02_Document Feature Engineering.ipynb

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   "source": [
    "# Document Analysis in Python\n",
    "In this notebook we will cover:\n",
    "- Reading document data into memory\n",
    "- Creating bag of words features\n",
    "- Creating smoothed tf-idf features"
   ]
  },
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   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
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     "output_type": "stream",
     "text": [
      "{'status': 'OK', 'response': {'docs': [{'word_count': 0, 'multimedia': [], 'type_of_material': 'SectionFront', '_id': '53c00c2038f0d85f5c71ae10', 'headline': {'main': 'World Cup', 'print_headline': None, 'name': None, 'sub': None, 'seo': None, 'content_kicker': None, 'kicker': None}, 'score': 2.3329575, 'keywords': [], 'blog': {}, 'document_type': 'sectionfront', 'web_url': 'https://www.nytimes.com/pages/sports/worldcup/index.html', 'snippet': ''}, {'word_count': 548, 'uri': 'nyt://article/b9596925-8224-5c9a-b31c-d4f84d329c2a', 'type_of_material': 'News', 'snippet': 'The Americans defeated Belarus, 3-2, after CoCo Vandeweghe and Shelby Rogers won the deciding doubles match to claim their first title since 2000.', '_id': '5a08d3fe7c459f246b634065', 'blog': {}, 'document_type': 'article', 'source': 'The New York Times', 'web_url': 'https://www.nytimes.com/2017/11/12/sports/tennis/fed-cup-final.html', 'pub_date': '2017-11-12T23:06:16+0000', 'multimedia': [{'legacy': 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'height': 50, 'width': 75, 'type': 'image', 'caption': None, 'credit': None, 'subType': 'videoThumb', 'crop_name': 'videoThumb'}, {'legacy': {}, 'rank': 0, 'subtype': 'watch268', 'url': 'images/2017/12/16/sports/16FOAMweb/16FOAMweb-watch268.jpg', 'height': 303, 'width': 272, 'type': 'image', 'caption': None, 'credit': None, 'subType': 'watch268', 'crop_name': 'watch268'}, {'legacy': {}, 'rank': 0, 'subtype': 'watch308', 'url': 'images/2017/12/16/sports/16FOAMweb/16FOAMweb-watch308.jpg', 'height': 348, 'width': 312, 'type': 'image', 'caption': None, 'credit': None, 'subType': 'watch308', 'crop_name': 'watch308'}, {'legacy': {}, 'rank': 0, 'subtype': 'windowsTile336H', 'url': 'images/2017/12/16/sports/16FOAMweb/16FOAMweb-windowsTile336H.jpg', 'height': 336, 'width': 694, 'type': 'image', 'caption': None, 'credit': None, 'subType': 'windowsTile336H', 'crop_name': 'windowsTile336H'}], 'score': 1.5818497, 'headline': {'main': 'FIFA in Hot Water Over Foam', 'print_headline': 'Vanishing Spray Lands FIFA in Court Trouble', 'name': None, 'sub': None, 'seo': None, 'content_kicker': None, 'kicker': None}, 'keywords': [{'major': 'N', 'rank': 1, 'value': 'Soccer', 'name': 'subject'}, {'major': 'N', 'rank': 2, 'value': 'International Federation of Association Football (FIFA)', 'name': 'organizations'}, {'major': 'N', 'rank': 3, 'value': 'Infantino, Gianni', 'name': 'persons'}, {'major': 'N', 'rank': 4, 'value': 'Valcke, Jerome', 'name': 'persons'}, {'major': 'N', 'rank': 5, 'value': 'World Cup (Soccer)', 'name': 'subject'}, {'major': 'N', 'rank': 6, 'value': 'Foam', 'name': 'subject'}], 'new_desk': 'Sports', 'type_of_material': 'News', 'byline': {'original': 'By TARIQ PANJA', 'person': [{'middlename': None, 'rank': 1, 'qualifier': None, 'title': None, 'firstname': 'Tariq', 'lastname': 'PANJA', 'organization': '', 'role': 'reported'}], 'organization': None}, 'snippet': 'A court in Brazil has demanded FIFA immediately stop issuing a vanishing spray to referees after a patent dispute with its inventor.'}], 'meta': {'time': 425, 'hits': 80252, 'offset': 0}}, 'copyright': 'Copyright (c) 2018 The New York Times Company. All Rights Reserved.'}\n"
     ]
    }
   ],
   "source": [
    "import requests\n",
    "import json\n",
    "from contextlib import closing\n",
    "\n",
    "# get API key saved on hardrive\n",
    "with open('../NYTimesAPI.txt') as f:\n",
    "    api_key = f.read() # read in my private key (sorry, not in this repo ¯\\_(ツ)_/¯ )\n",
    "    \n",
    "# make base URL and dictionary of get request key/values\n",
    "url = \"https://api.nytimes.com/svc/search/v2/articlesearch.json\"\n",
    "payload = {'api-key': api_key, 'q':'world cup'} # key/values for get request (look up in api, there are lots)\n",
    "\n",
    "# Perform the actual request\n",
    "with closing(requests.get(url, params=payload)) as r:\n",
    "    articles = r.json()\n",
    "    print(articles)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# OR we can load an example query like this\n",
    "# run this block of code if you can't run anything else\n",
    "import json \n",
    "with open('data/nytime.json') as f:\n",
    "    articles = json.loads(f.read())\n",
    "    \n",
    "articles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['',\n",
       " 'The Americans defeated Belarus, 3-2, after CoCo Vandeweghe and Shelby Rogers won the deciding doubles match to claim their first title since 2000.',\n",
       " 'Five months after declaring its interest in hosting the 2026 World Cup, Morocco hasn’t said much about how it proposes to stage the world’s most-watched sporting event.',\n",
       " '<p>News about the World Cup, including commentary and archival articles published in The New York Times.</p>',\n",
       " '<p>News about the World Cup, including commentary and archival articles published in The New York Times.</p>',\n",
       " 'The 5-year-old is one of the most popular horses in Japan, and he will be retiring at the end of the year.',\n",
       " \"News about Breeders' Cup World Thoroughbred Championships, including commentary and archival articles published in The New York Times.\",\n",
       " 'Soccer’s scandal-marred governing body pays nonexecutive board members more than some of the biggest companies in the world, a concern to governance experts.',\n",
       " 'Shiffrin, best known for the more technical slalom and giant slalom events, bested Lindsey Vonn, who has dominated the event but ended 12th.',\n",
       " 'A court in Brazil has demanded FIFA immediately stop issuing a vanishing spray to referees after a patent dispute with its inventor.']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get the summary text from each article\n",
    "#  lead_paragraph  is no snippet\n",
    "summary_text = [x['snippet'] for x in articles['response']['docs']]\n",
    "summary_text"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Converting document data into different representations\n",
    "First lets go through and count the unique words in each opening sentence (that is what the NYTimes give us for free).\n",
    "- http://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.CountVectorizer.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "count_vect = CountVectorizer() # an object capable of counting words in a document!\n",
    "\n",
    "# count_vect.fit(summary_text)\n",
    "# count_vect.transform(summary_text)\n",
    "bag_words = count_vect.fit_transform(summary_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(10, 118)\n",
      "=========\n",
      "  (0, 1)\t1\n",
      "  (0, 91)\t1\n",
      "  (0, 105)\t1\n",
      "  (0, 41)\t1\n",
      "  (0, 102)\t1\n",
      "  (0, 21)\t1\n",
      "  (0, 106)\t1\n",
      "  (0, 66)\t1\n",
      "  (0, 34)\t1\n",
      "  (0, 28)\t1\n",
      "  (0, 114)\t1\n",
      "  (0, 86)\t1\n",
      "  (0, 89)\t1\n",
      "  (0, 6)\t1\n",
      "  (0, 107)\t1\n",
      "  (0, 22)\t1\n",
      "  (0, 4)\t1\n",
      "  (0, 11)\t1\n",
      "  (0, 30)\t1\n",
      "  (0, 5)\t1\n",
      "  (0, 101)\t2\n"
     ]
    }
   ],
   "source": [
    "print(bag_words.shape) # this is a sparse matrix\n",
    "print('=========')\n",
    "print(bag_words[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Self Test: ML01b.3: \n",
    "Do you expect the vocabulary from the articles above to be:\n",
    "- A. Greater than 1M words\n",
    "- B. Greater than 10,000 words\n",
    "- C. Fewer than 10,000 words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "118\n",
      "{'dispute': 32, 'declaring': 29, 'vandeweghe': 107, 'york': 117, 'horses': 50, 'thoroughbred': 103, 'issuing': 59, 'has': 47, 'how': 52, 'and': 6, 'event': 37, 'since': 91, 'hasn': 48, 'proposes': 82, 'title': 105, 'championships': 20, 'year': 116, 'in': 54, 'cup': 27, 'immediately': 53, 'the': 101, 'hosting': 51, 'best': 12, 'marred': 65, 'match': 66, 'interest': 56, 'published': 83, 'bested': 13, 'sporting': 95, 'body': 16, 'nonexecutive': 75, 'end': 35, 'claim': 21, 'pays': 80, 'biggest': 14, 'slalom': 92, 'soccer': 93, 'retiring': 85, 'giant': 44, 'members': 67, 'japan': 62, 'to': 106, 'companies': 24, 'with': 113, 'of': 76, 'known': 63, 'than': 100, 'new': 73, 'will': 112, 'five': 42, 'he': 49, 'at': 9, 'experts': 39, 'americans': 5, 'governing': 46, 'watched': 110, 'including': 55, 'rogers': 86, 'for': 43, 'coco': 22, 'articles': 8, 'some': 94, 'commentary': 23, 'morocco': 70, 'court': 26, 'patent': 79, 'most': 71, 'one': 78, 'belarus': 11, 'technical': 99, 'stop': 98, 'after': 4, 'brazil': 17, 'old': 77, 'said': 87, 'defeated': 30, '2026': 2, 'times': 104, 'news': 74, 'popular': 81, 'shelby': 89, 'archival': 7, 'events': 38, 'their': 102, 'won': 114, 'ended': 36, 'about': 3, 'vonn': 109, 'be': 10, 'referees': 84, 'first': 41, 'spray': 96, 'concern': 25, 'demanded': 31, 'lindsey': 64, 'stage': 97, 'vanishing': 108, 'months': 68, 'breeders': 18, 'doubles': 34, 'fifa': 40, 'world': 115, 'more': 69, 'it': 60, 'governance': 45, 'its': 61, 'who': 111, '12th': 0, 'dominated': 33, 'inventor': 57, '2000': 1, 'board': 15, 'shiffrin': 90, 'is': 58, 'scandal': 88, 'but': 19, 'deciding': 28, 'much': 72}\n"
     ]
    }
   ],
   "source": [
    "print(len(count_vect.vocabulary_))\n",
    "print(count_vect.vocabulary_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array(['2000', 'since', 'title', 'first', 'their', 'claim', 'to', 'match',\n",
       "        'doubles', 'deciding', 'won', 'rogers', 'shelby', 'and',\n",
       "        'vandeweghe', 'coco', 'after', 'belarus', 'defeated', 'americans',\n",
       "        'the'],\n",
       "       dtype='<U13')]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# we can still look at the data using an inverse transform\n",
    "# but we lose the ordering of the words (after all its just a bag of wrods model)\n",
    "count_vect.inverse_transform(bag_words[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# now let's create a pandas API out of this\n",
    "import pandas as pd\n",
    "\n",
    "pd.options.display.max_columns = 999\n",
    "df = pd.DataFrame(data=bag_words.toarray(),columns=count_vect.get_feature_names())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   12th  2000  2026  about  after  americans  and  archival  articles  at  be  \\\n",
       "0     0     0     0      0      0          0    0         0         0   0   0   \n",
       "1     0     1     0      0      1          1    1         0         0   0   0   \n",
       "2     0     0     1      1      1          0    0         0         0   0   0   \n",
       "3     0     0     0      1      0          0    1         1         1   0   0   \n",
       "4     0     0     0      1      0          0    1         1         1   0   0   \n",
       "5     0     0     0      0      0          0    1         0         0   1   1   \n",
       "6     0     0     0      1      0          0    1         1         1   0   0   \n",
       "7     0     0     0      0      0          0    0         0         0   0   0   \n",
       "8     1     0     0      0      0          0    1         0         0   0   0   \n",
       "9     0     0     0      0      1          0    0         0         0   0   0   \n",
       "\n",
       "   belarus  best  bested  biggest  board  body  brazil  breeders  but  \\\n",
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       "\n",
       "   championships  claim  coco  commentary  companies  concern  court  cup  \\\n",
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       "8              0      0     0           0          0        0      0    0   \n",
       "9              0      0     0           0          0        0      1    0   \n",
       "\n",
       "   deciding  declaring  defeated  demanded  dispute  dominated  doubles  end  \\\n",
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       "1         1          0         1         0        0          0        1    0   \n",
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       "8         0          0         0         0        0          1        0    0   \n",
       "9         0          0         0         1        1          0        0    0   \n",
       "\n",
       "   ended  event  events  experts  fifa  first  five  for  giant  governance  \\\n",
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       "9      0      0       0        0     1      0     0    0      0           0   \n",
       "\n",
       "   governing  has  hasn  he  horses  hosting  how  immediately  in  including  \\\n",
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       "9          0    1     0   0       0        0    0            1   1          0   \n",
       "\n",
       "   interest  inventor  is  issuing  it  its  japan  known  lindsey  marred  \\\n",
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       "\n",
       "   match  members  months  more  morocco  most  much  new  news  nonexecutive  \\\n",
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       "\n",
       "   of  old  one  patent  pays  popular  proposes  published  referees  \\\n",
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       "\n",
       "   retiring  rogers  said  scandal  shelby  shiffrin  since  slalom  soccer  \\\n",
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       "5         1       0     0        0       0         0      0       0       0   \n",
       "6         0       0     0        0       0         0      0       0       0   \n",
       "7         0       0     0        1       0         0      0       0       1   \n",
       "8         0       0     0        0       0         1      0       2       0   \n",
       "9         0       0     0        0       0         0      0       0       0   \n",
       "\n",
       "   some  sporting  spray  stage  stop  technical  than  the  their  \\\n",
       "0     0         0      0      0     0          0     0    0      0   \n",
       "1     0         0      0      0     0          0     0    2      1   \n",
       "2     0         1      0      1     0          0     0    2      0   \n",
       "3     0         0      0      0     0          0     0    2      0   \n",
       "4     0         0      0      0     0          0     0    2      0   \n",
       "5     0         0      0      0     0          0     0    4      0   \n",
       "6     0         0      0      0     0          0     0    1      0   \n",
       "7     1         0      0      0     0          0     1    2      0   \n",
       "8     0         0      0      0     0          1     0    2      0   \n",
       "9     0         0      1      0     1          0     0    0      0   \n",
       "\n",
       "   thoroughbred  times  title  to  vandeweghe  vanishing  vonn  watched  who  \\\n",
       "0             0      0      0   0           0          0     0        0    0   \n",
       "1             0      0      1   1           1          0     0        0    0   \n",
       "2             0      0      0   1           0          0     0        1    0   \n",
       "3             0      1      0   0           0          0     0        0    0   \n",
       "4             0      1      0   0           0          0     0        0    0   \n",
       "5             0      0      0   0           0          0     0        0    0   \n",
       "6             1      1      0   0           0          0     0        0    0   \n",
       "7             0      0      0   1           0          0     0        0    0   \n",
       "8             0      0      0   0           0          0     1        0    1   \n",
       "9             0      0      0   1           0          1     0        0    0   \n",
       "\n",
       "   will  with  won  world  year  york  \n",
       "0     0     0    0      0     0     0  \n",
       "1     0     0    1      0     0     0  \n",
       "2     0     0    0      2     0     0  \n",
       "3     0     0    0      1     0     1  \n",
       "4     0     0    0      1     0     1  \n",
       "5     1     0    0      0     2     0  \n",
       "6     0     0    0      1     0     1  \n",
       "7     0     0    0      1     0     0  \n",
       "8     0     0    0      0     0     0  \n",
       "9     0     1    0      0     0     0  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df # display the full bag of words matrix  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "news          3\n",
       "new           3\n",
       "including     3\n",
       "to            4\n",
       "about         4\n",
       "cup           4\n",
       "and           6\n",
       "world         6\n",
       "in            7\n",
       "the          17\n",
       "dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# print out 10 most common words in our data\n",
    "df.sum().sort_values()[-10:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12th            1\n",
       "referees        1\n",
       "proposes        1\n",
       "popular         1\n",
       "pays            1\n",
       "patent          1\n",
       "one             1\n",
       "old             1\n",
       "nonexecutive    1\n",
       "much            1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# print out 10 least common words in our data\n",
    "df.sum().sort_values()[:10] # small sample size means most words occur one time"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TF-IDF Conversion\n",
    "We have a very small sample of data, but lets covert to tf-idf for the sake of programming it. Recall that Tf-idf transformation (default in `sklearn` is):\n",
    "\n",
    "$$ \\text{tf}(t,d) = f_{td}\\text{, } t\\in T \\text{ and } d \\in D $$\n",
    "\n",
    "$$ \\text{idf}(t,d) = \\log{\\frac{|D|}{|n_t|}}\\text{, where } n_t=d\\in D \\text{ with } t\\in d $$\n",
    "\n",
    "$$\\text{tf-idf}(t,d)=\\text{tf}(t,d) \\cdot (1+\\text{idf}(t,d))$$\n",
    "\n",
    "- http://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.TfidfVectorizer.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "tfidf_vect = TfidfVectorizer() # an object capable of counting words in a document!\n",
    "\n",
    "tfidf_mat = tfidf_vect.fit_transform(summary_text) # that's it! its converted!!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "      <th>12th</th>\n",
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       "      <th>it</th>\n",
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       "      <th>lindsey</th>\n",
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       "      <th>new</th>\n",
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       "      <th>nonexecutive</th>\n",
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       "      <th>old</th>\n",
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       "      <th>patent</th>\n",
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       "      <th>scandal</th>\n",
       "      <th>shelby</th>\n",
       "      <th>shiffrin</th>\n",
       "      <th>since</th>\n",
       "      <th>slalom</th>\n",
       "      <th>soccer</th>\n",
       "      <th>some</th>\n",
       "      <th>sporting</th>\n",
       "      <th>spray</th>\n",
       "      <th>stage</th>\n",
       "      <th>stop</th>\n",
       "      <th>technical</th>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.139495</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.210963</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.179338</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.210963</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.210963</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.210963</td>\n",
       "      <td>0.210963</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.102836</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.210963</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.210963</td>\n",
       "      <td>0.179338</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.210963</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.210963</td>\n",
       "      <td>0.179338</td>\n",
       "      <td>0.210963</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.210963</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.210963</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.210963</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.210963</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.187298</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.139495</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.210963</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.250549</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.241136</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.195770</td>\n",
       "      <td>0.271223</td>\n",
       "      <td>0.271223</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.271223</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.241136</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.177766</td>\n",
       "      <td>0.271223</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.271223</td>\n",
       "      <td>0.271223</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.271223</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.323771</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.271223</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.216554</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.271223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.241136</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.195770</td>\n",
       "      <td>0.271223</td>\n",
       "      <td>0.271223</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.271223</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.241136</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.177766</td>\n",
       "      <td>0.271223</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.271223</td>\n",
       "      <td>0.271223</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.271223</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.323771</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.271223</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.216554</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.271223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.111233</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.207203</td>\n",
       "      <td>0.207203</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.207203</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.207203</td>\n",
       "      <td>0.207203</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.101003</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.207203</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.207203</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.176142</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.352283</td>\n",
       "      <td>0.207203</td>\n",
       "      <td>0.207203</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.207203</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.207203</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.367920</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.207203</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.414406</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.209854</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.170373</td>\n",
       "      <td>0.236038</td>\n",
       "      <td>0.236038</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.31737</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.31737</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.236038</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.209854</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.236038</td>\n",
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       "      <td>0.236038</td>\n",
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       "      <td>0.236038</td>\n",
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       "      <td>0.188461</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.236038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.227856</td>\n",
       "      <td>0.227856</td>\n",
       "      <td>0.227856</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.227856</td>\n",
       "      <td>0.227856</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.227856</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.227856</td>\n",
       "      <td>0.227856</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.111070</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.227856</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.227856</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.193698</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.227856</td>\n",
       "      <td>0.193698</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.227856</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.227856</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.227856</td>\n",
       "      <td>0.227856</td>\n",
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       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.227856</td>\n",
       "      <td>0.202296</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.150665</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.135306</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.212026</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.113822</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.212026</td>\n",
       "      <td>0.212026</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.212026</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.212026</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.212026</td>\n",
       "      <td>0.180242</td>\n",
       "      <td>0.212026</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.212026</td>\n",
       "      <td>0.212026</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.180242</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.212026</td>\n",
       "      <td>0.212026</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.180242</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.212026</td>\n",
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       "      <td>0.424053</td>\n",
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       "      <td>0.0000</td>\n",
       "      <td>0.212026</td>\n",
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       "      <td>0.188242</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.212026</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.212026</td>\n",
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       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.182140</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.2449</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.2449</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.2449</td>\n",
       "      <td>0.2449</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.2449</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.208188</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.2449</td>\n",
       "      <td>0.119379</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.2449</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.2449</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.208188</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.2449</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.2449</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.2449</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.2449</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.161935</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.2449</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.2449</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       12th      2000      2026     about     after  americans       and  \\\n",
       "0  0.000000  0.000000  0.000000  0.000000  0.000000   0.000000  0.000000   \n",
       "1  0.000000  0.229014  0.000000  0.000000  0.170324   0.229014  0.122941   \n",
       "2  0.000000  0.000000  0.210963  0.139495  0.156900   0.000000  0.000000   \n",
       "3  0.000000  0.000000  0.000000  0.241136  0.000000   0.000000  0.195770   \n",
       "4  0.000000  0.000000  0.000000  0.241136  0.000000   0.000000  0.195770   \n",
       "5  0.000000  0.000000  0.000000  0.000000  0.000000   0.000000  0.111233   \n",
       "6  0.000000  0.000000  0.000000  0.209854  0.000000   0.000000  0.170373   \n",
       "7  0.000000  0.000000  0.000000  0.000000  0.000000   0.000000  0.000000   \n",
       "8  0.212026  0.000000  0.000000  0.000000  0.000000   0.000000  0.113822   \n",
       "9  0.000000  0.000000  0.000000  0.000000  0.182140   0.000000  0.000000   \n",
       "\n",
       "   archival  articles        at        be   belarus      best    bested  \\\n",
       "0  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "1  0.000000  0.000000  0.000000  0.000000  0.229014  0.000000  0.000000   \n",
       "2  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "3  0.271223  0.271223  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "4  0.271223  0.271223  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "5  0.000000  0.000000  0.207203  0.207203  0.000000  0.000000  0.000000   \n",
       "6  0.236038  0.236038  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "7  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "8  0.000000  0.000000  0.000000  0.000000  0.000000  0.212026  0.212026   \n",
       "9  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "\n",
       "    biggest     board      body  brazil  breeders       but  championships  \\\n",
       "0  0.000000  0.000000  0.000000  0.0000   0.00000  0.000000        0.00000   \n",
       "1  0.000000  0.000000  0.000000  0.0000   0.00000  0.000000        0.00000   \n",
       "2  0.000000  0.000000  0.000000  0.0000   0.00000  0.000000        0.00000   \n",
       "3  0.000000  0.000000  0.000000  0.0000   0.00000  0.000000        0.00000   \n",
       "4  0.000000  0.000000  0.000000  0.0000   0.00000  0.000000        0.00000   \n",
       "5  0.000000  0.000000  0.000000  0.0000   0.00000  0.000000        0.00000   \n",
       "6  0.000000  0.000000  0.000000  0.0000   0.31737  0.000000        0.31737   \n",
       "7  0.227856  0.227856  0.227856  0.0000   0.00000  0.000000        0.00000   \n",
       "8  0.000000  0.000000  0.000000  0.0000   0.00000  0.212026        0.00000   \n",
       "9  0.000000  0.000000  0.000000  0.2449   0.00000  0.000000        0.00000   \n",
       "\n",
       "      claim      coco  commentary  companies   concern   court       cup  \\\n",
       "0  0.000000  0.000000    0.000000   0.000000  0.000000  0.0000  0.000000   \n",
       "1  0.229014  0.229014    0.000000   0.000000  0.000000  0.0000  0.000000   \n",
       "2  0.000000  0.000000    0.000000   0.000000  0.000000  0.0000  0.139495   \n",
       "3  0.000000  0.000000    0.271223   0.000000  0.000000  0.0000  0.241136   \n",
       "4  0.000000  0.000000    0.271223   0.000000  0.000000  0.0000  0.241136   \n",
       "5  0.000000  0.000000    0.000000   0.000000  0.000000  0.0000  0.000000   \n",
       "6  0.000000  0.000000    0.236038   0.000000  0.000000  0.0000  0.209854   \n",
       "7  0.000000  0.000000    0.000000   0.227856  0.227856  0.0000  0.000000   \n",
       "8  0.000000  0.000000    0.000000   0.000000  0.000000  0.0000  0.000000   \n",
       "9  0.000000  0.000000    0.000000   0.000000  0.000000  0.2449  0.000000   \n",
       "\n",
       "   deciding  declaring  defeated  demanded  dispute  dominated   doubles  \\\n",
       "0  0.000000   0.000000  0.000000    0.0000   0.0000   0.000000  0.000000   \n",
       "1  0.229014   0.000000  0.229014    0.0000   0.0000   0.000000  0.229014   \n",
       "2  0.000000   0.210963  0.000000    0.0000   0.0000   0.000000  0.000000   \n",
       "3  0.000000   0.000000  0.000000    0.0000   0.0000   0.000000  0.000000   \n",
       "4  0.000000   0.000000  0.000000    0.0000   0.0000   0.000000  0.000000   \n",
       "5  0.000000   0.000000  0.000000    0.0000   0.0000   0.000000  0.000000   \n",
       "6  0.000000   0.000000  0.000000    0.0000   0.0000   0.000000  0.000000   \n",
       "7  0.000000   0.000000  0.000000    0.0000   0.0000   0.000000  0.000000   \n",
       "8  0.000000   0.000000  0.000000    0.0000   0.0000   0.212026  0.000000   \n",
       "9  0.000000   0.000000  0.000000    0.2449   0.2449   0.000000  0.000000   \n",
       "\n",
       "        end     ended     event    events   experts    fifa     first  \\\n",
       "0  0.000000  0.000000  0.000000  0.000000  0.000000  0.0000  0.000000   \n",
       "1  0.000000  0.000000  0.000000  0.000000  0.000000  0.0000  0.229014   \n",
       "2  0.000000  0.000000  0.179338  0.000000  0.000000  0.0000  0.000000   \n",
       "3  0.000000  0.000000  0.000000  0.000000  0.000000  0.0000  0.000000   \n",
       "4  0.000000  0.000000  0.000000  0.000000  0.000000  0.0000  0.000000   \n",
       "5  0.207203  0.000000  0.000000  0.000000  0.000000  0.0000  0.000000   \n",
       "6  0.000000  0.000000  0.000000  0.000000  0.000000  0.0000  0.000000   \n",
       "7  0.000000  0.000000  0.000000  0.000000  0.227856  0.0000  0.000000   \n",
       "8  0.000000  0.212026  0.180242  0.212026  0.000000  0.0000  0.000000   \n",
       "9  0.000000  0.000000  0.000000  0.000000  0.000000  0.2449  0.000000   \n",
       "\n",
       "       five       for     giant  governance  governing       has      hasn  \\\n",
       "0  0.000000  0.000000  0.000000    0.000000   0.000000  0.000000  0.000000   \n",
       "1  0.000000  0.000000  0.000000    0.000000   0.000000  0.000000  0.000000   \n",
       "2  0.210963  0.000000  0.000000    0.000000   0.000000  0.000000  0.210963   \n",
       "3  0.000000  0.000000  0.000000    0.000000   0.000000  0.000000  0.000000   \n",
       "4  0.000000  0.000000  0.000000    0.000000   0.000000  0.000000  0.000000   \n",
       "5  0.000000  0.000000  0.000000    0.000000   0.000000  0.000000  0.000000   \n",
       "6  0.000000  0.000000  0.000000    0.000000   0.000000  0.000000  0.000000   \n",
       "7  0.000000  0.000000  0.000000    0.227856   0.227856  0.000000  0.000000   \n",
       "8  0.000000  0.212026  0.212026    0.000000   0.000000  0.180242  0.000000   \n",
       "9  0.000000  0.000000  0.000000    0.000000   0.000000  0.208188  0.000000   \n",
       "\n",
       "         he    horses   hosting       how  immediately        in  including  \\\n",
       "0  0.000000  0.000000  0.000000  0.000000       0.0000  0.000000   0.000000   \n",
       "1  0.000000  0.000000  0.000000  0.000000       0.0000  0.000000   0.000000   \n",
       "2  0.000000  0.000000  0.210963  0.210963       0.0000  0.102836   0.000000   \n",
       "3  0.000000  0.000000  0.000000  0.000000       0.0000  0.177766   0.271223   \n",
       "4  0.000000  0.000000  0.000000  0.000000       0.0000  0.177766   0.271223   \n",
       "5  0.207203  0.207203  0.000000  0.000000       0.0000  0.101003   0.000000   \n",
       "6  0.000000  0.000000  0.000000  0.000000       0.0000  0.154705   0.236038   \n",
       "7  0.000000  0.000000  0.000000  0.000000       0.0000  0.111070   0.000000   \n",
       "8  0.000000  0.000000  0.000000  0.000000       0.0000  0.000000   0.000000   \n",
       "9  0.000000  0.000000  0.000000  0.000000       0.2449  0.119379   0.000000   \n",
       "\n",
       "   interest  inventor        is  issuing        it       its     japan  \\\n",
       "0  0.000000    0.0000  0.000000   0.0000  0.000000  0.000000  0.000000   \n",
       "1  0.000000    0.0000  0.000000   0.0000  0.000000  0.000000  0.000000   \n",
       "2  0.210963    0.0000  0.000000   0.0000  0.210963  0.179338  0.000000   \n",
       "3  0.000000    0.0000  0.000000   0.0000  0.000000  0.000000  0.000000   \n",
       "4  0.000000    0.0000  0.000000   0.0000  0.000000  0.000000  0.000000   \n",
       "5  0.000000    0.0000  0.207203   0.0000  0.000000  0.000000  0.207203   \n",
       "6  0.000000    0.0000  0.000000   0.0000  0.000000  0.000000  0.000000   \n",
       "7  0.000000    0.0000  0.000000   0.0000  0.000000  0.000000  0.000000   \n",
       "8  0.000000    0.0000  0.000000   0.0000  0.000000  0.000000  0.000000   \n",
       "9  0.000000    0.2449  0.000000   0.2449  0.000000  0.208188  0.000000   \n",
       "\n",
       "      known   lindsey    marred     match   members    months      more  \\\n",
       "0  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "1  0.000000  0.000000  0.000000  0.229014  0.000000  0.000000  0.000000   \n",
       "2  0.000000  0.000000  0.000000  0.000000  0.000000  0.210963  0.000000   \n",
       "3  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "4  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "5  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "6  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "7  0.000000  0.000000  0.227856  0.000000  0.227856  0.000000  0.193698   \n",
       "8  0.212026  0.212026  0.000000  0.000000  0.000000  0.000000  0.180242   \n",
       "9  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "\n",
       "    morocco      most      much       new      news  nonexecutive        of  \\\n",
       "0  0.000000  0.000000  0.000000  0.000000  0.000000      0.000000  0.000000   \n",
       "1  0.000000  0.000000  0.000000  0.000000  0.000000      0.000000  0.000000   \n",
       "2  0.210963  0.179338  0.210963  0.000000  0.000000      0.000000  0.000000   \n",
       "3  0.000000  0.000000  0.000000  0.271223  0.271223      0.000000  0.000000   \n",
       "4  0.000000  0.000000  0.000000  0.271223  0.271223      0.000000  0.000000   \n",
       "5  0.000000  0.176142  0.000000  0.000000  0.000000      0.000000  0.352283   \n",
       "6  0.000000  0.000000  0.000000  0.236038  0.236038      0.000000  0.000000   \n",
       "7  0.000000  0.000000  0.000000  0.000000  0.000000      0.227856  0.193698   \n",
       "8  0.000000  0.000000  0.000000  0.000000  0.000000      0.000000  0.000000   \n",
       "9  0.000000  0.000000  0.000000  0.000000  0.000000      0.000000  0.000000   \n",
       "\n",
       "        old       one  patent      pays   popular  proposes  published  \\\n",
       "0  0.000000  0.000000  0.0000  0.000000  0.000000  0.000000   0.000000   \n",
       "1  0.000000  0.000000  0.0000  0.000000  0.000000  0.000000   0.000000   \n",
       "2  0.000000  0.000000  0.0000  0.000000  0.000000  0.210963   0.000000   \n",
       "3  0.000000  0.000000  0.0000  0.000000  0.000000  0.000000   0.271223   \n",
       "4  0.000000  0.000000  0.0000  0.000000  0.000000  0.000000   0.271223   \n",
       "5  0.207203  0.207203  0.0000  0.000000  0.207203  0.000000   0.000000   \n",
       "6  0.000000  0.000000  0.0000  0.000000  0.000000  0.000000   0.236038   \n",
       "7  0.000000  0.000000  0.0000  0.227856  0.000000  0.000000   0.000000   \n",
       "8  0.000000  0.000000  0.0000  0.000000  0.000000  0.000000   0.000000   \n",
       "9  0.000000  0.000000  0.2449  0.000000  0.000000  0.000000   0.000000   \n",
       "\n",
       "   referees  retiring    rogers      said   scandal    shelby  shiffrin  \\\n",
       "0    0.0000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "1    0.0000  0.000000  0.229014  0.000000  0.000000  0.229014  0.000000   \n",
       "2    0.0000  0.000000  0.000000  0.210963  0.000000  0.000000  0.000000   \n",
       "3    0.0000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "4    0.0000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "5    0.0000  0.207203  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "6    0.0000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "7    0.0000  0.000000  0.000000  0.000000  0.227856  0.000000  0.000000   \n",
       "8    0.0000  0.000000  0.000000  0.000000  0.000000  0.000000  0.212026   \n",
       "9    0.2449  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "\n",
       "      since    slalom    soccer      some  sporting   spray     stage    stop  \\\n",
       "0  0.000000  0.000000  0.000000  0.000000  0.000000  0.0000  0.000000  0.0000   \n",
       "1  0.229014  0.000000  0.000000  0.000000  0.000000  0.0000  0.000000  0.0000   \n",
       "2  0.000000  0.000000  0.000000  0.000000  0.210963  0.0000  0.210963  0.0000   \n",
       "3  0.000000  0.000000  0.000000  0.000000  0.000000  0.0000  0.000000  0.0000   \n",
       "4  0.000000  0.000000  0.000000  0.000000  0.000000  0.0000  0.000000  0.0000   \n",
       "5  0.000000  0.000000  0.000000  0.000000  0.000000  0.0000  0.000000  0.0000   \n",
       "6  0.000000  0.000000  0.000000  0.000000  0.000000  0.0000  0.000000  0.0000   \n",
       "7  0.000000  0.000000  0.227856  0.227856  0.000000  0.0000  0.000000  0.0000   \n",
       "8  0.000000  0.424053  0.000000  0.000000  0.000000  0.0000  0.000000  0.0000   \n",
       "9  0.000000  0.000000  0.000000  0.000000  0.000000  0.2449  0.000000  0.2449   \n",
       "\n",
       "   technical      than       the     their  thoroughbred     times     title  \\\n",
       "0   0.000000  0.000000  0.000000  0.000000       0.00000  0.000000  0.000000   \n",
       "1   0.000000  0.000000  0.203324  0.229014       0.00000  0.000000  0.229014   \n",
       "2   0.000000  0.000000  0.187298  0.000000       0.00000  0.000000  0.000000   \n",
       "3   0.000000  0.000000  0.323771  0.000000       0.00000  0.271223  0.000000   \n",
       "4   0.000000  0.000000  0.323771  0.000000       0.00000  0.271223  0.000000   \n",
       "5   0.000000  0.000000  0.367920  0.000000       0.00000  0.000000  0.000000   \n",
       "6   0.000000  0.000000  0.140885  0.000000       0.31737  0.236038  0.000000   \n",
       "7   0.000000  0.227856  0.202296  0.000000       0.00000  0.000000  0.000000   \n",
       "8   0.212026  0.000000  0.188242  0.000000       0.00000  0.000000  0.000000   \n",
       "9   0.000000  0.000000  0.000000  0.000000       0.00000  0.000000  0.000000   \n",
       "\n",
       "         to  vandeweghe  vanishing      vonn   watched       who      will  \\\n",
       "0  0.000000    0.000000     0.0000  0.000000  0.000000  0.000000  0.000000   \n",
       "1  0.151430    0.229014     0.0000  0.000000  0.000000  0.000000  0.000000   \n",
       "2  0.139495    0.000000     0.0000  0.000000  0.210963  0.000000  0.000000   \n",
       "3  0.000000    0.000000     0.0000  0.000000  0.000000  0.000000  0.000000   \n",
       "4  0.000000    0.000000     0.0000  0.000000  0.000000  0.000000  0.000000   \n",
       "5  0.000000    0.000000     0.0000  0.000000  0.000000  0.000000  0.207203   \n",
       "6  0.000000    0.000000     0.0000  0.000000  0.000000  0.000000  0.000000   \n",
       "7  0.150665    0.000000     0.0000  0.000000  0.000000  0.000000  0.000000   \n",
       "8  0.000000    0.000000     0.0000  0.212026  0.000000  0.212026  0.000000   \n",
       "9  0.161935    0.000000     0.2449  0.000000  0.000000  0.000000  0.000000   \n",
       "\n",
       "     with       won     world      year      york  \n",
       "0  0.0000  0.000000  0.000000  0.000000  0.000000  \n",
       "1  0.0000  0.229014  0.000000  0.000000  0.000000  \n",
       "2  0.0000  0.000000  0.250549  0.000000  0.000000  \n",
       "3  0.0000  0.000000  0.216554  0.000000  0.271223  \n",
       "4  0.0000  0.000000  0.216554  0.000000  0.271223  \n",
       "5  0.0000  0.000000  0.000000  0.414406  0.000000  \n",
       "6  0.0000  0.000000  0.188461  0.000000  0.236038  \n",
       "7  0.0000  0.000000  0.135306  0.000000  0.000000  \n",
       "8  0.0000  0.000000  0.000000  0.000000  0.000000  \n",
       "9  0.2449  0.000000  0.000000  0.000000  0.000000  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# convert to pandas to get better idea about the data\n",
    "df = pd.DataFrame(data=tfidf_mat.toarray(),columns=tfidf_vect.get_feature_names())\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "commentary       0.271223\n",
       "including        0.271223\n",
       "times            0.271223\n",
       "thoroughbred     0.317370\n",
       "championships    0.317370\n",
       "breeders         0.317370\n",
       "of               0.352283\n",
       "the              0.367920\n",
       "year             0.414406\n",
       "slalom           0.424053\n",
       "dtype: float64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# print out 10 words with max tfidf, normalized by document occurrence\n",
    "df.max().sort_values()[-10:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Working with (a bit) more data\n",
    "What if we do not have the memory to deal with dense matrix representatioan and we need to keep it sparse?\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sklearn.datasets import fetch_20newsgroups\n",
    "bunch = fetch_20newsgroups(subset='train', shuffle=True, random_state=42)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "the `bunch` object returned from sklearn is similar to a python dictionary. We can access different fields of the object with keys."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11314"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(bunch.data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "From: lerxst@wam.umd.edu (where's my thing)\n",
      "Subject: WHAT car is this!?\n",
      "Nntp-Posting-Host: rac3.wam.umd.edu\n",
      "Organization: University of Maryland, College Park\n",
      "Lines: 15\n",
      "\n",
      " I was wondering if anyone out there could enlighten me on this car I saw\n",
      "the other day. It was a 2-door sports car, looked to be from the late 60s/\n",
      "early 70s. It was called a Bricklin. The doors were really small. In addition,\n",
      "the front bumper was separate from the rest of the body. This is \n",
      "all I know. If anyone can tellme a model name, engine specs, years\n",
      "of production, where this car is made, history, or whatever info you\n",
      "have on this funky looking car, please e-mail.\n",
      "\n",
      "Thanks,\n",
      "- IL\n",
      "   ---- brought to you by your neighborhood Lerxst ----\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(bunch.data[0]) # we should split this up by newlines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "From: system@garlic.sbs.com (Anthony S. Pelliccio)\n",
      "Subject: Re: arcade style buttons and joysticks\n",
      "Organization: Antone's Italian Kitchen and Excellence in Operating Network\n",
      "X-Newsreader: rusnews v1.02\n",
      "Lines: 26\n",
      "\n",
      "dnewman@lynx.dac.northeastern.edu (David F. Newman) writes:\n",
      "\n",
      "> Hi there,\n",
      "> Can anyone tell me where it is possible to purchase controls found\n",
      "> on most arcade style games.  Many projects I am working on would\n",
      "> be greatly augmented if I could implement them.  Thanx in advance.\n",
      "> \n",
      "> -Dave\n",
      "> dnewman@lynx.dac.northeastern.edu\n",
      "> \n",
      "\n",
      "Contact Chris Arthur at Chris_Arthur@pennies.stratus.com\n",
      "He restores lots of old video and arcade games and knows where to get\n",
      "parts.\n",
      "\n",
      "Tony\n",
      "\n",
      "-----------------------------------------------------------------------\n",
      "-- Anthony S. Pelliccio, kd1nr/ae    // Yes, you read it right, the  //\n",
      "-- system @ garlic.sbs.com          // man who went from No-Code    //\n",
      "-----------------------------------// (Thhhppptt!) to Extra in     //\n",
      "-- Flame Retardent Sysadmin       // exactly one year!            //\n",
      "-------------------------------------------------------------------\n",
      "-- This is a calm .sig! --\n",
      "--------------------------\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "#randomly grad an index\n",
    "idx = round(np.random.rand()*len(bunch.data))\n",
    "# and print it pretty\n",
    "print(\"\\n\".join(bunch.data[idx].split(\"\\n\")))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3.92 s, sys: 125 ms, total: 4.04 s\n",
      "Wall time: 4.1 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "news_tfidf = tfidf_vect.fit_transform(bunch.data) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(11314, 130107)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "news_tfidf.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'hypocrisy': 64962,\n",
       " 'kelleyb': 72176,\n",
       " 'innoculate': 67402,\n",
       " '3ctp': 12658,\n",
       " 'hzrck': 65053,\n",
       " 'cscx': 43789,\n",
       " 'r8bx82i': 98853,\n",
       " '8108': 20151,\n",
       " 'interurban': 67963,\n",
       " 'ddavis': 45454,\n",
       " 'eventhandler': 52920,\n",
       " 'shield': 106812,\n",
       " 'cruelties': 43626,\n",
       " '23s': 9452,\n",
       " 'microcomputer': 81853,\n",
       " 'private_key': 95993,\n",
       " 'jfox': 69960,\n",
       " 'eeam': 50564,\n",
       " 'marauders': 79408,\n",
       " '10460': 2714,\n",
       " 'anatol': 28114,\n",
       " 'kfri': 72412,\n",
       " 'truths': 116716,\n",
       " '21864': 8890,\n",
       " 'signatures': 107344,\n",
       " 'o5xt': 88789,\n",
       " 'gondor': 59759,\n",
       " 'jtm': 70887,\n",
       " 'mohrman': 83382,\n",
       " 'ch41': 38878,\n",
       " 'replication': 101025,\n",
       " 'chod3horb_': 39474,\n",
       " 'xlock': 126625,\n",
       " '1qiijs': 7487,\n",
       " 'ranford': 99258,\n",
       " 'commemorates': 41213,\n",
       " 'offen': 89381,\n",
       " '_a6': 23473,\n",
       " 'reconnected': 100089,\n",
       " '8vk': 21353,\n",
       " 'utahn': 119867,\n",
       " 'majesty': 79041,\n",
       " 'hkj35': 63448,\n",
       " 'cbr_128000': 38330,\n",
       " 'outburst': 90783,\n",
       " 'q8u': 97576,\n",
       " 'diagrams': 47029,\n",
       " 'instalation': 67560,\n",
       " '16702': 5312,\n",
       " 'axles': 30872,\n",
       " '5650': 15482,\n",
       " '0wa8nfu': 2202,\n",
       " 'additonal': 26080,\n",
       " '388enh': 12468,\n",
       " 'weiner': 123714,\n",
       " 'nonvolatizer': 87818,\n",
       " 'wbr8e2fa8z': 123463,\n",
       " '6934230': 17293,\n",
       " 'indeo': 66854,\n",
       " 'frequented': 56871,\n",
       " 'molotov': 83446,\n",
       " 'rye': 103747,\n",
       " '2yd': 11359,\n",
       " 'ohlwein': 89521,\n",
       " 'h1z': 61240,\n",
       " 'turbo_f': 116984,\n",
       " 'tingling': 115201,\n",
       " 'osteopporosis': 90649,\n",
       " 'm965': 78369,\n",
       " 'legitamate': 75207,\n",
       " 'demean': 46190,\n",
       " '734062534': 18591,\n",
       " 'maa609': 78570,\n",
       " 'flatpack': 55766,\n",
       " 'archive': 29207,\n",
       " 'celibate': 38576,\n",
       " 'bowen': 34600,\n",
       " 'icgln': 65551,\n",
       " 'mi0o': 81757,\n",
       " 'cw6': 44243,\n",
       " 'gullata': 60864,\n",
       " '8efv6': 20970,\n",
       " 'k1': 71336,\n",
       " 'unethical': 118741,\n",
       " 'xttblposition': 127304,\n",
       " 'reconstruction': 100096,\n",
       " 'gary_suter': 58198,\n",
       " 'celeborn': 38562,\n",
       " '150437': 4624,\n",
       " 'cmmr': 40639,\n",
       " 'fan': 54333,\n",
       " 'herbalists': 62809,\n",
       " 'trails': 116094,\n",
       " 'daylight': 45306,\n",
       " 'fegmania': 54798,\n",
       " 'gpalo': 59945,\n",
       " 'redefine': 100181,\n",
       " 'aids': 26904,\n",
       " 'sterrenkundigen': 110612,\n",
       " 'dubchak': 49318,\n",
       " 'abkect': 25354,\n",
       " 'archau': 29174,\n",
       " 'competitor': 41454,\n",
       " 'batum': 32090,\n",
       " 'lhzd': 75631,\n",
       " 'aa05710': 25083,\n",
       " 'everx678': 52947,\n",
       " 'op290': 90005,\n",
       " 'fati': 54507,\n",
       " 'zrn31p_': 129857,\n",
       " 'uhf': 118027,\n",
       " 'gems': 58566,\n",
       " '6ahl6ah': 17374,\n",
       " 'cuny': 44064,\n",
       " '19424': 6314,\n",
       " 'iubacs': 68899,\n",
       " 'v_': 120475,\n",
       " 'templates': 114018,\n",
       " 'swaim': 112266,\n",
       " '22534': 9100,\n",
       " 'subborned': 111282,\n",
       " '4h12': 14405,\n",
       " 'j_3_w': 69320,\n",
       " 'waha': 123043,\n",
       " 'mhl_': 81719,\n",
       " '90h': 21535,\n",
       " 'inen': 67000,\n",
       " 'routinely': 103085,\n",
       " 'mbs3': 80144,\n",
       " 'wdl50': 123562,\n",
       " 't_a84ta84_4z7': 113099,\n",
       " '____1____': 23328,\n",
       " '87f350800': 20643,\n",
       " 'odometers': 89311,\n",
       " 'halegna': 61671,\n",
       " 'demarche': 46187,\n",
       " 'oep': 89353,\n",
       " 'manic': 79266,\n",
       " 'qumran': 98455,\n",
       " 'xfacemaker2': 126352,\n",
       " 'libtermcap': 75749,\n",
       " 'geenwood': 58514,\n",
       " 'irresponsibility': 68496,\n",
       " 'ebcin': 50213,\n",
       " 'gananney': 58094,\n",
       " 'cwm': 44265,\n",
       " 'inflection': 67139,\n",
       " 'gy_': 61109,\n",
       " 'simplifies': 107492,\n",
       " 'b53d14': 31124,\n",
       " 'naturei': 86190,\n",
       " 'n__5': 85874,\n",
       " 'acaps': 25561,\n",
       " 'ryxkg6': 103780,\n",
       " 'nhq': 87135,\n",
       " 'impoliteness': 66493,\n",
       " 'enum': 51950,\n",
       " '54y': 15339,\n",
       " 'v05': 120204,\n",
       " '5meg': 16110,\n",
       " 'hampshire': 61782,\n",
       " 'ecqm': 50368,\n",
       " 'cataclysmic': 38085,\n",
       " 'scenery': 105028,\n",
       " 'ms9x6': 84421,\n",
       " 'eqtid': 52178,\n",
       " 'coreographed': 42652,\n",
       " 'ma8li8': 78564,\n",
       " 'ikjjhv': 66078,\n",
       " '1830s': 5930,\n",
       " 'acheron': 25772,\n",
       " '1tm': 8078,\n",
       " 'uj6': 118110,\n",
       " 'hh07b': 63049,\n",
       " 'psa': 96657,\n",
       " '55th': 15443,\n",
       " 'mu9p': 84665,\n",
       " 'inerancy': 67008,\n",
       " 'repudiate': 101123,\n",
       " 'bondra': 34313,\n",
       " 'm3xsb': 77941,\n",
       " 'tabac': 113147,\n",
       " 'impedances': 66415,\n",
       " 'highlite': 63175,\n",
       " 'pale': 91771,\n",
       " 'apr19': 28997,\n",
       " '7vzneutpeut': 19931,\n",
       " 'marv': 79655,\n",
       " 'a47': 24794,\n",
       " '76206': 19119,\n",
       " 'iacs3650': 65393,\n",
       " '39529': 12520,\n",
       " 'mutliple': 85069,\n",
       " 'shaman': 106556,\n",
       " 'tby': 113638,\n",
       " 'manhattan': 79256,\n",
       " 'xle': 126609,\n",
       " 'glibly': 59387,\n",
       " 'tv0': 117086,\n",
       " 'mabbot': 78582,\n",
       " 'adwr': 26368,\n",
       " 'pxphigs_info_display': 97245,\n",
       " 'sing_': 107557,\n",
       " 'alberta': 27259,\n",
       " 'isolar': 68662,\n",
       " 'bmmw': 34035,\n",
       " 'relitigate': 100731,\n",
       " 'trivia': 116582,\n",
       " 'macc': 78607,\n",
       " 'refered': 100308,\n",
       " 'm1478': 77682,\n",
       " 'prince': 95934,\n",
       " 'currently': 44110,\n",
       " 'achilles': 25784,\n",
       " 'smth': 108386,\n",
       " 'jokp': 70543,\n",
       " 'faqs': 54382,\n",
       " 'maggia': 78843,\n",
       " 'c5l9qb': 36743,\n",
       " 'los5': 76809,\n",
       " '740': 18845,\n",
       " 'quantizised': 98283,\n",
       " '164801': 5237,\n",
       " 'm50hv': 78046,\n",
       " 'horvath': 64065,\n",
       " 'p3yg': 91407,\n",
       " '59v': 15724,\n",
       " 'mine': 82215,\n",
       " 'equaled': 52184,\n",
       " 'gmf': 59510,\n",
       " '0536': 1102,\n",
       " 'sophistication': 108894,\n",
       " 'qrr_ac6_qs4u': 98071,\n",
       " 'corny': 42694,\n",
       " 'dense': 46332,\n",
       " 'gnrh': 59572,\n",
       " 'adapt': 26025,\n",
       " 'moscom': 83805,\n",
       " 'outfit': 90807,\n",
       " 'socorro': 108625,\n",
       " 'caen': 37302,\n",
       " 'm4p': 78022,\n",
       " 'ljpz': 76306,\n",
       " 'eoneill': 52035,\n",
       " 'uzl34': 120190,\n",
       " 'prepayment': 95694,\n",
       " 'elton': 51233,\n",
       " 'safeties': 104327,\n",
       " 'disctribution': 47649,\n",
       " 'gax': 58303,\n",
       " 'bathed': 32052,\n",
       " 'pc9_b109': 92565,\n",
       " 'rep': 100942,\n",
       " '4645': 13872,\n",
       " 'baffeled': 31540,\n",
       " 'overheated': 91007,\n",
       " 'lb4t': 74879,\n",
       " 'sarge': 104655,\n",
       " '_alternative': 23510,\n",
       " 'corep': 42653,\n",
       " 'bloodline': 33901,\n",
       " 'jockey': 70443,\n",
       " 'hayman': 62276,\n",
       " 'forsook': 56474,\n",
       " 'gt380': 60679,\n",
       " 'music': 85002,\n",
       " '221': 8963,\n",
       " 'compiliers': 41464,\n",
       " 'voters': 122128,\n",
       " 'frater': 56764,\n",
       " 'catullus': 38176,\n",
       " 'preservative': 95747,\n",
       " 'mizan': 82614,\n",
       " 'decreases': 45744,\n",
       " 'tweede': 117145,\n",
       " '29338': 10431,\n",
       " 'include': 66722,\n",
       " 'toungues': 115862,\n",
       " 'wk': 124699,\n",
       " 'chiftlik': 39358,\n",
       " 'ksuvxb': 73711,\n",
       " '63631': 16764,\n",
       " 'iojqzg75osvv': 68219,\n",
       " 'californians': 37415,\n",
       " '6eh': 17503,\n",
       " 'bisharat': 33515,\n",
       " '9n': 22832,\n",
       " 'wa3uqv': 122953,\n",
       " '23670': 9405,\n",
       " 'khoros': 72551,\n",
       " '9_e': 22482,\n",
       " 'irratation': 68469,\n",
       " 'e2vx': 49876,\n",
       " 'spacify': 109096,\n",
       " 'jpw0': 70736,\n",
       " '7hlc': 19615,\n",
       " 'numberless': 88369,\n",
       " 'underneath': 118614,\n",
       " 'guqr': 60935,\n",
       " 'blir': 33837,\n",
       " 'sucked': 111538,\n",
       " '6vg_f': 18092,\n",
       " 'arnd': 29442,\n",
       " 'fo9h': 56113,\n",
       " 'gw2k': 61046,\n",
       " 'su6': 111264,\n",
       " 'jetting': 69919,\n",
       " 't7': 113002,\n",
       " '5g8': 15932,\n",
       " 'isbm': 68555,\n",
       " 'widefield': 124227,\n",
       " 'dvl': 49584,\n",
       " 'apologised': 28782,\n",
       " 'r2d2': 98697,\n",
       " 'xyfgaj': 127547,\n",
       " 'chzrcj1rd': 39771,\n",
       " '3tti': 13213,\n",
       " 'mcdougall': 80313,\n",
       " 'health': 62466,\n",
       " 'shortsighted': 107004,\n",
       " 'fh': 55126,\n",
       " 'telling': 113985,\n",
       " 'liff': 75848,\n",
       " '45g': 13819,\n",
       " 'consequnces': 42064,\n",
       " 'sucessor': 111532,\n",
       " 'beneficent': 32758,\n",
       " 'thailand': 114412,\n",
       " 'rhubarb': 101862,\n",
       " '8ba_': 20862,\n",
       " 'workman': 125038,\n",
       " '8pws': 21221,\n",
       " 'terminals': 114142,\n",
       " '573': 15549,\n",
       " '8983': 20782,\n",
       " 'republic': 101115,\n",
       " 'shord': 106978,\n",
       " 'poets': 94709,\n",
       " '25mz': 9859,\n",
       " 'soundblater': 108962,\n",
       " 'hzrci': 65048,\n",
       " 'turkmen': 117027,\n",
       " 'coleco': 40944,\n",
       " 'neosoft': 86639,\n",
       " 'uqvf1': 119608,\n",
       " '_m': 24038,\n",
       " 'document': 48411,\n",
       " 'boivert': 34240,\n",
       " 'ladwig': 74371,\n",
       " 'dialogic': 47045,\n",
       " 'retardent': 101477,\n",
       " '_zw_': 24636,\n",
       " 'karr': 71840,\n",
       " 'hhrx': 63084,\n",
       " 'tempory': 114031,\n",
       " 'kidda3': 72606,\n",
       " '06': 1167,\n",
       " 'michael': 81794,\n",
       " 'discredited': 47625,\n",
       " 'serbia': 106178,\n",
       " 'makedepend': 79056,\n",
       " 'peter_bondra': 93248,\n",
       " 'dvjrlojsq': 49583,\n",
       " 'cas': 38007,\n",
       " 'xeblaz01ox5': 126303,\n",
       " '82238': 20241,\n",
       " '2901': 10373,\n",
       " 'outages': 90777,\n",
       " 'solicts': 108745,\n",
       " 'somehow': 108805,\n",
       " 'smarting': 108273,\n",
       " '141112': 4210,\n",
       " '03': 789,\n",
       " 'h0i': 61199,\n",
       " 'megatrend': 80909,\n",
       " 'weidlich': 123691,\n",
       " 'share': 106610,\n",
       " 'cormier': 42674,\n",
       " '34i': 11998,\n",
       " 'someone': 108809,\n",
       " '1zj': 8255,\n",
       " 'astm': 29956,\n",
       " 'gallons': 58032,\n",
       " '08544': 1450,\n",
       " 'underscore': 118630,\n",
       " 'ucs3ea8': 117845,\n",
       " 'relieveing': 100707,\n",
       " 'littleton': 76216,\n",
       " 'cxte': 44345,\n",
       " 'occipital': 89152,\n",
       " 'ukp': 118167,\n",
       " 'dastar': 45138,\n",
       " 'softball': 108660,\n",
       " 'aul4su': 30404,\n",
       " 'repute': 101136,\n",
       " 'jerusalem': 69887,\n",
       " '2277': 9151,\n",
       " 'chemotherapy': 39246,\n",
       " 'ds2160': 49171,\n",
       " 'burners': 35720,\n",
       " 'passthrough': 92277,\n",
       " 'ttlg': 116849,\n",
       " '24450': 9527,\n",
       " 'parachutes': 91964,\n",
       " 'diginst': 47253,\n",
       " 'uowtl': 119446,\n",
       " 'broiled': 35125,\n",
       " '_naive_': 24111,\n",
       " 'vcd': 120883,\n",
       " 'teledetection': 113927,\n",
       " 'b518q': 31123,\n",
       " 'aqeng': 29058,\n",
       " 'jvw3q6m': 71152,\n",
       " 'bahamas': 31568,\n",
       " 'greenhorn': 60289,\n",
       " '71zzlc': 18425,\n",
       " 'beaten': 32379,\n",
       " 'armeniens': 29406,\n",
       " 'wysiwig': 125598,\n",
       " 'imprint': 66539,\n",
       " 'compress': 41552,\n",
       " 't3s1t': 112855,\n",
       " '6257': 16692,\n",
       " 'criminalized': 43410,\n",
       " 'blacksburg': 33688,\n",
       " 'okopowa': 89629,\n",
       " 'nk2j4': 87456,\n",
       " 'shamsky': 106572,\n",
       " '200629': 8331,\n",
       " '10111011': 2575,\n",
       " 'hparc0': 64246,\n",
       " 'ammeter': 27896,\n",
       " 'c5ij7h': 36614,\n",
       " 'gskolan': 60635,\n",
       " 'emotive': 51421,\n",
       " '9075': 21521,\n",
       " 'scanjet': 104958,\n",
       " 'statistical': 110390,\n",
       " '757': 19003,\n",
       " 'c0ryl6b': 36115,\n",
       " '074352': 1338,\n",
       " 'emk': 51393,\n",
       " 'gainfully': 57973,\n",
       " 'ny3': 88556,\n",
       " '_a7': 23474,\n",
       " 'azp': 30978,\n",
       " 'itars': 68786,\n",
       " 'streamflow': 110991,\n",
       " 'asrcq': 29800,\n",
       " 'guilt': 60839,\n",
       " 'mutlu': 85070,\n",
       " 'wedge': 123646,\n",
       " 'lq18': 76980,\n",
       " 'tale': 113302,\n",
       " 'rampant': 99219,\n",
       " 'apoligized': 28771,\n",
       " 'armegedon': 29397,\n",
       " 'sprained': 109630,\n",
       " 'merciless': 81178,\n",
       " 'c84hm2': 37103,\n",
       " 'ralcgm': 99165,\n",
       " 'llyr': 76423,\n",
       " 'imperial': 66434,\n",
       " 'frlyz': 56963,\n",
       " 'ghost': 58997,\n",
       " 'masonic': 79704,\n",
       " 'chavey': 39144,\n",
       " 'misconduct': 82386,\n",
       " 'raise': 99140,\n",
       " 'misunderstood': 82544,\n",
       " 'ub9c68': 117748,\n",
       " 'inital': 67305,\n",
       " 'heathen': 62508,\n",
       " '6vunma0_': 18102,\n",
       " '5925': 15679,\n",
       " 'rq588': 103181,\n",
       " 'lowdown': 76896,\n",
       " 'disarmament': 47505,\n",
       " 'c5hs5j': 36586,\n",
       " 'brady': 34759,\n",
       " '7su': 19827,\n",
       " 'trojan': 116608,\n",
       " 'macdermid': 78619,\n",
       " 'heretics': 62837,\n",
       " 'ashton': 29718,\n",
       " 't68': 112986,\n",
       " 'r3ecs': 98719,\n",
       " 'wampyr': 123165,\n",
       " 'smedley': 108301,\n",
       " 'fuw': 57398,\n",
       " 'j51': 69185,\n",
       " 'transmitter': 116250,\n",
       " 'devguide': 46828,\n",
       " 'me6yaridi': 80662,\n",
       " 'factually': 54154,\n",
       " 'restating': 101386,\n",
       " '12c65': 3769,\n",
       " '9304051847': 21739,\n",
       " 'theatrical': 114473,\n",
       " 'w8yz': 122900,\n",
       " '195024': 6349,\n",
       " 'dwallach': 49610,\n",
       " 'monk': 83521,\n",
       " 'kbaud': 71983,\n",
       " 'vr': 122214,\n",
       " 'creator': 43328,\n",
       " 'yr8': 128492,\n",
       " 'ventura': 121117,\n",
       " 'mtxu': 84642,\n",
       " 'drying': 49154,\n",
       " 'bullwhips': 35591,\n",
       " '6a0k': 17363,\n",
       " 'antti': 28578,\n",
       " 'trackball': 116029,\n",
       " '1483500353': 4535,\n",
       " 'bats': 32064,\n",
       " 'ruined': 103469,\n",
       " 'a85pa4': 24970,\n",
       " 'sentimentally': 106102,\n",
       " 'migrations': 82016,\n",
       " 'transocean': 116254,\n",
       " 'inquirys': 67457,\n",
       " 'qtcv9f0': 98175,\n",
       " 'ukol6': 118166,\n",
       " 'lsm': 77120,\n",
       " 'o92v': 88846,\n",
       " 'voecking': 121990,\n",
       " '486dx': 14064,\n",
       " 'rm8qw': 102461,\n",
       " '16mk16m': 5423,\n",
       " 'cigarettes': 39839,\n",
       " 'deny': 46351,\n",
       " 'c5ftjt': 36540,\n",
       " '7797751': 19238,\n",
       " '141skwa': 4240,\n",
       " 'nelson_p': 86612,\n",
       " 'cul': 44008,\n",
       " 'myname': 85425,\n",
       " '_subject_': 24428,\n",
       " '10100100': 2523,\n",
       " '23665': 9403,\n",
       " 'canonicity': 37661,\n",
       " 'xmlabel': 126697,\n",
       " 'sandpoint': 104570,\n",
       " 'proceed': 96087,\n",
       " '735383339': 18785,\n",
       " 'fgqi': 55116,\n",
       " 'm34u': 77875,\n",
       " 'ij5': 66027,\n",
       " 'nitems': 87392,\n",
       " 'u09': 117385,\n",
       " 'wordprocessor': 125005,\n",
       " '2ss': 11165,\n",
       " 'dw': 49601,\n",
       " 'qaplus': 97629,\n",
       " 'dif88': 47190,\n",
       " 'e25': 49850,\n",
       " 'garryola': 58189,\n",
       " 'epfl': 52072,\n",
       " 'formulating': 56451,\n",
       " 'erzurum': 52418,\n",
       " 'deborah': 45568,\n",
       " '986e14': 22387,\n",
       " 'xsat1': 126957,\n",
       " 'prv6ej': 96633,\n",
       " '2hz': 10835,\n",
       " '5454': 15294,\n",
       " 'a2x': 24752,\n",
       " '1874': 6055,\n",
       " 'corrolary': 42766,\n",
       " 'grenades': 60339,\n",
       " 'jonah': 70554,\n",
       " 'kj3': 72867,\n",
       " 'arenas': 29252,\n",
       " 'wisodm': 124604,\n",
       " 'pricey': 95889,\n",
       " 'chapdelaine': 39022,\n",
       " 'zeus02': 129292,\n",
       " '8wf': 21380,\n",
       " 'maq175u': 79398,\n",
       " 'cooperates': 42526,\n",
       " 'home2': 63813,\n",
       " 'karabag': 71774,\n",
       " 'lafcol': 74379,\n",
       " '38432': 12426,\n",
       " 'purple': 97073,\n",
       " '1313': 3868,\n",
       " 'i06p': 65088,\n",
       " 'mirandized': 82334,\n",
       " 'avpvv': 30712,\n",
       " 'colortable': 41072,\n",
       " 'xtwindowofobject': 127328,\n",
       " 'mkk6': 82802,\n",
       " 'p_8o': 91571,\n",
       " 'brother': 35180,\n",
       " '8x': 21395,\n",
       " '4510a': 13772,\n",
       " 'hays': 62278,\n",
       " '0dq3': 1688,\n",
       " 'correctable': 42725,\n",
       " 'broken': 35127,\n",
       " 'cocking': 40788,\n",
       " 'dork': 48646,\n",
       " 's2813': 103922,\n",
       " 'peaceably': 92673,\n",
       " 'bulev': 35545,\n",
       " 'hhhmmmmm': 63072,\n",
       " 'detections': 46714,\n",
       " 'aryana': 29614,\n",
       " 'ib6l': 65461,\n",
       " 'amplified': 27947,\n",
       " 'saltpeter': 104460,\n",
       " 'picnic': 93773,\n",
       " '0ww': 2220,\n",
       " 'schisms': 105116,\n",
       " 'upbringings': 119467,\n",
       " 'skaggs': 107778,\n",
       " 'freiberg': 56847,\n",
       " 'alphabetic': 27600,\n",
       " 'handlbars': 61841,\n",
       " 'sacremental': 104259,\n",
       " 'shnekendorf': 106915,\n",
       " '5t': 16283,\n",
       " 'diplomats': 47407,\n",
       " 'littel': 76204,\n",
       " 'chzalii': 39746,\n",
       " 'reformatted': 100360,\n",
       " 'lta_': 77160,\n",
       " 'zrcim': 129800,\n",
       " 'obtaining': 89113,\n",
       " 'nonbelted': 87732,\n",
       " 'serpent': 106229,\n",
       " 'firing': 55516,\n",
       " 'm41': 77952,\n",
       " '7gy': 19588,\n",
       " 'bankruptcies': 31764,\n",
       " '25141': 9731,\n",
       " 'nrk': 88167,\n",
       " 'superb': 111843,\n",
       " 'daft': 44861,\n",
       " 'pkd': 94133,\n",
       " 'remarked': 100783,\n",
       " 'uninspiring': 118894,\n",
       " 'omni': 89832,\n",
       " '1917': 6207,\n",
       " '13963': 4088,\n",
       " 'pleases': 94364,\n",
       " 'ketosis': 72299,\n",
       " '21rbz': 8919,\n",
       " 'smartdrv': 108269,\n",
       " 'obmoto': 89034,\n",
       " 'uofaz': 119404,\n",
       " 'verm': 121195,\n",
       " 'inxs': 68187,\n",
       " 'sigle': 107328,\n",
       " 'david_anthony_guevara': 45243,\n",
       " '1283': 3731,\n",
       " 'nuclei': 88334,\n",
       " 'boom': 34381,\n",
       " 'universidad': 118969,\n",
       " 'basica': 31993,\n",
       " 'xy6': 127540,\n",
       " '4ed40jc2q0v': 14331,\n",
       " '11110011': 3059,\n",
       " 'arresed': 29495,\n",
       " 'md6f1qvei': 80567,\n",
       " 'demnaechst': 46209,\n",
       " 'quipped': 98429,\n",
       " 'yf9f9f9f0': 128117,\n",
       " 'nightmarish': 87275,\n",
       " 'curtech': 44136,\n",
       " 'panicked': 91880,\n",
       " 'carseat': 37957,\n",
       " 'reastful': 99885,\n",
       " '673102': 17126,\n",
       " 'geode17': 58705,\n",
       " 'csce': 43782,\n",
       " '6ukz': 18041,\n",
       " '175327': 5675,\n",
       " '5_v4kui': 15741,\n",
       " '42366976': 13550,\n",
       " 'certianty': 38717,\n",
       " '48201': 14034,\n",
       " 'roofing': 102908,\n",
       " 'timezones': 115169,\n",
       " 'naiman': 85971,\n",
       " 'davydov': 45284,\n",
       " 'tso': 116791,\n",
       " 'informs': 67196,\n",
       " 'ddg': 45463,\n",
       " 'w2ehd': 122680,\n",
       " 'wagers': 123030,\n",
       " '30v': 11540,\n",
       " 'inhabitant': 67267,\n",
       " '972167': 22296,\n",
       " 'asher': 29705,\n",
       " 'avid': 30674,\n",
       " '6347': 16757,\n",
       " 'penguins': 92868,\n",
       " 'ep7y': 52060,\n",
       " 'hit': 63365,\n",
       " 'blasphemer': 33743,\n",
       " 'utrechtse': 119937,\n",
       " 'graduation': 60048,\n",
       " 'lva': 77391,\n",
       " 'represenatives': 101069,\n",
       " 'geco': 58493,\n",
       " 'nd9': 86374,\n",
       " 'dragon_': 48904,\n",
       " 'helgesen': 62647,\n",
       " 'warmly': 123246,\n",
       " 'n9lnq': 85859,\n",
       " 'q4t7': 97464,\n",
       " 'dozed': 48798,\n",
       " 'referenda': 100319,\n",
       " 'v93w': 120431,\n",
       " 'vanderwal': 120663,\n",
       " 'nolo': 87710,\n",
       " 'jack': 69371,\n",
       " 'coloradu': 41053,\n",
       " 'newsgroups': 86933,\n",
       " 'umk': 118297,\n",
       " 'mqvdz': 84221,\n",
       " 'g9v4i65': 57865,\n",
       " 'yza': 128737,\n",
       " '1146': 3209,\n",
       " '1cmj': 6701,\n",
       " 'guarded': 60762,\n",
       " 'coroner': 42706,\n",
       " '5633': 15474,\n",
       " 'micrometer': 81887,\n",
       " 'nonsolution': 87799,\n",
       " 'daul': 45208,\n",
       " 'abnormalities': 25364,\n",
       " 'ciarlett': 39809,\n",
       " 'commissions': 41264,\n",
       " 'duplicating': 49481,\n",
       " 'cardiology': 37834,\n",
       " '19407': 6300,\n",
       " '734981173': 18699,\n",
       " 'burial': 35700,\n",
       " 'b5l': 31141,\n",
       " 'enticed': 51900,\n",
       " 'regress': 100468,\n",
       " 'graham': 60069,\n",
       " 'blauser': 33763,\n",
       " '1hd': 6907,\n",
       " 'wamsley': 123166,\n",
       " 'erdal': 52270,\n",
       " 'cmaps': 40608,\n",
       " 'rebelliousness': 99903,\n",
       " 'ooaid': 89966,\n",
       " 'hqux': 64375,\n",
       " 'wqh5': 125182,\n",
       " 'nu4y': 88318,\n",
       " 'finds': 55419,\n",
       " 'overstress': 91105,\n",
       " '165gppfijlk': 5297,\n",
       " '1qv': 7767,\n",
       " 'hobbyist': 63618,\n",
       " 'fakefully': 54253,\n",
       " 'scripps': 105449,\n",
       " 'tsha': 116769,\n",
       " 'sunos4': 111801,\n",
       " 'uniting': 118948,\n",
       " 'configs': 41852,\n",
       " 'branum': 34820,\n",
       " '2180': 8882,\n",
       " 'rundqvist': 103514,\n",
       " 'orlin': 90466,\n",
       " 'mmqirk7': 83022,\n",
       " '2bc0d53b': 10590,\n",
       " 'hifonics': 63155,\n",
       " 'i0ws': 65122,\n",
       " 'revans': 101577,\n",
       " 'e9': 49993,\n",
       " 'y9kew': 127780,\n",
       " 'comunity': 41649,\n",
       " 'wysiwis': 125599,\n",
       " 'ml6': 82851,\n",
       " 'uovf_o': 119443,\n",
       " 'o_n_l_y': 88866,\n",
       " 'etaylor': 52640,\n",
       " 'mjuric': 82714,\n",
       " 'ql0d': 97864,\n",
       " 'resell': 101201,\n",
       " 'peckham': 92719,\n",
       " 'earthly': 50133,\n",
       " 'pyron': 97294,\n",
       " 'zg': 129319,\n",
       " '9netm': 22847,\n",
       " 'needfunctionprototypes': 86497,\n",
       " 'acheng': 25771,\n",
       " 'colossians': 41076,\n",
       " 'ikmali': 66082,\n",
       " 'transcript': 116167,\n",
       " 'demands': 46186,\n",
       " '3292': 11719,\n",
       " '5i16x59': 15986,\n",
       " 'motelling': 83850,\n",
       " 'curiousities': 44100,\n",
       " 'rocking': 102735,\n",
       " 'complexity': 41500,\n",
       " 'acquiescing': 25869,\n",
       " '174': 5625,\n",
       " 'dog': 48455,\n",
       " '466666': 13885,\n",
       " 'rivlin': 102177,\n",
       " '17mb': 5795,\n",
       " 'buenneke': 35472,\n",
       " 'possibility': 95128,\n",
       " 'if5e1': 65803,\n",
       " 'tusone': 117060,\n",
       " 'depressions': 46437,\n",
       " 'acad3': 25542,\n",
       " 'haps': 61936,\n",
       " 'which': 124055,\n",
       " 'temptor': 114039,\n",
       " 'w1x': 122655,\n",
       " 'carefree': 37848,\n",
       " 'zr1': 129782,\n",
       " 'f2sf': 53833,\n",
       " 'stingray': 110718,\n",
       " 'c4z3xw': 36334,\n",
       " '23jt96': 9446,\n",
       " 'iorp': 68232,\n",
       " 'eshkol': 52492,\n",
       " 'balthazar': 31700,\n",
       " 'fmtme': 56044,\n",
       " 'admissible': 26197,\n",
       " '277': 10102,\n",
       " 't2rn': 112811,\n",
       " 'vitalism': 121743,\n",
       " 'physiologic': 93712,\n",
       " 'wycliffe': 125581,\n",
       " 'divider': 48056,\n",
       " '182038': 5890,\n",
       " '8tcqi': 21318,\n",
       " 'pursuing': 97099,\n",
       " '037': 881,\n",
       " 'calgene': 37398,\n",
       " '1926a': 6239,\n",
       " '40b': 13414,\n",
       " 'k4bat': 71418,\n",
       " 'indoctrination': 66944,\n",
       " 'piewm': 93828,\n",
       " 'hog': 63686,\n",
       " '1ilph9': 6934,\n",
       " 'bivariate': 33565,\n",
       " 'including': 66727,\n",
       " '1r21g2inneah': 7881,\n",
       " 'jca2': 69652,\n",
       " 'ff1r': 55035,\n",
       " '121757': 3502,\n",
       " '165dse5': 5293,\n",
       " 'eryc': 52407,\n",
       " 'rhyme': 101864,\n",
       " 'wau': 123391,\n",
       " 'pouring': 95238,\n",
       " '0tg': 2127,\n",
       " 'struble': 111126,\n",
       " 'antipsychotics': 28543,\n",
       " 'xtgc0': 127131,\n",
       " '3dx7wdy': 12701,\n",
       " 'politic': 94810,\n",
       " 'choong': 39512,\n",
       " '3htzh': 12847,\n",
       " 'ret_yes': 101452,\n",
       " 'az8': 30933,\n",
       " 'c5p26b': 36814,\n",
       " 'serbians': 106180,\n",
       " 'reddish': 100172,\n",
       " '4354': 13644,\n",
       " '7ey_3': 19547,\n",
       " 'dlc': 48200,\n",
       " 'undertaking': 118657,\n",
       " 'impart': 66400,\n",
       " 'tunics': 116965,\n",
       " 'hsczllqc': 64460,\n",
       " '5mg79n': 16113,\n",
       " 'wgep': 123938,\n",
       " 'avoided': 30697,\n",
       " '29970': 10502,\n",
       " 'ncel': 86322,\n",
       " 'cassia': 38051,\n",
       " '4h1a': 14407,\n",
       " 'ix6': 68979,\n",
       " 'rosenfeld': 102975,\n",
       " '2005': 8321,\n",
       " 'immotile': 66349,\n",
       " 'bulked': 35557,\n",
       " 'prophetically': 96395,\n",
       " 'kufdm': 73779,\n",
       " '0s9': 2086,\n",
       " 'sort': 108931,\n",
       " 'parlodel': 92102,\n",
       " '7u8': 19872,\n",
       " 'triglycerides': 116507,\n",
       " 'obsessions': 89086,\n",
       " 'biking': 33307,\n",
       " 'kerim': 72266,\n",
       " 'barkwell': 31859,\n",
       " 'volant': 122023,\n",
       " 'msprague': 84497,\n",
       " 'aphelion': 28726,\n",
       " 'xl': 126594,\n",
       " 'stemmed': 110541,\n",
       " 'pmview': 94601,\n",
       " 'vak12ed': 120561,\n",
       " 'enf021': 51690,\n",
       " 'ied': 65781,\n",
       " 'rededicate': 100175,\n",
       " 'backgroud': 31433,\n",
       " 'brent_gretzky': 34933,\n",
       " '140649': 4186,\n",
       " 'diy': 48099,\n",
       " 'workshift': 125045,\n",
       " '0lu': 1906,\n",
       " '0_4': 1593,\n",
       " 'tenant': 114047,\n",
       " 'gsulliva': 60652,\n",
       " 'mssc5kcru': 84513,\n",
       " 'soothing': 108885,\n",
       " 'bceqq4': 32228,\n",
       " '_l6': 23994,\n",
       " 'substantiate': 111436,\n",
       " 'mare': 79447,\n",
       " 'bey_': 33008,\n",
       " 'pixelpaint': 94072,\n",
       " 'snohomish': 108511,\n",
       " 'dvv5e265d': 49598,\n",
       " 'mx15f': 85283,\n",
       " 'perpetrated': 93101,\n",
       " 'games0': 58077,\n",
       " 'mngf': 83120,\n",
       " 'hdm': 62388,\n",
       " '300bps': 11407,\n",
       " 'bartoshuk': 31936,\n",
       " 'biginning': 33274,\n",
       " 'knkf7': 73184,\n",
       " 'jvmg0j': 71137,\n",
       " 'bii1': 33293,\n",
       " '5742': 15556,\n",
       " 'propagandize': 96360,\n",
       " 'nedlands': 86489,\n",
       " '_2_x': 23154,\n",
       " '2n6': 10982,\n",
       " 'surf': 112043,\n",
       " 'eei': 50584,\n",
       " 'wethepeople': 123877,\n",
       " 's1471w9': 103864,\n",
       " 'f4o': 53894,\n",
       " 'glxmdraw': 59477,\n",
       " 'aj': 27035,\n",
       " 'inferior': 67082,\n",
       " 'engdahl': 51715,\n",
       " 'paschal': 92222,\n",
       " '82k': 20296,\n",
       " 'maulers': 79915,\n",
       " 'davisonj': 45276,\n",
       " 'recomendations': 100053,\n",
       " 'dialect': 47033,\n",
       " 'dalls': 44920,\n",
       " 'c5t3b2': 36939,\n",
       " 'pdes': 92639,\n",
       " 'slqnsl': 108191,\n",
       " 'mvj': 85143,\n",
       " 'languagelevel': 74545,\n",
       " 'm5c5fkj': 78072,\n",
       " 'normals': 87880,\n",
       " 'unqualified': 119160,\n",
       " 'wgrant': 123945,\n",
       " 'cpc4': 43112,\n",
       " 'ps9u': 96655,\n",
       " 'lk8rcj1ack': 76339,\n",
       " 'earlw': 50110,\n",
       " 'pitchiong': 94022,\n",
       " 'precendent': 95495,\n",
       " 'acis': 25813,\n",
       " 'galleries': 58023,\n",
       " 'spcvxa': 109193,\n",
       " 'ksky': 73696,\n",
       " '9f5z': 22582,\n",
       " 'grandfathers': 60104,\n",
       " '70fpkitnb9': 18282,\n",
       " 'i07': 65089,\n",
       " 'fwm': 57457,\n",
       " 'wardsgi': 123220,\n",
       " 'defensive': 45898,\n",
       " '120m': 3463,\n",
       " '3113': 11557,\n",
       " 'gvznkhf7': 61037,\n",
       " 'mu6': 84659,\n",
       " '6ei3': 17514,\n",
       " 's2sz9nf5htdii0r6sseypl0r6': 103931,\n",
       " 'shope': 106966,\n",
       " 'yguo': 128162,\n",
       " 'gilmartin': 59124,\n",
       " 'connor': 42007,\n",
       " '5zbpi': 16444,\n",
       " ...}"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tfidf_vect.vocabulary_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# create pandas dataframe\n",
    "vec = news_tfidf.max(axis=0)\n",
    "df  = pd.DataFrame(data=vec.toarray(),columns=tfidf_vect.get_feature_names())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "kk          0.870294\n",
       "db          0.871473\n",
       "scsi        0.875086\n",
       "blah        0.879426\n",
       "donoghue    0.891653\n",
       "00          0.907726\n",
       "___         0.908826\n",
       "25          0.913127\n",
       "forged      0.940511\n",
       "ax          0.998314\n",
       "dtype: float64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# largest tfidf \n",
    "df.max().sort_values()[-10:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(11314, 28592)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "dialix            0.947270\n",
       "blah              0.952881\n",
       "ualberta          0.956563\n",
       "stephanopoulos    0.959855\n",
       "forged            0.971300\n",
       "mufti             0.976947\n",
       "ax                0.999881\n",
       "meyers            1.000000\n",
       "slower            1.000000\n",
       "ucsd              1.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# now lets do the transformation with a smaller vocabulary\n",
    "tfidf_vect = TfidfVectorizer(stop_words='english',\n",
    "                             max_df=0.01,\n",
    "                             min_df=4)\n",
    "news_tfidf = tfidf_vect.fit_transform(bunch.data) \n",
    "print(news_tfidf.shape)\n",
    "vec=news_tfidf.max(axis=0)\n",
    "df = pd.DataFrame(data=vec.toarray(),columns=tfidf_vect.get_feature_names())\n",
    "df.max().sort_values()[-10:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Using your own vocabulary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(11314, 79340)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "incoming    0.925305\n",
       "siemens     0.927114\n",
       "water       0.928029\n",
       "echo        0.947289\n",
       "blah        0.951962\n",
       "dos         0.953675\n",
       "lib         0.954914\n",
       "forged      0.978762\n",
       "la          0.982737\n",
       "ax          0.999999\n",
       "dtype: float64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read in scrabble dictionary from file\n",
    "with open('data/ospd.txt') as f:\n",
    "    vocab = f.read().split('\\n')\n",
    "    \n",
    "# now lets do the transformation with a custom vocabulary\n",
    "tfidf_vect = TfidfVectorizer(vocabulary=vocab)\n",
    "news_tfidf = tfidf_vect.fit_transform(bunch.data) \n",
    "print(news_tfidf.shape)\n",
    "vec=news_tfidf.max(axis=0)\n",
    "df = pd.DataFrame(data=vec.toarray(),columns=tfidf_vect.get_feature_names())\n",
    "df.max().sort_values()[-10:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "Looking for how to do a word cloud? Check this out:\n",
    "- https://github.com/amueller/word_cloud\n",
    "\n",
    "Want to perform more serious NLP with richer options:\n",
    "- http://www.nltk.org"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
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