwCE5BB9ANVEED/SbGvb09pLUZu56GOIC5AAxOh4BSAF4+Knxb1OpDX+vIyy+/DKBcARiF2LoPN2/e1HKDR9FqtyHcIBOAmq4xRikaAup5S1qOrYrDg4IC8JIX7kVRn+2sEFDbsuE7vtZuLNCvfL3qDQvAwZ/pjmrnij/syq56S5f+HigAp9But+HaNhxr+i57TfMQUCXsNic4gACwGbi5UNSROI5hXREB6Nr6C8AgsCbeD1/zENDjk+NSIaCAnsnxu3u7eYjnJIQrYHmW9gIw30EfHKN6AlDXjYRpfOELX8AP/b2/Z8yCfZRcANazhaPO7+Pll1+GcByI1Y3Sr7U2ryPsdnHnzp0LaNn50Gq3IFzfSAE4OwRU7xzAw6OjiQVgFPVgFYeajlG5iTEjBBTIwkB1FuNAXzytDYhy9W+TBKDvuKiN7EKv9XIALzOUlQJwCq1WC8EM9w/oh4DqumhXwm6WANzZ3r6sJpUmjuNCOYCWyMKXdCQXgDOqT3ou0GzqOykeHx9PzP8D9HYA1SH2hR1ATcWslLIXAlpgCF+ytReAyuUTgw6gb64A/Kmf+il84fOfx7bGY+o08rmsrn9xiJdeegnW+jWIIjuEI1gb1wBkYaS60m61ILwAwg3QabeNyHXqh4DOLgKjq+iQUuLoqFgO4NHR5S7ci5I7gAUEYODUtL0Xir4D2M8BXPNXhn6mOwcHB1gd44yv+ksIo/BSx1oKwCm0Wq2Z+X8A4Fo2LCG03Z3b2dnBkufCdyY7mRs1vUNAkzRBgRRA2EJqLQA9d3b1yUwA6jsQHx0dwZuSQ+f29hl0DN3rdruIo7iwAFTX6fZeWq0WojCafgZgD1mH1u4+MOAADghAYVuwAs9IAaiKpug6Fs1CzWViaXnoax15+eZNYH1rrtcqAajCSHVDSol2qxcC6tUgZap1OK4iDwH1pgsP16+j02lrGbXTarUQRdHsENBgFVEUablJ0k9jmu7EApkA1LmfA/1c9sEQUOUA6r7JqTg4OMDamNzY9Z4ovEwhSwE4hXa7jcCeLQCFEKi5npYDAJAJwM0JR0Aotmoemq2Wtu8hiZNCOYCW0DsE1HNnvwnPyXZ9deXw8GBiARggO8YiCCwtE+OVk1c4BNQbfp0u5EVdCghA1AV29/UWgLnIG4lSEDXXSAGo3ACdc8umoeYBsVQf+lo3Wq0W9nZ3cyFXFuH5sJdXtXUAO50OpEwzB9DLjiLQOWRS0Ww24bg+LHt6uIsqEqPj86Xmr6UZDuBSL0RUx/lOfa7FHUD97sMg+/v7WPaW4A2sy5fdOmyhf5qDYn9vH+sDRWwUa0EmAC/zfVAATqHdbiNwCpwWjawQjK47c9v37mFzQgEYhQoP1dUFTBLzHcB2uz0z/BPoCUBNnyUAODo+mioAgSwMVDfRBPQXT2UdQN0WXUoAikIhoBYO9g+0DFFSHB4ewvJdiJFdntR3jQntGYeum1Gz6AvAbFGia0TCa6+9BgCwNuZzAAFArm/ilVdfPa8mnStq3BF+HcI3o1Q/kLVxlvsH9B1CHd+TEnRFcgABPUPV+w5ggRxAp4aWhvdhkP39/aH8PwCwhIW1YNUYAXhwsI/14HQIqBKFl1mxmwJwCu1WC8GMHSxF4Dja2ueZAzg5/w8AturZz3XNWUmSFFYBBSg0zgFsNptwndmLcNcFut1Qy/chpcTJ8clMAeh6qZYTohKlzvTukKPCWXUTgPlkV8gBtBCFkZaLLMXh4SHEuDGq5mLvwIyJfRw69uEi5M/KcrYo0dGhAfq5e9acIaAAYK1t4dVXX9VygyQXgF4NoieWdBuLxpEJwNlhh+oaHd9TWQGotwM4/iD7QQJX/xzA/b19rA/k/ynWvVXtjzoCsmM5ThqNsQ7genD51UwpAKfQbrfhF3QAfVtPAdhut3HSaOBaffqKfUtzBzBN00IOoGUBaarnoqvVahUSgOqgeB0d5Xa7jThOCjmAh4f6LdzVBFfUAbQcAdsR2i1Q+gKwQKcw4CiI/YN9pOOiFOqetiXWi2CqA6j6iQgCCMfRdmF469YtQAiI1fW5f4e1volOu61l/1AbVsJfggjqQ9/TmUajUUoA6vh8LYIALFsERsc17CC7u7vY8NdOfX/DX8Pujt5pDkB/Dt4ITgvAZTeAY9l0AHWh3W4XKgIDADXH0XKXVAm6rRkO4HrgQQiNHcA0KV4FNNZTALZbzWIhoL1HTsfnSbl6/owNRd/Xr3AKMBACWtABzK7VTwDu7e1BuBbgFnDFl/Q/DD6raHr6poi6h2ajYayQiqKo6ibMRf68ex4sX9/zwW7dugV7ZQ2iYKTOONTxEbdv3z6vZp0b/eq4dYhekQgjBGCzCadA2KHr6+sAqrnO5BDQdrsN27LhWLPXsYFTQ7ujb5XZJEmwf7CPjWCMAAzWtC90BvTn4PUxVUCFENiorVAA6sKoA/i+L38WNw/3cfNwH//4t38d7/vyZ/Of+baDjoa7J0rQzQoBtS2BzVqgrQBMkxQzimcCACwhkCR6Lhbb7fbQGYCf/HyCnUNg5xB4/ydifPLzmXB1nf71uqEWJEUcwOPjE+0mk3EC8IXPSDT2gMYe8KX/IPHCZ4bb7Hj6LVD29/ch6tbMirIA8qMidBaABweHYwWgKgpjah6gqcK10WjAcj0IywY8T7vnX3Hr9m3IM7h/AGCt6SsABx1Aq7do1HFjbZRWszWUA/jFJ96Hw72bONy7iU9++B/ji0+8DwDguvoeM3J4eAjfq8GZUQjQsV34Xk1LBzA7yqyWzxMfePLn8NrRTbx2dBP/7In/ER948ufya30ngJRSy8gjILsfaZqOFYDr/iqaraa2bVcokbpROx3GCmTC8DKFLAXgFLphCH9gZ/Hm0T5acYRWHOHp3Xu4edQPGfEdR8uHTwm6a+MWVyNs1hx9BeBACGgnkgiCAO9+97sRBAE6UX/Bbgkg1Ux0KNqddi7uAGDnUCKMgDACbu1kXwP9cwJ1fJ5yB7CAAIzjRDsRq0Ji7IHu0NgDkij7c3Q3+3oQ25PahSjt7e9Bzo6wyuiFieoY4gZkeRGtZhNi3BjVC103VQCa7AAKP7sfUmMBeOfOHVgrkw+A7z7xG+g+8RtTf4dYXgOEpeVh8Gq8tYJlwAsgLNsIATiaA3i4exNx2EYctrF752s43L0JQO8qoEdHR6gH4xfqo9SDVX0F4ED+32tHN9GO22jHbTy39zW8dnQz/5m6Tsd7AfQ3MDeD9VM/U9/TeZMTGBCAE56rDX8Ze5cYykoBOIEkSRBFUakcQB0X7Nvb2xAiC/GcxVbNw/a9e5fQqvKkUuYOYDsC3vnOd+I973kPvvM7vxPtgTWWAJBqWnih3e4UCgF1NQ4BVYuPaQfBD/5ct7CYVqsF2xGFCgopLEc/Abi7t1vsEHgAcAWEq2+Z7LxdY/KUxVL2Pd0n9kmEYVh1E+bi5OSkv8vj+zjWMOyw1WqhcXIyNf8v3dtGujd9U1PYNuzlFdy9e/ecW3h2jo+PIRwPwvUghIBdW9JuTB1Hq9WC4xfJAdTbAazNOANQUfNXtBSAnU4Hvj27AAyQOYCAnpFHQD+daZoA1LWGhWJvbw+u7WDZHX9PNmsr2N3bu7TIqfkD5xccJeb8grkFnu3kh//qxPb2NjZrAewCC96tmofP3dlBkiSw7cmHxl826iwtJQBrLvDYY49BSonHH38cmwPrRiGgXdghkG0ohGEEx5l9H9xesqOOA3EZBxDIFjAPPPDABbeqOM1mE44nABR/RhwPaDT1ckAO9g+AtxQTgEIIoK6vAMzF3VgH0Bu+xjBMFYDHx8dI1S6OH+DoUD8H9l5vs9JaLrZIn8ryqpYC8PDwEHZtoGBEsKyl0BgkSRJ0u508vHMalu3AdlztNtgA4PDgEHV/srs8SN1fxaGGUQqtVqu4ALQpAC+a3d1dbNZWJ6ZubAYr6IZdNJtNLC+fLhRz3tABnIASc0UFoO846GgqALdmHAKv2Kr7iJNEuwlGCTqlYQNXoNPp4EMf+hA6nQ6CgUIYQuh5+LJ6nrwCAlDlCeroKB8fH0OIvks5iUEBqBOtVqtUARggCxdttfRZoLTbbXTaneIOIABZ1zcEND/TcGnMrkIvB1DXts9Cx03BIhweH0ME2f0QgY8Tzfox0E9vEOcgAMXyGu5puHg8ODgABvOFghXtw6GVgChyDqC6TkfRcVgqBHQFhxo6s+12G75drOS1CQ6gazlYcU8XUNns5QXqLgB3trexMaYAjGKz19cv631QAE4gX7AXFYC2gziOtTv3afve3eICsKbnWYC5A1jgWl0FoBJzRSKKHXv4NTpxdHSEILBmFuTROQTUKnAUxyCOm4Xv6kK+ACxyBEQPWbeysFENyd29MQJQ2BaspcA4B1BtWunYh4twfHQEBL0FfFBD2O1qJ2bVIul8BOAqDvb3tZu/Dw4PIQZKxlu1FexpLgBVOKczIcxtFFfD8+eklDg+Pp5ZAVRRD1ZxfHysXfRRu9XOhd0sAgME4GZtY6x75tkeVvxlAwTgDramPFPqZxSAFdMXgMVCIdV1Ok2SaZpid3dvZgVQhRKA9zTLA1SDapGChwJ6hoDmu6IFHidX4yIwx8fHM/P/AL0dQMst93zYLtDtdLV5rpQAFCUcQKF5CKiwLGDcOYAAUPeMKPE9SNLbhNJpPihKmqZZbl2QLQjV37pt5mSbAgKifvZQKbG0jFTD6Je9vX2Ier/qoahnoYa6jEXjKCsAHQ0dwFarhSSJUSvoANaCFSRJrF0uY1Z3oNh98HpOoY7rDqCXzjTmDEDFpr+unXkxSJIk2N3fy12+caifXdb7oACcgMrdKCoAXQ0F4MHBAeIkwdaMQ+AV6rB43XZRcgFY4FohymR3XR7quXCLFIHRXQC6sx1Wz8vuhXYCsN3CjKrep7BdaFUeu180pcTwXRfotDta5qTt7u7CWgkm5kXIJQ/bmo1Js1D9XZdnpgwnJ73jW2q9hWNNTwG4v78Pu76UbR6cEVFfyX+nLiRJguOjI1j1vmNg1VcRhaF2QmOQXAAWDAG1nUC795OfAegXDAHtXadbH+l2OyVCQPUWgDv3dsbm/ym2gnVs39NXAB4cHCBNU2zVJjuA6/4yhBB0AKumtANoZdfptMBSuwizDoFX1FwbNVe/oyDykM6iDqDGIaBFBKBtZeJJx4H46OiwkAMoBOD7lnYCsN1uoeyZ0bZmgjwPAa2VEYDW8Gs1YntnB+m0Y2qWfOMcQOVo6LawLYJywUQvBFT9rZs7dnBwANQn59OUQdTq/d+pCYeHh5AyhRgQgMoN1DkkWj37jltMeDhugGZTr36ihFxRB1DXw+A7nU7u7M1CZwcwSRLs7e/hWm1z4jVbwYZ25sUgqm3TBKBtWdisrVAAVk3u2JSoAjr4Oh0oKwABYKvuaScAFUUznnQMj1HPhWPPfhdCCLiOpdWzpDg+KRYCCmR5gCealY/vtDulBaDVcwx1CVPqC8DiOYAqXFQnh0OxvbM9Nv9PIZYDNBsNLRcm40iSBGGv7+ryzJShH2JcG/pbJ3EEAPsHB0BQ9DDM6YhaJiR1ErlK5FlL6/n3rCVzBGCRKqBAJgB169tq47Je4hiIwdfpgJQS3bALr2DVM19jAbi7u4tUptgKJldl3aptoNVuaXtmaX89Pn1TYStYvTQnkwJwAuoAX+XszUKFgOp08G9eNreMAAxcbG/rlQNYhiJ5glVQxgFU1+kmAKWUaJw04Bd8nDw31W9HtNstHwKqmQN4eHgIq+5AlDjLULmFOi1wgczd39vdA5an5KksZwsTU1zAQdFnogPY32CoD/2tmwA8ODycKgC7T/wG0r17SPfuof2Rn596ILxyAHUar3IBOJADaBngAOYFzwoXgQm02yjJHUC/WH6puk6n5ycMQ0gpC4eAOr2JUbd1BzAontYnXrPVCw/VrYaFQrXrWm1yHmP289VLW4NTAE5ACTnHLvYRub08BN1CQAPXwVKR08d7bNY87Gzra6ObSt8BLHa9YwvtBuJOp4MoimeeAajIHEB9dkQBIApDWHOGgOpyP7LS8CV3OnrX6yYADw8PkcQxxPJ0BxDQrzrxJAYrGp5ouhs9jfxYjnomioTrwvI87URHVqhmssuU7m0DYRcIu0jvvDL9QHjXAyxLq4gFtYE77ACuD/1MR/ohoMUEoK2xA1gLCgrAQD8HsB/FVmzH1hIWPNvTZp4bJBdPweQQUBUeqmvf2NnZQc31UZ8RGr1VW8Xu7u6lVCSmAJyAEnJuQQfQsfR0AMuEfwKZADw+OdFyEDAZ9TwVF4BSu3ugFkeFQ0A9vXZEs2Na0vIhoLoJwMMDpEHJMGdNcwDzyXqqA5j9TNed3VEGQ5B0EhRF2d/fh3CcrAP3EPUlrQRgkiRot1oQRQejGQghYPs1re7Xzs4OhGXnBWoAQLg+7KCu7SIXmCcH0Ee73dYqdePk5ASWsOC7xUKMfbcGS+i1gdCvY1F8Deg5egpAtfm3WcAB1HWj8N69e1Pz/xTXaquIk+RS5moKwAkoIVdUACoHUC8BuI3NoNxqV4WLmhJuZQplHUDb1stNBgYEYNEQUB9ane+k7kHBLp2jowNY5ggIABCOgPAsrQQ50Bd1YmWKAFzSszrxJPJF4OqyVgvCouzu7sJaWhqqyprWa9jVSACq0FrhF3OZiiB8X6vxamdnB/byOoQY7utiaVPbRS7QDwG1C+aeOY4PKVOt1k7Hx8eoBcsTKxOPIoRALVjWygHsmxjFBaCrqQO4vb2NFX8Z/hQxu+qvwLUcbTcK7929h+sFBKASiZfxPigAJ5CHgBYsMa1yAHVatO/u7GBjDgcQ0FMAFtkf1GgTcYjSDqAltXqWgPkcwHa7gziOL7BVxVGfZ9kQUCUYdbkfR0dHQFB+6BY1/QRgvpCdIgCFbcFeDrSd2EdRi0CxtoxGo6GVs1GE3d1dyPqw8yHqS1oJ8Dy38pwcQACQrqdVzua9e/eApdNFL8TyOu5pLgAdxzslXCdhu/oVHzk+PkZQMP9PEXhLegrAEg6ga3vazHOD3Lt3b2oBGCALYd2sbWi7ObK9fW9m/h8AXOtV/b2M90EBOAG1aC0qAO3edZcRt1uEKIpwcHiEzWA+AajTZJ/vwhVcRxXdtbtMyoeAZmf46ERZB1AVi9HFBckFYEkHUCcBGEUR2q12+RxAADLQKyQXyCY5y3OAGXnK6bKv7cQ+Sl8AriCJY60WtkW4t70NLA0fryCWl7C/v6/N/KY+U+GUrOg0Bem4WhUjuXtvG9bK6Zwna3kT9zQ+76zb7cJ2i687nJ5TqJPzdHJygsArd8RI4Onl+PcFYPE+4ghHKydWsXNvG9dmCEBAnQWo30Zhs9lEs9XKxd00lEikA1ghSgDaRQVgb7dLF7djf38fUsrSDuBGkA0WOgrAQg4g9BWAAkDRM4ttG3kpeV0oKwDdBRGAQiMBmO8wlzkDsIcMRFY5USPu3bsHTDkEPmclwO27dy6nUWdEiWyxkU32uhXemUaSJNjf24NYHnY/xPIy0iTR5r3kYuEcBaBwXLTbeoj1OI6xv7cHa3mMAFzZQqfd0mZcHSVzAIs7s7aGB5DPJQD9Ja3uSb7pbJUQgJarxTw3iJQS2zs7eY7fNLaCDS03R4pWAAWAwPGw7NfpAFZJWQdQXaeLAFQJ+xu1chOk79ioe65W54WVEnSZArywtsxLFEWwbVH4vdgWEGq2E6eKWxTOAexdp0tejdrZLBiZlKMEow47o7kA9Ms/4yKwcHyslwN4+84dyGkFYBQrNezt7mnjQE3j6OgIludCLGVhlLqIpiIcHBwgSZJTAhC9r3UJw1WLVOGUjOeehuMijPRY/O7s7EDKFNbK1qmfqe/pci9GCcOwcP4f0M8V1El4nJw05nAAl3Byok/V374ALN5HXMvVyokFMjHe6XawNeUQeMW12gb2D/a1epaAQQFY7FzJa7VV3L179yKbBIACcCK5A1g0jl3oFQKqcvg2SoaAZq9xtcoBzB3AAhZgCsDSWAAWxbaASJPFiKLRaEAIoOiaS6Xn6LIrqvp0aQewNwTo0LfVZynmyAFEIHB8rMe9ALKd3Xv37gGrswWgWAmQJolWlSgnkRXpqQH17H2ZJABzUbE8fFix6H2ti+jIN2PKduZpWJY2C0e1+JsmAO/c0dMR73a7sErkndkahoA2Gg34cwhAnQ4hzwsZlgkBtVzEkR4mhqIvnoqEgGbX6LR+BQbeQ322AwgA14NVbN9lCGhlJEkCS5RxbPR0ANeD4c7/819+BTePWrh51ML/9Ntfw89/+ZVTr133Hexp1IGs3mebFhCAUvav14kwDAvn/wGqCmj1jtMgjUYDvm8NGayf/xxweJD9+fhvZF8rlAOoy6So+mZpB7B3vVYOYDA8LqW/3QR2Y2A3RvLLR9nXowQCYberxfsAsuei027n5/xNpVck5jJ2Rc/K3v4+0poPUcvarFM0xSzU5ytWRgRg72tdPv98nj3HsV7YNuK4+k0eoC/urNVrp35mrWYCUJd7MUoYhrBLiA5bswPI0zRFu9065QB+7Pfeh+39m9jev4mff/wf42O/976hn/veEtrtFtI0vczmTiSPYhPFHUDbshHFeswPivwQ+AI5gOosQN3yxe/duwfPdrHqFTtW5Fp9Dfe27114ATH9VsqakKYprJGVYisKEQQB3v3udyMIArQGHBrlOunS+Q8ODmBbAssjxRVeOWqhHSdoxwm+tneCV45OVz1bD/QKAVWCrmgVUB0FYBzHsKzhRXs3wtDz1B0YdzMHUK+BuNlsYjS3/+AAiKLsz8529rXCdfuv0wHl4I3u6cTh8H2IR0wAnRzAXEyPhIDK3RgIkf25HWdfj+Jbw7+jYvIF7Orkw7wVYqU2/BqN2d3bhagHQE8AmuBaKpTwOCUAXRdWva7N55/Ps1PGehl2h/q1DGcIDGEhlXrM33fu3IGw7KFD4BWWX4cdLC2OA2jrFQKqziQMRhbr9/Zvohu10I1aePXe07i3f3Po54FXh5RSm0JCav1gD4SAtqP2UJ9oR8NtdSwHkWYbz7kAHHAAf+7pX8bPPf3Lp67V9SzAe/fu4Vp99ZSh9L4nP4b3PfmxU9dfq62iG4YXXrTtHAPoFwvlAA7SiiK8853vxHve8x5IKfHER/s3TkcBuBZ4c4VDrgUuDu7uQkqpRUGVMiGgugrAKIpgjzQrjDD0PH3iNz6U/8y29BAcgzSbTbhu8R0pJQB1ERy5ABy5D3EIvGvgPjz2sQ8N/Vx1AR3uRx5OG8zRL3ui8eTkBBsbs3dTL5q+2zRbAJriAEopsbe7B7ztYQjbglWvGScA7aWl8bl1Kyu4ffv25TdqDPnO+LT5KewMja8f/vhvzv69RcJMLoE7d+7AXt2CmDCXidVr2tyLUcIwgm0X6NM9rF4hH10EoJqv/IJujUJd32g0sLRULnz0IugfZTYgAOPWUJ/47Y8+MfQa23K0iWJT7OzswLVdrLj9z/SV41tjr93QVQDevYet4HT+383j8e1UoaL37t3D+vr6hbWLAnACUspTjk3ddfHYY49BSonHH38cN/z+IKebANzf38eaP9/tXfNdRFGMRqOBlZGd4KqwhCiWAygxcdKskmxDYfh7nouh52kwEs4S+oQTKxqNBhyn+ALJtgHLFvo5gCOPh+MN3wdndN7v3Tcd+naz2cza485RBMYTkNDHke07gAVyAG0L1nJNewF4cnKCKAxhL/ceoqWadouRady6dQtydUKhgtVVvHpr/MKrMqZNCl4w1K+xVCz/Rgdeu3ULWL0+8edi9Vp2jYaEUQjLLr5usO1snaJLxIs6C9J3i4vYwet1OUtSzXf2QJ5szakP9Ylr3o2h19jC1mKjc5CdnR1s1dYLmRGe7WLVX9Gqij2QCblv23hT4esHj4J429vedlHNYgjoJNI0hcCoAPTQ6XTwoQ99CJ1OB/WBeDglAHXpPAf7+1idcbbWJNb8bEdOp+IFlm0VzgG07XMsDHBOZCGgw2/AdzH0PPkDaROWrc+zpGg2G4UrgALZ5rznCm0mRCXgRqcRxxu+D6MF7IQQEEKP+9FsNmF59nzOfM8B1EkAWoEH4RfLF5IrPu5oLgDVwkP0BKBcquHuth6FU4qQCY/xQkmsrmF/d1eLXK0iUR7C84f6tZh1aLyUsEbDNCpASonbt2/DHpP/p7BXr2Nne1sb0TRIHMWw7OJrD6vnUOmy4bloAtASAwLQrQ31idrIe7SFrc19UGxvb2PTWy98/VawrtWmW7vdxvHJMa4XLAADXN5h8NWPdpqS5QAWX2Tp5gAeHh5gteDCapTVnnOokwC0bbuQAEykHNrx0oU4jk85gNOwBbQpSKBoNpulj91yXX0ERz9sbI4XC1x4QnYRms3mXEdAAAA8vQTgnTt38tDOQqzWcPuOnmFvin4VzUwAipUl7GzvaPHszKLZbOL46AhibYIA7H1fh9DDXACe43wrZapF+sDBwQE67TastckOoLV2HVKmWjriURTBKlEERl2rSwioEnBeSQHoaSsAiz/TlmVpsdE5yM72DjYLnAGo2PTXsbujTxFDJeKKnAGoWHID1Fz/wqsuVz/aaYwO+W/zIKXE4dExVuYMAV3R0QEUZjuASZKUKlgnLL02FIBsJ8stKQAdV5+keLUIn6dbCyG0WMS3Wq1cyJWm9zpdFii379yBXCl+YLRYCXC4f6DNQnEc/SIq2bl5YnUJYber1Vg6iVdffRUAICbknKjvq+uqxFE5iuk5LlaTtP97K+RWL7TTXr1v4jV2Lzz0loZhoFEcwyqxCWtpGgLquSU2pwau12V8zUNARfF7YQtHKwGYJAn2D/axWVsv/JqNYE2rYyD6RWyKnQGouFZbowCsCh0We/PSarUQxzFW5gwBVQ7gRVcgKoNtW0gLKMBUApamAlAUqmOaodxCXQbjrLpZB27JR8pxpDaO01n7tA5jQqvVgpx3jdrLG9RBkKdp2jsDsMQu+2qtf3agpty5cweW5wG981eVENS1YuMgr7ySHQk0WQCuDV1XJV4vFl2e5/iYxvDLxLhfEK+99hoATHcA1+8bulYnkjjOwzqLoMSiLnNdp9MBUF4Aur3r1eurJk95KOEACiG02nTe399HmqbY9NcLv2YrWEez1dRGiOcOYL2sAFzB9j2GgFZGmX320XzBKlFnhY0eAVEU9br8zDENKBoCmkqhpQOYpmk5B1CjwiNAFp6TpmnpEFDHAdptPQbis6JDREC73YacL7JbKwdwb28PSRxDlBCA6lqdxdTt27eBteX8WRFry/3va84rr7wCYVkQE4rACMeFvbqqhQPo+z3n+BzzlWQcwZ+VJ3gJvPbaaxC2M/YQeIUVLMMOlvQUgEk5B1D0HCpd5jq1QeY6JR3A3vU6bLABgxEvZVKZLC02OhXKydsMiodPqkqguriA29vbsISFjWC51Ou2aqvYpgNIyqJKxa94860UHctC4NraCcCkwPyQpNAijGeUJElKhR7q5gCqSa3sR+u6+kyIi0C7056rAiiQhRULW2hRxCPPXSpyBIRiVf+zAG+++iqwOlACfmUJEELLhfooL7/8MsT6+tQqynJtHS++9NIltmo8fQF4juHAUYxardyi/yJ49dVXYa9dn1nNWqzdh1df1e+5SpIUokwIaO9aXYqPKAfPdcptBqjrdZnvlJCzSpgTAno5gOoInY0SOYAb/trQa6tmZ2cHm7WVUrmYALAZrKLRal7o80QBOIV59kF02D1Rwm3Jm98JW/JcrQSg4zhIChWB0dcBLOUo9y7W4XkC5heAjqOH4wQMnCc5z4s1uQ+dbgfiDPsbwrW0EIB5rlyZENC6B+HY2grAMAyxu70NrPcdNGHbsNdWtHDNZvHSyy8DM86HFJsbeO211ypfrNdq2XMjo/MTgFYc5r+3Sl559TWIKfl/CmvtPryi4XOVJHEpAaiEri6bnd1uFwICTolCNgDy63XJUc6FXImdZ91CQJWLt+EXD5/c6LmF2jiA97axGZQ/Tu1aL2fwIo+0oACcQNmiD7K3rNShipjKuaqXTdgaoO7Y2uRuAYDtOIUKviUScMtWKrkEpJRzFR/RZTBWu6LzCMAwrF5wAAOhMHNoOSn16NvdThdw5g9F1c8BLO64CCEgVvQ9C/DVV1/N+vn68GIlXVvGSzdfrqZRBWm1WtjZ3obY3Jx6ndjcRBLHlTua9XrvmI3zHFuisPIDvOM4xt27d2Cv35h5rb1xP44OD7Sap4HeZmcp0WEBEFoJQMfxSof8CyHgOp4W4yswEAJa0gHUib29PdjCwrJXvF+u98Ti/v7+RTWrFNvb8wnAzdpK/vqLovoVjaaU7fzpHPHWF0Wj0QAA1N35nbC6Y6HZbJxXk86MY9uIC2ihNNWzCqiUslRSqW4O4LwC0LaBTkePHVEl4Ob5SHURgFEUZWeEzIujxw713bt3YS/XIEqeuyZXfNzSNJ/u5ZdfBgCIzWEBKDbWcPvWbW2qHI7jpV5Yp9icnHc2+POXKg4DDYIgK/Z1jovttNupXADeuXMHaZLkRV6mYa1l1+jmLqepLFV4BNCnyjKQCUB39DDYgriOr40AXAT29/exFqyWCp8MHB81N9BCAEopsbu3i63a/ALwIp3M6lc0miKEyEVdEdSlOiwS+w7g/EKo5tponOgjAF3PK3gOoKYOYNkQUPU6jSZFAChxvi+ATDAmSVJ5yBjQ3xiQJU3VPJdCg76dCcD5Xy9toYUQuXv3LtISR0DkrAS4d09PB/Dll1/OiqisjQjArTWkSaLdQn2QF154AQBgbc0QgOvrELaNF1988TKaNbkdQmB5eRmyez75MTJNkXY7WJ1QAOeyUM+IvX7/zGuVS1i1GzuKlKnRAjAMQ9glwz8Vtu1qscG2KOzv72PdK98n1/xVLQTg0dER4jieywHc8LOiMQwBrQDLsvKwziKoa3VwANvtNgQAv+Tu+iA1x9KqeqPruIgLKEBdi8CURjMHUAlAp6T4UIJRh13RXACW/EiVYNThuUri5GwOoKXHeVu375Y8BL6HWK2h1WzlUQ468fzzz0Nsrp1yNa2tdQB9kaUjL7zwAqygBsxwwIRtQ2xs4Lnnn7+klk1mZXUVsjNZAFpb9wGeD3g+rAcezL6eRE9IrqyUX6idJ30BODsE1Fq9DmHZWhzLoZin8mR2vT7VJ6MoglN2p7OHYztajK/zUmbNexkc7B9g1StXPRMA1txlLQRgv4hN+XHFtR2s+ksXWsyGAnACQggkJfKvUo1cgna7Dd91ziRGA8dGp63HeTYA4LhuoSqgcSq1WKifmd44rMOGAtAPGywbXauu12FXVD0XpR3A3vVVhxanaZrlhJ5liNFAAEZRhIO9/XIVQBU90ajbWYBSSjz73HPA5phy5WsrEI6D5zUQTZN49rnngK3NYuPN1haefe65yhfsG+vrkJ3Jm5T+H/0OWFs3YG3dQO3P/mX4f/Q7Jl6rhOTaWvFy8xfBq6++CntpFcKf3TeEbcNevaaVAOznrJfPn9MlBzCKItjWnA6g5VY+vir6Rc/KRLJJLdawioODA6z55cXTqreCw/3D829QSZR426yVF7EAsBEsXz0BKIT4b4UQcsyfv3ZZbXAcp1QIaNJbJVa9SAR6ArCsVTOC71hoaVLOGMjCOpN09qSSJHqGgEKUOQa+X6dENwFYorgbgMUQgKkmDmC+uDrDqC2t6gsL7ezsZMVSVudwAFf0PApiZ2cHJ8fHENdPF1ERlgWxtY5nnnmmgpbNJooivPzSSxDXrhW63rp2HY3j4wsNTSrC5sYGrCkCsAyylaVNbMyognrR3HzlFYi12eGfCrF+Q8tKoPPUEtFlrotLHmQ/iGXp4wD2c96Lj/cS+gjANE1xdHyEVa+8AFzzV3BweHABrSqHEm/r/nwCcN1fwt7uxQlA3a2SPwFgUIVcWuKBbdulFkppLzxRBwEYhuGZwj8BwLMsRFHUq15Z/cDsum6hYyDiVGopAHX4DM/CvA6gmkt0CAFVz0VacqNZlxDQecp6n0LIygVg7t4tz3HmWs8BvMjKaPPwta99DQAg7ptQRfO+TTz3zPOI47jy52iUl156CUmSwLk+u/AIAIjr1wEAzz77LO67r9hrLoKNjQ2krfOpgClbWUjx5owqqBeJlDJzAB/6g4VfY6/fwO2vPKXfc1U2zF6j0MM4jmGX3ensYVu2Nk5mLgBLOYDlKrheJI1GA2mazhUCuuoto9FsVN4vVBjqmj9fcal1fwmv7d86zyYNoYfUn8xnpZSfGfhzabO+bduQANKCuyc6OYDdbhfuWfKEAHi2hVRKLYp3ANniPU6mvycpJeJEVwGIOQ+g0wP1HJTdV1DdQYdJcV4BmPa6gOfNVxnuvOgLwPl/h0T1eaVKvIk5cgARuBCOrV0I6Fe/+tUsP66X7zeKuG8LURhWXjxlHEq8Wj1hNwuxuQlhWZU7mltbW0i7nXM5C1AJwK0ZRXAukoODA7SaTVgbs/P/FNbG/UiTJD9Xs2rOIh50ER5JksAS863jLKGPAFSfZ9E1bHatPg7g0dERAGBlDgGojo2o+izrg4MDLHk1uHPmlK75yzg4OrywZ0qPO60hSsglRUpPDlynwy5cFEVwzziYur2Vvg6he0BPAM4Yx5RDqKcAtEoVH1HX6rChAPQFYNm5QV2vQ1iMei7mDQHV8bkqjQZrrNy9m8MBVGcB6uYAfuXJJyHu24SY0F+t+7PwyieffPIym1WIZ555BlatBiwXW2gJx4HY2sLTPeFYFdd6IauyeXLm35U2T+AHQX6+YBWUKQCjUNfqV2G2tAWoDUmSlK5iqhDC0kYAqrVDqUg2mcCa0/08b5R4WylxBqBCuYZKRFbFwcEB1oL5j5ZZD5aQpilOTs4+xo1DdwH4ghAiFkI8I4T4gcv8j5WQiwt2nlgmQ6+rkiiK4FhnW+nZvddr5QDOEoBJ/1rdUI5yUXQ6VgToC7iyc4NOAlA5eGnJR1o5hlU7gIvCzs4OrKVg7BmAye88C+yeALsniD/8+9nXI8glD9s7+gjAVquFF55/Hrh/soMmluuwVpfx5S9/+RJbVoynvvpV4Pp95RyY6/fhmWeeqXSxe73nWMrG2RdHsnGMa9euVepCTToCovXEB3DykX+W/2k98YH8Z0oA6lIIJi88UjLKQKfQwyztZX4BWHWEhUKtRRNZvI8mMoFzxvoR54USb8vusID6uad/GTdPbuHmyS38k9/9X/FzT//yqdeq11TtAB4eHmLVHV/Q6X1Pfgw3j7Zx82gb//hT/w7ve/Jjp65Z9bINqYsSsnqsLk9zB8A/BPC9AL4bwGcA/KQQ4m9dVgOUiIgLxospoaiD+IjjGJP0XztKEAQB3v3udyMIArSj8e/PFnoJQM/zZgrAKO1fqxuWVW5iSDWrAqqeg9HmRBGGnqdRnacEoA67or6fnTtXtilKMKrXa0koh+4DwgnPmgZrk52dHWBpfB+VeydAmGR/bh9mX4+y7GN7u9oCJIN85StfQZqmsF7fz4eLn/g84ic+P3zhA9fxxS9/SYu+oDg+PsbtW7cgbpzO5Ys/9QTiTz0x9nXWjfvQ7XTw8ssvX3ALJ6PyD9PGOSyOGke4/0Zx5+0iePXVV2G5PsTS+tD3k73XEN95Pv+T7PXP/RNeDc7SujZnAQoheiJoeLKOwvbwPBEOF5iTMtVmszNNx4vRbtgaeg/d8HQBIiFE5TnWitwBLCMA00SbqCN11M+yO+zKv3J8C+24g3bcwdcOXsArx6dz5JZ6r7ko56wohwcHuYgb5ebxNtpxF+24i6/tvYqbx6c3NVf87LWHh4cX0r7q7aoxSCl/HcCvD3zrMSFEAOCHhRD/ixwZXYQQ3w/g+wHgwQcfPJc2lHYAe2cU6OAAJkkCZ4JwaMUx3vnO78J73vMeSCnxxEd/bex1SgDqsljxfR/xjCowscZOjWVZSGVxMaebA6ieg9HmRCHwzne+M3+efuM3PjT0c/UY6vAcKQFX1gFMetcHwRw5a+dI/iyMC0vvyqH78KGPf2Ts7xCy+mfq7vY9yKUziOnlAEfP3K08wV/x+c9/HsKxIW70q2jKvcNT14k33EDrmZfw3HPP4e1vf/sltnAyTz/9NADAunG68mQ6pfy4uv6rX/0qHnnkkYtp3AyuX7+eHSB+cjjxmqln/w3SOMb993/b+TRsTl555RVY6zfKb/qt3YebN/VwAAG12TkqAFtD49NHP97fWJBSQkqpjfBIUwkxJla+Gw2/h9/82OnNER0FYFIi6T2R+ghAJd7qbvmw7KWe61b1ebHHx8d4y0ax6srjWO69j4tyMqufPYvzAQD/VwAPY6QaqJTyvQDeCwDveMc7zmWPW4mIqKgD2Ntl0cEBnFa5s+44eOyxxyClxOOPP44b3vhHQL1cl8HM8zxE8fRbG/UEoo4C0LbtUjmAqWY5gOo5GH2sXA9Dz1MwEu2gkwC0bRuOYyONy7VFlyIw+bMw7jnyxdB9wPKERaQUlT9Te7t7wKPzF9sQSz5SKbG/v19pFUrF7/7e7wEPXIeYETplvf5+JAA+97nPaSMAn3rqKcCy8sqehVlZgVWv46mnnsJ3f/d3X0zjZuA4DrauXcfB8WQHcNrZfwoZdpG0W7j//uLHL1wEN195FdZa+Q1se/0GXr35eW0qdluWBTmybnC9+tD45C8NuK0anaGcM+Zj9N3h97BaG+MYywkvroB+FFvxHc8kjeEG1a9hgUy8CQjUnPKbhcoBrFIAqty9lRtznHfbY8XLXnvVQkDHIUf+vlD6nac/kD20tom646LuuPi6azfw0Fq/ZHSU6BMCOo2aa6PT6eBDH/oQOp0Oau74Rcu4HbAqyXIAJVIp8cCahcABAgd48zWBB9ayxzjWOAQ0O1ak+GeaptlkXvViXZEkydgCMK6Loedp9PHPTStNNhJ8388dPcXyFmC72Z+1+7OvB1HX12rzD+TnQd8BHPNDTwzdB3jjn7WqHcB2u41Ouw1RP4MD2HMPL/KA3KLcunULt2/dgvXgAzOvFTUf1o0tfOrTn76ElhXjK08+CWvrGkTJeUsIAdy4gS9XXNTm9a97AJjiABYhPc7OC3vggdn38KLodrvY292BVaIAjMJavw+tZvPCwsTKkjmAw5tsrlcbnie8/liq3EKtBOCYVabv1Yfegz8mtE9CnumUnvMkzwEcEIBvWHsINaeGmlPDW7bejjesPTT0mjiN4Wiyhm21WghcH9Yc+Zi+7UFAoNU6n3NC56HdbiOVEkvu/JFDy1722osSsiY5gN8DYBfAzcv4z5SQCweci+/95v8Tbh5l53r88Lf/6aHrlVOoo/hYBNTnGifAn/0DDu4cZZPGD/zn/c870jgE1HGcsZF7k0hTwD7jWY7niZTyTGdZ6JIYH9QCJNHwpPDIHxZo7GXt+wPfdXr2Tnp5jVULQLUhkJZ5kEZJqt2kUuci4QwhoEo87u7unkeTzsQTT2RhYNZDry90vXjodXj+976C7e3tyt3LMAzxzDPPQLz96+Z6vbj/Aex++lOVvpfXve51+Mqzz53pd8ijTAC+/vXF7uFFcOvWrSwMcq3852ivZaLxtddeq/wge6A315UIO0x7AkWHcG4gm+bmP5dw/gIy5804B/B7vvGv4LWjbAn9//yj/69Tr4nTGJ4mArDZbKI+oYDKLCxhIXB9NJvnc07oPCjRdhYB6FoOHMu+sPehx5M6ghDil4QQPySEeKcQ4s8IId4H4L8E8GOj+X8XhcoXigqGroU9m0CXQhFnXW6rAVCHkBJg8H5Mvkb9TJd7MEi2cC9+fSr1Cf8EemHF87xQ9F+vA7VaLRd0RUl711edAwgAjusAZ4mm1UUA1s+wSdN77cHBwTm06Gz81m/9FqzrmxArxUp9W296A4C+cKySZ555BnEUQTwwX+ij1XPMvvKVr5xns0rxhje8AWm7Bdltz754AmlPAL7uda87r2aVRhVxsdbLC0D1Gl0KwTiuC1lKAOpTQR0oX7BtEKnROXpqnI/S4hNeksbZHKMBrVYLgT3/Wi5wgkodQCUA6+4ZNjuFwJJXu3LHQDwD4PsA/BKA9wP4egD/tZTyn19WA5SICAvGTyunUIcQUNu2kZ5xwa1bDloxASiHrtWJzAEsEwKqz4R4FtQ71kUALtWXSwvAuHd9lWeEKVzP7R94OQcikZU+V0q0idoZBGAtG2OrDnm7c+cOnn32WYg3v6Hwa8T6KqytDXz8E5+4wJYVQwk36/75Qh/F5iYs36/0aIs3vCH77NPD/bl/hzzaw8bmVqUO/61bWSXDeRxAa3kTwrJx+/bt827WXDi2jXQ0zn4KujmAjuOcCmEtipSpNmumPGqqhACM0kib9VOn04Fvzz9PBLaXpUNUhBKf8+QwDhI4Htrt+Te4pqGlAJRS/gMp5duklHUpZU1K+W1SyvddZhtU5wkLOoDKKdSh8ziOU/gA+0mo1+s3mE1+XzpXAXVdt9TxA3ECuJpMiIvE0tISkqicl5lEgOe5WixQfN8HznAyi0xkpU5mLtrO4AAKy4JV8yp3AD/+8Y8DAKxHyhXuEI++Ec8+80y+6K+KL335y7A2tyDmfB6EZQE3buBLFQrAN77xjQCA9HD+fFB5uI+HHnzjeTVpLm7fvg1naQ1iDrdAWBbstWv6OICOk4u6IiixqMP4CqgN9PkEYKpRFc3+pnlY+DVRGmqzfmq32/Ct+dviWdUKQCXaAudsn2fNdi/MydRSAOpA7gAW3MkKNRKAtm2fxSQAACS9SFtdBjO1aA2n3I5Q4xBQ13VLifI0hTahGEAWijDPI6Veo0socb1en0sABrXqwz8BwPd8YEY13GnIqFoBmFcz888YKVHzLqwyWhHSNMXjv/7rsF5/X+HwT4X1locAIfDRj370glo3myiK8NRTT0GcsfCJeOB1uH3rVmUFeR544IGswvKcAlBKCXm4d27HR83La7duAavzl4sXK9dx65YeDqDneUjKOIC9a3URHlm6xpwCMNXnPMO+iVHCAUz0EYDdTvdMDqBvu1oIQN8+21zn2+7VcgB1QImIbsGS8V2NcgA9z0N8xpC7KNXrSIV8N2tKHp0KD9UhV2uUTAAWvz5J9QgnVgghUOocC4Vm5xlmDmC518QhsLy0fDENKkkQ1CCj+fNTZJRWOkYdHx/D8l2IMxY4kp5zYWcjFeELX/gCtu/dg3jbm0u/VizVYb3xfjz2+OOI4zPYuWfg2WefRdjtQpwx783qvb6qMFDbtvH6N7wB6f58BYFk8wRp2K1cAN66dRvWyvwC0Fq7jtt3bmsRau95HtISg2zSu1aXtUYWQTWfAEzSWJt5ez4HUJ8Q0DAM4Vrzf5ae5SIMi7/386bb7QI4uwD0bAdh73edN3qsyjRE5QN0Cw5k3TiC4zhahDF4noewjNoYg3q9LoNyPphNWS/pnAPoeR7iEs5NJgD1+OyBngM4v/7ThqWlJcTdcq2KQ2B5WQ8BuLRUB+YUgNAgl/H4+BjiPM6Zqrk4rNAB/Miv/AqsWpAXdSmL9fWP4vDgAJ/61KfOuWXF+OIXv5i146wO4NYWLN/Pf18VvOnhh4HD+QRgepC97uGHHz6/BpWk0+ng8GAf1lrJsxgHsFavIex2K8+LBQDf95DExQWgEou6CCfXdUuFsA6SpJE27yOPmkqKi4cw7mqzgR6GIVx7/vW0YzkIu9UJQCU+z/IegEzIdjoUgJeK6gTdgju03SRGoInw8DwvF0PzEiUpHMfRxrnpD2aT35cKD9VVACapLLxDGyd6vQ91kH1ZEahq9uoSSry8vIw4kpAlwnGTEFheXrnAVhWnXqvDKhnCmtMTjlUWu2g0GpDeOWySeU5lh/zeuXMHn/n0p4G3vWnm4e+TEG+8H9bqMn7pg790zq0rxhe/9CVYW/Pn/ymyPMD78YUKBeDDDz+M5PgQMiq/2JP7OwCAhx56aMaVF8e9e/cAAPbK1owrJ6Nee+fOnXNp01nIHMDi90KJRV02m7Mzh0uGifRIEv0cwKICUEqJrkYCMIoiuNb8c4VbsQMYRb2NDetsax/HthGX2FApgx6rew3JQ0ALxrJ34xi1oNpzwhS1Wg2dgqGrk+jGKWqBPgIkH8ymOoCZU6XLADyIan/R25IJQD0GYqAfwllWAOpWTXZpKcvXikvMC0loaeMA1ut1YN45LZT931ERjWYT0juHZ8Fz0GpVc8bTBz/4QUAI2N/46Ny/Q1gWxDe+BU9/9Wk8/fTT59i62YRhiK8+9RTEA+dz7IF43etw984d7OzsnMvvK4ty75SbV4Z0fwdr6xtYW1s751YV5+7duwAA6wwC0FrdGvpdVZLlAJYQgL1rddnwzNo/34I7TvRxAPtr2GICME5jpDLVRgDGcQxbzC8AbctGcsZ18FlQ4f3OWQWgsBFf0PugAJyAZVnwPQ+dgg5gJ4m1KRQRBAE6cXymfIBOnCDQRNACxY6BCJMs/ESXgiOD5IeyFuzHiYYOIIBSZxkC+jmAKyuZkxeXiKjQKQR0eXkZ6M4Z3t17XZXvpdFoAOfkAHbaHSRlSuueAwcHB/i1xx6DePRBiKWzCWnr7W+CFfj4hV/4hXNqXTG+9rWvIYqiM+f/KVQe4Je+9KVz+X1ledOb3gQASPe2S79WHuzgkUfK53GeJ8oBPJMAXN4c+l1VEgRBOQcw6uav0wHP8xCV2SEcIE5CbeZt27bhuR66BSc7lSuoy31IkgS2mF+i2MKaO5fzPFAC0DrDewAA27LoAFZB5qQVFIBxjJoG54QBvUqHqcwLucxDJ04rDRUbRQ1KUwVgLLUJwx2ltAOYCm1CYoB+ie7SDmA6/PqqUQKwaLSYlBJRJ81fVzXLy8tIu8l8mzu93McqBWC73Qbcs28GiJ6L2L2g5PhJfPCDH0QUhrC/5evO/LuE60J8w6P4zGc+gxdeeOEcWlcMJdTOmv+nEFtbsIKgMgF4//33w/cDpPvlBKBMU6T7u3hzT0BWxfb2NoTtQNTnH2OE68OuLWF7u7wIPm9830dcIhw37gkUXYRTEASIovnGlSjSJ4QSyN5LNy5WCbMTt/PX6ECSJGcST5awkJ6xFsZZSHuLH+uMhoQQolTKShkoAKeQCcBiyrsTR9oIJhXmdpYw0FacYFmTRS8weAzE5I4QJfoMXqPkArZgbnkcC63ei3Iwy26oKQGoS1hM7gAWrA6dxtl70EUArqysZJV15igEIzUQgN1uF5gzb24I5/IF4MHBAT70oQ/BeuRBiI3Vc/md1je9FZbn4d++7/KOuf3Sl74E69o1iHNacAshgPvvxxcrEoCWZeHhNz0MWdIBlEf7kEmMN7+5WgdwZ2cH9vI6xBmdArG0qY0ATEqEWCSaCUDf95HKFHHJMNAkyUIoddq4rdXqJQRgdl2VKQKDpGl6JvFkCTH3cR7ngdqkPasAtCByMXneUABOoV6vFxeASaxNx1ECsDktYW4GrSjRJuwNGDzTZvI1YayvACzrAOomZpWAK7uhpsZf3QRg0Q3eqDP8uqrJ29GZY0ewk9281dXzES/z0O12z8UBVALwMs95+sVf/EV0wxD2t33Duf1O4XsQ3/xWfPpTn8Izzzxzbr93EmEY4qtPP33m8/9GEQ+8Dvfu3q1MgLzl0Uch93dKOePpXhYuqYMARH39zL9HLK1hZ2e+aqjnSRAEiEs4aLFmIaBqIz+Kyo0tYZQ5aLqsAwGgXq+hkxR7H0oo6mJkZJxFPOmXCjQ3F5TWRAE4hVq9jnZBAdiOY206jloktqbFS86gFadaCUDLshD43oyD4CWCmj6D7yBlHcAorvbA7lHmdQATzUJAlfgpukGt1jFViqZB8na05xGA2WuqFLNRGAJnPAMQAOBkv+Oyqrzdu3cvO/rhrQ+fm/unsL7prbBqAf73f/W/X/g5bs8++yziKDq3AjAK64H7AQBf+cpXzvX3FuXNb34z0m4HslH8bMh0bxu2beONb3zjBbZsNts7uxBLZy9CYy1tYGe3egFYq9UQxyFkQddCCUBd1k+qHWHRMJEeoYYCql6voxsXO0S8m+jXfpNRhfPSM47pEvLMLuIkKACnsLS0hHbhHMBIm50ftcBrnMEBbISRNq6Hwg+C6cdAJELbwasvAGcPBlJKhBUf2D2KakvZmhvqel3E7PLyMoQQhR3AWFcB2JkjJKSTor5Ur6wgT5qmkFJCWOcwmfV+x2UVgfnZn/1ZpJCw3/GNM6+Nn/g85N4h5N4hoo98AvETn596vfBciG/9Onzpi1/CZz/72fNq8liUQLPuvzH1uvhTT0Du7UHu7SH8lY8g/tQTU68Xm1uwPA9PPfXUubW1DI888giAvqtXhHT3Hh586KFKoxOklDg42IdVP7sAFPVVNBsnefn5qlBzcFxQQMVxB7btaBMlkgvA0g6gfgKqvlTPQztn0e45mCqCTA/OIp6qPYVYFSM8qwBMz2vOHAMF4BTq9To6BePAW2GoTcdRJa1P5hSAcZqiFcaVlsYeRy0IZjiA+gvAIiGgSZoVW9HpvagQ3HkFoC55EbZtY2m5jqJzu7pOl76wvr4OAJDzOIAtmb++CnKxNm0yC2MEQYB3v/vdWZ+Z1OF7k2tccIPuLDz77LP4+Mc/DvGNb4VYnr3JJ/cOgTACwgjyzk729Qysr38E1toKfuq9771QUfvUU0/B3tiAmFHhOd3bA8IQCEPIO3eyr6cgLAu47z58uSIH8OGHH4YQAuluiSqY+zt4y6PzH+VxHrTbbURhCKt+9g0mq5Zt2FZ9GHwuAMOCAjDsaDXXqY38blTMOVN0NQwBXVpaQicp9j5UERhd1rGWZSGVpzc623FnaI5oTxC4qZSwzngEw1nI02bk+PG83SsYlL+PCbvScZrAcS5mc4QCcApLS0toFdhNC5MEcZpo0/FzAdidb3GknENdFr2KYKYA1MdpGkU9G2GB/QQVJqrTpJjnMJZ8pNQxmjq5mWura8YLQLTLO4CynWJzY/N8G1SCPJF9WjhLN8Y73/lOvOc978F3fud3ApPGsEtyAKWU+Mmf/ElYtQD2t5698uckhG3D+kPfhFdfeQWPPfbYhfwfUko89dWvQt5334X8fnHjBl595RU0m5d/PmOtVsMDr3t94aMg0lYDSatRef7fwcEBAEDUzh5tI3oiUv3OqlBzXdEcujhqazXXqdSXbtgq9Tp1vU6pM/V6He2o2PtQ1+myjs0E4OmNzlbUHpojWhOEeipTWOeRbjAnKtImnhAK3Yq7w+9jQl5KJgAvRsjqkZijKVnnmZ1joq7RZeekXq/DcRwcF1EbYzju6ikAa/U6ulOcD52LwJTJAQw1FICq/WXX23GchULoEt4DAOvrG3ht/3aha6NO1n5dJvV6vQ7HdZC0ygtAqyMqdQAL4Tt47LHHIKXE448/DixPn6Iu+szP3/md38GTTz4J+9u/DcK72GdYvOkNsB64jp/52Z/FH//jf/zc55Pbt2+j2WjAuW96+Oe8WPfdQCIlnn32WXzrt37rhfwf03jLo4/g3heKVSJVTqEKHa2K4+MsZ9EKzj6+WMHS0O+sCiUg4oIOWhR1UD/jmZrniep38zqAuqwDgV4aU8H30Y71EoC2bSMZ4wDW3drQHHHDHX9+ZirTPA+vClTUU5SMX/TVHX/4fXjjowCiNIFfu5gNdDqAU1haWkKUJIhmrHqVS6hLxxFCYGN9Dced0wLwwbU6ao6NmmPj7VsreHDtdJuPutnrNjercwvGUavVEcWTF3zdSGpzD0bJHcCBseD6uoDnAp4LvP569jUAKNNZJwHYz+sY/v7GBuC62Z/r92VfDxLHQBD4F75QL8P6+jriTrGhL+oAKyvL2hxkL0RPxI0IQHHNATxkf17nZF+P0kwr7dOFngHPQafTwYc+9KGswueMQ+Mv8rkKwxDv/emfhrW5DuvtF+8UCSFg/ZFvwcnJ8YUcDv/ss89m/8/16+f+uwd/r/p/LptHHnkEyfEhZHe286ScwqoF4NHREQBABGcXDaInItXvrIrcAQz7wmP92kNwvBocr4ZrD7wd69ceyn8WhS0s1fUSTQDQ6Q472Tc2H4Lv1uG7dbzxxtfhxuZDQz/vhs2h1+vA8vIy4iTKD3mfRidqoxbUtJnrXMcZGz5Zc4KhOaLmjN/0j9Ok0o1nFfUUpuMF4Nu33og0SvCrH/kV3PBW8fat8cWooiSCd0ERVHQAp6A6cisOsWZPXoy3Yr0cQADY2NzE0eHpfIi//M0P4pWjbKfn73/728e+9qgnHDdGV/MVU6vVECbjF3yplAjjVFsH0PM8WJY1VATmj/1BGzuH2eDwF/9EvysqkaiTmM1zGEfGsj/4DkBFHP3J7zj9ujgGgppe92Rtba14FdCOfk741tY17DaGF3nWty8h2c1ujv3u0+2VsUTaTfTY1DmP3PxeaNBFCsCPfOQjuHf3Lpx3/Z+zHLdLwLq+CestD+OXPvhBfNd3fRceOMfjGp5//nkI24bYvJhxXQQB7NVVPP/88xfy+2fRLwSzDft1D069Nt27h2v33Ve5s99oNAAAwj/7WK9+h/qdVaHWQdFACOW3/NHvxeHuTQDAH/tzPzx0fRy2sbx8MZsS86CK33XCYQH4p/7Q9+LefvYe/vJ3/vCp17V7glGn4nnqXrSjNlx7eh5+K2pheUmPSBcgy6GLJ4inIsRpDNetTuIoAdidcJLA937jn8LN42wj6of/0/9q4u/pJjGWLkgA0gGcQi4AZ4RStnohoFVPJoNsbm7hcM4cQOUA6igAuxPMWHXihU6u2SBCCNRrQaEcwLB3yLdOArB/NlK518VxVrxHJ9bX1xG200Il96NOFjKqE9e2tmCVS0/JHcMq+7Q6CqRoefip9KoBX9TxIsfHx/i5n/95WG98ANYb77+Q/2MS9h/6JqQAfuZnfuZcf++LL74IsbEBcYGFEeTGJp5/4YUL+/3TUPl8hSqB7m3jLRW7fwDyfEnhnX3eEl4w9DurIg8BDYuFHsZRW6u5zvM8eJ5/SgDOohM24Xm+NgXPgP6aVIV3TqMdtbC0rI+J4boeojMIwCiN4brV3Qu1ZuoWcF+n0Ukv7oQBCsApqM7TmpEHqKMA3NrawmFnvs5z0A5RCwKtBmUgc6G6E45RUK6Zrg4g0BOwRQSghjmA/byOcq+LImBJo11FIBOAUhY7CzDuWHq4ZgNsbW0BzZIiqnf91tb4fInLwLIsWLbdPxzyLPRE5EUJwF/8xV9Eq9mE9Z9884X8/mmIpTrEN70Vn/zkJ/Hcc8+d2+996eWXT8donzNicwN3bt+u5CiCzc1NrKyuzSwEI6MIydF+5eGfwKAAPPu8JWwXwnYqF4Bq4zzsFtulisKWVtFTALCyvIx2t5yT2uk2tFoDAgNr2AJithU1tRKAnu8hKliFfxxRGsHzqxOAas3Ujs8oAOOQArAKVOdpzjg0rBnqKQBPuiGiORZbB50I165Vt1CcRL1ez92xUZQw1Ek0jVJfWiroAGZ/6zQpep4Hx7FLO4C6CkAAKLJBHbahXeGUra0tpN0EckJfGEtPAF67du2CWlUMx3GA9BxiQHvj2kXkeOzt7eHDH/4wrLc8BGtr/dx/fxHsP/A2WIGPn/nZnz2X39dut7G/twdxwW62WF9Hmqa4fbtYkaVz/b+FwKOPPgK5P10Apgc7gJSVVwAFgG63CwgLsM5nI8Ny/ex3VsjS0lJ21mqBKppSSoSdplZrJwBYXVtDu3tS6jWt7ol26QJ9E2O2AGzHTW3OuwV6G/7p/OIpTKNKDYF++O3Z+mMr6l7YWpACcArqQ28a6ACqhd5Bp3wHOuhE2LqmT0y+IggCRIlEMmYB2dXQNRtlaWm5lADUzYGt1WpzhIBa2t0TJehmFUdLE4mom2onAHMRV8IFlJoIQD/w+/HaZ6F3oOZFTPDvf//7EcVxoUPfLwrhexDf/DZ87rOfxde+9rUz/z4lyMTaxS7wRG8BXIUABIBH3vxmpPu7U8OMdSkAAwCdTgeWe35FsoTrZcWTKsSyrKxgW3e26EjiEGmaaLV2AoC1tVV0SjqA7e4J1i64f5WljABsRnoJcc/3zhQ+GaZRpcdP9Q2k+ftjKiVaYefC7gsF4BT6N3D6Q9iMQliWpVX44fVeRbb9dnkLfb8T4b4LOivqLCghMe4sQDME4BLCKVVMFd1ITzdzeXlpLgdQp6R4oLgDqMZtbQVgo4S730jhum7l96JWq52PAOz9jvPuI8fHx/jV//AfYD36IMRqtYsh6xseheV7+Pf//t+f+Xdtb2eiRyxf7P1Xv1/9f5fNm9/8Zsgkhjzan3hNur8NPwhw48bFHIdRhjAMIc4zjNl2EYZnCzk7D5aWlgo5gOoanaJdgKzwV1kHsN1taOcAqvG+iABsRc3K54dBarUawjM4gJ2kW+kaSn2WjTMIwHbchYSkAKwCdQObMwbUZhRiuRf2oAtKAO61y9nPcZrisB3mr9cJ5YiNq20TGhACury8jDAqIABDoFYLtCnHrFheXkHZtUXYldpN7iqnb5YDqASibsWQVN+UZfIAGym2rm9VPkbVglqxwzBnIMMEQohz3+F9/PHHEXa7sP7A+ArJl4nwXODr3oxPfepTuHevQGGTKezu7ma/86L7Yq0GYVn5/3fZvOlNbwKAqXmAcm8HDz/8cKVnhCniOIY4p/BPABCWjXi0VHMFrKysICzgAKprdHKegEwAtsoKwM6xvgJwRg5gksboRhfnNM1DvV5H5wz5c+24U+l60PM8BH6ARsFiSOM46b32okJzqx8BNcb3fbiuO9sBDEOsXPDOaln6DmC5DnTYiSCl1FIAKod1XCEYUxzAboG8rTACljQ6GFexvLyCGV1hiDQFoujidq/mZXl5GbZtIZyxMRdpKgBzB/CkhJPWkLhxvXrHY2VlZfwOTlnCGLV6/VwFrZQSv/bYY7Duv15Z7t8o9tc/CiklPvrRj57p9xweHmb/uOAjWYQQsGq1/v93ybzxjW+EZVlI93fG/lxKCXmwg0c0yP8DgCRJgHMUolIbAbhcKAQ00vDoBCCL+mh3GkgKVqFMkhjtblO7aBHHcVALamhG08NZmz2BqFMOYK1WQzuZzz2TUqITVesAAtnneXIGAdjoOeQXtbFAATiD5aUlNMMZRWCiLpY1G8BqtRpWV1aw1yonAHd71+sQHjPKuMPUFWpNqVve3CBLS0vohHLm8QNdDQunAJlwiqLiQ4YKF9VNAFqWhbW1NcyKUFLjtm6TehAEWF5ZLhUCajWlFmHdqysrEOE5hIB2o3NfND7//PO4fesWxFsfmn3xJSFWlmC9/j58/BOfONPvaTQasDzvQo+AyPF9nJyUc0/OC8/z8LrXvz4r9DIG2Woi7bTx8MMPX27DJiClBM7TlRei0PE2F83KygqiApUnw16enY4CEADanWLPsXILdZsrgOyzbYbTBWAr0u8+LC0toR2253qewzRCKtPK14Pr62s4LrARMomjLgVgpawsrxTIAYywsqpPx1HcuHEjF3RF2Wt189fqRn6uylgBaEYIaJpKJDPWv90IWFnRZydOsbq6WioEVBWj02lXUbGxsWlsCCgA3HfffZAFBaBMJZJGrIUAXFlZgShyFsosOvG5L1Y+85nPAACsh99wrr/3rIiH34Dbt27h1q1bc/+OVqsFcQEVU8chXbfSQiRvevhh4HBv7M9kTxg+9JA+In8RKRwC2tHXAQSAZueo0PXN9tHQ63RidXV1Zg6gcgB1ug/Ly8tIZIowLT9ftHqTe9WbzxubmzgukAs7CSUeL2oNQgE4g5XVlZk5gK04rPxBG8eN++/HbskQUCUYdVgsjtIXgGNCQKPha3RE5cJ1ZoxnYSS0fJ5WVlbQ7aYouiGnuo1Ok4pic3MTUWf6znvUBoJaoFVxJ8WN+27AKlqkrpkCElqEda+trSFth2d2KUQnwsY5L7a+/JWvwLq2AVGrrnLcOKw3ZJtxX/7yl+f+HXEcA5eUUywtq9IwxIceegjJ0QHkmENL04Pd/BodEEKg8IBaBCkrz/MFenNFpzGzn+vqAKoFd7N9XOj6Vk8o6rhZmK1hZ4SA9hxAnTZr1XqpNWundgytWA8BuL6+jsMCTvgklAN4URsLFIAzWFldRXNGImojDLXqOIr7778fu61uqcXWTquLzY11eF51B2hOYmoRmARwXefCDoY+D9Rg1J2hybuaCsDV1VWkKVB0bacip3Wb3IGeAGxPXyiFLT13dIGeA3iSFOvbJ2n+mqpZX1+HTNLxcdwlEO3o3Bdbzz//PHBNvwUc1lZgeS5efPHFuX/FuYcaTkUgnXIMw0Xz4IMPAlIiHVMJND3Yw9LysjYLddu2s2Tpc0KkiRZz4MrKCtIkRhJPT58Ju00IYVUeqjdKXwAeFrpeOYC6PFeDrK6uohnPygHUT4j3q/CXd9DUa6peR21tbeGo00Qq5+vjB50GVpdXLmw9TgE4g5WV6SGgqZRodjtadRzF/fffjyhJcVQi5Gqn1cUDD7zuAls1P/0iMKd/1o0kaho6NYMUFYCdUL/KmUB/d7DoOcN6h4BuIGxPz8cMO8C1rWrPzZvEjRs3IMMUCGcLQKmRAMwXSCVD0weRUiJtd891sdVut9FsNCDW9Nt4EUIAK0tnqgR63kJjGiJNKxUhDz74IABAHpwOA5WHe3jwwQe1cMkAwHVdyIKFRoogNRGAaswPO9OFR9hpYHllWYuKrIP0BWC5EFBtBeAMB7ARZjmMOlUxVc9Q4wwCsOq1x9bWFqSUuZNXlsNOA5tbW+fcqj569ToNWVlZQWNKEZh2FEJCr50Txf333w8A2G4WPwpipx3h/gceuKgmnYm+Azi+CqjO4Z9A/xnpTKkEmqYS3TDV8nmaVwDq6KJtbGwgTSWmbVDHbUvLCR0YEHMnBRb1vWqhOghAdQSHbJU7nmaITgSZpPnvOg+azV6YjoaRDwAgPbffxjkIggDyksIyRRJXegDz61//egghkI7LAzzax4NvfOPlN2oCruuODVWdmzis9LNX9OeKWQLwBKsa5rvXajUEQQ2Ngg5go32IIKhpuQZZXV1FqzvdhWqGDTi2o1X7++folR/3VPXMqtdRqmL3fsFiQqPsd0+wdY0CsDJWVlbQiSLE6fjKHY1eolPVVvM4HugJuZ2CAjBOU+y3urlw1I0gCCCEwDhDsxvrXQEUKOYAhr33VvXANQ61O9gtWN+h2wVsW7/wHqC/UzstPzts67mjCwwUaSokAFOsrq1qkcuY5yGW2JQ6Re+1+XEY50r1FRQncgbXanl5GWmnczkVIsOw0ggG3/exde36qRBQ2e0gaTXwRo0EYBAESKOz58QqZBxq0c+LOoDdbgNra/oJQCDbrGq0Dwpd22gfnOuG1HmyuroKCTn1LMBm2MgKdGnijAMDDuAcRVSUaKx6HZULwPZ8AvCg27jQjVuhQ8ng8+QdKyvyc9/2bef2+3b39nDr1i28dfM6bMvCzd6k8tBa1tk7UYSXjvbxpocfrtxuHiWVEl/5yldwre7hWr2/K/jKYdahHlwfXpiHSYoXD5p44xvfiE1NF75fefJJrHgpVCX5B9ayAevOkYTl1vHoo49W2LrpxEmCp556CuvLwHIta/fOYdb/rq+L3jUSd/eh5T3odrv42jPPYHUVGFxjHPTmyNHmnpwAUWTjG77+Gy6vkQVpNJt44YUXsLQJuB7Q6K0Vl3tzuJTA0b3MRb+hgXM2ShTH+OpXvwqsWRBL2T6e3M06hbg2XOxD7iWoWQHe+pa3XHo7R0nSFE8++STESgCsnF6oyt3GcH6g50BcG9lc60SQ+008+uijWDqnzYU0TfGVJ5+EWFmCWD7b73yxHeJ9X/8N+I53vQu/8Wu/hu/96lN4c+1szqLc2cfq0jIenrN4yc7uLm7fvg3rxo1C58692G7jfV//9QPv4at4c0F3IL17F9e3tvC611WXSvDCiy+i2Q1hXetvZsooRLp7Fw8/9JA2oW73trdx9+5dOPc/Aojx9+WF9h7+7de/Pb8X//VXv4ZHauNcAYn4zvO47/r1fPO3KjqdDp559lmsbrwefi1bFx3u3gQArF/rP8MHOy+iXvOzyq2a8fwLLyAOU9zYfDj/3r397D3c2Bzuh/f2X4bjWXj0kUcus4mFODg4wCuvvoqH198M1/bw2tErAIA3rD2YX3Pn5DXEIsbb3vbWqpp5CjUmX69t4lqtv7i4eXwLrbi/C113Ajy0+vqh12639rDfOcI3ffM3oUpJq+bpG/V1bNZOi9GbR9sAgIfWTq8xpAS+tv8qbty4gfvPUJVf/Mf/+PtSyneM+1n1weKaY/cqp8VpCtuyENjDpbSTnq1uaxB3P4olBFzXQZQMuwSBM36iUdf5moZBAYBtWUhlCm+koF0qAeeSqtzNi91beA2m4rgjj03a24/R8b2o3JLRVKLR96BIU2iRjzIO1S7Z20iwR5qpomV0br8QAnIwqs8dP9WJBPADPfq0bVmwbRtJks4/MffGKe8cjzWwLAuu45xL9coXl5bxHe96F37gr//17OubN/Hm9Aw5jwBknJxpXHZ7n5VMEogiAnBpacx7KOA2pxKQMv//qsL3fTSbI85BL9TS0yBEUqHWF5DpZAE4ci9euPkqHhl3K3qb+bYGc4edzxX9/uS4pz93mSZaznVA1mfCzvAz5Lnj3dU0TeCOeX86oOawJE3g2oDvnG5nkiZwfL3ug2VZsIRAMiH6bhpJmsBx7ErFH5B99pYQEyMIA2fyOBn1+s55znOj6Lm6OQtvexvwyU+e26978fd/H3//7/99/Mi3/2m87doNqO6vUoOfePVF/IvP/Q7+1b/6V1jSKLRE8a//+/8e7dsv4Ye//evy76mbPloj7eMvbuPffvkmfuEXfgFLF5h4ehb+v3/1v8UG7uKv/CdZp1ABGv/0YzHe/i1/FD/8wz9cXeNmIAD86J//c3jr6zv4Y39w/GB7826KX/6PKX7iJ34C3/ANejlnlpT4B3/mu/DIW2J8y7fOvv5jvw684Q3fgh//8R+/+MaVJGk28Xfe/W68+Q8Bb/im09PE8bbEF38F+LEf+zFs/eE/XEELpyMA/MT3/VXc8ndgf+fkMBcpJeR7D/AX/vxfwPd///dfXgOn8L/99ffgxfAQ9nd9y6mfxR/+feD2Yf8br1uH8+eGIzqSTz8P68lb+A+/+quF3KyivP8f/SN8+stfhP2XvutMoVDhB34dweOPIwHw+OOPo/ONX4ePf8+fnvv3pXd2EH/kE/iRH/kRPPCf/Wdz/Y7tZ5/F3/nBH4TzHd8B+01vnnl995c+MPIevhGf+AvfM7utOzuIfvmD+JEf+RFcn7Ot58FnPvABvPe970X9v/mbEEHm6Ib///bOO0ySon7cb23O+XLijoxwIJIkI2AAJCgKiiiCiAERERVFEHP4+jOLOWfBBCpmwYAkRQQlSpJ43N3ubZg8Xb8/PlXbPb2ze7t7M9Pds/U+zzy709MzUzXdVfXJ9Y+/kr/5T1x99dUQEyXw9j/+kQ9+8IP0nHIJjX3lrfyjV36Q5sC1yO++Nzec/PYp53kTW9jy7Ys577zzOO6446rc8plpKBZ5y/Oex277vJDd9jmp7Dlaa376lTN5wUkncvbZZ9e4hVvnV1/4Alf97Odc8NKvTJkPHgz8r7XmY989i+NPOI5zzjmnpm2cDY+bsX/Ofm9i/dK9J48HdxV937VvY8c9t+eSSy6pfQNn4CMvO53tm1bymvUvmzz26Rs/w13D/518vkv/9rxj/3NL3nf537/MSGeKL3zxCzVrazkU8LEzXskK3cV5+5w45XU7C42Uee+/Nz7EB//2fT784Q8z8PRZCFzTNmL6tczlAG4FPxG1vAXXFoiJW/inZdny5WxIzS7JfMNEhtaWltjGsgO0d3SUrSCfS0ARGIDu7i4yMzgDMjHeO08pRW9vz+xzAHMNsSwAA5Iv2tzcPLnZexi79VCcx8KypctoGNtKCH9Kows6Vnm9y5YuQ42XzwFUg92wvG/yoQbLjIOxNIsWL6p45cD99tsPb2wCvWlkmz6nYdkiMp1t/PT3vyXT2UbDsm3bf9F78FEaGhvZa6+95v0ZK1fK5vZ6ZGRW5zcuW0ams5Of/v73ZDo7aZxlSKEeEZNc1Hl2NvzUGx2ZPKZHR+jr749FkRSLzQvXmenzs5qW7Ui+c5Crfv8n8p2DNC0rH8qts/EofQ/ihezs7CI3Q/GLYiFLsZCPrew0ODhIvpAlu5V96LL5NPlClsGYGs1tuPN4dvo9DSdy47G8Dn19fYxmS++h1T0raG9qo72pjV36t2d1KPwTYEt+jP6BeKTQLFm6hI2z3E8yyMaUuJmWbEP459aoPw9ghZlUAKepBGqPx2HSLcfy5cvZks6SLRRpbZrZxb9hQgrAxCkROEx7ewejU7d3IlvQCVEAe8hMbJz29UyM984D6OvrZyJV5gKUIZPWsS2iopSir7+XXLr8tcglQAFcunQp/PvWmU8yFUCruYjMlaVLl6JvSKPLbFrdePDWc1DUWIblqyqfz3jQQQfxqU9/Gu/uB2jYhv0Amw7ae+snzRJd9OC+h9l33322aY3p6OhgcNEihjfPbuw2HXjQvIQDvXkzjY2NrFgxVSirJdbgoce2wOLl5v+RyHPjwlgDmTdDsZSOg7bueQXwTKGJuBjdZDP46QXfbCZ+m48HsQrdeGozbS3T5wWPp8ToEde1wv6+020F4WmP8exYbPJig/QP9PPoEw+XHHvZrifx8Kj4L8OeP8tobpy1/dHnvIPMRff9++45v29jegsNSvmF06qA8wBuBb8S0XQKYI6ujs5YxN2Xwy54T86i6t6GdI7lES/cW6Ojo4NssVRo1FqTyXuJUAB7enpnrAJqPYBxNSgMDAySzW7dQFAoQD6vYyOMlGOgf3DaKqBWAYxz+xcvXoyXLqJn2AswTnsAWpYvX44uFOdfCXQ0w4oqFBjp6enh8MMOQ9/9IDqzDVVKK4h330N4qTTPP+752/xZO++4I2rj9ManSqA3bmS7tWsjz521Bg9vLLCP2/goy2LkCQffO6NTc/cQhNHpeO3l1tvbO6nklcN6B+PS3jCTCuBWtoKwCmB1qhJvO21tbbQ0t0zu9RcmnU+htY7ldejv72d0mnZPh+y7NxYb4/OSJUsYzU6QKcwtD/yp1BYGBwarmk/tFMCt0NHRQWNj47QK4EQ+S1d3PIV18ENhtrYXoNaaDePZ2FlIw7S3t08JAc0XJf89jtsNhJFtRaYfdpmcprW1JfIiCtPR19dHNrN1BTCT8c+PKwMDAxQy5a9FLgVdXZ2RC7Iz4W8FMUOSvFEA4+QBnJxjRmcOrSqHzuTxMrmqzVMvfvGL0YUCxdvmbrGtNLpYRP/jP2y3di377rvvNn/eLrvsQnHLFnRm7r/7bNCeh96wgV132aUqnz8XOjs76ejsRI+LYqU9j+L4aKwMIeBvM+PNs0x8EM8okXEJRezr6yU/wz6A2YQogGOpmbeCGDMRMXH53cMopejp6WF8Gg+gVQzj6Int7+9nNDs+4x6GYdKFDPliPjYe2cnt2FJbtnJmKRtSW1i2vLryuFMAt4JSiu6ursn9/sKM5bKxHDgWe/NtmJg5cWskkydXLEZauns2dHR0kA0pgPZ5EjyA3d3dZGfw2GRy0BPT8E+QCTmd9tja7jE2TzAuVrhy9Pf3k59mWOQz8W47zHIvwLEinV2dsTKO2DlGj8x9fye2yHuqFWK4du1ajnzWs9B33IMenXkPs2rj3XEv3ug4rzrrrIqE5e++++7yuU88sc2fVQ69eRM6n49N8arFixajx0Xo0ukJ8LzYKYDNzc109/TiTYxs82d5qS00NTfHJn2gt7d3xhzAXMw8lmGCIaAzYRXEuCqAAD29vYznynuZJ2KsAA4MDKC1npIHOBMjJtcxbgrghtTInN73VHoLy6osjzsFcBZ0d3dP7wHM5eiO4cCxdHd3093VtVUPoA0RjbsC2N7eTrZQKvAmTQFMZ71pN/7N5oj1/dTf34/nwTT2kEnSCcih6+/vJ5f20N7Ua5FLS7hrnLEKoJ5BAdSjXqy8fyDhqE3NTfNSAO17qpljdtZZZ9HS1EzxL/+ozcbpZdBjE+i//4f99tuP/fbbryKfudNOO9Hc0oJ+9LGKfF4Y71HJy9mWYjWVZPHiRTAhSrz1BFYzn2a+LFo0hK6EAjgxTP/AQGxy+Ht6esikR6df6zLxVTxAQie7OrsYm5jZAzie2kxXZxdtbeW3iIgDvb09TOSn8wCOm3Pip4hb+WFkhgI2Yey5cTHg+k6YkVm/J1fMM5weq/ra7RTAWSDu82kUwEIuNha36Vi2fNlWFUDrIYx7CGhHRwf5gqYYENqzBfk/KQqg1pCdpjBrOid5gnHFTqqZrVQCta/HXQHUGvJlhkYh0xCbBWQ6+vv7Zb+tGUJAG8Zh6ZJ45T01NjaybNnySW/eXNAjKRoaGqo6Tw0NDXHWmWfi/e9xvLsfqNr3TIfWmuJ1N9Pc0MC555YvcjAfWlpaWL/HHuhHH6nYZwbRjzzCylWrYuMJGRwchJQoGdoognHM01qyeDF6fGYlYzbo8WGWxcjY09vbS7GQp1goL3tkM2Mo1RDbfHeAwaGhWYSADjMYw/sqSG9v7wwKYHw9sXYumY8CGJd5qLu7m472jjl5AO251XbIOAVwFnT39DAxTQLnWDbeIaAAy5ev4Kn0zC6bpyayNCgVO29BGKvk5QIyr80JjFOY23TYe2W6rSCyeRVrg4JV6NJbSSNKQg6gbVu5rSByMa5gamloaGBoaHDaEFCtNXqsGMsxvWb1atTIPHLRRlIsWbqk6jmyxx9/PHusX493/T/RW2obCurdfg/eo09yzjnnVHz7jv322w9vZAQ9Ord8lK2h83n0E09wwP77V/Rzt4XBwUGKqZTkUhpFMI4GqcWLF+ONb952b/P4cKxCXK1CkZ0mvzGbHqWnp6fi27lUkqGhQcbTM4eAjqeHZR6OMb29vYxPE0Y5kY2vJ9YqccMJVgCVUixfvpwnt+JJDvKk8RY6BTAGiAdwqsTuaY9UzHMAQbx6GyeyFLzpQ8U2pLIsWjQU66IX4CuAQQ9a0jyAwLSVQLO5eE7ElkkP4NYUwLTseRjn+8kqgOFtnooFTSEX7wqmlmVLl02fA5jV6Hz88p5A9onztqRkm4M5oEZSrFm9pkqt8mloaOBtb30r7S0tFP/wN3RxhkI7FcR7ajPeTbez3/77c+yxx1b88w844AAAig8+VNHP9f73P3SxyP4xUgBF2dPo9AQ6NUFDQ0MsvRxLly7Fy2XQ2en3AtwaupinMD4Sq/0+JxXAafIAc5l47j0XZGhoiPH01kNA4+hZDtLT00MqN0HRmzqPjefGaG5ujmUIqx8COnuD1XBmC22tbbFyCCxfsZwN6dn3YYNTAOPDdDmAqXweTXz3bLMsX74cT2s2z+AFfCqVY9nyeG8BAQEFsBAMAS19Lc7YBS+dnWrt1VqTznqxvp+sVW1rIaDpdDyt7UGsMhv2AOYTsAWEZcmSJajp5MYYVgC1rF69Wkr3ziEMVHseeiTFmjXVVwBBPDMXvvnNeBs2U7zhtqp/n87m8H73N/r7+njLhRdWJZdr2bJlrNluO/SDlQ1t9R58gK7u7slCM3HAzj+iAI7T09cXS2+Tv2n9/Lfo8MY2AzpWOfxbUwCzmVH6+vtq2KK5MzQ0xHhqBK+M4gTgeUXG01tirwDaa5EqEwY6nhunt6c3NrmjQZqamujr7WM4MwcFMLuFwRjlwoKM8acmRijO4IQJsiE1QldHZ9VlwfjNhjGku7ubbCFPPmQFtkphnAV2CJShnSEP8KlU9UqrVxJr1QluBZFNUAiovVfKhYDmCuB58fYAdnR00NzcPIsQUMXgYLwXRasAhiuB5hNQwdSyaNEivPECulgmfCyGewBaVq9eDYAenoPXY0sa7XmsWrWqSq2aysEHH8xJJ52Ed8e9FO97eOtvmCdaa4rX3gQTaS555zur6qk67NBD8Z54Ap2av8cpiC4U4OGHOfigg2K1H64dvzo9gU5P0B9Tg45dd70tT837M6zyGKc13N7DuXT58L1cZozeGK91IAZPrfW0ewGOp0fQWscm3HA6/P2spyqAE7kxemLoGbcMDg0yPBcPYHYLg4viJXssW7aMovbYOEsv4BMTwyxbvqzqSqxTAGfBdJvBJ00B3JAqrwCm80VGM7lYWQ+nw/cA+sdyxhsYxxCGMDMpgHHfBB4knn1goG+rIaDZjIq9B7Czs5PGxsZpFcA4houFmVTuJqZaFvW4GKziWPlw1apVsrjNQQG0ymKtPICWV73qVey62254f7oZPVzZ3DmL98+78B58lHNe/eqqb6Nw6KGHAlC8//6KfJ73v//h5XKTnxsXJjdZT6cgk2Ygpgad5cuXo5SiuA0KYHFkAwArV66sVLO2Gd8DWD6HNpcdj32UhfXsjU9TCCbum8BbfBl2qjd2PD9GT098ZdhFixaxeY4KYNzWPFu1eraVQJ9MjbC8ipWuLU4BnAVWaJ/Il0rtNi8wzh4bECtWU1PTtJVAnzKKYZzyB6ZjsghMQkNAZ8oBzJrLE/f7aWBgcEYPoNaQSuvYK4BKKXp6u6eEgOYSFAI6udCNlwktGfdobGqKpSLb1tbGoiWL0Zvn4IUyCqD1HtaK5uZmLr3kEno6uyj+5np0bpoSvvPEe+RJijffzmGHH86JJ55Y0c8ux+rVq9lu7Vr0f/9bkc/z/nsf3T09PP3pT6/I51WKyfs+k0Zl07EcByDVWYcWLaa45cl5f0Zxy5N0dHbFau3o7OykoaGh7F6AWntk02Oxam85rGI3XSXQsYQogPbenyhTCGYiNx7bsQHy2842BNTTHsOZ+IXkWgXwiVkUgil4RTamttTEIeMUwFlgPTJhD+BEPhkewIaGBpYsWjRtCKg9HqfwkemY9ACGqoA2NTVWvTJgJWhqaqK9va1sDmDabBAf9/tpcHCIbHb6qSOXA68YfwUQoK+3b1oPYJIUwLJ7AY57DA4NxDLvCWDddmtRw3PIAdw8waLFiyMx9AwODnLJO98Jo+MUrrupYvsD6vEU3h9uYNWqlVzwpjfVLG/lqCOPxHvyyW2uBqpzOfTDD3P4YYfFKvwTJFy9sbERnUnhpVOxVjZWr1qJNl68+eCNPMmqlStjlfeklKK7p7dsDmAuO4HWOtaKB/g572PTbAZvj8c9BNR3YpQJAc3HuxjP0NAQ47kJcsWtbD4MjJlCN3HzAA4MDNDa0sqTW9lSBGBjague9qq6160lnpJBzLCDJ6khoABLly9n4zRFYJLpAfSPZQua9gSEf1q6u7vKegBtCGicJ2OQyWwmD6AND01CDl1fXz+FTKnQlM8Q26poYbbmAVyyOH4FYCxr1qxBj8y+EqgaTrF2u+2q26gZWL9+PWeeeSb6/kfw7rh3mz9PFz2Kv/8bzRredem7aqrYHn744RJ2eO+29cN74AF0ocCRRx5ZoZZVDqUUXd3dFO78J14uG+t1evXq1RRHnkTruVXFteiRJ9luu9qGRs+G3p4esmVyAHMx3wTe0tvbS2Nj04whoI2N8YyyCGJ/54lQDqCnPVLZiVhfB+vNm40XcHNmpOQ9cUEpxbJlyya3d5gJu12EUwBjwtZCQOOcs2VZunQpT6XKK4AbU1na29pivUBarFAerAKaK0BrW2tUTZozPd09M+YAxv069Pf3k8t6TFcZ3yqHcbeKgnj5yimAPb3dsbKmT0d7ezsdnR0wMfViNEzAoqF4WUKDrFmzBu15s6oEKhVAJ2qe/xfmRS96EQcccADeDbfhbdi0TZ9VvPl2vCc2csGb3lTzsNbFixezx/r16Pvu2yZvpnfvPSxdtoxdd921gq2rHKe/7GUcesD+POtZz4pdjmKQNWvWoAs5U81zbnjZFMXUaE2LI82Wvr5ectmpXqdsWo7FXXFqaGhgoH9g2iIwY6lhBvrjG2VhaWtro6WldUoOYCo3gUbHWgG0Rs5NRrmbibgqgAArVq6YlQfwyRptAg9OAZwV03kAJ/JZOtrbYxf6Uo7Fixczns2TKUwVFDemclJOPgECr1UAw1VAO9rjXwHU0t3TW1YBzCagCAxsfTN4ezwJIaC9vb3kQ5HR+YyEhiaFoaEhdMgDqLXGG49fKEyQ7Yw3b1aVQLek0UVv8j1RoZTiwgsvZGBgAO8PN847H9B75Am82+7imGOO4YgjjqhwK2fHs48+Gm/LFvSG+eWe6fExvMce4+ijjort2nH88cdz8cUXc9FFF0VuPJgJ2zZv+Ik5v9fb/DhA5GOjHD09PeTLhYAmxAMIUoVyuhDQ8fQwgzHfBN7S0909xQNoQ0LjfB18D+DIVs+1CmAc170VK1awYWIEbyte/icmhmlva69JCopTAGdBR0cHSqkpHsCJXC72wrrFhnduLOMF3JTJsyQB4Z8AjY2NtLQ0lyiAuYKmPUEKYE9PD9n81KGXyWpaW1toaWmJoFWzZ3IvwGkUQLtHYBIUwJ6eHvJZD8/zvSCFrKKvL/7hq5bFixbTENah0hrtxbs8ua0EOptCMPacOAjxPT09vOPtb0ePjlP82z/n/H6dzeFddzMrV63iNa95TeUbOEsOPvhgmltaKN4zvzDQ4r33AXDUUUdVslkLEntfF4cfn/N7i8OPAfFUAHt7e8mW8wAaBTDuHkCAoaHBaTeDH08PM5QUBbCnh4l86VxrFcI4K4BWmds8yxDQppgWPlu+fDkFr8jmdPmquJYnJ4ZZvmJ5TYxqTgGcBQ0NDXR2dDCRCymA+Vzsw/Ustlz8xjJbQVgPYFJoa20tDQEtKtoTsAegpbu7m0xuathVJif5gXHHKnbTbQafSUNra0si9mW0C0Uh0JdCVsV6QQwzODgIqdD9ZLaFiGMojKW1tVUMT7OpBDo8jlKq5qGS07HHHnvwohe9CO+u+/H+NzevTfH6WyGV4aK3vS3SPNOOjg4OPugguP9+9HTx3NOgtUbfdy+7Pe1piSgeFne6uroYGByiuOmxOb+3uPlx2trbY+n16OnpIZsen5LbmMvEX/GwDA4OMmHC8sKMp4ZjbWQL0t1TxgNonsdZjm1ra6O7q7skBHR1zwpW90zNkducGWFoYDCWIbl2nnxiYuYw7w3pkZptyRa/XymmdHV1TVb9tEzkc3TFeOAEsQre5lAhmHS+SCqXj+Vm0dPR3t5eug9gUSWiYIelu7ubTNabknsjCmD8F8TZhIAmoQAM+AJIsBJoPpMMwcQyODiIN1FAB7yYVgGMu3Cy3Zo1s6oEqjdPMLR4UazG+ctf/nJWrFyJ95e/o/OFrb8BE/p5z4Occsop7LTTTlVu4dY56qij8LIZvIcfmtP79MaNeMPDHO28fxVj+3Vr8YbnowA+yrq1a2MZhtvT04PWHvnQXjvZzFhiCm0NDAyQyaXIF0rlv3whSzaXTkSkC8i1SBVKFcCU8QjGfb0bGhpic8b3wr5s15N42a4nTTlvc2aERUviKctapW7DNMYEkKI8GyZqswUEOAVw1oj7PLkewP7+fhobG9gUUgDt8zhaD6ejra2NXHAbiGIy9gC0dHV14enSPEaAbD4ZCmBvby9KqRlDQAcH4+t5CjKpAJq1XXuafNaL/YIYZHBwEDSQ9hVAnRQFcLvt8LZMbLUSqBpJsW67tTVq1exoaWnhTeefjzc6TvGfd271fF308P56K0uWLeW0006rQQu3zt57701vXx/eHKuBevfeQ2NTU6wLqySNtWvXUhx+Yk7eWK013ubHWbduXRVbNn/sPBreCzCXHaeruyeWSmsYO4eOhwR3+zzuc6ylu1wOoCkKE3c5dvGSxbPaDH5zdiS2suzQ0BBNTU2TVT7LsTk9RtEr1iyqwimAs6Sru7usApiUHMDGxkYGBwbZFAoB3ZSW58nyAHaUbASfK5AIS6LF3jPhrSCyeRX7iRjkXurt7ZnWA5jNNCTOA2iNu1YRTJICOGmBTgWUKPN/3K/DmjVrwNMzVgLVnoceTsUyx2n9+vUcfvjh6H/djR6f2ZPp/ec+vJFRXv/a18Umz7exsZFnHXEE+n//Q2fL7xMbRnse+v772X///RMxXyWFtWvXor0i3hw2hNfjw3jZFGvXxss4YrEh9tlMqeKRzYzRm5A51s6v4TxAWxk0KR7A7u5uUmb/RUsqn0IpRWdnZ4Qt2zqLFi2aLPAyHZ722JzZElsFsLGxkSWLl8zoAbQVQJ0CGDO6urpIF0pdNqkEFYEBWLR4McPp0qp1m5PoAWxvJ1/0LYfZgk6UAmiFpnAl0EwuGQogmLCYaXIA05lkWUXBDwEtJFkBnChVALu6u2hubo6mUbPEFr+YsRLoljTa82KT/xfmrLPOogFF8e//nvYcnc+jb72TPffak/3337+Grds6RxxxBLpYxHvggVmdrx9/DC+V4lkRVS+tV6wXr7Dp0Vm/p7D50ZL3xg07v07xAGbG6e1Nxhxr17KJdKkHasIogEla64q6SLboL9wTuXG6OrtimTMXZNGiRYznJsjOsBn8aG48lpvAB1m+YjlPpab3ZG4w3kEXAhozOjs7mQhsA5EvFskVC8lSABctYjhbqsQOp/M0KJUYKxZIuGfOKIBaa3IFL5EKYDYXzgH0EnM/DQwMks1MDd8pFiGX9WLvebLYa1Ew64r1ACZFEQdfAdQBD6CeSMY1WLlypYSBzVAIxiqHcVUAlyxZwnHHHou+50H0WPl+eP/5L146wyvPeGXswt523nlnlixdinf/f2d1fvG//6W1rS12imzSWbVqFY1NTRTnoADac+PoHYdgCGipBzCfHU+Mkc3Oo+G9AO3zJMyzENjPOufPUan8RCLWOlvMbCYvYJz3ALQsW7aMJ1Mj0+69uiG1hcbGxpr1wSmAs6S7u5tUIAQ0VUjOJvCWoaEhNqezJTffcDpHX18vTU1NEbZsbgRzAAseaJ3MENCgB7BQ1BQKOhGTMVgP4FRB1uYFJmVRbGtro7GxcdLzZ/8maVxP/tYBBVClNYMD8bdMt7W1MbR4EXpkBg9gzBVAkA3iFVC8Y2ounfY89B33ssf69ey22261b9xWUEpx+GGH4T36KHo6t75Bex48+CDPPOAAWltba9TChUFTUxNr1qyhuOmRWb+nuOlRFi9dGtsQvkkFMFs6vnMJUgB7enpobGyc9PhZJtIirCelH1a2SOV9ZXwiN05XAiqPW6/e8AxbQcR5D0DL0qVLSeezTOTLz7MbUiMsWby4ZnuLOwVwlnR2dk56/YDJLSHiOvGWY3BwkHzRYyLvJ5kPZ3IMDcV3wJSjra1tsoCK/ZskBdD3APrHkrIJvKW/v5902iNsyLLyY1IUQKUUXd2dk56/QgI9gC0tLbS1t5VsBaESVIl1u9VrUCPTJJQCeiTFwOBgrAs9LV68mIMPPhjufgAdShXQDz2GN57ihS94QUSt2zqHHHIIaI330IMznqcffxwvk3HFX6rEDttvj948+0qgevOj7Lj99lVs0bbR2dmJUopcYC9ArTW5TDI8TyDbgPX29pUNAe3t7Yt9+KTFyhapgAcwXUjGdbBK3abMTAVURoD4ewBh+kqgT6W2sLSG2+ok486NAVbRS+Xz5m8yFUCAkYyfBziSLTIY4wFTDlEARdi1nsAkKYCTHsBAOmYmYQpgX18fnge5cB5jgjaBt3R1dk2GgBYSdh0sff19kA6EgKY9+vr6ImvPXFi9ejV6JDVtWIwaTrFdDDaA3xrHHnssXjaH92CpAO/d/QD9AwOxDpnccccdGRwawntw5u0gvAcfpLmlhX322adGLVtYrF27lmJqFC81utVzdT5LYeSp2BaAAbOHcmcXuYyvdBTyGTyvmAjFw9Lf38dEyPs0kdlCf39fNA2aB74H0C9WlSqkErHWWaVuRg9gVjaBj/O6t3TpUgA2TpMHuDEzWtN9VZ0COEt8BTBn/or0noTBY/EVQF9qH8nkE5PEbGltbSVX8Ez+nwiNSVIA29vbaWhoKMkBTKIHEKZuBm+fx3kSDtPd3e2HgCbsOlj6+/rRRgHUBY3OJUcBXLlyJbpQhLGpYTFaa/SWFKtWrYqgZXNj/fr19A8OUPz938h94QeTD++hxzjyWc+qWVjPfFBKcdCBB6IffWSKB9OitUb/72H23nvvRM23ScIWc5lNHmBx8+OAjm0BGEt3d3eJB9CGgyZLAewnlSlVylOZ0UQZOu3vnc4HcgBzyfAAtra20tPVvZUcwC0MDQ7FLsc6iN2P+6n0VAUwU8gxmpmYPKcWJCfxK2KsApg2il+6kDwPoJ2srAew4HmMZXOJCRWztLW14WkoepBPoAdQyi53kAmEYmTzogwmRfGYVADTYCp9Tz6HZCmAXV3dFDfJolHIQltba6yF9XL09fbRsMEsfEYRTMo1sMqd3pJC9YTCPFM5dK7AypUrI2jZ3GhsbOQdF72d2267reR4Q0MDxx57bEStmj37778/V111Fd5jj9FYJt9Sj4zgjY5yQIw9mUlnexPOWdz0KM2rdp3x3KKpALp9jENAAbp7utkyEVQA5f8kKB6W/v5+7rmrtEruRGYLfX3x/u2DTIaAGgVQa006l0qMDDu0aBGbxkemfX04M8KilfFOZ+rq6qKro5ONZTz8G41S6BTAGDI5eAqlHsCkDB7whfbRbN78LZQcTwpW2csXk6kAAnR1dZILWOKsBzApi6JVLsJbh2Uy0NnZEZt9zmZDV1cXxZwCNIUcdCRoTFv6+vr8jeAz8jcpxQkmlbuRFKwqjUbQIxKutGLFilo3a17sueee7LnnnlE3Y17sueeeNDc34z3yPyijAHr/+x8A++67b62btmDo6emhf3CQiVnkARY3PUpbe3tNBcb50NPdzcbhzZPPbUXQpKx1IPsZptKjaK1RSqG1JpUeTYyRDUzkkWogXRArba6YpaiTE4q7aPEinpihQNLm3BZ2H4p/qsDiJUvKhoBapbCW49mFgM6SqSGgyfMAtre309rawhbjAdxiFMEkhTEAk9XnckW/CEzSKtJ1dXWTDeQA2v+Tcj/NFALaG3QJJoDOzk6K5vcv5qErIdcgSE9PDzpdlDw64wFMynXo7++nta0NXW4zeHMsCR7ApNPS0sIe69ejHy0ffqgffYQVK1eyePHiGrdsYbHDunV4s1EANz/G2rVrY1+EpKuri3ygCmg+m5o8nhT6+vooFPPkCrLg5QoZCsV8ohRApRQdHR2kTQ6g/ZsUmWNoaIjhbPncOa01w+n4bgIfZMnSJWxMj005vjHtFMDY0tHRAQRDQOVvnCvThVFK0d/bN6n4WU9g0jyAVtnLFzX5YvJyAMEogMEqoAlTALu7u1FKTYZ8WjIZ6O9PlkFBBBS5jwrZZAkmlp6eHrSnIQ86YR5ApZRsfLtlaiVQvSVNY1NTIhb2euDpe+2FNzyMTpUq49orop94gmfsvXdELVs4rFu3juLw4+hicdpztNZ4mx9jXYwLwFi6urrIBdIdbA5gkuZZq+iljJBu/ybFyGbp7OyaLAJjPYFJkTkGBwcZzY6T96bmKI/lJyh4hUTUs1i8eDGb0lNDQDelR2lqbKypPO4UwFkymQNoFL9MPk97W3vsrW9h+vr7GTNuszETApokKxb4yl6u4FcBTZ4HsItcwb93snlNS0tzYkInZf+jrikhoLlcQ+IMCh0dHXhFjVfUFAuKzs7kCCaWSWUv48mDZIVYrVq5EjVaZm+kLSmWLFmSuJzMpLJ+/XoAvMcfLzmuN25E5/OTrzuqx3bbbYf2inhbNkx7jp4YwcumYl0B1NLd3U0u41f5zeeSpwBaRS+dHSv5mzTZqbOrc7IIjP2bFAXQVgIdKVMJ1FYHjfMWEJZFixaRymdI5UuFp03pUQYHB2uqUyRLe4kQ6+mzCmC6kKejIzneP0tvXx+jRmuyHsCkWbF8D2BycwA7OzsnC7+A5AB2JMibDNDb2zdFAcwmMATUevcLOfDyavJ5kphU9rJaHiRLAVy2bBl6NC1ezABqLMPKhOT/1QM77rgjzS0t6CefKDnuPfEkALvvvnsUzVpQWKXOFnkpR9GEiCZBAezs7ERrj6IptZzPpmhoaEhU9JQ1sKWM4mf/JiXKwtLV1UnGeP7S+bQ5lgxFfHIriDJhoCPZZCmAAJtDVWU3pUdZVOPweqcAzpLGxkbaWltLQkA7O5JhOQnS19fnewBzBZqbmxI1EUNYARSBMSmeM0tnZ2fpNhD55FjiLH19/WQDThvPg0zGS6wCWMyLEphEBXByEc+IAtja1kpTU3JqfC1duhTteTDhWxS01jCaqem+SAudpqYmdt55Z/SGUu+T3vAki5csSVy+eBJZtWoVDY2NZpuH8lgFcLvttqtRq+aPnZts6Gc+l6KzsyvW5frDTIaAGqE9nUmmAtjZGVAACxIKmpT1zoZ3ltsLcLM5loQQ0EkFMJQHuDk7XvNUB6cAzoH29nbfA5jP055AD2B3dzfjxvM3nivQ09WdqIkYwjmApceSQkdHB/mCxjMej1weOhNiibP09fWRzflTiKmLlDgF0BpAijko5HRiFsQgvgfQg6xO3L1klTw9GsgDzBbwcvnJzXMdtWGXnXdGb9qE9vwcNLVxI7vuskuErVo4NDc3s3z5corDMyiAw4/TPzCQCC+/VQDzOVE4ctnkbD1gsYpe2mxhYT2ASVvrOjo6JhXATD55OYAAw9mp+XPWA5gEA5X1Um7O+AqgFLEZcwpgnOlo7yBjFcBinvYECoo9PT3kix7ZQpHxbIHuhFmwYGoVUKUUzc3NEbdqbthJ11YxzeVJXO5ZT08PuUAIqA0HTeKiCFDIQ7GgE+cRB/9+0jmNznp0J0wBnKx8FtwMfixd+pqjJuy4447oYhG9eRgAnclQHB1lxx13jLhlC4e1222HnkEB9IafYG0CvH8QWOsCHsCkhB1aOjo6aGhoIGP6kMlO0NDQkDhjYWdn52TxF/s3KX3o7u6muamZLWUVwFF6e3oTEfXiezL9vTHHc2kKXrHmHkynAM6B9o52MgWR2DOFQmIGThBryRrPFRjPF+npTa4CWChC3oOWlubEeTHtomirf+aLKjGWOEtvby+ZjIcnNUcmFcCkhcVYhS9nnE9JHNeTApXJAezuir9nIMik5XPc9wBqoww6BbC22I3F9ebNJX/XrVsXWZsWGmvWrKEwuhFdyE95TWsPb+QJ1qyJ/55n4K91BTPBSghosuZYpRRdXd0lRWC6Ehg91d7ePun5yxYyKKUSUz9BKcXAwEDZENCRzGgivH8gHv6e7p4SBXCz+d8pgDGmvcP3AGYKhUR6CqygOJEvMpEv0t2dLGEd/Hy/fBEKRZ24/D/wlQyTUkounzwF0Cp6NvQz8QqgqXyflAUxSHt7uwgjWU1DAu+llpYWevv60GMBl/K4KIBu37nasmLFCpqam9GbNwG+ApiEgiP1wqpVq0DrspVAvfERvHxOzkkAk2udUQCL+XTi5icQD1TQA5iE8NswHR0dFL0i+WKeTCFNW2tboirZDwwOMJIr4wHMjTI4FP/8P8vQ0GCJAjhiwkGdAhhjOjo6SFsPYDGfSAXQTlqpfIFUvpi4UAyYmgPYmkAFcFLpMApgNp+80EOr6GVDCmDSQkDt757PlD5PEkopyUnOaVQuOXkdQZYsWTyp9AHo8SzNLS2JMygkncbGRlasWIH36KMU/vUvig88QHtHR2Is7PXA6tWrASiOPDnlNW/4iZJz4o6di/KTHsAEK4BmC4tMLrkKIECmkCZTSCcu2mVgYIAtuambqI/kxhI1P/UPDLAl6++NOWL+r3UfnAI4B9rb28kUjQKYT6YCOOkBzBVJ5QuJnMSsx6/giRcwiR7AyRDQgkZrTS7nJW4ytoK5zQPM5UqPJ4XJfSXTpc+TRntHO+Q1OoH3EsCioUWoVM4/MJFhcHAwcWFW9cD6PfZAb9pE8Ya/oR9/jN13391dhxqywmx9Uk4BLBqvYNI8gIWAApjE+am7uyukACbPeG5l1mwhQ6aQoaM9WddhYGCAkVAOoKc9RhMUAgri6duS8xXALREpgPHPmIwRbW1tZAsFip5HvlhMtAI4liuQLRQTaYlrbpacP7sPYEvCKoBCqQcwXwBN8nLPrPHAev5yWbNdSsIUKNvefMIVwI6OTjblxiChCuDQ0FDJNhBM5Fi8KBlejnrj3HPP5cwzz5x8nsS1Lsm0tbUxuGgRYyNlQkBHnqS9ozMxm5C3tUmYYT4nm8Hnc6lEzk9dXV1k8w8BkM0nr5AN+DJGtpAhW8jQ3pescd3f389ELkXeK9DcIOrLeD5FUXv09/dH3LrZ09/fz0hmAq01SilGshN0tHfUvJq98wDOgba2NrLFPFnjBUyioGgVvs3pXMnzJCFVP5somBzA1pbkKYDBHMC8qQSaNCHLKoDW85fNyUazSfMUtLS0iEHBRB8mcVwDdHZ0QMZDF5O5lcXQ0BBeNo82e7s0TOQSsa9TPaKU5JHaR5LyhOqFVStW4I1OVQCLo0+xYsXyxMyzSina29sp5DMUC1m01omUO7q6usgaL2Y2gZVMwV/bssUM2UI2cTKHVfJGs34YqP0/SQpgX18fRa9IKi8Gz9HsBP0RGHTcrD4H2tvbyRYKk5VAkygoWsFwk1EAkygoArQ0N5P3JAy0NYHXYdIDWPC3gkjaZBxWAPM5EhkWo5SipaU58QpgR3sHpGRfyaTdSxBYwFMiJHqprFMAHQuWlStXokc3Tn1h9ClWrVxZ+wZtA+3tHeTzaQpmkk3i/NTZ2UnGeDEz2YlEKrF+CGiWnJdJ3HWwa0QwD9D+nzQFEPzQz9Fsir7+vpq3wymAc6CtrY2i5zFhtPYkCopNTU20NDdPegATqwC2tEgRGE8lMgdwsvBIwa8EmrTJeHJ/J6MA5nLQ3Z2sAjCW1tbWSQWw1mEYlaK9vR1SsidHEuemyfyHVA5yRXShmKi8DoejkixfvpxiZgIvm5o8posFCmObWb58eYQtmzvWA5jPJVsB9Lwi6ewYnvYSqQDadSFjcgCTtk6U8wBuSagHEGDUlB4fzafpdR7AeGMHy2g2U/I8abS3tzOSSbYC2NzcLCGgXvI2gQdRxJubm8gV9KQHMGnXorGxkfb2tsltIPI5lciiQgAtrS0UjSKeRIMCmPkop/3/E4ZV9nQqCykxsiUlz8nhqDTLli0DwBvdNHnMGx8GrSdfSwqdnZ3kc2kKJtE6qQogwOjE5pLnSWKy4FkxS66YTdw6YdeDsUABldHceMlrScDvR3rybxTV050COAfsYBnLJtcDCFYBzE/+n0RaWlooeLIZfJIF9nwB8oXkCu2dnZ2TW1nkE7j/nCXo9UvidYDk92FyAU/nwUQoJMmq63BUEl8BfGrymGdCQpOmALa3t1EsZCmY6KmkGTvBb/NYanPJ8yQxmQNYyJArJFcBHA2EgI7lxmlsbExUTqZV9sZMSPFYNuUUwLhjBayxXPI9gClTaCGxCmBrq/EAkkgPIAQVQHmexGvR1dU16QHM5UjUJByktdUfy0k2KJT7PylMbh+SzqGNgSpJVl2Ho5IsWbIEAG9s8+Qxb2xTyWtJob29nWI+O5kDmMT5ya7P40YBTOJ6HfQAZhOoALa3t9Pa0jLp9QPxAPZ09ySqUJWNlBrPpUkVsnjai2T7rOT8YjHACoZjZuOzpOYKtQUmrqRNAJbm5hYKnqboJVdgbw8pgEm8Ft3d3eTzoDXkcl5iFcC2wFhO6v0UnI+SODc1NTXR0dkpyp/xADoF0LFQ6ezspKOzE288oACOb6ahoSFxxZHa2tooFDKJLwIDMJYaBpLtAUzlU3jaS6TM0dPTWxICOpYbj8R7ti20trbS2tLCeC7NuAkDdQpgzAmHgCZRyILkewrAhIAWIV/UifUAtrd3JN4D2NnZRT6vKBZFCUziogjQYrYSaWpqTJQlMUhQcU3q3NTT0w2ZPGRkUCQ1p9ThqASLFy8u9QCODzMwOERjY2OErZo7tghMoZCdfJ40rKw0kR4BktmHxsZGmpqamDAetCSuE729vYzlAwpgfoLevmQpgCBr23g+w7gxijgFMOaEQ0CTOHigjhRArSh4yVUA29rbRQGUaNxE3k8dHR0UCmqykmlScwCt8pTUewlK75+kejF7e3ohk0dn87S0tia2Hw5HJViyeDE6NTL53BsfZsniRdE1aJ60tbVRyGcpJriC+mQIaHpLyfOk0drSyrjJoUuizNHb18tY3g8BHc9PJM4DCNDV1c1EPkPK6BNRGDtjqwAqpXZTSv1eKZVSSj2mlHqPUipSs5cVRiZM0lNShZPg5JvECQBMFVBPUUiwB7CtrU36UNAopRJ5LTo6OsjnmMwDTKoH0N5DSb2XoD48gL29vahsATL5xIYTOxyVYmhoCD0x4h9IbWHRoqQqgDkKheTmAPoewIQrgK1tTBgFMInXoaenh/G8vzXKWH4iEu/ZttLT28NELsO4qYwbxXrXVPNvnAVKqX7gd8B/gBOA7YH/hyis74yqXZMKoNn4LKlClu1HS3MzSqmIWzM/mpubyZuww6QK7W1tbRSKinxR09KSzGshVUD1pAcw6QpgU0LvJShVAJM6Jrq6ulC5Ajqbd+GfjgXP4OAgxfQ4upiHhiaKEyMMDQ1F3aw5I7KSJpcZR6lk7t07mT+X2VLyPGm0trYwMSEetCReh56eHiaMAuhpj4lcKpEKYGdnJyPFJ0gZ67lTAH1eA7QDL9BajwK/VUr1AJcppT5ijtUcq/BNJL0IjJm4kjj4Lc3NzWTzsn1CUvvR2tpKweQAJvVeam9vxytqTFps4hXAloQqTlA6DpI6Jrq6utC5AuQKdA86BdCxsLHFXrzUGKqlDV3IT+6XmSQmtx9Ij9HS0ppIY6evACY3fBKk3SMjWyb/Txrd3d2kcmk87ZEuZNBaJ9JY2NnZKSGgxiseRfpMXENAnwf8OqTofR9RCg+LpkkBBTCfo6GhIXGJ2BYr7LYmVEgE6UPGKIBNTXG1Y8xMa2sr+aKmUEzutbBhMJlM6fOk4XsAk3kvQanXL6kewM7OTrxMHpUr0pXQfFKHo1JYZU9PjKBTIrQnrQIo+LJTNjNGS2sy17rm5mYaGxspFHM0NjYmdo5taW0hZYqoJNFQ2N3djUYzkU9PhoImVQFM53Ok8lkaGxsjUcbjqgDuAtwVPKC1fhhImdciIZgDWA+egqROYCBKX74oCmBS+yEeQKMAtiXPEge+wpdOlz5PGn4OYPIWREu9KIBoDalcYgsKORyVor+/HwAvPYaXGis5liSscJvLTpTsuZo0Wk216CQqTpaWlhZyxeTWsbChkql8ajIUNLkKYJZ0IUtHe3skXvG4KoD9wEiZ48PmtRKUUq9WSt2ilLrlqaeeqlqjrFDlaZ3IgWOxbW9IqAcTSgXcpHoAW1payBe0CQFN5qJoQz7rxQPYUicKYBJDrMC/f7xUNrH3ksNRKayyp9Nj6LQogEncG9PKHLnMWGKjXcDfLqi1JZnrNSS/WrRV9iYKaVIRFlDZVjo6OtBoRjITkaXOxFUBnBNa6y9qrffRWu9TzQpZ9WBhB7/tSRUSoT6uxaRVNK8TGYsPfl5EJl36PGlYI0JSjQmQ3HEQJLgQOg+gY6FjlT0vPYaXSa4CWOoBTOZaB0yGryY1jBVK14kkKoC+BzBNqpBsBRBgODNGe3s0CmBcpZ1hoNzGHv3mtUhobGyksbGRYrGYyIFjSbKQawn2Ian9sQthJpdcD+CkApgpfZ407D2UZCUqqeMgyG677cb69evJF/Lsu+++UTfH4YiU5uZm2to70JkJ8DyUUokMd/MVwHFaW1dG3Jr5Y/uRaCU24cXCrGEwVUgzkWAPoJWVRrITLOmMJqw7rhLDXYRy/ZRSq4AOQrmBtaa5qYlisZhoQXHSA9iQXA9gPSiAdvLN5pJZFhsC1d0y0NzclNjCSLbdSfaKJ3UcBFm2bBkf/ehHo26GwxEbenp6eOq+W1ANDXR2dSVyjp1c33Ry9+0Fv1hbksNYkx49ZZW9iTrxAG7JTrBdROkOcZUYrgHeopTq1lqPmWOnAGnguuiaZapPZrM0J3gCWL9+PXvvvTeHHHJI1E2ZN0FhN4mTGAQUwHxyc0onFcBsMq2JFnsPaa0jbsn8qQcF0OFwlHLiCcdz8803A7DHHntE3Jr5EVwbEu09q7MQ0CTKTkEPYDqfoUE1JDLyyLa54BUjy3ePq8TweeA84MdKqQ8D64DLgI9FtQegpR72C1u9ejUf+tCHom7GNlEPHkB7LxWKyVWeJpXYLHR2Jndhb2hIfjp0Ej0DDodjZk4++WROPvnkqJuxTSQ97NDiV4tOrvyXdAWwra0NpRTpQoZ0IUN7RBU0t5Wg0hqVAhtLyVlrPayUOhL4DHA1UhH044gSGCmTxSISOHDqiXpQAOthUQxac5Ns2bX3UBIXEktSx4HD4ahvkl54xOIUwOhpaGigva2djFEAo6qgua04BXAGtNb/AZ4VdTvC1MMEUA/UgwKY9IkY6kcBtN6zJIeA9vf3MzA4wNOe9rSom+JwOByTBJW+pK51UB/yXz1sodXR0UG6kCVdzNDZmUwFMA7bcSTz6keIHTxJHTj1QjDcLamhb/XnAUxeHL6lHjyAHR0dfP9734+6GQ6Hw1FCPRg7wV+nk7peQ0CGbWxK7HrX3t5OJp8hU8jSXgcewKiM58lPfKkx9VAuvh5wHsB40NjYOJk/Vw8eQIfD4XBUlnoo2gb14QCYNHYmuAq89QBmitnICqhsK8Fx4BTAhFAPG0bXA8HfP6nCez0ogAAtLaYwUoKtovVQBMbhcDjiSL2sdVbWSLL8Z9ue5HSH9o52MsUsmWIusQpgHEJAndQzR2zxl6QqHfVC8PdP6mRcL4viZGXcBCuA9ZAD6HA4HHEkGCmS1PUa6iMHMMm/v6W9vZ2slyNbJx5ApwAmBBcCGg/qQQEMDvqk9gHqY1G0wklScyIcDocjztg5NsnrRF9fX8nfJJJkWcPS1tZGtpgjW8wlcg9AKI06impMJP9OqDF28DgPYLTUQwhoveRFWEU2yX1wIaAOh8NRfZKsgJx22mkcdthhrFy5MuqmzBsrLyXZ2NnW1kaumCNbyCZWAQziFMCE4HIA40E9VAGth0I2UB8hoP39/QDssssuEbfE4XA46pckr3WNjY2sWbMm6mZsE0n+/S1tbW1kCllyxXxdKIBuG4iEYJWNpCod9UI9KID1sB8P1EcI6O677873vvc9BgYGom6Kw+Fw1B02uzrJa109kFR5KYhVAO3/SSeqMeFG4hxxCmA8qAcFsB7yGAGampKvAAIMDg5G3QSHw+GoS2zAYZLXunrArwIacUO2gThU0KwkUclOLvFljjgFMB7UgwJYLyGgNiQmyXkRDofD4ag+SV2v6wU/BzDihmwDQaUvyfsPW5wHMCE4BTAeBIt2JPVa1IsCeOGFF3L++ecn3gPocDgcjmohGkeS17p6IKnyUpCgAlgPHsCoxoTzAM6RetjLph4ITmJJreAYbHeS7yellFP+HA6Hw7FVkrzW1QP1oAAGvX7OAzh/kik5x4B6GERJph4UwGAZZnc/ORwOh6PecWtdtCRVXgriPIAV+t5IvrUOqIdBlGTqIQQ0SD30weFwOByOmXBrXbTUw+8fjDhKsgJ4/vnn889//pNVq1ZF8v1OAZwn9TCIkky9/f4uLMbhcDgc9YoNeKm3tTtp1IPzol48gMcccwzHHHNMZN+f/DshIuphECWZevv93aLocDgcjnrHrXXRUg+yU73soRw1yb8TIqIeBlGSqbdFxN1PDofD4ahXbLEOt9ZFy8DAAAD7779/xC2ZP0GvnytAN3+c6jxP3CQWLfX2+zsrlsPhcDjqlde97nXccMMN7LjjjlE3ZUGzcuVKrrjiCrq6uqJuyryplxzAqHFS5zypNwUkadTb719v/XE4HA6Hw3LUUUdx1FFHRd0MB9Db2xt1E7YJFwJaGZzUOUds6f56C0FMGvWmMLn7yeFwOBwOh2NmgvKSUwDnT31J0TVg9913B2DZsmURt2RhUy8K4HZr1gDQ3d0dcUscDofD4XA44k3QA+hyAOePU53nyHOe8xyOPvroulFAkkq9eMw+89nPksvlEh2P73A4HA6Hw1ELgvJfvciCUeAUwHnglL/osaG4SaelpcUlMTscDofD4XDMgmDYpwsBnT9Ok3EkEqeEOxwOh8PhcCwsnAJYGZwU7UgkTgF0OBwOh8PhWFgE8/6cLDh/nOrsSCRu0DscDofD4XAsLNrb2znvvPNoaWmpm3SgKHAKoCORuEHvcDgcDofDsfA47rjjom5C4nFuFEcicR5Ah8PhcDgcDodj7jgp2pFInAfQ4XA4HA6Hw+GYO04BdCQS5wF0OBwOh8PhcDjmjpOiHYnEeQAdDofD4XA4HI654xRAh8PhcDgcDofD4VggOAXQ4XA4HA6Hw+FwOBYITgF0OBwOh8PhcDgcjgWC2wfQkVie+9znsnz58qib4XA4HA6Hw+FwJAanADoSywUXXBB1ExwOh8PhcDgcjkThQkAdDofD4XA4HA6HY4HgFECHw+FwOBwOh8PhWCA4BdDhcDgcDofD4XA4FghOAXQ4HA6Hw+FwOByOBYJTAB0Oh8PhcDgcDodjgeAUQIfD4XA4HA6Hw+FYIDgF0OFwOBwOh8PhcDgWCE4BdDgcDofD4XA4HI4FglMAHQ6Hw+FwOBwOh2OB4BRAh8PhcDgcDofD4VggOAXQ4XA4HA6Hw+FwOBYITgF0OBwOh8PhcDgcjgWCUwAdDofD4XA4HA6HY4HgFECHw+FwOBwOh8PhWCA4BdDhcDgcDofD4XA4FghOAXQ4HA6Hw+FwOByOBYJTAB0Oh8PhcDgcDodjgeAUQIfD4XA4HA6Hw+FYIDgF0OFwOBwOh8PhcDgWCE4BdDgcDofD4XA4HI4FglMAHQ6Hw+FwOBwOh2OB4BRAh8PhcDgcDofD4VggKK111G2oKEqpp4CHqvw1Q8DGKn9HtXF9iA/10A/Xh3hQD32A+uiH60M8qIc+QH30w/UhHrg+xIdq92ON1npRuRfqTgGsBUqpW7TW+0Tdjm3B9SE+1EM/XB/iQT30AeqjH64P8aAe+gD10Q/Xh3jg+hAfouyHCwF1OBwOh8PhcDgcjgWCUwAdDofD4XA4HA6HY4HgFMD58cWoG1ABXB/iQz30w/UhHtRDH6A++uH6EA/qoQ9QH/1wfYgHrg/xIbJ+uBxAh8PhcDgcDofD4VggOA+gw+FwOBwOh8PhcCwQnALocDgcDofD4XA4HAsEpwA6HA6Hw+FwOBwOxwLBKYAOh8PhcDgcDofDsUBwCqCjaiilVNRtmC9Jbns9oJRqCPzfGGVbZsLeJ+5+qQ/cdaw9dqzH/bdXSjWFnse6vQ6HY/YsxPHsFEBHVVBKNepQidmkDLBybU8icVacpsMKg1przzx/E/C8oEIYB5RSDUqpBnuf1MP9YknifVMJlFJNSZ2zgth7M3Qsdv0IjCEPSsdQnMa7Vfy01gXz/ETzPHZjPinXHkAp1Wz+tsS1jZWkHg0IgWvYEF43ktI/JSRK5qvUbxubSXahEZ4M6g2tdVEp1auUeqVS6ugkDDA7qAJtf4tS6gyl1Iqo2zZXlFJKa100/++plFoTmKxjOzEHFL9OpdTFwAeAPqA9ynYFsUKr1tpTSu2ulHqzUup0pdQeUbdtWzALYYO9b+qV6e5/rXXBCDIvV0o9TynVFfc5K4yZZ+29OaSUWgPxVFYC7dxbKXW5UupSpdTx9rWo2xdQUK3i91ql1JPAj5RSh0TcvCmErv1qpdQeSqmOOF17M8esUUpdBbwEQGud01prpdSuSqkdg0pFpI2tMIH7aH05Y1NSCES9fAy4yMyTnpGbmu06mJT+aaGolFqplDpZKbVn1G2ajrDheVupqwGWJIywoZRSpymljlRKDdnX4iygzxal1OnAg8CHgF8D31dK7RRpo7aCHVRKqWOA+4HzgMuBa5VSh0XZttlirXBmQV2hlLoO+APwF+BypVSzeS2W95hSqk0p9RHgR8AhwLHA97TWE9G2zMcIWB1KqS8ANyJt/DDwDaXUCyFZwktA8dOmbwcppa5QSn1KKfWiqNtXBXpgcjGdHAdKqWcDjwIfA34G/DLOwkA5jCDToJT6NPBP4PdKqR8ppY6IuGlTUEo1KqU+BFwPrAVOBb6tlPqAUqrTnBPZPBVQpg5VSv0buAz4PbAFeCiqdk2HufZdSqmvA9ci9/C1SqkzIB5yhVljh4H9geOUUsuUUq1KqV8ga9R1wFeVUgPmt4+8zduCKk1lOFEpdT/wC+C3SqkXm+OJ6mNA+VgDnAvsDmIgAR4ArlFK/czMp4lYC5VSlwJ3A58H/qGUerudg+KCKjU872qU1YOVUi3z/czYX5h6xQhWG4APAlcCf1RKvQ6SYzkph1LquUqpw4FdkAXzcOBk4BjgdUqp/qjatjWMIv5GYHvgo8BBwF7IOHmLUmrXCJs3KwJWuGcArwKeBF4OXA08H/ikOTXyRUeVDzUsAEuRRaVda/2HuHmklFK9wMeBPYAXaa2fhdwrDcAnlVKtcfBgzJaA4teslDoauVc6gOcB31VKnRJtCyuDUmpQKfVz4D0wKeBrpdS+SqkTgF2BLwGHAs8BnoaM+9WRNXqOGKHle8BRwNuR/jQBP1FK7RVhu8rJGrsjc9IbgRcD+5m/FwKvNeMosrXQjIdPIcrU9cAzgV8BWSAdteAe/k2VUgcibd0JuAA4Dfgt8Hml1O5xkCuM52sUeAdi4DsBeD1QBF4BfN8c/2JkjawgZl5dqpQ6AHgd0r/3A13AB5VS+5s5KDGyeGDdfjmyTpyqlDoWeCnwKfNYC3xMKbU8zoq8UuqFxsi3FjgTOB65Pu8BTppGRokE8zt2KqW+BNwAvA34E/A5pdTeMA9lW2vtHjV+IILFHcB7EUXpacBngHuBE8w5DVG3cx796kcWHA9ZMJcHXns/4hE8Lep2mvao0PNW4P9M2/8L7B547UREkXpnEq4L8GfgP8AtwEHmWDNwkenfPuV+g1r+9sHvBlYDjfYYcCBwG3D/dNerFveGadOU6w0MAm8GjjDPj0M8Ao8CeeBT5njs75VAn14OfBcRUM5DlNl1wFcQQ9WaqNtYgT42IkLx0sCxbtNHD/g38LTAa+cAjwNviLrtZfqiprk3DzTX6ySgOXD8UTM3r61xOxuAxmC7A/+/C9gItAaOHWWuxZeBxbW8N6Y5/mpE8Wszzy8D7oz6+ofa2Gf+vhT4NtBvnh9j1lwPuApoibCNDeE5HPH43WjWqWMCx19j2vy88D2TtAdiJPSQKKivAz3m+L7IOv2nqNs4x/40hv6+FZgAfg58xI5lxHj4b+Dbcb2GwJ5m3U4DVyAGZ/va74B/AesjbF94vKwCfozI1seYY89GotV+OK/viPoi1PMDaCp3QRHr1yPAroHXDkGsYP+Iut1z7VfoteciCtRVwXMRBesO4KfA9jFt+55IuOSdiGUrKKxcCfwDOCzq39/eS4QEwMBvfQqQAm4Lvb498Ffg+ih+8zIT2oHATWai/SsBQRvxXjwFnGmeV12ZQgwY30HCkxoCx4eAFYHnDcAi8//7kJCwj5jf94NmHO9Yrs9RPygjiJnjHwYeQ8Jg+gPHdwIeBr4Qddu3sd/he+9Fgf8PBm42j+bQtb8WCUvbO+o+BNrUFPi/G9jO9hF4pbmOVtBci3h0PcTg2F3Ley10H30AeEmgrZ8ArjPPdze/f8qMoaFa3Rehdu6AeGesINscOv8q4Dvh/kVwDyhkTf008DlzbLV59CLrbApJwTjLzEkviqidQQPAYnttgSOAceDh0HtWIArF3VH9vvPoZ1kDgnnt52b8vSn0u5wDjABnRH0/zbV/wGDg/ztM/44PHGtHDOZjwCFR9o9pZD6gBfGijQJvte02f9eZPr0H6Kxxe8sazYCnI06K3czz5yMhtyOIge/suf7Okd9Y9fgIXwDghYinr8E8/xpwbeBifxQJffs5cGjU7Z+hX2Eh6mQkkfuZGMECEZY/ZhafpeZYi/n7cuAJ4I1RtjvQlgsQZWmFOdZqFsug9dEKArshgtUnMMJVhNchvKA+Izghm+M/RrwXRwR/ByTEqkhAEKvWb24m2K8Bpwfuffv3eHMvfBM4A/gB4rn4kHl9LXANYu3qDb63ir9rH5AzbbYW/8+ZSfZOZLEIerV3QSzsrwc6zLHTzP3z3Wr+vhW4b8LGKeu9zwA7Ba5hAxK6lAcOjLoP87kPyxx7vZmfzjHPu4G3mOv2DHPMzllHIN7/9xChB2Wavr0XuB1RAuwcdq6Zp3ZCwr2L5rruG1Ebm4HPmt/7l4ihYcC8dgFiPPmF+e2vwHhgzX13DDWaa5FQ/z8gkQe3A18Nvd6AhNJeB3wy/Np091qF2lYiEIZe+zvw5VA73muOH2nG8DrES3AjVVasw/NK4PigmVevRRQf60H6PCLAnhA6/7nmnrmgmr9tpa5P4P9nIMaMYJSBVSa+GLyfEWX9CnNtmuPeT9O+VyBr8sXAOnPsWaZ/76TUm78eCVGsqcE58P1TjH5IStLawFjZ3bTxrsB59lp8CjFCHxbRvbQ9ErVlvX1NwHbInHo5olx/AAmd/xNiTLfe/1ndR5HfUPX8QJLa7zMD/CJMSAvwJnNjXYAIvf9FFCk7Ke5GwB0dYfsPBPYrc/wQxOrzKFJo4BECHgIkvOFB4BvmeVDwvAZZZA+qctsPB14wTZ/+hQhJv0aEu6uBHczrVvH4d+A99rp82Fyv06O+NqY9/w8JYbjPtOt8fEVkX0TB+n8ELFiIwvhtc+2mtVpWsI13IYLH9qHjP0aKFAwFjoVDf84C7gEuM8+rtjjiW9legSiBhyOe+uuRkMgfIAr1ZwPvOdOM4wMDx14G/M/0Y8r9F9F9EvRkdyMGp+8hisMO+IvhSxFl9/2h9y8yv8OviZkSVKavqwPXcjphdEfEk3M9vjKyK+KB+mOZ3+xryBx9fDXaPI8+7oOEV/0HWUOOBbrMayuBzeb+uxMx+Fgj1mLgW9QwrMnca7cjYdLLgvcPEmVxPxJCdnLgeBPwAiQqYPcqt6/BjO/HkCiPY8wc8D/gM6Fz2814Pyvw/Gjg3VVo16uBS8sct2uRNVC8B7gn8Hovsr5+J/S+f5l74rIq/paXAV8gpLQjBr7NwB+BNyDyg40KWWN+6y9S6lXqQwwYW+wYjfMDEcyvBTaZe2Qz4o0fNK9/HpE1Dg2970REVvo/ez9G3Zdp+rfWjMfHEcXoNEojRX5txvkeofe9CpFNXmueV3MNP5SA4h04fhKyrt1v7rU7gXMDr78SKUz0evPcjq1GJET9SmBJDX/rJmRtHgd+gyjbvYHXj0LkvlPxDdUfN+P74rn8zpHfWPX4QBaVC81E8G7gAAI5NMgic6e5YG8moLUjFudvA8+MuA9rESXhRaHjRyFK3+cx+STmBk0BF5rnnYiS62Esz4FBdTgSSlm1hd0M3H8inougRWVvJO7+S8Bqc+zliCXle4HzjkM8IW8Itb0XmeT3r/X9ZO8P83dXMzHchgjtuwJnI4LUywLt/RyiQJ0Q+ryjzbU5uYpttm3Yy3zXhYHJarVp11sC578SWSjuBQ42x/qQvIl/YRaW2U5ss2zjZK5f6LgNB/wFcGzg+MdNu08J3MvjwGsRz/dK4CeIJfTtBPLJany/vAN4dZnjZ5jf+HpEULsRUdCDffyh6fvBofceY65jLIwf0/R7H9PGkwLH+hCv2MsoFVjOQsJd32ueN+F7b18Yuod3QBSumkdnlLvfEavvH804CntyWxFBvAgcFTi+BPFg3wIcXek2MjXqpQExHPwNeEfotX58K7s1uLwbyZfax/z/MJIX31fBdk7x1Jn746uUzkVvM/dBAXhO4PjuyFpxFJK3/31z3uUEcpgr0M4+RHG2AmkD4tH9KfCq0LlvReZHa8BchAjqXwj09wTEqPltqmjEQdagM0LHBhDP6keR9TOYl2rn33cjAu3LQu89AFnTzq1Ge+dxj3ea/60SbtvfjcgFf0CUkGcj+dSPY4wDSDTMqLnXgkbPPmSNe4KAkB+3B3AJ4v1eT2munL3HyoZMInlrv0U80lVTbpGiXWlgr8CxJmSevwuZM1eYcfojxKBnDc2rzdj4H74hzRrNLkBkyUVVand43lSIbH0HEiW1HQGvqjnni4gcEryPPoDMmU9iolhm9f1R31hJf1DGi4LkENyC0cYDx+2i14YIkxsQ661CQiSORxbMKwnkHEXQJzuxrQwfN218qxlcTUjuU9HcfBvte5AF668EkpypQXhDYHLuL/PagYgi0mMmgv9nJq07EAX2RHPeYjMIn8IPbW2udttn0Tc7OT0PqUZnldiDzQTrmftnb3N8iZnovgksC3xOB7Cq2tcg8PxyxEt5gHnehIT9nIUoiLchgtUl+MYQOwGfhFjn31uhti0GnlXm+Argxeb/Q8xveS8BARQRAH+HhFvYXIErTV9uRhSKW4FdIrxHWhFh6xVl7v3fmvvfjm+r1F2ByUdGwnn+jRThCHruu5AohnVRj4MZ+t6NGEZuRoxQL0Qs8Q8jwvy1+IV7+oFvIIa49ebYSkQ4uDfwmdZTUXVveagv03kvFQGvuDm2DAllt/1oMffhPxHP9WWI0e0JKqzAh+6RQUoNnQ3mt/8Qkq9yirk+NyCGkqAB8VbEe3IXIoi9rAJt2xs/NLbs/I148Z4Z+Hs3Yvg8F1Gyb8JfAw5EFJJvIp6pG4E9K/x72rFpjQ995u+A+e1s5JA9fhRSlXRV4DM+hHg8foJ4N29DUhc6qnSvhoXYlRiPCaIweAQiQJDQ+aPsvYLMWbcjCu66wHktxKD4lBlzpyPKTW+Z15+NKB9Bw1Mr4m2/CxNCiHg/c8HzzPEdiDitxLQjvG4HDSX/wBQ3Cxw7AqnYbeWSy839GfZy7hr+7Cq138pDdgy1IQ4WmxvXjyhPHiJT/A5/fj8e8cR+zDyftlZEldpudYN1Zg46K/R6F76y/VrE8LwTMm+tRdb2TyDh9mtm/b1R33RJfZSZ9IKepgFkkXsfIojsgihNX0bi35eYm/ELiFXoTsR6lDE3aOThn4G+HIsoQzbee7kZWDsjAsY95pzjkIXzq+a8RiTm2iMkjNbwmhyG5FUebp53mbavRJTTu02790IW+n8E3vtMZGH9WpnvqbUw2IB4lK4NHNsbUaQ+Z+6bzyA5Hx5iUe0z570JEx5a4zZ3IaFz30cKq3hICK0tAPB1RCgvmNd3Crz3ZPyQGEUFc8/MuJz0QOMXU7iPgJJpxuYwpmJq4PjrzblvN88XIZ61rwOX1PI3nul+MX8HAseWI55JhVgVr0OEll+afr45cO4nzNh+adR92Uo/n2va+hF8r+zBZtyehRQTeRsSZnYossD/CCMsm7H/T0youjlmq1C+v9b9maaPr0IE/kPwCw99GFFErkAW/gKi3OWAL5pzViAREL9E5sBPUsV1xVyHR8zY+Am+df3liDJyH2IgvAIxvD0C/MHer4gH/WkEvJbb2J49mVp4Yxfz3e8g4Ckwr1nP2XcwOUL4Iem2ENWp+FWiKz42KJUhlLmXx/BzgPqQ+XwjMj91IwathwkIjMjc+z7EM/gA8NHQ98xbuGVqXlWwzW2IN8Uz7Ww2/bgdUUI/hyjNWcQ79ih+1fOXI8rDu6IYZ7Po94mmX0cgETTj+BFPxyNGcOshDOYP34FRKsyxOxAj7Q5R9yl0r4UjpVYTyL1H8kpHEOPCN8z/G5Cwyk/a+wox4tQsZJKQ5x0x3Lw5cC12NO0/EjEs3YIYci5GvGWvM+f1IfOqR2kF+KqmnSAK3MfwI1EazJh/E7K11PFIqsxvkMi1HkSnuN38/lciBttfE6oDMas2RH3zJf1hLtC1iKX1PRhNHbG05xABYwsySV9nBs638IW05yPx/u/AVPeJqB/TlRV/i5nsXhM6/jFEabJJ+82IQuXhe3pWIwtRTSvo4Vt1DkEEpQ8TsH4iuXL3IXly1lr0Y9P2c83zXiQ86YAat326ZP9vIxaroFB/GiKMvBg/9+8a07dg+NffCVmUqtyHxchC/y8kT+49iFdmMyakCpmQHySQq4JYfA9BLMGfpIJWUXzP8PMR4fOdgWPPQISP4BYA2yET8QcxoauBvn0P8VjsuLXrVsPfPCyYHYEIJfuGjm+HGJx+DjzdHLvNXKsDzfOdEMHxymDf4/JAkuP/iMylP0A2534jYnhrRnJUPNOvoEfhXMQi/87AsY8int5jzfMhxNjynFr2qUwfDzDj+BH8xf7Xgdc/gBgUv4kot3sgRsYCIQsw1VX8OhCl6W5kvnwLogCOBe6vAcSgFpy7XocYICoeWoU/p/8cEbj3RCIJtiBr1qj5TV8QeM/xSKGjwwPHrAHzPkzxJ4yhocLtLanMa+7lM8w1vR74S+j8V5t+XYOEvt2MGAnCFTcHKc0d2uYQPHzBOhyW9mb8wle/NGPPhu0/DVm/foIogU9Hog+uAf4W+IzrzOfEshAKIudtRAyuwRSY5yDynS0qFbwGf0LWM+vheS6i/MZGAQy0db25Bg+Yx934kSF9iHPiamS+PROZdz6PyCA21efNVDFkMtDW8Hp3GCI/fBcxaD4z9PovkPXMGv/WmrF9K36UwOGIB21lldpcLlqwCUlL+hsmtciM5XFk3hlF5rFvmP9/YM7ZGVnnfgd8YN5tivqmS8qD0gnaVjj8KCKEfM1coDEzqVnvwrPNQHl24L2fMAMkNqFUlFp/WpnqSbsO8VDuaZ4vRhagL4XO+7MZfPfVsO3BkuiN5jqcHphwL0eEvueb581I+ORvKS1I8CP8PZPCFTWraQV6NvC+6a4JvjXxVYh1zYZbKNOPv4be9zPTh28FJruaepSRENUJSvNn1iLWwqsRa3sTIuh4GO8Zkvg8bPpQlUnYtOUKZOJ/lnn+BuDvZc67FBEaw4vJKYj18K21/F1n2bcTEePFIFIk5EeUCiSXIgvLHpTubWa3srDbBzyHGIQllenfLsj+YVcjintvmXN2Q6yit1Aawtts3nc9prgVknP2Z8QrHAvBE7EK/wjxnu+CRIw8CxG0vhqYG8JC+OsQQXTXWvUF2TJlA+K1D86nDyEC8w6h81uRsLGfEvC8VrA9jZQWGLHVCb+MWNW7EGX0GmRdsIazM5FolqPM804zH30HEbxeXoPfsg8/J/2d+FWphzFhbOY868X/D/4WAx+1/S/zuWW3fplj2zqQwkm/CB3vQZTVB5F5tMW0zUOMv3Y+aaQ0N6zRjMUf4yuVsTE2MTXPbwfTJw+R4YK5jCsQQfwX+IX+7Bj9OUbJrdWYnGP/Gsz99HJkfvkh4nm2RV9+j2/IUYRychEv+WMEtjSrcT86TZufQDyznWb8XI6fTvJ0xNgU9JKvRpTcx6nCPLSVNtvCY/YaPMeM5WCBue0RI669nxoRL+zjlBZL2qZ83shvxDg/kMVtN8rkD5hJ7r9IPK5dRHZFhJMpm3uaC9iEhG78Juq+2TaFnl+GeG6+g9m7xRx/LiLwXoavkPwBWeC3RwSrUxCr/JsxSf+1nPCQhXJ3xOv6c3zP5FJE8fgWfn7i+xCh5WBEWD7K9Oc1iJdA1aLt5nezBQf2C7T3q/jhJXYB2huxPh5nnrci1tTbA5+3F+IR+SZiga2aFY4yYUSBtp6E5FQOBc9FKvt5iKfAHnsFIuz+GhHEK1qYhlLjhp1wd0UWrc/gKwV28/bgwt6JKEvfY6oiUVPPCKXXUQAAONhJREFU8Cz7ejwirNrwO+vBCO7P9AUC+2shAvHvEUPWY8FxH6cHvkD1fnNNnh56vWSLC8S4kMePRrDvPxbxgH4icP7F5nNbajHuy7U5dNwKLC8LHOtBjBZbKA1RajRzxtFIePM3pvvcbWjnTGP9dEQoscLWGnwj1AfwFYBOZH49GzGA/pfAFjXb0Db7+WGjpZ17PoZv6Q8KTiciSuonA+2+ExF6z0UMJXcgindvhX7HQcS7fKH5LdYHXrsU8Zz9xfymNsd4pZl/HsI32Ng1+OmIUOiZa1+VHD97vZHUgmH8fd0uQSInfoYYKBsC4+zjyHp1ROhzupCc1TMQD9PZ1WrzPPs52Ycyr+2PeLweJ7BVjvn7OgJGccSIsx+iGJ8Tdb9m0e9PEfAkIfNnAYkimRzHgdcHzP13NaKA1VR5N9fprYgB/eeIB9DOQW9D5I/jzfNGZG2zKVnNSD77zxBF8cwatbkRCeO8kan7i34BicI5wfYv8FoLMsf/hlBl4m1uU9Q3Xlwf5mJ92EysVnA8n9KtHDZRuq/LhWbQ/JrS/cL2RBaSryOKxyvM8VhYhExfP2Am5K8iltFNBKrFIdbo2/BD+PZFYvnvMwNwi+l/VcvEh38z046HTJu/gIRM5RA3uvWWvdUct8nArYhSOGyu7ziywWbVJzGzMHwycE8tRoSO35jnS5FQhSwiJNhJbT1ioQ6XL34IERouMn35cZXbH5yYmpG8mJLyy4g18X+Uhlg1IFbkfyNhMeFy0RXdoJqtCMGIt+t+RCB7GFP5Mfx+xLBRMP2MzXgtd00QS3QWeK553o9Y7W/DF5TPQBSjc5D8iNPN/bY7gWqgcXyYsXMPs8i1NOPo74hQHa6U+Xlz7W3Rn5oXeKI0oqQ99NoJSLi0vWYXIQrhTZh8MHN8pbl215g57FuVHkehdr0CKawTrD73WsQ4uBOSX1dAjGkHhN67Dgm7/DeilG1TkQUz93wEWZeaAsdaEAPYVwLnPooI7WsCx3qQCJ5h/IidU03bH0Pm1YoVzDHzzDjilb4VMbiMIwbTRuBdiGzwnzLvPQGZT8t6+ZDQvNuo/h5/i5G5+6/m+YHmt92CH+456Tkz9/A38QvCHIkoC9chESIXV7O929jXZyIhq19FvLF2jl1m7vfPUpoa0IaEP+cQmehqc96fqGLBtW3o31IkEsLKRDsgSt2eiCLyKGLI/TSiyFvP+ApEkfq+OX4tJhS2xu3fBVnHPEL7cprX70c8srYwjK1K/ydE8RtGwpCrkrox3eci8kQeY+gO3Fd7IFEoP8AvOtWFpPm8wrx2DxU20EZ+I8bpgYQUBQtB7IJYQD6Hn99mc0VeYQZAA6LcPYhM4K+ntEzuCYiC9CAioNd0C4Gt9LcTERr+iMRO74tYz1uQBeVaTEVDJOb4EUR4stbVFyCL6M8wXocqt7ck4dz8/ZwZHLuYSXhXROh7MPhbI3kSv8ZfqNYjlt6vEMr3obohnyeZdgTzx55v7rOXmufNiLf1SQIWH3NNLg9dv5eY++pu05eKWoGRXKTe8O+CWPKfQKzmm5AY9jPMa13IAvJFShXDDsT6lUcs150Vbqsq084TECHkAwQKNyAFFO7C3x/ranMvPYepoXV/RwwEkezRhHgOpnilCSjRZtw2IErClwLHD6R0i5ZVpp+euUZpYiyIBa8tEgr5CCaHj60r+SeZcRVebPdGlKZI52Jk3bjRzFeXBo4vNWPkU4in7EnEw2AjTZ6Gn5P2ZnPeXhVsVzgnbTdEeduMCPt3YMKiTVs3mfvpHjMf2Qq+Q4hHch/zfHcqGJVg5pf/AKcGjg0SKoWOGKQ84CWh9z8TUcZ+FjjWROUre55rfpuzEQWiGYkg+pYZm5809/d1SH6Z9S7ZNIZeRLkexqwbpp1W2drP9K/qioa5viP4c/0HEKXnUPz517b7bMQgYLdV2RuJuvhQJe+DCvTJtrvBPN6JKOc/QkJUM0jIsr2P32SOTdkWBvFEfRDx2k7Ziiei/pWr7bAzYlR4XfB3QAxKv8bP/dvJ3KNfNmNrNeIJ/iEmraaG/TgQfy5vR+ZED3hb4Bx77z3fvPaqwDi5EIlu+wVViuAJ/9bmd24MtKEXSUG5k6nhtB82Y/yV5vnB+Irfp6mCoTLymzMuDzOhhsPxhpAFL2tunLWB808wF+Z+MwF+Bj/nqhXZd2p/RBg+jkByeVT9K3OsE4ln3wz8PPTaAea3uABf8PgAUjBhm0t0z7Ht4XL0X0a8X+2IABDORVyBTOCfxK+c9wJE4J205pX5nmruU1NS3tv8b5XYPsSidg+lhRLehgi830fy5t5lJo6wItDLPCpAzaLNZ5p74ITAsXbEI3EXYvEcMO3/IyIY2mTwtyCCmK2WqRCB6wrEyn4VFVBWzbWesmcmEtJ1DSKc/sB8n4d4VfsC/RtDBLFLEGE8jSyMP8avzBVZLhwSsvgFSgvUdCPCycOYxcLeT0ixhZ8G+tiKH45l56cGJOz5TAKRCnF/mDHwiOlP6yzO7zDX8TYquJ/cPNse9kLuZsbLNxBhyoZM9prr+FX8fKMlgfdtb679m8t9bgXaGZxr7bz/QmTO3QkJ+3oIMZhYReVS09Zgzu9iMwfcgvFIV7qNiBL1NzO2rZfpDERpbqI0nPufiPV/h+Dn4HsGXlDJNga+YxAxzn0RUxUz9P2fxa8u+SxCW97grxsHmt/ymjLfcQpi8NyjGn0IfVeHuV8fMP1Zbuahr4TbbP7/B2JAs/sUxqnCebCd1ou8GPFSvwM/gmid+e1/bvrfYvp0Nb4xfDdiuol76D4K9vkWSo2Fu5p7MRh6vheilDyFXw23aqHGge8NK1JdiFLt4YdHr0IM+7+lzHqA5GX+nUC6AJWfL4/ET8sJ1qN4MbLu3IYYZYNjel9EPrWpUnY+2wFRtn8TGC/7UmZz+4q1P+obM04PM9CvBW4wz3dGhMhhJFa4NXBuF2JJeBI4zRyzJeVPQ6woFd1wd559CisLu2C8Beb5AWYQ/SvQB3tD/gCZ6K21t9309xdUQeGYRV+6EIHo34ilbSWSN/b1QH9s2z9grlswZOpaROjaPvS5VZ+4YUqhnU9TWtVvHyR/K1ihsAURCoYRA8Q3kXytqi30iNEj6MG+HwmFsfmTfYgiasPn1iBCdhERXn4YeO+3EQXsr4gyficiCFWkGh0iPN2BLE6HB17rMffEFZRuDHsv4skI3hN/MWPcbnOyDvHu/4TA1ghRPfCLD7zF3AtPIRbY3c1YyBHY5BzJZbufUkF+RzOOvxZ1f7bhd7Dj+4dm/K+e5jwr6Ng98ezm8JdWu42z6INCjIHLkYIZ78PP5zofMTSeZJ4fioQtfsVcvxWIsPE7ZL6u2NYo5vuCwos1sv0J8S5eTSA8GFEINyBCskIU1lsQYeeHZn64xZzzykq2s8x1fiOiYL3NPL8SuML8H7S8H2jug/MpNcI9DZmL96xSO49C5vVwSGxD4Puvx4R+Isa+mwnsmRroy7uRqIs1gc9ZhcyrN1EjQxVSqflR4IPm+RsQj/VB4fvJ3LNPEtjmJ8qHuV/D2x6cjBjNdsQP0RsKve6Zsbe9OfZsc+yH+Er8a2rZl631MfD8BNNOOyfae+99iCHXjpGdkTXyEvO81VzbyxGjysVUMTpqFv06EDEA2nz9Jsrnudt7b0fz2ruohvdM5M+bEOOSLWQ0YH6vx5GooWOQCAAPX09oRrx9mwlU/kcM6w8ha/x5NflNo75Z4/QwA+dkRJg93RxrNIMgg5/8HNxI+XpzE5yIhBx9ERF6/x8VDnHbxr4dZwb7PcgCc1ngtXMRQdIK9TaEZwCxSHwMP/fxOdS4hDGSy/QLxNv3G0otOt9EQiDDk9txZtB9Db9c87oI2h4UrOx904ooqFvwK1F2IKEjI/jWH3v+i/ALK3hUqeIWIkykMZYpc+xE851n4S8UNiz4JeZe/x3iGfg4IqC8wLy+2Iyna5BJ8iMVaueJyAR7AxJm9ApCVklEYbLj9QLTrxvwtw6wuQFHmc8qCUklwoUu0Ab7e9v9QvOIYruzvdcR4eO/mApiiJc1TWD/QnPeRebaxCb0ap6/yaHIXHU+vvIUthbviQg82yNCwnmE9nOsUVuDQtixiEKUQowQD2EEgsA5dyBGqtWB99xtrv315u9PqeIeW+Ze+ZH5vh8hxoQMxsodOO8niHX9cPN8KZIPeA2iMH6GbVz/COQzMv1G7h3mO/+ChBheC7wq3Cfz94fIGrjvtrRrjn04Gpk/Dwy2JXTO+UhO3LORNJS7gM8HXrcC7RJCeepmPHyEKuZ+lmlvIyITDCNraiMyt/6RUuU6Fh4x87utKHO8B1EqHkCUoe2AlyLrQTfi1bvVXJt341dvtPfTW5G17wZCm7vH4YEf8XGq6cd/KTWIvhUxptmCeT2I/DqKrCsfRYy6x1Jhz9ks2v4805bgNj4dSKROEX8NtHnu/6K0HocdM6/EyK4VaNMUmQCJKLoTP9JpDwIGM0TW+7qZA+4PXJNliDx7PSJbPRdJBTiKGjqOIr9Jo3ow/b53i5F8uMfwBbBuZLG7hqlxu89AyvH/F1nAb8EI9XF5IArEk4iAfgpi1R3DbD+AWDKuBu4MvMcKV+8xN+/hNWpruTLWHYjF5ClMqCq+cmQrf76XUoHhbfg5Ts8NvacmCxOlAuArEKu6ja3fAwmFvClwzjpzH00pS4xflvnnVCmMBrHkX45Y2VYHjl+HLCDB6oM2n+9yfOOAtbL/ltIE+RYqFDaChMj9ytzDyyn1dE3mLgXG7qfMffAG8/w1iKfl5fgL+Y/NeH9GJdq4jf2zbbKW6jZEAPeQBWJpmXvrLcii/RFE4f4bU/ft7Cw3tuLymG3bkCiEL5u5YEoOCrKw/hDjBYr6gRhGjkWs5xcjHpFPmutZEsaJRDV4iMHRGuG2Q5SIl1JFJRYRpG5B1rhvIJ79diSNYQIRkINjeg8zZj5BqEpmJeYnxPM9AbwxdPw0xLi3InDsRYgg+4fA77eeqbm8i83rnwy/VsXf9bnl+mFes2N9N8QYaIXITyEGs1OD5wXeN7n5NREZqsz1uR240jx/HjKv1my/2Vm00Xqy70GU6q9iFCDEK5ZHPMbvx0/HOA4R1G8198p38Q2eDUil5UMD39EfdT+n6fupiKK0t3k+ZPp0k71GiMGkSKlSuAOi3N+KKDZnVLmd08nhb0TCJF8XOr4LEmnwq8D7DzTnvjFwXsVlPHwvX3D8DSEG5TsQg2MDvuH5LPy9R1+JGGA/Hfi8vRED30bT/q9R44Jkkd+oUTwoFRrbCFkqkQ0hhzEhDubYMWawvCT8OeYz2ohoL5St9NXue/f94GSFWMU9/ATtF5sb1BZYCOZPVD20gdKQjEYz0FvxhaN9EWvJPYHz7GsfQPK2voqEtB6HKC2HI97Or4a/o4a//wGIcPIwspicEXjtLCQM4HXmeQuStFygdJEpu+9Xldq7E6IwfTbwvTY34FL8+PtjEMX7eYH37mfeuwF4T5Xa9yzzvccE74Fpzt0DUWbPC7R7X0Qg+zH+/karCezVGcWDmcuPr0OE2hyl+ZjBeewUxKv0U0x1weC9E9cHTKlouNUqwkgY8p2IYPdGRNDbAQlNuxqpwlf1olSzaOcgfu7pbfhhxn34Ob+D5pgVKH5i5ouqeanCv3mgTXbLhK+EXns/4unfJ3T8/8z4qnhOOKKsfRtRMlsQRfpBxIM/av4/P3D+N83c8zAy948jFvbLECPtbua8UwmEUNboPnjUzDfLgtfa/G/XsEfwt6R4mhnLn5tpfov6gXgutwBHmue/MeMv8jYjVVfTiJHy1UjhmfvNdWjFzx+blIEC77Xb4rw+cKwRkSt+R4VzWrexn2UNAEj01iNICHmfObYjomRkEEPhdohj491l3l/13HBKo6PKzUl/MGO5JIcPkZE8fMN+B2I08ajC/sGE9sDEn6vt2D0KMdgE9/E7CFHuLkPm1g7EsDZBaYGqIURuqmlk2uT3R/GlNe+kWFZ7gxfP/H8pYvX8C+LutgJhH351KxuO04RfvecIRLj8CTVeTGbZ31fiV5RcgcR1XxB4/W3IInoDvoVoEBH6n8DP96r5RI6Eoz5kBs+/KK2Odw5itXuFeW6t5K2IIPgUYk0pIMpgJxI6el0t+hKexBBvxE3IJLwLIWshsgh9FxFabMGFxcgicyNV8PTBlJxQFfrbgCzsOUwxJHP8C+beODTQzpS5Jp2IAeTjpj+fB06s0m+8G1O3KGlELO2HEciNQsIhPUoXkLMRb7iHVAWLg7ASNH48DQkfv5SQYI1YZf8IbDfNtXwFknvsAV+Pul9z/A1OQebhqxCvclljGqW5U1839+AIIsxtQIS3dbVqt73/ZnjtRciaMWmxNn/3RoTnS0P9Wmau30ep8JY6TPWWh/f22gfx6vwqeD7idX8YEWCCYVb9iLK6zdUAKROmhVj2n0JC488x88oeSK7SDxGj3znm3APM+PgaEo66v5mPbkXWut8R0UbjyNqUQ6IO7G8avBYrkHXr/MCx/WrZxnn2a8DMRw/b+yEGbepE1iAPSVHoD4y5ixC5Yi/Ec3SaOc9uhWAF+mfhV0E/Ekl7eT+y/n2VCOofzKLfz8F4xSkNf8wj3lk7v/Qgct4DiIHhF0gOrJWlarH/cXjduhCRpT+LRDvYth6FrNXvpdQhsQdi4LkhcGxnJCe5Gp6/4B6YB5tj4WiIR83jCHPs/xDj1aLAeVZJ/WlUc9GUvkXdgCrfaLsi8dxPAC8KHH8GImDfi8RBX4QITn8NDIS9kLCBHwfetwrx2DyACB3/QcLQogrDmM76cz3+vnLdpq1nIxasBxBB6Vx8r4gN93wuIlzXtCy8GWANZgDb4gJnIFZyDz9UdQViwbsPfyENWpHWIEK/jQ/fDRESqlrMg6mK33sQYerZSEhnuABAsKrf800bP2E/yxzLU8HS7oHvs4rmtMIlIkDdhHiObWhMKxI2/GX8ymf/z1yf35jx8yQ1EFzM/X2rmWT/H2LpTOPnSH7cjMsdkdCMH5uxuxey0BxCoHBKLe/zGV5rRULTUkio53WIUPjewDU43PTv9ZQuiJNKPGLVrUrhjSr9JsuQMKwNSN7YRYgy9zv80KuZFKx9EWv26ZSpBluD9geV96MQYWvvwPw0gCz8BUqrSDchYZVbCJT2N39fRhVL+pv75+/mHvsyvlDTgXiaPfzCX7YfrzBj7FgCRSZmmkdm0Q77Ge/HrzgdDO3sRAo4eIgieFTgte0QZW8T/pz2YcSr+tLQ9+w+3zZW6PduxA+pe37otRbT7/vs/R5+b5Rtn0XfXmju45KtQyJsTzlh3YbuvdDMqbYyeC9iMLqRqTnkRyPz8JPmut1LaBuRCPsXVqAON+38Yplzr0eU9GWh1z6AKLkexuBTxTYfhBj4XhQ6fpj5bW2V3J8hsmqw3sC3EUdAsHDb7vjbsm11T9gK9cHugfm3wLEOxLhfRObSfwJXm9c+ijhYrDNlFWLc/AbigZ0y1iO5n6JuQJUv2s7mJplAFro15vjbkJARm5C5DlH2POBD5lg7YnUsyX9DlIrTiHhbhzJ9tVaTJkQA/jP+XlHfMP1II0KWtRQpRDG05e7bCFQlqmJbyyXTdiEK9WcDg78VUdCz+BuRvgCxrFilMKx8tZkJ53Qk5OMfteiT+e5uM2FtQBTAFyAW8rchhUs+giwkNyBejg5zn30EEWT2CPSht8JtW4x4uy8PHX8eUgr9BfgVzhqRHIkipYaTNyKW7JMCx96FeMavoEaV3pCk/j+Ze/oxJG/p/5Aw5s+b+9xWBXw9ImQ/ZP7eQJmCADVq92QOQeh4k/kd/0pAQESU1WHEIGCVgyuQucpGK+yEP49FLoCF+lXW2xzq91lIsZGg5/b3yCL5tdl+dsT9fBoy3z6FCAHjiOJuK7MeZuaBK0PvW4MIQLZqZVX7hOSo/BoxmLzbjOerTZutoLKjGVs3hd6rzHm3E9iqpkLt+ooZy/ci1vGgUW8vxBiwgVCYFL6BzY71FeY6/I1pqsRGeI/siRhfh5GQxP0RQ/RbzRz2fjMeYnNfz7JfsWsvvrB+feBYD2KotIZDW6jMphS8Otwfcz36CESQRNCXXvwotOk2F29D5Lo7MZVY8deLQ83YOjs0rrqQNX4TxgNahbbvYcbjg2beSCOymTJz35VIDrFVyJchBtC/YCJ88GXznyNh4ENmrHwMSe2oWb0N/D0wT0O2UJowc+LzzOvvQOSM5yMRCY8iRoSXIp7jPyO1HKq+jcas+xR1A6p4sZS5Wa4wF+lhTHUwxNO1I5If9wUzQK5E9gMbwd/faB3iBbkj6v7M0M/JggGBY28yg87mHOyLWIi+iu/ta0cs1r8xg6kWe7vMZMnfFfGEnR04Fiwx/lNzbJGZNDbh59QEJ+1FZgJ5BPhoFe+thtB3fgcR2H9B6QbdlyNeqPsQBfd9iHXIwyQtI5P0I8DHq/jbDyIKsa0WuQNiGdxk/j5CQHBCFj4b8hzcm/AuM6kFN7KvaKjaLPvTggjevQRKdpvXbkDCdxoQI8K+iLBblb2+ZtHWsjkEoXNOwQ9tfrYZv4+Yv3/BV/KW4Fc0tXPXh6Po1yz63bu1+wPxKFmh5XxE8bsR8f4/iF9NLZaeEESguRkJSbRK+Tsxe46a561ITtIovmBji/yci6w5FTVKhH8vM17ONO20hqZeM+Y94FvmWAPiUS0E7sdgHvaLK9hG6wF8hbmnr0Qidn6Kn5rQZtpdxK9SbTd77kEE+k8E2ng+Eho8VKl2VrC/+yMGwo3mXvi3uU9iUzilXh5MFdbHzO/9QcQrlkYMsx2I9+kRQvutEbFya8bsg0gESzD0+hwzx+yHb1Q83MybwYi1RkTG/S3i7dsl8FrVCuKZee2N+HvwHo44Y5YRKKKIpDksMWP8a2Ye+rUZH5/FN6CdichOI4g88gQm1LLG16MDfy/CjUjV42BdjbWIMfoG87u/DpH9HkccETWvRL3VPkXdgApenFcQCvVAwm9+ZS7E3xBBKjgIPom4l20hFLt1wHcCN/KLzbGDI+7flBAL/JLof6S0aMjO5vhhgX68AVl0rjGT4LcRS/U3qbBFdxZ9ORWpiHcqfjhhNzJJT8ZxByapNyOWIXvuUYhC/8bwb2T+7kMNyt3jCyKrzH22AVNAIdCWNkT5enrovTfiV1BrJLDRdwXaFb5PbFuuMONgNZJgfSVm/ysk1yFD6QKyr70mgWO2rPmrwt8T9QNfCPwx4k2oaUWtma4HU8OSwgK6vZdeg4SZfwJZHI9ChN/X4oe6vRjJc/kroXC3ODyQhfInTPUiHY5YQ/cKHLPe/vMQYedN5vl+iADxq8A5Ue5BNZ31/QVIor8VxC4w4+hxJEzJKoXrEc/mDaH3t1PB4k5l7qs9A/8fFRjv70WUvN8gXvNx/C1pliNK1BO1GEOI8eNxxDN2DCKc/yvw2y1D1q27mboNwgPA56K6L+bZ390Rw8FzQsdjXbApSQ/KC+tWfuhCom5GkbVwJ0IVGiNu+16It2spIiOlEafFTkjo9uOI/LMBuCjwvncjRt5w7rjNifwQtTH074wYxS4lVDXfvG7lkQZEUfo1oiBZY9+XEGXPGnyUGTNvRQxpNdvypEzbD0WM+V8I9iXw+isRI7ndS7GXKu7bvM39iboBFbggwYF+J5LfE/TOfBuxLuyKuGwvRoTy5YjA8aHAuY1msshjNpZEkoirXhFpK30MJoz3U5qAuiuiTNyOv3nsOvP8naHPeb75Pa5EvDhVsaIgHrGhMoNjO0QJH0Y8NHnz1xYW+TIiuC+h1Kv3diRMxnpmm4gojC/QptMR65bdAsFujnyNeT5dRcdORBD7D6GY+Aq2rblcGxDhdBTxMF2Avz/iBYiCfS+llWHbkbyaDZjwUHP8tVRpK4p59DV4nygzQd9FoIJbHB6UCUsqc84AEq3wMYzFF4lU2IBYrfcMnBuL33+afjTiF2w6zhy7ClGMnjD32On4Ocj9Zg77LtAV+Jx/IUqgVQqjyrUOrif9lOZfLjbHVpnr+xjidXgBIox9LXDuKxFl/i01aPMrEY/HbzEVbvEFr4uQXDlbDv4AzJwceP9RiIJYNQMDvoFv0Mw/tnLty8z8+CB+td+jzTlfww8FO8WMjZOjvufn0t8yxyMvRFWPD6YK60E5ak9EsbJFhD6IGBN6I2zvHog8dJdp9y8R48f1iEHttUgU1w6Icvh9c65dr3dDIpBuxY/02sXMq1chkVQ9VWy/Hc+fQBTU5YHXGigNQV1hjj0PkbmPx891t0agbxKINIrDA38PzM34KTNNgb73IrmMdxLyKMfxEXkDKnBBrHX9EcQy8sPgAou/R1AjYtW8CwnFWIUIJKcFzj0DUZxuxwjyUfRnmuODiPJ2EyJovBFTTARZwH+K5KDY2PZb8MtKN4c+qyrbCSCL8heQWOdHkFDH4KT7EdP2vRGP3z6I8v4AfkjfZvMZdr+zfjPRlU1UpopWU/wwrXL71LwPEVDs/nKt+FVUp3h5EMPEa8w5w6bffRVu7yCSjPzdcvcU4iXfAJyEKKJdZrJ6HMkR2BkRGO8OvHcdMkFfWc3fehv7vc6MgTcjMfhXUYVy0BVo50vMtbeCd9hbs7O5f14XOHaoGR8ekudR83DbOfbRemFXInkbtyPeryuQAk1PQ8KlH8JUijVj5ylKrdlHmDnkVkQ57IqqL+b/HRGB7AbE8LMidO67EIV1n8Cx2xAPulVi1iFFi46sYpsHzVh9AilG9Xz8sO4G/P3+vkmpInuPucfONc+7qWIhmsD3KsSIez3wa3OsETEC3mHGyxnmHvm4aeNDyDqfMv2IrTHEPaJ7UCqs72CO2fnpWHP/WC9T1RSjWbRTIUbYETO3PBuRF1YhRtgjzH2/CbM3pHnfnkhUwbX4xQtPRQxP9yLG27+aubdm6wYig3zT/B+WPXczbf4H4tV7MeCFzvmUGfdpTBh6nB6IAv4v4Ceh49bAthcV2ny+6n2JugEVuiBLkWT2e5GiAinEWtKJhB3djlgcViHC7OfM+65GNPXXIxbG3yKbKu8cUT/ehFhn7WAOhjTeawbzxYjL/Cngd6H3X40s5GcjYUm317DtFyAe1j8hsfUXIV6xLjPBLUGsWh8Lve87ZnI7wTx/KSI03WUmgmsQr9VkOECV+7GCMtUE8ffrstek11yHP+LvMXUYIqz+KPA+q3ydZyaN6zBekSq0vQER+rJIYYXdzXHrEVxkXjvdPD8dEaaOxA+z+xylgmCLuSbHRzEmZtHndeZ+uRkpCPHGqNs0Q1s7kAX+AXwLbdC7tAYxnlyFKIMrzfV4G5KwH/lG9XPs77MR4WuUUuWuw4zvH+FbUT+HeM9egZT//4a5l59JtCE/DUjEyE3munzG9OevmL36kHXmP8A3Qu/9oxlft1EFLw9lwlIRYfFupLhFuVzTQaYq28817f8bslbW1COFhIH9yHx3X6AfTyBCbx5Zo49DBMcbkciXvaO+x90j3g98Yf3HoWPfRhSnSKO7THt2RUI73zHdXIfUEvAIyQ6IXHEfxumBGEoOQOSmWxGPec2MZ2Zu/zkBBwq+DHS+6cPvkUiIdyHePrvv8I5m3roG8fJXLN+4Cv08H1HYbU53Ir34kTegghfkNLNYvBCxgtxqbiqFVP+zF+oDiBfkeUgY6L/MgjiOWE6jFDa+iAize4WOvxtRANcFjp2OeDCD3s4VwCVmkNl+VT3+2Pz2dyBeyf5yg8G0bQK/4MOZpn33IiE/QUH4uUg46G+QfK6qV5dEhLjPmn48RWnl12MQIeRp5rlVAl+CCFvBMOLLEAvcaeZ50Mpedm+zKvTldESY/julZdWXYApsmOeXE6rqhwi4m8w9lAwrloSPnEzMvWOmrYcgnq0Pm+eNlIaxnot4lh9HlIcHgUOibneZfuyGGG/Who7vY8bsOiSk9SOUbtprjVtnIQL+eeb5ICLcbzbzxK21GPfmu3ewc25oHtoBsUR/DVFQrRFoZzNHfCpw7MeIF6sfUWiegwiYH0MU2VYqZLxiquc4WEH1g2aMDyLKay8yvz4Xf//IL5v7682IovUT877dwp9dg9/ezqUXm3FxLCIg5pFcoP2RyJ1RxMhzNjEox+8eyXngC+svQPZi3ICs8/tG3C57738MCZkMb9UQXBfWmTHwYQIeb8T5cYWZO9cEjrdT4QijOfTr+4hBaffAMYXI5nYd+JQZ7ycga55nnueQYoyxXsvx98D8X9Rt2aZ+RN2ACl6QDjMQ7jUL33OQqpLfQSyw/2fOU4j1+SfmIrYg5ZhrslVAqM0l3iYjPDxsFuhuc6wdsaj8LPTeTiTW+immVgG90AyoG6myhQupFnmH+Z2D+TuNlCo/7fjhq9cjQt678QWoJUxNiu8JfV5VvH/IFg2PI+FdZyNeiI7A6+sQ79I3y7z3u4iiZTcA3Q0JFftz4BrWPHQSUYjuMm2zIWjNSFGN35rnFyHWt2PN+NkfEVrPRBTZrmr95gv1QWlYUrCSqjJj+gXm938ngY2h4/Ywc6aHKBHBcf4x4OeB5/shHs9vmOfBsMo/mvlgH/N8kfncmlV4M9fjLGTdsDmJRyOex04ktN4jtJcofs7Qqeb5MxGD3B1IeOIGxMJdtfBEJHzq34gR5xXm2NPxS6n/wsyzmxFF9n4kTL8TmYOfRAyOfyT6PPejEeHPM3PUkZTmur8buDTq+949kvdA5Lzf4m8JVtV9gefRvj8C3zb/T1t0yazJw4T22kUUq/soI59E1J+DzG99LgFFjtAehoiR5yuI7PFMJNQ7MVEu5nd/LzHZA3NefYi6ARW+IIdg9tQxz/cyi2MRqYDUZY6fbm7QMyJqZ9jbdETgtVeZhfA5+Baiq4A/m/+DeWVHmMX+ZeZ50Hpdk5KzSNjjZkor+wUHeR/ilTwdKeYyhuzrNBQ4ZymSU3c5oSpv4T5Xof29RuD4FOIRbiz3vYhSWMTfj9Bem8PNpPxl/FDLN5rf5LRqtXuWfVuHhDg/jCmUYK7BU7YP5h7chCh+GxFFvqYbpC+0B+JZug0TKmzmgwPxq7W9vpr3fAX78XEz3643z5sRj2Uwh7ENCav38CtQ2vDXQxEl5FNUKS95lv3YBfFGfg0JP/IwyjcSKbIZ+Ih5bj2YnWZs/Rjfs3YS4rW6lgqsLZTxwOPnzF2OrB0fMm3cFT/U6iWIYPJ1xKCwAgkL24K/9Uw/YqyKhcBl7v/HTJt7g/01f2M/Htwjvg+kFsQ7KSNfRNyudiR15zezOLcLMTqV1A9Aogs+jdnLMA4P/JSscvUQms3ccxvw1qjbug19TKTSV9KHqBtQ4QsStK7vbI7tYwZ+2Lt0RkRtPJGZvU0NiOfu9/gbuZ+MKB/WUm6Vjx2RsIBTa9mHUH+OQhTWvYNtM/+/C8k58xDv7ImIRf1BRAjeAfE6fd9MFlWpirmV9tuNYK2XrGwsN2I5/z2SJ9NBqZJ7K5J7eYZ5PhC1YEVp/uj3kRDnsxCvwZP4lQH3RPIIvgu8PMo2L6QHfljSq/ANI3djQmSS8EA8dhuQ8Mh2xNs3QqhymxnnNwF/Chyzgv0VyMbMkYX8GIHkRqTq5fVIkSprzOlHwqLH8PPT7GtnIVEmb6xgW+zv8n4zb16ACePGz9Pd0dwrp4beO9M+q09DQopfV6m2VuE6PARcHvwd3MM9KvGI8/2EKHR3EtrGLPC6HfeNiNcph6Q9qPA5cXkg22tsQbab2jdwvAsx9lyDRErZSuSxvT71/Ii8ARXvkJ/0+9PAsaD1IbJKhsze23S4WfztxvUrkJCeG/G3HWhALL1PEQoJqHGfrIX8VaHjByNFUl6CWKELSGn4HZGwryeR8CWrDEeyVwpiidqEyRG11wLJmTmMwP6PiLKYxRRIMcf2R8IvHkXCimterXAWfWzE3xvvFmSrgdhYCxfiAzES/MaM83HiHe6pwgIGvoHhXKRa28FI4a3fljnHzlUF/CrF1pNWU8WP8vup7oBEWTxEqLCWeX0fRNH7knkeDGP9O2IAWlvhdn7F3Bv3Ikaz4Heehqxx+yIlyAeR8KkzCGwVYs5dhijm3zfjfl0l21nhPv8QuD/qdriHe9TyYebOkpDJ8Bxljr0R2B4JGb2bQBRVHB/INi1/RxTBryH7bn8biVq7mlDOo3vU/mGtjXWFUup8JF76xVrr3yilmrTWBaWU0hF2WCn1LEQBPFFr/UvbrmnO/S6ywD9Ha32/UmpvZOD/G1EGH0Osw39DysqP16QT5dv6GFLd8jyt9VPmWDMi5I2b5z9Diicciyh/uyJVWTdrra815zQAutbXSCl1PeLB+B0iIJ6CCFWt5pRPItVL/6eU+iSyx9aHEG/By5Brcgey8fWWWrZ9ayilGrTWnlJqEPE2XYxY4d6ptf5AtK1b2CilXoSMiY9qrTNRtwcgPEcqpRq11kXzfxfi9XvQnqOUakGKc2xEtg6we/8Nhz53BeJJO0Zr3UoE2LFg/t8Jyf9+WGs9avr2HMQjebLW+seBsdMGvAEpwLCX1vpfSqlWrXVWKfUMRNG9uUJtVFprrZR6BbJB+y+QnJobgfdorf+hlFqFWM8bkcIJ+wEaUcS7kcIKf0R+76chG0g/iBjp/lOJdlYDpdQlyJx7CchCEG2LHI7aoJT6ObIWnKm1/nNo3m1A5IxLkVDWBiTK4vuRNXiWmLnqbCTcfxiJZPuc1vr3kTbMAVC3CuAAUlZ6B631qqjbY1FK7YYUBzlVa/1bc6wRSYBPAwWt9V/NcbuZ+yeA92mt00qpw5HB9HQkbOkHWut31rgbU1BKvRERjk5H8pq8sHKrlHoN4vk8VGt9Q5nPmJzwao1Sagki+B2M5ALdhih0NyNev5cjeaXvN+f/HPEKdCIx+S/WWt8VQdPnjFLqbMSS+MpKCa2O+RG1QaocAWPZpLJkjl+GGEY8ZIx8yQogSqlnI4atUWSR70GqwP0G+IVRWhoQIeBIJDS8qoYepVS71jpd5ngfkqd3FOJ5zSNFs36GKITfRaICnq61TgXetwOyNQVa64Oq1e7A952CzP3vQpS8HyHewFdqrf+ulDoQyetbi0RU/A7xBv4F2dD9HGNwPBHZQ/WX1W7zthK+5xyOhYJSag3i1b8VyYu7yRxvRxwBlyHj/1ytdT6qdm4L083JjuioSwUQQCn1QqQITNWFjbkwC2/TJ4BPa60fUEq9F7E8P9tOCOYzlgLjUXr9ghjh7h+IFfrCoHXHvLYP4nm6G3h7VIreTBhPxo6IsNWstd4YeO0GpHrYiVrrMaVUB1K4ZoXW+s+RNNjhqCBGAPkqcIPW+uKAJ2pXxJO0Gr/oy8FIoZqnW8OHUupbyHz7KiRH9lTEsLUIMW6drrX+dY368lqkIMv5QY+XGePfRfZbfDviCX8eEpXwdq31t5RSz0QqBr5fa/3B0Oe+EgnN3FNrfXuV2m5/90Ek7PQSrfX/U0q9DNknrBN4bVihU0opZB25BrhOa31hNdrncDiqg1LqxcBbEY/9j5HUlCEkb/8a4BwbYZUknGEnvtSzAhg76zrM2tv0Aa31+5RSnUjexh1ImOfmSBo9C5RSeyFW6mZE2bsXEQQPQpTYfyAFCO6Pqo1zJeAN+TGwB7JVSD6u99ZsSHLbHdVDKbUIqWS7Bnih1vq/xnhzIjInXWBC0XdD8jn2RXLTTtVa55RSuyBz1Ye01peZz+xEclYGtdZ/rEEflgDfRLxir9Fa/yH0+oFISOWrkW11cub4/YiB51TESPUBJNLi+YhB6NWIUvVrpdRirfWGKvdD4RsJx7TWzzGRIrYQ1TLgHVrrL5jzVyPb6JyDrCEvLRdl4XA44o0JlT8bqT8wihjVP6O1/l2kDXPUJXWrAMaZWXibUkgeTUop9SrE/b+/1vrRKNo7W5RS+yPK3pFIwZt7ECv7h7XWX4qybbMlqCAZQewQ4IuIV/azkTbO4agCAa/TCch2LH/VWr/GvLYWySv7N+IBfC1iwLoRqbh8itb6SnPuB8zrx2qtr6+1sUEpNWTa9Sut9euNYrQ0EE51PFIMpdP090Dgo0gl3HcCX9RaTwRy7IYwe1eZfl5bw740m7buBByitR5RSh2BVAxsQubX85Fw1e0Q7+uTiOJ7U5mPdDgcCUIp1REMQ3c4Ko1TAGPCdN6mqNs1H5RSOyMW7C6t9V8CxyPL85sLJv9yMeK9PA/x0r5Oa/1IpA1zOCqAMSr9xyhpjYBnFKI24CNIWOQ5Wus/BOal8xEP07sRT/8yJMdvC1LYZZPJvb4X2Rbh21XuQ7hYjS3Y8kNgJeK9+xuy+fmLTOj22cDbgIuQcuqnIErWZVrre4zS1aG13qKUsp8xrrX+VjX7UqZvti8XIwr1OUjBr0ORffK+bI4/27zl08C/tdZX1bKdDoej8riQSUetcApghNSbt2k6i39SFD+YVP5uA+5CSvV/Smv9yWhb5XBUBiXVL38KpLXWzzDHGpFtHnLGePNT4C6t9UnmdRuOOKy1Pi7wWTcDz0Dy1GyBpD6t9UgN+tFswrHDxWouAN6DhES+Htln9dNa688rpRYjUQk9SHnyNwF/01oXjdfvIqTvv4tDmLRS6mgkZLUJUbb/D/HOZszr7wHyWuv3RtdKh8PhcCSRhqgbsJAxVvd1SqkDEAvvtxAB5WfRtmx+TCc0JUX5AzA5iqchVU13dcqfo57QWt+DhG6uMZ5AtNbFQB7fF5F98Z6plDrTvK0HqZb5pP0cpZTNUfkVcKopjES1lT+l1KBS6jr8ipx2WwdlTtmIVCrdEynYshF4oVJqR5O79xFkL8+vm+iEJhMqei5SVbMYB+XPMIG0/5tICOrvtdaZQF/f7ZQ/h8PhcMwHpwBGSMDb9Gngdchec8e7UMNo0VpfpbW+0haJcDjqjF8jxUQutgeUUl9Btm54EtlH7u/AOUqpQa31k+b5YUqpr5lqdZciG6e/RGu9Rw1zVYaRPUdfqJT6ilJqd3O8yfy9BqmovKPWehOy8fBqZIsatOx9eQ1wgVLqz8hee39AwkEvDReOiRKt9fWI4p0yYanKHNfmb2IMaw6Hw+GIFy4ENGJMYYIW4CqncDgcjlqglDoR2d7hfsRb9iCyzcBvjTfwlUhI5JVatoXoR4pRHY/k9/4FOFuHNnyvFUqp0xEv/ePA8bZAlqkEejXwgNb6FKM0XYnkBV6oZZPlIWTz9GORbRX+rbX+vyj6sTVMTuM+Wut1UbfF4XA4HPWDUwAdDodjgaFkQ/RLkKq9/6cDe/8FXv8kkuP3Eq317aZIyhKkcvED0bTcRyl1MlK1dALJQ/ylaePVSOXO07TWG5VSRyJRFtcCry9XPKb2rZ8dSqlLEI/mJTB9mL3D4XA4HHPBhYA6HA7HAsPk6v0UuBPYxRyzyl+Def17iCL1PvN6Xmv9SByUPwCz/cQxyH6jn1dKnWwqJ1+HeDXHzXm/RzZ3fx7w0tBnxFb5M7xfa/1ObYi6MQ6Hw+GoD5wC6HA4HAuTvwHfAY5WSj0HJiv2egBa618h+XJV38R9PhhF9X4kv+964OtKqbOA/yKK6zMDp38J2eT9oZo3dBtIgILqcDgcjgTiQkAdDodjgaKU2hX4FDAQ2BZCIWuDZ/cBjLSRs8BsZXEFsofqFqQozGe11l+q9Yb0DofD4XDEHecBdDgcjgWK1vpOpFLmCqXUm81hFfACJkH5azAVMc9GNknfCVgPLAKXN+dwOBwORxjnAXQ4HI4FjFJqObL/31pgL5NHl1iUUmcDbwReqbW+Oer2OBwOh8MRN5wC6HA4HAscEwr6X7cVjcPhcDgc9Y9TAB0Oh8NRN7icP4fD4XA4ZsYpgA6Hw+FwOBwOh8OxQHBFYBwOh8PhcDgcDodjgeAUQIfD4XA4HA6Hw+FYIDgF0OFwOBwOh8PhcDgWCE4BdDgcDofD4XA4HI4FglMAHQ6Hw+FwOBwOh2OB4BRAh8PhcNQNSqmvK6VuibodDofD4XDEFacAOhwOh8PhcDgcDscCwSmADofD4XA4HA6Hw7FAcAqgw+FwOOoSpdQypdRXlVL3K6XSSql7lFLvU0q1BM7ZTimllVIvVkp9QSm1RSn1iFLq3UqphtDnvUgpda/5rD8qpZ5u3ntG4BytlDo39L7LlFIb59Iuc95qpdQ15pwHlFJnKKWuVEpdGzpvd6XUL5RSY+ZxhVJqaWV+RYfD4XDUG01RN8DhcDgcjioxBGwGLgCGgZ2Ay4BFwDmhcz8C/Ag4GTgSuBT4N/BDAKXUPsD3gSuBNwC7Aj+oVruUUgq4CugDzgQywCXmnP/aD1JK7QD8FbgFeBmyrr8XuFoptZ/WWs+zjQ6Hw+GoU5wC6HA4HI66RGt9O3Chfa6U+iswAXxVKfUGrXUucPqftNZvNv//Vin1XOAFGAUQeBtwJ3CqUap+pZRqBj5cpXYdA+wJ7Ke1vtmcdxPwIAEFEHgX8ATwPNsfpdS/gLvMZ/xiru1zOBwOR33jQkAdDofDUZco4Xyl1H+UUmkgD3wHaAVWh07/Tej5f4CVgef7AleHPGpXVbFd+wJPWOUPQGv9KPD30McdBfwE8JRSTUqpJuABRFHcZz7tczgcDkd94xRAh8PhcNQr5wMfRRSkE4D9gNeb19pC546EnudC5ywFngqdE35eyXaV+75y3zmEeCfzocc6YNU82+dwOByOOsaFgDocDoejXnkRcKXW+mJ7QCm12zw/6wkk/y5I+DlAFmgJHeufR7vKfZ/9zkzg+WZEkfxymXM3ljnmcDgcjgWO8wA6HA6Ho15pRxSyIKfN87NuBp5virNYji9z3iNIgRgATCXRI+fRrpuBpUqp/QKftQJ4Rui83wNPA/6utb4l9HhwK31yOBwOxwLEeQAdDofDUa/8FjhPKXUjUjjlNGCHeX7Wh4Ebge8rpb6GKHlnm9e8wHk/AV6vlLoVuB94FdAzj3b9ErgN+KFS6u1AGin48mTo+y4DbgJ+oZT6KuL1WwEcDXxda33tPPvrcDgcjjrFeQAdDofDUa+8B/ge8D7zNwecN58P0lrfArwE8cD9FHgh8Frz8mjg1HcDV5jv/DrwT+Brc22XKTZzAlLN82vAJ4HPIcVpRgPn3QMcAKSALwLXmDZkgfvm01eHw+Fw1DfKbRHkcDgcDsfcUUq9DPgWsE5r/UANvq8X8Sp+Rmv9rmp/n8PhcDjqExcC6nA4HA7HLFBKfQ4J3xwG9gbeCfyiWsqfUuo1SLjnvUjxlwuQrSK+Wo3vczgcDsfCwCmADofD4XDMjkHgcvN3E/AD4K1V/L4MssXDGkAjuX5Haa0fquJ3OhwOh6POcSGgDofD4XA4HA6Hw7FAcEVgHA6Hw+FwOBwOh2OB4BRAh8PhcDgcDofD4VggOAXQ4XA4HA6Hw+FwOBYITgF0OBwOh8PhcDgcjgWCUwAdDofD4XA4HA6HY4HgFECHw+FwOBwOh8PhWCD8f/6K+QaEfPvyAAAAAElFTkSuQmCC"},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":45,"source":["## Unique keywords\n","\n","fig, ax = plt.subplots(figsize=(15,10))\n","sns.violinplot(x=\"language\",y=\"wl\",data=main_data_lang.loc[main_data_lang['language'].isin(low_lang),:],bw=1, ax=ax)\n","ax.axhline(3, c='red',ls='--')\n","ax.tick_params(axis='x', rotation=30)"],"outputs":[{"output_type":"display_data","data":{"text/plain":["
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"},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":46,"source":["languages = main_data_lang['language'].unique()\n","from tqdm import tqdm\n","data = []\n","for l in tqdm(languages):\n","\ttdf = main_data_lang[main_data_lang['language']==l]\n","\ttdd = dict(tdf[['counts','wl']].groupby('wl').sum().reset_index().values.astype(int))\n","\tfor w in tdd:\n","\t\tdata.extend([[l, w] for i in range(tdd[w])])"],"outputs":[{"output_type":"stream","name":"stderr","text":["100%|██████████| 53/53 [00:12<00:00, 4.14it/s]\n"]}],"metadata":{}},{"cell_type":"code","execution_count":null,"source":[],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":47,"source":["len(data)"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["23965839"]},"metadata":{},"execution_count":47}],"metadata":{}},{"cell_type":"code","execution_count":48,"source":["data[0]"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["['Italian', 3]"]},"metadata":{},"execution_count":48}],"metadata":{}},{"cell_type":"code","execution_count":49,"source":["data = pd.DataFrame(data, columns=['Languages','Word Lengths'])"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":null,"source":[],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":50,"source":["# Extractions\n","\n","fig, ax = plt.subplots(figsize=(15,10))\n","sns.violinplot(x=\"Languages\",y=\"Word Lengths\",data=data.loc[data['Languages'].isin(low_lang),:],bw=1, ax=ax)\n","ax.axhline(3, c='red',ls='--')\n","ax.tick_params(axis='x', rotation=30)"],"outputs":[{"output_type":"display_data","data":{"text/plain":["
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"},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":51,"source":["import matplotlib\n","matplotlib.rcParams.update({'font.size': 15})"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":52,"source":["# Extractions\n","\n","fig, ax = plt.subplots(figsize=(15,10))\n","sns.violinplot(x=\"Languages\",y=\"Word Lengths\",data=data.loc[data['Languages'].isin(low_lang),:],bw=1, ax=ax)\n","ax.axhline(3, c='red',ls='--')\n","ax.tick_params(axis='x', rotation=30)"],"outputs":[{"output_type":"display_data","data":{"text/plain":["
"],"image/svg+xml":"\n\n\n \n \n \n \n 2021-08-21T19:49:24.853889\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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Extractions\n","\n","\n","fig, ax = plt.subplots(figsize=(15,10))\n","sns.violinplot(x=\"Languages\",y=\"Word Lengths\",data=data.loc[data['Languages'].isin(low_lang),:],bw=1, ax=ax)\n","ax.axhline(3, c='red',ls='--')\n","ax.tick_params(axis='x', rotation=30)"],"outputs":[{"output_type":"display_data","data":{"text/plain":["
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Extractions\n","\n","fig, ax = plt.subplots(figsize=(15,10))\n","sns.violinplot(x=\"Languages\",y=\"Word Lengths\",data=data.loc[data['Languages'].isin(medium_lang),:],bw=1, ax=ax)\n","ax.axhline(3, c='red',ls='--')\n","ax.tick_params(axis='x', rotation=30)"],"outputs":[{"output_type":"display_data","data":{"text/plain":["
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"},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":55,"source":["# Extractions\n","\n","fig, ax = plt.subplots(figsize=(15,10))\n","sns.violinplot(x=\"Languages\",y=\"Word Lengths\",data=data.loc[data['Languages'].isin(high_lang),:],bw=1, ax=ax)\n","ax.axhline(3, c='red',ls='--')\n","ax.tick_params(axis='x', rotation=30)"],"outputs":[{"output_type":"display_data","data":{"text/plain":["
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"},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":null,"source":[],"outputs":[],"metadata":{}}],"nbformat":4,"nbformat_minor":2,"metadata":{"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.8.10"},"orig_nbformat":4,"kernelspec":{"name":"python3","display_name":"Python 3.8.10 64-bit ('extraction': conda)"},"interpreter":{"hash":"6c1af08f550f1e79cc5d9ab10c5079bfaf9a0f55be3d5399a261a914e77614d8"}}} \ No newline at end of file diff --git a/eda/plot2_violins.ipynb b/eda/plot2_violins.ipynb new file mode 100644 index 0000000..a347331 --- /dev/null +++ b/eda/plot2_violins.ipynb @@ -0,0 +1 @@ +{"cells":[{"cell_type":"code","execution_count":1,"source":["low = [\"mt\",\"br\",\"rm-sursilv\",\"sl\",\"sah\",\"lv\",\"cv\",\"ga-IE\",\"ka\",\"cnh\",\"ha\",\"rm-vallader\",\"vi\",\"as\",\"gn\",\"ab\",\"or\"]\n","medium = [\"eu\",\"nl\",\"pt\",\"tt\",\"cs\",\"uk\",\"et\",\"tr\",\"mn\",\"ky\",\"ar\",\"fy-NL\",\"sv-SE\",\"id\",\"el\",\"ro\",\"ia\",\"sl\",\"zh-CN\",\"dv\"]\n","high = [\"de\",\"fr\",\"ca\",'es',\"ru\",\"it\",\"po\",\"fa\",\"eo\",\"cy\",\"ta\"]\n","higher = [\"en\",\"rw\"]"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":2,"source":["import matplotlib.pyplot as plt\n","import seaborn as sns\n","import pickle\n","import pandas as pd\n","import numpy as np\n","from pathlib import Path\n","import collections\n","from collections import Counter\n","from tqdm import tqdm\n","# import plotly.express as px\n","base = Path(\"/mnt/disks/std750\")\n","data = pd.read_csv(base / \"data\" / \"csvs\" / \"new4.csv\")\n","main_data = pd.read_csv(base / \"data\" / \"csvs\" / \"new3.csv\")\n","main_data = main_data[main_data[\"counts\"] >= 5]"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":3,"source":["iso_code_to_name = {'ab':'Abkhaz',\n","'ar':'Arabic',\n","'as':'Assamese',\n","'br':'Breton',\n","'cnh':'Hakha Chin',\n","'ca':'Catalan',\n","'cs':'Czech',\n","'cv':'Chuvash',\n","'cy':'Welsh',\n","'de':'German',\n","'dv':'Divehi',\n","'el':'Greek',\n","'en':'English',\n","'es':'Spanish',\n","'eo':'Esperanto',\n","'eu':'Basque',\n","'et':'Estonian',\n","'fa':'Persian',\n","'fr':'French',\n","'fy-NL':'Frisian',\n","'ga-IE':'Irish',\n","'ia':'Interlingua',\n","'id':'Indonesian',\n","'it':'Italian',\n","'ja':'Japanese',\n","'ka':'Georgian',\n","'ky':'Kyrgyz',\n","'lv':'Latvian',\n","'mn':'Mongolian',\n","'mt':'Maltese',\n","'nl':'Dutch',\n","'or':'Oriya',\n","'pa-IN':'Punjabi',\n","'pl':'Polish',\n","'pt':'Portuguese',\n","'rm-sursilv':'Sursilvan',\n","'rm-vallader':'Vallader',\n","'ro':'Romanian',\n","'ru':'Russian',\n","'rw':'Kinyarwanda',\n","'sah':'Sakha',\n","'sl':'Slovenian',\n","'sv-SE':'Swedish',\n","'ta':'Tamil',\n","'tr':'Turkish',\n","'tt':'Tatar',\n","'uk':'Ukrainian',\n","'vi':'Vietnamese',\n","'zh-CN':'Chinese'}"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":4,"source":["languages = main_data['language'].unique()\n","main_data['wl'] = main_data['word'].str.len()\n","wordlengths_counts = dict(main_data[['counts','wl']].groupby('wl').sum().reset_index().values.tolist())\n","language_fractions = {}\n","for l in tqdm(languages):\n","language_fractions[l] = dict(main_data[main_data['language']==l].groupby('wl')['counts'].sum().reset_index().values)\n","for l in tqdm(language_fractions):\n","for j in wordlengths_counts:\n","if j not in language_fractions[l]:\n","language_fractions[l][j] = 0\n","language_fractions_df = pd.DataFrame(language_fractions)\n","language_fractions_df = language_fractions_df.rename(iso_code_to_name, axis=1)"],"outputs":[{"output_type":"stream","name":"stderr","text":["100%|██████████| 48/48 [00:01<00:00, 46.25it/s]\n","100%|██████████| 48/48 [00:00<00:00, 116575.91it/s]\n"]}],"metadata":{}},{"cell_type":"code","execution_count":5,"source":["language_fractions_df"],"outputs":[{"output_type":"execute_result","data":{"text/plain":[" Italian Maltese Polish Slovenian Georgian Sursilvan Vallader \\\n","3.0 98098.0 5383.0 93486.0 2561.0 673.0 6234.0 1731.0 \n","4.0 60035.0 7849.0 64831.0 2703.0 763.0 3866.0 922.0 \n","5.0 107270.0 4599.0 74697.0 2708.0 656.0 2504.0 573.0 \n","6.0 81082.0 3424.0 67352.0 1422.0 621.0 2131.0 477.0 \n","7.0 65570.0 2205.0 52483.0 658.0 737.0 1102.0 243.0 \n","8.0 54892.0 1810.0 43169.0 314.0 445.0 658.0 88.0 \n","9.0 34074.0 670.0 31409.0 182.0 241.0 401.0 69.0 \n","10.0 26622.0 453.0 18960.0 53.0 286.0 253.0 27.0 \n","11.0 16161.0 180.0 11082.0 19.0 209.0 143.0 10.0 \n","12.0 7548.0 123.0 6449.0 0.0 95.0 96.0 13.0 \n","13.0 4481.0 86.0 2743.0 12.0 75.0 23.0 5.0 \n","14.0 3186.0 13.0 1189.0 0.0 28.0 5.0 0.0 \n","15.0 1959.0 35.0 534.0 0.0 16.0 0.0 0.0 \n","16.0 408.0 12.0 185.0 0.0 0.0 5.0 0.0 \n","17.0 180.0 5.0 165.0 0.0 0.0 0.0 0.0 \n","18.0 103.0 0.0 99.0 0.0 0.0 0.0 0.0 \n","19.0 61.0 6.0 10.0 0.0 0.0 0.0 0.0 \n","20.0 16.0 0.0 10.0 0.0 0.0 0.0 0.0 \n","21.0 5.0 0.0 0.0 0.0 0.0 0.0 0.0 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"]},"metadata":{},"execution_count":7}],"metadata":{}},{"cell_type":"code","execution_count":8,"source":["language_fractions_df.columns"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["Index(['it', 'mt', 'pl', 'sl', 'ka', 'rm-sursilv', 'rm-vallader', 'mn', 'ro',\n"," 'es', 'eo', 'sah', 'lv', 'fr', 'eu', 'cnh', 'pa-IN', 'dv', 'ar', 'vi',\n"," 'as', 'cy', 'ab', 'or', 'cs', 'fy-NL', 'sv-SE', 'id', 'ky', 'ia', 'et',\n"," 'el', 'ga-IE', 'ja', 'nl', 'de', 'uk', 'rw', 'pt', 'ta', 'fa', 'en',\n"," 'br', 'cv', 'ca', 'tt', 'tr', 'ru'],\n"," dtype='object')"]},"metadata":{},"execution_count":8}],"metadata":{}},{"cell_type":"code","execution_count":9,"source":["language_fractions_df[low]"],"outputs":[{"output_type":"error","ename":"KeyError","evalue":"\"['ha', 'gn'] not in index\"","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlanguage_fractions_df\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mlow\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3459\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_iterator\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3460\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3461\u001b[0;31m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_listlike_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3462\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3463\u001b[0m \u001b[0;31m# take() does not accept boolean indexers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_get_listlike_indexer\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1312\u001b[0m \u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnew_indexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reindex_non_unique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1313\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1314\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_read_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1315\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1316\u001b[0m if needs_i8_conversion(ax.dtype) or isinstance(\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_validate_read_indexer\u001b[0;34m(self, key, indexer, axis)\u001b[0m\n\u001b[1;32m 1375\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1376\u001b[0m \u001b[0mnot_found\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mensure_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mmissing_mask\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnonzero\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1377\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"{not_found} not in index\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1378\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1379\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: \"['ha', 'gn'] not in index\""]}],"metadata":{}},{"cell_type":"code","execution_count":10,"source":["low = [i for i in low if i not in [\"ha\",\"gn\"]]"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":11,"source":["language_fractions_df[low]"],"outputs":[{"output_type":"execute_result","data":{"text/plain":[" mt br rm-sursilv sl sah lv cv ga-IE \\\n","3.0 5383.0 6056.0 6234.0 2561.0 1629.0 4859.0 1497.0 2245.0 \n","4.0 7849.0 5324.0 3866.0 2703.0 2972.0 4476.0 1355.0 3065.0 \n","5.0 4599.0 3525.0 2504.0 2708.0 2469.0 2884.0 2150.0 2177.0 \n","6.0 3424.0 2639.0 2131.0 1422.0 2370.0 1434.0 829.0 1784.0 \n","7.0 2205.0 1607.0 1102.0 658.0 1220.0 878.0 659.0 889.0 \n","8.0 1810.0 761.0 658.0 314.0 740.0 390.0 545.0 493.0 \n","9.0 670.0 233.0 401.0 182.0 418.0 245.0 258.0 308.0 \n","10.0 453.0 171.0 253.0 53.0 97.0 57.0 213.0 257.0 \n","11.0 180.0 27.0 143.0 19.0 86.0 25.0 80.0 57.0 \n","12.0 123.0 21.0 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34.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
\n","
"]},"metadata":{},"execution_count":11}],"metadata":{}},{"cell_type":"code","execution_count":12,"source":["language_fractions_df[low].shape"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["(31, 15)"]},"metadata":{},"execution_count":12}],"metadata":{}},{"cell_type":"code","execution_count":13,"source":["language_fractions_df[medium].shape"],"outputs":[{"output_type":"error","ename":"KeyError","evalue":"\"['zh-CN'] not in index\"","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlanguage_fractions_df\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mmedium\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3459\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_iterator\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3460\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3461\u001b[0;31m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_listlike_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3462\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3463\u001b[0m \u001b[0;31m# take() does not accept boolean indexers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_get_listlike_indexer\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1312\u001b[0m \u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnew_indexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reindex_non_unique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1313\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1314\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_read_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1315\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1316\u001b[0m if needs_i8_conversion(ax.dtype) or isinstance(\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_validate_read_indexer\u001b[0;34m(self, key, indexer, axis)\u001b[0m\n\u001b[1;32m 1375\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1376\u001b[0m \u001b[0mnot_found\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mensure_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mmissing_mask\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnonzero\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1377\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"{not_found} not in index\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1378\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1379\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: \"['zh-CN'] not in index\""]}],"metadata":{}},{"cell_type":"code","execution_count":14,"source":["medium = [i for i in medium if i is not 'zh-CN']"],"outputs":[{"output_type":"stream","name":"stderr","text":["<>:1: SyntaxWarning: \"is not\" with a literal. Did you mean \"!=\"?\n","<>:1: SyntaxWarning: \"is not\" with a literal. Did you mean \"!=\"?\n","/tmp/ipykernel_10977/2792009696.py:1: SyntaxWarning: \"is not\" with a literal. Did you mean \"!=\"?\n"," medium = [i for i in medium if i is not 'zh-CN']\n"]}],"metadata":{}},{"cell_type":"code","execution_count":15,"source":["medium = [i for i in medium if i != 'zh-CN']"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":16,"source":["language_fractions_df[medium].shape"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["(31, 19)"]},"metadata":{},"execution_count":16}],"metadata":{}},{"cell_type":"code","execution_count":17,"source":["language_fractions_df[high].shape"],"outputs":[{"output_type":"error","ename":"KeyError","evalue":"\"['po'] not in index\"","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlanguage_fractions_df\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mhigh\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3459\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_iterator\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3460\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3461\u001b[0;31m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_listlike_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3462\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3463\u001b[0m \u001b[0;31m# take() does not accept boolean indexers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_get_listlike_indexer\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1312\u001b[0m \u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnew_indexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reindex_non_unique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1313\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1314\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_read_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1315\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1316\u001b[0m if needs_i8_conversion(ax.dtype) or isinstance(\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_validate_read_indexer\u001b[0;34m(self, key, indexer, axis)\u001b[0m\n\u001b[1;32m 1375\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1376\u001b[0m \u001b[0mnot_found\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mensure_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mmissing_mask\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnonzero\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1377\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"{not_found} not in index\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1378\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1379\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: \"['po'] not in index\""]}],"metadata":{}},{"cell_type":"code","execution_count":18,"source":["language_fractions.columns"],"outputs":[{"output_type":"error","ename":"AttributeError","evalue":"'dict' object has no attribute 'columns'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlanguage_fractions\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;31mAttributeError\u001b[0m: 'dict' object has no attribute 'columns'"]}],"metadata":{}},{"cell_type":"code","execution_count":19,"source":["language_fractions_df.columns"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["Index(['it', 'mt', 'pl', 'sl', 'ka', 'rm-sursilv', 'rm-vallader', 'mn', 'ro',\n"," 'es', 'eo', 'sah', 'lv', 'fr', 'eu', 'cnh', 'pa-IN', 'dv', 'ar', 'vi',\n"," 'as', 'cy', 'ab', 'or', 'cs', 'fy-NL', 'sv-SE', 'id', 'ky', 'ia', 'et',\n"," 'el', 'ga-IE', 'ja', 'nl', 'de', 'uk', 'rw', 'pt', 'ta', 'fa', 'en',\n"," 'br', 'cv', 'ca', 'tt', 'tr', 'ru'],\n"," dtype='object')"]},"metadata":{},"execution_count":19}],"metadata":{}},{"cell_type":"code","execution_count":20,"source":["'po' in language_fractions_df.columns"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["False"]},"metadata":{},"execution_count":20}],"metadata":{}},{"cell_type":"code","execution_count":21,"source":["high = [\"de\",\"fr\",\"ca\",'es',\"ru\",\"it\",\"pl\",\"fa\",\"eo\",\"cy\",\"ta\"]"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":22,"source":["language_fractions_df[high].shape"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["(31, 11)"]},"metadata":{},"execution_count":22}],"metadata":{}},{"cell_type":"code","execution_count":23,"source":["language_fractions_df[higher].shape"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["(31, 2)"]},"metadata":{},"execution_count":23}],"metadata":{}},{"cell_type":"code","execution_count":24,"source":["language_fractions_df_T = language_fractions_df.transpose()[wl15].tranpose()"],"outputs":[{"output_type":"error","ename":"NameError","evalue":"name 'wl15' is not defined","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlanguage_fractions_df_T\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlanguage_fractions_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtranspose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mwl15\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtranpose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;31mNameError\u001b[0m: name 'wl15' is not defined"]}],"metadata":{}},{"cell_type":"code","execution_count":25,"source":["wl15 = [3,4,5,6,7,8,9,10,11,12,13,14,15]"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":26,"source":["language_fractions_df_T = language_fractions_df.transpose()[wl15].tranpose()"],"outputs":[{"output_type":"error","ename":"AttributeError","evalue":"'DataFrame' object has no attribute 'tranpose'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlanguage_fractions_df_T\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlanguage_fractions_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtranspose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mwl15\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtranpose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m 5476\u001b[0m ):\n\u001b[1;32m 5477\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5478\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mobject\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__getattribute__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 5479\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5480\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mAttributeError\u001b[0m: 'DataFrame' object has no attribute 'tranpose'"]}],"metadata":{}},{"cell_type":"code","execution_count":27,"source":["language_fractions_df.transpose()[wl15]#.tranpose()"],"outputs":[{"output_type":"execute_result","data":{"text/plain":[" 3.0 4.0 5.0 6.0 7.0 8.0 \\\n","it 98098.0 60035.0 107270.0 81082.0 65570.0 54892.0 \n","mt 5383.0 7849.0 4599.0 3424.0 2205.0 1810.0 \n","pl 93486.0 64831.0 74697.0 67352.0 52483.0 43169.0 \n","sl 2561.0 2703.0 2708.0 1422.0 658.0 314.0 \n","ka 673.0 763.0 656.0 621.0 737.0 445.0 \n","rm-sursilv 6234.0 3866.0 2504.0 2131.0 1102.0 658.0 \n","rm-vallader 1731.0 922.0 573.0 477.0 243.0 88.0 \n","mn 9198.0 7453.0 9803.0 9278.0 3461.0 2337.0 \n","ro 2124.0 4252.0 2639.0 2697.0 2081.0 1100.0 \n","es 245760.0 149234.0 193815.0 163536.0 158812.0 118989.0 \n","eo 63249.0 39706.0 61925.0 37970.0 33165.0 22098.0 \n","sah 1629.0 2972.0 2469.0 2370.0 1220.0 740.0 \n","lv 4859.0 4476.0 2884.0 1434.0 878.0 390.0 \n","fr 531946.0 505521.0 401404.0 342535.0 278515.0 240996.0 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"]},"metadata":{},"execution_count":27}],"metadata":{}},{"cell_type":"code","execution_count":28,"source":["language_fractions_df_T = language_fractions_df.transpose()[wl15]\n","language_fractions_df_T.tranpose()"],"outputs":[{"output_type":"error","ename":"AttributeError","evalue":"'DataFrame' object has no attribute 'tranpose'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mlanguage_fractions_df_T\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlanguage_fractions_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtranspose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mwl15\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mlanguage_fractions_df_T\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtranpose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m 5476\u001b[0m ):\n\u001b[1;32m 5477\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5478\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mobject\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__getattribute__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 5479\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5480\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mAttributeError\u001b[0m: 'DataFrame' object has no attribute 'tranpose'"]}],"metadata":{}},{"cell_type":"code","execution_count":29,"source":["language_fractions_df.transpose()[wl15].transpose()"],"outputs":[{"output_type":"execute_result","data":{"text/plain":[" it mt pl sl ka rm-sursilv rm-vallader \\\n","3.0 98098.0 5383.0 93486.0 2561.0 673.0 6234.0 1731.0 \n","4.0 60035.0 7849.0 64831.0 2703.0 763.0 3866.0 922.0 \n","5.0 107270.0 4599.0 74697.0 2708.0 656.0 2504.0 573.0 \n","6.0 81082.0 3424.0 67352.0 1422.0 621.0 2131.0 477.0 \n","7.0 65570.0 2205.0 52483.0 658.0 737.0 1102.0 243.0 \n","8.0 54892.0 1810.0 43169.0 314.0 445.0 658.0 88.0 \n","9.0 34074.0 670.0 31409.0 182.0 241.0 401.0 69.0 \n","10.0 26622.0 453.0 18960.0 53.0 286.0 253.0 27.0 \n","11.0 16161.0 180.0 11082.0 19.0 209.0 143.0 10.0 \n","12.0 7548.0 123.0 6449.0 0.0 95.0 96.0 13.0 \n","13.0 4481.0 86.0 2743.0 12.0 75.0 23.0 5.0 \n","14.0 3186.0 13.0 1189.0 0.0 28.0 5.0 0.0 \n","15.0 1959.0 35.0 534.0 0.0 16.0 0.0 0.0 \n","\n"," mn ro es ... pt ta fa en \\\n","3.0 9198.0 2124.0 245760.0 ... 46686.0 174.0 342686.0 1388735.0 \n","4.0 7453.0 4252.0 149234.0 ... 40565.0 758.0 374783.0 1647976.0 \n","5.0 9803.0 2639.0 193815.0 ... 39645.0 536.0 249590.0 1145729.0 \n","6.0 9278.0 2697.0 163536.0 ... 28267.0 209.0 122726.0 872236.0 \n","7.0 3461.0 2081.0 158812.0 ... 21638.0 175.0 56283.0 741493.0 \n","8.0 2337.0 1100.0 118989.0 ... 15118.0 59.0 27342.0 511727.0 \n","9.0 1143.0 764.0 88250.0 ... 7030.0 27.0 9520.0 339622.0 \n","10.0 304.0 337.0 60122.0 ... 4655.0 40.0 3450.0 204458.0 \n","11.0 193.0 80.0 36264.0 ... 2499.0 5.0 1665.0 103044.0 \n","12.0 96.0 27.0 17623.0 ... 1167.0 0.0 1144.0 56223.0 \n","13.0 19.0 34.0 11746.0 ... 636.0 0.0 392.0 25893.0 \n","14.0 12.0 0.0 7415.0 ... 269.0 0.0 273.0 9492.0 \n","15.0 5.0 0.0 3039.0 ... 102.0 0.0 116.0 2513.0 \n","\n"," br cv ca tt tr ru \n","3.0 6056.0 1497.0 558947.0 19437.0 12494.0 55168.0 \n","4.0 5324.0 1355.0 300366.0 22853.0 11760.0 44716.0 \n","5.0 3525.0 2150.0 317731.0 29017.0 16137.0 67622.0 \n","6.0 2639.0 829.0 298827.0 15707.0 11444.0 64864.0 \n","7.0 1607.0 659.0 255145.0 10250.0 9248.0 55053.0 \n","8.0 761.0 545.0 213997.0 6141.0 5971.0 49666.0 \n","9.0 233.0 258.0 171156.0 2280.0 4850.0 43873.0 \n","10.0 171.0 213.0 107368.0 1019.0 2861.0 32573.0 \n","11.0 27.0 80.0 63211.0 405.0 1187.0 29620.0 \n","12.0 21.0 26.0 38509.0 170.0 925.0 22595.0 \n","13.0 5.0 12.0 20046.0 56.0 331.0 12592.0 \n","14.0 0.0 15.0 9306.0 22.0 152.0 8209.0 \n","15.0 0.0 9.0 4319.0 16.0 55.0 4318.0 \n","\n","[13 rows x 48 columns]"],"text/html":["
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"},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":31,"source":["language_fractions_df.transpose()[wl15].transpose()[low].plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Number of Audio Clips\", xlabel='Word Length', title='Number of Audio Clips by Word Length for low resource languages', colormap='tab20')\n","plt.savefig('plots/stacked/audio_clips_by_word_length_vs_word_length_low_resource.png')\n","plt.savefig('plots/stacked/audio_clips_by_word_length_vs_word_length_low_resource.pdf')"],"outputs":[{"output_type":"display_data","data":{"text/plain":["
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"},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":32,"source":["language_fractions_df.transpose()[wl15].transpose()[medium].plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Number of Audio Clips\", xlabel='Word Length', title='Number of Audio Clips by Word Length for medium resource languages', colormap='tab20')\n","plt.savefig('plots/stacked/audio_clips_by_word_length_vs_word_length_medium_resource.png')\n","plt.savefig('plots/stacked/audio_clips_by_word_length_vs_word_length_medium_resource.pdf')"],"outputs":[{"output_type":"display_data","data":{"text/plain":["
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"},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":33,"source":["high.extend([\"en\",\"rw\"])\n","print(high)\n","language_fractions_df.transpose()[wl15].transpose()[high].plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Number of Audio Clips\", xlabel='Word Length', title='Number of Audio Clips by Word Length for high resource languages', colormap='tab20')\n","plt.savefig('plots/stacked/audio_clips_by_word_length_vs_word_length_high_resource.png')\n","plt.savefig('plots/stacked/audio_clips_by_word_length_vs_word_length_high_resource.pdf')"],"outputs":[{"output_type":"stream","name":"stdout","text":["['de', 'fr', 'ca', 'es', 'ru', 'it', 'pl', 'fa', 'eo', 'cy', 'ta', 'en', 'rw']\n"]},{"output_type":"display_data","data":{"text/plain":["
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"},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":34,"source":["high.sort()"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":35,"source":["high"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["['ca', 'cy', 'de', 'en', 'eo', 'es', 'fa', 'fr', 'it', 'pl', 'ru', 'rw', 'ta']"]},"metadata":{},"execution_count":35}],"metadata":{}},{"cell_type":"code","execution_count":36,"source":["high = [\"de\",\"en\",\"fr\",\"ca\",'rw','es',\"ru\",\"it\",\"po\",\"fa\",\"eo\",\"cy\",\"ta\"]"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":37,"source":["language_fractions_df.transpose()[wl15].transpose()[high].plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Number of Audio Clips\", xlabel='Word Length', title='Number of Audio Clips by Word Length for high resource languages', colormap='tab20')\n","plt.savefig('plots/stacked/audio_clips_by_word_length_vs_word_length_high_resource.png')\n","plt.savefig('plots/stacked/audio_clips_by_word_length_vs_word_length_high_resource.pdf')"],"outputs":[{"output_type":"error","ename":"KeyError","evalue":"\"['po'] not in index\"","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlanguage_fractions_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtranspose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mwl15\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtranspose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mhigh\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0muse_index\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'bar'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mstacked\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfigsize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mylabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"Number of Audio Clips\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mxlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Word Length'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtitle\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Number of Audio Clips by Word Length for high resource languages'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolormap\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'tab20'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msavefig\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'plots/stacked/audio_clips_by_word_length_vs_word_length_high_resource.png'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m 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\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_listlike_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3462\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3463\u001b[0m \u001b[0;31m# take() does not accept boolean indexers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_get_listlike_indexer\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1312\u001b[0m \u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnew_indexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reindex_non_unique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1313\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1314\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_read_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1315\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1316\u001b[0m if needs_i8_conversion(ax.dtype) or isinstance(\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_validate_read_indexer\u001b[0;34m(self, key, indexer, axis)\u001b[0m\n\u001b[1;32m 1375\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1376\u001b[0m \u001b[0mnot_found\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mensure_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mmissing_mask\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnonzero\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1377\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"{not_found} not in index\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1378\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1379\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mKeyError\u001b[0m: \"['po'] not in index\""]}],"metadata":{}},{"cell_type":"code","execution_count":38,"source":["high = [\"de\",\"en\",\"fr\",\"ca\",'rw','es',\"ru\",\"it\",\"pl\",\"fa\",\"eo\",\"cy\",\"ta\"]"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":39,"source":["language_fractions_df.transpose()[wl15].transpose()[high].plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel=\"Number of Audio Clips\", xlabel='Word Length', title='Number of Audio Clips by Word Length for high resource languages', colormap='tab20')\n","plt.savefig('plots/stacked/audio_clips_by_word_length_vs_word_length_high_resource.png')\n","plt.savefig('plots/stacked/audio_clips_by_word_length_vs_word_length_high_resource.pdf')"],"outputs":[{"output_type":"display_data","data":{"text/plain":["
"],"image/svg+xml":"\n\n\n \n \n \n \n 2021-08-20T10:51:25.127283\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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"},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":40,"source":["main_data"],"outputs":[{"output_type":"execute_result","data":{"text/plain":[" index word counts language wl\n","0 0 che 9624 it 3.0\n","1 1 per 8938 it 3.0\n","2 2 del 8419 it 3.0\n","3 3 non 7403 it 3.0\n","4 4 della 7323 it 5.0\n","... ... ... ... ... ...\n","354102 15901 нептунием 5 ru 9.0\n","354103 15902 поддерживается 5 ru 14.0\n","354104 15903 барнаулом 5 ru 9.0\n","354105 15904 березы 5 ru 6.0\n","354106 15905 окончена 5 ru 8.0\n","\n","[347772 rows x 5 columns]"],"text/html":["
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indexwordcountslanguagewl
00che9624it3.0
11per8938it3.0
22del8419it3.0
33non7403it3.0
44della7323it5.0
..................
35410215901нептунием5ru9.0
35410315902поддерживается5ru14.0
35410415903барнаулом5ru9.0
35410515904березы5ru6.0
35410615905окончена5ru8.0
\n","

347772 rows × 5 columns

\n","
"]},"metadata":{},"execution_count":40}],"metadata":{}},{"cell_type":"code","execution_count":41,"source":["sns.violinplot(x=\"language\",y=\"wl\",data=main_data.loc[main_data['language'].isin(higher),:])"],"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":41},{"output_type":"display_data","data":{"text/plain":["
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"},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":42,"source":["sns.violinplot(x=\"language\",y=\"wl\",data=main_data.loc[main_data['language'].isin(higher),:],bw=1)"],"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":42},{"output_type":"display_data","data":{"text/plain":["
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"},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":43,"source":["sns.violinplot(x=\"language\",y=\"wl\",data=main_data.loc[main_data['language'].isin(high),:],bw=1)"],"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":43},{"output_type":"display_data","data":{"text/plain":["
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"},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":44,"source":["sns.violinplot(x=\"language\",y=\"wl\",data=main_data.loc[main_data['language'].isin(high),:],bw=1)\n","plt.savefig('plots/violin/isocode_high_resource.pdf')\n","plt.savefig('plots/violin/isocode_high_resource.png')\n","sns.violinplot(x=\"language\",y=\"wl\",data=main_data.loc[main_data['language'].isin(low),:],bw=1)\n","plt.savefig('plots/violin/isocode_low_resource.pdf')\n","plt.savefig('plots/violin/isocode_low_resource.png')\n","sns.violinplot(x=\"language\",y=\"wl\",data=main_data.loc[main_data['language'].isin(medium),:],bw=1)\n","plt.savefig('plots/violin/isocode_medium_resource.pdf')\n","plt.savefig('plots/violin/isocode_medium_resource.png')"],"outputs":[{"output_type":"display_data","data":{"text/plain":["
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"},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":null,"source":[],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":46,"source":["iso_code_to_name"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["{'ab': 'Abkhaz',\n"," 'ar': 'Arabic',\n"," 'as': 'Assamese',\n"," 'br': 'Breton',\n"," 'cnh': 'Hakha Chin',\n"," 'ca': 'Catalan',\n"," 'cs': 'Czech',\n"," 'cv': 'Chuvash',\n"," 'cy': 'Welsh',\n"," 'de': 'German',\n"," 'dv': 'Divehi',\n"," 'el': 'Greek',\n"," 'en': 'English',\n"," 'es': 'Spanish',\n"," 'eo': 'Esperanto',\n"," 'eu': 'Basque',\n"," 'et': 'Estonian',\n"," 'fa': 'Persian',\n"," 'fr': 'French',\n"," 'fy-NL': 'Frisian',\n"," 'ga-IE': 'Irish',\n"," 'ia': 'Interlingua',\n"," 'id': 'Indonesian',\n"," 'it': 'Italian',\n"," 'ja': 'Japanese',\n"," 'ka': 'Georgian',\n"," 'ky': 'Kyrgyz',\n"," 'lv': 'Latvian',\n"," 'mn': 'Mongolian',\n"," 'mt': 'Maltese',\n"," 'nl': 'Dutch',\n"," 'or': 'Oriya',\n"," 'pa-IN': 'Punjabi',\n"," 'pl': 'Polish',\n"," 'pt': 'Portuguese',\n"," 'rm-sursilv': 'Sursilvan',\n"," 'rm-vallader': 'Vallader',\n"," 'ro': 'Romanian',\n"," 'ru': 'Russian',\n"," 'rw': 'Kinyarwanda',\n"," 'sah': 'Sakha',\n"," 'sl': 'Slovenian',\n"," 'sv-SE': 'Swedish',\n"," 'ta': 'Tamil',\n"," 'tr': 'Turkish',\n"," 'tt': 'Tatar',\n"," 'uk': 'Ukrainian',\n"," 'vi': 'Vietnamese',\n"," 'zh-CN': 'Chinese'}"]},"metadata":{},"execution_count":46}],"metadata":{}},{"cell_type":"code","execution_count":47,"source":["main_data_lang = main_data.replace({'language':iso_code_to_name})"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":48,"source":["sns.violinplot(x=\"language\",y=\"wl\",data=main_data_lang.loc[main_data_lang['language'].isin(medium),:],bw=1)\n","plt.savefig('plots/violin/isocode_medium_resource.pdf')\n","plt.savefig('plots/violin/isocode_medium_resource.png')"],"outputs":[{"output_type":"error","ename":"ValueError","evalue":"min() arg is an empty sequence","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/mnt/disks/std750/code/eda/plot2.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mviolinplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"language\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"wl\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmain_data_lang\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mmain_data_lang\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'language'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0misin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmedium\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mbw\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m 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\u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparameters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 46\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 47\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0minner_f\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 48\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/seaborn/categorical.py\u001b[0m in \u001b[0;36mviolinplot\u001b[0;34m(x, y, hue, data, order, hue_order, bw, cut, scale, scale_hue, gridsize, width, inner, split, dodge, orient, linewidth, color, palette, saturation, ax, **kwargs)\u001b[0m\n\u001b[1;32m 2395\u001b[0m ):\n\u001b[1;32m 2396\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2397\u001b[0;31m plotter = _ViolinPlotter(x, y, hue, data, order, hue_order,\n\u001b[0m\u001b[1;32m 2398\u001b[0m \u001b[0mbw\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcut\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscale\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscale_hue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgridsize\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2399\u001b[0m \u001b[0mwidth\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minner\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msplit\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdodge\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morient\u001b[0m\u001b[0;34m,\u001b[0m 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523\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mestablish_colors\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcolor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpalette\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msaturation\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 524\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mestimate_densities\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbw\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcut\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscale\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscale_hue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgridsize\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 525\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/mnt/disks/std750/miniconda3/envs/extraction/lib/python3.8/site-packages/seaborn/categorical.py\u001b[0m in \u001b[0;36mestablish_colors\u001b[0;34m(self, color, palette, saturation)\u001b[0m\n\u001b[1;32m 317\u001b[0m \u001b[0;31m# Determine the gray color to use for the lines framing the plot\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 318\u001b[0m \u001b[0mlight_vals\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mcolorsys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrgb_to_hls\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mc\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrgb_colors\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 319\u001b[0;31m \u001b[0mlum\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlight_vals\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0;36m.6\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 320\u001b[0m \u001b[0mgray\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmpl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolors\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrgb2hex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlum\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlum\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlum\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 321\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mValueError\u001b[0m: min() arg is an empty sequence"]}],"metadata":{}},{"cell_type":"code","execution_count":49,"source":["main_data_lang"],"outputs":[{"output_type":"execute_result","data":{"text/plain":[" index word counts language wl\n","0 0 che 9624 Italian 3.0\n","1 1 per 8938 Italian 3.0\n","2 2 del 8419 Italian 3.0\n","3 3 non 7403 Italian 3.0\n","4 4 della 7323 Italian 5.0\n","... ... ... ... ... ...\n","354102 15901 нептунием 5 Russian 9.0\n","354103 15902 поддерживается 5 Russian 14.0\n","354104 15903 барнаулом 5 Russian 9.0\n","354105 15904 березы 5 Russian 6.0\n","354106 15905 окончена 5 Russian 8.0\n","\n","[347772 rows x 5 columns]"],"text/html":["
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indexwordcountslanguagewl
00che9624Italian3.0
11per8938Italian3.0
22del8419Italian3.0
33non7403Italian3.0
44della7323Italian5.0
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35410215901нептунием5Russian9.0
35410315902поддерживается5Russian14.0
35410415903барнаулом5Russian9.0
35410515904березы5Russian6.0
35410615905окончена5Russian8.0
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347772 rows × 5 columns

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"]},"metadata":{},"execution_count":49}],"metadata":{}},{"cell_type":"code","execution_count":50,"source":["medium"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["['eu',\n"," 'nl',\n"," 'pt',\n"," 'tt',\n"," 'cs',\n"," 'uk',\n"," 'et',\n"," 'tr',\n"," 'mn',\n"," 'ky',\n"," 'ar',\n"," 'fy-NL',\n"," 'sv-SE',\n"," 'id',\n"," 'el',\n"," 'ro',\n"," 'ia',\n"," 'sl',\n"," 'dv']"]},"metadata":{},"execution_count":50}],"metadata":{}},{"cell_type":"code","execution_count":51,"source":["medium_lang = [iso_code_to_name[i] for i in medium]\n","medium_lang"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["['Basque',\n"," 'Dutch',\n"," 'Portuguese',\n"," 'Tatar',\n"," 'Czech',\n"," 'Ukrainian',\n"," 'Estonian',\n"," 'Turkish',\n"," 'Mongolian',\n"," 'Kyrgyz',\n"," 'Arabic',\n"," 'Frisian',\n"," 'Swedish',\n"," 'Indonesian',\n"," 'Greek',\n"," 'Romanian',\n"," 'Interlingua',\n"," 'Slovenian',\n"," 'Divehi']"]},"metadata":{},"execution_count":51}],"metadata":{}},{"cell_type":"code","execution_count":52,"source":["high_lang = [iso_code_to_name[i] for i in high]\n","high_lang"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["['German',\n"," 'English',\n"," 'French',\n"," 'Catalan',\n"," 'Kinyarwanda',\n"," 'Spanish',\n"," 'Russian',\n"," 'Italian',\n"," 'Polish',\n"," 'Persian',\n"," 'Esperanto',\n"," 'Welsh',\n"," 'Tamil']"]},"metadata":{},"execution_count":52}],"metadata":{}},{"cell_type":"code","execution_count":53,"source":["low_lang = [iso_code_to_name[i] for i in low]\n","low_lang"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["['Maltese',\n"," 'Breton',\n"," 'Sursilvan',\n"," 'Slovenian',\n"," 'Sakha',\n"," 'Latvian',\n"," 'Chuvash',\n"," 'Irish',\n"," 'Georgian',\n"," 'Hakha Chin',\n"," 'Vallader',\n"," 'Vietnamese',\n"," 'Assamese',\n"," 'Abkhaz',\n"," 'Oriya']"]},"metadata":{},"execution_count":53}],"metadata":{}},{"cell_type":"code","execution_count":54,"source":["sns.violinplot(x=\"language\",y=\"wl\",data=main_data_lang.loc[main_data_lang['language'].isin(medium_lang),:],bw=1)\n","plt.savefig('plots/violin/medium_resource.pdf')\n","plt.savefig('plots/violin/medium_resource.png')"],"outputs":[{"output_type":"display_data","data":{"text/plain":["
"],"image/svg+xml":"\n\n\n \n \n \n \n 2021-08-20T11:03:14.936928\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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"},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":55,"source":["fig, ax = plt.subplots(figsize=(15,10))\n","sns.violinplot(x=\"language\",y=\"wl\",data=main_data_lang.loc[main_data_lang['language'].isin(medium_lang),:],bw=1, ax=ax)\n","plt.savefig('plots/violin/medium_resource.pdf')\n","plt.savefig('plots/violin/medium_resource.png')"],"outputs":[{"output_type":"display_data","data":{"text/plain":["
"],"image/svg+xml":"\n\n\n \n \n \n \n 2021-08-20T11:05:21.489644\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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KLX66XdjBuPoY50dmOONBBCPC+E+IoQ4kdCiHeFEH8j/PqiEOKLQoj74X8X4moD0bT44CAiomn983/+z/GLv/iLaTfjxuOzOV58f+N1k6Zf9gH8Ld/3fxLAfwLgF4UQPwngvwfwZd/3Pwbgy+GfiYiIiLTw2muvYXV1Ne1m3HgMHfHgrKSbKbZQ5/v+tu/7b4W/rwN4D8CzAP4igF8Pv+3XAXwqrjZQ+nS5IevSTiIioqfFcDhMuwlEc7sx0y/HCSFeAvAzAL4N4Lbv+9vhX+0AuJ1EGyhZuo0C8cFBRESkFg64xovvb7xu0vRLAIAQIg/gfwPwy77vH4//nR9cTROvKCHELwgh3hBCvLG/vx93M+kpxxsbUbK++MUv4p133km7GUSkMA64xku3AXi6XCbOFxdCWAgC3Wd83//fwy/vCiHu+r6/LYS4C2Bv0s/6vv+rAH4VAD75yU+yx60Z3UKSbu0l0t0/+Sf/BADw+c9/PuWWEJGq+Gwmml6cu18KAL8G4D3f939l7K9+D8BfDX//VwH8blxtoPTpMgrEBwcREZFaWKkjnSXdt4yzUvefAvgrAH4ghHg7/Nr/AOB/BvDbQoi/BmAVwP8lxjYQTYUPDiIiIrVwwDUefF+TkXRhI7ZQ5/v+1wFc9L/mL8T17xLNgzc4IiIitXDANV66zKai6SSy+yWR6vjgICIiUotuz2YOENO4G3mkAZHq5IODN2QiIiI18JkcL76/8bpxRxrQ002XG4ZsJ6ciEBERqUG3Sp1u2Oe5WRjqKBa63Sj44CAiIlKLbs9mXQay6WZiqCOCfg8OIiKiad2/fx9f/OIX027GzBiS4sX3N1436UgDeorpdqPgmjoiIrqp/t7f+3s4OjrCz/3cz6XdlJlwwDVeus2q0g3X1NGNossNQz44dGkvERHRtI6OjtJuwlwGg0HaTZgJB4YpTQx1ROBoIBERkWr4bI4XQ2i8eKQB3Si63DD44CAiIlKLbs9mXfo8EmcnxYvTL+lG0O1GodsUD4pfvV7ndUFElCKGOqLpMdQRgaGOnvSX//Jfxq/+6q+m3QwioqcWn83xYgi9WRjqNOH7Pt577z1tbnC63Sh0Gw2k+A0GA3z2s59NuxlERE8tPpvjpcusqnfffRe/+Iu/iEajkXZTZsI1dTTRG2+8gV/+5V/GV77ylbSbMhNdbhh8cBAREalFt2ezbgPauvi3//bf4sGDB3j48GHaTZkJ19TRROvr6wCABw8epNySm0lWQHlDJiIiUoMus5N0pUufp9/vp90ELTDUEeH0waFLZZGIiOimY6UuXuzzxIvTL4lSwEodERGRWnSr1LEPQeM4/ZIoBaejgbwhExERpWW8OqdbqNMNQ+jNwlCnCV0/eLq0W87XHgz0mupBRER0k4wHOYa6eHH65c3CUKcZ3T6AurRXPjgGAy7GJSIiSovOoU6XgWxd+ma645o6ohTISh13WCKiSYbDoTYdNiKdMdQlR5f26tLO87imjm4UXT6Io0odQx0RTfB3/+7fxT/9p/807WYQ3XgMdfGT7WTF7mZhqKNY6XLDGFXqOP2SiCZ466238MUvfjHtZhDdeOMzZnSbPaNLqKNkcPolXYo3jHjI0cB+X69RQSIiopuElbrk6NZe3XD6JU2kS8VLV6PdLzUbFSQiIrpJxoMcK3Xx0qW97ANPh6GOCNwohYgoTRsbG3jw4EHazSAFjIe68TPrdKBLSNKNru9r0u3OJPqvESmq1+sBYKgjIkrD3/7bfxuHh4f4/Oc/n3ZTKGXjz2H5bNaFbuFDt/bqhtMv6UbR5YYhHyI9rqkjIkrc4eFh2k0gRYyHOq6pi5dulVC6HEOdJnS7UUi6zIPm9EsiIqL0cfdLovkw1GlGl5CkGznFw/d97UYGiYiIbgqdQ51ulS+G0HjxSAO6UXS5YfR63bHf6zWHn4iI6KbQOdTp0ueRdGuvbrimji6l2wdQl8pit3Ma6rrd7iXfSURERHFhqEuObu2lyzHUaUKXcHSeLu3uslJHGuODmYhuCvkMFsLQ7nms2/RL3dqrG06/pIl07bTp0u7xB4duDxEiXT5nRERXkc9gy3K1ex7rdi/Wrb264fRLupQulS/d9LpdZMzg95x+Sbrhg5mIbgo55dKyXE6/jJlu7aXLMdQRIZh+6VjB73UbGSQiIropZJCzLRfdrl7PY912z2aoixenX9KldPsA6tLebrcH15K/Z6WO9KLL54yI6Cqn0y89bQZZ5T1Yt3uxLmvqdJ2lxlBHl9Ltwtalvb1eH44d/L7T6aTbGKIZ6fJgJiK6ihxYtW3vzHFDOmCoo3FJV24Z6jSj2w1Dh1DX7/cxHA7h2UFbdRkZJCIiumnkM9i2s9pMv5R9HV2mX8q+pC6hTre+r5T0+8tQpxkdQtI4HT6IsjLnslJHmtLhc0ZENI1RqLM89DUbZNUlJMm+pC7t1RVDHd0oOoRQOdVDhjquqSPdMNQR0U0RhDoBK+Ogy1AXK93aqxuGOrqUbp03HdorK3Ny+mW73U6zOaQAHa7bcbq1l+im4Gcvet1uF5lMBqZpabccQreQxOs3Xgx1dCkdKl/jdLhhjEKdE/yZlTrS4bodp1t7iW4K3T57OrS32+0iY9owMzZ6va4WbdZtjZqkW3t1w1BHl9Lh5jZOhxAqK3NZ5+yf6eml2+dMt/YS3RS6dYp1aG9QqbORMYNzhnSq1umyUYqkw/Wgs6Svh8xlfymEWLzs733fP4y2OXQVHUKSbsY3ShHgRimkHz6YidLBz170er0eTNOCadqjP9u2nXKrLqfb7peSbu3VjVKhDsCbAMaHgMcThQ/glchblJDhcIj79+/jx37sx7QISrqOxOvQblmZs0wBKyNYqSPt6PA5I7qJdAt1OtwrOp1OGOqs0Z9zuVzKrbqcfFt1ux50a68O/fVxSk2/9H3/Zd/3XwHwTQD/CMB/GX5Nfl1bX/3qV/FLv/RL+O53v5t2U240HT6AMsTZGcCyGOpIvwedDh01optIt3uFDu3tdrswTQuZjDX6s/qCe7BulS/d2qvbs07Vw8d/DcBdAP9vIcRDIcS/F0L8jRjbFbsHDx4AAFZXV1Nuyc2mwwew1WoBAKwMYLNSR9Djuh2nW3uJbgp+9qLX6XTQaNbw4cNvj/6sC91Ckg4hX0fyvqDa9EsAgO/7XxFC/AcAfxrAfw7gvwPwJwH88xjbFivdbsSy4qVru1U2mn6ZASzTH4U8Il3odl8guil06xTr0N52u4N+v4N6owKAoS5OurVXF/JzpmSoE0J8GUAOwOsAvgbgT/u+vxdnw5KiQ+gYp1t7dcBQR+fpFpJ06KgR3US6ffZ0aG+n04EQBgxhjP6si36/n3YTZsJQFw95HSR9PUw7/fIdAF0E1bmfAvAnhRBebK1KkG6dN93o8P42m00YAsgYwbq6ZrOZdpMoZTpct+N0ay/RTaFDSBqnw72i2w1CndybT6dQp1tI0u361YW8DpSs1Pm+/38DACFEAcD/FcD/CuAOACe2lsVM14qXDjfkcTq8z61WC7ZlQAgBKwO0Wgx1TzvdPmd8MNO48evX930t7sO60u2zp0PoaLc7EEKEwU6XjVICOry/43Rrry7SqtRNO/3yrwP4PwD4UwAeA/jXCKZhaku3TpvEh3P0glAXvK+2BRzWGeqedrrdH3RrL8VrPGgMh0OYpplia2423TrFOtwrOp02DGHDMILnshabl4VvqzbTL3Vrr2aUDnUAXAC/AuBN3/dv1BXAkBQvHR4gzWYTdsYHIILpl1xT99TT4bodp1u1gOI1fj0MBgOGuhjp9tnT4d7W6XTgOu6oUqdFqAu7krqFJN3aq4tBPxjsUTLU+b7/T+JuCE1HhxvyOB1C82moAxwLaLXanLL0lNPtc6Zbx5LiNV494rURL93eX9Uri4PBAP1+H8IVeoW6kG4hSfXrQVe9fg+AuufUUcpkJ5NBI3qNRgNOOLxhWwK+72v1EKHo6dZR0y2EUrzGOxK6dTJ1o9u9QvX2ymevEAZDXQJ0a68u+r0g1PXC/yaFoY5ipUNns9k4gW0Fv5fhrtFopNcgSp0O1+041TtqlKzxUMeR+Hjp9v6qfq8YD3UAYBimFqFOvq9Jd+Ln5Q/TORz7adHvqX2kwcyEEP9aCLEnhPjh2Nf+RyHEphDi7fDXfxXXvz8t3TpvutGhsthoNEahTv6Xxxo83XS7L6jeUaNkjXckOBIfL93eX9XvFWcqdRCwLFf5UDcYDEbvqy7Xw2AYhDldQqhueoqfUzePfwPg1Qlf/2e+738i/PWHMf77U9EhdAD6tFNHjWYTbhjm5H9PTk7SaxClTvWOz3m6hVCK13hHgiPx8dLtXqF6e1vhRmXCCLqnluUoH+rGP2+6hKS0dmd8WvR6wTEcSR/HEVuo833/PwA4jOv1o6JbZ4jtjVa/30en04UTHmkg/8vpl0831a/b81TvqJ2n2/urW3u5pi5e49eDbqFZ9fbKUGcIGerc0ddUpWNlXIZPXdqrm144/fJpWFP314UQ74TTMxdS+PcB6Fv50qXdspOpentleHPkmjr77NdV9e677+Jv/a2/hd/4jd9Iuyk3kuodn/MY6uKl2/urYydTJzqvWVT9Wj6dfhn0HTKm+pW68Y67Lgely90ZdWmvbhrNoA95Yyp1F/hXAD4C4BMAtgH804u+UQjxC0KIN4QQb+zv70feEN06FZIu7ZYPOtVDnZxm6YZhztFk+uWbb76JH/7wh3jttdRnMN9IunzOJHYs46Xb+8tKXbx0DnWqt3c0/VJW6jLqV+rGO+66Tb/Upb26kZ+zXvcGV+p839/1fX/g+/4QwP8C4M9c8r2/6vv+J33f/+TKykpsbVI9dJynS3tlp031zrEMbzLMyXCneqiTDxHekOOh+nV7nm4hie2N1/h9QfVOvI50roSqfi3LTcrE2PRL1WfOjIc6HSpf4xu7sA8RvfF7brfTSfTfTjTUCSHujv3xvwbww4u+Nym6dN50aaekS0fitFIXhGXLFMiYQvlQ1wlvFN0Ob8hx0OX6lVTvqJ3H+1m8dNy4QSes1MVHhjpDmAAAy3bRbOpTqdMh1I3fE3S7P+jw7Bh/TzsJXw+ZuF5YCPFbAP4zAMtCiA0A/08A/5kQ4hMAfACPAfy3cf3709Kl8qUbXTqZ9XodwOmul0AQ8OTXVSVDXbvTge/7vI4jpsv1K6neUTtPhwfzON3eX507bTrQuVKn+rV8fvdL2/I4/TJiurV3nA7Pjs5Yda53U0Kd7/s/P+HLvxbXvzcvHS4QHckHh+rv7yjU2adfc231K3Vy4bjv++j1erBt+4qfoFnoFup0a6/qHcvzdOu4j3fUdGu7DnQOdaq3t9VqwTQtCISzZzTY/VKGJCHEmQ69qnTc2EXS4VknrwFDiMQrdWnsfqkUXSocsp2qhyRJl41SJoY6a6h8pW58NzDVdwbTkQ4PjnFsb7zGO8I6tJ2VunjpPL1V9QGVRqMBx/ZGf7YtD91uR+kwKjvxnp3XItSNt7HbYaiLmnx/TWGg0+0k2m9/6kOdLiFJUj0kSSrfgMfV63XYmWAdneTaQK1WTa9RUxgfuWSoi57qHZ/zdGuvDg/mcbrtJslQFy+dD3dXvb3NZhO2nR39Wf5errVTkax2Ze08OhqEpPHqnA4hdJwOzw75/prhZj9JVkOf+lCnS0jSjU7TL13n7MfAs4H68XFKLZpOq3X6gFP5YacrHR4c43Rrr+r3hfN068Qz1MVL5/dX9UGJZrMJy3JHf7bDqp3Kz7nTSl1Oi5Ak22gbNit1MZAD7aYRbPaT5DXx1Ic63ToXurRXPjhUD821Wg2effY9dW3guH6i9HvdaDRgh5u7qL7eQEc6PDjGjQcNHdquQzAaN95eHTrxOq+Z0YFuoU6nSnOj0YBljVXqwt+rfKyB7LRnHT2mX8p7Qs7Ko9NVv73jdHi+jUJdWKlLcjbVUx/qVA8d5+nSXvngUL3zdnz8ZKjLOgK9Xk/pm3Oz2YTnnf6eoqX6dXuebmu+dGjjON02HtFti3Xd6BzqVG9vo9EYVecAPSp1stOec4pK9xsk2ca8pUcIHafDs0O+pxmDoY6uoHL1aJx8iKj+AKnVqvDObRzpOfLvask3aEqtVgu5cDBT5YedrnTouI/TaSQe0OPBPE63jTHObISgWajT4RmnWyVUp8PoT04asK0nQ50OlbqcW0S321H+/jZqryYbu4xT/b0FTkNchtMvk6fDA2ScLpU6+RBRvYN5XDsehThJhrxjRdfV9ft9dDpd5MNQp/LDTleqX7fn6XYYsg5tHMdKXXJ06LTpVqnTaVCi2WzCcXKjP9t28HuVn3PtdhtCCHhhW1X/zMnQUbQKie/OeF06PDvkkhgZ6pJcIvPUhzpdQpJu5IND5QdIv99Ho9mC5wh8+e0Bvvx2cLPwnOCaqFarKbbuYvLhlgufe6qfqacjHTqW4xjq4qVbJ77T6QBCAJqcmzVOh2tDt8ObdQl1w+EQrdbZ3S+d8PcqP+fa7TYcy4WdcUd/VplsX8Euwvd95UPoOB2ezTLEmYKhLnG6jFDIdurS3tNQp+7NQk6vzDrAXtXHXtUf/Xn871UjH26s1MVHh2rMON0OQ9bhwTxOt1DX7XZhWBYMy9KqwwbocW3oPP1S5ftDs9mE7/tw7PFKnfobpbRaLdiZ01Cn+uZlo0qdXQSgfnvH6TDoc1qpM878OQmZxP4lRelSqZMPOl3aOwp1XXU7QOOhbpwuoc6xAdcxlD8oXUc6PDjG6bamTrf3V7dQ1263ITKZ0e91osO1odv0Vl1CnQxu4xulmGYGmYytfKXOzjiwM0HnQfV17jJkyFCn0z1Ch/tDs9mEgBjtfpnk9fDUhzpdKl+6nPsmyQddV+Htck9D3dmg7FiAaQhlp1/KEGc7gOOAoS4GKnd8JtHtHDUd2jhOt058p9MBGOpiI6e0CtvR4nrQpbJ4OmCZO/N1x8kqXalrNpuwMy4cjaZfWqYFLzwuQvX2jtPh2dxsNmEYAgZDXfJ0qXzp8KAbJx8iKp+BcnR0BADIume/LoRA1jWUD3WOBdiWz1AXAx0eHON0m355/lw9w1B7JYBua6ja7fYo1HFNXfTk9WA4WS3eX12u39Gzzcme+bpj55R+zrVaLdimCzs8NF31Sl2z2YSbceGaelQWx+lwf2i1WjBgwAjzRZLvr9pP0gToUvnSrVInH3QqT7+UoS3nPPl3WcdXNtTJXTldB7BtH8fHak4TPe/tt99WdkfR83QIRuN0C3W6VRZ1q9S12234ZgZ+JqPFKPz4c02H63dUqXOyWlwP2lXqnPyZr9t2Xunpl81GE47lwrHUP1MPCEKHm/HgZrzRn3Whw/2h0WjADAOdZ9kMdUnSpVInL2QdLmjgtJzfUfgBUq1WYRoCjvXk32VtH0dHh8k3agoyGNl2EOxqtWq6DZrCYDDA3/k7fwf/4l/8i7SbMpXxTpAOAyk6hzod2jveEdahMtNqteBnTPiZjBYdNt12b+10OhBmBn7G1uJ60GVQ4jTUnZ9+qXalrtlswrGy2oSkZrMJ13ThmnpUFsfp8LxoNBqjqZee5SQ6dfipD3W60C3UdTtBqFP5AXJ0dISsKyYG+6wLZUNdrVaD6xgwjCDUHR+r+7CT5EY/r7/+esotmY4uGwtIuozES7pt7DLecdehE99qtwHLAjJW8HvF6Rbyg41owve3pf77q0uoG02/fGJNXQ71usKVumYTruVpU6lrNptwDRdeRo/2jtNh0OekfjLaJCWbYaijCeSFrMMDDwDaYajr9wfKfgir1erEqZcAkHOBarWmZJWmVqvBCdvt2EC73dGio6kT3XY71C2E6jz9UofPWrPZDEKdZWnRYdMt5LfbbRiWA5GxtQjN49esyqHu5OQEhmHCss4udHednNLTLxvNBhzLGx1poPKmLgDQOGkgm8nCy6h/XITkD4O+mA7P40bjZLROPGs6iV67T32oU7HTPom8kHV44AFAp336EFF1TcfhYQVZZ/L//zlXoN8fKHmzq1arcJ2g8uWGzz5Vj184T7fP2/nfq0q39o534nVobzDdzhj9XnWtVgvIWBBWBk3Fp4IBZ68BHUJ+sBGNDWHZaLfVf39lkMvYam/sUq/X4br5J2bPOE4erVZTyf5Pt9tFv9+HY3kwDAOO5SnZbxjXaDTgZTytKnXyzGMdnhcnJyejNXVZy0l06vBTH+p0WVMnH3Q6PPAAoNPpwgzfWlVD3dHhIXLu5L+TXz88VG8K5tHRIdywUif/q+qmLpIunzNJl+lKkm6hTsdOvBGOoKjcKZba7TaEbQGWjY6i999x4511Ha5fGepgOVpMv5TXbMbJKX39Hh8fP7GeDggqdQCUrNbJNrnh8QCu7SnZznHNRhNeJgtDGHAzrvIhFDjddE/1+0O320W31xtNv8xZLhoJTh1+6kOdbpUD1S9oIHhP2502CmEwUjHUDYdDVGu1J44zkGSok8ceqKRaPYIXts9TuJ3jdPmcSTqHJB3aO96J1yE0B514E8JSfzfJwWCAbqcDWDZgW+h2OsoHZ91CXavVgm/ZEBkbnY7a1wMwFurcPNoKh7p6vf7EejrgdDdMFXdPPg11Xvhftc/U830fJ80TZMMQmrWyyodQAOhq0geW76UxFurqnH6ZHF0qCDqFul6vh8FgiGJ4qLeKnaDj42MMBkPk3cn//+fCr6tWqev3+6jXG0+EOtUrdZIunzdd1qBI3W4XsjSuyz1CUnFK1Xntdhu+lYGwLCXvZ+NGU6nCSh2g/poZXc5RkxrNFoTlQNgOet2u8qFZ3s8sN690pe6qUKfiDpiyE++F7XYzWSXbKbVaLQyHQ2TD9XTZjNrrFSVd+sBy4MEM19TlbRfNVjOxe8RTH+p0qSDockEDp9v5nnSD91bF+dqysnXR9Mu8ohUwGd7cc6GuUqmk06AbSsvpl44JQI/pgbqFularBd/Uo1InA5yw7WAKJtS8B4/TrdLcbDUBywHCDT1U38K+0+nAMExkbA9thaeL1mrHcNzCE1+X0y9VDEujSp0MdXYOJwrv1CnbK0OdZ3pKvq/n9cLnsOrPY/lemiJ4HufDe0RS7/FTH+p0IR90ql/QwGkHoh8OTKj4wJMVuLw3uXLkWEDGFMpV6mR7ssFMD2QygG0byoXPi+gyiKLbFvbdbhewg9u5Dp1i/TrxLcDOaHHu26gqZ9naVOq0ux4azaBSZwWLmlUPze12G6blwLAcpQcl6vU63HMHjwOA6wRBT+Xpl7JS59m5RKfbzUqGi5yVH/1X5RAqdXQLdaNKXdBZS+rafepDnS7TweSF3FP8ggZOH3AZ4+yfVSLD0UWVOiEEcq6hbKjzxtqd9dSbJqq78QeHyp0gqd1pA44+uzNq14lvNoFMBn7GVPJ+Nm4U4Gw7OPMEeoU61TttANBqNSHsYPoloOYzblyr1YJpuTAzzui4IdV0u110Ou2Joc5x1V1TJzvx46FO5emMp6EuN/qvDpW6Tjd4rqn+fJM7kcuNUhjqaKJR6VnxCxoYC3VB9VnJDsWoUndBqAOAnDtUblqjbI+s1AGA56jXTt0F51AFv1f9IQKEbQynX+rQKdZtemur1QrPfcugoXgHXnYohWOPQofKnUxArzV1/X4fvW4XwvYgbD3OJZOVOtNy0Wm3lZwxIYOFO2H6pW15MAxT8VAXBM+sk0e73VL2Op4U6o7r6r2v4/r9PobD4Bgn1QdZz6+pKzDU0SSyY9ntqd8Bkg+4jCHO/FkllUoFjm3Aylxcqc27QOVgP8FWXe2iSt2BYu28iC6V8VarBVPh3VvP63Q6gG1AmIYWIXS8w6NDe5vNJoSdAWxLm1AH2xlV6lQPdTpNdz5ds+gCYYdNxWfcuGCQyoVpORgMBkoGDlnhcN0nK3VCCLhuXtlQ59oeTCMYVJPhTtXql3wP5fTLvJVHt9tV+jl3ZuMyxe8P1WoVTsaCgaCvI0NdUpvZPfWhTsURq0m6o/nE6t2Mz5MPONMADKHmA+/w8PDSKh0QTM08PFRrrdrBwQGyngFj7JPrecGGLipfy7JtKrdxXKvdQnguq9IPO6nd6QCmgMjoEerG26hiB3PccDgMznoLK3XNpnr3s3Gnoc4Ogh3UD3XjlTrVr9/T99cdVepUf3+bzSaMTFCpA9S8p8mwIdfPnee5BSVD3fHxMbL2aRDNKnz8AnAangujUKfuekVp/HpVeaMfIHh/5ZRL4DTUyfc9bk99qNOlciBHJ1R/4AGnDzhTAJ5tKBnqKpUKcs7lASPvCTSaTaXe80qlAs872+5cFuj3B4ndNK5Dl89bu92CpVGo67TbQEYAlh6hTqfpl61WKxiMsC0I20KrqfZGKaMKgW0Hv4RQtmog6XSEyOn01ixE2GFTPdQ1ms3R9EtAzTWAo1A3YfolADi2uqHOGwuiWTv4vaqfuePjY7gZF5YZVPELttohFDh9BpvCUP55XK1WUbKzoz/bpgXPclipS4oulQN5YKjqDzxg7PBFA8haanYoKgf7yHuXf4/8e5U2Idnf30P2XKiT6+u4ri46rVZbq0pdp9MBLAPICG3aKyw9jmA4nW5nAbaFTrut9Llk9XodhutCGAaEEDAcR8l78LgzI/GKX7+noc6DcPQIdc1GExk7C9NWN9TJQUnvglDnunlUq+oNXNZqtYmVOlXPjg0qSaftLVhFAOq2Fzi9J5ScwqgvrKqjoyMUx0IdABSdLEMdnSU7Pv3BQPlzner1OoQABADP8pXrUPi+j8Ojo6tDnYJnwB0cHCB3rt258P6xv6/uujpdBk+kdqsNwwZMSyhZaR43GAzQ7/UhMvqEum63C+Hao9+r7HQ3SSuofEHNKeVSvV6HcJzRn4XjKj0KD4wFOcNUPuTL55mwPQgzA8OylXvGnddsNoPdL8PpByqGOnmNOhPW1AFBBU/F67hWrY2qcwCQVfj4BSAIb0WrNPpzwQ5CncozfeT1WrILyh8pUzuqouicC3WWl9ixUwx1GhgMBuj2eshm9BjZPj4+hhnOsvMsH3XFbm71eh29Xh959/KpgPIMu4ODgySadaV2u42Tk8YoxEmyUqdyqJN0mH7Z7/fR6/VgWkGoU/0hMrofWAJDTUJdsFtnsL2o6u0dVWEcGyJss8qh7vj4GMOxUDd0bGU7mFJwDQuYnqf8820U6tzgRmy4WaVDne/7QaizPWQU3tjl+PgYtu3BNDIT/951C6jXj0e7IKqidlxDbqy6mAtDnaohqXpURcE6bW/BVru9wOlZxwtuEf1BX9mBwOFwiKNaFSUnd+brJSeHo4RmfD31oU61G8Qk8iFXdIMOheqdzHq9jnDjS+RsgeNjtW4WsvKm2/RLGS6z59rtuYAQ6oTPSXTaKEWOChp28EvFUe1xo/uBZQCWUL69QBDkhhkDIqN+ZWY81MlKncrT7aq1GuCM7QLluqgpHuqC3RktwLKVf77JgCzkaLyTVTo093o9DAZ9ZMZCnYr3iGq1Cs8rXvj3rlvAcDhU6rPXbrfR6XSQc07bnTEtuLanbEiqVquj6hwAZDNZmIaZWCVpHvJ6LYfvs4rXLxAOqA2HKD8R6rKs1CVF9amMwGmnrRhuT636Q69Wq8EMr6wg1Kn1wJPhR1biLuJaQMYUyky/lJW485U6wwByWYOVuoiMdm+1AcPylRzVHnc21BlotNR84I1rtVsQlglhmdpU6oRzepi3ypWZaq0GuKeVOriu0utlgOAaFhqFOsNyIMygouQ7WaVD8+iIIduDGa71USkYSbVa7cKdLwHAc9WbJig/V7lz7c45RSU/c8PhENVaFSXndPqlEAIlp6RFqFtyywDUrDQDGL2Hkyp19ZOTRCqMT32oU3nBuyQfcmVNKnXHtepo+mXOBpqttlLlcll5K1xRqRNCoOAZyoc6AMh6Qy1CnQ6VujOhzvZx0lCvAzTufKhTdRRzXKvVBjImRCajfKgbBTjHDoId1A11vu/juFaDcE9vbsIN1tSp/NlrNpuAZcPPWGiq/nw7Pobhna77Ek4uCNKKkgEu4+SQCauLKnaKrwp1cldMlQaJZXDLu6UzX1c11MlKUsk+296irXaok9fwklcGoG6lTvYtz1fqyuHmOUm8x09tqJMVOp0qdeWwQ6HqBS1Vq6eVurwdpDuVbsSyUpe74py64HuGykxr3NvbAzA51OWzwO7uTsItuplGu7eG0y9PFO3AS6P7gW0AtoG24p1iILynWRnAMtUfpArvXYM3fwiEm7uodD8b12q10O/1AM/D4PXXMXj9dcD10O/1lH6fg+vBBixbg+dbFXCzaH/zd9H+5u9CeHkcKxzqTit1WRimBcPMKFmpq1Zrl06/lLtiKlmpc0v4w7d+E3/41m+O/qzaGbfAaagoOiX81r3P4LfufQYAULJKOKyoscxkkkajAUMYWAinX6p4/QKnS3sWzm32s+AGIS+JpTwMdRqEOnlTXvDUn37Z7XbRardHlbp8OAtIpRtxpVKB5xjImFdPBcx7wfEHKtjf30fWM2CaT/5dNhv871J1jahOa+pkFcZ0gmpdXdEHiPRkqGsr/z63223AMuFnDKXvZ0AY4AwBVKrKT7+UnUzhuvArFfiVCoQXjF6pPBLfaDbhZywIy1ayijQumN6ax6CyhUFlC4aXQ7PRQK/XS7tpE53ez7IQQsBycsp1in3fR71+DNeZvPMlcFqpU6kCJj9TebeI7aNVbB+tjv5cVfDzJkNH2Sljvb6G9fra6M8qh7qTkxPkbA85hacPA2Pvr3uuUheGvCRmfTHUaRDqRvOJPefMn1Ukb7ijSp0TBCeVOhSVSuXKqZdS3gUqh4dKdJL39vaQy05uRz4XHECu0vs8ToZNHdbUyQeG6QS/Go2GEv//X+R0y30DwjLg+77yQSkIdRn4GRNNxdcAHh8fAyK4oQnThGFbSg1SjRt9/sd3U/KC36vUGT6v0WgAtgPYNhoNta+Hw6MjiPHpl2GHTdVrQoY6K2xnRsFQ12q10Ov14F5aqQv+TqUq+WmoOzudMe+WUD+pK9e/HE0PtMtnvl5yyqjVa8q1Vzo5OUHO8pDLqH0uZKVSQdZ2YZvWma8vMNTFT6dQJzttS9kg1Kl6QQOnNzkZ6gpKhroD5NzpOul5T6DT6SoRpHd3dy4OdRqcVacL2WnIOMGvfq+v9A6N46EOjnH2awrqdrsY9PvB4eO2iYYCn63LVKtVjLbzBSA8V9kOvLzPCu90jrb8vUr34PNOGg0I24GwXbSa6g6ijNYseqdrv0Q2+L2q768MdZlwnY/pqHcEw1UHjwNAJmPDshylPntHR0fwnBwy5zrxBbcM3/eVaitwGipKTvnM18tO0F5Vdvo+7/j4GNmMh7yVHf1ZRZVKBYsTruGCHewwylAXIzlVQqdQtxyGOpU7bKehLugEFZyzX1dB5eBgdLD4VeSxBmmvq/N9H/v7+xPX0wFALqz27+7uJteoOajaWRtXr9dhmAIiA5jhdaLqQwQYD3VBSDrzNQWNqoh2BrAyaCpemTmqVoMtZkNDx1ausyaN7rPek5U6VTtsANAcVeocDAYDZQdR6vU6hoPB2Uqdl9wmCPMYVerCUJdx8qjV1LqfnYa6iyt1AOB5RaU+e4eHh09U6YDTyp1qn7lKpYKcnYNt2me+XnYWAKjXXum4doyClYNtWrCMjHKDEtL+/j4Wz22SAgCGEFj08on0I5/6UKfSrowXkZW5gm3ByZhKV+rkTSETXllOBnAyQpkH3mAwwFG1duUZdZI89iDtm12tVkO320P+yfsFAIy+LjdTUY0MczpMvzw+PkbGFRBCwHROv6aqer0OkTEgTDGq1Kl8jzgNoRnAzihRBb9MrVY7E+rgOjhU5H523uHhYXBopXv2nDoIde7B5w2HQzQbDQjHhXDUHriUzwEjexo+5O9VfX+Pj49hOVkIIxjwsdy8ckcwyKnB7hWhznUKSk0jPqwcIu9MCHVe8DVVds6W9vf3RwFunPyaqjN9jo+PkbeCNaF5J6dUsB93sL+PhQuqzQt2PpH+2VMf6lRd3DyuXq/DszIwDYGsbSndYZMPPTn9UgiBomukHoqkarUK3/evPKNOkhW9tG/OsgJ3UaizLcCxDWUrdapu4DJJrVYbVejCKfzKPkSAIMAJNzgzC445+pqqzoe6dqulbAV3MBgEu5+aY49Kzwmqdwo6PDyE4XkQYyFUGAbMbFaZe/B5zWYz+P/fdgA7+OCpOhIv38OzlbqgE5f2M+Iix8fHo/V0QBDq6oqFulGlzrt4+iUQhL5qVZ17caVyiEK4zf64QniemmqfucpBBQv2k6Fu0Q2+puo1XKvVULSDzk/Ryik5yNrtdnFUrWLRnbzZz6JXwEECofmpDXWyQqdDpa5eryNnB3O285ap5AUtVSoV5F0D45Gp4Pg4UGQHSXmTnXX6Zdo3u1Gou2D6JQDkcr6yoU4n1eoRDCcIoRlXfq2aXoOucHJyMqrQyf+q2ikGzoY6YWcwHA6VPauuVqsFgWM8JHku6rWakgMVlUol2Ar3HN/Lpn4Pu4i8VoXrQThqhzr5Hhq5scObMxZMV93QXKvVkDkT6gro9bpKfeamnn7pFpQZYPN9H0dHh6MANy4ffk21z9z+3j4W3MUnvp63CrAMS8lKXbvdRqfbQcEOruGClVN6Z9GlCzb7WXQL2D84iP258fSGunDOvi6VurwVjMDnNAh1Refs10pusI5NBfKDN22lzs4IOHb6B5BfVakDgHzWx+7udkItmo1ORxocHR2NKnTyvyqHuuP6MYbheZBwg/uEqp1i4LSKKOxMUGKGuu0dTakbn36ZdTEcDpW8D+8fHMD3JoS6rId9Re7B541CneOODk1X9XqQzwGRO9txE9li6uuuL1Kt1ZAZmxJmeeqd91ar1ZDJWMhknEu/z3WLpwMtKavX6+j2uihmn6x8ZcwMcm4x9X7DuG63i+pxFUvu0hN/J4TAgreoZKiTz95Rpc7J40jBMwDle7d4QbV5ySug3+/H/rl7akOdXIit6oLscbVqFXk7mF5VsC0cK9zB3N/fQ/lcFazkCRxUKkrciE9D3fQ/k3dF6qOwOzs7cGwDtn3x9+RzwM7OrhLv83kqtukiR9Uqwk22ggPITXXXIwFh5ywMc7ANQKi9BnA0NdSxgkW3UHe66OhzPzb9UmTV3Xjk4OAAIvfkyI/I5pQNdaNOjusFv6BW4BhXqVRgOB5E5uyN2M8WlX1/q9UarLEKmKXgeW+1Wg2eW7xyzbWnUJVRfv4L3pOVLwAoegtKhTo56DCpUgcAi/Yi9vfUC3WnZ+sF13DJLuAoXEajErlebunCUFc8831xeWpD3Wj6pQ6hrlZDIQx1eTuj7AMPCBaKls4FprIL9Hp9JTqalUoFAkDu8gHBM3LOMPVK4+7uLvK5y29i+RzQ6XSVvD50Oaeu1Wqh2+mOKnRCCFhe+qH+MrXj41GoE0LA8CwlPmsXGVVhHCv4BQ1C3blKHaDe1Kputxus/5u0RW4ui0a9ruQgprxWhZsdVepUvX739/dh5MtPfN3IlXFwoNb1AMgjGKqwvfFKXdC5VC3UuZccZyB5YdtVeMbJkFT0nqzUAUDBW1CqejsKHRMqdQCw6C4puXxDDqgWw4Ppy04B3V5Xuc2UTkPd5OmXMuwx1MVEhrpOW72H3HlBqAs6P0XHQr3RwGAwSLlVT+p0Ojiun6Dsnu24l8Opjirc4A4PD5H1DBjG9OEi7wVn26Vpe3vzylBXCJdN7OzsJNCi2chQp9ro2nmyo54Z6xebWV/ZSp3v+0FHXlbqAMBVe4p2vV4Pzn2zTAhX7emXo+CmQaVO3l9F7smF+vJrKtyDz5MddOF6EBkLwrKUChzj9vb2geyTux2KXAm16pFyyzkajQb6/T4s77TNtoKhrlqtXrnzJYBR8FOh7fLecFGoK3oLqCgU9GVguyjULXlLODw6VO4alu/zYrjLqKzYqXb/3dvbQ9HJwjl3ZqG0zEpdvGT5vtNVO9R1Oh202m0U3dNQ5/u+kp022WEoe5NDnQrb7Qfnysz2MzkXODw6Si2Q+L6P3d39S9fTAafr7VQOdapX6uSDwhoLdRnPx74iG/2cd3JyguFgCOGdhrqhI3BUVTOEAuE5gK4dXAuO+qHOcJ2z120Y6lSr1I3Ww0y6UYRfU3HNzNHREYRpBrtfAjC8rBKVmEn2D/Yhck+GOiMfHN6s2jUxup+NV+rCUKrSQFW1Wrv04HFJbqSiwvUhP0uFS0Jd7bimzGZ8e3t7EBBYvCjUucvwfV+5gZ9KpQLTMJG3g4fyQngNqPZZ293dvbBKBwA5y4WbsRnq4tIOp6GoMDf7MvLGWwo7P/K/Kt2QJXmxLmTPdtwXFAp1lcoBcs5s4SzvCfR6/dTK/YeHwehZYfJOuSMFDUKd6pU6+UAbr9RlculXai8iOzf+egPDr4efL89Udst9IJhaNxwMMfjG+0A4WKVCJ22Sg4MDIHd2PrnImDA8V7nOj7y/XlapUzXUGV5uFJx9N6vk863T6eC4VoORf7ITL6dkqvb+yvfRzpXx4Tc+gw+/8RmYGRsZ21PqPQ6mX15dqVMp1B0cHCDnFpExMxP/vpgN1q6pEj52d3dR9srIGJPbu+wtj75PJZVKBWW3CEMEcWUhrNSpdv/d3dkdVeMmEUJgOVuK/f19KkNdv99Hv98HoP5GKXKkreQEC7NLrn3m6yoZhbpzlbq8A1imUCLUHR0eIjdHpQ5I7z2XIa1wRaXOsgDPNZQOdaqTDwpr7L22ckCz0VJyAGjUMWv0gUp4L/NMJbd8lqq1KuD78Ct1IGNCZNSdLrq3vw8/O2FXpZynXKdiFCgmbJQiv6Za6ADCa3h8x04vhwMFn2/yvRMT1tSJMOip1iEehTqvhJODNZwcrAEAnGxJmbDR6XTQ6bSnqtTJ6ZcqhLr9/X2UspM3HQGAUriBiir3id3dXSw5yxf+/bKrZqjb29sbTb0EgAU3+L1K97LhcIi9/T2seE9W8ceteEXsxtw/eypDneycZS0bnW5XyfVpkgwS5XBEW+VQt7OzAyGA8rk+kBACC9n0D8YeDoeo1mrahbrt7eCYgqsqdQCQz/mj71eJDHWGofYt5+DgAKYtYNqnAxMy4Kn0EJFGa0vM0/aKbAaNk8Zo4Eo11WotWFMHubGLrUQnbZL9/X2I3JOhzs962FGs87O7uwsjm4XIPDkSLzIZGNls6vfgSQ4qFfjeaRAVXg6HFfWeb/K9MwoXV+pUe39lcHNy5TNfz2TLyvQh5Gd/mo1SLMuFaaqxWdz+/gGKF+x8CZxW6lR5buxs74yC2yQL7iKEEMoNCu/v7WPROa2A2aaFgpNTokggHR0F62lXspdXm5e9Iit1cWg2mwCAcrjTlooj8NJoO9cwzC2E4U6VUbZxQXnfhDlhE5IFdxj7CMVVjo+PMRgMkXNnW9clvz+t6SoypF21pg4ACnkfW1sbMbdodnLgRPXpl3t7e7DzZ6+P8MxTpR4i0uk5auNrvsyzf6eYarV6pr2+q+bGGJ1OB/Xj44klcpHPKtNZk/b29iZX6aRcDrsKXsOHh4cQ2bFQl83hpH6s3IYNl4U6kbFgZovK3SMODw9hZiyY9tkdUe1sGQeKBOdpDx4HgkEgzysqEuquqNQpFOr6/T4ODg6w5F0c6jJGBovuolIDE8PhEPv7+1g6t25xyS0r9VmTQXj5qkpdtoRGsxnrGvKnMtTJELcQhjrVtkYdFywSNVAI19LZpomcbSkZ6nZ2drDgTe60L2QFdnbSrSDJjmN21kpdePxBmqEunzNgmld/byEH7O9XlOsQqVwNH7ezu4NM7uxUUUvhUHd4eAgIcTbUeUGlRsVQNxgM0Dg5OXNEgO/aylQNxo2m2006IiCfRbPRGA0QqmBrZwd+/uJyvp/PY1uxUfher4fjWg0ie9pukQsqNqpdEzs7OxCGATFh90sAQGFBuff34OAATm7hiQ2qnFwZh4qcHSunXk9TqQMA1ymkPl270Wig2WyglJ286QgAOJYHz1Zj8Gdvbw9Df4hb3q1Lv2/ZXcH2ljozfQ4PD9Ef9LFyLtStuAvY3VEnfMogvHLRvSEkp2fGWQ19KkOdDHGL4ZQPlR7M5x0cHKDs2TDGbsqLnq3EjeK8ne0tLE3o/wDAUk7guH6S6nstO7mznFEHAK4d9EHTqiZsbW0in5tuTVqhEFTDVAsg2lTqdndHIU6yckFuUu09BcLdGXMWMN5ny2VGf6eaqjw0dnwarmfjUMEAOhqxnlipC76myjUxHA6xv7cHUbi4YywKBezv7Sm1vlUGNxnkgt+refzCzs4OzPwCxAVTyEVhEVtbWwm36nIHBxVY2Scri3ZuAb1eV4ldZ2eZfgkEoS7tSp3sf10W6gCglFtWoq8mQ8TKFaFuxbul1PRLeQ9ePhfqlr0F7O7uKnMvG72/V0y/lKGPoS5io1DnZs/8WUV7u7tYCqdeSouujT2FSuRAcO7f4VEVi9nJUxuXwq+nud5rFOpmnH4phEDONVKrfGxubqI4xXo6AKPvU61zIUOdykcaNBoNNBpN2Ofuy8IQsPNqbkBTqVTgZ8/dxsPplyqGutFnyByfLuqgVqsp84CWZIdCFCaMVIVfU2Wq0uHhIQb9PpC/pGOcL2DQ7yt1XZxWQ8dDXeHM36lia3sbfuHi6XZGYRGVgwOl1rLu7+/Dzj0Z6pycOlMDZdVtmo1SgCD81WrpVuqmDXVFb1GJgR/Z71rJrlz6fSveCg6PDpVZkiT7MbfOvc+3skvo9XvKVPN3dnZQdvOwLzijTpKhLs5+8FMd6paz6lfq9vZ2seSdDXVLWfUqdTs7O/B9H0u5y0Ndmh3j0fTLGSt18mfSqNQ1Gg0cH9dRnO55N/o+1UKdatNBJ5HXpj3hvc7kh9jaVus9BYJzs/zcuXm52Qwg1Ax1o4fwWLVD5BwMB4PUp1Sdt7OzE7Rzwu6XIqzeqRL0ZSdBXHKjkH+nSpuBsWMY8qcjKfL3qj3jtra2YRQv7sQbxaVgFzwFOvFAUL2tVA7g5J8Mok64W6cK1dBarQYhBGx7ikXjkKFOjUpd+YpQV84uBQfWp2x7exuWYaHsTD5TT1rJBpU8Ve4R29vbEBBPVOpWwg1qVNkUbnt7GyuXHGcgZS0HedtjpS5qMtSthNM8Tk5O0mzOhQaDAQ4qFSyfSyHLnoP6SbpTGc+TH64LQ1349TTDRrVahSGC6ZSz8mwf1RQOdJbv1zQ7XwKA6wCWJZQLdTqsqZPv2flKnfzatoKhLjhH7exuh8IQMHK2Eh2280ZB0xx79GTts3+niJ2dHZiF3OTpdp4LkTGV6fzIdojCJeckhX+nSpuB8WMCxip1tgPDcZWpggJAvV5H46R+ZagD1Olo1mo19Pv9yaEuF7RVheB8fHwM18lPvTOy6+bRaJyk+kzZ29uDIYwLDx6XSrllnJzU0Wq1EmrZZFtbW1jOLo/OeruIXHOnSv9ha2sLS9kyrHNn693OLY/+XgU729u4lS1P9b0r2RJDXdTkPPJb4eJsFeaVT7K/v4/BYIjlczt7LId77Kv00JMPsuULpl9mbYGsbaT6wKvVasi6xlxTAINKXfKhbnNzEwCmrtQJEUzB3NhQawdMHSp1o1A34b22i0CteqzUQEqr1UKz0YTIPTnlw8+ZSnTYzhsFt7GNXUR4f1Mt1G1vb2OYn7xIWAgBUcgrE5BG7bhkoxTk84BQa8BnZ2cHppeFsM6OtIm8WjtJyueWUbp490AZ6lR5f+X7J6dajrOzJQjDVOI9Dg4en3LUEsGaOiDdftve3h6K2YUrg6is5KX9Pm9tbmHFvXw9HQDcyt4Ovl+Ra3hzYxN3JuzYueyWYQpj1D9KU6/Xw8HBwZWbpEi3vFKsm9HEFuqEEP9aCLEnhPjh2NcWhRBfFELcD/97+TBHTOr1OizTxGJ44KmqlbrR4stzO3ushJU7VUYEgeAm4FoG8pdMbVzOpXuzqNVq8OaYegkEoS6NefyjUDf9Mw/Fgo+NjfWYWjQfGepU3ihla2sLlmecOaNOksfkqPKwA8ZG2fNPnkvm50zs7qkz6CPt7+/DyDrB6IMU3t9Uqyxubm9DXPLB8ws5bCpyPWxtbcEsFCAu2SJXmCbMfF6p58bu7i6Qf7K66OeL2FKonfJzbxQvDnUiW4Rh2Up0NIHTIOEWnqwuCsOAm19IPWwAQX/McWYIdWEATHO69u7uLkrZi68FqaRAqPP94Oza22Fgu0zOyiFnq3GP8H0fm5ubo6rcONMwcSu3pMTgdbCzqD91qFvJlrC3txtbpTnOSt2/AfDqua/99wC+7Pv+xwB8Ofxz4ur1OnK2g4xhwrWs1OdnX0R+sG6dq9TdCit1KnzwpK2tLSznLt8IYykLbG2m9yGs1WrwrPlChecIdDpddLvdiFt1uc3NTeRzBiacJ3yhYh7Y3d1TqjrW6XTSbsKVNjY2YJcmb9Zhh/drVTpswFhHoTBhcXbBwv7+vnIhOpguem5kJQx5KlUWT05O0KjXLx1NEcUctre3lXiPN7e2MLxk50tpWCgoE0SBIDgj/2RnSBRK2N3dVeK9BU5nPlw2/VIIAaO4pMw9Qs7kcQqTw4edX1Zitk+tdgzHmXIqCgDXUSDU7eyiPEWoK4eBJM33+fDwEO1Oe1SFu8ot75YS13C1WkWj2cDd3OTNXe5kV7Cxnn6ok8WX21NOv7yVLaM/GMQ2MyW2UOf7/n8AcH5rmr8I4NfD3/86gE/F9e9fplaroWgHHYuC4yo7/XJrawumYWDp3Jq6vG0hZ1tKVQ02N9YvPM5AWskL7O8fJB6MpONadWKl7stvD7BXBfaqwG99tY8vv/3kCIrcqybpB8n6+hqK+dl2BSwVT0fnVJHW/+ezWN9Ym7ieDgCcsN+pwsigNAp1Eyp1Ip9Br9tTbsBqZ3cXfu7sIJUwDZg5V6lQd7rxyCUVhGIB3U5HiR3YNjc3gUvW00miWFSiwwYE62z3d3chiuUn/s4oltHtdJQ5azGohJYhMpfvbofiMtY31Hh/9/b2kLFdZOzJD2Y3v4QdBc76kmvqxn399d/AQWUVB5VV/O4f/H18/fXfGP2dPPogrVA3GAxQOayglLt8kxQAKLhlGClPc5X9xKuOM5BuebexqcA1vL4ezDZ65oJQ90xuBZtbm6mv1z/dWXTK6Ze5eHfATHpN3W3f9+X/kh0A0w0dRKxWrSFvBb37ouWkdv7YVTY3N3Er58IQAp955xE+886j0d/dyrnKPJz7/T529/awcsEmKdJyTmDo+6mtQzmu1ydukrJX9dHpAZ0esL4f/Pk8GQaTfJD4vo/19XUUr+6rnSHX36kUQEaVOkVPNDg5OUGtegynHPx563UfW6+fXgdGRsApGEq9p8HujOKJjVIAjKp3qqz5AoLr+eBgH8i7T/zdMOcoMRVMkvdWUbqkUhf+XdqDaycnJzip1yFKU9woikU0Tk6UGMgM1owPRqGu+/ofofv6HwHA6Gtpv7fS+voGcEHFa5xRWsHu7o4Sxxrs7OzALaxcOHvGLa7g6Ogw9QG3er3+xJq6SmUV3V4T3V4TWzvvoVJZHf2dnKqZ1jVcqVQwHA6v3PkSAAzDQCmb7rEG8jM0zfRLALiVvYWDg/QG36XV1eD/87u5IIz+5nu/h9987/dGf/9M7hb6/X7qg9fb29uwzAzKU64LlRuq3JRQN+IH8younFshhPgFIcQbQog3oh7BrR4doeQGHYui7aCqyGjgeZsb67gTTlVaqzWwVjs9T+9uzsXGuhrrpnZ3d4MNXfKX99hl6EsjjPq+j5OTBrw5dr4E0qnUHR4eotVqozT9zBQAQaUOOB3pUsHo3BtFplOdJ98rGeraleDXOKs4xOrq40TbdZnd3V0YBRvCmPC5K1qj71FFvV5Hu9WGKDx5RAAKLrYVCqCj8H7Z9Mvwg5n24NoogBavHimW36NCWDoNzsHSer+yB78SHnFQXDjzPWnyfR8bmxswypef8QUEG6kMBwMlBlO2d3YvnHoJBNMyfd9PNXB0u110u53Z1tQ5wdEHaVXq5D21PGGt1yQlbynV+/Dm5iZMYWLJna69t7O3MfSHqV/Dq6ur8CwHi25wz1o73sba8WkQerZwe/R9adre3sZKtgRjyg34Ft0CTBHfpoFJh7pdIcRdAAj/e+HdxPf9X/V9/5O+739yZeXqm+ksjqpVFO0w1DmuMlM8xg0GA2xtbeN2fkIHCMCdvIv9gwMlDomUD94rK3Vh6Euj2tFsNjEcDuFO2ARjGvLnkhwdlEFjmgH4cbYF5LKGkqFO0UyHtbU1AKehbhJnAVjf2FDmkOztnW0M8xfcwhWs1I06NoUnK3XIezg4OEh9Ko0UTLfLQVy2mDWfhTDSr96ehqMppl+G36NCWJJtMIpP7pcmCsHujCq0s1arodlowChNEerC4Jf2NeH7PnbDSt1FvGLwd2neI+TzVAa1aViWByGM1Da4kyF42lC3kFvG7m66lbrl7ApM4+JNlMbdzt4Z/VyaVldX8Uzu9oWV5mfCCl7qoW5rG7e86aZeAoBpGFjOxXesQdKh7vcA/NXw938VwO8m/O+j1Wqh1W6h7AZhqex6qNZqynQmpL29PXR7PTxzQai7G452q/DQkw+wlSsqdTlbIOcYqdws5ANgnjPqxn9OnnGYBBnKyjOGOgAo5oep3+zGyXN6hsNh6tM6JlldXYWREROPM5DcMtDtdJWZJri1tTWqyJ0nbAOGl0l9asq407PUJh3m7WEY4+LxWa2tr2N4xZazwjAgSoXUO/Cj++kUa+rk96TdYQOC+5thO0D2yQ69MAwYpXLq7y1weh82p6jUmaVbZ34mLUdHR+h02nBLF6+jcgvB36V5j5DPZWfKg8eBYEMa182lFupGlbopNkoBgrPqDg8PU9u4bHNjE7e86Vc6yQ1V0uxb+r6Pxw8f4bn8xe12Mw5Wsot4/Phxcg07R+5dMO0ZddItr4StzXjuwXEeafBbAF4H8HEhxIYQ4q8B+J8B/JwQ4j6A/yL8c6LkovbTUJfFcDhUbkMB2SF/ZtJUpbGvq9Bx39zcRNY2kJsiMK3k0hnFvG6oc8K+c9KVOssSyE6+BC5VKgWbrKiye9z4+W4qnfUmra6uwilj8lTGkBMWFNJ8iEjNZhP14zpE6eIL2i9a2FLowPRR57E4YeOGYnCRqxA2fN/HxsbGaHrlpd9bymMt5Q785uZmcJzBFFvkikwGZqGgxGDg+vo6RGnxwpF4v7iAx2EFPU2jnS/LV280IdwsTC+fehiVnzXvkkqdnSvBzFiphjr5PJ1l+iUQ7ICZ1pq63d1d5L0irMx0nYlybhm+P0zlyJbRsQBTrqcDgLyVR85O9xo+OjrC8Ukdz+XvXPp9z+Vu49HDR5d+T5yOj4/Rarem3iRFWsmWsB3TsznO3S9/3vf9u77vW77vP+f7/q/5vl/xff8v+L7/Md/3/wvf9xPfNkx+sBbCM+oWwnCnygixJKeDPVOYvHPV7ZwHQwglQt3G+vqVxxlIKzlgYz35B/Xo4XHF5mUXsTPBnhRJjg6urq6iXDx7pNe0ykWg1Worc12PVziTrHZO6+Gjh3DKlwdgNwx1KnzmTgPSxRe0X8wo0XmXtre3YXgOhD1ht84w1KlQWTw6OkKr2ZyqRC7KRWxvb6e6Mcb6xgaG01TpQsNCEesKVMAer64BpYuPqjUWlrC9tZX6piPr6+sQGQsiX57q+0VpJfVKnRwc8UoXd+aFMOAVb6lRqZth+iUA2HY2tVC3t7c31Rl1kqzopbGurlKpoNPtzBTqAOC2dzu2StI0Hj0KgtrzhctD3fOFu9jY3Eht9s/psWMzhjqvhPrJSSx9odQ2SkmLDHWLbhCWFr3gZqLSdtpAUA1YyLrITegAAYBlGrhT8JToYG5srOPWlPfklbzA4VE18WqN/Pdca741dUIIOLaRaLtXVx+jVJiv0ib7oypcH8DZCqcKO++Nq9frOKwcwl28/PtMR8DJG6MHTppGYa10yShF0ULloKLMdNfNrU34k9bTAUDehTDSmZp9nhxQE+WrK3WiXMBwMEitY3xaVZy+UyFKJWxsbKRaxW80Gjg6rEAsXHKYd3kJw8Eg9YGJtbU1mKVlCDFdd0mUb2F1Lf1QJ4Rx6UYpAOAUb2Ejxc77/KEuh5OTdAYHd7Z3ptr5UkrzrDr52ZHr5KZ1K5vusQYffvghAOCFwjOXft8LxbsYDtNbaiKXFMxaqZMhMI51dU9dqJPrYRbDSt1S+F/VQt2jRw/x7IStv8c9m/fw6OHDhFo0WbvdxkHl8Mr1dNKtfDo7YMowZs9ZqQMAxxKJhbqTkxMcHVVRnu1eMSJ/TpVQd1w/hhXOVlEt1MnplFeFOgCwF4b48OGH8TZoCqeh7uIpQKJsK3Ve4frGBlCaPPMgWJ+WTb0DD5yuhxILU1S/wtGTtCoztVotqCrOEOpQKqHVbKa65EDel4yFizvHRhj40r6Hra6tA5esTTvPKK/gpH6c6vu7tbUFt7AEw7x8Sq5Xuo3tra3UNn+SlQr7grP0LuLY2VTW1A2HQ+wf7KN8wdlpk5SyixAQqazFPg11s1fq9iv7p0cRJezhw4dY9MrIX3FdPF+4C+A0BCZt1jPqpFu58pmfj9JTGeoKjgs3PES06LiwTFOprb/7/T7W1tbx/KS1J2OeL2axs7ub6hqlaTdJkeT3Jd0Jku/RvNMvAcDO+Im917IjM2+ocx3AddXZAbNWqyIX9pFVC3UPw4GRaUKduxRc82lXvzY3N2HkLAjrklt4WMVTISi1220cHlQgLgh1AOAXXCWmBa6trcGwLUyzmFWEoW4tpbVf8v47a6UOSHczDzmQIhYv7hyL8iIgRKprWLvdLvb3dqdaTyfJ703rmgCAjY1NuJdMvZTc0m30et1U1nsBp5U6255t4bhtZ1OZxl+r1dDr9abeJAUAMqaFQracSh9za2sLGSODRXf6yiJwGgLTGhB8cP8BXszfvfL7bmeX4Gac1ELdzs4Oim4O7pTrK6UVj5W6yOzs7GDZOy31CyGwnM0rFeo2NjbQ7/fxfOnyKQny79OcDiY7FbemDHXLOQGBFCt1V+8lcCErjVA3x86XQLAOr1QY4vHj9KcK+r6P41odhXLw52q1mmZznvDw4UNYroHMFIPF7iIwHAxTD8vrG+vwS1dczOXgQZP2pg3AeGXxkntaOYftra3UdyJeXVsFysWp1ggL24KRz6XWgT89zmD2UJdm2H/06BEMy4bIX3yDExkLZmkh9eeb7/swF6YPdWY56BCndY+Q5+pdtp5Okt+T1rXQaDRgZRyYxmwPZtvOotlMPtSdnlE3W0gqZZdSqdRtbW3hVvYWjCmnDktpHmvQbrexubmJF4uXT70EAEMYeL5wFw8ePEigZU/a2dnBijd7Jy1nu8haDkNdFHa2t3Erd3anpVvZHLa31JiiBJxWDl64olL3Qjjq/TDFKZgbGxsQwJUHj0uWKbCYMxPvaLbbbQgBmNe44i3zdGv+uK2uriKTEcjPttTgjHIpeJ20d8BsNpvo9XrIlwDDgHLnQj748AGcxeFUnXgvfJanNTIIBJ22tbV1+OXLRweFY8LIWkqEutMpjRdf0KKcQ6/XS30q/OPHq/BnGE3xywU8SqmatLGxAWGaQH6G3QPzeQgz+XvwuIcPHwKLy1d+5vyFZXyY4vNNhvVZKnWiUIbIWKmFumq1inarBa909TqqbPg9aV0LjUYDtjP79s6OnUWv10t8xsSsZ9RJ5ewy9lI4q25zfbbjDKRb2eB6TyPsP3z4EEN/iBeLz071/S8VnsHDDx+mMhi4u7OD5TlCHQAsZ+M5q+6pCnWDwQC7e3u4lTu7AP5WtoCtra3UO7/SgwcPYJnG6Cy6iyx5DnK2lWoHc2NjAws5E7Y5/QYky7kh1hMe2W6327AzxlQd94tYGaDdTibUPX78eO6dL6VyEWg0mqNjPNIi/33HA9yskXp7xvX7fTx+/BjTzk6xi4BpiVQ/c/IwZHFFqAOAYTmDtRR2mz1v1Gm8ZPqlKAeBL81pa/V6HbVqdbr1dCFRLmJ9fT2VdUkbGxsQxSKEMf2jXBgGRLGYWkfe9318+PDhpVMvJWPxFnZ3dlLbMXd9fR0QYqqDxyUhDJjlldSn5Hrlq6ev2bkFmJaTbqibcT0dcDpdM+mlJ7OeUSeVc8vY399P9B4xHA6xtbM9V6jLWjkUnHSOPrl//z4A4KVpQ13xWbQ77cTbOhgMsL+/P5pKOasVt4i9GGYIPlWhbmdnB4PBAHfOhbo7+QJa7ZYy08I+fPAAzxWzyFzxoBZC4MViFg8e3E+oZU/a2FjHSna2G9WtvIHNzc1EQ3Sn04F1jamXQFCp67Tb0TToCo8fP0K5eL33Z6EkX+vx9Rt0DfJYBTcLOF465/VcZH19Hf1eH+6Uz2hhCDiLwP0UP3OjCsDCFPP4yzbW1tI/r3B1dRVGKQeRMS/+poX0Q52c9iwWZpjOuFhEr9tNZQr/2vo6/OLsI8V+sYi1lDryu7u7aDWbMBavrn4ZS0GYSusetra2hkxhESIz42Ls0i2spnQdy/tDdorpl0IIZEt3Ugt1rVYLVubyDeEmsax0Qt3+/j5c24M7YxAtZZfQH/QTnaVyeHiIbrczqrrNasW9lcoMtvv376Po5LHoTncPfqn07OjnknR4eIj+YDBxk5TffPePsHq8h9XjPfyDb/47/Oa7f/TE9yxnS9jd3Y382fxUhTqZ5O/ki/iNd76L33jnu6M/A2qsPfF9H/fv38eLV6ynk14s5/Do0WP0er2YW/Yk3/exsb4x9SYp0kpOoN3pJHqGWrvdhjVDNXGSoFIXf6g7Pj5GtVq7dJOUb78V/LqMKjtgyul0Gw+CYLe3p876VTkX35thiYS75OPDDz9Mbce4UeiZItSJBRuNk0aqO/EBwOPVVfjlyztCwrVhZF01Qt3iDEEpDIBJB49BeJTCLOvpJFEqYSel9Yuyym0sTxPqgmCS1pqZ1bV1YIapl5JZvoWD/f1EnhfnbWxswMxYcArT3dTc8h2srafT92k2m6OANgs7pVC3t7c3c5UOOJ2umeTUcrke7taMO19Kt7K306nUfXAfLxWemXpW1TO5W7BNK/FQJwfxJk2/XK3todXvotXv4v3DDazWnpx6u+IV0e50cHx8HGm7nqpQd3qgdwmrtSOs1oJRk2fy6e8GJm1vb6PRbOLl8nRrJF4u59Hv91PpuB8dHaHVbmM5N1tYkpuqJBmiu90uLisSTCNjIJHwLK/Ty0Ld4VHw6zKeG+yAmXaokze/5gng5YD9/YPUK0fSgwcPYFoCzgz9Ym8ZaLfaqe0Mtra2Fux6mZ+i9BwGvzSvgX6/j82NDaB89UCVX86mujHG48ePISwLyE0/Ei+naib9Hu/t7WHQ788d6gaDQSrVxQcPHgBCTDX9Erk8DC+bSqgbDAbY3NyYaT2dZCzcGp0hmLT19XV45btTn6uXLd/F/t5uKtvXN5vNUUCbhRVOv0xqjbu0u7uL4gxn1Eml8GeS/LydHow9Z6jzbuGgcpDousV2u421tTW8XHp+6p8xDRMvFp/BBx98EGPLniTXVy5n51tTtxT+XNQb6Dx1oa7oeijYzpmvL2VzcDKZ1Du/AEYX5ktTdIDGvy/pCxo4rXzeKsx2Ga2kcFZdr9eDaVwvSJgm0O31I2rRxeR1OMMMsAuVi0Ospjz9cmdnB4YBQADZfPD/hSrr6j744AO4i8G0yml54UBt0iODUrA7oz3dSGYY6tLdXn0Dg8EAYnGKgarFPB6vrqZWBX28ugosTrfzpSRsG2Yhl/jz43Sd4hw3ihR3wLx//z7MheWppjQKIYClW/gghc/a7u4u+r3efKEuxR0wV9fWp9okRfLKd+H7firXQqPRhGXNPv3SDn8m6bWWe3v7KGWnOPvmHHlYeZI7YG5tbcEUJhad2dsLBJul+L4fy2YeF/nwww8x9IdTr6eTXi4+hwf3HyQ682B05rVbuOI7J5MVPoa6a3j86BGeKzz5ADSEwLOFcuprj4Cgk2mZBp67YudL6VbORc62Ugl1ozPqZqzUlbxgF8ykK3XXDnVGUHWIu8q0uroKyxKzFAsuVC4Cj1cfp1oZ29raghFWSbOF06+lbTAY4MGHD+Auz/beOGXAMEVqoe7R48fwp1lPBwC5DIRtpjpgNTqTbOnqh59YzKPb6aSy/TcQHg8zxzkiw3IBDxOuMI6OMyjOUakrphPqfN/Hvfv3gaUZzn1bvoO1tbXEdzqUgWyuUFdaBoRIPNR1u13s7e5OtUmKlA2/N40A2m635wp1ch1ektNb2+02Tk7qo6rbLFw7C8fyEl1PvrOzg6XsEkxjvilKK15w3SdZXbx37x4A4JUZKnVAEOo63U6i1/De3h7yjjfzGXXSklcYvU6UnppQNxwOsbq6iuflYVnnPFco4dHDh6lPC/vg3j28UMpduUmKJITAS6Us7t17P+aWPWlzcxMZQ2BhxvBhCIHlcLOUpPR6PcywQdxEGVPA9330+/FW61ZXV6+986VULgGtVjvVytj6+hrM8Lkij6VSYf3qxsYGup3uqPI2LcMUcBfTqY7X63VUD48gFqd7kAghgEU71QGrR48eBRfzFLMPZDUvjWNaqtUq6sfHM22SIomF0qgimZTNzU0Ytg14s09fg+fBsO3EP4cHBwc4rlZhLE9fSTKWb2M4GCR+TZweZzD9zpeSMDPIFJcSr5AHG5ANkV2YPtR55TsAkg+gQLCBWSbjXP2N52TCjnSSU0blerh5Ql3wc4uJrqnb3trGijvfJinAaahLcpnB/fv3seAVseDONrD2cuk5AKehMAl7e3tYmrNKBwB5y4NlZhjq5rW1tYV2p4MXS5NL0S+WFlA7Pk618zsYDHD//n28POUmKdIrCwU8frya+KLszc1NLOUNGHOkj+Wsj82N5B4ig0H/WmfUAYCcoRf31LDV1ccoFaIZXJBFh7Q69cfHxzg+rsMMl395OcA00+lAnCcrbbOGOgBwl33cv/9B4tMERxW3KUMdAPgLFh6tPo6nQVN49OgRjIU8xDQfwBRD3aiiuDhHqFssod/rJVqB3tzcBIqzTRWVhBBAsZR4xVwOhBgr04c6EX5vkh02INxwxMvDcOc8LLS0kvgGJDJEZstXH9wsmRkbXnE58QA6HA7R7XZGAW0WGSv5Sp2sss0z/RIAit5iojMQtre3sezOPiAhFe0ibNNJNNTde/8eXi48N/PP3cktw7PcRAdaD/b3seDMcD7oOUIILHnFyKu3T02okwutXygtTPx7GfbS2mULCG7I7U4HryzOlv5fWchjOBwmfnbW5sY6VrLzhY+VnMDOzm5iI9uDwQAzLJuaSPad4mxzo9HA0VH10k1SZlFKuTImQ4gMdcIA8qX0d+QEwrU9loBTnv1nveWgApr0ZimnoW760W2x6ODkuJ7akS0PPnwAf3G6jrGwMjBKuVRC3enOl/NV6oBkB0/WNzbmOs5A8osFrCd8X7h37x5gGBBLM5z7livAyOYSr4yvb2xAzHA+3XlGeQVbm5uJDvwEwUyE1bfpeeW7WF1NNtTJKps1R6VO/kwqoc6bL9SVsks4OEhmx+9Wq4Xj+jGWvfmvXyEElrPLiU2/PDk5webW5sxTLwHAEAZeLj6Le+8nN2OtclDBojd/pQ4AFpwcQ928grVqJp4rlif+/YulRQikt/kBALwfXpAfWZgt/cvvf++99yJv00WGwyG2trdn3vlSWs4L9BPcfW3QH1x7OqOcvhlnqJMVrOL17hUjngs4tpHaRhmyc26ObdSYL/v48MP0Bk+kDz64N/MmKZJ8Vibd0Xz8+DGEbU6386UUBsA0dpU8Pj5G5aAy1Xo6yV/K40EKh7s/fvwYhusEH5pZJbwDZr/fx8H+PsQ1Qp0olrC/t5focTj3PvgA5uLKTOe+CSGA5Tt4L+FK3fr6+vVCXekWer1uotWZtbU1ZEsrMGesfmUXnsHGZrLTh0ehzpo91JmmBUAkGurk1MlCdnJh4CrF7AKq1aPYl28A49vtzzENZcySs4yd7WQ2SpHP0ldKs1fqAODl4vN49OhxImtvu90ujk/qc2+SIi26BVQY6ubzwb17eKG4cOFaNc+y8EyxnMo6Gen9999H3rFwOzdbp6Lk2ljOuaNQmISDgwP0en0sz3hGnSTDYFKVjsEwglCXQKVOhro59mqYSAigWPBTm+748OFDOK6B8bXapUXg6KiaWuUIkJukfDjzJimSu5DOZimPHj0CFqbc+VIKp2qmMQV3VHFbnv6CFksF7O7sJL6z3ePHj+EvzDmdMZOBWSok9h7v7u5iOBzOtUmKJIpF+L6fWOgYDodBpW559i3WjZW72NrYSOyaODk5wXGtNtd6Okn+bJJrx1fX1uCWpl9PJ2UXnkG/10t0UwwZ6kxz9umXQghkMlaim+ccHBwg6+RhzdFeIJh+6ft+Ikt85I6VS+586/+kZXc5sd0vZd/75TlD3Sul59Af9BOZ5SHPWF6Yd2p2aMHNo1KpRLqXx1MR6gaDAT64fx8fWbj8An+lvIT3fvSj1DZLef+9H+GVcm6uTsVHyjm8/96PYmjVZDKMLWevF+qSXNMRwb4jsdvY2IBhAIX5p2o/IQh16VTq7t17H8WFs9OPiuHslTQHUNbX14NNUubsswlDwF1K9n+D7/t49PgR/MXpqxwAAM+E4WVSCXVySrhYmuGCDqt6SU7BDN7bx6Mz5+YxLBfw8HEy1dDRYNh1SvrhzyZ1D97c3ESr2YRxa/r1XpJx6w5830/s8yaDmFGav9Ihfzapqe/BuXqbM22SIsk1eEnO6JCBLKi6zS5jJhvqKpUKit58VToAKHrl0evETVYVl65ZqVt0l9BoNhI5D/DevXu4nVtGzppv2+8kN0uRwbx8jTV1AFBycugPBqjX61E0C8BTEuoeP36MTqeDj15x2OnHFpdxXK+nst16o9HA6to6XlmY7yH9kYUC9g8qidwwgNNOxdKc0y+LbnCsgQpb26tkc3MThbxx7Z06xxULwOHhUeIb6bTbbayuruF8v6gcjq0kvfHBuOtskiK5yz7uP7if2JqZw8NDnNRPIGZYTwcEo9r+gp34lvtAEOqMvAfhzbAGcLkw+tmkVCoVtJrNax0OKRZK2N7aTmQ6o7z/isL1pl8CyYU6OZNklk1SJGMlCCpJ3TNOQ9011iR5BRi2m1ilbmdnB/1eD9mF2UOzDIJJzuiQgSwzZ+XLTLxSV0HhGqFO/mwSxxrs7+/DNEwU7etN+VlyF0evF7cP7n2AlwuznU83bskto+jkE5k9I0Nd6ZqVunL481FWb5+KUPfDH/4QAPCxhatCXfD3P/pRchUv6YMPPoDv+/jojJukSB8Jfy6pKZjb29swDKA8x27aQHCswVLOSHS6hw42NzeQz0UbEuRgftIB+v79IPCc/9hlLKC4IBJdA3regwcPgk1SrrEhjbcMtFvtxN7XUaVtxlAHAP5ScKxB0rt13vvgg6k3SRnJOjCybqKbVo02SblWqCtiGFZL4ra9vQ2RyQDZaxxm6XkQmUxi06vu3bsHw7IhyrNPCROOC7O8mNg9I/hMCxiF+TbFAILBFKO4lNj9QQayWXa+lDJODk62lGilTg5+mDOsrxyXMe1E14NWKhUU3PLcP18IK3VJTL/c39/HorsIQ1yvi7/oJnNo+uHhIQ4qB3NPvQSCz9vLxefwwb34q/mnlbprhjqHoW4uP/zhD7GYzWE5e/n/Ac8WysjZzigEJkk+rF4pz1fOfbGUg2kYiT30dnZ2sJg1YU7YZOJ3ftDHZs3HZs3H/+frXfzODyYvDF70fGxvJbfeIN0TCK/m+z62t7dRvOIS+PZbQKUa/Prcl4M/X0a+XlKdN+ndd98FACxMqIaVV3z86EfvJrowf9x1NkmRZJUvqXV1o1C3NMcalEU78UO92+02Njc2ZlpPB4SVxaUcPrif3NTW01D3ZFsH33wLfqUKv1JF//f/CINvTv7AyUCYRMd4Z2cHRr5w4VT9weuvw69U4Fcq6P/BH2Dw+utPfI8QAka+kNjA2o/eew9YvgMx7zSE5Tv40fvvJ7I8YmtrC5lC+cINXdrf/F0MKlsYVLbQ+P1/hfY3f3fyCxWXEtthdHScwRzTLwHATXgHzFGoM2bY9GmMmeD0y8FggFqtinwYzM77w7d+E9vVVWxXV/FrX/4H+MO3fvOJ78k6BRjCSCzUle2Lq4q/de8zWKuvYq2+in/8xj/Cb937zMTvK7vBa8Q9A0w+Q68T6oDgEPL19fXYZyVVq1UIIVCw56xqhEphqItyf4EbH+p838cP3nkHH19cuXKtmiEEfmxhGT/4/jsJte7U+++/j2eKWeTs+W5wlmngxVIuuUrd1hYWvcmj/lu1Idp9oN0HPqz42KpN/r7FrMDW9nYiD2nTNHHRP9PpAa7r4lOf+hRc10XngsG/oX/6WnGo1+totdrIXzH4c3gE9HrBr5394M+XKYSvl3So+8EP3kGxLGBP2Pdn6VZwJEAaW9cPBgN8eI1NUiS5WUpSFaVHjx7ByFoQ3hz3iBR2wHz48CF834dYmWMK0HIR62vriXXa1tbWYHguxISdL/1KFej2gG4P/vZ+8OdJykFJPIkdMLd3djC85EbhVypArwv0uvB3toM/TzDM57GVwGZV3W43uH5vzRc4AMC4dRfH1WoiAxMbm5vwCxdXFAeVLaDbBrptDLYfBn+ewCguYW9vL5HBq7W1NTi5EjJzVg+y5WewtraW2J4CMtQZ5pP3s263eeaZ3O02n/geYZiJ7CQJBM/m4XB4YaVu+2gVnV4LnV4Lj/ffx/bRk/cAQxjIeyUcHV3xwI5AZb+CsnNxqFuvr6HVb6HVb+He0ftYr08O8+XwvJ+4p4zev38fAgIvFeeffgkAL5eexdCP/3ivarWKgu1duxIqQyFD3Qw2NjZwVK3iJ5enm8f/Eyt3sLm9lci8Z8n3fbz3o2CTlOv4yEIeH9y7l8gDZGd3BwtzbpIiLWaBdrsT6SLRi5imOQpl53V6wKuvvopPf/rTePXVVy8OdWE2NaJc8DZGjphHuUkKANg2YFki0amuvV4PP/jBD7Bwe/Kbvhh+HL///e8n1iZpa2sLnU73WuvpgHCzlMXkzrZ89PgRhgvzTVWSoS7JzVLk6KuYsVInf2Y4HCYW+lfX1uCXrrc9tchkYBQLiVTqdvf2IPLXP/dE5POJhKT79+9jOBhcO9QByayr297ehlG83s6BQBDqhoNBIv2J9fV1uKXZp15K2YW7aLWaiYQO4HQXacN4cpC0022efSZPCHWGMBOb6SGra3n3emvU8m459kqd7/uoHFawcEmom5ZlWCg4hURC3d38Ctw5ziwc91LxudHrxalWq6HgXGPqeyhruTCEgVqtFkGrAjc+1L399tsAgJ+Ychtl+X1Jdja3t7dxXK/jI3NukiJ9ZDGPTrcbe8et3W6jVjvGonfdUBf8fBKdCsMwLqzUORbw2muv4V/9q3+F1157Dc4F/WY/5kqdXIycu/694gwhgHxWJLLYWbp37x46nS4uGkvxskChZOB737ti7mgM5CjeNXd7BgA4Sz7u3/8g9tHt4XAYVIDmmHoJAMI2YBTtREPdgwcPYHgOkJv9QS2re0lNbV1bW4MoXz8k+eU8Hq/FW6lrt9to1OtAPoLRn3wejZOT2He3k0HsOqFOLN6CMDOxz0ZptVrBcQbXWE8nGWG1L+6je3zfx9r6OrLl+d9f+bNJrasbhTrx5PPUsbNnn8n2kw9FwzASC3WykpJ3r7EIG0DOKcR+lE+r1UKn20HpOgvGxxTtUuxtfnD/AV4szD8gIZWdAkpuIfaB1uPaMfKZOc4zPccQAgXHY6ibxfe+9z0sZ/O4nZvugf1iaRF5x8H3vve9mFt26vTQ8WuGuoVkNkuRIez6lbrg55OoIGUyFgYX7BHhWEFH6bOf/Sza7faFoS7u6ZdxhToAyHpD7O0lV6l78803IQSwfEkfY+nuEO+8806iO5gBQagThkA4s+RavCWg0WjGHpi3t7fR6/YgFuYfyRwuWHj4KLnprh/cvw9/KT/XES3IuzBcO5EdMGu1Gk7q9UgOhxTlIrY2t2LtbMr7r4gg1MnXiHtg7d69ezDzRYjs/G0WpgmxdAvvx1ypk8+jaELdwpnXjEu1WkWz0UC2PPvOopIXrsVL6ggGOXVyUqXOtrNnnsn2hFAnRCax6Zcy1OSuW6lziqgeVa/foEvISmvRjibUlaxSrNXFWq2Gg8oBXixeP9QJIfBi/i4e3I831NXrx8hb1w91AJCzXJycnETyWsAND3WDwQBvv/02fnL59tQdC0MI/OTSHbz15puJzS2/d+8enIyJ54rX682vZB0UXTv2UCc7sAvXrNSVw59PooJkWReHumn1B8H1kMnMt+7xKpVKBYYBuNebgTBR1kvmfBzpO9/5NhZWBKxLCksrzwDdbjBNM0kffvjhaD3cdYU7Psc+TXC0TmvOSh0AYNHG5sZmIh2hbrcbjPjPs54OcrOUPO4lcC6Z7MRGUakTpQL6vV6s97TRa+euN11//DXinl71o/fegz/HUQbniVt3cf/+/YRCc/naryVyJQAi9tAsr2Fvzk1SAMDJLcC0nETP1QMmh7ppGAmuqRuFOud6oS7nFlGtVWPtW45C3TXbKhXtIo4Oq5G81iRy4O6FCCp18nXW1tdiHSyuH9eRm7RZwBxyGYfn1E3r3r17aDQa+Knbs10sP3XrLiqHh4kseAeAe++/H+5eeb1OphACL5ey+OBeQqHumpW6nB2cVZfE9EvLsjAcXq+9gyFgWZn5Kg9TODo6gucaiOPlPReoVmuJbGlfqVTw4MGHuPXs5Q+u5TuAmRH49re/HXubxn348EM4i9E8VGWoi3sDktG96BqVOrHojA4ojtujR48wHAxGZ87NZbmI1cePY9+2/DTURdAJCoNhnOd9ycEZEUGok68R54BPrVbD3u7uXOfTnWes3EG304l1GvFppe76a5KEmYGZL8ZeqRsdZ1Ca/z0WwoBXup3YWXXyWSTm3GxCCJHYwPvx8TGEEHAnVAxnkXUK6PV66HQ6EbXsScfHxwCAghVNqCvYBRwfRzc98Dz57HyhOP+AxLgXis9gMBjEeh2fNE6Qi7BSVz9mqJvKG2+8ASEE/uTKbBfLfxSGwO9+97txNOuMfr+PDz/8EC9fc5MU6eVyHmtr67GukZChrnjNa1oIgXLWSKxS179mnhkMASumKh0QdH5cJ56HlOsGD9Eoy/wX+da3vgUAuHXF7sRmBli+4+Ob3/xGYg/nWq2G6lF1FMauy7QFnKKRSKgzCjaEfY1b9kJQ5UtiXZ1c0zDPJimSWC5iMBjEPri2sbERbLOfv/68ZxFuthLn2WSjqtp1zqiTwteIs1L3QVhtNWZ8Dk8iXyPOtZYHBwcQhgHhXb9yCwDIlWOvhG5ubsIwLTj56y0U9kp3sLGRzDFD173nCyQX6mq1GrJO/tq7HWbt/Oj14iJfu2BHs+Na3iqg1W7FNrj28OFDlN0iihG19/nCndHrxqHf76PT7SJ7zU1dJC/joNlsRPJawA0Pdd/9znfx0cVl5O3Z3vwlL4fnSwt4I4FQt7q6im6vh5cXormgX17IY+j7sS4UDQ7hNJG5ZmURAIr2MJFpgY7jYDC4Xnv7A8C2rzH97Qq1WhWOHVOoCz8CchQvTt/4xjeQKxoolK/+3tvPA/v7B4msnQJOA417/UH4EXthiIcP423/49XHGC5cc0ChHFy7SYzEP3jwAIZjAYX5z/ERK4XRa8Vpa2sLRjE///lp4zwXwrJiDXWHh4cwHDc4fPyaRCYDw3FjXTMThDoBY8rNyi4jimUYjhPrDpgHBwcwc6VorgcAIlvCXswDl5ubm/BKt67dZq90G3t7u4ke6j33zBdx/WA4rXq9Pgpk15F1gntanM9h+do5K6pQlz/zulF79PARns9fv4ov3ckuwzIysQ1eNpvBTqxeJpq+oGfZo9eMwo0NdUdHR/jg/gf46VvzzdP96VvP4Ac//CEajegS9CSjQxfnPHT8vJfC14l7JLPkRnMzLXkCB/vxT790XRfdwfXa3OsHrxOXk5M64sqM8nXjrtQdHx/j7be/h9vPD6eaRnrn+WB3zq997WuxtkuSO7tFVakDgoC4tbUd2/qOwWCAjfWNa029BABhGTBKTiLTyu8/uA9/6eLDsadSzMKwM7GHuo3NTQwL0cyUEEJAlPKxTnE9OjqCyF7v0NtxIuvFuo39/fv3YZYXIGYcXJ1ECAEs3cYHMT7f9g8O4GejmboGAEauGHulbmNjE27x1rVfxyvdwXA4TGTzMhnIBOa7Rwhx8Y7WUavX63Dt698jvPA14nwOn5ycIGNk4JjRVJKyVnxtltMkn81ff8BHMg0Td/MrsT3n5Cw4N6JQ55p2pDPrbmyo+853vgMA+Jnb851Q/4nbz2IwGOCtt+Ldcv3+/fvwrAxu5aIJC2XXxkLWiTXUHVYqKEa0mUfJFTg8Oop9xM1xHFy3z90bAE6Moa7RaMCe8xiyq8jXjXuQ4vXXX8dgMMTdF6f7ftsFlu4A/+E//HEio66rq6vI2AKZCHcYdcrBwymu6sze3h56vR5E+foPkWE5E/uW+4PBAI8fPQaus54O4ZqZxXi3p/Z9Hzs7OxDF6A6H9As5bMa4hf3h4SGGEd6Hhm68lbp7H3wALEXXaTOWb+PRo0exVZMqlcPopl4CENkiOu12bEsihsMhdnZ24JWu/x67pSAYxn0EAzBWZbvGwI/vx79GHABO6idwres/NOSavLhDnRdBWyUv441eN2o7Ozvo9rp4Nn/9AYlxz+RuB8+gGJyGumg6a27GQrfXi2zzpxsb6r71rW9h0cvhhdJ886w+triCvOOM1gfF5cMHD/BCMQsjwt0xXixk8WGMHaGjo0MUIgp1BQfo9fqRlp8ncV0X3f7wWsGh1wccJ75Q1251ENeSPfm67XY7nn8g9Md//MfIFQTKMyztuPtiUOlK4hDv9fV12OVrTPmZQB6NENe0xtFudAsRjAyWbWzHvOX++vp6EEKXIugYLxfw4cOHsW3wc3x8jHarBRSjqdQBgCjksLe7G1ubq7VasEg2Kq4bvGYMqtUqDisViAimXkpi+Q4G/X5sI/GHh4cQ2ShDXWH0unGoVCro9brRVOrC14hz+rA0ugdf45k87yYrszo5OYFrRVCpi7HqJTWbzVEQi4IXjoDG0UeTz7ZnclGHuhXsH+zH0t+Ru2paZjShzjYzZ173um5kqOt2u3jrzTfxM7efnbvzZhoGfmrlGXzn29+OrQM0GAzw6NEjvFCKrkMBAC+Ucljf2Ihlh6XBYIBq7RgFN5pOccEJXifOkWIA8DwPvh+si5tXtw/kothG/KLX73WRiecIvNHrxrnrVrVaxfe+9z3cfdGfafD17ouAYQh85Stfia1t0vrGGuxitBVBecZrXFuBj8JiBJU6UbbQi3nLfblAPYpQJ5by6HY6sVUO5DQzEdH0SwBAIYd+rxfblMba8TFEhKFOuC5qMa2XkWtljaXoOm3yteJYh9vr9dBsnMCIsFInXyuu62FnZwcA4BZXrv1alldExnJGrxkn2TfzMd/92PeHMCJY1z+NZrMJ175+UHIsb/R6cWk2m3DN6O4PbnjIdpyh7k7u+tfuuLvh68UxDV72oWwjmhF4+TpR9c1uZKj7/ve/j3ang5+9O9/US+ln7z6H43od7733XkQtO2tnZwftTgcvlC4vlX/mnUdYrTWwWmvgH33th/jMO5fvtPdCKYvhcDhaPxSler2O4XCIfERrv2Sok+fAxCUb7vLWucYUzF7fGL1O1IbDIQaDIeY8sudKcv18nOf6fPWrX8VwOMSzr8z2c7YDrDzj4ytf+aNYK0idTgeVg0NcdSbr1us+WhWgVQEe/oGPrdcv73SYtoCdNWJbR7WxsQHDzUB4ky+O4df3gIMOcNDB8HfXgz9fJAyGcZ5F9fDhQwjTAC7Y0XfwjfeBSh2o1NH/ve8Gf76ADIZx7WR2eiZZhJW68LXiCM7D4RDNkxMgyhkDrovmyUkslcVpQ1339T/CsLKHYWUPnT/4d+i+/kcXfq8oLcCw7FiuCbkZhPAivB7C14pro4lRqCtc3DH+8BufwUllDSeVNXz/d/8RPvzGZyZ+nxACTmE5kVBnhA8lf87rzvf92I4XOq/VbsGJoPplhwEpzt3JO50OHCO6w27l2rw4BoQ3NjaQt7MoXLFe8Tff+z2s1rewWt/CP/z2/xe/+d7vXfr9d2IMdaeVumg6a7Lix0rdJb75zW/CyVj4ieXr7ajzU7eegWkYsU3BlLvzXHXo+FqtgVZ/gFZ/gPcrx1irXb4u6rlwKlEcu//IB1PeieZmmgvvPXFu8QucVti611iG0ekj1lAHTLe8oNsLppN+6lOfCqaVTvG/Sb5unKHuS1/6IkqLYqpdL8979hXg8PAIb7/9dtTNGpEdlavOZG1XgGE3+NXYDv58lUxhGFs1aXNzE37pkqkelQ7QHQa/tlrBny9SskevGZdHjx5BlPNBsJvAr9SDsne3D2wfBX++yEIeECK2IyNGZ2RGcJyBJMLXimOziVarFUwhdyLcUcm24ft+LB3Nx48fw8wXINzLO8R+ZQ/odoBuB8Pt9eDPFxBCQCws4WEM18Qo1LkRhjo33lAnrzO3cPGc95ODNQy6LQy6LdS27+Hk4OIBXye/jO3tBEPdNSp1ZkQd68v0+330ej04EZxLZhgG7IwTa6Wu3WpfuUlKq98604do9S/+7MvXimMq4/b2Nm55V6/VWDveRqvfRqvfxvtHD7F2fPmz9lZ2afT6UZN9qIy4+Npr9Tpn39/exc/kTPg5iKpvduNC3XA4xLdefx0/tXIX9jU/8FnLxk8s38Y3v/GNiFp3lgxdzxaiDQq3ci4sM56zs2T4ytsRhbrwdeLean9UqbtGqOv2/NimX57uBDZNO4BXX30Vn/70p/Hqq6/OFOrisrq6ivv3H+DZV+Z7QN9+HrAdgS9+8YsRt+yUvMHb0c2sGrELwNZ2POtQ1jc34BcjWmyZNSEsM9Y1Mw8fPYK/GNFukhkTRikb2/bUlUoFwjSjDUk5b/TaUZNrcaLYSVKSrxXHOp8PHz6EX16O/HWxsIyHDx9FvrnSKNQ5EYZ8J95Qt7e3BydXhhHRGh+nsHQ62BGj0fRLxSt1o+l2EZ1LZmWcWJdBdLtdZIzLr4Vmr3mmD9HsXRwyrfC14mjz9tY2bnkRbkUd8jIOik4+luecnE1kXnJ8SLPfOfv+9i9+78xwXWhUs5TiO0k5JR988AEOj47w3/zsT0Tyen/qzvP49Xe+g7W1NbzwwguRvKa0traG5ZwHJ+KFVKYhcCfvxbJxQ70ejKpnI+oDydeJO9TJMNbp+ZguOp019H20u8PYQt3pqOXVbAt47bXXAAT/zU4xgCj7PkZEZy+d94UvfAGGATz78nw/b5rA3Rd9fP3rX0ej0YjlfZYj2lYMoc4qAAcfVjAYDCIdPe71ejg8qAAvRHOwnhACKFqxVRVPTk5wWKnA+OjHIntNfyGHDx/FM/2yUqnAyGWj7Rw6NkTGjGUb+9EIf5Tb5IbnnZycnOD27eg2NBkMBsHU4R//6cheUzIWlnFy7weo1Wool8uRva7cHVg40W00gYwFCCO2nYf39/dh56LrGDv5RTQaJ2i1WvC8CN+Hc+R9cujP15kdDqO9115EVqisiI4IsDN2rKGu3+vDumK9V9bKnulD3LIu/txnwteKemnEYDDAwcEBPvnCj0f6utKyuxDL4MQo1F2ySU8245x5f29f0ukwIg51N65S961vfQtCCHzizvXW00k/G77O66+/HsnrjdtYX8fdXHQjruPu5FxsrEe/pk6O5npWNJ0g2xTImCL289MKheBD1Z4wbflWWcCxAMcCnl8J/nyerPDJ14na6fqCq7/3zi0g67bxpS9+Flm3jTtT7EEgQ10cD8F+v48vfumLWHkWuE5f6LmPBiHmq1/9amRtG7e/vw9hABFuDDZi54KR46irM3t7e8GIdDG6TvywYMZWVRztSLgQ3REBWMhjd3snsjUH4w4PDzHMRnsPFkLAiOnst9EUyYi20w5eK+i0RT29and3F/1eD2KWrXCnJF8z6oHLUaizI9yIRgiYjhtbqNvd24eTjzDUhQExzs2UAMCygmt4MJxv2tlw2B+9RpxkAMuY0YxkW6Yd6y7UvX4P5hWhzst4aLfb+OxnP4t2u33pbplmOM0w6qUb1WoV/UEfi1450teVFt0S9nejD3WjWVWXDAR6lnP2/bUufsbIne+jWtN840Ld6998HR9fuoVCRNNTlrI5vFhejHxdne/72NzcxJ18PFvk38l72Nndi/yDKMNXVJW64LWM2ENdPh90MieFur/wCRO3ysCtMvDz/1kGf+ETTwYf+XPydaImhIBlZabanfM//lngL74K/Df/5+C///HPXv0zchDIjuF08+985zuoVWt44ZrFmfISUFwQ+Nxrn4umYeccHBzAzhuxTNmxwssi6o7QaMOCCEMdihZ2d3djORdQbsAiLtgkZR5iITe6X0bt8Ogo2uMBQkPXiWXzp1Fn0Ipwko0V7e5rkgxcohz99Cr5mlGHulElNIL1U+OE7ca2juqwUoGdLUf2ek4umBUQ947UmXAwYTicr0Lh+4PRa8RJnoeYiWh6q2lYsZ2xCACD/uDSKtKsDBE8M6PuS8pn5ZJ7xc5lc1p0SzioRD9bImrThMRZ3KhQt7Ozg8erj0fVtaj8qTvP4b333ov0IV2r1dBqtyM7dPy8WzkHw+Ew8vKzHG10IryXupn4D8Uehbo576Uy1MVVqQOCwHWdIxcu0wvvx44TfWX4c5/7Q7hZAyvPXO91hACe+6iP+x/cj2Vnu8OjQ5hePGeHyYHOqKszpxt5RBfqRN5Ct9MdTaWO0vr6erBBSiG6cqgMiHHs5lutViG8GGZLuE4QGCMmg5eIsDMrwqpf1NUDuZ7FKMUQ6vJFCDMT+ZoZ+R6ITMSDXxkrlupMu91Gq9WEnStH9pp2GOrimD48bhTqBvOFhcGwn2ioMyPamto0zFhDXSDagUsR8esBp8/K0lU7l82p7BTRardj3Wk0Sgx1E3z7298GgMhD3c/ceQ6+7+M73/lOZK8pR+BXplkQNQcZFqNeO9NqtWBnRKSHpdumH/uh2K7rwrYttDrzVSfkzxWL8dyAACCXyyKue7183ajXqu3v7+O7330Dz31kiCiW6z33MmCYYjQfPUqHh4exTL0E4gt1o8pfLsLOSz5z9rUjtLGxAVHKQUR5flR45EvUlTrf99E4OQHcOEKdjeMYQvOoMxjl2SdmtLuvSVtbWzBsB7hi58t5CCFgFMuRXxOjamXEYcGPacqdrKbZXnTVDjsbvFZc5+pJ155+OUgm1I12O4zoXDJTZGLdhVoX8voqO/HMfio58ZwPOdrgJ6KZLlHPl7lxoe5uoYQ7+Wg73i+VFrHgZUehMQpyBH4p4vUc0lI4+hz1aFur1YKTifaycTI+ms14K3UAUCoW0ZpzhlErrNSVSvFMFQCAfL6AGJYNATg9yiHqUPf5z38evu/j+Y9G83q2C9x53seXvvTFyKeD1WpVZOIZQxmFuqiP5jg4OICRsyDMCENSjKFufWMDfjHiqWtWBkbOjbwq02w2g3UMTvTrcoRj4ySGUDfqDF5wXMRcjHjWzOzs7EAUSrHtUOjni9iO+Dy1Xq8HYWYgIpy+BgAw4+nIy9lDMohFwbRcGKYV+zFDo1DXn28ksz/oxrKc4Dy5gYVxyRb2szAMM5YzIc+KNirMe+zEZUY7qVvxbD5XDM++i/o6lvsSDKbZAGEK8nWiGqC4MaGu3W7jne+/g5++dc05YBMIIfDTt57Bm2+8GdmNWYatRS+em9JC+LpRd9w6nQ7siPfasE0Re6UOAIqlEppzhqZmmC/irNSVSmV0Ygp17Y78N6J7+A8GA7z22uewfBfIRTgr9YUfAxqNJr72ta9F9pq+7+PkpAEzplAnDAHTFpFPaaxUKvCzEX/gwqpf1GtmfN/H7s4OcMW5m3O9dtGLvCpzuilGDPdgx0a304l8x7jR8yfKXWzD14p6StjO3h78iAdYx4lCEbsRb4TQ7/choqyCSjFNuZMdVsuN7gYshICdLcayJnScXArQH8z30Ov3e4mEuqjXPAmIWEOdYZoYRhQ4gOB/v+/7kW+yVq/X4WRs2BGtVTwvZwUjrVHv1yDDVz+i/w/74ZpShrpz3n77bfT6PXzi9rOxvP5P334WrXYLP/rRjyJ5vYODA1imgVyUC97HZAwDRdeOfDe+TqcDK+JnnmUA3Ri3+JVKpfL8lbqOD8MwYjvSAAgCV7sTz0dSZuYoQ+lbb72F/f2Da2+Qct7SbSBfNPCHf/iHkb1mu93GcDBERBuYTZRxot/F9fDoMPpQ5wX3nKinpRwdHQWVjgjX040UXOxEfJj36aYYMdyDw9eMenOM0yk/8Z/PdV0H+/sQUY72nCNyRTTDrfejElTqYgh1poleDJU6eRRQxo12ClvGycWy5nacDGT9/ryhrhvLGvHzov7MCRFvqDNNA4M5N5+ZZBAeORF1qDs5OUHWiu/IjFwmGFyM+jqW4Suq93gQXgtRvb83JtS9+eabcDIZfHxpiv3d5/AnVu7ANAy88cYbkbxetVpF0bVjPTyz6FiRj7YFB1tGW4rPmPEcbHnewsICWt35LvlGByiVCrGd8wYAS0tLaLZ8xLApIZotoFDIR7oF9Oc+9zk4roHbz0f2kgDkhilDvPvuu5FtjiE710aMoc6wEPmi7MPDQ8CL9mEqTAHDzUQe6uQ5gFFukjKS93B0eBhptWP0/1UMoU6EnzNdFulHrdPpoNloQGTjWS8DACIbDLBFvktjDM9kARHLbrNyEMmK8LB0ADDtbOyhTgaywRyVOt8fYjBIplIXNR/RVf0myWQyoyAWhbhCXavVghvjKKsTbnYU9Swwec1151wLel4vfJ2oruUbE+reevNN/PjSLVgxHUaZtWx8ZGEZb731ViSvV6vVUIzyANkJilYG1Yg7bv1+HxEvqUPGiP5gy0nK5TIa7eFcD9dmGyiXozkA+iLLy8vo9/1Y1tU1WsHrR+Xo6Ajf+tbrePaVIeL4yD33kWBW2Oc///lIXk8OGkS01n0ikYl2wx/f91Gvn0Qe6gAAnhn5WgM51VvEcEyLKLiRnwM4Ovcujs0WMubZf0MDUYYOOWAgg1cc5GvHvaGHyoJQJ2Da0Q6kZJwc6ifxrnMfTb+co1LXH/TOvEacTgdyI/p8+H6soc5xHHSH0Q1+9WJ6r9vtNpw4Q1342lEPrMn3oTvnrq3ndcP3143oaJ0bEer29/exsbmJP7Fyd6rv/413vovV2iFWa4f4+1/7An7jne9O9XP/0cpdPHjwYDTl4TpOTk6QjTodnZOzM5FPBxsMBjBEtCOOhkgm1C0sLKDX99Gd47PY7AALC9FvzT1uZWUFAHASw3FGzabA7dt3Inu9L33pSxgMhlNNvXz3u8DxYfDrm58P/nwV1wNuPQd84Qufj6Q6Mwp18Yz5AACE6aPTiS7UdTodDPp9CCf6Rvu2EflI/GhTplwMHa1wQ6lYQl2Um45I4UhH1DMQRh3MKKs+4WtFORIvn5Eihp0vJeFmz/xbkYlhpgQQbWiWWq0WMrYT+cYupuWiFdO5epJtBzOVev3ZPyP9XvAzUXWELyMDWFTr1HzEG+pcz0V3EN19pzuM573udruwjPgKG3KtXtT3YPk+yDB2XZ1BP1jHykrdqXfeeQcA8JPL03VaV2tHaPV7aPV7eL+yi9XadCN9P7F8G77v44c//OHcbZWajQayU077afX6cF0Xn/rUp+C6Llq96VKJlzEj31VyMBhcOTul3fPPtLfdu/xhZorod16bpFwuAzjd9GQWzY6BhYV4K3V37gTXbz3ic9h9P3hN+frXfz0fr732OSzeEshPse9K7RDo94Jfh7vBn6fx/EeB4+N6JLvOykGDafo+gy7OXL/Tzg4SBtCPcHBi1Fm9KtR1B2fai+7VbfAdA7XjaCt1h4eHwRl1cewmGR7REuVUO3nPEVeEOr/bO/P++t0pHubhkQ5RD1aNgtcVa3L8bvdcmy+5iP1o13QAY+tYnOk6gn63c669U9ykw9eOcnDCNE34U3Te/W77XHsvH8zxh/EclN1qtWBOcVB6v9s6095+9/LqhWk5aMW8eZlhGHAcF/3e7P9Orx/8jOfFN2ggyYGUy66Ldq91rs9z8fs7jPnQ9KBSF2GoCx+AUU917ff7yEw5GNHqn/28tfpXXzPyAPao1y/KUNeec9fW8zqDLhw7uqVYNyLU/eAHP0DWtvFCqRzrv/PKwjIs08QPfvCDa79Ws9mY+miAZn+AV199FZ/+9Kfx6quvojnlCdVuxkSzGW3p2ff9Ky+aVh9n2tu6Kq8ltOZ/cTGotJ3M+Jb4vo+T1nD083F55plg59bjiENduwP0+j7u3p2ukn2V999/Hxsbm3juIzENaYdWngG8rIEvfOEL136tUed6ylA3fv1OveQj4orzaJMN54pGd4Zn2ovOFA8x20Aj4pH4arUKI+vEMwod7uYb5RrhqTdA6PbOvr/ThDo5uh9xh2K0Jvaq1+12z7X5kot4EH2okzNEhD3l6H63c669V3dKhe2c+beiYJomMMUGCH63daa9/hUhCcMhrBg68u12G+YUB6X3u80z7e13L//smxkHnQR2pHZdF915Ql03uVAnP3P9S9ZQtXtn39927+L3N+5D0z3PQzvCSl2rH1zb2Wy06zaDWV9T9oF7Zz9vzUtCs2QIA0KIyAsG8n1ozlFhnqTZ6yIX4TT1+E9uTMC7P/whPrawMvUFMi/bNPFKeQk/evfda79Wr9efuvSczZijw5hfe+013J7yTIGMKdCLaDRhFl4GZ9q7pMhaZhnKGm0fsyTJTg8YDP3YQ10ul0OpVIx8OlEtfLnnnnsuktf7whe+gExG4JmX4g11hgE88/IQ3/3ud3F0dHStSuksU59M++z1a057vxXRTrEarc+7avDHMc60F/kp7oOWgXbEaw2Oj4/hO1Y8YzRh9S/Kz8YocF3VYNs6+/7mpggqER9QO2pKOFru9/uXN9u2z7b5kk6DHw5ERLlmZnTtTrsxk+2ce4+n2KU3fO0o17FaloXhFJ1AYXtn2ityVzwbYurI93o9GFNsCZ+xs2fam8ldvqGcYWbQ7/fgx7z+y/O8UdVtFklW6qbZ7dC1zr6/Zff2hd87iKlqK+VyOTT70c3Qavabo9dNS9Y6+3m7bU3ZF/Oj35TG8zwYQqAVVajrd5CN8L3VvlJ3cnKCtfV1fGwxuk0gLvOxxRU8ePDg2gvge70erCl3UvSsDNrtNj772c+i3W7Dm3LapmUY6PX6kXcsrno11xJn2utaV3yo4s0GI6ehbrafO2mf/fk4vfDCi6hFvOlYlKGu2+3ij//4q7j9vI9MvPv8AAg2TBkOh/jqV796rdcZVSGmuNZMG2eu36nXcg8BM8JFe6e7M17x+bHNM+2d6iBJK/qzIau1Gnwnns6KMA0YjhVpqDtdn3bFv21bZ95fMc0GVxGfbSWNgtcVwUPY9rk2X3IRh68V5ZoZuY5FTHmTELZzrr1XB0xhmBCmGel17DgO4A/hX7EJgrDdc+29/L0Tg14s67/kYelXydjemfZmrthYRZgWfN+Pfa2757mjqtu4paUXYVtZ2FYWz9z5CSwtvXjm72V1L4lQNzp64ZIpG67lnevzXNyu/qAb6S7U5+VyObSmqGRNS1bqog51hmFM3Tf1Mmc/b17m6s+S7/uxrF80DAOel0WzF02oa/U6yOUZ6kYePHgAAHilnEyoe6W8hP5ggMePH1/rdYbDoVx2ERsjhilAhmFgGHEIGwKxHhUgFQoFmKaJk9Zs/wPk9ycR6l588UVUj0Wk+yAcHQOOY+PWresf9/HGG2+g0Wji2VciaNgUCmWgtCjw5S9/6VqvM1oXEd/xQPB9wIhw043TjTxiuFGYAv0p1+ZOq9FoAHZ8I9DCzowODI/C6VqZGEaVhtFvPgKMBa8opxT1o9/dbjTlKabdqCVhmJEGj9P3N+IZLv14Qt1wOIQQ0b/HwohnPdJ5uVwO3QkB5M/92b+C5aUXsbz0Iv7i/+n/gT/3Z//Kmb/vdeMJGpPIz8U8G7pM0h10Y93gpVAooDvojtbCXVejdzJ63SiZpolBjA/kYQxrhaVisYCTK9bRTuuk3470/OAbE+peKsff4R7/d+S/Oy8hROwFKtlZiTIwZTIZDIbRdjIHQ8Q6HUEyDAOLiwujytu05Bq8paWl6Bt1zksvvYRu10cjwuVO1WoQFqO4Dr761a/CcQ0sR7M8byrPvOTj/v0H2Nramvs15IM5wuN7nuAPAHfKjSGmcboOMIZQZwgMBoNIA02z1Yw11PlWJtLDvEf3nEEMHYuwMxz1iPxoXUsvwqMSwsGDKDvIo2s3xql7AADDiDTUycqPH9EovOT3OrF05H3fj+lcvSRD3eyf6U43GNyJep3XJKe7HUZzTfT68VwLUqkU7F520otmral8Hfm6UbFte3RGWxy6EZ//Nq5YLOIkomroSY+h7ozHjx+j7GVRjLAzdZmVbB6uZV27UidEtNWYSUbbAER407csC4OI2z0YAmYCoQ4IzmqbdaOUJEPdK68EJbCjajSv5/vAUc3ARz7y0Wu/VqfTwbe+9TpuvzBEAoXVkbsvBf/92te+NvdryFAX4zMEft+Ip9oRQ6gTYfUvykXk7VZ7dD5bHPyMEf1UOwCIY4pZuJlV1KFOBq9Ld7OckdzNM801M3OL+CGazweHpV+1m+Wshp3W6LWjFEuVOUG5XA69KzZtmaSbQqWuG1HQ7/TaiYS6ejeadRz1bh2e60UejhzHQWcY3zmecZ2vBwClcjmyUFfvtBjqxq2vreGZXLRl4csIIXA3X8Ta2tq1XseyLPRiHgXrDYewplx/Ny3LstCPuFLXHwJODKMpkywvr+CkPVv76y0fuWw2kTNxXn75ZQBAJaLzdBtNoN0ZjsLidbz55pvodLq4+0IEDZtBNg+UlwW+9vX5Q50cgY/wTNYn+L1o13iMOmwJ7Q57Xf1+P54z30K+ISI5s1AadVKm3E14Fn4YlqPuUIw6sVEeah7uNBllBzmW8/Qm8f1IZ6LIyo/fia4i7A/68Pu9WALItEcwzEq+ZtzLIvL5PDpX7Rw6QbfbhBBGImvqTNOE63ro9K/fie8PehgM+7GGUXl0U70bzfrj4+5x5FU6IPistSOaIjqJPPYgjve6VCrheI7r9rzuoIdOvxvp+6t9qNvc3MTdaQ7LitDdXBEb6+vXeg3bttGLY9rPmN5gCNuKNiy5rotexH2g7gBwEghMQFBtq8+8pg5YWo6/SgcEN7pnnrkbWaiTr/Oxj01xSvgVvvWtb8GyBZaiO8N8aref93H/g/tzHz6dzWYhhECEOz0/od9FpKPxowp7jP3iKDttcYc6YRqR7uZ7OpUxhqQfrleMenqY4zhB9a8d4YXc7sCyrEgD6Ghq6xTHA1yHPxxGumZGjphHGurC14p6TRIQrheKJdQNTl8/RrlcDt1uc+Zg2u02kc16iazFB4Csl0UngsqMfI04p43Ktf/VbjWS16t1qlhcin55Uz6fn+pognk1Ygx1CwsLqLUb166UVzvBNOIo92tIJdQJIR4LIX4ghHhbCPHGvK/TbDZRPznBcoRnPExjJZtD5fDwWnP5Pc9DO4YR4nHt/jDy6pLjONOcbTyT7sCHk9D02eXlZXR7PjpXHIg+rt4WWFm5/iYj0/qxH/s4KkfRfDQPDoOO+3Urdb7v49vf/haW7/qJTr2Ubj8b/PeNN+a7XRiGAS/rIqK17k/wfR/99jDSjlucW4nHERT94TDeNVRCYBDhPXNUlZnm3LlZ9XoQQkR+/xVCoFAqwY9wGqrfbqNQLEZ6vY3WsEZ8RtQ4fxjsUhnleyxHzP12dBvy+K1gTZKsoETJNM0rd+qchz/oQwgRe2gqFArwfX80nXJa7U4D+XxyM7Ty+Rxa3etfE/L8ujgrdfLon1qnGsnr1XrVWDaJy+fzaPXa6Mc08NMI3+s4pj0vLCygPxxcewfMWjjgc53jms5Ls1L3n/u+/wnf9z857wvs7+8DAJYSDnVL2RyGw+HcVQNAjlLEG+oavT4KhWgvaM/z0OlHOzLY6YvE1nOsrKwAAOozPENOWqc/l4SPf/zjaDSHiOLc+IMK8NJLL157FH51dRXVag0rz1y/TfMoLABu1sBbb70192uUSmUMYjpPV75ulB2302pH9AnMHwRbPUc+Eh/zdDsRYSdzFMA7MUwBanfhZbOxdIrLpRLQjnCEu92KfHrVKGjFUQWVwqptLKGuFWGoCwNilOtmJNd1MRxE/x4PBz1Yth3vwBJOP4Odzmzvd6dzgmIxuVBXKBYiCXXNbhDw47gWJNd1kcvmUO1EM93nqH0Uy34Cp9NEo/usjTvuBO91lIFJGlVDO9fbjKbajr6NWk+/rFarAIBSQlUeqeQE87hrtdrcr5EvFHASc6Wu2e0jX4j25pHNZtHt+xhE2NHsDEQiu1gBQaUOAOrN6do/GPpotIajn0vCxz/+cQDA/vxjBgCC/vXBkcDHP/7j127T97//fQBIdNfLcUIAi7eHePvt78095WFpaQn9CHcVHSeXW0R5cz5d8xVDUBr4sKY5b20GcXcAEfFByLZtw3acaKcyhvx2J5Z1KACwtLgIEeHB8aLVwnLEnbbTDV1iGkUB4IdrAaMciXccB66Xhd+K7rBQvxm8VhzVDtu2MYhh+sGg14U9xVmB1yVDXXvGznGnexLLdNaLFItFtHrXDx+tTvyhDggGoQ/b1w91rX4L7X47lkFtGepqEW3ocp583Tgq5DLkHravF+qOwp+Psn+ZVqjzAXxBCPGmEOIX5n0ReRBt4YqDP89r9YJzQj71qU/BdV20ZtweuhDe7K4T6srlMurdGLfiA3DcG0Q+SiEf1u0Im97uJbM1MTAW6qbsE520gos1yVD30Y9+FKZpXjvU1epAt+vjJ37iJ67dph/96Efwcgayc/Sfel2c+bzNuxv74i2gWq1hd3d3vp9fWMSgFc8tT+7KHUuoi2Pt7WAY+c6MZiYzXVu7/TPXA6a8D/pDH1bEu+QWSyX4rRjm5LY7KJfjCXWLMYS6qAPHqNMaZUXxvPC1o+4gLy0tYtiI7pD7YfM4fN3oqx2e52EQQ3Ae9FqJbEJyWqmbMdR1GrEHo3HFYhHNzvXDR7MTz5lv563cWsFR5/Dar3PYDjohcYQ62ac6akf3WRt31D6G67ix9C1P2369a+KwXUcmk7kRG6X8Od/3fxbAfwngF4UQ/8fz3yCE+AUhxBtCiDfkNMvzWuGDzZ3xQd/s9/Dqq6/i05/+NF599VU0Z1x872asM//+PBYWFnDc7mAY43SlWrsbeaiTN6NmRDOWfN9HozNIbNRtaWkJQggcT1mpk+EvyemXjuPgIx955dqhbv8g+G8Uoe69936E0tJ84aLfw5nP27x7XSyEufr999+f6+dv3bqF7okfyzbg8kigKA54l0adqm4Moa7rR95ps217ylB39v6LKde0icEw8m21lxYXgVb0nWKj1cHSYjybKy0tLWHQbAZrGK/JHw4xaDYjD3Wna9PiC3V+OxhJibpzv7y8DL85/4DteX6jBiemzmUul0O/14Ef8bqkfreFfAJLIuau1HUasayVuki5XEajfXztZ8dJpzZ6vTitrKyg0j649utUWvGFOvmalXY18teWr7uyshLLDJJRpa51vUrdYesEy4tLkbYxmcPBzvF9fzP8754Q4ncA/P/be/Mwyc67vvfzq+qu3qr3fd+mZ5+RZEu2JEu2ZGPjYBtjNuMNHHID5iYE7r2+uWwBQ4DEIUDYbsISx1wISwgBjO3YAYMDsQ3I2LLkTftIo5nea9+X894/3nOqT/dUVVd113JKej/PM89UnTrn1Nun3u37/pb3ZcBfHTnn14BfA7jzzjvLtqRsVq+w9vjr+zP6u7r52Mc+BsDHPvYxpgP1TW4CdhyK8/0nYXx8nKKliGfzDPc2Pp1/tlAkmcs3bQU2lVM0Itd6pqBDhlq16tbd3c3I8BDxVG2rQ474a6WlDuDixUt8+MNPYlknT0yyswcDA/0sLCycqizJZJLt7R3O3XGy67u6OdTeuk+oJQZHwOeDp556igceeKDu66emprCKikIauhs8v8ontPthI1fjD9LXN0PUFRkYaOykKBAIkKrFpTxwuP9loDaLoRSthm8RMDE+zpPbmw29J4BKpZu2r+XExIT2rU6n4LS/YToFSjV80uaMOyrVmA2Qy6FSjc8cBzA1OQlPXmvY/axEhOmp5iwKOn1EIZemu7dx7bmYSxOcaL6oc8b9TB1ubJZlkc4kWmqpGxkZoWgVyeRT9AVO/lySmRjd3d1N90yamZkhkUuQLqTp6zr54t2eLQxnZhqf8np0dJSuri720w1K9X2E/UyEyfnmJLgLBAKMDA+znz6dlXE/E2NyrrF9Q8stdSIyICKDzmvgdcAXT3Ivy16p9NWpcvu6A2QyGf74j/+YTCZDX51p/53vO82qjbOiv1eD68/S8AB9XX76uvycHx9iafj4TmXfvu/09PSJy1gOpyNN5hpj7XAsfq3soCenpmp2v4zbbnWttNQBXLx4kUJBEYqc/B67+z4uXrx06mQN1+3tOwZP6CHQHeBQezvpLhs+PwSHfSfeI9JpC/ljPCZ6x8EX0P8GZvX748jFYWx87CC5SQNorqizGr4SPzAwUJsrZaDrUH0gUNszk1yx4QmVJiYmUMlU1b5cxkcg0A2BbmR2Ur+vgsrnsbK5pok6py9SicoxPjI+rhtedwCZmdXvy5XVvkej+7dAIMBAMIhK1jZZl/EpCPRAoAff7KJ+fwzOvRst6iYnJykmo1WtX/7xOQj0QqAX/+yafl+JZISZBlrw3TgW0fwpY3uOUswmmhYT6mZwcBARIVOHG1s2lwRU061dbkpJPdKRsp/Pji7T091HT3cfK5PnmR1dLntePBNleHik6fHHjgjbT5e31i0OLtHX1UdfVx/nRs+zOFh+89m99C6B7kBT4kF9Ph/TU9PspI53E10amqWvq5e+rl7Oj66xNHR8cP9OOsTcXPMyu01PT7NXQdQtD0/R1xWgryvA+bEFlofLt//9TJzpBgvmdljqpoE/sit1F/A7SqmPneaGTd7etPL3nkLUORPMvVSW9dHqrofvuLrKc1E9+P7g/Zdruv9eSou6RrqDgatza1AYSjyrn2EzMhRVYnJyiq9uPVXTufG0or+vt2XZOR0uXrwIwPYuTJygP83mIBy1Svc5DTdv3gRgoHW6uyJ9QYsbN54/0bVOB5+NQX+VtY65e4TMvq6Xa2+sbfDNxYSNU1pEjxIMBhERVKbY8P3HfVnV8Enb4GAQos3JZAagso3fwHlqagorl8eXy0NP+dUG/70vQe1HAOh606uPv2lCrwQ1ekHNodSnJxJQ4Tv899yDsrMzd73xjZVvlkgcvmcDmZ6e5lqitpXswD2vJru/A0DPG7+tpmtUIsrg0FDDt42Ynp4GpVCJCDJUXgz33vtmivt2v/im7zmmnGGmp682tIwOzmJoPh2HkcZNDnPpWEsWWv1+PwMDQTJ1xKs5ArCVC8HOAk0iE2FqeP6Wz7/uJe9kM/wsAP/oNT9c8T6JdISJFux564i6nfQOC4OLt3z+tnPv4HpcL47+8zt/sOJ9dtO7TE9NN02Ezs3PsfPYzWPPe+eFr+e5mPao+KGXf/ex5yfzKZK5VFNF3dT0NE/c/FLZz9556dU8G9X92Q/fW74/K1hFQul4w/vellvqlFJPK6Vus/9dUkr91Env5QT655u8welR8raF8DTxHbOzeqVhJ9Gc7GDbSX3fRldqR3w5Yuy0xDKtF3VTU1PEU7XFVsVS2rLXaiYnJ5mcnGDnhG7xznWXL9e2CFCNvT19s77W6tqy9A1w4q1EZmZmEBFyjQuXAfTiTi4mzM/dOtifBp/PR3AwCOkm9G/pYuNFXXAQyTYn+ZMqWli5fMPjaErCK97AFPb2vZohlOCgzCp++sQNzj2aIUBnZ2aQRIMbmwsVjzLbBLcwZ0JsxU4Z1IzO/llMJ5vivgYH42Y+3cAYQKtIPpNomSVsaGioLktdO0SdY6mKVbDU1Uo8E2maBd+NM+/bTe2c6j476W3mFponjObn59lK7WLVufn8cWwmd0v3bxYzMzPsp2MnzosRysRRSjW87+3oLQ2cFbpsEzc4LYfzfadZIezr62N8dJStRHMCybcTafp6exsulnp6ehjo7yPWIC3qWPxaa6mbJFdQZGvIzxBPC1NTzVlxP44rV66ys+c70dZf27vg9/s4e/bsqcsRDofp6hK6Gpss8UT09EIqlSaXqz9TTyAQYHpmmgbtyVqimIFCxmJx8dYV0dMyPDzccFGnLIWVLjR80jYyMgLpJuz5BpDR9210P+EsrqlY49zXnHs1a5W4r69Pb0DeIFE3ODTUlEyHs7OzWLFoQxK6lEPikaY8Y+eeVvz02QMdYdisuuCIjVwq0rB75tI6IUgrxAfAyMgw6TpEXdrOltgK91AH51nEThn/FU+Hm+LKeJTBwUEGg4PspE+WKRr0YuVOaqep1q6lpSWyhRyhTGMXf24mtJhtxpjsMDMzQ75YKO01Vy+7djImZwxqFB0t6pzMSYlcE1JSV8H5vtNmbFxYWmIz2RxL3c14mvn5+aaYzcfGxohmGmOpi2YUPp+vpf7xTvxIrIY9y+It3njczcWLF0mlLaqEzlRkZ09vjdAI16RUKkV3oMl7kNWIIyxPmnl2ZXmFXLSx3Z6zHdDycvk4itMwOTGJpBpsqUsXoQmTttHRUax0tinZRR2x2AmijliCnt7epk4652ZmIN6AVODxWFOsXQALCwuoYgFVowtmPahCnmIs1pRJ28TEBF3d3VjR02cPdERdoyduDsPDw/h8PrLJSMPumbPv1QrxAbpNZ+pIa+9Y6lq5ENzf309//wCxGuK/KpHNZ0jnUi2bT8zNzbGdOrmoi2Qj5IrZptVd0KIODkRYo7iZ3KW7q7tpFnI4aNO7J8yUu5M0ou4WSpsXZpu3wWk5Yvb3nVaILC8vcyOebsok6EYiw8rqasPvCzA5NU20QY88mlaMjY7gtzOKtgLHLSqerv7c80VFKmO1TdQ5rpPb5Xf0qEixCHsh4dKl07teAuTzeXyt+3mq4pTjJJY60G0uE7Gwio1rc46ocwaoRjIxMYEkGyzqkoXSvRvJ+Pi4TmWbaby1TiX1QlqjJ5oDAwMMjQyjog3cbDoab9qCmsP8/Dy+BljqfPH4qbPjVsIRXCpyeovXUVQ0DKimlN3n8zE7O4cVrbPjLYNzj2a5gfl8PsbGxskmG/eMnXu1atwbHh4uWd9qIW27mrbS/RL084imTu6S61zbque6sLjAdnrrxNdvp/S1zeof4GAh9Hri5OUsx/X4JktLS02dVzqCcfuEVvKdVIQuv7/hi6sdLepKGwCmazC5NJD9tDadnPbHWFlZIZMvlJKaNIpELk8knW2K5QD0c49kGjNhiaQVEy0WTbVa6tqV+dJheXmZ/v6+ukXdXhiKRcWVK1eaU7AOZm1tDWXRUBfMTAgGggNN2fZicnISK5lHWQ1c+GmSqCu1k0QTPCfs2ONmxKktLy4hkcaJOl80wVIT3X5Ai4RiPI46ReiBKhQoxuNNc69yxh8rdHpxdBTnnisrKw2/N8DS4gI0wlIX2WV0bLypG3lPz0yTjZ8+/s8hE9d/d7NiQo8yMjJCOh1D1RhXlU7HGBgIlnIqtIqpqQ4TdQsLhNIhssWT9cdbSZ2YpJkujENDQ0yMT3A91thtZa4ntlhbX2voPY8yPT2Nz+dj54SibjsVYXp6puHCs6NF3cjICD2BALtN3AunHHupBMMNyLq1alvSrtfiB1gH16P6fuvr6w29r8P09DSxdJFCA6wd4YyPmZnmmffLMTIygt/vI37MBuTO5+0SdT6fj0uXLrG7X18z3bHnUI3IfAk6jrLY2lxEFXFyIp10vzKnzWUaaDzIhoT1tfWmWGampqb0nmSJBsYNx3QwaaMDtEup9mvdL6QOVCKN3+9visvV4uIiROMN8ZhQhQLFWKKpEyFwxWidxgXTvrZZVqTBwUHGJyZQ4caLOhXaw+/3N82KsLCwQDG2d+pNvVV0l6Wl5taF6akpcsnGibpsfJ9AT0/LLGEjIyMopchka4szSGdiLQ3XcJiZmTmVqIskm7fnWzmcPmgreTIr2FZqk0Cgp+l79K6tr/FconGiLpqNE8nESmN9s+jq6mJ6aoqt5MniLLdTEeYXGt/3drSoExFmZ2fZaoLPfjU2k3HmGpDpbm1tDRHhWqSxotS5XzNFHUD4lHM3SynCKatpqb8r4ff7GR8fO9ZSF7P/vnaJOoBLly4TjlrUs8/99i7Mz881bOAbGBggn1UnStjSaPJ2cpuTrnwvLCwQCHRTYfueulGWIhPS8YvNoDQBiNeQ1adGVDxPb1/vqWOCj3JQ1iYkf4qlmZyeOvWei+VYWVnBymQh3QCf8rAei5rlJeFw4Np48gQDzrXNFKBn1tdhvwmWuv1tlpaXG7ovpJulpSWUZZ0qrk4phRXZYbkJbtluZmZmyMT3sYqNWfhJx3aYmZlt+l5qDs44la4xg2cqHWVkpHVJUhymp6dJZRNk8ifr3yLJPbr8XS2LVXTa9Wby+C0DyrGZ3GRxYaEpfa6bM2fOcCOxTbbYGLf9a7EbAGxsbDTkftWYm59n+wTxrEoptpPNSfTU0aIOYHllheeTrRV1N+JRlldOP2j39vayMD/Ps5HG7u30bDTJ+NhY01azHBEWOsbSdRzRDBQt1TI3DzdTU9Ml0VaJdrtfAly6dAmAnRoXCJXSm443Kp4OdBxTsajINymxYT1kU3o/tJO63vj9ftbW18k0SNRlI2AVVNMGkFIQdaxxoo5YnunpmYZP2gYHBwkOBlHRxrvDSyzN4nxzrDKOAFOh02dgU2F9j2a5BTo4FioVjZz4Hs61zYyZ2djYoBjZRzWw81BKwf4O5xqQ2bcSTnysFT5F9sBkFCuXaUqsrZu5uTlt6Yo3plPLxneYn2ud94wzT0nVKOoymVhLk6Q4OPOeSPJkixTh5C4TExMtyx8wNzeHT3wnF3WpmywtN7fugu4jlFKlfehOiyPqmmXUcDM/P892Kly3l0ckmyRbyDXFS6LjRd3Kygq7iTipFs04w+kU8WymYabdc+fP80w01dBkKc9EU5w7f75h9zuKM9HcT56uzM71zcyuVInJySkS6erVP5ZSDA8Pnmo/wtNy9uxZ/H5fyaXyOGJxyGQbs+m4gyNq0631ci5LKnH6fQPPbpwlsy8NiVNzLH7NstRNTk7i7+pCRRrXv/mihabFfM3PL0CDRZ1SChVt3kayTl+uQpFT30vtR+ju7m5qGnDQluqx8XFUJHLie6hIhNGxsabGe21sbIBSWPuNy26n4lGsTLppbQ5coi5yclHnCMJWiDqATPTkZXVQyiIT2216/XXjCLR6LHXtEHXOPCV0wkyN4eQOc/Ote66BQICZmZkTibpsMct+er/pdRcobbv0TPT5htzv6ejzLMwvMDDQ/I11FxYWSOdzRLP1jXlbCR3/YURdGUoVItI4n/JqPG1/T6NW5s+dO0c0kyXUoP2dErk8W/EU586da8j9yjE+Pk53dxd7p7TU7dmirpkbRFZicnKSeMqqKqb1dgattyK66e3tZW1trWZLnbPpuGPhawSOG0e8efsI10wy5mN56XRW8rNnz1LMq4YkS0ntQF9fb9OsHX6/X08moo3pH1RRYUWbs0IIsLy0hDTaUpfMovKFprkJDg8PMzI2itqPnPpeKhRleWWlJavxy8vLSPTkjVKi0aZbFJ1xyNppXMyMtavvdb6JC5e9vb1MTc9QDJ08K18xrK9tldU2FTl9BsFsfJ9iId9U6+1RHIGWqiE1fLFYIJNJtEXUOe7l4cTJLXWtiqdzWF5ZZjNVv6jbTOhrWiHqJiYmGB8d4+nY9VPfSynFM7HrnDvfvPmvG2cc3aoz++ymHYfXlOy9Db9ji3FE3ZOhBvlTHcOTYR2g3SjTrjMwPRluTPa1p8PanNJMUefz+ZidmWEvcXpR1+X3t8W9cXJykqKlSFaJVWvnxuNuLl68xF5IqGUP3509GBjob2hnMT8/T1d3F7HGZyavi1wGUgnr1FZyp22kGhDqk94Vzp0739S4g6XFRXyRBiVKieVBNScVPOhJgJXMoLINjAG0+7RmxqmdWT+D7J9u1UIphexHdBxZC1heWkJFIify8lBKoSKRpsd7jY6OMjE5hbVzMhewclg7m3R3dzc9EcLa6gqETy6UrNAWQyMjTd8ke3h4mODgEKnI6YVzKqr/3mYn+nETDAbp6uqqyVKXtjepboeoGxwcZGBggFCifotoJp8mmYm3XtQtL7Od3KZg1Td+3EjeKF3fCs5dOM9T0dOLulAmSiQTb+r8140zjm4m6kuWspUMEejubsrct+NF3dDQEMtLSzxWh3vH8vAofV3d9HV1c358muXh2juIx/Z32NjYaMimzqCTpQQCAZ4MNUbUPRmK4xNp6iomwMLiErup8jE5c8M+erugtwvWx4W54fLVbDehmJltfErXWnAaU7yKUSHRxo3H3Vy4cIFCQRGuYc65FxLOn7/QUJHR3d3NmfV1widcNxke05uGd3XD2LR+fxKc7z9t3V5YWKB/oJ/0KT3CrIIiE1JNH0CWlpawojlUpWyz4z0Q8Ol/c336fSXCehWjWYN16b6hyr66Mj4IgS79b3ZUv6+GLeqauWq8ceYMVjiKKpwi22EyhZXJNtUt0M3y8jIqn4fECfyiEwlUPt+SlfjLly4iO5uNCzHYucm5c+ealiTFYXV1lUJkF1U42QKFCm2yvtbctOoOS4sLpCOVhXNwYgl/oA9/oI/h2XMEJ8r/7qmQvkcrRZ2IMDIySiodOfZcx5rXDlEH2tX1JO6Xofh26fpWsry8TFEV2UrVtzhxM3mDrq6ulpX3woULbCf3iOdOl1/iycizQOMyfx/H5OQk3d3dbNZrqUuE9V6jTVgM7nhRB3Dl6lUeD+9SqMWUAbzr6l0sD4+xPDzGj9z/Ot519a6arssU8jwV3mvo/l9dXV2cO3uWJ6tMgurhyVCclZWVpsZJgLbe7CUsrDID9VuudDE/LMwPC//kvgBvuVJ+8N1NCgsLrRs83DhpehMVNiDP5hWZnNX0dL61cOHCBQB2j3HBzOchHFVNEfRXr95GZA9OMr+5dBcMjel/936tfn8S9regq7vr1H+fz+fjwvkLpHdOlygkvQvKav4Asry8rDf1rhBX57tvCiZ6YKIH35sX9ftKhPU9mjWZL8Wn7VdepPK/4jyMD8L4IF1ff5d+XwW1H2d4ZKSpaczPnDkDSp0qrk7thQ/u1QJKCV7C9afUdq5ptmsg6PZRTMZRDchSrQp5invbDXUvr8Ta2pqOBzxBXJ2yihTD2y0TdSsrK6TDNysK5/VXvIPg+BLB8SVue/MPsv6Kd5Q9LxW+wdDQcMu3DBgbG60pUYpjzWuXqJufnyeUrL8+7NvWvVaHmjh9xGbiRl3X3UzcYGF+oWUL7s4c58nIc6e6z5OR5wh0B5puxXfw+/3Mz82xmahT1KXCLDRp4eQFIeruuOMOMnktuJrJY/s7FC2LO+64o6H3vXjpEs9GE2RPs0qMziT5VCTJpcuNy3xYicXFRYqWYv+ECyuWUuwlrZb67rspWeoqZMBMeGA7A4fp6WkGB4PsHSPq9kI6+2UzRN0dd9yBsrSwahe7N4VLFy+deI86NxcuXCAdUhRzJ7cepOwF22ZbxQ+sX6ff1FuFckxOTTbM0+AoExMTDASDVUVdvUgo2XSXRidG2hFmJ0HthvH5fC2bUByIuvr9op1rWuFeddkej6zt+iaW5bB2NsGyWiLqnN+xuF+/W6MV3UMVCy0RzaB/x1wmQa6GuLRqpMI3WG5BxsOjjI2N1eR+mbQ3em7VtgBHmZubI5zYpVDn9hHtstQtLi7iEx836hR1N1I3WFldaU6hyrCxsYHf7y9Z2k7KE9FnOXfubNOt+G4Wl5bYqmMD8nyxwG4y2jRr+AtC1N1+++34fD4eacCgUY1Htm8S6O4uDVKN4vLlyxQtVYqHOynPxZJk8oWGl68cToXcSdRmHT3KfhIKRdUS959yDA0N0dXlJ1Yh2UvctuB5wVInol0q98LVLUt79tyuGe6AV65coa+vl63Tu72fiGQc4hHFPffc05D7Oda19Cni6lLbMDM70/RV7cXFRXx+H2r/9MlSfPs5zqw3z5IkImycOYM0SNSpooUKJZpu/ZqamiI4NIjaPXngqNoLsbS01DTBfJRgMKgzYIZOZqkbHRsjGAw2oWSHWVlZoa+/H2vz9J2HtfU8ItISUTc3N0d3IIB1ElG3r90YW5FWHQ4srqnQyTMIKmWRCt9o2aKEm9HR2twv0/Y57dh8HLSlTSlFuM5tDfbjm4yPjbesb3AIBALMzs6WYuRqIVPIsJ/aa1k8HejERGfWz/B45NqJ75Et5ng2eoOLLegb3CwsLLCTjFCwajPK7KQiWMoyoq4awWCQixcu8PntxgVjH0Upxee3b3Db7bc3xFLg5uLFi4gIj+2fzj3l8T19fSsGPEeMbcdPZulwxGArfffd+Hw+xsZGSxa5ozgWPC+IOtAJgSJRVdp8uxx7IZiammxKYH53dzd3330P29eFGvuuhrJ5Tf9/7733NuR+58+fR0RIntDyqJQivePjcgP3A6xEIBDQFu1TWupUwcKKZJs+advY2ECFEqjiyRZ8DhGKoyyr6RvJigjnz55DTmipU0ohe5GWBeg7rK2tIZH6yyzhcMtcA/1+P5cvXYJGWOo2r7O8stISMer3+1ldWaW4X/+8orh/E7+/q2XjmyPqkqGTC+dMfI9CrnHbNdXD6Ogo6XQM65gQmlQ6ysBAsG3bDDmeRaF4fQPHfmKbhcX2eCWtrK5wM1V727tpC8BWWZkdLl2+xNPR5+tO6uLwTPR5iqqx2znVwuLiIpayat6E3EmqYkTdMdx9zz08Fw2xl2rsRt4ON+NRdpJx7r777obfOxgMsrq6cmpR99h+jJnp6Za4DAaDQUZHhk8s6rbs69plqQOYmJg61v1yfHy8dQWqwtmzZ1EKqoX8hCI+NjaatyHvgw8+SC6r2GmuQfwWlIIbzwgXL14obQB7WgYGBlhaXiJ1wq2dcjHIp1s3gJxZP4PvtJa6cA6UHSvURDY2NrSga0CcsNrVfWIr4tTOnj2LFYqi8ieYVMSTWOlMy0Xd6sqKzoBZYzw5gLIsVCTS0sn7bbfdRjG8jzrF+KyKRdTOJrffdlsDS1adM2fWUeH6k7wU92+yuLREd3d3k0p2mJGREUZHx0jsn1zUJe1r2yHqxsbG9EJZproLZioVaVs8HRzExO3F67Pe7ie22rJ1EzgZMLfIF2sbPxxXzVZa6kAbI/LFfGnz8Hp5PHytdJ9W4oizWuPqbiabt0cdvIBEneOW9febpwu0rMRD9n2bIeoArly5ylPhRM3JXo6ilOLxUIIrV682uGSVWV5ZZeuEXlbbMcXY6EhLVlwrMTk5SSJTvgnEU4rBwYG2bjzuxpnU7ldYlM/lIBZvrkXjpS99KcMjw1x/smlfUZbInna9fO1rX9fQ+16+dJn07sk2IXfEYKsGkPX1daxEHpU+xdYGu5nSvZqJI2zU7uk3NlQ7UYJDgy1JBX7u3DmdLOUE1jrHbdPZYqdVLC8vo4pFqGe/umgUVSy2dNJ21R6XiqdwwbR2N1GFPLe1UNStra1hZVKoGlfhS4Q22TjTGtdLhzNn1kmdQtQl9p5DpHUxoW5q3asulY4yPt6eeDrQ2xoMDQ6xV4elLpVNkMzE25Y/YHl5GaUUm6nahOiNxPMEugMt337BGUsfs8VZvTwefoaV5WUGB4/JptxgnN/1ZqK2zYQ3E/uMj47R39/flPK8YETdwsICK8vLPNQAv/1yPLR5nQvnzzfNHe/KlStkC0WuRU62knkjniaezTU0M+dxrKyssJ1QZTNgHsdWAlZWW+P+U4nx8XES6fIbkCcyMD7mDSsd6LIODQ1SKXzGseA1c8Le1dXF177ua9m5AenmGMTL8tzj0NMT4IEHHmjofS9dukQxp8icwOMuuQX9A/0tszSXLFV7J3fBVHtZevv6mj5YT09P6/i0ndOLOtmNc+GcdpVtNgdi9ASJR3b26erubrnLkmN1rSdZinNuKyfvZ86cobevD+sUi67WTT22tyJm3MHpT4t7tbtgWqkYxVS8ZfF0DmtrayTDN7GKJ9uCIbl/nbn5+ZbHfcFB4pPj4urS6UjbkqQ4LCws1GWpc85tl6XO6ZNuJGqLt7yReJ7FxcWWbzU1OjrK/OxcyeJWD5ayeCL6XMvj6QD6+/sZHx2reVuDm4kwi02cN7xgRB3Affffz2N724QzVTYfOwFbiRjPRkLcd//9Db2vG0eMfXXvZBOhx+zrrrbSUre8TK6gCNf5uC2l2I6rlk+AjjI+Pk6+oMiVMX4kMsLEZJXU8C1GRFhfXycULT+5bYWoA3jDG94ACM8+3tSvKZHLwM1rwtd8zWsbvrLlrAzWuYUPQCmerpmbjrsp/a67Jxd1spfjzPp608ssIlqI7Z7OnVzlCliheNOzizrojbInUTu1rbgeYjfMmTPrLXO3c1hcXMTn89WVLEWFdJbOVrq++/1+rly+DKex1G0+x8rqKkNDQw0sWXVWV1cREaz92l3CnCQpzXZzPsr6+jrKKpIKnyy3QGr/uZZbFx0coVYtA6ZSilQ62lb3S4CFxQX267DUOee2K3/A/Pw8fr+fmzVmwLyZutnSzJduLl25zBORZ7FUfR5r1+NbpPOZlho13CwuLbGZPL4PVkqxlQyxuNS8uvCCEnWvetWrUMBDNxrrgvm3N3Sa1Ve+8pUNva+bkZERlhYX+ereySZCX92PMTE+3lKTuSPKtuL1NcD9pCJf9IaoA8omS0lmxDPxdA6rq2tEo1DOQzccgcHBYNNXMWdmZrj77ru5/oRQZ1bnE/Hs41AsKr7+67++4feenp5mdGyEercdKmQUmXBr0qo7DA4OMjk9hbJdKOtFWQr2sy1zD7x48SJWKIHKnsxqAJQsfa0SdQAXzp+vO1mKsizUXpjz51pXTodAIMDs/DwqVJ+lbnZ+vuWu5bfddhvFSAiVrD/WUhULqJ2bLY2nA+jr62Nmdq6ubQ2KLc586eBY8xN79aeFz2cSpON7LS+zgyPUklVSw+fzafL5rCcsdfF0hEy+QkD+EXZjN+nyd7XcndGhu7ub+bn5mrY1SOWTRDLhlsfTOVy+fJlELslmndlFHeteq5OkOCwsLrCZCB0bexvNpkjls00V+C8oUbe0tMTK8gqfuXGtoff9zI1nuXjhAlNTzbXcXL3tNp4IJyjWGeOjlOKx/ThXb7utJW5KDqWNLWP1ldc53zui7nD5LaVIpIueE3Vra2sUiop4mTlROCqsrq615Pf/pm/6JrIZ1fTYumIRrj3m484772xKXRERLl+6Qmanvm6w1fF0DufPnsO3d8JkKeEcqtD8LJIOzmayp3LBbIOoO3/+PFYsgUrXIZ5DUVSh0NJyullfXcVXRwZMXzjMehvipm6//XYAiidwwbR2NlGFQukerWTjzDqEard+FfduMjk13fJ48dnZWXr7+kjs1i/qEvv6N2mXqOvp6aG/f4BUFVHnbE7eblHnTMj3YrUJ/b34FjOzsy13Z3SzvLLMzdTxdfhmUp/TLlHnjKn1umA+Hn6GifGJhiVSq5eFhQVS+SyxXHW3NcdFs5nxlS8oUQfw6te8midCu+wkq2fwWB4eZXn4eDP+9ViY52NhHnz1qxtVxIpcuXKFTL7As9FbZ+1LwwMsDQ+UvW4rkSGaaW08HegMglOTE2VF3dywj7nh8tVrM6YQkbZ1HA7O4JDIwNSIMDWiBVEqozMutnvwOIrzvMJH5slKQSTWOpF8+fJlzp0/x9Nf8ZW1GpZjeEz/q4frT0I2bfEt3/It9ReyRi5dukQ2bpFPHK7DveP6XzlS29qdrNVJMTY2NrBiOVSmzJ4S4z36XyV2MqV7tIJz584hIqjtSNnPZXwQGa8e0K62IywsLrR0clyKqzviginjI8j4SNlrnBi8dom61dVVirEY6sh+JzI+jhxZmFL5PMVYrC3JMNbW1ugfGCjFxh1FxqeQ8fILp9bN5xCRtrhXra+vU4iFUNnDlhn/+Bz+8TKbSYc2ObPe+nhxn8/HmfUzFS11wYklghPlXW4dIdiKLLOVOLoB+fj4MuPjB3OEVJs3HndwJuRH4+pmR5eZHb11TrMf32SxTdsZOKysrLCX2iVbPHDfXxxcYnHwcH1wrHntWnCfn59neGi4rKhbGpplaWj2luNKKR6PPsvlK5dbatRw49QJdwbM5eEplocP92fO580Uda3bdr1FPPDAA3zgAx/gM89f483nKg8A77p6V033+/T1Z/D5fE11vXRwBqzH9mKsjR6e8LzjauVB2NkKoR0D3uraOs9+5dZV4rdcqVy1NmOKmZnptgRku3GLutfcfrCKlswc/twrODEwkSMeuskU5POt28hdRHj7297Oj/3Yj3HzGVioYXH3Um3NrYRlwdNfEs6dP9vUbHfOymByG0Zc2mHunsqDQ2oH1tfXGr5f5XGURORuBhYPL/D47qvuRaB2M/T29bUsWL+/v5/llRWe3S5vqfO/oroAUkohOzEuP3BnM4pXkY2NDS1Gd0OwfPCs/Pe+pOI11s4+wcHWZOgshzMBU+Ew4vIm8dsZod2ocPjQNa3E7/dz9coVHvrKY2U/D9xTeeHU2rzO2vp6W7Ill5KlhDbpmj0Qa733vvmWc1U+RyGyy/p6YzP11srGxhm+8tWPoKwi4jtsGVp/xTsqXpfYu8bEZHP2OK2VsbFRdncipff33fOuQ587lrp2x9TNzs7i8/lusdR93Uveecu5lmWxH9/mVQuN2V/1pCwtLaFQbCW3WB7SwvNt526tD5vJG/QEeprulVYJEeHS5Us88YVb+4h3XigfgrGXDhNOR9vmegnubQ3CnB/Xr9956db+bCsZItDd3dRtx15wlrrp6WkuXbrEp29cq3tvmaNYSvHpG9d46UtewsjISGMKWIXx8XHmZmf5ap371X11L8rI8HBbUuaurq6yEy9SKNb+rLcS2lWw3fT399PTEyB5xP0ykdHvvSbqent7mZgYJ3qkekRto3QrEx+8/OUvZ2Vlmae+KNQZ01wTN56GVELx9re9vamrb2trawQC3aR2ajtfWYr0rnD5cusXUEpWtp364+pkN8fZsxstS+wCcPnSJWQneqItI4gksTK5lru49vb2srS8jNqpPUZNdsOlzezbQUmg1ZIB0z6nXSvxt912G8VoGCtR+xinCnnUzk3uaIPrJRwkPLFq2IS8GN4CVNvcGM+cOUOxkCMVqW8fteTes5xtkRW/EkctdUfxiqWuu7ub6emZmjJgRpK7FK1C25KkOJRCZZLV4+puJm+Wki+1i4sXL7KT3CeSrW2/rCci2src6rHCzeTkJN3d3cdmwNxMhJmbm2/q833BiTqAV7/61dyIRXg2eoJc5S4e399hP5Xk1a95TYNKdjxXb7uNJ0KJurYJeDyU4PKVK22ZVKyurmIp2E7UVt5cQbGbKLbF/acco6OjJI7MkR1LXbtXBMuxtLRELH74d3ZEXitFvYjwjne8k3hUcbP+EI6qWBY89UUfa+trvPzlL2/szY/Q1dXF2bPnSO/U1nbS+2AVVClmrJUEg0Fm52brTpaiigr2M5w729qNsS9evIiVK0D4BIkxtiKle7QaJ1lKLYuCKp/HCkc512JXXDczMzN0BwI1ZcBU4TDdgdbvQeXgWN2tOrJgWjubqGKxpZmd3YyNjTE4NFxTshRH+LVrfHMWfuqJqyvk0qQiWy1zza7E6OjoMTF1Efz+rrbubeuwuLjAfuL4DJiO8GvXHnUOc3Nz+Hy+UsxcJTZTmywtt25xuByOOHuixri6JyLP0tfb29Y5pd/vZ252lu1jMmBupXRIQTN5QYq6V77ylXT5/Xz6+WdOdZ9PPf8MvT093Htv60znly9fJpnLczNe2z4Be6kM+6lM2wY8pyHVmixlO65Qqn2D3lHGxsZJdZCom59fIJYQ3PPNWBx6e3tavoJ53333sbS0yJOPNtZad/MZSMQs3vXOd7VkoeLixYuk9xRW4fg67CRJaYeoAzh39hy+3TozSoayqKJqeQygMzirrRNs5r0VITg02Ja9nc6dO4eVyUL8+M0Y1V4YlCrF4rUDn8+nNxiuwVKnQjqzXbtW4ldXV+kfCNYn6jav66RGLdyfzo2IsL62ihU6XtQV9zfp7etra8KGQE8P8d1rNV+T2NNJUrwg6nL5DPl8+UWrVCrKyMhIW61IDgsLeluD41Lvt3uPOofu7m5mZ2bZTFauw5lChlB6v+1WxTNnztDV1cWTkdoWJp6MPMu58+fbmogGYGFxka0qixJFy2I3GWl6XWh/62gCQ0ND3PWyl/HpG9fq3u/CIV8s8nc3n+Oee+9taeyXM3A9VuPWBo/vxw9d12oWFhbo6vLXLOqc81q9h08lRkdHSeUOC4dURtHX29vymKlamJ+fJ5ezyLq2K4sl9Epcqy21Pp+Pd77zXcQjjbPWWRY8+aiwtrbKPWVigprBhQsXUJa2wh1HakfHfjTTJ74a586dw0rkUKk69pOw3TVbLeqmp6cZGRstWd3qQbajXL54qS3eB85zqsUF00mS0upne5TVlRUkEjn2PIlGWG1j1mGfz8fVK5dhq7aNkAHU5nVW19YYGCifKKwVrK2tYYW3UMdkhlKhTdZWV9smPPx+P+tr6yTr2NYgYQvAdiZJAfcG5OVdMFPpCGNj3lhoXVhYIF/IEUtV7yP24lsEB4JtjVV0WFpeYrNKBsytlBZ87RZ1gUCAjTMbPBk9PktuppDlufhmW+PpHObm5thORipqjr10lKKyjKg7Ka9+9auJpFN8ea/OTahsvrB9g2Quy2ta6HoJ2pVmbHSUJ0K1+RM/vh+jv6+vbTESfr+fpaUlbsZqE883Y4qeNrr/HGVkZITUkf2ck1kYGW1/J1yO2Vmd/Snm8mhLJH3Mz7fHveP+++9ncXGhYdY6baVTvOtd396yCb1jZUnV0FVkdn1cvNg+3/2SeKgjrk7tZAgOBltuPRARLcy264sRVqksVjTZthiJlZUVurq7UXu1iLow4xMTbbfqLy8vY6VSqEzleqGyWaxksu1Zh69evUoxGkaljnfLVcUC1u5my/enO8rq6iqqkMeKVV75UUphhbfavmC5sXGGxP6zqBo75MTeNcbGxtteh53vr+SCmU5H2x5P5+C4Ux63Cfl+bIuFxYW2xdu6WVhYYCe1XVF0bCXbu0m6mwsXL3AteoOCVX3x8pno8yjVnnCIoywsLFC0iuyny8/dt5MRoPlW2xesqHv5y19OX18fn75+MhfMTz//DCPDw7zkJZWznjUDEeHipUs8UWMcypPhBOcvXGir6Xl1dY2teG1VaTOmWF5ebrup3GF0dJR0xsJyJXNIZWB01Ft71Dk4oi5he4YpBYmEaptIdlvrNk9prWuHlQ50gqLxiXHSx+x3WsgosjGrra52Z86csbMz1i7qfLs5zp0915aJxaVLl7DiKVSyDhFqZ8xsl6jr6upibXW1ZIWrhuyF2xpP51DKgFnFWudkvmxlQqVyOF4lxc3jrXXW7haqUGibJ4qD83yruWCqZBQrm277/qsbGxsU81nSkeNjvkAnSdnYaK+VDg5EXTpdfhEonYm2XXg6VNrW4Cj7ya22u146LC4uUrSK7FUY6LZSm/jEx9xcmW06Wsz58+fJWwWeO0Y0PxXVbtztHJMdnLmZI96O4sTbNfv5vmBFXU9PD694xSv47NZ18sUy+zpVIZ3P8/ntG7zyVa9qi/i4dOkSe8kMoXS26nmpfIHn27ii7bC6uko0XSSRPd4FczMBqx5xvQRtqVNA2rWncyonLcl2ehIca4sj6tIZKFqqbTEcoK11C4617hQJZ29e01a6d7Yols7NhfMXyOxV7w6dsbCdA0hvby+LS4uwU71vcFB5CyuUbVuZD+LqIjVfo7bC+Lu62hrjc/bsWWQ/UjVZisrlsKLxtscigWt1vZoLpv1Zuy11Z86cIdDTg7VdPRMfgLWlz2n3GLe0tISIUAxVnmQ6n7Vb1DmZN51YuWoU81mS4U1P1OGSpS4dueUzpSxSqZhnRN3Y2Bi9Pb3sxyu7d+QKGaLJUNuTpDg45XAsckfZSm4xNTVFIBBoZbHK4uz5+XSkeh1+Onqd2ZlZT7i3OmJtO1U+hnw7FaG3p6fpdfgFK+pA71mXyuV4ZOf4VMRu/t4Wgg888EBzCnYMjn/wU6Hq1rqnwwkU7Uva4OAMYlvx6jP6eFaRyFhtH/TcDA0NARxywUxn8UQnUY7e3l4GBwdI2Hl0HHHXrn1lQLvgvuPt7yAWUWzVnv/gEErBU18UlpeXWmqlczh79izZmEUhU7kOp3a1Jb3dsSfnzp7Dt5erbcuW/Swo1bZJ29raGt3d3SXrW03sRNnYONPWycXGxgZWLn/Yz/kIai9SOrfdTE1NEejpQUUqJ6VREZ35sp19Bej+4sL581CLqNu+wez8fNsX2Xp7e5mansEKV57EW2E9WW63aF5eXqarq6viJuRukvvXaecWDG6Gh4cR8ZWNqctkEihleUbUiQhz83NVLXWO4POKpc4px3a6fB3eSW8zv+CNsk5NTTEyPMwzserW/Gdiz3PufPutdKA9fgLd3RUzYG4nI8zONj/3wQta1N1xxx0MDQ7ytzeu1XXd3954lsmJibaJpbW1NZ39J1w9ru6pUBwRKa1qtItaM2A6n3sl8yUciLeUbWVUSpHOWp4VdQBTU9MkbTGXtMVduxJ3OLzqVa9idnaGp05ordu6DvGI4m1ve3tbkgw4E/NMlWQpmT2YnZtta8IGsAVHKg/JGpKl2G6a7RKi3d3dnD13FqlR1KmiBbsxLrUxbhEOrB1qr4pI2g8fOred+Hw+FhYWqrtfRiJt34PK4dKlSxT3d1D5XMVzlFKwc5PLHkiCALC6sgyRaqJum+GR0dJCYbvo6upiZWW1JlHnnNPuhSrQYn9oaKjsXnVe2XjczcLCAqFE5fqwn/CWqBseHqa/r5+d1K2WOqUU2ynvuIqKCBtnz/JMrPLCTzQbZz8daXuSKgefz8f09Ay7qfLuwzvpKHPzzXdtbX/v3kS6urp4xX338bntG+SKtWWLS+ZyPLqzyf2vfGXbBr9AIMCZ9XWeiRxvqVtcWGj7JHN8fJyB/n42j0mWsmV/7iVLnbMC7FjqMnmwlHctdQATE5OkMnq1xxF1ExMTbSyRHpC/9VvfSmRfsV9bKEcJpeDpLwozM9O88pWvbE4Bj8GZ1FSLq8vu+zi70f4BpDQB2z3eBVPtZhkcGmyr6L944SJqL4Yq1OAGvx9HFa22ex8sLy/j8/tR+5GK56i9CEMjw55J3rC0uIgvVjkpjS8WY8kDSRDA9i5RCqtKIjMVi2Bl0p7IbAe6ThSjuyirfD1WkW1WVtprpXM4c2adVOj6sdb8xP5zBIPt7R/cjIyMlI2pc4Reuy22bubm5ggn9yhWSOYRsi11XohRAy2U5ufn2S6TESyWi5EpZDwj6kB7z9xIbJMtll/4uWYLPq+IOtCLvjtlFiWUUuymoi3JffCCFnWg430y+TyP7hy/xwzAw9vPU7CK3H///U0uWXXOnT/PtUiSolW+U1ZK8XQ0ybk2W+lAdxYrqytsH5OwczOuGAwGPdUxO6uqGXt+7IQxelvUTZBKa1GXSmtryODgYJtLBV/zNV/DyMgwT325vutCOxDeU3zzN39L2xLoDA0NMTk5QbpCboxCRpFNWJ5Y0V5fX9fJUvaOTz7i289xduNsW7Ov6S0jLNg7PqOv2o6UrmkngUBAW76qiDoJRdlYb399cFhcXKQYi6EKt04yVaFAMRbzRGY7OIiZsbYrh0ZYdthEuz1RHJaWllCWVTYDplIKK7LLcpuT0Disra2RS8fJVUja4JDcf471M+ueyM4IMDo6Utb9MuVRUWdZRaLJ8u4docQ2I8Mj9Pf3t7hklZmbn2M3s3PL8d20PuYVAQp68VIpxfUKLq7PxnT/0O5ss25mZ2fZTd0aix3NJskXC6VkKs3kBS/qbrvtNgYGBnjo5vFBwwAP3XyO8bGxtg8kZ8+eJVsospkovwl5KJ0jlsl5ZpVieXmF7QRVVwa349pK55UBBCiJISdRivN/u11oqjE2NkYmY1Es6kQpY2OjnnimgUCAN7/5G9i9AfFI7dc9/WUYHAzy2te+tmllq4UzZzbIhsp3iY5bphcGkN7eXuYW5mGvuqVOFXWSlHYLUacvVTuRY89VO1HGxsfbbnkGOLO+joTLW76UZaHCUU/UB4dSQoZy1jr7mFdW4oeGhpiemcHarbzYau1uEejpaXuMmoMjiMvF1alUDCuX8YxoduplYr+yC6ayLFKh51n3UB0eGRkhky1jqcvESp97BUcA7VdwwQwldjwlkkBvmbWf2qd4xNrsiDqvbDUFBx4pjng7yrOxG8zNtj8cws309DTpfI5k/vCC604qWvq82bzgRV1XVxcvf/nLeXjnBsVjNg7NFYs8urvJPffe2/a4AyfG51okWfbza7ZrpheC9EGLtVTOIl5hnqmUYjsByx5yvQRt5err7SWd02I0bcfWecHyVQnH3Sud0Za68XHvbL/whje8ge7uLq59tbbzUwnYvg5veMMb6e3tbW7hjmFtbY1MxMIq3LowkbEteF6InwI4e2YD336++kmhHFiq7aLO2TJC7Ry/X53sxrnogT2HQPdpViKJypZx/4nGUZblqfhgR7CpaBn3n5g+5pVMfAAXzp9Hqrlf7m6xsbHhme1vSqIucquPtnPMK8/XEXXJUOVEE+nYNsVC3lMLEyMjI6RTt9bfdDqK3+8nGAy2oVTlcawu4cStli+AUHKH2bnmW2bqYXZ2lqIqEsoedknZTen66yVRNzk5yUD/ANcrbGtwPbnFmkfGYwcnCdXeERfifft9K5JUveBFHcA999xDIpvliVD1jai+vLtFtlDg7rvvblHJKrOwsEBPIFBR1D0bTeLz+TzTITt7H1XKgBnNQDpntX2PpHIMDgVLbpeZDrDUOauVmSxkcz5GR70R0wPabfWBBx7kxjNClRwIJZ59TLvvvuENb2h+4Y5hdXUVFGQjt36WCcHwyJBnVorX19ex4jlUpkqcmm3J84IQvXD+ArJbXdSpTA4rmvSM94Ej2FS4jEgK6WNeig92rAKOgHOjorFD53iBjY0NiokYKn3rGKcsCxXa8cQegA79/f2MjI5hRfdu+cyKekvUDQwMMDk5ZWe3LI/zmZfq8MjICLl8hkLh8OCRTscZGhpu+2K7m7GxMQLdAUJlRF2hmCeWDHmqvcGBaNtPH67De5ldxkfHPbGdgYOIsLa2xvXErdb8bCHHdmLfU4tqcPB8944kS9m1RZ2x1DWIl770pfj9fh4+JoXyw9vP09vTw2233daiklXG7/ezurbG9VhlUbcwP09PT0+LS1YeR6ztVBB1Owl16DwvMTg4VBJzjvully11JVGX0f+8Fv/3xje+kUJecfNa9fMsC2487ePuu+9ue5p1OEhFnikTV5cNC6sr3lhAAZcb6H5lF0y1nyXQ09MSP/7jOHfuHFYshcpUyXZoW/K8sJEsuFLTl3HBVOEYIuIZdzvQE/nBoSFUGfdLFYsxODTkKVclx4Js7d86KVaREKpQ8MSChJvFhXmsWBlLXXSX7kDAE27DDmtrq6TDlec8ydDziPg8494KB2OZ427pkM7EPDfO6WyH02VFXSS5h0J5yvIFB6Li6Abke+k9pmfat9dtJVZWV3g+sXVLWM+N5DYK5TlRV9FSl4oxFBykr6+v6WV4UYi6gYEBLl26xCNVkqUopfjCzia33X67Z1Yr1tbWuB5Ll41Tez6e9pTpeWxsjP6+XrYT5V1ct+MeF3W2J1smpxART01+jlIa+LKQ8eD2C+fOnWNlZZnrT1aP89t5HjJpi9e//vUtKll15ufn8fv9ZI5ksVdKkY20f/8pNyVRVy2ubj/L6uqKJ1a3HTdxVc1atxc7dG67mZyc1Hu/lRN1kRjTMzOeGSsc5ubmIF4mIU085jmrQUnU7d06Kbb2tw+d4xXm5+chVs5St8fs7Kwn2prDysoKyfAmVoXM38nQDebm5jxVhw8WLA/X4UwmxsiIt8Y5gJnZGSKpW+tDOOk9d0bQfZqIsH9k755Qdt+Tom55eZl0Pksoc9j74IadWdRLYzJoD69AdzehI4sS+5kYE1OtyTDrnR6oydx55508Fw0RyaTLfr6djLObjHPnnXe2uGSVWVtbI5nLEz6yup3KF9hLZjy1SqFXrZfYqZDgbjdh0dfb65n0324GBwfJ5rUAyeZhoL/PU4PzURzX0ERCbwfgNVdREeG1r30dkT1Fosr2ZM8/DcPDQ9x1112tK1wV/H4/c3OzZI+UuZCEYl55yiozOjrK0PAQKlRe1Cml8IXyrK16w7pYmpzvVRZ1ajfGjIcC330+H4sLC6jIrWWWSNwzmQ7dzM3O4isj6nyJBHMesNi6CQaDjE9MosqERajQLv6uLs+4MzrMzc1RTCVQuSOZZ+MhFjyShMZhZWUFZRVJR8vHJKXDz3tmCwaH0oLlEUtHJhv3jOu7m5mZGSLJW+uvI+pa4W5XD93d3YyNjLGfORCilrIIpUOe8JY5iiPabhxJRnMjuUNXV5cnvFDciAgTE5OE0oe3IwtnEy17vt6duTaYO+64A9Bxc+X4kn3cOc8LOL7uN2KHM2DejKcPfe4VFhYX2U2Vt87sJBQLiwueyNJ4lMHBQZelDs9MKisxMDCAiBCz525edBV98MEHEZGKLpj5HOzeEB588NWeSYQAOotrPnK4W3REnpdEHeiYLwlXSJaSKmJlCp5Z+BkcHGRyegpVZVsDCSU8FUMF+jf3xQ4P0EopVDTuufoAdiKEREJvIWGjLItiPO65CRDA+toqhMtYvkJ7LC4u0tXV1YZSVcZ5hlb8wEdbKYtiPOS55+t4xaTCt2YPtAo50tEdz1k6HOF2i/tlOuZJUTc9PU06lyKTOzxHiyT36PJ3eSqJmcPk1CQhV4xBNBulqIqe2avQjdPHbh4RzpuJHebn5j01d3CYmp5i/4ileT8db9nzfdGIuvX1dQYGBvjyXnlR95W9LcbHxjy1Muh0uM8fEXXOe8+JuoUFIqki2TLZA/dSPhYWvDcJAi2Ssnb2y0wegkHviSQ3Pp+PgYF+4na4pRdF3fj4OJcuXWTz2Qoi/3koFlXbNhuvxPz8PNm4hXLtD+mIOi/1DQAryysQypXfRsS24Hlp0raxfgYJJcp+prJ5rFjKczFUCwsLFGOJw3u/JVKoYtEz2wO4mZmZ0eb7pOs5J7VJ32tWA7AzjEZCh0QogET2WfPIgoSbsqIunUAV8p5ztVtY0IuoqfCtYSfp6DZKKc+FQ5T2jc0c1N9isUAul/acRwocxFAddcGMJPeYmJjwpMfP5NQk4dxBjEHYzoTpRVE3MjLCQH//raIuvcfCorfGY4eJiQnC2YP6my3mSeYyLYu39V6NaxJ+v5/Lly/zWDlXD6V4LLTLlatXPWVJGhoaYnhoiM3EYZfRzXiKQHe358zlziRnP3l4kpkvKsJJb06CQIu6QlFRKCpyeQh6UCQdZWBggHji4LUXue+++4lHFMkyxpmt6zAyMtz2TaaPMj8/j7Ig5ypzNgqBnoDnVl2XlpZQ+SIkysTMhLXLtpdE3fr6OlYkicqXKe++fuBeyebrUOqz4gcJq1Q0fvgzD+EINxU/mFQ4r70o6vSG3kVULFI6pnJZiomY5wQHHDxDK34wKbZielLsNVHX29vLxOQUqcitos455rVnPDAwgM/nI5M96ICz9gTZi6LOqQ9HNyCPprwZowZadITSodJiYNgOIvdSkh8HEWF+YYEtl2guWkV2k/ue7H9BL2hHMkks+/lGMsnS8VbwohF1AJcvX2YzHiWaPSySdlMJwukUly9fblPJKrOwuMhm4rD//mYiw/z8vOdWgZxA/L0joi6UUii8OQmCA1GUzUO24O0kKQ7BYJBM9uC1F3G2Btk+slWSZcHepnD33fd4tg7nXN4/uRjMzs54asEH3NkZb80oqcI5+gcGPOWyVBJs4TIp7G0LntdEnWOZUS4XTOe119ztwLXannBZ6uzXXlsEhAP3KhU5mBSrqBZJXhMcoL0ienp7UW5LXUJPij0pmhcXyJSJqUtH9DGvjck+n49gcPBQopS0/dqLos5pb0ctddH0victX6DFRa6YJVPU88pI1ruiDvSYvOtyFw1lohSV5bnETw7j4+MUrSJx2yU3bNdfI+qagGMVeCp0uAE+ab+/ePFiy8t0HIuLi2wlD4u67VSWBQ/GcziNbPeIqNu1tzPw4iQIjoi6vNDf39/mEh3PwMCBkPNqeWdnZ5mbm2XvSEhHZA/yOeWppEQOzmq721JXSPiYm/XW5AdcMX5lRB3hHMtLS54Soo67uCrjgqlCCQaCQc8lUjrY+81V5liSru5uT06CnImkcrlfOq+9OMl0XJqt6MGkzYqGD33mJUSEyckprESkdMyyRZ0XRfPCwgLp6K0p4VPRLcbHJ+jt7W1TySozPDx0SNQ5r72W5Rm0e6Df7yeWOrDcFq0i8VTEk+0NDsSFI+Yi2Qh+v9+Tohn0PGI/FaFg6T1Zt1P7peNexBnDHAtdJJs8dLzZvKhE3cbGBj6fj6eOBGY/Fd6jJ9DjuRg10JOKWCZHOq8rdNFS7CbTnlylGBgYYGgweIv75X5Kv/dimYHS3iG5AuTyqiMsdW4h51VRB/CSl7yU0I7gDpnZ29KTIy/sB3mU8fFxurr8JVGnlCIXV54cQIaHh+kfGEBFbxV1vljBc4k8ZmZmCPQEUKEy/rjhBCsry54SoaCtAz29vYfdLxNJJicnPWdlBggEAnqvuoTLGppMMjg05KnU9Q7BYJCh4WFU9GBSrKJhRMSTbQ5gemoSlYyU3luJCP0DwZbsQVUv8/PzFHIZ8kezSUZ3WFjw3kIV6DbnjqnL2O6XXowd9/v9jI2OEU0fLEokM1EsZXly0Qfcoi5S+n90ZNST/Rlo8WYpi1AmAsCu/ay92j844i1qi7loxoi6ptHb28vS4hLXXKuCAM9EQ6yvr3kyk45TcXdsa91+OkvRUp4VSDMzs4RSR90voa+317MrQY4oyuYV2bzlycH5KO4yerm8V65coZBXxFxNLrQNy8tLnqwPPp+PickJ8vacopjV2xl4cRVeRHQa9cjhDJgqV8RK5j1n6fD57GRJkcPul0opJJLSiV88hogwPT2Nih8kq5J4klmPxU+5mZychKRLhCaTnrUagF7sU7GDfURULMLY+IQnRSg4z9dV3kSUyUlvTuCdeUI6engvwExs27NziKGhIXL5g/rr5Zg60PUhlnJlk7RFh1dF3ejoKAAxOwNYLBdldGy0nUWqysGG3hEA9tMRPU579Pk6IQ8x2/0ymkvR5fe3LEzmRSXqADbObnDNtSpoKcVzsTDrHtvk1MERdbupzKH/vRaU7TAzO0s4fbha7ScVMzPTnluFd3BEXSqrE8d52fLl4LjNiIjn0n67uXTpEgBhOz+RUhDdEy5fvtLGUlVnenqGfFLXVUfceVHUgZNy/0jikagWeV6ctC0vLeGLHtkrNJPHyuQ8J0IdpqemkKQrA3Ey7dn6ADA5MYGkD56xpNJMenQCBHpvPXFtaKniUebnvLkKD3qyXkwlULY7GOkYUx4VzSVRFzvY56uQS5NLe3OLC7C3GHJnD7QtHl601AGMT4yTsK1IAHFbfHgtsZaDIzqiOVvU5aMloedFnL52P63n7fuZCONj4540wsCBaHbcL6PZJMPDIy2zhL7oRN3a2hrRTJpYVoujvVSCTD7vuVTaDqUKncoe+t+rom56eppwyipl/gEIZ4TpGW8OIHBg6XKSjHaCqHPq67lz3trX6ygTExOMjo7g5EFIRCGfV5w7d669BavC1OQUhSOizquWjtnZWax4DlV0+bfGvCvqFhcXKcZSqELx4KBtufOau6iDtszozkEVi1iptGfrA9iTybRLhKZTnotVdDMzM0MxESttayCJmCeTjjjoybpCpbQbsUrFPDuBn5ycRETIxg9CTjL2a6/OIQYHB0tCDrT7ZXd3Nz09PW0sVWXGx8eJ2UIOvC/qBgcH6fJ3EbOzgcVycU+LOqevDWd1eUOZKJNT3u1/+/r6CHR3lxKlxLKpliYse9GJuoO93yKH/vdS6m83Q0ND9PQE2EtrMbeXytq71ntz5XVqaoqCpUhkD45F0t50X3NwRFwyo4WoF4PHj/KmN72Jj3/84/zCL/xiu4tSFRFhY+Ms8bAWSTHbSH7Go5Zx0INxPqn3qsunDo55kdJqu9taZ4s6L07aStn2XHtvqmjq8GceY3JyEiud0ULUFndeFnVjY2NYqRTKslCWhZXytqibnJwEpVCpBKpYpJhMeFrUOc/SSmkhWkzFPft8A4EAo2PjZGIHWzk5r73YP4AWHfl8lmJR92PZbIJgcNCznj5jY2Nk82myeW0oiKfDiPg8mdgF9Jg8NDREIhdHKUU8F/NsWUHX4aHgIPu2NTSci3p2/gv6+Q4PDRPL6bEink8zPNK65/uiE3VOmuSbtrvHzUTs0HGvISJMTkwQTutkCOF0jrGREc+63DniLWzH1aXzinTO8vQkyBFxtmerp2PUOpHV1VXiUYVV1KLO7/d51ioD2rqoFBQykE/pNuilrQHcHIi6g7g6FcszMBj0ZMIfR7gplwumiqbw+f2enciXBH06g0qlDx/zIKVV93Ra/3Mf8yDOmKHiMVQyDihPjxeOgFOpOCqTBKU8K+oAZmemS9Y5oGS182p7c2KPHBfMbDbp2W174KA+JDN6TpnIxEpZMb3K8PAw8XyCTDFD0Sp6Nl7RYXxigoi9d2E4413LuMPwyHDJUhfPpVsqml90om5iYoKenh62bDG3mYgxMjzs6U5jYnKKUEaLulAmx7iHVylK+7bYVq9oWv/vZUudI+qcnSM6wVLXSSwvL6MsSMa1++Xs3Czd3d3tLlZFnEG6kNL/hkeGPDtAlyZmCVeylHjes4k8DkSoyz0wlmJqatKzz7g0iU+mSys/Xp5UlBN1XhYdzqq7SiVQqcShY17EWeBR6TgqHT90zItMTk6Sd6XczyZDdHcHPGudcWLnclndR2RzKQYHvTs/c377RNYRdRFGR0faV6AaGB4ZJpGPEbddML1aFxxGx0aJZuOkC1myhZyn+zOAoeFh4jnbcmtEXXMREebn5thK6M54OxlnzqNuPw4TExNEMnrSFsnmPS3qnMHYEXNRWyh5eRLk9/vp7u4mme0c98tOwrHOJGOQjvtYWvSmq7ODM0gX0vrf6Kh3B5DR0VF8fh8qfuB+6UsUmZ7y7ip8/0A/Ku5K5JHIMDfrvfg/h9IEwmWp87Ll60B0pFGZ9KFjXsQZG1QyXtpTrzNEXQKVThw65kWmpqbIxPdRSscsZuL7pVg7L1LaN9a2dORy3rbUOX1BIqMFUiIb83T/AFo4JwspknaWUc9b6sbHieTiRG1rndef79DQEMlChoJVJJ3PtjTJz4tO1IHO0Lib1pV5N5X0bBYoh9HRUaKZHEopopm8p1cphoaG6O7uKok5R9x5eZAG6OkJYIctGlHXYJyEHakEJBPe3PPNjVvUFTPCmIdFnd/v14s8tqVOKYVK5D1tGZ+engaXqCOe8Wx8D7gn8RlI65hmr2biA9eqeyYDmezhYx4kGAxqy306qTsJvD1pCwQC9Pb1oTJJ7X6Jt5/vxMQEllUkb1sVc8kwUx5ONOEIuGxOP9tcLuVpUef0D0lb1KWyMU+LfLBFXT5REnVe7s/AdhfNJojlvL+IAvbzzWVI5bOl963iRSnqpqen2UslKFgWoXTSs77lDmNjYxQsi3guTzzrbdOziDA6MkLMdr+M2dYvL1vqAHp6erATi3o2y1anMjg4SG9vD5E9KBaU59tbSdRltKjz+gAyNTkJSdtSl7NQeW/HsM5MzyB2JiWVL2Kls54WoaXfP51BpTMEh7zrjgsHAkNlMiVLnZdX4kWEoeERVCqJSuv4Sq9PMoeGhrEySawOsNQ5C6q5VASAfDri6fHYsdTlcgful16MD3Zw2lbSzs6YzMQ9LfLBER1JEnnvbuzuZmRkhLxVKG087uX2BgeiLm4nSzGirslMTk6SLRS4EY+glLeDsuGgAt+I6Qri9Q5jbHycuC3mYhkY6O/37EayDr09PThZ4Y2lrrGICJOTk9y8pt97vb319/fj8/soZqGQUZ6eEANMTkziS9qVN6HFnZcnbZOTk5CwTfl2IKuX64Tf76d/YEBbvTJZRjze/waDQb0nkm2pExFPWzoAxsZGUekUKp1iaHi4ZXs6nZSR4WFtqcumPP98nb4gmwyjlCKb9LaoK1nqsild3qy3RV0gEKC/r59kNk6ukCVXyHp+jhYMBimqIpFsuPTeyzhj8M3EDuD9OXAwGEShCGXipfetoi0pFEXk9cAvAH7gN5RS/7qV3++sXD0V1lmgvDyhgIMKfCOuV668vkoxNjbO0zf1oBzPKs8HDQMEXNY5Y6lrPO95z/fw8MMP09vby0te8pJ2F6cq2r0uSCEVo5jzvqgbHx9HJfN6Z3fbYudld+fJyUmsXB7JFVC2qPNyeQGGhodIp7OQyTEy6V1XUdD1t39ggFQuCwj9jsjzMKMjI0j4OVRXl+dFM6ATd4R3UJkUff0Dnn6+jitrLhWlkE1iFQuedm91BFw+n6ZQyKKU5XnRMTg4RCqbIG1n7PT6mOE8z/3M/qH3XsV5ntup/UPvvYrzPHdTOnlOKxclWi7qRMQP/ArwWuB54CER+ZBS6sutKoPjvvhsJHzovVdxRN1m3PuuNKBFZyKnLXXxrGJ01tvPFw4LOa9bFTuRO++8kzvvvLPdxaiZYDBIJBYrvfYyY2NjqIKF5C1IFUrHvErJSpDKQlK7YXpd1A0PDrGdiODL5Tzf/4IdqJ/Vom7I465VYI9pmTT4/IzMenuRFbQ7lWSvoXJpz/cPjoDLp6Lk7Emml/uHQCCA3+8nl0uTy+s5j7OXrFcZGh4knUiQynWGqHOe5356j66uLs/PeRz3xe2ULq/XF94dEbefbv0coh3LSy8DnlRKPa2UygG/B7y5lQVwOrRr0c7xzwXYsdNpe73DGBkZIZm1sJQimfcx4uFVQYeengOXS693cIbmMzQ4hJ1oy/OTttIELVWEdBHwdqKJg32+sjiBrF6eZII9ic/lIZv3fPwJ2GNGNgvZDIMer7+gy6uyGSSX6Zjnq3JpyKYZGvJ2eQOBAP39A+TSUfL2JNPLcx4Roa+vn1w+RS7XGaJucHCQdC5BOtcZMWqO6Ahnw/T3efvZwsEYvJcOE+wf8GzmVocDUacnEa2sv+0QdfPAddf75+1jLcOxfN2MRw+99yqlVQo7DsXrHcbIyAhKQSoHiazy/POFAyHX1eX3tCuNoTUEg4MUks5rb0+KSxO0VAGVKhDo6aGvr6+tZapGScAls6hUjkBPj+cnbcFgEMnmsbI5z9cHgODAAJLLI/nOEaFWLotKpzqivP39/RSzGW2p83C8l8PQ8DD5TIJ8xvv76oF+vrlcumNE3dDQEJl8irSd3MXrddh5npFs2PPPFg5EUjKfZqAD+l9n/HVi6l7ooq4mROS7ROSzIvLZ3d3dht57YGAAv99PupAnODBAV1dbQgtrpq+vD5/Px569qu31SYXToSWyilTO8rxlEQ5EXXeXdzfFNrQOtw+81we90qJJWlvqhoe93d5KVsRMDtI5hke8v+gTDAaxMhlUoeDppA0OwWAQyeeQXK5jygtgZdKdU15lQSrWEeUdGRkmn46XtjXw+kJrf38fuXyafIe4Xw4MDJDOpcjY2zB4fY7miI5YLub5ZwtHxuMB75fXeabhjLbctnKRtR2i7gaw6Hq/YB87hFLq15RSdyql7mx0IhMRKa2ueX1FBXR5B/r7KCqF3+/3vD+xI+JCKYVSnfGMu7u1mOsOGFFnODyJ8PqgV1p1zxQhU/T8KryTnVGlc5DJMTbiXVdRh4GBAVQuX3rtdfr7+1G5HHSIqHO3sU4orzNJKyajnu8fQGfrLGQT5LOd4R7Y399PPp8hn9feSV72PADdp6VzSTJ5banzeh12P8/ePu9n+3ZnJPf6s4XDoq63p6el3l/tEHUPARsisioiAeDbgA+1uhCO8Ah6vHNzGOjXFbm/r8/z/sTOgLGbVIfeexnHUhfoNqLOcHjQ8/qkrWQJTxeRjMXI8Ehby3McPp+P4NAgpHNIJu95EQqdJfLBFnX5PFY+3xHl7STLOLjKaFkdUd7BwUGK2SSFTJK+vv6O8E7K5zOlRCleF3UDAwNYVpF4Jqqzz3q8Trifp9efLegxo88Wdp1QXqeM2WK+5eVtectWShVE5J8CH0dvafABpdSXWl2O737Pe3jkkUc8n17doc/uJPr7vV+hHdeDkF606ghRZyx1BjedNOh1d3fT09tDNlvE3wFbMIBORBPPZpFsoSPK20n1AQ5EnfPa63SiaHbohPoQDAbJZ5Pks0nPuwaCfqaFwhb5fLb03ss49SGWCtHX1+/5hXe35atT9uXt7e0jncl4vi5Ae59vW5ZrlFIfBT7aju92uOuuu7jrrrvaWYS6cERdJ1RoR8SFUtpS1wmDSEnUdZvMl4bDHbHX3Z1Bt7FsNo/KFDpiEWV4aIgb4ZtYmVxHlLfTRN0h96oOmLS5y9gJz7fTyhsMBinkMuTTcUYGvT8e9/X1kS9kyRc6w/3SsTRHU6GOWJRwj2md0D/AQTk7obx+v5/urm7yhXzLy+vZRCmGwzidWm8HpJ91OjhH1HWCD3RJ1JlEKQY6T9QNDg5CpoiVLXZEexscHETSeVS+0BGLPp22st1pItQ83+bi9AnZxH5HZOvs7e0ln0uXYuq83geXLHXpEP0dUB9EpBRy4vVn6+D0C51SXqecvS2uD0bUdQidtkrREwgQTXeOqHNiDLpMTJ2BwwOH111pwLaGJ/IHrz1OMBhExdOl116n00RHp1mSOvn5dsIk02lj2cR+R4zHvb295As5CoUsPS1ONHESnPqQyERLXlVepyeg620n1F+Anp7OEqE9bRLN3m4phhIl1d8BAx5AX18vKT3H7Ah3BEfU+f3+NpfE4AU6bQP64EAQEnrj8U6YtA0MDKAKnVPeTnNX6jTR0WnldfcPnVDeUrbOfKYj2ltvby/FYp58PkMg0DnPt1DM09cB2STBlRyuQ8Y6vz1H64T2BgflNKLOUJZOM5V3WiC5I+o6wSpjaD6dMtA5DAwMQFaLpE5YROm0xBjufrcT6oa7vJ0wZnS7PCQ6obyd9nw7tb2lM/GOWETptBhWOJjzdEJ/5qa7Q7ypAnYdbvXzNaKuQ3A6ik5pgH127F+gu7sjrF+dUEZD6+iUgcOhk7ZggM4rb6dZZjqtvJ0smjuhvO421gmiwyljJhPriPJ2miXfTaeNdZ3Q3qB9llBvb1ZiKPGa17yGZDLJ61//+nYXpSb67K0Xenu9P6EAPL9vj6G1dNpA12mJGzrNku8emDthUtFpoqOrq4u3vvWtJBIJJicn212cY+k00dypMZbpdJzJwc5wFy33uhPolLHO6Rc6YQscgECPEXWGKpw9e5b3vve97S5GzfT2OqKuMzo4R9QppdpcEoMX6KTERNB5oq7TJpnugbkTJkGdJjoAvvM7v7PdRagZdx3ohPrQaaLDqb/ZbIKenrE2l+Z4Os0dFwA70qQT6i/A933f9/GWt7yFjY2NdhelJpw63Orna0SdoSm0K0j0pDjulyamzgCwsbHBd3/3d3PmzJl2F6UmOm3S1mnldQ/MneCq3WmWxU7DPU50wqS409qbM2/IZpMdMYfoxPbm1OFOKW9/fz/nz59vdzFqxjEUGFFneEHQqaLOYABdH77xG7+x3cWomU5bKV5cXKSru5tgMMjw8HC7i3Msneae7Z5IdFrZO41OEHWd5o7rlNFSxY4or8/nw+/3UywWO6L/dWP6h+ZQ2vvYiDrDCwGnYwv0eH9VEIyoM3Q2nSbqVlZW+MiHP9zuYtRMJzxTN+6JRCdMijuZTpgUd5o7bqf1Z9B5li8n1KQT6m8n4swpjagzvCDotC0YjKgzdDKdOAnqJAKBAL/wC7/QMc+202K+OplOmBS7x7dOEB2dFsMKgB2O3ynldURoJ9TfTqRdz9f8moam0GkbW/p8ZncPQ+fibmdmkG4OnRjPcfS1ofF0yiTeoRPG5I60NNthlh1TXhuzoN0cHEtoq5+vmckamsLU1NSh/72O6dgMnczc3BziExYWF9pdFIMHMKKudXTKJP6ee+5lemaGhQXv9xGdbGnulPIa98vWYNwvDS8I3vSmN3HfffcxMjLS7qLUhLHUGTqZpaUlPvqRj5rsrQbg8CKVWbBqDu9///vZ399nYMD7+6gBvO99P9buItRMJ2aTdOgUUedg+ofm4IzFrX6+RtQZmoKIMDbm/f1lHIyoM3Q6pg4b3Dzw4INm380mcvvtt7e7CC9YjKWu+QSDQba3t42oazImps5gaAOmYzMYDC8kfvAHfqDdRTAYTkRnirr2WGZOynve8x4+8YlPdMxerJ2KsdQZDG3AWDkMBoPBYGg/nSnqtFW8U8p79epVrl692u5ivOAxiVIMhjZgRJ3BYDAYDO3H7bLWKSKpXTFUBm/ywAMPMDMzw8rKSku/11jqDAYORJ2JQTEYDAaDoX24F1k7JTvj+fPnefTRRxkcHGx3UQwe4N577+Xee+9t+fd2RmsxGJqMM4iY7IEGg8FgMHiDThF173vf+9je3mZtba3dRTG8iOmM1mIwGAwGg8FgeFHRKaIuGAwSDAbbXQzDixwTSGQwYCx0BoPBYDB4DROjZjDUjhF1BoMLE1NnMBgMBoM36BRLncHgBYyoMxhcGIudwWAwGAzewIg6g6F2jKgzGAwGg8FgMHgO435pMNSOEXUGg4tO2RPHYDAYDIYXOkbUGQy1Y0SdwQCsrKxw9epV3vnOd7a7KAaDwWAwGDDulwZDPZjWYjCg0xH/zM/8TLuLYTAYDAaDwcZY6gyG2jGWOoPBYDAYDAaD5/D5zDTVYKgV01oMBoPBYDAYDJ7DWOoMhtoxos5gMBgMBoPB4DmMpc5gqB3TWgwGg8FgMBgMnsNY6gyG2jGizmAwGAwGg8HgOYylzmCoHdNaDAaDwWAwGAyew4g6g6F2TGsxGAwGg8FgMHgOI+oMhtoxrcVgMBgMBoPB4BlWV1cB6O3tbXNJDIbOwWw+bjAYDAaDwWDwDD/xEz/BzZs3GR8fb3dRDIaOwYg6g8FgMBgMBoNnmJqaYmpqqt3FMBg6CuN+aTAYDAaDwWAwGAwdjBF1BoPBYDAYDAaDwdDBGFFnMBgMBoPBYDAYDB2MEXUGg8FgMBgMBoPB0MEYUWcwGAwGg8FgMBgMHYwRdQaDwWAwGAwGg8HQwRhRZzAYDAaDwWAwGAwdjBF1BoPBYDAYDAaDwdDBGFFnMBgMBoPBYDAYDB2MEXUGg8FgMBgMBoPB0MEYUWcwGAwGg8FgMBgMHYwRdQaDwWAwGAwGg8HQwRhRZzAYDAaDwWAwGAwdjBF1BoPBYDAYDAaDwdDBGFFnMBgMBoPBYDAYDB2MEXUGg8FgMBgMBoPB0MEYUWcwGAwGg8FgMBgMHYwRdQaDwWAwGAwGg8HQwRhRZzAYDAaDwWAwGAwdjBF1BoPBYDAYDAaDwdDBGFFnMBgMBoPBYDAYDB2MEXUGg8FgMBgMBoPB0MGIUqrdZTgWEdkFnm3CrSeAvSbct1mY8jYXU97mYsrbXEx5m0unlRc6r8ymvM3FlLe5mPI2F1NezbJSarLcBx0h6pqFiHxWKXVnu8tRK6a8zcWUt7mY8jYXU97m0mnlhc4rsylvczHlbS6mvM3FlPd4jPulwWAwGAwGg8FgMHQwRtQZDAaDwWAwGAwGQwfzYhd1v9buAtSJKW9zMeVtLqa8zcWUt7l0Wnmh88psyttcTHmbiylvczHlPYYXdUydwWAwGAwGg8FgMHQ6L3ZLncFgMBgMBoPBYDB0NJ4XdSLywyLyJRF5REQeFpGXi8gnRaQlGWVE5D0i8u01nKdE5Ldd77tEZFdEPtzcEh4qwwdF5Jvt178hIhePOb9oP9MvisifishISwp6azlqesbH3MP5W74gIp8TkXsbVb5m4ir3l+yy/18i4rM/u1NEfvGE932fiLy3wmefPmWZv8Gu7+dPcG2iwvGfEJGvOU25jvneGRH5PRF5SkT+XkQ+KiJnG3Dfis/5hPdz6oPzb6XMOR+t1lZrafunKN8t/XED752w/58Tkf9a5bwVEfni0evq+J4HWtUvn7Zeu/82Efk6EXlcRJYbU7r6y1DlnO8Xkf4T3LuuMes0lGlbP1Dl3G84TVlO03fXeP9pEfkdEXna7s8+IyJvacB9m9I2ZpfcFwAAGIpJREFUqo1zx1z3QzWcU6pDNZblUP9hH3ufiLz3tHPLWtq7iHz9MXXPPS/7g3ralYjcLiJfV0+Z24WIjLva4paI3HC9Dxw591TtsZllK3PtLfXLPl61T2hU2+s67Q2aiYjcA7wReIlSKisiE0DVB9polFL/ocZTk8BlEelTSqWB1wI3mley6iil/rcaTksrpW4HEJHfBP4J8FPNLFc56njG1XD/LV8L/CvgVQ24b7Nxl3sK+B1gCPgxpdRngc82+guVUqcVvG8D/pf9/4+5PxCRLqVU4QRl+tFTlqkiIiLAHwG/qZT6NvvYbcA08HizvveElOrDUey/Q5RSVQftGtt+3bSqP1ZK3QRqnqR5mUbVaxF5DfCLwNcqpY7ds/Wk7fAUfD/w20Cq1gtExO9+36x666Ji2yrDNwAfBr58ki9qVt8NpX7gj9H92dvtY8vA1x85r9V1oBoVx7ljrvsh4KebW7T6EBG/UqpY7rNa2rtS6kPAh6qc4n5W/xl4D/BzNZSrC7gduBP46HHntxul1D66vIjI+4CEUurfVjj9G6izPZ6m/tdZtkPfWeWeTesT3HjdUjcL7CmlsgBKqT17wC8hIm8TkUftVY3328feIyI/4zrn3SLyy/brd4rI39mK+1edgUVEEiLyU/Yq0t+IyLR9vLQSLyL/WEQess/5Q2cFRUQ+iJ7cTADX7FWjtwG/6yrDmIj8segV7r8Rkauu+3/AXiF6WkT+meuafyEij4nI/xKR33WV43b7Ho+IyB+JyOjRB+decRKRfy8inxW9SvbjrtP6ReTHReRzwNcAl6rd377nz9v3+oqI3CUi/01EnhCRn3R99x+LXj38koh8l+v4qZ6xiPyiiHzafk7VJn1DQNi+LiginxBtvXtURN5sHx8QkY/Y3/NFEXmrffz1IvJV+/xfFHvlRI5YZOxrVqrVqXpRSu0A3wX8U9E8ICIfFhGfiFwTl3XGfubTIjJpP6eH7H+vcN3yYoV6VZdlw42IBIH7gH8EOALpARH5axH5EHanW6kO2J/9vH38EyIyaR9zr9jfZf/OX7Cf6+BJy2vzIJB3Lx4opb4AvFYOVt9uiMh/sr+/Uh/xertefEFEPuG6f9nn3AhEr/o9JiL/H/BFYNGuCxNV6vCxbd++x4+72kUtVtdb+mNgXkT+m33PN4tIWkQCItIrIk/bx9dF5GN2ffhr57tEZFW0heFROdx/lFY6ReSS67d4REQ27NP8IvLrIvIloFdE+ux6+EkR+a92G/7PIiL2fUrtGvhG13edpF++pX7Y/z5o/w6Pisj/YZ/rrtc/arfRL4rIr7nK9kkReb99z8dF5P4jdeCVwK8Db1RKPSUifyUit7s+/18icptd5t8SkU8BvyW6b/gz+7f/DRF51q43PyEi3++6/qdE5Pvs47e0B9d5ZZ+v/WzmgL8Ukb+0z32d/dt+TrS1Ieiqd++3f4dvOXJ/d72tNFas2+8fFZGflAPr7gPiWuUWkV8WkXe7nzvQ537urnP/tYh82a4D/1a0l8fXAz9jP4t1qT4m3vLbucsjIi+zn8XnRfdr5+zj7xY9fn5MdH/+b6iNVwO5I/3Zs0qpX7Lv+SER+QvgE6L7iA/Y5fu8HIx/fhH5Gbs+PiIi3330S0T3w58XkfUay1UTZca50vzM/t4P28/vX6N/s4dFixtE5Nvt8n5BRH7LddtXSm1zg5oQPeZ+UOx+ya6PPysiXwDukcpt2d3ey/axcng++iYR+Vv7Of+5HJ4TfQC4C/gxEfkBqdxPldo88BPAW+1n9lapPm+pNL90t8MJEblmvy5bZ0RkVnSf9LB9f6cNlO0Djnnut8z/pHx7rDZP/A8i8rdAre2pJuSIRVgO9z2H5j+uc9bs3/YuOdwnvEoO+trPy8EcJyhlxq+6UEp59h8QBB5Gr6b/v8Cr7OOfRK9GzAHPAZNoq+NfoBX9JPCk6z7/HT0RvQD8KdBtH/9/gW+3XyvgTfbrfwP8iP36fcB77dfjrnv+JPC99usPAgXgNuDjwFN2uR8APmyf80to6wvoTvlh1/0/DfSgReE+0I1uzA8DvcAg8ISrHI+4nsVPAP/OVY5vdj8j+/WY/b/fPn7Vfm8B32sf/xzwsWPu/0ng/fbr7wNuoid6PcDzzvNxfV8feiI63qBn/AfohYiLuH5f+/Oi/by+CkSBl9rHu4Ah+/UE8CQgwDcBv+66fth+1teBDfuc/+L6/UpltN9/EVihSp2qsY4nyhyLoK1ID7i+/xeAf2i/fjnw5/br3wHus18vAV+pVq8qfWcd5X0H8B/t158GXmqXMwmsus6rVgfeYb/+UeCX3XUXvTjyNHCXfXwI6DplP/LPgJ+v8vkI8Kj9t5T9PdF9ynXnb3T9fRWf8wnL6tTjh9HWxRV0O73bdc41+7tuqcN1tP1rHLSt/x34jRrKdkt/jG5fT9uf/1vgIeAV9me/ax//BLDhqrt/Yb/+EAf97z9x6qX9N3/Rfv1LrvoSsOvTCrq/vd0+ngfeia6HUWAB3U98Bt3vV2vX9fbLlerHS4E/c9cpd712/xb269/ioC/8JPCz9uuvw27brr8t5Pxu9rHv4KBPPgt81lXmvwf67Pe/DPyg/fr16LY3YT+/z9nHfejxyt3vjmC3B3d/Uen5uuuk/XoC+CtgwH7//wA/6jrvn7u+y/18PslBva00VnwYeJv9+j1HyvZh131/GXj3kTZQtJ/l0+h6/FZgHHgMSknjbvnd7PfVxsRbfjsO992lPgy9ePqH9ut322Vxxp5ngcXT9Gf2PZ93/c0/DbzT9bs+DgygRZXzTHvQFoRVp9zAvei6tHTSvuxIuaqNc+/GHgdcv/EDR69DLzo/zkE9c/7GD1JlblDme1ew+xfXsfcB77V/z7vRC/I/7PpcAd/qel+pLZfqDRX6WPffC4xyUPf+N+BngQQH/c+f2uVKAz9eoZ9yt/mjz/J9lJ+3VJtffpKDdjgBXLNfV6oz/5fzrNDjzCBV+oAKv4nz/KvN/9ztsdp5Hwb8jai3R8p2tAzuvqc0/7Gf7xeBc8DngdvK9Al/CrzCfh1Ej6MPUKF/reefpy11SqkEerD8LmAX+H2xV99s7gI+qZTaVdrM+p+BVyqldoGnReRuERkHzgOfAl5j3+8hEXnYfr9m3yuHrgygG8lKmSJdthX5o+jJ7SXXZwWlV//H0WLzqPn7PnTjRyn1F8C4iAzZn31EKZVVeuV7B93RvQL4E6VURikVR1cCRGQYPfD8T/va3wReWekZ2nyr6JXRz9tldnyTBT0wbtmvu2q4v+M28CjwJaXUptIr908Di/Zn/8xe0fob+5izun7aZ/zHSilLKfVl+xm5SSulbldKnUdPYP4/e5VDgJ8WkUeAPwfm7WsfRVtq3i8i9yulouh68oxS6gmlW9tvczzV6lQj+X30JAS0hez37ddfA/yy/d0fAoZcK2Ll6tVpeRvwe/br37PfA/ydUuoZ13mV6oDlKvtvo9uFm3PAplLqIQClVEw10YXIriO/DfycUurvqfx73g38lfM3KqVCrts08jk79fh2pZQTI/OsUupvypxbrg4fpVLbB/hv9v+V2uIhyvXHaDH1lIhcAF6GdhN6JXA/8Nd2XbwX+AP7ef4qeiEIdB/neDO4V93dfAb4IRH5f4BlpV3bQbfTh+3Xlqv8f6eUel4pZaEnLStUb9f19suV6sfTwJqI/JKIvB6IlflbHrRX5R9FT8zcfVul3yKPntz9I9exPwDeKCLdwHeiJxsOH3I9o/uw26pS6mPY3gtKqWvAvojcAbwO+LzS7kbl2sNRyj3fo9yNrmefsp/RdwDLrs9/v8w1R6k0VtyD/vtBL2jVwoP2yj3oyfGv2e3r99GTqAzwH0XkGynjPlrDmHhcOxpG1/8vAj/P4d/9E0qpqFIqg17lXy5zfVVE5Fdsi8VD9qE/c/VPrwN+wP4dPomexC/Zx7/dPv636HmL00dfQKdif5NS6rl6y9NEXg38gd0ej/bB1eYGR1HHHP9VtOhzh6IUgT90va/Wlt0cVzcWgI/b9/m/7fv0oedlq2hh+IvoeczHoWw/5W7ztVJ2fnkMlerMQ8A/FO2meMW+33F9QCWqzf9qPe8PVAX32CZydP4zCfwJekHyC2XO/xTwc6K9HEZcc5xa+teqeDqmDsD+cT4JfNL+Ab+jxkt/D/hWtOXmj5RSyh6wflMp9YNlzs/bAz7oBlzu2XwQ+Aal1BdscfmAu6j2/x9CD/q/i670tZB1va703SdCRFbRqwx3KaXCol1Fe+2PFXpFPYWuZLU0OqesFofLbaFF4QNooXGPUiolIp90fd9pn7H7+yqapZVSnxEd7zOJXj2dRK8650W7EvQqpR4XkZfYn/+kaHe6an7uBQ67Kzt/U7U6VTcisoZ+NjvowdXhM8AZ0e6K34BencIu0932pMB9H2hwvRKRMfQAdkVEFHpVTgEfQa9UOec9QOU6cJRKA2wj+RKVY7TeBzyvlPpP9vuyv6eIvKnK/ZvWfm2S5Q6Wq8NKqZ9wPj+m7bvLXXOZK/THfwX8A7QA+XN0G/ajJyk+IKIqxzJV/f2VUr9jT8jfAHxUtMvP0xx+5rjK38jfoty9KrZ30XGaX4uekH0rWnA5n/WirXp3KqWu2xOgWn4Ly77XJ0Tkh5RSP223qT8D3mx/9lLX+WXrShl+A72qPwN8wHX8fRxuD0ep5fkKWli8rcxntZaxlrHCTdn+2f3cga+g3VhLz10pVRCRl6HF+TcD/xTdx9XDce3oXwJ/qZR6i2jXt0+Wubba9Uf5EtpKD4BS6p/Y450Tr+N+vgJ8k1LqMfcN7LnQ9yqlPn7k+APAJvoZ3YH2xmk4R8a5SmNrPdQ0N7DZR1vI3IwBzqT802jR9rOucTXjCIUa2nK5clX6bX8JvYDyIfvZvw+98PAfcMVxucbbclRrTyd5tu5r3OeXrTN2+V6J7qM/KCI/h15AqtYHVOKDVJ7/1XperX1gvZSei+gkP+548qPfGUV7Ed5HmThApdS/FpGPoMfuT4nOAwENGL88bakTkXNyEEMBOnDRHST+d8CrRPv9+tFWA2c17Y/Qg57bsvAJ4JtFB+o68RT1rIwNApv2Cuk7KpzzAbS/+6NHjv+1c43dePeUUuVWcx0+BbxJdGxKEJ2gAHs1PiwHcRfv4uBvLscQusJFRftr/4OjJyilUmjXqUX73Hruf5RhIGxPPM6jV2zqoZZnXBX7e/3oznsY2LEF3YPYwlVE5oCUUuq3gZ8BXoJeAFiRgxgCd4d0zT4HeyK9ah8/bZ1yl3sS3Zn/smtCA4D9/o/QlpCvOCvrwP9Au9A697j9JN9dI98M/JZSalkptaKUWkQPhPcfOa9aHfBxILDejk644uYxYFZE7gIQkUGpEnxcI38B9Mjh+M6rIvIv0OLTHQdX6ff8G3Tcxqpz/JRlOjUV6rCbY9t+nd9XqT/+a3SijM8o7SUxjra4ftHu454RkW+x7yG2+AHdx32b/bpsW7cnf08rpX4RvfJ59QRFr9au6+2Xy9YPe1LtU0r9IfAj3PpbOJOjPbs/rznux+6f3wC8Q0Qci91voFfwH1JKhStc+im06ENEXsfhiewfoT0a7sK2ANgLF0fbQ63E0X036LbyChE5Y993QBqQadZ1b0fQfJvr+LPo2NYe0bHHr7GPl567/f+h527/FsNKqY8C/wc6hAJcf88JxtyjDHOQNO3ddVxXib9Ax5F+j+tYpQyJHwe+1xZxiLbOOse/xx5nEZGzIjJgfxZB17d/ZbeJhlJmnLsG3C46jm0RbfF3yDtlRP/d3yLa++rEfbDtcbApIq923ef1HIxF/xHtafVfKow9J27LZXDXjWoGixR6Mfe4fsrdDqHyvKXs/NJ1jbNQ5P7bytYZe3zcVkr9Orpfegkn7wMqzf+O/l2nnieegGscPJevR7vjVyIHvAVt2Xz70Q9FZF0p9ahS6v1oS2fdmcQr4XVLXRD4JbuTLqDjob4L+K8ASqlN0alh/xK9ivARpdSf2J+FReQrwEWl1N/Zx74sIj8C/A9baefRsRzHZhOz+Rdos/Ou/f8tCRyUUs+LSL7Mte8DPiDaDTDFMRZHpdRDogMvHwG20a5WjnvVdwD/QXRw6NPAP6xyny+IyOfRE5vr6MZcjsfQvtxvq+f+ZfgY8B772T+Gbtz1cOwzrkCfaDM/6LrwHUqpougA6z8VbVX4LPo5AFxBB95a6HrwPUqpjD3x/4iIpNATPuf7/xDdQL9kl+txaEidcsrdja7jv0XlTFe/j+4A3u069s+AX7HrVRfaavKeGr+7Xt4GvP/IsT8Evgcdl+NQrQ4kgZfZz2yHA5dSAJRSOdEJP35JRPrQq5Zfg66bJ8K20r8F+Hei3fgy6A66H+2O+3f2nOdDSqkfLfd7KqX+xq4b/80+voPOcNtObqnD7g/raPu1Uqk/TqJdnv7KPu8RYMa1MPEO4N/bz7Ubvcj2BXRc7u/Yv8mfVPjObwXeZfepW+gYoaEK55blmHb9Purrlyu19zTwn+QgTfsPHrkuIiK/jo612EK343r+hpBot86/EpFde2U/BlSyqAH8OPC7IvIutKV/Cz05ctrZX6KtqI6r0v9JmfZQYxF/DfiYiNxUSj0oevX8d0Wkx/78R2hMptnvB35bRH4Y3c9E7b/nuoj8F/TzfQbtbnz0uQ+gXX/fIyLfYF//C8CfiLa+CPoZgK6jvy7aPeqbOd2Y+G+A37TrzUdO+HeXsPuzbwB+XkT+OXqsTKLjlvqOnP4vgX8HPGLXzWfQE/jfwI6ttAXfLrZosL9jW0TeCPx3EflOpdTfcjqqjXOfssv1ZbQ19XOu637NLvvnlFLvEJGfAv6niBTRv/G7T1ieb0ePm04ZflzpJEQAKKV+TrTb7W+JyCHRcNq2fIT3oV1zw2jRulrhvB20h8xx/dRfcuBu+6+oPG+pNr/8t2hB+10crq+V6swDwP9t99EJdJz07gn7gErzv6Pt8aTzxNPw6+i+4gvovqOqRVAplbTb0J+JTqriFuHfL9rIYKEt7/8d7Vp+akQdNggYPISIBJVSCXsg+Svgu5RSnzvuOkNjsFfE3quUeuMxpxoMBkPLEG2l/SRwXun4i3Ln9ABF28XwHuDfq4NU6T705PlblFJPtKbUp8ceC9O2sPk2dNKUN7e7XAZDp2Hmly9MvG6pe7Hza6I3XOxFx3GYBmcwGAwvYkTk29H7if6flQSdzRJ6xd2Hdgf6x/b1F9FJSP6okwSdzUvRiaEE7Sb4ndVPNxgMFTDzyxcgxlJnMBgMBoPBYDAYDB2MpxOlGAwGg8FgMBgMBoOhOkbUGQwGg8FgMBgMBkMHY0SdwWAwGAwGg8FgMHQwRtQZDAaD4QWDnT7aYDAYDIYXFUbUGQwGg8FgMBgMBkMHY0SdwWAwGF5wiEhQRD4hIp8TkUdF5M328RUR+YqI/LqIfElE/oe90T0icpeIPCIiD4vIz4jIF+3j7xaRX3bd+8P2PpaIyL8Xkc/a9/px1zlfJyJfFZG/F5FfFJEP28cHROQDIvJ3IvJ5p1wGg8FgMJwGI+oMBoPB8EIkA7xFKfUS4EHgZ+39zQA2gF9RSl1C73f2Tfbx/wR8t71Jd7HG7/lhpdSdwFXgVSJyVUR6gV8F/oFS6qXApPt84C+UUi+zy/UzIjJw0j/SYDAYDAYwos5gMBgML0wE+GkReQT4c2AemLY/e0Yp9bD9+u+BFREZAQaVUp+xj/9Ojd/zrSLyOeDzwCXgInAeeFop9Yx9zu+6zn8d8AMi8jDwSfTmv0t1/WUGg8FgMByhq90FMBgMBoOhCbwDbSF7qVIqLyLX0AIKIOs6rwj0HXOvAocXQXsBRGQVeC9wl1IqLCIfdH1HJQT4JqXUY7X8EQaDwWAw1IKx1BkMBoPhhcgwsGMLugeB5WonK6UiQFxEXm4f+jbXx9eA20XEJyKLwMvs40NAEoiKyDTwD+zjjwFrIrJiv3+r614fB77XcQUVkTtO8LcZDAaDwXAIY6kzGAwGwwuR/wz8qYg8CnwW+GoN1/wj4NdFxAL+JxC1j38KeAb4MvAV4HMASqkviMjn7Xtft89DKZUWkf8d+JiIJIGHXN/xL4F/BzwiIj77vm88xd9pMBgMBgOilGp3GQwGg8FgaDsiElRKJezXPwDMKqW+7zT3si1yvwI8oZT6+QYW12AwGAyGEsb90mAwGAwGzRvs7Qy+CNwP/OQp7vWP7WQoX0K7gv5qA8pnMBgMBkNZjKXOYDAYDAaDwWAwGDoYY6kzGAwGg8FgMBgMhg7GiDqDwWAwGAwGg8Fg6GCMqDMYDAaDwWAwGAyGDsaIOoPBYDAYDAaDwWDoYIyoMxgMBoPBYDAYDIYOxog6g8FgMBgMBoPBYOhg/n9XyrPIUd5V2AAAAABJRU5ErkJggg=="},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":56,"source":["fig, ax = plt.subplots(figsize=(15,10))\n","sns.violinplot(x=\"language\",y=\"wl\",data=main_data_lang.loc[main_data_lang['language'].isin(medium_lang),:],bw=1, ax=ax)\n","ax.tick_params(axis='x', rotation=30)\n","# plt.savefig('plots/violin/medium_resource.pdf')\n","# plt.savefig('plots/violin/medium_resource.png')"],"outputs":[{"output_type":"display_data","data":{"text/plain":["
"],"image/svg+xml":"\n\n\n \n \n \n \n 2021-08-20T11:06:40.460560\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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"},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":57,"source":["fig, ax = plt.subplots(figsize=(15,10))\n","sns.violinplot(x=\"language\",y=\"wl\",data=main_data_lang.loc[main_data_lang['language'].isin(medium_lang),:],bw=1, ax=ax)\n","ax.tick_params(axis='x', rotation=30)\n","plt.savefig('plots/violin/medium_resource.pdf')\n","plt.savefig('plots/violin/medium_resource.png')"],"outputs":[{"output_type":"display_data","data":{"text/plain":["
"],"image/svg+xml":"\n\n\n \n \n \n \n 2021-08-20T11:07:01.257275\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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"},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":58,"source":["fig, ax = plt.subplots(figsize=(15,10))\n","sns.violinplot(x=\"language\",y=\"wl\",data=main_data_lang.loc[main_data_lang['language'].isin(high_lang),:],bw=1, ax=ax)\n","ax.tick_params(axis='x', rotation=30)\n","plt.savefig('plots/violin/high_resource.pdf')\n","plt.savefig('plots/violin/high_resource.png')"],"outputs":[{"output_type":"display_data","data":{"text/plain":["
"],"image/svg+xml":"\n\n\n \n \n \n \n 2021-08-20T11:07:29.248403\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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"},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":59,"source":["fig, ax = plt.subplots(figsize=(15,10))\n","sns.violinplot(x=\"language\",y=\"wl\",data=main_data_lang.loc[main_data_lang['language'].isin(low_lang),:],bw=1, ax=ax)\n","ax.tick_params(axis='x', rotation=30)\n","plt.savefig('plots/violin/low_resource.pdf')\n","plt.savefig('plots/violin/low_resource.png')"],"outputs":[{"output_type":"display_data","data":{"text/plain":["
"],"image/svg+xml":"\n\n\n \n \n \n \n 2021-08-20T11:07:57.051991\n image/svg+xml\n \n \n Matplotlib v3.4.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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"},"metadata":{"needs_background":"light"}}],"metadata":{}}],"nbformat":4,"nbformat_minor":2,"metadata":{"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":3},"orig_nbformat":4}} \ No newline at end of file diff --git a/eda/stackedplot.py b/eda/stackedplot.py new file mode 100644 index 0000000..1578fef --- /dev/null +++ b/eda/stackedplot.py @@ -0,0 +1,168 @@ +#%% + +import matplotlib.pyplot as plt +import seaborn as sns +import pickle +import pandas as pd +import numpy as np + +from pathlib import Path +import collections +from collections import Counter + +from tqdm import tqdm + +# import plotly.express as px + +base = Path("/mnt/disks/std750") + +# data = pd.read_csv(base / "data" / "csvs" / "new4.csv") +main_data = pd.read_csv(base / "data" / "csvs" / "final-v2.csv") +main_data = main_data[main_data["counts"] >= 5] + +# %% +def stacked_audio_vs_wl(main_data): + languages = main_data['language'].unique() + main_data['wl'] = main_data['word'].str.len() + wordlengths_counts = dict(main_data[['counts','wl']].groupby('wl').sum().reset_index().values.tolist()) + language_fractions = {} + for l in tqdm(languages): + language_fractions[l] = dict(main_data[main_data['language']==l].groupby('wl')['counts'].sum().reset_index().values) + + + for l in tqdm(language_fractions): + for j in wordlengths_counts: + if j not in language_fractions[l]: + language_fractions[l][j] = 0 + + language_fractions_df = pd.DataFrame(language_fractions) + language_fractions_df = language_fractions_df.rename(iso_code_to_name, axis=1) + wl15 = [3,4,5,6,7,8,9,10,11,12,13,14,15] + + language_fractions_df_T = language_fractions_df.transpose()[wl15] + + language_fractions_df_T.nsmallest(50,3).nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel="Number of Audio Clips", xlabel='Word Length', title='Number of Audio Clips by Word Length (1 to 15) for top (1 to 10) languages', colormap='tab20')#, logy=True) + # plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small') + + # plt.savefig('plots/stacked/audio_clips_by_word_length_vs_word_length_top1-10.png') + # plt.savefig('plots/stacked/audio_clips_by_word_length_vs_word_length_top1-10.pdf') + + language_fractions_df_T.nsmallest(40,3).nlargest(20, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel="Number of Audio Clips", xlabel='Word Length', title='Number of Audio Clips by Word Length (1 to 15) for top (11 to 20) languages', colormap='tab20') + # plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small') + + # plt.savefig('plots/stacked/audio_clips_by_word_length_vs_word_length_top11-20.png') + # plt.savefig('plots/stacked/audio_clips_by_word_length_vs_word_length_top11-20.pdf') + + language_fractions_df_T.nsmallest(20,3).nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel="Number of Audio Clips", xlabel='Word Length', title='Number of Audio Clips by Word Length (1 to 15) for top (21 to 30) languages', colormap='tab20') + # plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small') + + # plt.savefig('plots/stacked/audio_clips_by_word_length_vs_word_length_top21-30.png') + # plt.savefig('plots/stacked/audio_clips_by_word_length_vs_word_length_top21-30.pdf') + + # language_fractions_df_T.nsmallest(20,3).nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel="Number of Audio Clips", xlabel='Word Length', title='Number of Audio Clips by Word Length (1 to 15) for top (31 to 40) languages', logy=True) + # plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small') + + # plt.savefig('plots/stacked/audio_clips_by_word_length_vs_word_length_top31-40.png') + # plt.savefig('plots/stacked/audio_clips_by_word_length_vs_word_length_top31-40.pdf') + + language_fractions_df_T.nsmallest(10,3).nlargest(10, 3).transpose().plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel="Number of Audio Clips", xlabel='Word Length', title='Number of Audio Clips by Word Length (1 to 15) for top (41 to 50) languages', logy=True) + # plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize='small') + + # plt.savefig('plots/stacked/audio_clips_by_word_length_vs_word_length_top51-50.png') + # plt.savefig('plots/stacked/audio_clips_by_word_length_vs_word_length_top51-50.pdf') + + +#%% +iso_code_to_name = {'ab':'Abkhaz', + 'ar':'Arabic', + 'as':'Assamese', + 'br':'Breton', + 'cnh':'Hakha Chin', + 'ca':'Catalan', + 'cs':'Czech', + 'cv':'Chuvash', + 'cy':'Welsh', + 'de':'German', + 'dv':'Divehi', + 'el':'Greek', + 'en':'English', + 'es':'Spanish', + 'eo':'Esperanto', + 'eu':'Basque', + 'et':'Estonian', + 'fa':'Persian', + 'fr':'French', + 'fy-NL':'Frisian', + 'ga-IE':'Irish', + 'ia':'Interlingua', + 'id':'Indonesian', + 'it':'Italian', + 'ja':'Japanese', + 'ka':'Georgian', + 'ky':'Kyrgyz', + 'lv':'Latvian', + 'mn':'Mongolian', + 'mt':'Maltese', + 'nl':'Dutch', + 'or':'Oriya', + 'pa-IN':'Punjabi', + 'pl':'Polish', + 'pt':'Portuguese', + 'rm-sursilv':'Sursilvan', + 'rm-vallader':'Vallader', + 'ro':'Romanian', + 'ru':'Russian', + 'rw':'Kinyarwanda', + 'sah':'Sakha', + 'sl':'Slovenian', + 'sv-SE':'Swedish', + 'ta':'Tamil', + 'tr':'Turkish', + 'tt':'Tatar', + 'uk':'Ukrainian', + 'vi':'Vietnamese', + 'zh-CN':'Chinese', + 'zh-TW':'Chinese'} + +low = ["mt","br","rm-sursilv","sl","sah","lv","cv","ga-IE","ka","cnh","ha","rm-vallader","vi","as","gn","ab","or"] +medium = ["eu","nl","pt","tt","cs","uk","et","tr","mn","ky","ar","fy-NL","sv-SE","id","el","ro","ia","sk","zh-CN","dv"] +high = ["de","en","fr","ca","rw",'es',"ru","it","pl","fa","eo","cy","ta"] + +iso_code_to_name['gn'] = "Gaurian" +iso_code_to_name['ha'] = "Hausa" +iso_code_to_name['sk'] = "Slovak" + + +# stacked_audio_vs_wl(main_data) + +def stacked_audio_vs_wl_new(main_data): + languages = main_data['language'].unique() + main_data['wl'] = main_data['word'].str.len() + wordlengths_counts = dict(main_data[['counts','wl']].groupby('wl').sum().reset_index().values.tolist()) + language_fractions = {} + for l in tqdm(languages): + language_fractions[l] = dict(main_data[main_data['language']==l].groupby('wl')['counts'].sum().reset_index().values) + + + for l in tqdm(language_fractions): + for j in wordlengths_counts: + if j not in language_fractions[l]: + language_fractions[l][j] = 0 + + language_fractions_df = pd.DataFrame(language_fractions) + language_fractions_df = language_fractions_df.rename(iso_code_to_name, axis=1) + wl15 = [3,4,5,6,7,8,9,10] + + high_lang = [iso_code_to_name[i] for i in high] + low_lang = [iso_code_to_name[i] for i in low] + medium_lang = [iso_code_to_name[i] for i in medium] + + language_fractions_df_T = language_fractions_df.transpose()[wl15] + + language_fractions_df_T.transpose()[low_lang].plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel="Number of Audio Clips", xlabel='Word Length', colormap='tab20') + language_fractions_df_T.transpose()[medium_lang].plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel="Number of Audio Clips", xlabel='Word Length', colormap='tab20') + language_fractions_df_T.transpose()[high_lang].plot(use_index=True,kind='bar',stacked=True, figsize=(10,10), ylabel="Number of Audio Clips", xlabel='Word Length', colormap='tab20') + + +stacked_audio_vs_wl_new(main_data) +# %% \ No newline at end of file diff --git a/eda/to_csv.py b/eda/to_csv.py new file mode 100644 index 0000000..2656c67 --- /dev/null +++ b/eda/to_csv.py @@ -0,0 +1,57 @@ +import matplotlib.pyplot as plt +import seaborn as sns +import pickle +import pandas as pd +import numpy as np +import argparse +from argparse import ArgumentParser + +import pathlib +from pathlib import Path + +import collections +from collections import Counter +from tqdm import tqdm + +def main(): + """ + Create argument parser + """ + parser = ArgumentParser() + # An argument of type string that takes directory name as input + parser.add_argument("--output_file", type=str, help="output file") + # An argument of type filename that takes as input string to tell which file to read + parser.add_argument("--input_file", type=str, help="input file") + # argument for output directory + parser.add_argument("--output_dir", type=str, help="output directory") + # argument for input directory + parser.add_argument("--input_dir", type=str, help="input directory") + args = parser.parse_args() + return args + +def get_paths(args): + input_file = Path(args.input_dir) / args.input_file + output_file = Path(args.output_dir) / args.output_file + print(input_file, output_file) + return input_file, output_file + +if __name__ == "__main__": + args = main() + # Read the file + input_file, output_file = get_paths(args) + + stats = pickle.load(open(input_file,'rb')) + + data =[] + for l in tqdm(stats): + counts = stats[l] + counts = Counter(counts).most_common(50000) + datat = [(i, counts[i][0], counts[i][1], l) for i in range(len(counts))] + data.extend(datat) + + df = pd.DataFrame(data, columns=['index','word','counts','language']) + + # Save file + df.to_csv(output_file, index=False) + + diff --git a/eda/violinplot.py b/eda/violinplot.py new file mode 100644 index 0000000..e67da1f --- /dev/null +++ b/eda/violinplot.py @@ -0,0 +1,235 @@ +# To add a new cell, type '# %%' +# To add a new markdown cell, type '# %% [markdown]' +# %% +import matplotlib.pyplot as plt +import seaborn as sns +import pickle +import pandas as pd +import numpy as np +from pathlib import Path +import collections +from collections import Counter +from tqdm import tqdm +# import plotly.express as px +base = Path("/mnt/disks/std750") + +# %% +iso_code_to_name = {'ab':'Abkhaz', +'ar':'Arabic', +'as':'Assamese', +'br':'Breton', +'cnh':'Hakha Chin', +'ca':'Catalan', +'cs':'Czech', +'cv':'Chuvash', +'cy':'Welsh', +'de':'German', +'dv':'Divehi', +'el':'Greek', +'en':'English', +'es':'Spanish', +'eo':'Esperanto', +'eu':'Basque', +'et':'Estonian', +'fa':'Persian', +'fr':'French', +'fy-NL':'Frisian', +'ga-IE':'Irish', +'ia':'Interlingua', +'id':'Indonesian', +'it':'Italian', +'ja':'Japanese', +'ka':'Georgian', +'ky':'Kyrgyz', +'lv':'Latvian', +'mn':'Mongolian', +'mt':'Maltese', +'nl':'Dutch', +'or':'Oriya', +'pa-IN':'Punjabi', +'pl':'Polish', +'pt':'Portuguese', +'rm-sursilv':'Sursilvan', +'rm-vallader':'Vallader', +'ro':'Romanian', +'ru':'Russian', +'rw':'Kinyarwanda', +'sah':'Sakha', +'sl':'Slovenian', +'sv-SE':'Swedish', +'ta':'Tamil', +'tr':'Turkish', +'tt':'Tatar', +'uk':'Ukrainian', +'vi':'Vietnamese', +'zh-CN':'Chinese'} + +# %% +main_data = pd.read_csv(base / "data" / "csvs" / "final-v2.csv") +main_data = main_data[main_data["counts"] >= 5] + +# %% +languages = main_data['language'].unique() +main_data['wl'] = main_data['word'].str.len() +wordlengths_counts = dict(main_data[['counts','wl']].groupby('wl').sum().reset_index().values.tolist()) +language_fractions = {} +for l in tqdm(languages): + language_fractions[l] = dict(main_data[main_data['language']==l].groupby('wl')['counts'].sum().reset_index().values) + +for l in tqdm(language_fractions): + for j in wordlengths_counts: + if j not in language_fractions[l]: + language_fractions[l][j] = 0 +language_fractions_df = pd.DataFrame(language_fractions) +language_fractions_df = language_fractions_df.rename(iso_code_to_name, axis=1) + + +# %% +low = ["mt","br","rm-sursilv","sl","sah","lv","cv","ga-IE","ka","cnh","ha","rm-vallader","vi","as","gn","ab","or"] +medium = ["eu","nl","pt","tt","cs","uk","et","tr","mn","ky","ar","fy-NL","sv-SE","id","el","ro","ia","sk","zh-CN","dv"] +high = ["de","en","fr","ca","rw",'es',"ru","it","pl","fa","eo","cy","ta"] + + +# %% +iso_code_to_name['gn'] = "Gaurian" +iso_code_to_name['ha'] = "Hausa" +iso_code_to_name['sk'] = "Slovak" +high_lang = [iso_code_to_name[i] for i in high] +low_lang = [iso_code_to_name[i] for i in low] +main_data_lang = main_data.replace({'language':iso_code_to_name}) + + +# %% +medium_lang = [iso_code_to_name[i] for i in medium] + + +# %% +## Unique keywords + +fig, ax = plt.subplots(figsize=(15,10)) +sns.violinplot(x="language",y="wl",data=main_data_lang.loc[main_data_lang['language'].isin(low_lang),:],bw=1, ax=ax) +ax.tick_params(axis='x', rotation=30) + + +# %% +## Unique keywords + +fig, ax = plt.subplots(figsize=(15,10)) +sns.violinplot(x="language",y="wl",data=main_data_lang.loc[main_data_lang['language'].isin(low_lang),:],bw=1, ax=ax) +ax.axhline(3) +ax.tick_params(axis='x', rotation=30) + + +# %% +## Unique keywords + +fig, ax = plt.subplots(figsize=(15,10)) +sns.violinplot(x="language",y="wl",data=main_data_lang.loc[main_data_lang['language'].isin(low_lang),:],bw=1, ax=ax) +ax.axhline(3, c='red',ls=':') +ax.tick_params(axis='x', rotation=30) + + +# %% +## Unique keywords + +fig, ax = plt.subplots(figsize=(15,10)) +sns.violinplot(x="language",y="wl",data=main_data_lang.loc[main_data_lang['language'].isin(low_lang),:],bw=1, ax=ax) +ax.axhline(3, c='red',ls='-') +ax.tick_params(axis='x', rotation=30) + + +# %% +## Unique keywords + +fig, ax = plt.subplots(figsize=(15,10)) +sns.violinplot(x="language",y="wl",data=main_data_lang.loc[main_data_lang['language'].isin(low_lang),:],bw=1, ax=ax) +ax.axhline(3, c='red',ls='--') +ax.tick_params(axis='x', rotation=30) + + +# %% +languages = main_data_lang['language'].unique() +from tqdm import tqdm +data = [] +for l in tqdm(languages): + tdf = main_data_lang[main_data_lang['language']==l] + tdd = dict(tdf[['counts','wl']].groupby('wl').sum().reset_index().values.astype(int)) + for w in tdd: + data.extend([[l, w] for i in range(tdd[w])]) + + +# %% + + + +# %% +len(data) + + +# %% +data[0] + + +# %% +data = pd.DataFrame(data, columns=['Languages','Word Lengths']) + + +# %% + + + +# %% +# Extractions + +fig, ax = plt.subplots(figsize=(15,10)) +sns.violinplot(x="Languages",y="Word Lengths",data=data.loc[data['Languages'].isin(low_lang),:],bw=1, ax=ax) +ax.axhline(3, c='red',ls='--') +ax.tick_params(axis='x', rotation=30) + + +# %% +import matplotlib +matplotlib.rcParams.update({'font.size': 15}) + + +# %% +# Extractions + +fig, ax = plt.subplots(figsize=(15,10)) +sns.violinplot(x="Languages",y="Word Lengths",data=data.loc[data['Languages'].isin(low_lang),:],bw=1, ax=ax) +ax.axhline(3, c='red',ls='--') +ax.tick_params(axis='x', rotation=30) + + +# %% +# Extractions + + +fig, ax = plt.subplots(figsize=(15,10)) +sns.violinplot(x="Languages",y="Word Lengths",data=data.loc[data['Languages'].isin(low_lang),:],bw=1, ax=ax) +ax.axhline(3, c='red',ls='--') +ax.tick_params(axis='x', rotation=30) + + +# %% +# Extractions + +fig, ax = plt.subplots(figsize=(15,10)) +sns.violinplot(x="Languages",y="Word Lengths",data=data.loc[data['Languages'].isin(medium_lang),:],bw=1, ax=ax) +ax.axhline(3, c='red',ls='--') +ax.tick_params(axis='x', rotation=30) + + +# %% +# Extractions + +fig, ax = plt.subplots(figsize=(15,10)) +sns.violinplot(x="Languages",y="Word Lengths",data=data.loc[data['Languages'].isin(high_lang),:],bw=1, ax=ax) +ax.axhline(3, c='red',ls='--') +ax.tick_params(axis='x', rotation=30) + + +# %% + + + diff --git a/eda/wordcounts.py b/eda/wordcounts.py new file mode 100644 index 0000000..0e4a96e --- /dev/null +++ b/eda/wordcounts.py @@ -0,0 +1,105 @@ +import numpy as np +import os +import glob +import pandas as pd +import matplotlib.pyplot as plt +import subprocess +import seaborn as sns +import nltk +from typing import Set, List, Dict +import functools +from collections import Counter +import csv +import pathlib +import stopwordsiso as stopwords +import textgrid +import sox + +from tqdm import tqdm + +def wordcounts(csvpath, isocode, filter_stopwords=True, wordlength=5): + all_frequencies = Counter() + if filter_stopwords: + frequencies_without_stopwords = Counter() + stops = stopwords.stopwords(isocode) + if not stops: + stops = set() + #raise ValueError(f"unknown isocode for {isocode}") + else: + frequencies_without_stopwords = None + + with open(csvpath, 'r') as fh: + reader = csv.reader(fh) + for ix,row in enumerate(reader): + if ix == 0: + continue # skips header + words = row[2].split() + for w in words: + if len(w) >= wordlength: + all_frequencies[w] += 1 + if filter_stopwords and not w in stops: + frequencies_without_stopwords[w] += 1 + + return frequencies_without_stopwords + +#freqs = wordcounts("/mnt/disks/std750/common-voice-forced-alignments/en/validated.csv", isocode='en') + +langs = """common-voice-forced-alignments/ab/validated.csv +common-voice-forced-alignments/ar/validated.csv +common-voice-forced-alignments/as/validated.csv +common-voice-forced-alignments/br/validated.csv +common-voice-forced-alignments/ca/validated.csv +common-voice-forced-alignments/cnh/validated.csv +common-voice-forced-alignments/cs/validated.csv +common-voice-forced-alignments/cv/validated.csv +common-voice-forced-alignments/cy/validated.csv +common-voice-forced-alignments/de/validated.csv +common-voice-forced-alignments/dv/validated.csv +common-voice-forced-alignments/el/validated.csv +common-voice-forced-alignments/en/validated.csv +common-voice-forced-alignments/eo/validated.csv +common-voice-forced-alignments/es/validated.csv +common-voice-forced-alignments/et/validated.csv +common-voice-forced-alignments/eu/validated.csv +common-voice-forced-alignments/fa/validated.csv +common-voice-forced-alignments/fr/validated.csv +common-voice-forced-alignments/fy-NL/validated.csv +common-voice-forced-alignments/ga-IE/validated.csv +common-voice-forced-alignments/ia/validated.csv +common-voice-forced-alignments/id/validated.csv +common-voice-forced-alignments/it/validated.csv +common-voice-forced-alignments/ja/validated.csv +common-voice-forced-alignments/ka/validated.csv +common-voice-forced-alignments/ky/validated.csv +common-voice-forced-alignments/lv/validated.csv +common-voice-forced-alignments/mn/validated.csv +common-voice-forced-alignments/mt/validated.csv +common-voice-forced-alignments/nl/validated.csv +common-voice-forced-alignments/or/validated.csv +common-voice-forced-alignments/pa-IN/validated.csv +common-voice-forced-alignments/pl/validated.csv +common-voice-forced-alignments/pt/validated.csv +common-voice-forced-alignments/rm-sursilv/validated.csv +common-voice-forced-alignments/rm-vallader/validated.csv +common-voice-forced-alignments/ro/validated.csv +common-voice-forced-alignments/ru/validated.csv +common-voice-forced-alignments/rw/validated.csv +common-voice-forced-alignments/sah/validated.csv +common-voice-forced-alignments/sl/validated.csv +common-voice-forced-alignments/sv-SE/validated.csv +common-voice-forced-alignments/ta/validated.csv +common-voice-forced-alignments/tr/validated.csv +common-voice-forced-alignments/tt/validated.csv +common-voice-forced-alignments/uk/validated.csv +common-voice-forced-alignments/vi/validated.csv +common-voice-forced-alignments/zh-CN/validated.csv +common-voice-forced-alignments/zh-HK/validated.csv +common-voice-forced-alignments/zh-TW/validated.csv""".split('\n') + +lang_to_c = {} +for l in tqdm(langs): + words = wordcounts("/mnt/disks/std750/data/" + l, isocode=l.split('/')[1]) + lang_to_c[l.split('/')[1]] = words + +import pickle +pickle.dump(lang_to_c, open('common_voice_stats.p','wb')) diff --git a/embedding/word_extraction.py b/embedding/word_extraction.py index bff1982..5cc56cc 100644 --- a/embedding/word_extraction.py +++ b/embedding/word_extraction.py @@ -18,6 +18,7 @@ import multiprocessing import functools +from tqdm import tqdm def wordcounts(csvpath, skip_header=True, transcript_column=2): """count the frequencies of all words in a csv produced by @@ -53,6 +54,24 @@ def generate_filemap( filemap[mp3name] = os.path.join(root, textgrid) return filemap +def generate_new_filemap( + lang_isocode="en", + alignment_basedir="/home/mark/tinyspeech_harvard/common-voice-forced-alignments/", +): + """generate a filepath map from mp3 filename to textgrid""" + filemap = {} + for root, dirs, files in os.walk( + pathlib.Path(alignment_basedir) / lang_isocode + ): + if not files: + continue # this is the top level dir + for textgrid in files: + mp3name = os.path.splitext(textgrid)[0] + if mp3name in filemap: + raise ValueError(f"{mp3name} already present in filemap") + filemap[mp3name] = os.path.join(root, textgrid) + return filemap + def _extract_timings(words_to_search_for, mp3_to_textgrid, timings, notfound, row): # find words in common_words set from each row of csv @@ -79,6 +98,36 @@ def _extract_timings(words_to_search_for, mp3_to_textgrid, timings, notfound, ro end_s = interval.maxTime timings[word].append((mp3name_no_extension, start_s, end_s)) +def _extract_new_timings(words_to_search_for, mp3_to_textgrid, timings, notfound, row): + # find words in common_words set from each row of csv + mp3name_no_extension = os.path.splitext(row[0])[0] + mp3name_no_extension = mp3name_no_extension.replace("_", "-") + # print(mp3name_no_extension) + words = row[1].split() + for word in words: + + if word not in words_to_search_for: + continue + # get alignment timings for this word + try: + tgf = mp3_to_textgrid[mp3name_no_extension] + except KeyError as e: + # print("error1", mp3name_no_extension) + notfound.append((mp3name_no_extension, word)) + continue + try: + tg = textgrid.TextGrid.fromFile(tgf) + except TextGridError as e: + # print("error2", tgf) + notfound.append((mp3name_no_extension, word)) + continue + for interval in tg[0]: + if interval.mark != word: + continue + start_s = interval.minTime + end_s = interval.maxTime + timings[word].append((mp3name_no_extension, start_s, end_s)) + def generate_wordtimings( words_to_search_for: Set[str], @@ -104,14 +153,14 @@ def generate_wordtimings( timings[w] = manager.list() worker = functools.partial( - _extract_timings, words_to_search_for, mp3_to_textgrid, timings, notfound + _extract_new_timings, words_to_search_for, mp3_to_textgrid, timings, notfound ) pool = multiprocessing.Pool() - for ix, result in enumerate( + for ix, result in tqdm(enumerate( pool.imap_unordered(worker, reader, chunksize=4000) - ): - if ix % 80_000 == 0: + )): + if ix % 10000 == 0: print(ix) pool.close() pool.join() diff --git a/extraction/__init__.py b/extraction/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/extraction/clean.py b/extraction/clean.py new file mode 100644 index 0000000..8a7fd04 --- /dev/null +++ b/extraction/clean.py @@ -0,0 +1,95 @@ +#%% +from cvutils import Alphabet +from cvutils import Validator +from pathlib import Path +from tqdm import tqdm +import os, multiprocessing, shutil + +data = Path('/mnt/disks/std3/compressed/generated/common_voice/frequent_words/') + +# langs = os.listdir(data) +langs = ['lt'] + +# %% +map, nolang = {}, set() +# langs = ['en'] + +#%% +# for l in tqdm(langs): +# map[l] = {} +# try: +# v = Validator(l) +# except: +# nolang.add(l) +# continue +# words = os.listdir(data / l / 'clips') +# for w in words: +# tw = correct_spelling(w) +# map[l][w] = tw +# out = v.validate(w) +# if out is not None: +# map[l][w] = out +# else: +# print(w) + # map[l][w] = w + +# def correct_spelling(word, alphabet): +# return [w for w in word if w in alphabet else ''] + +#%% +def correct_spelling(w, alphabet): + nw = '' + for i in w: + if i in alphabet: + nw += i + else: + continue + if nw == '': + return '' + + if nw[0] == "'": + nw = nw[1:] + if nw[-1] == "'": + nw = nw[:-1] + return nw + +# langs = os.listdir(data) +map = {} +novalids, noalphas = [], [] +for l in tqdm(langs): + valid, alpha = False, False + map[l] = {} + try: + v = Validator(l) + valid = True + except: + novalids.append(l) + valid = False + try: + alphabet = set(Alphabet(l).get_alphabet()) + alpha = True + except: + noalphas.append(l) + alpha = False + + words = os.listdir(data / l / 'clips') + + if not alpha: + map[l] = {k:k for k in words} + continue + + for w in tqdm(words): + nw = w + if valid: + nw_validated = v.validate(nw) + if nw_validated is not None: + nw = nw_validated + nw = correct_spelling(nw, alphabet) + map[l][w] = nw + + +cleaned = map + +import pickle +with open('cleaned_LT.p','wb') as file: + pickle.dump(cleaned, file) \ No newline at end of file diff --git a/extraction/clean2.py b/extraction/clean2.py new file mode 100644 index 0000000..d8b2411 --- /dev/null +++ b/extraction/clean2.py @@ -0,0 +1,35 @@ +#%% +import shutil, multiprocessing, pickle +from pathlib import Path + +data = Path("/mnt/disks/std3/compressed/generated/common_voice/frequent_words/") +new_data = Path("/mnt/disks/std3/compressed_cleaned2/generated/common_voice/frequent_words/") + +map = pickle.load(open("cleaned_LT.p",'rb')) + +def create_paths(map): + old_paths, new_paths = [], [] + for l in tqdm(map): + if l in ['ja','pa-IN']: + continue + lpath = data / l / "clips" + + for w in map[l]: + old_paths.append(lpath / w) + new_paths.append(new_data / l / "clips" / map[l][w]) + + return old_paths, new_paths + +from tqdm import tqdm + +old_paths, new_paths = create_paths(map) +#%% +print(f"Total paths {len(old_paths)}") +def copy(oword, nword): + shutil.copytree(oword, nword, dirs_exist_ok=True) + +pool = multiprocessing.Pool() +with tqdm(total=len(new_paths)) as pbar: + for i, result in enumerate(pool.starmap(copy, zip(old_paths, new_paths)), start=1): + pass +# %% diff --git a/extraction/collect.py b/extraction/collect.py new file mode 100644 index 0000000..2f24ad3 --- /dev/null +++ b/extraction/collect.py @@ -0,0 +1,66 @@ +#%% + +alignments = """ab.tar.gz +ar.tar.gz +as.tar.gz +br.tar.gz +ca.tar.gz +cnh.tar.gz +cs.tar.gz +cv.tar.gz +cy.tar.gz +de.tar.gz +dv.tar.gz +el.tar.gz +en.tar.gz +eo.tar.gz +es.tar.gz +et.tar.gz +eu.tar.gz +fa.tar.gz +fr.tar.gz +fy-NL.tar.gz +ga-IE.tar.gz +gn.tar.gz +ha.tar.gz +ia.tar.gz +id.tar.gz +it.tar.gz +ka.tar.gz +ky.tar.gz +lv.tar.gz +mn.tar.gz +mt.tar.gz +nl.tar.gz +or.tar.gz +pl.tar.gz +pt.tar.gz +rm-sursilv.tar.gz +rm-vallader.tar.gz +ro.tar.gz +ru.tar.gz +rw.tar.gz +sah.tar.gz +sk.tar.gz +sl.tar.gz +sv-SE.tar.gz +ta.tar.gz +tr.tar.gz +tt.tar.gz +uk.tar.gz +vi.tar.gz +zh-CN.tar.gz""".split('\n') +# %% + +alignments = [i.split('.gz')[0] for i in alignments] + +#%% + + +import subprocess +paths = [] + +for a in alignments: + out = subprocess.check_output(['rclone', 'link', '--drive-shared-with-me',f'msc3:MSC/audio/{a}']) + print(a, out[:-1]) +# %% diff --git a/extraction/compress_data.py b/extraction/compress_data.py new file mode 100644 index 0000000..3b18674 --- /dev/null +++ b/extraction/compress_data.py @@ -0,0 +1,128 @@ +import os, multiprocessing +import sox + +from pathlib import Path + +from tqdm import tqdm + +def collect_language_path(): + path, newpath = "/mnt/disks/std3/data/generated/common_voice/frequent_words/{0}/clips/", "/mnt/disks/std3/compressed/generated/common_voice/frequent_words/{0}/clips/", + # language_directory = path.format(lang) + old_clip_paths, new_clip_paths = [], [] + # languages = "ca cv de el en fa lt pt ru rw ta tr tt uk".split(' ') + # languages = ['ab', 'ar', 'as', 'cnh', 'cs', 'cy', 'dv', 'el', 'eo', 'es', 'et', 'eu', 'fi', 'fr', 'fy-NL', 'ga-IE', 'hi', 'ia', 'id', 'it', 'ja', 'ka', 'ky', 'lg', 'lv', 'mn', 'mt', 'nl', 'or', 'pa-IN', 'pl', 'rm-sursilv', 'rm-vallader', 'ro', 'sah', 'sl', 'sv-SE', 'vi'] + # languages = ['zh-CN','gn','ha', 'sk'] + languages = ['lt'] + # languages = "br ca cv de el en fa lt pt ru rw ta tr tt uk".split(' ') + + # languages = ["br"] + # path, newpath = "/mnt/disks/std3/data/generated/common_voice/frequent_words/{0}/clips/", "/mnt/disks/std3/compressed/generated/common_voice/frequent_words/{0}/clips/", + for lang in tqdm(languages): + language_directory = path.format(lang) + for word in os.listdir(language_directory): + word_directory = os.path.join(language_directory, word) + new_path_word_directory = os.path.join(newpath.format(lang), word) + + old_clip_paths.append(word_directory) + new_clip_paths.append(new_path_word_directory) + + os.makedirs(new_path_word_directory, exist_ok=True) + # for clip in os.listdir(word_directory): + # newp = os.path.join(new_path_word_directory, clip.replace('.wav', '.mp3')) + # if os.path.exists(newp): + # continue + # paths.append(os.path.join(word_directory, clip)) + # newpaths.append(newp) + + return old_clip_paths, new_clip_paths + +def collect_paths(): + """ + Collects the paths to all the files in the data directory. + """ + paths, newpaths = [], [] + languages = "ca cv de el en fa lt pt ru rw ta tr tt uk".split(' ') + # languages = "br ca cv de el en fa lt pt ru rw ta tr tt uk".split(' ') + + # languages = ["br"] + path, newpath = "/mnt/disks/std3/data/generated/common_voice/frequent_words/{0}/clips/", "/mnt/disks/std3/compressed/generated/common_voice/frequent_words/{0}/clips/", + for lang in tqdm(languages): + language_directory = path.format(lang) + for word in os.listdir(language_directory): + word_directory = os.path.join(language_directory, word) + new_path_word_directory = os.path.join(newpath.format(lang), word) + + # os.makedirs(new_path_word_directory, exist_ok=True) + for clip in os.listdir(word_directory): + newp = os.path.join(new_path_word_directory, clip.replace('.wav', '.mp3')) + if os.path.exists(newp): + continue + paths.append(os.path.join(word_directory, clip)) + newpaths.append(newp) + return paths, newpaths + +def compress(oldpath, newpath): +# def compress(): + # oldpath, newpath = "/mnt/disks/std3/data/generated/common_voice/frequent_words/en/clips/above/common_voice_en_18923823.wav", "test.mp3" + # try: + transformer = sox.Transformer() + transformer.convert(samplerate=48000) # from 48K mp3s + transformer.build(str(oldpath), str(newpath)) + # transformer.fade(fade_in_len=0.025, fade_out_len=0.025) + # transformer.pad(start_duration=pad_amt_s, end_duration=pad_amt_s) + # except Exception as e: + # print(e) + + return True + +def main(): + uncompressed_audios, newpaths = collect_paths() + print(f"Total files {len(newpaths)}") + pool = multiprocessing.Pool() + with tqdm(total=len(newpaths)) as pbar: + for i, result in enumerate(pool.starmap(compress, zip(uncompressed_audios, newpaths)), start=1): + if i%50000 == 0: + print(f"{i} files processed") + + +def remove_paths(old, new): + newoldpaths = [] + processed_paths = [] + # for i, word_p in os.listdir(old): + # assert len(old) == len(new), f"Length of old {len(old)} does not match length of new {len(new)}" + for clip in os.listdir(old): + newp = os.path.join(new, clip.replace('.wav', '.mp3')) + # newp = os.path.join(new_path_word_directory, clip.replace('.wav', '.mp3')) + if os.path.exists(newp): + continue + newoldpaths.append(newp) + processed_paths.append(os.path.join(old, clip)) + return processed_paths, newoldpaths + + +def main2(): + paths, newpaths = collect_language_path() + print(f"Total paths to process {len(newpaths)}") + pool = multiprocessing.Pool() + oldpaths, newprocessed_paths = [], [] + # with tqdm(total=len(newpaths)) as pbar: + for i, (r1, r2) in enumerate(pool.starmap(remove_paths, zip(paths, newpaths)), start=1): + oldpaths.extend(r1) + newprocessed_paths.extend(r2) + # if i%5000 == 0: + # print(f"{i} paths processed") + + # pool = multiprocessing.Pool() + print(f"Total files to process {len(newprocessed_paths)}") + for i, result in enumerate(pool.starmap(compress, zip(oldpaths, newprocessed_paths)), start=1): + # if i%50000 == 0: + # print(f"{i} files processed") + hello = 1 + + + + +if __name__ == '__main__': + main2() + # compress() + \ No newline at end of file diff --git a/extraction/extract_language.py b/extraction/extract_language.py new file mode 100644 index 0000000..3a74a2a --- /dev/null +++ b/extraction/extract_language.py @@ -0,0 +1,340 @@ +#%% + +import csv +import functools +import glob +import multiprocessing +import os, sys +import pathlib +import pickle +import shutil +import subprocess +from collections import Counter, OrderedDict +from pathlib import Path +# import nltk +from typing import Dict, List, Set + +import matplotlib.pyplot as plt +#%% +import numpy as np +import pandas as pd +import seaborn as sns +import sox +# import stopwordsiso as stopwords +import textgrid + +sys.path.append("../multilingual_kws/embedding") +import word_extraction + +# LANGUAGE = 'uk' + +# local +# ['ar', 'cs', 'cy', 'et', 'eu', 'id', 'ky', 'pl', 'pt', 'ru', 'ta', 'tr', 'tt', 'uk'] + +# sns.set() +# sns.set_palette("bright") +# sns.set(font_scale=1.6) + +#%% +# how large is each language? +langs = {} +alignments = Path("/mnt/disks/std750/data/common-voice-forced-alignments") +# new_alignments = Path("/mnt/disks/std750/data/new_alignments") + +for lang in os.listdir(alignments): + if not os.path.isdir(alignments / lang): + continue + validated = alignments / lang / "validated.csv" + if not os.path.isfile(validated): + continue + with open(validated, "r") as fh: + langs[lang] = len(fh.readlines()) +langs = OrderedDict(sorted(langs.items(), key=lambda kv: kv[1], reverse=True)) +# too many results in english +# del langs["en"] + +# %% +iso2lang = { + "ar": "Arabic", + "ca": "Catalan", + "cs": "Czech", + "cy": "Welsh", + "de": "German", # + "en": "English", # + "es": "Spanish", + "et": "Estonian", + "eu": "Basque", + "fa": "Persian", + "fr": "French", + "id": "Indonesian", + "it": "Italian", + "ky": "Kyrgyz", + "nl": "Dutch", + "pl": "Polish", + "pt": "Portuguese", + "ru": "Russian", + "rw": "Kinyarwanda", # + "ta": "Tamil", + "tr": "Turkish", + "tt": "Tatar", + "uk": "Ukranian", +} + +# %% +# paths +disk = Path("/mnt/disks/std3") +LANG_ISOCODE = "ab" +generated_common_voice_path = disk / "data/generated/common_voice" +frequent_words_dir = generated_common_voice_path / "frequent_words" / LANG_ISOCODE +timings_dir = frequent_words_dir / "timings" +errors_dir = frequent_words_dir / "errors" +clips_dir = frequent_words_dir / "clips" + +frequent_words_dir.mkdir(parents=True, exist_ok=True) +timings_dir.mkdir(parents=True, exist_ok=True) +errors_dir.mkdir(parents=True, exist_ok=True) +clips_dir.mkdir(parents=True, exist_ok=True) +print("Generating", LANG_ISOCODE)#, iso2lang[LANG_ISOCODE]) + +# %% +# total +# ['ar', 'ca', 'cs', 'cy', 'de', 'en', 'es', 'et', 'eu', 'fa', 'fr', 'id', 'it', 'ky', 'nl', 'pl', 'pt', 'ru', 'rw', 'ta', 'tr', 'tt', 'uk'] +# non-embedding classification: +# done: cs cy eu +# ['ar', 'cs', 'cy', 'et', 'eu', 'id', 'ky', 'pl', 'pt', 'ru', 'ta', 'tr', 'tt', 'uk'] + +# we are just using the speech commands dir directly, ignore this for now +# background_noise_dir=f"/home/mark/tinyspeech_harvard/frequent_words/{LANG_ISOCODE}/_background_noise_" +# BASE_BACKGROUND_NOISE="/home/mark/tinyspeech_harvard/speech_commands/_background_noise_" +# shutil.copytree(BASE_BACKGROUND_NOISE, background_noise_dir) +# if not os.path.isdir(background_noise_dir): +# raise ValueError("need to copy bg data", background_noise_dir) + +# %% +# generate most frequent words and their counts +# alignments = Path("/home/mark/tinyspeech_harvard/common-voice-forced-alignments") +counts = word_extraction.wordcounts(alignments / LANG_ISOCODE / "validated.csv") + +# %% +MIN_COUNT = 5 +MIN_CHAR_LEN = 3 +SKIP_FIRST_N = 0 + +non_stopwords = counts.copy() +# get rid of words that are too short +to_expunge = counts.most_common(SKIP_FIRST_N) +for k, _ in to_expunge: + del non_stopwords[k] + +already_exists = os.listdir(clips_dir) +skipped = 0 +for k in already_exists: + if k in non_stopwords.keys(): + print("already exists", k) + skipped += 1 + del non_stopwords[k] +print("skipped", skipped) +longer_words = [kv for kv in non_stopwords.most_common() if (kv[1] >= MIN_COUNT and len(kv[0]) >= MIN_CHAR_LEN)] +print("num words to be extracted", len(longer_words)) + +new_words_file = ( + disk / f"data/generated/common_voice/new_words/new_words_{LANG_ISOCODE}.txt" +) +new_words_file.parent.mkdir(parents=True, exist_ok=True) + +with open(new_words_file, "w") as fh: + fh.write(LANG_ISOCODE + "\n") + fh.write(",".join([l[0] for l in longer_words])) + fh.write("\n") + + +# %% +# fetch timings for all words of interest +timings_count = 0 +dest_pkl = f"{frequent_words_dir}/all_timings_{timings_count}.pkl" +while os.path.isfile(dest_pkl): + print("already exists", dest_pkl) + timings_count += 1 + dest_pkl = f"{frequent_words_dir}/all_timings_{timings_count}.pkl" +words = set([w[0] for w in longer_words]) +tgs = word_extraction.generate_filemap( + lang_isocode=LANG_ISOCODE, alignment_basedir=alignments +) +print("extracting timings") +timings, notfound = word_extraction.generate_wordtimings( + words_to_search_for=words, + mp3_to_textgrid=tgs, + lang_isocode=LANG_ISOCODE, + alignment_basedir=alignments, +) +print("errors", len(notfound)) +print("saving timings to", dest_pkl) +with open(dest_pkl, "wb") as fh: + pickle.dump(timings, fh) + +# %% +# write timings to csvs per word +MAX_NUM_UTTERANCES_TO_SAMPLE = 300 +df_dest = pathlib.Path(timings_dir) +from tqdm import tqdm +for word, times in tqdm(timings.items()): + df = pd.DataFrame(times, columns=["mp3_filename", "start_time_s", "end_time_s"]) + # print(df_dest / (word + ".csv")) + if "/" in word: + print(f"Cant save {word}") + continue + df.to_csv(df_dest / (word + ".csv"), quoting=csv.QUOTE_MINIMAL, index=False) + +# %% + +################################################################ +# now, run extract_frequent_words.py +# below, select splits between 165 commands and 85 other words +################################################################ + +# %% +# LANG_ISOCODE = "uk" +# disk = Path("/mnt/disks/std750") +disk750 = Path("/mnt/disks/std750") +common_voice_dir = disk / "data/generated/common_voice" +common_voice_data_dir = disk750 / "data/common-voice/cv-corpus-7.0-2021-07-21" +WORD_CSVS_DIR = timings_dir +# WORD_CSVS = Path(f"/mnt/disks/std750/data/generated/common_voice/timings/{LANG_ISOCODE}/*.csv") +# WORD_CSVS = f"/home/mark/tinyspeech_harvard/frequent_words/{LANG_ISOCODE}/timings/*.csv" +# CV_CLIPS_DIR = Path(f"/media/mark/hyperion/common_voice/cv-corpus-5.1-2020-06-22/{LANG_ISOCODE}/clips/") +CV_CLIPS_DIR = common_voice_data_dir / LANG_ISOCODE / "clips" +# CV_CLIPS_DIR = Path(f"/media/mark/hyperion/common_voice/cv-corpus-6.1-2020-12-11/{LANG_ISOCODE}/clips/") +# SWTS_CLIPS_DIR = Path("/home/mark/tinyspeech_harvard/commonvoice_singleword/cv-corpus-5-singleword/en/clips") +OUT_DIR = clips_dir +# OUT_DIR = Path(f"/home/mark/tinyspeech_harvard/frequent_words/{LANG_ISOCODE}/clips") +ERRORS_DIR = errors_dir +# ERRORS_DIR = Path(f"/home/mark/tinyspeech_harvard/frequent_words/{LANG_ISOCODE}/errors") +WRITE_PROGRESS = True + +def extract_one_second(duration_s: float, start_s: float, end_s: float): + """ + return one second around the midpoint between start_s and end_s + """ + if duration_s < 1: + return (0, duration_s) + + center_s = start_s + ((end_s - start_s) / 2.0) + + new_start_s = center_s - 0.5 + new_end_s = center_s + 0.5 + + if new_end_s > duration_s: + new_end_s = duration_s + new_start_s = duration_s - 1.0 + + if new_start_s < 0: + new_start_s = 0 + new_end_s = np.minimum(duration_s, new_start_s + 1.0) + + # print( + # "start", + # new_start_s, + # "end", + # new_end_s, + # "\nduration", + # new_end_s - new_start_s, + # "midpoint", + # new_start_s + ((new_end_s - new_start_s) / 2.0), + # ) + return (new_start_s, new_end_s) + + +def extract(csvpath): + word = os.path.splitext(os.path.basename(csvpath))[0] + # print(word) + if os.path.isdir(OUT_DIR / word): + raise ValueError("trying to extract to an existing dir", OUT_DIR / word) + os.mkdir(OUT_DIR / word) + + with open(csvpath, "r") as fh: + reader = csv.reader(fh) + next(reader) # skip header + + for ix, row in enumerate(reader): + if ix % 1000 == 0: + print(word, ix) + if WRITE_PROGRESS: + with open("progress.txt", "a") as fh: + fh.write(f"{word} {ix}\n") + mp3name_no_ext = row[0] + start_s = float(row[1]) + end_s = float(row[2]) + mp3path = CV_CLIPS_DIR / (mp3name_no_ext + ".mp3") + # if not os.path.exists(mp3path): # must be in Mozilla SWTS + # mp3path = SWTS_CLIPS_DIR / (mp3name_no_ext + ".mp3") + if not os.path.exists(mp3path): + # really don't know where this came from, skip it + with open(ERRORS_DIR / mp3name_no_ext, "a") as fh: + pass + continue + + duration = sox.file_info.duration(mp3path) + if end_s - start_s < 1: + pad_amt_s = (1.0 - (end_s - start_s)) / 2.0 + else: # utterance is already longer than 1s, trim instead + start_s, end_s = extract_one_second(duration, start_s, end_s) + pad_amt_s = 0 + + dest = OUT_DIR / word / (mp3name_no_ext + ".wav") + # words can appear multiple times in a sentence: append w number + count = 2 + while os.path.exists(dest): + dest = OUT_DIR / word / (f"{mp3name_no_ext}__{count}.wav") + count += 1 + + transformer = sox.Transformer() + transformer.convert(samplerate=48000) # from 48K mp3s + transformer.trim(start_s, end_s) + # use smaller fadein/fadeout since we are capturing just the word + # TODO(mmaz) is this appropriately sized? + transformer.fade(fade_in_len=0.025, fade_out_len=0.025) + transformer.pad(start_duration=pad_amt_s, end_duration=pad_amt_s) + transformer.build(str(mp3path), str(dest)) + return word + +def main(): + if not os.path.isdir(OUT_DIR) or not os.path.isdir(ERRORS_DIR): + raise ValueError("create outdir and errordir", OUT_DIR, ERRORS_DIR) + if not os.path.isdir(CV_CLIPS_DIR): + raise ValueError("data not found") + # print(WORD_CSVS) + all_csvs = [x for x in WORD_CSVS_DIR.glob("*.csv") if x.is_file()] + print("num csvs found", len(all_csvs)) + if len(all_csvs) == 0: + raise ValueError("no csvs") + + unextracted_csvs = [] + for csvpath in all_csvs: + word = os.path.splitext(os.path.basename(csvpath))[0] + wav_dir = OUT_DIR / word + if os.path.exists(wav_dir): + print("skipping", wav_dir) + continue + else: + unextracted_csvs.append(csvpath) + print("\n\n::::::::::::::::::::") + print("unextracted csvs:", unextracted_csvs) + print("\n\n--------------------") + print("extracting", len(unextracted_csvs), "out of", len(all_csvs)) + + pool = multiprocessing.Pool() + for i, result in enumerate(pool.imap_unordered(extract, unextracted_csvs), start=1): + print("counter: ", i, "word", result) + if WRITE_PROGRESS: + with open("finished.txt", "a") as fh: + fh.write(f"counter {i} word {result}\n") + pool.close() + pool.join() + + if WRITE_PROGRESS: + with open("finished.txt", "a") as fh: + fh.write("complete\n") + +main() + +# %% diff --git a/extraction/extract_language_new_alignments.py b/extraction/extract_language_new_alignments.py new file mode 100644 index 0000000..551c499 --- /dev/null +++ b/extraction/extract_language_new_alignments.py @@ -0,0 +1,362 @@ +#%% + +import csv +import functools +import glob +import multiprocessing +import os, sys +import pathlib +import pickle +import shutil +import subprocess +from collections import Counter, OrderedDict +from pathlib import Path +# import nltk +from typing import Dict, List, Set + +import matplotlib.pyplot as plt +#%% +import numpy as np +import pandas as pd +import seaborn as sns +import sox +# import stopwordsiso as stopwords +import textgrid + +sys.path.append("../multilingual_kws/embedding") +import word_extraction + +# LANGUAGE = 'uk' + +# local +# ['ar', 'cs', 'cy', 'et', 'eu', 'id', 'ky', 'pl', 'pt', 'ru', 'ta', 'tr', 'tt', 'uk'] + +# sns.set() +# sns.set_palette("bright") +# sns.set(font_scale=1.6) + +#%% +# how large is each language? +langs = {} +# alignments = Path("/mnt/disks/std750/data/common-voice-forced-alignments") +new_alignments = Path("/mnt/disks/std3/alignments") + +for lang in os.listdir(new_alignments): + if not os.path.isdir(new_alignments / lang): + continue + folder = new_alignments / lang + langs[lang] = len(os.listdir(folder)) - 1 +langs = OrderedDict(sorted(langs.items(), key=lambda kv: kv[1], reverse=True)) +# too many results in english +# del langs["en"] + +# %% +iso2lang = { + "ar": "Arabic", + "ca": "Catalan", + "cs": "Czech", + "cy": "Welsh", + "de": "German", # + "en": "English", # + "es": "Spanish", + "et": "Estonian", + "eu": "Basque", + "fa": "Persian", + "fr": "French", + "id": "Indonesian", + "it": "Italian", + "ky": "Kyrgyz", + "nl": "Dutch", + "pl": "Polish", + "pt": "Portuguese", + "ru": "Russian", + "rw": "Kinyarwanda", # + "ta": "Tamil", + "tr": "Turkish", + "tt": "Tatar", + "uk": "Ukranian", +} + +# %% +# paths +disk = Path("/mnt/disks/std3") +LANG_ISOCODE = "ha" +generated_common_voice_path = disk / "data/generated/common_voice" +frequent_words_dir = generated_common_voice_path / "frequent_words" / LANG_ISOCODE +timings_dir = frequent_words_dir / "timings" +errors_dir = frequent_words_dir / "errors" +clips_dir = frequent_words_dir / "clips" + +frequent_words_dir.mkdir(parents=True, exist_ok=True) +timings_dir.mkdir(parents=True, exist_ok=True) +errors_dir.mkdir(parents=True, exist_ok=True) +clips_dir.mkdir(parents=True, exist_ok=True) +print("Generating", LANG_ISOCODE)#, iso2lang[LANG_ISOCODE]) + +# %% +# total +# ['ar', 'ca', 'cs', 'cy', 'de', 'en', 'es', 'et', 'eu', 'fa', 'fr', 'id', 'it', 'ky', 'nl', 'pl', 'pt', 'ru', 'rw', 'ta', 'tr', 'tt', 'uk'] +# non-embedding classification: +# done: cs cy eu +# ['ar', 'cs', 'cy', 'et', 'eu', 'id', 'ky', 'pl', 'pt', 'ru', 'ta', 'tr', 'tt', 'uk'] + +# we are just using the speech commands dir directly, ignore this for now +# background_noise_dir=f"/home/mark/tinyspeech_harvard/frequent_words/{LANG_ISOCODE}/_background_noise_" +# BASE_BACKGROUND_NOISE="/home/mark/tinyspeech_harvard/speech_commands/_background_noise_" +# shutil.copytree(BASE_BACKGROUND_NOISE, background_noise_dir) +# if not os.path.isdir(background_noise_dir): +# raise ValueError("need to copy bg data", background_noise_dir) + +# %% +# generate most frequent words and their counts +# alignments = Path("/home/mark/tinyspeech_harvard/common-voice-forced-alignments") +# csv = + +new_csv = pd.read_csv(f"/mnt/disks/std750/data/common-voice/cv-corpus-7.0-2021-07-21/{LANG_ISOCODE}/validated.tsv", delimiter='\t')[['path','sentence']].rename({'path':'wav_filename','sentence':'transcript'},axis=1) +# new_csv['transcript'] = open('/mnt/disks/std3/alignments/zh-CN/chinese_lines_segmented.txt','r',encoding='utf-8').read().split('\n')[:-1] +# new_csv['transcript'] = new_csv['transcript'].str.replace('.mp3','') +new_csv.to_csv(new_alignments / LANG_ISOCODE / "validated.csv", index=False) + + +# new_csv = pd.read_csv(f"/mnt/disks/std750/data/common-voice/cv-corpus-7.0-2021-07-21/{LANG_ISOCODE}/validated.tsv", delimiter='\t')[['path','sentence']].rename({'path':'wav_filename','sentence':'transcript'},axis=1) +# new_csv['transcript'] = open('/mnt/disks/std3/alignments/zh-CN/chinese_lines_segmented.txt','r',encoding='utf-8').read().split('\n')[:-1] +# new_csv.to_csv(new_alignments / LANG_ISOCODE / "validated.csv", index=False) + +counts = word_extraction.wordcounts(new_alignments / LANG_ISOCODE / "validated.csv", True, 1) + +# %% +MIN_COUNT = 5 +MIN_CHAR_LEN = 2 +SKIP_FIRST_N = 0 + +non_stopwords = counts.copy() +# get rid of words that are too short +to_expunge = counts.most_common(SKIP_FIRST_N) +for k, _ in to_expunge: + del non_stopwords[k] + +already_exists = os.listdir(clips_dir) +skipped = 0 +for k in already_exists: + if k in non_stopwords.keys(): + print("already exists", k) + skipped += 1 + del non_stopwords[k] +print("skipped", skipped) +longer_words = [kv for kv in non_stopwords.most_common() if (kv[1] >= MIN_COUNT and len(kv[0]) >= MIN_CHAR_LEN)] +print("num words to be extracted", len(longer_words)) + +new_words_file = ( + disk / f"data/generated/common_voice/new_words/new_words_{LANG_ISOCODE}.txt" +) +new_words_file.parent.mkdir(parents=True, exist_ok=True) + +with open(new_words_file, "w") as fh: + fh.write(LANG_ISOCODE + "\n") + fh.write(",".join([l[0] for l in longer_words])) + fh.write("\n") + + +# %% +# fetch timings for all words of interest +timings_count = 0 +dest_pkl = f"{frequent_words_dir}/all_timings_{timings_count}.pkl" +while os.path.isfile(dest_pkl): + print("already exists", dest_pkl) + timings_count += 1 + dest_pkl = f"{frequent_words_dir}/all_timings_{timings_count}.pkl" +words = set([w[0] for w in longer_words]) +tgs = word_extraction.generate_new_filemap( + lang_isocode=LANG_ISOCODE, alignment_basedir=new_alignments +) + +# for k,v in tgs.items(): + + +#%% +print("extracting timings") +timings, notfound = word_extraction.generate_wordtimings( + words_to_search_for=words, + mp3_to_textgrid=tgs, + lang_isocode=LANG_ISOCODE, + alignment_basedir=new_alignments, +) +print("errors", len(notfound)) +print("saving timings to", dest_pkl) +with open(dest_pkl, "wb") as fh: + pickle.dump(timings, fh) + +# %% +# write timings to csvs per word +MAX_NUM_UTTERANCES_TO_SAMPLE = 300 +df_dest = pathlib.Path(timings_dir) +from tqdm import tqdm +for word, times in tqdm(timings.items()): + df = pd.DataFrame(times, columns=["mp3_filename", "start_time_s", "end_time_s"]) + # print(df_dest / (word + ".csv")) + if "/" in word: + print(f"Cant save {word}") + continue + df.to_csv(df_dest / (word + ".csv"), quoting=csv.QUOTE_MINIMAL, index=False) + +# %% + +################################################################ +# now, run extract_frequent_words.py +# below, select splits between 165 commands and 85 other words +################################################################ + +# %% +# LANG_ISOCODE = "uk" +# disk = Path("/mnt/disks/std750") +disk750 = Path("/mnt/disks/std750") +common_voice_dir = disk / "data/generated/common_voice" +common_voice_data_dir = disk750 / "data/common-voice/cv-corpus-7.0-2021-07-21" +WORD_CSVS_DIR = timings_dir +# WORD_CSVS = Path(f"/mnt/disks/std750/data/generated/common_voice/timings/{LANG_ISOCODE}/*.csv") +# WORD_CSVS = f"/home/mark/tinyspeech_harvard/frequent_words/{LANG_ISOCODE}/timings/*.csv" +# CV_CLIPS_DIR = Path(f"/media/mark/hyperion/common_voice/cv-corpus-5.1-2020-06-22/{LANG_ISOCODE}/clips/") +CV_CLIPS_DIR = common_voice_data_dir / LANG_ISOCODE / "clips" +# CV_CLIPS_DIR = Path(f"/media/mark/hyperion/common_voice/cv-corpus-6.1-2020-12-11/{LANG_ISOCODE}/clips/") +# SWTS_CLIPS_DIR = Path("/home/mark/tinyspeech_harvard/commonvoice_singleword/cv-corpus-5-singleword/en/clips") +OUT_DIR = clips_dir +# OUT_DIR = Path(f"/home/mark/tinyspeech_harvard/frequent_words/{LANG_ISOCODE}/clips") +ERRORS_DIR = errors_dir +# ERRORS_DIR = Path(f"/home/mark/tinyspeech_harvard/frequent_words/{LANG_ISOCODE}/errors") +WRITE_PROGRESS = True + +#%% +def extract_one_second(duration_s: float, start_s: float, end_s: float): + """ + return one second around the midpoint between start_s and end_s + """ + if duration_s < 1: + return (0, duration_s) + + center_s = start_s + ((end_s - start_s) / 2.0) + + new_start_s = center_s - 0.5 + new_end_s = center_s + 0.5 + + if new_end_s > duration_s: + new_end_s = duration_s + new_start_s = duration_s - 1.0 + + if new_start_s < 0: + new_start_s = 0 + new_end_s = np.minimum(duration_s, new_start_s + 1.0) + + # print( + # "start", + # new_start_s, + # "end", + # new_end_s, + # "\nduration", + # new_end_s - new_start_s, + # "midpoint", + # new_start_s + ((new_end_s - new_start_s) / 2.0), + # ) + return (new_start_s, new_end_s) + + +def extract(csvpath): + word = os.path.splitext(os.path.basename(csvpath))[0] + # print(word) + if os.path.isdir(OUT_DIR / word): + raise ValueError("trying to extract to an existing dir", OUT_DIR / word) + os.mkdir(OUT_DIR / word) + + with open(csvpath, "r") as fh: + reader = csv.reader(fh) + next(reader) # skip header + + for ix, row in enumerate(reader): + if ix % 1000 == 0: + print(word, ix) + if WRITE_PROGRESS: + with open("progress.txt", "a") as fh: + fh.write(f"{word} {ix}\n") + mp3name_no_ext = row[0] + if LANG_ISOCODE == "zh-CN": + mp3name_no_ext = mp3name_no_ext.split('-') + mp3name_no_ext = mp3name_no_ext[0] + '_' + mp3name_no_ext[1] + '_' + mp3name_no_ext[2] + '-' + mp3name_no_ext[3] + '_' + mp3name_no_ext[4] + else: + mp3name_no_ext = mp3name_no_ext.replace("-", "_") + + print(mp3name_no_ext) + start_s = float(row[1]) + end_s = float(row[2]) + mp3path = CV_CLIPS_DIR / (mp3name_no_ext + ".mp3") + # if not os.path.exists(mp3path): # must be in Mozilla SWTS + # mp3path = SWTS_CLIPS_DIR / (mp3name_no_ext + ".mp3") + if not os.path.exists(mp3path): + # really don't know where this came from, skip it + with open(ERRORS_DIR / mp3name_no_ext, "a") as fh: + pass + continue + + duration = sox.file_info.duration(mp3path) + if end_s - start_s < 1: + pad_amt_s = (1.0 - (end_s - start_s)) / 2.0 + else: # utterance is already longer than 1s, trim instead + start_s, end_s = extract_one_second(duration, start_s, end_s) + pad_amt_s = 0 + + dest = OUT_DIR / word / (mp3name_no_ext + ".wav") + # words can appear multiple times in a sentence: append w number + count = 2 + while os.path.exists(dest): + dest = OUT_DIR / word / (f"{mp3name_no_ext}__{count}.wav") + count += 1 + + transformer = sox.Transformer() + transformer.convert(samplerate=48000) # from 48K mp3s + transformer.trim(start_s, end_s) + # use smaller fadein/fadeout since we are capturing just the word + # TODO(mmaz) is this appropriately sized? + transformer.fade(fade_in_len=0.025, fade_out_len=0.025) + transformer.pad(start_duration=pad_amt_s, end_duration=pad_amt_s) + transformer.build(str(mp3path), str(dest)) + return word + +def main(): + if not os.path.isdir(OUT_DIR) or not os.path.isdir(ERRORS_DIR): + raise ValueError("create outdir and errordir", OUT_DIR, ERRORS_DIR) + if not os.path.isdir(CV_CLIPS_DIR): + raise ValueError("data not found") + # print(WORD_CSVS) + all_csvs = [x for x in WORD_CSVS_DIR.glob("*.csv") if x.is_file()] + print("num csvs found", len(all_csvs)) + if len(all_csvs) == 0: + raise ValueError("no csvs") + + unextracted_csvs = [] + for csvpath in all_csvs: + word = os.path.splitext(os.path.basename(csvpath))[0] + wav_dir = OUT_DIR / word + if os.path.exists(wav_dir): + print("skipping", wav_dir) + continue + else: + unextracted_csvs.append(csvpath) + print("\n\n::::::::::::::::::::") + print("unextracted csvs:", unextracted_csvs) + print("\n\n--------------------") + print("extracting", len(unextracted_csvs), "out of", len(all_csvs)) + + pool = multiprocessing.Pool() + for i, result in enumerate(pool.imap_unordered(extract, unextracted_csvs[:500]), start=1): + print("counter: ", i, "word", result) + if WRITE_PROGRESS: + with open("finished.txt", "a") as fh: + fh.write(f"counter {i} word {result}\n") + pool.close() + pool.join() + + if WRITE_PROGRESS: + with open("finished.txt", "a") as fh: + fh.write("complete\n") + +main() + +# %% diff --git a/extraction/map.py b/extraction/map.py new file mode 100644 index 0000000..53e13d8 --- /dev/null +++ b/extraction/map.py @@ -0,0 +1,50 @@ +{'ab':'Abkhaz', + 'ar':'Arabic', + 'as':'Assamese', + 'br':'Breton', + 'cnh':'Hakha Chin', + 'ca':'Catalan', + 'cs':'Czech', + 'cv':'Chuvash', + 'cy':'Welsh', + 'de':'German', + 'dv':'Divehi', + 'el':'Greek', + 'en':'English', + 'es':'Spanish', + 'eo':'Esperanto', + 'eu':'Basque', + 'et':'Estonian', + 'fa':'Persian', + 'fr':'French', + 'fy-NL':'Frisian', + 'ga-IE':'Irish', + 'ia':'Interlingua', + 'id':'Indonesian', + 'it':'Italian', + 'ja':'Japanese', + 'ka':'Georgian', + 'ky':'Kyrgyz', + 'lv':'Latvian', + 'mn':'Mongolian', + 'mt':'Maltese', + 'nl':'Dutch', + 'or':'Oriya', + 'pa-IN':'Punjabi', + 'pl':'Polish', + 'pt':'Portuguese', + 'rm-sursilv':'Sursilvan', + 'rm-vallader':'Vallader', + 'ro':'Romanian', + 'ru':'Russian', + 'rw':'Kinyarwanda', + 'sah':'Sakha', + 'sl':'Slovenian', + 'sv-SE':'Swedish', + 'ta':'Tamil', + 'tr':'Turkish', + 'tt':'Tatar', + 'uk':'Ukrainian', + 'vi':'Vietnamese', + 'zh-CN':'Chinese', + 'zh-TW':'Chinese'} diff --git a/packaging/copy.py b/packaging/copy.py new file mode 100644 index 0000000..fe7553a --- /dev/null +++ b/packaging/copy.py @@ -0,0 +1,23 @@ +import shutil, multiprocessing, pickle, os +from pathlib import Path + +from tqdm import tqdm + +old_data = Path("/mnt/disks/std3/compressed_cleaned3/generated/common_voice/frequent_words/") +new_data = Path("/mnt/disks/packaging/data/generated/common_voice/frequent_words/") + +languages = os.listdir(old_data) +old_paths, new_paths = [], [] + +for l in tqdm(languages): + words = os.listdir(old_data / l / "clips") + for w in words: + old_paths.append(old_data / l / "clips" / w) + new_paths.append(new_data / l / "clips" / w) + +def copy(oword, nword): + shutil.copytree(oword, nword) + +pool = multiprocessing.Pool() +for i, result in enumerate(pool.starmap(copy, zip(old_paths, new_paths)), start=1): + pass \ No newline at end of file diff --git a/packaging/filter_small_words.py b/packaging/filter_small_words.py new file mode 100644 index 0000000..fe7709f --- /dev/null +++ b/packaging/filter_small_words.py @@ -0,0 +1,49 @@ +#%% +import os +from pathlib import Path +from tqdm import tqdm + +old_data = Path("/mnt/disks/std3/compressed_cleaned3/generated/common_voice/frequent_words/") +# new_data = Path("/mnt/disks/std3/compressed_cleaned3/generated/common_voice/frequent_words/") + +languages = os.listdir(old_data) + +words = {} +for l in tqdm(languages): + words[l] = set(os.listdir(old_data / l / "clips")) +# %% + +lt3 = 0 +lt3s = [] +old_paths, new_paths = [], [] +for l in tqdm(languages): + for w in list(words[l]): + if len(w) < 3 and l!='zh-CN': + lt3 += 1 + lt3s.append(f"{l}/clips/{w}") + elif len(w) < 2 and l=='zh-CN': + lt3 += 1 + lt3s.append(f"{l}/clips/{w}") + else: + # new_path = new_data / l / "clips" / w + old_path = old_data / l / "clips" / w + # if os.path.exists(new_path): + # pass + # else: + # if old_path.is_dir(): + # # copy(old_path, new_path) + # old_paths.append(old_data / f"{l}/clips/{w}") + # new_paths.append(new_data / f"{l}/clips/{w}") +# %% +import shutil, multiprocessing, pickle +print(f"Total keywords {len(old_paths)}") +print(f"Skipping {lt3} keywords") + + +def copy(oword, nword): + shutil.copytree(oword, nword) + +pool = multiprocessing.Pool() +for i, result in enumerate(pool.starmap(copy, zip(old_paths, new_paths)), start=1): + pass +# %% diff --git a/packaging/tar_alignments.py b/packaging/tar_alignments.py new file mode 100644 index 0000000..cf1a9ec --- /dev/null +++ b/packaging/tar_alignments.py @@ -0,0 +1,30 @@ +#%% +import os +from pathlib import Path + +old_alignments = Path("/mnt/disks/std750/data/common-voice-forced-alignments/") +languages = os.listdir(old_alignments) + +to_remove = ['pa-IN','ja','zh-CN','zh-TW','zh-HK','README.md','LICENSE.md'] +languages = [x for x in languages if x not in to_remove] + +#%% +final_alignments = Path("/mnt/disks/std3/final/alignments/") + +os.chdir(final_alignments) + +# %% +from tqdm import tqdm + +for l in tqdm(languages): + old_path = old_alignments / l + os.system(f"tar -cf {l}.tar.gz {old_path}") +# %% + +new_alignments = Path("/mnt/disks/std3/alignments") +languages = os.listdir(new_alignments) + +for l in tqdm(languages): + new_path = new_alignments / l + os.system(f"tar -cf {l}.tar.gz {new_path}") +# %% diff --git a/packaging/tar_audioclips.py b/packaging/tar_audioclips.py new file mode 100644 index 0000000..c9103f3 --- /dev/null +++ b/packaging/tar_audioclips.py @@ -0,0 +1,18 @@ +#%% +import os +from pathlib import Path + +audio_clips = Path("/mnt/disks/std3/compressed_cleaned3/generated/common_voice/frequent_words") +languages = os.listdir(audio_clips) + +#%% +final_audio_clips = Path("/mnt/disks/std3/final/audio2/") + +os.chdir(final_audio_clips) + +# %% +from tqdm import tqdm + +for l in tqdm(languages): + old_path = audio_clips / l + os.system(f"tar -cf {l}.tar {old_path}") diff --git a/packaging/tar_audioclips_parallel.py b/packaging/tar_audioclips_parallel.py new file mode 100644 index 0000000..d18960a --- /dev/null +++ b/packaging/tar_audioclips_parallel.py @@ -0,0 +1,33 @@ +#%% +import os, multiprocessing +from pathlib import Path + +audio_clips = Path("/mnt/disks/std3/compressed_cleaned3/generated/common_voice/frequent_words") +languages = os.listdir(audio_clips) + +# languages = ["ab","ar","as","br","ca","cnh","cs","cv","cy","dv","el","eo","es","et","eu","fa","fr"] + +#%% +final_audio_clips = Path("/mnt/disks/std3/final/audio/") + +os.chdir(final_audio_clips) + +# %% +from tqdm import tqdm +import subprocess + +def tar(l, path): + subprocess.call(["tar", "-zcf", f"{l}.tar.gz", path])#, env=dict(os.environ, **{"GZIP":"-1"})) + +old_paths, ls = [], [] +for l in tqdm(languages): + ls.append(l) + old_path = audio_clips / l + old_paths.append(str(old_path)) + # os.system(f"tar -cf {l}.tar {old_path}") +# print(old_paths) +# exit(0) +#%% +pool = multiprocessing.Pool() +for i, result in enumerate(pool.starmap(tar, zip(ls, old_paths)), start=1): + pass \ No newline at end of file diff --git a/packaging/upload.py b/packaging/upload.py new file mode 100644 index 0000000..402e1dc --- /dev/null +++ b/packaging/upload.py @@ -0,0 +1,22 @@ +#%% +from pathlib import Path +import subprocess, os, multiprocessing + +data = Path("/mnt/disks/std3/final/audio/") +files = os.listdir(data) + +paths = [] + +for f in files: + if f in ["en.tar.gz", "fr.tar.gz", "de.tar.gz", "ca.tar.gz", "rw.tar.gz"]: + paths.append(data / f) + +print(len(paths)) +# exit(0) +#%% +def upload(path): + subprocess.call(['rclone', 'copy', str(path), 'msc3:MSC_Sharad/']) + +pool = multiprocessing.Pool() +for i, result in enumerate(pool.imap_unordered(upload, paths), start=1): + pass \ No newline at end of file