main_code_development_v2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# read data\n",
    "df = pd.read_csv(\"Resources/DisneylandReviews.csv\", encoding='ISO-8859-1')\n",
    "reviews_df = df[df[\"Year_Month\"] != \"missing\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Review_ID</th>\n",
       "      <th>Rating</th>\n",
       "      <th>Year_Month</th>\n",
       "      <th>Reviewer_Location</th>\n",
       "      <th>Review_Text</th>\n",
       "      <th>Branch</th>\n",
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       "      <th>0</th>\n",
       "      <td>670772142</td>\n",
       "      <td>4</td>\n",
       "      <td>2019-4</td>\n",
       "      <td>Australia</td>\n",
       "      <td>If you've ever been to Disneyland anywhere you...</td>\n",
       "      <td>Disneyland_HongKong</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>670682799</td>\n",
       "      <td>4</td>\n",
       "      <td>2019-5</td>\n",
       "      <td>Philippines</td>\n",
       "      <td>Its been a while since d last time we visit HK...</td>\n",
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       "      <td>670623270</td>\n",
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       "      <td>United Arab Emirates</td>\n",
       "      <td>Thanks God it wasn   t too hot or too humid wh...</td>\n",
       "      <td>Disneyland_HongKong</td>\n",
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       "      <th>3</th>\n",
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       "      <td>United Kingdom</td>\n",
       "      <td>the location is not in the city, took around 1...</td>\n",
       "      <td>Disneyland_HongKong</td>\n",
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      ],
      "text/plain": [
       "   Review_ID  Rating Year_Month     Reviewer_Location  \\\n",
       "0  670772142       4     2019-4             Australia   \n",
       "1  670682799       4     2019-5           Philippines   \n",
       "2  670623270       4     2019-4  United Arab Emirates   \n",
       "3  670607911       4     2019-4             Australia   \n",
       "4  670607296       4     2019-4        United Kingdom   \n",
       "\n",
       "                                         Review_Text               Branch  \n",
       "0  If you've ever been to Disneyland anywhere you...  Disneyland_HongKong  \n",
       "1  Its been a while since d last time we visit HK...  Disneyland_HongKong  \n",
       "2  Thanks God it wasn   t too hot or too humid wh...  Disneyland_HongKong  \n",
       "3  HK Disneyland is a great compact park. Unfortu...  Disneyland_HongKong  \n",
       "4  the location is not in the city, took around 1...  Disneyland_HongKong  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
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    }
   ],
   "source": [
    "reviews_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/jessicaramosmolina/opt/anaconda3/envs/PythonData/lib/python3.6/site-packages/pandas/core/frame.py:2963: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self[k1] = value[k2]\n"
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Review_ID</th>\n",
       "      <th>Rating</th>\n",
       "      <th>Reviewer_Location</th>\n",
       "      <th>Review_Text</th>\n",
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       "      <td>670772142</td>\n",
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       "      <td>Australia</td>\n",
       "      <td>If you've ever been to Disneyland anywhere you...</td>\n",
       "      <td>Disneyland_HongKong</td>\n",
       "      <td>2019</td>\n",
       "      <td>4</td>\n",
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       "      <th>1</th>\n",
       "      <td>670682799</td>\n",
       "      <td>4</td>\n",
       "      <td>Philippines</td>\n",
       "      <td>Its been a while since d last time we visit HK...</td>\n",
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       "      <td>2019</td>\n",
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       "      <td>Thanks God it wasn   t too hot or too humid wh...</td>\n",
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       "      <td>670607911</td>\n",
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       "      <td>Australia</td>\n",
       "      <td>HK Disneyland is a great compact park. Unfortu...</td>\n",
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       "      <td>2019</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>670607296</td>\n",
       "      <td>4</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>the location is not in the city, took around 1...</td>\n",
       "      <td>Disneyland_HongKong</td>\n",
       "      <td>2019</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "   Review_ID  Rating     Reviewer_Location  \\\n",
       "0  670772142       4             Australia   \n",
       "1  670682799       4           Philippines   \n",
       "2  670623270       4  United Arab Emirates   \n",
       "3  670607911       4             Australia   \n",
       "4  670607296       4        United Kingdom   \n",
       "\n",
       "                                         Review_Text               Branch  \\\n",
       "0  If you've ever been to Disneyland anywhere you...  Disneyland_HongKong   \n",
       "1  Its been a while since d last time we visit HK...  Disneyland_HongKong   \n",
       "2  Thanks God it wasn   t too hot or too humid wh...  Disneyland_HongKong   \n",
       "3  HK Disneyland is a great compact park. Unfortu...  Disneyland_HongKong   \n",
       "4  the location is not in the city, took around 1...  Disneyland_HongKong   \n",
       "\n",
       "   Year Month  \n",
       "0  2019     4  \n",
       "1  2019     5  \n",
       "2  2019     4  \n",
       "3  2019     4  \n",
       "4  2019     4  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# split year_month to year and month columns\n",
    "reviews_df[['Year','Month']] = reviews_df[\"Year_Month\"].str.split(\"-\",expand=True,)\n",
    "# delete year_month column\n",
    "del reviews_df['Year_Month']\n",
    "reviews_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "   Review_ID  Rating     Reviewer_Location  \\\n",
       "0  670772142       4             Australia   \n",
       "1  670682799       4           Philippines   \n",
       "2  670623270       4  United Arab Emirates   \n",
       "3  670607911       4             Australia   \n",
       "4  670607296       4        United Kingdom   \n",
       "\n",
       "                                         Review_Text               Branch  \\\n",
       "0  If you've ever been to Disneyland anywhere you...  Disneyland_HongKong   \n",
       "1  Its been a while since d last time we visit HK...  Disneyland_HongKong   \n",
       "2  Thanks God it wasn   t too hot or too humid wh...  Disneyland_HongKong   \n",
       "3  HK Disneyland is a great compact park. Unfortu...  Disneyland_HongKong   \n",
       "4  the location is not in the city, took around 1...  Disneyland_HongKong   \n",
       "\n",
       "   Year Month  \n",
       "0  2019     4  \n",
       "1  2019     5  \n",
       "2  2019     4  \n",
       "3  2019     4  \n",
       "4  2019     4  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reviews_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/jessicaramosmolina/opt/anaconda3/envs/PythonData/lib/python3.6/site-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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      "text/plain": [
       "   Review_ID  Rating     Reviewer_Location  \\\n",
       "0  670772142       4             Australia   \n",
       "1  670682799       4           Philippines   \n",
       "2  670623270       4  United Arab Emirates   \n",
       "3  670607911       4             Australia   \n",
       "4  670607296       4        United Kingdom   \n",
       "\n",
       "                                         Review_Text               Branch  \\\n",
       "0  If you've ever been to Disneyland anywhere you...  Disneyland_HongKong   \n",
       "1  Its been a while since d last time we visit HK...  Disneyland_HongKong   \n",
       "2  Thanks God it wasn   t too hot or too humid wh...  Disneyland_HongKong   \n",
       "3  HK Disneyland is a great compact park. Unfortu...  Disneyland_HongKong   \n",
       "4  the location is not in the city, took around 1...  Disneyland_HongKong   \n",
       "\n",
       "   Year Month  is_good_review  \n",
       "0  2019     4               1  \n",
       "1  2019     5               1  \n",
       "2  2019     4               1  \n",
       "3  2019     4               1  \n",
       "4  2019     4               1  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create the label\n",
    "reviews_df[\"is_good_review\"] = reviews_df[\"Rating\"].apply(lambda x: 1 if x > 3 else 0)\n",
    "reviews_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# return the wordnet object value corresponding to the POS tag\n",
    "from nltk.corpus import wordnet\n",
    "\n",
    "def get_wordnet_pos(pos_tag):\n",
    "    if pos_tag.startswith('J'):\n",
    "        return wordnet.ADJ\n",
    "    elif pos_tag.startswith('V'):\n",
    "        return wordnet.VERB\n",
    "    elif pos_tag.startswith('N'):\n",
    "        return wordnet.NOUN\n",
    "    elif pos_tag.startswith('R'):\n",
    "        return wordnet.ADV\n",
    "    else:\n",
    "        return wordnet.NOUN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package stopwords to\n",
      "[nltk_data]     /Users/jessicaramosmolina/nltk_data...\n",
      "[nltk_data]   Package stopwords is already up-to-date!\n",
      "[nltk_data] Downloading package averaged_perceptron_tagger to\n",
      "[nltk_data]     /Users/jessicaramosmolina/nltk_data...\n",
      "[nltk_data]   Package averaged_perceptron_tagger is already up-to-\n",
      "[nltk_data]       date!\n",
      "[nltk_data] Downloading package wordnet to\n",
      "[nltk_data]     /Users/jessicaramosmolina/nltk_data...\n",
      "[nltk_data]   Package wordnet is already up-to-date!\n"
     ]
    }
   ],
   "source": [
    "import string\n",
    "import nltk\n",
    "nltk.download('stopwords')\n",
    "nltk.download('averaged_perceptron_tagger')\n",
    "nltk.download('wordnet')\n",
    "from nltk import pos_tag\n",
    "from nltk.corpus import stopwords\n",
    "from nltk.tokenize import WhitespaceTokenizer\n",
    "from nltk.stem import WordNetLemmatizer\n",
    "\n",
    "def clean_text(text):\n",
    "    # lower text\n",
    "    text = text.lower()\n",
    "    # tokenize text and remove puncutation\n",
    "    text = [word.strip(string.punctuation) for word in text.split(\" \")]\n",
    "    # remove words that contain numbers\n",
    "    text = [word for word in text if not any(c.isdigit() for c in word)]\n",
    "    # remove stop words\n",
    "    stop = stopwords.words('english')\n",
    "    text = [x for x in text if x not in stop]\n",
    "    # remove empty tokens\n",
    "    text = [t for t in text if len(t) > 0]\n",
    "    # pos tag text\n",
    "    pos_tags = pos_tag(text)\n",
    "    # lemmatize text\n",
    "    text = [WordNetLemmatizer().lemmatize(t[0], get_wordnet_pos(t[1])) for t in pos_tags]\n",
    "    # remove words with only one letter\n",
    "    text = [t for t in text if len(t) > 1]\n",
    "    # join all\n",
    "    text = \" \".join(text)\n",
    "    return(text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/jessicaramosmolina/opt/anaconda3/envs/PythonData/lib/python3.6/site-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "# clean text data\n",
    "reviews_df[\"review_clean\"] = reviews_df[\"Review_Text\"].apply(lambda x: clean_text(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Review_ID</th>\n",
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       "   Review_ID  Rating     Reviewer_Location  \\\n",
       "0  670772142       4             Australia   \n",
       "1  670682799       4           Philippines   \n",
       "2  670623270       4  United Arab Emirates   \n",
       "3  670607911       4             Australia   \n",
       "4  670607296       4        United Kingdom   \n",
       "\n",
       "                                         Review_Text               Branch  \\\n",
       "0  If you've ever been to Disneyland anywhere you...  Disneyland_HongKong   \n",
       "1  Its been a while since d last time we visit HK...  Disneyland_HongKong   \n",
       "2  Thanks God it wasn   t too hot or too humid wh...  Disneyland_HongKong   \n",
       "3  HK Disneyland is a great compact park. Unfortu...  Disneyland_HongKong   \n",
       "4  the location is not in the city, took around 1...  Disneyland_HongKong   \n",
       "\n",
       "   Year Month  is_good_review  \\\n",
       "0  2019     4               1   \n",
       "1  2019     5               1   \n",
       "2  2019     4               1   \n",
       "3  2019     4               1   \n",
       "4  2019     4               1   \n",
       "\n",
       "                                        review_clean  \n",
       "0  ever disneyland anywhere find disneyland hong ...  \n",
       "1  since last time visit hk disneyland yet time s...  \n",
       "2  thanks god hot humid visit park otherwise woul...  \n",
       "3  hk disneyland great compact park unfortunately...  \n",
       "4  location city take around hour kowlon kid like...  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reviews_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package vader_lexicon to\n",
      "[nltk_data]     /Users/jessicaramosmolina/nltk_data...\n",
      "[nltk_data]   Package vader_lexicon is already up-to-date!\n",
      "/Users/jessicaramosmolina/opt/anaconda3/envs/PythonData/lib/python3.6/site-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "# add sentiment anaylsis columns\n",
    "from nltk.sentiment.vader import SentimentIntensityAnalyzer\n",
    "nltk.download('vader_lexicon')\n",
    "\n",
    "sid = SentimentIntensityAnalyzer()\n",
    "reviews_df[\"sentiments\"] = reviews_df[\"Review_Text\"].apply(lambda x: sid.polarity_scores(x))\n",
    "reviews_df = pd.concat([reviews_df.drop(['sentiments'], axis=1), reviews_df['sentiments'].apply(pd.Series)], axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
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       "   Review_ID  Rating     Reviewer_Location  \\\n",
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       "1  670682799       4           Philippines   \n",
       "2  670623270       4  United Arab Emirates   \n",
       "3  670607911       4             Australia   \n",
       "4  670607296       4        United Kingdom   \n",
       "\n",
       "                                         Review_Text               Branch  \\\n",
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       "\n",
       "   Year Month  is_good_review  \\\n",
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       "1  2019     5               1   \n",
       "2  2019     4               1   \n",
       "3  2019     4               1   \n",
       "4  2019     4               1   \n",
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       "1  since last time visit hk disneyland yet time s...  0.040  0.730  0.231   \n",
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       "4  location city take around hour kowlon kid like...  0.000  0.899  0.101   \n",
       "\n",
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     "metadata": {},
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  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# add number of characters column\n",
    "reviews_df[\"characters\"] = reviews_df[\"Review_Text\"].apply(lambda x: len(x))\n",
    "\n",
    "# add number of words column\n",
    "reviews_df[\"words\"] = reviews_df[\"Review_Text\"].apply(lambda x: len(x.split(\" \")))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
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       "   Review_ID  Rating     Reviewer_Location  \\\n",
       "0  670772142       4             Australia   \n",
       "1  670682799       4           Philippines   \n",
       "2  670623270       4  United Arab Emirates   \n",
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       "4  670607296       4        United Kingdom   \n",
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       "                                         Review_Text               Branch  \\\n",
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       "1  Its been a while since d last time we visit HK...  Disneyland_HongKong   \n",
       "2  Thanks God it wasn   t too hot or too humid wh...  Disneyland_HongKong   \n",
       "3  HK Disneyland is a great compact park. Unfortu...  Disneyland_HongKong   \n",
       "4  the location is not in the city, took around 1...  Disneyland_HongKong   \n",
       "\n",
       "   Year Month  is_good_review  \\\n",
       "0  2019     4               1   \n",
       "1  2019     5               1   \n",
       "2  2019     4               1   \n",
       "3  2019     4               1   \n",
       "4  2019     4               1   \n",
       "\n",
       "                                        review_clean    neg    neu    pos  \\\n",
       "0  ever disneyland anywhere find disneyland hong ...  0.000  0.887  0.113   \n",
       "1  since last time visit hk disneyland yet time s...  0.040  0.730  0.231   \n",
       "2  thanks god hot humid visit park otherwise woul...  0.024  0.742  0.235   \n",
       "3  hk disneyland great compact park unfortunately...  0.080  0.760  0.160   \n",
       "4  location city take around hour kowlon kid like...  0.000  0.899  0.101   \n",
       "\n",
       "   compound  characters  words  \n",
       "0    0.7069         329     62  \n",
       "1    0.9901         970    171  \n",
       "2    0.9920         938    179  \n",
       "3    0.8489         485     91  \n",
       "4    0.2846         163     33  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reviews_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create doc2vec vector columns\n",
    "# !pip install gensim\n",
    "from gensim.test.utils import common_texts\n",
    "from gensim.models.doc2vec import Doc2Vec, TaggedDocument\n",
    "\n",
    "documents = [TaggedDocument(doc, [i]) for i, doc in enumerate(reviews_df[\"review_clean\"].apply(lambda x: x.split(\" \")))]\n",
    "\n",
    "# train a Doc2Vec model with our text data\n",
    "model = Doc2Vec(documents, vector_size=5, window=2, min_count=1, workers=4)\n",
    "\n",
    "# transform each document into a vector data\n",
    "doc2vec_df = reviews_df[\"review_clean\"].apply(lambda x: model.infer_vector(x.split(\" \"))).apply(pd.Series)\n",
    "doc2vec_df.columns = [\"doc2vec_vector_\" + str(x) for x in doc2vec_df.columns]\n",
    "reviews_df = pd.concat([reviews_df, doc2vec_df], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>thanks god hot humid visit park otherwise woul...</td>\n",
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       "      <td>0.235</td>\n",
       "      <td>0.9920</td>\n",
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       "      <th>42114</th>\n",
       "      <td>92061774</td>\n",
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       "      <td>Germany</td>\n",
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       "      <td>2011</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>return day family trip disneyland two boy age ...</td>\n",
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       "      <th>42115</th>\n",
       "      <td>91995748</td>\n",
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       "      <td>2010</td>\n",
       "      <td>12</td>\n",
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       "      <th>42116</th>\n",
       "      <td>91984642</td>\n",
       "      <td>2</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>Well I was really looking forward to this trip...</td>\n",
       "      <td>Disneyland_Paris</td>\n",
       "      <td>2010</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>well really look forward trip christmas period...</td>\n",
       "      <td>0.067</td>\n",
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       "      <td>0.108</td>\n",
       "      <td>0.9518</td>\n",
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       "      <td>314</td>\n",
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       "      <td>0.122786</td>\n",
       "      <td>-0.544030</td>\n",
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       "    <tr>\n",
       "      <th>42117</th>\n",
       "      <td>91827418</td>\n",
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       "      <td>United Kingdom</td>\n",
       "      <td>If staying at a Disney hotel make good use of ...</td>\n",
       "      <td>Disneyland_Paris</td>\n",
       "      <td>2010</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>stay disney hotel make good use extra hour fas...</td>\n",
       "      <td>0.041</td>\n",
       "      <td>0.840</td>\n",
       "      <td>0.119</td>\n",
       "      <td>0.8122</td>\n",
       "      <td>512</td>\n",
       "      <td>104</td>\n",
       "      <td>0.214665</td>\n",
       "      <td>-0.348490</td>\n",
       "      <td>-0.308453</td>\n",
       "      <td>-0.227267</td>\n",
       "      <td>-0.062956</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>40043 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Review_ID  Rating     Reviewer_Location  \\\n",
       "0      670772142       4             Australia   \n",
       "1      670682799       4           Philippines   \n",
       "2      670623270       4  United Arab Emirates   \n",
       "3      670607911       4             Australia   \n",
       "4      670607296       4        United Kingdom   \n",
       "...          ...     ...                   ...   \n",
       "42113   92198076       4        United Kingdom   \n",
       "42114   92061774       4               Germany   \n",
       "42115   91995748       1        United Kingdom   \n",
       "42116   91984642       2        United Kingdom   \n",
       "42117   91827418       5        United Kingdom   \n",
       "\n",
       "                                             Review_Text               Branch  \\\n",
       "0      If you've ever been to Disneyland anywhere you...  Disneyland_HongKong   \n",
       "1      Its been a while since d last time we visit HK...  Disneyland_HongKong   \n",
       "2      Thanks God it wasn   t too hot or too humid wh...  Disneyland_HongKong   \n",
       "3      HK Disneyland is a great compact park. Unfortu...  Disneyland_HongKong   \n",
       "4      the location is not in the city, took around 1...  Disneyland_HongKong   \n",
       "...                                                  ...                  ...   \n",
       "42113  Although our pick up was prompt the taxi drive...     Disneyland_Paris   \n",
       "42114  Just returned from a 4 days family trip to Dis...     Disneyland_Paris   \n",
       "42115  We spent the 20 Dec 2010 in the Disney park an...     Disneyland_Paris   \n",
       "42116  Well I was really looking forward to this trip...     Disneyland_Paris   \n",
       "42117  If staying at a Disney hotel make good use of ...     Disneyland_Paris   \n",
       "\n",
       "       Year Month  is_good_review  \\\n",
       "0      2019     4               1   \n",
       "1      2019     5               1   \n",
       "2      2019     4               1   \n",
       "3      2019     4               1   \n",
       "4      2019     4               1   \n",
       "...     ...   ...             ...   \n",
       "42113  2011     1               1   \n",
       "42114  2011     1               1   \n",
       "42115  2010    12               0   \n",
       "42116  2010    12               0   \n",
       "42117  2010     9               1   \n",
       "\n",
       "                                            review_clean    neg    neu    pos  \\\n",
       "0      ever disneyland anywhere find disneyland hong ...  0.000  0.887  0.113   \n",
       "1      since last time visit hk disneyland yet time s...  0.040  0.730  0.231   \n",
       "2      thanks god hot humid visit park otherwise woul...  0.024  0.742  0.235   \n",
       "3      hk disneyland great compact park unfortunately...  0.080  0.760  0.160   \n",
       "4      location city take around hour kowlon kid like...  0.000  0.899  0.101   \n",
       "...                                                  ...    ...    ...    ...   \n",
       "42113  although pick prompt taxi driver wasnt sure ti...  0.096  0.863  0.041   \n",
       "42114  return day family trip disneyland two boy age ...  0.028  0.910  0.062   \n",
       "42115  spent dec disney park lunchtime attraction sta...  0.067  0.832  0.101   \n",
       "42116  well really look forward trip christmas period...  0.067  0.825  0.108   \n",
       "42117  stay disney hotel make good use extra hour fas...  0.041  0.840  0.119   \n",
       "\n",
       "       compound  characters  words  doc2vec_vector_0  doc2vec_vector_1  \\\n",
       "0        0.7069         329     62          0.050431         -0.034836   \n",
       "1        0.9901         970    171          0.187021         -0.238030   \n",
       "2        0.9920         938    179          0.348343         -0.537727   \n",
       "3        0.8489         485     91         -0.014503         -0.042890   \n",
       "4        0.2846         163     33          0.122524          0.053267   \n",
       "...         ...         ...    ...               ...               ...   \n",
       "42113   -0.9551        1574    316         -0.031791         -0.736738   \n",
       "42114    0.9605        3593    653         -0.306130         -0.865878   \n",
       "42115    0.9372        2537    442          0.002912         -0.389017   \n",
       "42116    0.9518        1758    314          0.341874         -0.845304   \n",
       "42117    0.8122         512    104          0.214665         -0.348490   \n",
       "\n",
       "       doc2vec_vector_2  doc2vec_vector_3  doc2vec_vector_4  \n",
       "0              0.254213         -0.110911         -0.114619  \n",
       "1             -0.368185          0.201366         -0.664445  \n",
       "2             -0.192179         -0.094946         -0.168174  \n",
       "3              0.036652          0.126966          0.015273  \n",
       "4              0.052185         -0.011715         -0.010426  \n",
       "...                 ...               ...               ...  \n",
       "42113         -0.948358         -0.527268          0.176191  \n",
       "42114         -0.203343         -0.762818          0.637075  \n",
       "42115         -1.023200         -0.808383         -0.308483  \n",
       "42116         -0.555638          0.122786         -0.544030  \n",
       "42117         -0.308453         -0.227267         -0.062956  \n",
       "\n",
       "[40043 rows x 20 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reviews_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "## export all data to new csv\n",
    "reviews_df.to_csv('Resources/reviews_full_data.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# get a sample\n",
    "reviews_df = reviews_df.sample(frac = 0.1, replace = False, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>is_good_review</th>\n",
       "      <th>review_clean</th>\n",
       "      <th>neg</th>\n",
       "      <th>...</th>\n",
       "      <th>word_yet</th>\n",
       "      <th>word_york</th>\n",
       "      <th>word_you</th>\n",
       "      <th>word_young</th>\n",
       "      <th>word_yr</th>\n",
       "      <th>word_yrs</th>\n",
       "      <th>word_yum</th>\n",
       "      <th>word_yummy</th>\n",
       "      <th>word_zero</th>\n",
       "      <th>word_zone</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27680</th>\n",
       "      <td>122944085</td>\n",
       "      <td>5</td>\n",
       "      <td>United States</td>\n",
       "      <td>Spotlessly clean and so organized considering ...</td>\n",
       "      <td>Disneyland_California</td>\n",
       "      <td>2011</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>spotlessly clean organize consider thousand vi...</td>\n",
       "      <td>0.000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35899</th>\n",
       "      <td>290851203</td>\n",
       "      <td>5</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>Pricey but worth it, unfortunately the big thu...</td>\n",
       "      <td>Disneyland_Paris</td>\n",
       "      <td>2015</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>pricey worth unfortunately big thunder mountai...</td>\n",
       "      <td>0.115</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23932</th>\n",
       "      <td>168087311</td>\n",
       "      <td>4</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Disneyland is a magical place. Everyone, parti...</td>\n",
       "      <td>Disneyland_California</td>\n",
       "      <td>2013</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>disneyland magical place everyone particularly...</td>\n",
       "      <td>0.000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36122</th>\n",
       "      <td>282417360</td>\n",
       "      <td>5</td>\n",
       "      <td>Pakistan</td>\n",
       "      <td>Disney land is a must when visiting Paris. The...</td>\n",
       "      <td>Disneyland_Paris</td>\n",
       "      <td>2015</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>disney land must visit paris frozen show best ...</td>\n",
       "      <td>0.028</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8028</th>\n",
       "      <td>160953212</td>\n",
       "      <td>3</td>\n",
       "      <td>India</td>\n",
       "      <td>The HK Disneyland is definitely small, but it'...</td>\n",
       "      <td>Disneyland_HongKong</td>\n",
       "      <td>2012</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>hk disneyland definitely small definitely fun ...</td>\n",
       "      <td>0.000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18391</th>\n",
       "      <td>290217727</td>\n",
       "      <td>5</td>\n",
       "      <td>Australia</td>\n",
       "      <td>There's a reason why they call Disneyland  The...</td>\n",
       "      <td>Disneyland_California</td>\n",
       "      <td>2015</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>there's reason call disneyland happy place ear...</td>\n",
       "      <td>0.042</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39266</th>\n",
       "      <td>174264188</td>\n",
       "      <td>1</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>I visited Disneyland Paris with my family (tee...</td>\n",
       "      <td>Disneyland_Paris</td>\n",
       "      <td>2013</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>visit disneyland paris family teenage daughter...</td>\n",
       "      <td>0.081</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10069</th>\n",
       "      <td>638583788</td>\n",
       "      <td>5</td>\n",
       "      <td>United States</td>\n",
       "      <td>What a great day we had we did so much before ...</td>\n",
       "      <td>Disneyland_California</td>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>great day much great guide grandson amaze well...</td>\n",
       "      <td>0.000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21169</th>\n",
       "      <td>226159775</td>\n",
       "      <td>5</td>\n",
       "      <td>Philippines</td>\n",
       "      <td>It has been a childhood dream of mine to go to...</td>\n",
       "      <td>Disneyland_California</td>\n",
       "      <td>2013</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>childhood dream mine go disneyland whether you...</td>\n",
       "      <td>0.000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.432261</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40494</th>\n",
       "      <td>143521522</td>\n",
       "      <td>4</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>Well my wife and I visted in October 2012 for ...</td>\n",
       "      <td>Disneyland_Paris</td>\n",
       "      <td>2012</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>well wife visted october parcs real complaint ...</td>\n",
       "      <td>0.030</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4004 rows × 2150 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Review_ID  Rating Reviewer_Location  \\\n",
       "27680  122944085       5     United States   \n",
       "35899  290851203       5    United Kingdom   \n",
       "23932  168087311       4            Canada   \n",
       "36122  282417360       5          Pakistan   \n",
       "8028   160953212       3             India   \n",
       "...          ...     ...               ...   \n",
       "18391  290217727       5         Australia   \n",
       "39266  174264188       1    United Kingdom   \n",
       "10069  638583788       5     United States   \n",
       "21169  226159775       5       Philippines   \n",
       "40494  143521522       4    United Kingdom   \n",
       "\n",
       "                                             Review_Text  \\\n",
       "27680  Spotlessly clean and so organized considering ...   \n",
       "35899  Pricey but worth it, unfortunately the big thu...   \n",
       "23932  Disneyland is a magical place. Everyone, parti...   \n",
       "36122  Disney land is a must when visiting Paris. The...   \n",
       "8028   The HK Disneyland is definitely small, but it'...   \n",
       "...                                                  ...   \n",
       "18391  There's a reason why they call Disneyland  The...   \n",
       "39266  I visited Disneyland Paris with my family (tee...   \n",
       "10069  What a great day we had we did so much before ...   \n",
       "21169  It has been a childhood dream of mine to go to...   \n",
       "40494  Well my wife and I visted in October 2012 for ...   \n",
       "\n",
       "                      Branch  Year Month  is_good_review  \\\n",
       "27680  Disneyland_California  2011    10               1   \n",
       "35899       Disneyland_Paris  2015     7               1   \n",
       "23932  Disneyland_California  2013     7               1   \n",
       "36122       Disneyland_Paris  2015     6               1   \n",
       "8028     Disneyland_HongKong  2012     9               0   \n",
       "...                      ...   ...   ...             ...   \n",
       "18391  Disneyland_California  2015     7               1   \n",
       "39266       Disneyland_Paris  2013     8               0   \n",
       "10069  Disneyland_California  2018    12               1   \n",
       "21169  Disneyland_California  2013    10               1   \n",
       "40494       Disneyland_Paris  2012    10               1   \n",
       "\n",
       "                                            review_clean    neg  ...  \\\n",
       "27680  spotlessly clean organize consider thousand vi...  0.000  ...   \n",
       "35899  pricey worth unfortunately big thunder mountai...  0.115  ...   \n",
       "23932  disneyland magical place everyone particularly...  0.000  ...   \n",
       "36122  disney land must visit paris frozen show best ...  0.028  ...   \n",
       "8028   hk disneyland definitely small definitely fun ...  0.000  ...   \n",
       "...                                                  ...    ...  ...   \n",
       "18391  there's reason call disneyland happy place ear...  0.042  ...   \n",
       "39266  visit disneyland paris family teenage daughter...  0.081  ...   \n",
       "10069  great day much great guide grandson amaze well...  0.000  ...   \n",
       "21169  childhood dream mine go disneyland whether you...  0.000  ...   \n",
       "40494  well wife visted october parcs real complaint ...  0.030  ...   \n",
       "\n",
       "       word_yet  word_york  word_you  word_young  word_yr  word_yrs  word_yum  \\\n",
       "27680       0.0        0.0       0.0    0.000000      0.0       0.0       0.0   \n",
       "35899       0.0        0.0       0.0    0.000000      0.0       0.0       0.0   \n",
       "23932       0.0        0.0       0.0    0.000000      0.0       0.0       0.0   \n",
       "36122       0.0        0.0       0.0    0.000000      0.0       0.0       0.0   \n",
       "8028        0.0        0.0       0.0    0.000000      0.0       0.0       0.0   \n",
       "...         ...        ...       ...         ...      ...       ...       ...   \n",
       "18391       0.0        0.0       0.0    0.000000      0.0       0.0       0.0   \n",
       "39266       0.0        0.0       0.0    0.000000      0.0       0.0       0.0   \n",
       "10069       0.0        0.0       0.0    0.000000      0.0       0.0       0.0   \n",
       "21169       0.0        0.0       0.0    0.432261      0.0       0.0       0.0   \n",
       "40494       0.0        0.0       0.0    0.000000      0.0       0.0       0.0   \n",
       "\n",
       "       word_yummy  word_zero  word_zone  \n",
       "27680         0.0        0.0        0.0  \n",
       "35899         0.0        0.0        0.0  \n",
       "23932         0.0        0.0        0.0  \n",
       "36122         0.0        0.0        0.0  \n",
       "8028          0.0        0.0        0.0  \n",
       "...           ...        ...        ...  \n",
       "18391         0.0        0.0        0.0  \n",
       "39266         0.0        0.0        0.0  \n",
       "10069         0.0        0.0        0.0  \n",
       "21169         0.0        0.0        0.0  \n",
       "40494         0.0        0.0        0.0  \n",
       "\n",
       "[4004 rows x 2150 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# add tf-idfs columns\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "tfidf = TfidfVectorizer(min_df = 10)\n",
    "tfidf_result = tfidf.fit_transform(reviews_df[\"review_clean\"]).toarray()\n",
    "tfidf_df = pd.DataFrame(tfidf_result, columns = tfidf.get_feature_names())\n",
    "tfidf_df.columns = [\"word_\" + str(x) for x in tfidf_df.columns]\n",
    "tfidf_df.index = reviews_df.index\n",
    "reviews_df = pd.concat([reviews_df, tfidf_df], axis=1)\n",
    "reviews_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# export all data to new csv\n",
    "reviews_df.to_csv('Resources/reviews_sample_data.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    0.803696\n",
       "0    0.196304\n",
       "Name: is_good_review, dtype: float64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# show is_good_review distribution\n",
    "reviews_df[\"is_good_review\"].value_counts(normalize = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: wordcloud in /Users/jessicaramosmolina/opt/anaconda3/envs/PythonData/lib/python3.6/site-packages (1.8.1)\n",
      "Requirement already satisfied: pillow in /Users/jessicaramosmolina/opt/anaconda3/envs/PythonData/lib/python3.6/site-packages (from wordcloud) (7.2.0)\n",
      "Requirement already satisfied: matplotlib in /Users/jessicaramosmolina/opt/anaconda3/envs/PythonData/lib/python3.6/site-packages (from wordcloud) (3.3.2)\n",
      "Requirement already satisfied: numpy>=1.6.1 in /Users/jessicaramosmolina/opt/anaconda3/envs/PythonData/lib/python3.6/site-packages (from wordcloud) (1.19.5)\n",
      "Requirement already satisfied: certifi>=2020.06.20 in /Users/jessicaramosmolina/opt/anaconda3/envs/PythonData/lib/python3.6/site-packages (from matplotlib->wordcloud) (2020.6.20)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /Users/jessicaramosmolina/opt/anaconda3/envs/PythonData/lib/python3.6/site-packages (from matplotlib->wordcloud) (1.2.0)\n",
      "Requirement already satisfied: python-dateutil>=2.1 in /Users/jessicaramosmolina/opt/anaconda3/envs/PythonData/lib/python3.6/site-packages (from matplotlib->wordcloud) (2.8.1)\n",
      "Requirement already satisfied: cycler>=0.10 in /Users/jessicaramosmolina/opt/anaconda3/envs/PythonData/lib/python3.6/site-packages (from matplotlib->wordcloud) (0.10.0)\n",
      "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /Users/jessicaramosmolina/opt/anaconda3/envs/PythonData/lib/python3.6/site-packages (from matplotlib->wordcloud) (2.4.7)\n",
      "Requirement already satisfied: six in /Users/jessicaramosmolina/opt/anaconda3/envs/PythonData/lib/python3.6/site-packages (from cycler>=0.10->matplotlib->wordcloud) (1.15.0)\n",
      "\u001b[33mWARNING: You are using pip version 20.3.3; however, version 21.0.1 is available.\n",
      "You should consider upgrading via the '/Users/jessicaramosmolina/opt/anaconda3/envs/PythonData/bin/python -m pip install --upgrade pip' command.\u001b[0m\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# wordcloud function\n",
    "\n",
    "# !pip install wordcloud\n",
    "from wordcloud import WordCloud\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "def show_wordcloud(data, title = None):\n",
    "    wordcloud = WordCloud(\n",
    "        background_color = 'white',\n",
    "        max_words = 200,\n",
    "        max_font_size = 40, \n",
    "        scale = 3,\n",
    "        random_state = 42\n",
    "    ).generate(str(data))\n",
    "\n",
    "    fig = plt.figure(1, figsize = (20, 20))\n",
    "    plt.axis('off')\n",
    "    if title: \n",
    "        fig.suptitle(title, fontsize = 20)\n",
    "        fig.subplots_adjust(top = 2.3)\n",
    "\n",
    "    plt.imshow(wordcloud)\n",
    "    plt.show()\n",
    "    \n",
    "# print wordcloud\n",
    "show_wordcloud(reviews_df[\"Review_Text\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Review_Text</th>\n",
       "      <th>pos</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>31529</th>\n",
       "      <td>great fun, great characters, great shows and p...</td>\n",
       "      <td>0.686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26164</th>\n",
       "      <td>Wonderful time!!!  Great vacation with family ...</td>\n",
       "      <td>0.671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10750</th>\n",
       "      <td>Best park ever. In love with every single deta...</td>\n",
       "      <td>0.628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40925</th>\n",
       "      <td>The park of my dreams.  Cheyenne hotel is so a...</td>\n",
       "      <td>0.623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27097</th>\n",
       "      <td>I loved everything! :)  It's the Happiest Plac...</td>\n",
       "      <td>0.587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10095</th>\n",
       "      <td>Amazing! Small , easy to navigate with all the...</td>\n",
       "      <td>0.584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443</th>\n",
       "      <td>the best every to go to the best every the bes...</td>\n",
       "      <td>0.583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41722</th>\n",
       "      <td>Lovely time. 2nd time here. great rides and st...</td>\n",
       "      <td>0.530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>449</th>\n",
       "      <td>Love the Princess , Love the show and good pla...</td>\n",
       "      <td>0.528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38427</th>\n",
       "      <td>Great short break. Definitely a trip for all t...</td>\n",
       "      <td>0.526</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             Review_Text    pos\n",
       "31529  great fun, great characters, great shows and p...  0.686\n",
       "26164  Wonderful time!!!  Great vacation with family ...  0.671\n",
       "10750  Best park ever. In love with every single deta...  0.628\n",
       "40925  The park of my dreams.  Cheyenne hotel is so a...  0.623\n",
       "27097  I loved everything! :)  It's the Happiest Plac...  0.587\n",
       "10095  Amazing! Small , easy to navigate with all the...  0.584\n",
       "443    the best every to go to the best every the bes...  0.583\n",
       "41722  Lovely time. 2nd time here. great rides and st...  0.530\n",
       "449    Love the Princess , Love the show and good pla...  0.528\n",
       "38427  Great short break. Definitely a trip for all t...  0.526"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# highest positive sentiment reviews (with more than 5 words)\n",
    "reviews_df[reviews_df[\"words\"] >= 3].sort_values(\"pos\", ascending = False)[[\"Review_Text\", \"pos\"]].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Review_Text</th>\n",
       "      <th>neg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>42032</th>\n",
       "      <td>Dirty dirty dirty    Overpriced poor quality f...</td>\n",
       "      <td>0.495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35129</th>\n",
       "      <td>Terrible waste of money . Just want you to sho...</td>\n",
       "      <td>0.362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12643</th>\n",
       "      <td>Three year old twins loved it but I was disapp...</td>\n",
       "      <td>0.332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13048</th>\n",
       "      <td>Far too many people, rude service, uncomfortab...</td>\n",
       "      <td>0.328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40345</th>\n",
       "      <td>Fab time at Disney.... just avoid the restaura...</td>\n",
       "      <td>0.316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29593</th>\n",
       "      <td>The worst experience what we ever had with kid...</td>\n",
       "      <td>0.301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26536</th>\n",
       "      <td>Who doesn't love Disney? A little sad about th...</td>\n",
       "      <td>0.300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24447</th>\n",
       "      <td>Went here 5 years ago. Princesses was my favor...</td>\n",
       "      <td>0.288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12547</th>\n",
       "      <td>I was screamed at by one of the staff . Like w...</td>\n",
       "      <td>0.284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28048</th>\n",
       "      <td>What's not to love?  Fun tip: Splash Mountain ...</td>\n",
       "      <td>0.275</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             Review_Text    neg\n",
       "42032  Dirty dirty dirty    Overpriced poor quality f...  0.495\n",
       "35129  Terrible waste of money . Just want you to sho...  0.362\n",
       "12643  Three year old twins loved it but I was disapp...  0.332\n",
       "13048  Far too many people, rude service, uncomfortab...  0.328\n",
       "40345  Fab time at Disney.... just avoid the restaura...  0.316\n",
       "29593  The worst experience what we ever had with kid...  0.301\n",
       "26536  Who doesn't love Disney? A little sad about th...  0.300\n",
       "24447  Went here 5 years ago. Princesses was my favor...  0.288\n",
       "12547  I was screamed at by one of the staff . Like w...  0.284\n",
       "28048  What's not to love?  Fun tip: Splash Mountain ...  0.275"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# lowest negative sentiment reviews (with more than 5 words)\n",
    "reviews_df[reviews_df[\"words\"] >= 5].sort_values(\"neg\", ascending = False)[[\"Review_Text\", \"neg\"]].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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0tRY1WMucggZ1hEIKahHJA74A/CW+5SilerS2rpcIOjwvSqG2qP8X+D6gaxQqpdrX1MYSp6ATXqLUaVCLyHygxBizrpP9bhaRtSKytrS0NGYFKqV6kGAf9YmS7CBJGtQRCqVFfS5wmYjsA54B5ojIEyfuZIx51BhTYIwpyMnJiXGZSqkeob0+apHABW41qCPRaVAbY35kjMkzxuQDi4B3jDHXxr0ypVTP09b1EoPsLu2jjpCOo1ZKxU6T5+RZiUHaoo6YPZydjTHvAu/GpRKlVM/Wchmu9lrUbm1RR0hb1Eqp2Ghv5bwgbVFHTINaKRUbwZXztI865jSolVKxoS3quNGgVkrFRnvXSwyyu6BZgzoSGtRKqdgILnGqLeqY06BWSsVG8KIB2kcdcxrUSqnY6LTrQ1vUkdKgVkrFRmcnEx06jjpSGtRKqdjorI/a5tIWdYQ0qJVSsdHYzmW4guwu8DV1bU2nCA1qpVRsNFaDu511PgBsTu36iJAGtVIqNhqqwJ3Z/vN2F/ibrTVBVFg0qJVSsVFfCe6M9p+3Oa2tdn+ETYNaKRUbDVUdB3Ww79qn3R/h0qBWSsVGQxUkZ7b/fLBF7dUWdbg0qJVSsdFQqS3qONGgVkpFz5jOTybaAkGtIz/CpkGtlIqet8E6SdhhizrY9aFBHS4NaqVU9OorrW2Hoz606yNSGtRKqeg1VFnbjk4m2vVkYqQ0qJVS0QsGtbao40KDWikVvYZKa9vZzETQFnUENKiVUtFraVFntr9Py8xEbVGHS4NaKRW9ULo+7Do8L1Ia1Eqp6IU06kPX+oiUBrVSKnoNleBIOTayoy3aoo6YBrVSKnqdLcgErUZ9aIs6XBrUSqnodbbOB+jMxChoUCulotfZOh+g46ij0GlQi4hbRD4WkY0islVEftEVhSmlepCQuj50ZmKkQmlRNwJzjDHjgQnAxSIyLa5VKaV6ls6u7gKQlGRd/FZb1GGzd7aDMcYAnsBdR+CPiWdRSqkeprOLBgTZXdqijkBIfdQiYhORDUAJ8JYx5qM29rlZRNaKyNrS0tIYl6mUSlh+f+AK5J20qMHq/tAWddhCCmpjjM8YMwHIA84RkTFt7POoMabAGFOQk5MT4zKVUgmrqQaMP7Sgtrt01EcEwhr1YYypBFYAF8elGqVUzxPKOh9BNqeOo45AKKM+ckQkM3A7GZgH7IhzXUqpnqKu3Nqm9O58X21RR6TTk4lAf2CxiNiwgv2fxpiX41uWUqrH8ATOSaXmdr6v3aUt6giEMupjEzCxC2pRSvVEtSXWNi2Ec1M2bVFHQmcmKqWi4wkEtbao40aDWikVndpScKaBM6XzfW1ObVFHQINaKRUdTwmk9gltX7tLx1FHQINaKRWd2pLQuj0g0KLWro9waVArpaLjKYW0EINaW9QR0aBWSkWntgRSQ5yNbNO1PiKhQa2UipzPC3UVYbSoda2PSGhQK6UiV1cGGG1Rx5kGtVIqcsEx1NqijisNaqVU5GrDmD4Ox2YmGl3SPhwa1EqpyAWDOpwWNQb83riVdCrSoFZKRa5l+ngYfdSgsxPDpEGtlIpcbQnY3eBKD21/e/BK5HpCMRwa1EqpyHlKrda0SGj7t1yJXFvU4dCgVkpFLpzJLtCqRa1BHQ4NaqVU5CoPQkZe6Pu3tKi16yMcGtRKqcj4/VB5ALIGh/4abVFHRINaKRUZzxErcDPDCOqWUR/aog6HBrVSKjKV+61tOEFtD3R9aIs6LBrUSqnIVB6wtuF0feg46ohoUCulInM02KI+I/TXtLSotesjHBrUSqnIVO6DtL7gSA79NdqijogGtVIqMkf3h9c/DTozMUIa1EqpyFTuD69/GnRmYoQ0qJVS4fN5oaoovP5p0HHUEdKgVkqFr7oIjC/8rg+dmRgRDWqlVPiCY6jD7frQFnVENKiVUuEr32Nts4aE9zqdmRgRDWqlVPhKd4IjBTIGhfc6mx0kCbwN8anrFNVpUIvIIBFZISLbRGSriNzeFYUppRJY6Q7IGQ5JEbT17Mka1GEK5VP2Av9ljBkFTAO+JSKj4luWUiqhle6AnBGRvdaRDM31sa3nFNdpUBtjio0x6wO3a4DtwMB4F6aUSlD1lVBTHF1Qa4s6LGF9bxGRfGAi8FEbz90sImtFZG1paWmMylNKJZyyXdY20qC2u7VFHaaQg1pE0oB/Ad81xlSf+Lwx5lFjTIExpiAnJ4xL8yilepaS7dY2Z3hkr9euj7CFFNQi4sAK6SeNMc/FtySlVEIr3WmdEAx3skuQIxm8GtThCGXUhwB/BbYbY34b/5KUUgmtdAfknB3ZiA8IdH1oH3U4QvmkzwW+CswRkQ2BP5fEuS6lVKKKZsQHWOOvm+tiV89pwN7ZDsaY9wDpglqUUomursJa56Pv6MiP4XDrqI8w6cxEpVTojmyxtn3HRH4Me7J2fYRJg1opFbrDm61tv7GRH8ORrF0fYdKgVkqF7vAW6/JbabmRH0MnvIRNg1opFbrDm6NrTcOxCS/GxKam04AGtVIqNN4ma8RHtEHtcFsXHfA1x6au04AGtVIqNGU7wd8c3YlEsIbngU56CYMGtVIqNC0nEsdFdxy729rqyI+QaVArpUJzeLM1tC57WHTHcSRbWx35ETINaqVUaA5vhr6jIMkW3XGCQa0jP0KmQa2U6pwxsRnxAVarHHQFvTBoUCulOldVCA2VsQlqR7CPWoM6VBrUSqnOtUwdj0VQ66iPcGlQK6U6d3gzIFYfdbR01EfYNKiVUp07vAl6DwVXevTHcmgfdbg0qJVSnTu8BfpFOdElqGXUhwZ1qDSolVIda6iGo5/F5kQitBr1oV0fodKgVkp17MhWaxvtjMSg4KgPbVGHTINaKdWxWFwsoDUdRx02DWqlVMcOb4Lk3tBrQGyOl5QENpcGdRg0qJVSHTu82TqRKDG8dKpeNzEsGtRKqfb5vFCyPXb900F2vRxXODSolVLtK99ttXxjNeIjyKEXuA2HBrVSqn3BNahjdSIxyJGsoz7CoEGtlGrf4U1gc0Kfs2N73OB1E1VINKiVUu07vAlyhoPdGdvjOlK06yMMGtRKqbb5/VC0HgYWxP7YDrd2fYRBg1op1bayXdBYDXlTYn9s7foIiwa1Uqpthf+2tvEIakeKBnUYOg1qEXlMREpEZEtXFKSUShBFa8GdAdlnxv7YOuElLKG0qB8HLo5zHUqpRFO41uqfTorDF2+d8BKWTv8GjDGrgIouqEUplSgaa6BkW3y6PUAnvIQpZr8qReRmEVkrImtLS0tjdVilVHcoWg/GD3lxGPEBVlD7Gq2RJapTMQtqY8yjxpgCY0xBTk5OrA6rlOoOu9+CJAcMmhqf49t1Tepw6KgPpdTJdr4OQ2aBu1d8ju/Qq7yEw97dBSilEkzZbij/FM65uc2njTGU1jTS6PXjN4YUp50+aU4knGVQnanWtskDqdkxKPrU1mlQi8jTwPlAHxEpBO4yxvw13oUppbrJrtes7XBrsFdto5cP9pSzalcp6/Yf5bOyWuqbfce9JNVpY2hOGjPOzGbO8FwmD87CbuvgC7s709o2VAKDY/4jnGo6DWpjzNVdUYhSKkHsfA2TO4qPKlL555sbeHVzMQ3NflKcNiYPzmLa0Gzy+6SQ4rSTJFBV38z+8jp2HK7mr6s/408r9zIwM5nrZwxm4ZQzyEh2nPweyVnWtv5o1/5sPZR2fSilWvgOrsW2/33+nnwddz36IekuO1dNymP+uP4UDO6N097xaa2ahmZW7irlH2v288tXd/DHd3Zz+9yzuH5GPo7WLeyWoK6M3w9zCtGgVkphjGH59hKy//WfDDK9WJL0ee67agxXTBhIstMW8nHS3Q7mjxvA/HED2FJUxa/f2Mk9r2zn6Y8P8KsvjmNKfm9rx+RMa6st6pBoUCt1mtt6qIpfvLiNtANv85hzE5vH38lLV3weW1J010gcMzCDxTdO4Z0dJfz8pa0s/NMabjl/GLfPPRundn2ERYNaqdNUVX0zv3trF39fs4+LkrfzR/eDmOwRjL3suxBlSAeJCHNH9mXq0Gz+30vbeGjFHt7bXc4j106iv92tQR0iDWqlTjPGGJZ9UsQvX91BeW0jd48o5NoDv0b6nAVffR7srpi/Z5rLzv1fGsd5w3P43rMbufSP7/OBMwOnBnVINKiVOo3sOFzNT5/fwr/3HWXCoEyWXnCU/OU/hr6j4avLIKV3XN//krH9OSs3ja//fS37PA7SDh9mQFzf8dSgMxOVOg3UNDTz/17exhf+8B67Szz86qqxPHdlOvkrboP+4+D6F+Me0kFn9U3nhW/NxOfKZH9hEY+991mXvG9Ppi1qpU5hxhhe3HiIe17ZTpmnkavPOYPvXTicLPHAo/Ot0ReLnrbWne5CGSkO0vLP4NC+HVz98jbKPI1876Lh4c1uPI1oUCt1itpSVMXdL2/j488qGJeXwV+uK2D8oEzweeHJ/4CaYrjxNUjv2y312VKyyHM3cvWIM/i/d/dQ7mni3ivHdDyj8TSlQa3UKaakuoHfvLGTpesLyUpxcu+VY1g05Yxjw+3evgv2roDLHozfMqahSM5C6iv55ZVjyElz8od3dlNR18Qfr56I2xH62O3TgQa1UqeIhmYff33vMx5asZtmn5+vzxrKt+ecSS93qync7/0vrHnQWnBp0le7rVbA6nZprkV8Tdxx4XCy01zc9eJWblr8b/58XQEpTo2nIP0klOrhGpp9PPnRAR5ZuYfSmkYuGt2XH31+JPl9Uo/t1FQL794HH/wRxnwJLv5V9xUc1HoaeXpfrp+RT6rLzveXbuS6v37MYzdOOf6XzGlMg1qpHurEgJ4xLJuHrpnEOUNOGL2x60149b+g8gBMvgEueQCSEqBrIbiCXv3Rln7yL03OI8Vp4/ZnPuErf/6Ixf9xDr1Tnd1XY4LQoFaqhympbuDpjw/yjw/3U+axAvrBqycydegJ6zpXF8PrP4Rtz0Of4daJw8EzuqXmNrUzjfySsf1Jdtj4xhPrWPToGp64aSq5vdzdUGDi0KBWqgcwxrD+wFEe/2A/r20uxus3nHd2DreeP+zkgAarFf2vm8DbCHN+AjNuB3uCtUyDQd1QedJTF4zI5fEbp/C1xWv58p/W8MTXppKXldK19SUQDWqlElhxVT0vbTzEsk8Osb24mnS3netn5HPttMEMad0H3dq6x+HlO6zZhgseh+xhXVly6DpZQW/GsD7846ap3PC3j/nyI2t48uvT2v+ZT3Ea1D2EMYaq+mYq65rxNHqpbmjG0+ClrslHUpLgSBLstiTsSYLLnkRGioOsFCdZKc6wlqlU3a+itonXthTz4oZDfLyvAmNgfF4Gv7xyLFdMHND+aAhjYMW9sOo3cObnYMFicKV1bfHhCGEFvcmDs3j669O47rGPWfDIGh6/cQpjBnbt5JxEoEGdgA5V1rNu/1E+PVLDvvI69pXXsq+sluoGb0THc9mT6JPmon+Gm/6ZyQzIcLe6nUz/TDfZqWFe807FjN9v2FZczYodJazYWcKGg5X4DQzLSeWOz53NpeMHHD+Coy3eJnjpO7DxaZj4VZj/O7Al+IgJVwYgna6gN2ZgBv/8xjSuf+zfLHhkDX+4eiLzRnXPJJ3uokGdAPaUenh/dxlr9x1l3f6jFFXWA9ZKkwOzksnPTuXyCQMZnJ1CdpqTNJeDNJeddLedZKcNYwzNPoPPb2j2+alv9lFV18zRumaO1jVRWddEmaeJQ5X1bDxYyRtbGmjy+Y+rwe1IYmBmMgOzUhiYmUxelvXHeiyZ3HR31OsTK4sxht0lHj7eV8G/P6vg/T3llNY0IgLj8jL5ztyzmDeqL6P69wrtl2dDNfzzOmsSy/l3wnnfh57wSzcpyer+COEqL2fmprPsWzP42uK13PyPtfz0C6O48dz806ZxoUHdDXx+68TQW9uO8Pa2I+wtqwWgby8XBYN7c9PMIRTkZzG8Xzoue+y7LYwxlNc2UVzZwKGqeoor6ymqrKfwqLXdWlRFeW3Tca9x2IT+GcktIT4wK3g7hbysZPpluI+/1JJqUe5pZMuharYUVbHxYCVr9x+lIvD59klzMW1ob+aMyGX22Tn0SQtzidHqQ/Dkl6F0O1z+fzDxK3H4CeLInRnymtS56W6W3Dyd7y75hLtf3sa+8lp+Nn/UaTHlXIO6i1hn7St5bn0hr205TEVtEw6bMG1oNjeem8/5w3PJy0rukhaCiNAnzUWfNBdj89ru76tr8nKoVXgXHq2nKHB71aellNQ0Ysyx/ZME+vZyMzAzmb693OT2cpGb7iY33dVyv2+6m17J9lO2FVTd0MyeEg97SmvZU+rh0yMeth6qoriqoWWf/OwU5ozI5Zz83kwZ0pv87JTIP48dr8CLt1kjO675J5w5N0Y/SRdK62v9sglRstPGw1+ZzK9e38Gjq/ayv7yO/104gaxTfKy1BnWcHSiv47lPCnn+kyL2ldfhdiQxb1Q/Lhrdl9ln5yTszKsUp50zc9M5Mze9zeebvH6Kq6zwLjxaT2FlMMjr2H64mpW7GvE0ntyn7rQn0bdViOemu8hMcZKV4iAr1dlyAjQzcD/Vaev2YDfG4Gn0UlFrdSFV1DZxuMr6mYO/wAqP1lPmaWx5jcMm5Gencs6Q3owZkMGYgRmMGtCr7Styh6O5Hna/DR8+DPvfh37j4It/gZzhUf6U3aTvKNj8L+tEaIh/z0lJwp2XjCQ/O5W7XtzC/D++xx+vmcikM7LiXGz3EdO6WRQjBQUFZu3atTE/bk9RVd/MK5uKeW59IWv3H0UEpg/N5sqJA7l4TD/SEzScY6220UtJTSMl1Q0cCWxb7lc3UlJj3a/p4CSpwyZkpjjp5baT6rKT4rSR6rST4rKT5rKR4rST7LBhtwkOWxIOm2BPCmxtSVa/ugF33SEyq7bhw0ZR9nR84sDnN9Q3+6hv8lHX5KO+2RpFU9dkPXa0zgrl8tommrz+NmsL9uEPzExmSJ80huWkcmZuGoN6p8SuK6i+Ej59E7a/CLuXQ3Md9BoI078NU26KyxVZusy//wqv3AG3b4KswWG/fMPBSr791HoOVzXwn/PO5huzh/bYrhARWWeMaXOVLG1Rx0izz8+qXaU8t76It7Yfocnr56zcNL5/8XCumDCQAZnJ3V1il0t12Rnisnc69tXr81NZ30xlXZN1ArS26bj7lXVNVDd4qWv0Utvk40hNA3VlPmqbvNQ2+qhv9uHzt9/gGCt7edJ5L73EOkn7sm8qtzd/Gx9W/3+SWN8gkp02Upw2kh3Wtm8vNyP79yI7zUl2qpPeqa6W2317uclJc5EUrxOsNUdg5yuw/WX4bBX4myGtH4y/GkZeCvkzE39URyj6jbW2R7ZEFNQTBmXyym2zuPP5zfzmjZ28sfUwv/nSeIb3a/ubYE+lLeooGGPYeqia59YX8eLGIso8TWSnOrlswgCumpjHmIEhnrVXUfP7Dd7AqBevz9Dk8+P1+6F0J32XXoHfmUb1JQ/jLFxD2nv30jjqy9R/4UHcTjsue1Ji/D01emDbC7DhKatbAwNZQ6xgHnkpDCywRkqcSho9cF8enP8jOP8HUR3qlU3F/PSFLVTXN3P9jHxu/9xZCdu12BZtUcfYvrJaXttymOc/KWLnkRqctiQ+NyqXqybmcd7wHB390A2SkgRnkuC0t/rsG2vgta+BzUHSDS/Ru/cQGDEL7H5c796Ha9hMmHx91xVpjNVt4fcF7vvAUwKHN8Onb8H2l6C5FnoPhfN+AKMug9xRPWOoXaRcadbPe2Rz1If6wrj+TBvamwfe3Mlj73/GCxuKuOX8M/nK1DN6/PrW2qIOgTGGXUc8vL7lMK9tKWbH4RoAJp6RyRcn5XHpuAFkpPSc39ynBb/fWuti2/Nw3YswZNbxzz1xJRz8GL6+AnJHxOY9yz6FXW9AbSnUlVvDzuoqArcrrPv+dvrj3Zkwcj5MuBbOmHZqh/OJ/nkdFG+C2zfE7JCbCiu579UdrNlbTm66i5tmDmHhlEFkpiTu6JCOWtQa1O2oqG3igz1lvL+7jNWfllF4tB4RKBicxcVj+nPxmH4MPA37nXsEn9catrbxKZh7F8y64+R9ag7DIzPB7ob/eB0y8iJ7r/qjsOVfsOFpKAr8m7c5Ibm3dbHY4DZ4251xbIlRSYLUHOg9DAZMSIylR7vDyt/AinvgR4Xgim3f8po95fx++S4+3FuB25HEpeMGcOWkgUwdkp1wE7g0qDvh81szxTYVVrK5qIp1+4+y9VA1AOluO9OHZjP77BwuHN2X3PQeutyi32+17DyHrfuudOiVB7ZOer/8ga/n3gbwNVsntXzNx24n94asfHAkwOfibYS978LKX1uhecGPYfb32m+dFm+Ex+dbYXn5g50vAepttNZ0ProPSrZZLfJP3wRfk9VFMeEaGPNFSO9/erWIo7XzdXh6IXz1eRh2QVzeYntxNYs/2MdLGw9R2+Sjby8Xc0b05fzhOcwYlp0QI7GiDmoRuRj4PWAD/mKM6fDyEIka1PVNPvZXWOtmfFZWx2dlHvaW1rL1UDX1zVa/YZrLztiBGZx7ZjbnntmHsQMzuma4T1MdlO+G2hKoLbO+MnvrrTUcfI3WVgRSsq1gSc4E47eGbtUchppDVhA3N1ih6m0I3K63jl1bagVra0l2K2R7D7NWWEvNsQK45hAc3W8FUlXhya87iVgt0t5Dj/3pNeBYWBljhZy3wdoan1W7P7A1BjCB24H7xmc97/ce29fvDTzutX7xBO8311t1lu6wQjNjkLW05/hFnX/uBz6EpTdBdSHkTbFO2KVmW59NUx1UF1mfw9F9gYkZrf6/ZJwBIy6xRmL0H6/hHKmGaniwAFL6wM0r4jrcsL7Jx/IdR3h5YzHv7S7D0+hFBIb3TWfS4CzOzk1jWG4aZ+am0a+Xu0tPMkcV1CJiA3YB84BC4N/A1caYbe29JtKgLvc0EhxlZTAt/ycMgf/rfj9NXj9NPmvb6A3c91rrW1TXN1PT4KWmoZnqBi/ltU2UBsbqllY3UnPCBIw+aS6G9kll1IBejB+UwdiBmQztkxrbIVfBkDr2ADRUWcFSvAEOfQKHNkDJdit02pLksP7xGr91MqotqTlWiDuSwZ5s7e8IblMgLddq6aX3s75y1x+Fir1QvsfaVuw9duyUbMgcbIV41mArhB0p1lf6JLu1tTmsr+q15VCx5/jj1FdE+aGJVWOS3XoPsVnbJJv1WOv7YrO6L3oNsCZ9DJ4BZ84Lb+3lpjr48P+s1nHxRusXSlD6gMDnEPgsgrezz7ICXcXGrjfgqS/DzDvgc3d1yVs2ef2s23+Ujz4rZ93+o2w8WHncwmepThtnZKfSJ81JTpqLPuku+qQ5yUx2kuIKjOd32kh1WSOHHLYk3A4b/TIi+3YZbVBPB35ujLkocP9HAMaY+9p7TaRBPfKnr7e0bKMhYrWMe6c6A7Pf3OSku8hJdzGodwpD+6QyODula77u1FfC/R2MD03Jhv4TYOAk6DvGCtLUHGsJSEcy2FzHD8lqqrVa3A2VVmi50q3xtdEuCm+MFVBJjs67QzpTf9TqLmkh1i8Mu9uqM8luBbEkWUEr0up+ArRKvU1Wa93uPvWGwyWyF74N+1bDLWvA2fUXCTDGUOppZE9JLbtLPewp8XCwoo4yTyNlniZKPY1tTnxqrU+ak7U/mRfR+0c7PG8gcLDV/UJgahtvcjNwc+CuR0R2hltoiPoAZXE6dlc4of5q4DNgWTeVE7ZT7PPvcU79+r+b0BcH6LD+/YD8NOJjt9uii9k4amPMo8CjsTpee0RkbXu/dXoCrb97af3dS+uPTCjf64qAQa3u5wUeU0op1QVCCep/A2eJyBARcQKLgBfjW5ZSSqmgTrs+jDFeEfk28AbW8LzHjDFb415Z++LevRJnWn/30vq7l9YfgbhMeFFKKRU7OvZIKaUSnAa1UkoluIQPahFZICJbRcQvIu0OixGRfSKyWUQ2iEjCzF8Po/6LRWSniOwWkR92ZY0dEZHeIvKWiHwa2LZ5vSMR8QU++w0i0u0nmzv7PEXEJSJLAs9/JCL53VBmu0Ko/wYRKW31mX+tO+psi4g8JiIlIrKlnedFRP4Q+Nk2icikrq6xIyHUf76IVLX67H8W96KMMQn9BxgJDAfeBQo62G8f0Ke7642kfqyTtHuAoYAT2AiM6u7aA7X9Gvhh4PYPgfvb2c/T3bWG83kCtwKPBG4vApZ0d91h1n8D8GB319pO/bOBScCWdp6/BHgNEGAa8FF31xxm/ecDL3dlTQnfojbGbDfGxGuWY9yFWP85wG5jzF5jTBPwDHB5/KsLyeXA4sDtxcAV3VdKyEL5PFv/XEuBuZIQl3kBEvvfQ6eMMauAjhZ8uRz4u7F8CGSKSP+uqa5zIdTf5RI+qMNggDdFZF1gOntP0tY0/YHdVMuJ+hpjigO3DwN929nPLSJrReRDEbmia0prVyifZ8s+xhgvUAUkyipLof57+GKg62CpiAxq4/lElcj/3kM1XUQ2ishrIjI63m+WEJfiEpG3gX5tPPVjY8wLIR5mpjGmSERygbdEZEfgN2Pcxaj+btNR/a3vGGOMiLQ3nnNw4PMfCrwjIpuNMXtiXatq8RLwtDGmUUS+gfXtYE4313S6WI/1790jIpcAzwNnxfMNEyKojTGfi8ExigLbEhFZhvX1sUuCOgb1d+s0/Y7qF5EjItLfGFMc+Hpa0tZ+rT7/vSLyLjARq5+1O4TyeQb3KRQRO5ABlHdNeZ3qtH5jTOta/4J1LqGn6NHLUhhjqlvdflVE/k9E+hhj4rZY1inR9SEiqSKSHrwNXAi0ecY2QSXyNP0XgeAVYK8HTvqGICJZIuIK3O4DnAu0u155Fwjl82z9c30JeMcEzhQlgE7rP6FP9zJgexfWF60XgesCoz+mAVWtutcSnoj0C57PEJFzsHI0vr/ku/sMawhnYK/E6sNqBI4AbwQeHwC8Grg9FOvM+EZgK1aXQ7fXHmr9gfuXYF2gYU+C1Z8NLAc+Bd4GegceL8C62g/ADGBz4PPfDNyUAHWf9HkCdwOXBW67gWeB3cDHwNDurjnM+u8L/FvfCKwARnR3za1qfxooBpoD//ZvAr4JfDPwvAAPBX62zXQwmitB6/92q8/+Q2BGvGvSKeRKKZXgTomuD6WUOpVpUCulVILToFZKqQSnQa2UUglOg1oppRKcBrVSMRJY0e7B7q5DnXo0qJVSKsFpUKuEISLXBRYZ2igi/xCRfBF5J/DYchE5I7Df4yLycGABqL2B9YEfE5HtIvJ4q+N5ROR3Yq0HvlxEcgKPTwi8dpOILJPAGtsi8q4E1gwXkT4isi9w+wYReU5EXhdrXe5ft3qPG0Vkl4h8jDUjU6mY06BWCSGwAtlPgDnGmPHA7cAfgcXGmHHAk8AfWr0kC5gO/CfWlOTfAaOBsSIyIbBPKrDWGDMaWAncFXj878APAsfd3OrxjkwAFgJjgYUiMigwjfsXWAE9ExgV/k+uVOc0qFWimAM8awIL2xhjKrCC+KnA8//ACsOgl4w1rXYzcMQYs9kY48ea2psf2McPLAncfgKYKSIZQKYxZmXg8cVYC8V3ZrkxpsoY04C1jslgYCrwrjGm1FjrRi/p8AhKRUiDWvVUjYGtv9Xt4P32VoXsbL0EL8f+T7jbeT8AXwfvoVTMaVCrRPEOsEBEssG6ViPwAdbKcQBfAVaHecwkrJXxAK4B3jPGVAFHRWRW4PGvYnWLgHU5t8mB28HXdeQj4DwRyRYRB7AgzPqUCom2ClRCMMZsFZF7gZUi4gM+AW4D/iYi3wNKgRvDPGwtcI6I/ARrHe2FgcevBx4RkRRgb6vjPgD8M3CFoFdCqLlYRH4OrAEqgQ1h1qdUSHT1PHXKEhGPMSatu+tQKlra9aGUUglOW9RKKZXgtEWtlFIJToNaKaUSnAa1UkolOA1qpZRKcBrUSimV4P4/si9M642JycAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot sentiment distribution for positive and negative reviews\n",
    "\n",
    "import seaborn as sns\n",
    "\n",
    "for x in [0, 1]:\n",
    "    subset = reviews_df[reviews_df['is_good_review'] == x]\n",
    "    \n",
    "    # Draw the density plot\n",
    "    if x == 0:\n",
    "        label = \"Bad reviews\"\n",
    "    else:\n",
    "        label = \"Good reviews\"\n",
    "    sns.distplot(subset['compound'], hist = False, label = label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# feature selection\n",
    "label = \"is_good_review\"\n",
    "ignore_cols = [label, \"Review_Text\", \"review_clean\", \"Reviewer_Location\",\"Branch\",\"\"]\n",
    "features = [c for c in reviews_df.columns if c not in ignore_cols]\n",
    "\n",
    "# split the data into train and test\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(reviews_df[features], reviews_df[label], test_size = 0.20, random_state = 42)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Review_ID              int64\n",
       "Rating                 int64\n",
       "Reviewer_Location     object\n",
       "Review_Text           object\n",
       "Branch                object\n",
       "                      ...   \n",
       "word_yrs             float64\n",
       "word_yum             float64\n",
       "word_yummy           float64\n",
       "word_zero            float64\n",
       "word_zone            float64\n",
       "Length: 2150, dtype: object"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reviews_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestClassifier(random_state=42)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# train a random forest classifier\n",
    "rf = RandomForestClassifier(n_estimators = 100, random_state = 42)\n",
    "rf.fit(X_train, y_train)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>feature</th>\n",
       "      <th>importance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Rating</td>\n",
       "      <td>0.276159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>compound</td>\n",
       "      <td>0.042132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>neg</td>\n",
       "      <td>0.031856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>pos</td>\n",
       "      <td>0.030853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>doc2vec_vector_0</td>\n",
       "      <td>0.012924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>neu</td>\n",
       "      <td>0.011619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>doc2vec_vector_3</td>\n",
       "      <td>0.007798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>916</th>\n",
       "      <td>word_hour</td>\n",
       "      <td>0.007187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1199</th>\n",
       "      <td>word_money</td>\n",
       "      <td>0.006479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>words</td>\n",
       "      <td>0.006091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>827</th>\n",
       "      <td>word_great</td>\n",
       "      <td>0.005899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>368</th>\n",
       "      <td>word_close</td>\n",
       "      <td>0.004498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1359</th>\n",
       "      <td>word_pay</td>\n",
       "      <td>0.004450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1415</th>\n",
       "      <td>word_poor</td>\n",
       "      <td>0.004386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>characters</td>\n",
       "      <td>0.004354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2063</th>\n",
       "      <td>word_waste</td>\n",
       "      <td>0.004242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1599</th>\n",
       "      <td>word_rude</td>\n",
       "      <td>0.004023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>doc2vec_vector_4</td>\n",
       "      <td>0.003879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Review_ID</td>\n",
       "      <td>0.003766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>doc2vec_vector_1</td>\n",
       "      <td>0.003746</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               feature  importance\n",
       "1               Rating    0.276159\n",
       "7             compound    0.042132\n",
       "4                  neg    0.031856\n",
       "6                  pos    0.030853\n",
       "10    doc2vec_vector_0    0.012924\n",
       "5                  neu    0.011619\n",
       "13    doc2vec_vector_3    0.007798\n",
       "916          word_hour    0.007187\n",
       "1199        word_money    0.006479\n",
       "9                words    0.006091\n",
       "827         word_great    0.005899\n",
       "368         word_close    0.004498\n",
       "1359          word_pay    0.004450\n",
       "1415         word_poor    0.004386\n",
       "8           characters    0.004354\n",
       "2063        word_waste    0.004242\n",
       "1599         word_rude    0.004023\n",
       "14    doc2vec_vector_4    0.003879\n",
       "0            Review_ID    0.003766\n",
       "11    doc2vec_vector_1    0.003746"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# show feature importance\n",
    "feature_importances_df = pd.DataFrame({\"feature\": features, \"importance\": rf.feature_importances_}).sort_values(\"importance\", ascending = False)\n",
    "feature_importances_df.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ROC curve\n",
    "\n",
    "from sklearn.metrics import roc_curve, auc, roc_auc_score\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "y_pred = [x[1] for x in rf.predict_proba(X_test)]\n",
    "fpr, tpr, thresholds = roc_curve(y_test, y_pred, pos_label = 1)\n",
    "\n",
    "roc_auc = auc(fpr, tpr)\n",
    "\n",
    "plt.figure(1, figsize = (10, 7))\n",
    "lw = 6\n",
    "plt.plot(fpr, tpr, color='darkorange',\n",
    "         lw=lw, label='ROC curve (area = %0.2f)' % roc_auc)\n",
    "plt.plot([0, 1], linestyle='--')\n",
    "plt.plot([0, 0], [1, 0] , c=\".7\"), plt.plot([1, 1] , c=\".7\")\n",
    "plt.xlabel('False Positive Rate')\n",
    "plt.ylabel('True Positive Rate')\n",
    "plt.title('Receiver operating characteristic example')\n",
    "plt.legend(loc=\"lower right\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: funcsigs in /Users/jessicaramosmolina/opt/anaconda3/envs/PythonData/lib/python3.6/site-packages (1.0.2)\n",
      "\u001b[33mWARNING: You are using pip version 20.3.3; however, version 21.0.1 is available.\n",
      "You should consider upgrading via the '/Users/jessicaramosmolina/opt/anaconda3/envs/PythonData/bin/python -m pip install --upgrade pip' command.\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!pip install funcsigs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '2-class Precision-Recall curve: AP=1.00')"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from funcsigs import signature\n",
    "from sklearn.metrics import average_precision_score, precision_recall_curve\n",
    "\n",
    "average_precision = average_precision_score(y_test, y_pred)\n",
    "\n",
    "precision, recall, _ = precision_recall_curve(y_test, y_pred)\n",
    "\n",
    "# In matplotlib < 1.5, plt.fill_between does not have a 'step' argument\n",
    "step_kwargs = ({'step': 'post'}\n",
    "               if 'step' in signature(plt.fill_between).parameters\n",
    "               else {})\n",
    "\n",
    "plt.figure(1, figsize = (15, 10))\n",
    "plt.step(recall, precision, color='b', alpha=0.2,\n",
    "         where='post')\n",
    "plt.fill_between(recall, precision, alpha=0.2, color='b', **step_kwargs)\n",
    "\n",
    "plt.xlabel('Recall')\n",
    "plt.ylabel('Precision')\n",
    "plt.ylim([0.0, 1.05])\n",
    "plt.xlim([0.0, 1.0])\n",
    "plt.title('2-class Precision-Recall curve: AP={0:0.2f}'.format(average_precision))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# from sklearn import datasets\n",
    "# from sklearn.tree import DecisionTreeClassifier\n",
    "# from sklearn.linear_model import LogisticRegression\n",
    "# from sklearn.metrics import roc_curve, roc_auc_score\n",
    "# from sklearn.model_selection import train_test_split\n",
    "# import matplotlib.pyplot as plt\n",
    "\n",
    "# X_train, X_test, y_train, y_test = train_test_split(reviews_df[features], reviews_df[label], test_size = 0.20, random_state = 42)\n",
    "\n",
    "# clf_tree = DecisionTreeClassifier();\n",
    "# clf_reg = LogisticRegression();\n",
    "\n",
    "# clf_tree.fit(X_train, y_train); \n",
    "# clf_reg.fit(X_train, y_train);\n",
    "\n",
    "# y_score1 = clf_tree.predict_proba(X_test)[:,1]\n",
    "# y_score2 = clf_reg.predict_proba(X_test)[:,1]\n",
    "\n",
    "# false_positive_rate1, true_positive_rate1, threshold1 = roc_curve(y_test, y_score1)\n",
    "\n",
    "# print('roc_auc_score for DecisionTree: ', roc_auc_score(y_test, y_score1))\n",
    "\n",
    "# plt.figure(1, figsize=(10,10))\n",
    "# plt.title('Receiver Operating Characteristic - DecisionTree')\n",
    "# plt.plot(false_positive_rate1, true_positive_rate1)\n",
    "# plt.plot(color='blue', label='ROC curve (area = %0.2f)' % roc_auc)\n",
    "# plt.plot([0, 1], ls=\"--\")\n",
    "# plt.plot([0, 0], [1, 0] , c=\".7\"), plt.plot([1, 1] , c=\".7\")\n",
    "# plt.ylabel('True Positive Rate')\n",
    "# plt.xlabel('False Positive Rate')\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}