art_nyt_ft_keywords.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Art &The New York Times &The Financial Times & keywords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import string\n",
    "\n",
    "import nltk\n",
    "from nltk.corpus import stopwords\n",
    "from nltk.util import ngrams\n",
    "\n",
    "import blaze\n",
    "import matplotlib\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## NYT & FT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "nyt_data = pd.read_csv('art_nyt_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ft_data = pd.read_csv('art_ft_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_ngrams(sentence):\n",
    "    result = []\n",
    "    tokens = nltk.word_tokenize(sentence.lower())\n",
    "    tokens = [t for t in tokens if t not in string.punctuation]\n",
    "    for n in range(1, 4):\n",
    "        result.extend(ngrams(tokens, n))\n",
    "    result = [' '.join(r) for r in result]\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_ngrams_df(df, sentiment=None): # sentiment = pos, neg\n",
    "    result = []\n",
    "    for index, row in df.iterrows():\n",
    "        if not sentiment:\n",
    "            result.extend(get_ngrams(row['sentence']))\n",
    "        if sentiment == 'pos' and row['sentiment'] == 'pos':\n",
    "            result.extend(get_ngrams(row['sentence']))\n",
    "        if sentiment == 'neg' and row['sentiment'] == 'neg':\n",
    "            result.extend(get_ngrams(row['sentence']))\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "nytt = get_ngrams_df(nyt_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1260867"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(nytt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# nytp = get_ngrams_df(nyt_data, 'pos')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "983391"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# len(nytp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# nytn = get_ngrams_df(nyt_data, 'neg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "277476"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# len(nytn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "ftt = get_ngrams_df(ft_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "318960"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(ftt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# ftp = get_ngrams_df(ft_data, 'pos')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "237084"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# len(ftp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# ftn = get_ngrams_df(ft_data, 'neg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "81876"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# len(ftn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.9530568096313017"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(nytt) / len(ftt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def all_are_stopwords(ngr):\n",
    "    tokens = set(nltk.word_tokenize(ngr))\n",
    "    return tokens.intersection(stopwords.words('english')) == tokens\n",
    "\n",
    "def top_words(data, n):\n",
    "    result = []\n",
    "    fd = nltk.FreqDist(data)\n",
    "    most_common = fd.most_common()\n",
    "    count = 0\n",
    "    for w, f in most_common:\n",
    "        if not all_are_stopwords(w):\n",
    "            result.append(w)\n",
    "            count += 1\n",
    "        if count >= n:\n",
    "            break\n",
    "    return result\n",
    "\n",
    "def top_words_freq(data, n):\n",
    "    result = []\n",
    "    fd = nltk.FreqDist(data)\n",
    "    most_common = fd.most_common()\n",
    "    count = 0\n",
    "    for w, f in most_common:\n",
    "        if not all_are_stopwords(w):\n",
    "            result.append((w, f))\n",
    "            count += 1\n",
    "        if count >= n:\n",
    "            break\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "nyttt = top_words(nytt, 50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(nyttt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fttt = top_words(ftt, 50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(fttt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "inter = set(nyttt).intersection(fttt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "22"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(inter)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "nyttt = top_words_freq(nytt, 50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('director', 5547),\n",
       " ('art', 5453),\n",
       " ('executive', 4857),\n",
       " ('arts', 3693),\n",
       " (\"'s\", 3092),\n",
       " ('artistic', 2976),\n",
       " ('manager', 2647),\n",
       " ('founder', 2493),\n",
       " ('new', 2446),\n",
       " ('artistic director', 2415),\n",
       " ('said', 2229),\n",
       " ('executive director', 2054),\n",
       " ('director of', 1863),\n",
       " ('artists', 1861),\n",
       " (\"''\", 1859),\n",
       " ('m', 1599),\n",
       " ('artist', 1395),\n",
       " ('museum', 1378),\n",
       " ('center', 1307),\n",
       " ('theater', 1217),\n",
       " ('founder of', 1206),\n",
       " ('mr.', 1152),\n",
       " ('york', 1137),\n",
       " ('company', 1112),\n",
       " ('new york', 1106),\n",
       " ('director of the', 1090),\n",
       " ('chief', 1016),\n",
       " ('executive director of', 981),\n",
       " ('president', 962),\n",
       " ('chief executive', 878),\n",
       " ('music', 834),\n",
       " ('general', 812),\n",
       " ('and artistic', 809),\n",
       " ('museum of', 807),\n",
       " ('the arts', 798),\n",
       " ('founder and', 787),\n",
       " ('and artistic director', 780),\n",
       " ('chairman', 752),\n",
       " ('of art', 740),\n",
       " ('--', 737),\n",
       " ('the art', 707),\n",
       " ('the founder', 656),\n",
       " ('producer', 654),\n",
       " ('the executive', 650),\n",
       " ('like', 648),\n",
       " ('founder of the', 640),\n",
       " ('production', 632),\n",
       " ('presented', 619),\n",
       " ('f', 618),\n",
       " ('american', 615)]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nyttt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "nyttt = [\n",
    "    ('director', 5547),\n",
    "    ('art', 5453),\n",
    "    ('executive', 4857),\n",
    "    ('arts', 3693),\n",
    "    ('artistic', 2976),\n",
    "    ('manager', 2647),\n",
    "    ('founder', 2493),\n",
    "    ('new', 2446),\n",
    "    ('artistic director', 2415),\n",
    "    ('said', 2229),\n",
    "    ('executive director', 2054),\n",
    "    ('artists', 1861),\n",
    "    ('artist', 1395),\n",
    "    ('museum', 1378),\n",
    "    ('center', 1307),\n",
    "    ('theater', 1217),\n",
    "    ('mr.', 1152),\n",
    "    ('york', 1137),\n",
    "    ('company', 1112),\n",
    "    ('new york', 1106),\n",
    "    ('chief', 1016),\n",
    "    ('president', 962),\n",
    "    ('chief executive', 878),\n",
    "    ('music', 834),\n",
    "    ('general', 812),\n",
    "    ('chairman', 752),\n",
    "    ('producer', 654),\n",
    "    ('like', 648),\n",
    "    ('production', 632),\n",
    "    ('presented', 619),\n",
    "    ('american', 615)\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "31"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(nyttt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "fttt = top_words_freq(ftt, 50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(\"'s\", 1337),\n",
       " ('art', 1307),\n",
       " ('executive', 1128),\n",
       " ('``', 968),\n",
       " (\"''\", 891),\n",
       " ('chief', 860),\n",
       " ('chief executive', 805),\n",
       " ('arts', 628),\n",
       " ('artists', 488),\n",
       " ('founder', 483),\n",
       " ('executive of', 448),\n",
       " ('chairman', 440),\n",
       " ('chief executive of', 439),\n",
       " ('new', 392),\n",
       " ('says', 367),\n",
       " ('said', 358),\n",
       " ('artist', 340),\n",
       " ('manager', 285),\n",
       " ('director', 283),\n",
       " ('company', 279),\n",
       " ('former', 257),\n",
       " ('group', 253),\n",
       " ('music', 248),\n",
       " ('ceo', 237),\n",
       " ('founder of', 235),\n",
       " ('one', 222),\n",
       " ('business', 217),\n",
       " ('year', 206),\n",
       " ('president', 203),\n",
       " (\"'' says\", 185),\n",
       " ('chairman and', 185),\n",
       " ('and ceo', 173),\n",
       " ('co-founder', 168),\n",
       " ('london', 167),\n",
       " ('artistic', 162),\n",
       " ('electronic', 159),\n",
       " ('quot', 158),\n",
       " ('mr', 155),\n",
       " ('the art', 155),\n",
       " ('electronic arts', 154),\n",
       " ('would', 154),\n",
       " ('first', 144),\n",
       " ('also', 144),\n",
       " ('us', 140),\n",
       " ('contemporary', 137),\n",
       " ('of art', 136),\n",
       " ('last', 136),\n",
       " ('apple', 136),\n",
       " ('google', 136),\n",
       " ('entrepreneur', 133)]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fttt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fttt = [\n",
    "    ('art', 1307),\n",
    "    ('executive', 1128),\n",
    "    ('chief', 860),\n",
    "    ('chief executive', 805),\n",
    "    ('arts', 628),\n",
    "    ('artists', 488),\n",
    "    ('founder', 483),\n",
    "    ('chairman', 440),\n",
    "    ('new', 392),\n",
    "    ('says', 367),\n",
    "    ('said', 358),\n",
    "    ('artist', 340),\n",
    "    ('manager', 285),\n",
    "    ('director', 283),\n",
    "    ('company', 279),\n",
    "    ('former', 257),\n",
    "    ('group', 253),\n",
    "    ('music', 248),\n",
    "    ('ceo', 237),\n",
    "    ('one', 222),\n",
    "    ('business', 217),\n",
    "    ('year', 206),\n",
    "    ('president', 203),\n",
    "    ('co-founder', 168),\n",
    "    ('london', 167),\n",
    "    ('artistic', 162),\n",
    "    ('electronic', 159),\n",
    "    ('quot', 158),\n",
    "    ('mr.', 155),\n",
    "    ('would', 154),\n",
    "    ('electronic arts', 154),\n",
    "    ('also', 144),\n",
    "    ('first', 144),\n",
    "    ('us', 140),\n",
    "    ('contemporary', 137),\n",
    "    ('last', 136),\n",
    "    ('google', 136),\n",
    "    ('apple', 136),\n",
    "    ('entrepreneur', 133)\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 257,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "39"
      ]
     },
     "execution_count": 257,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(fttt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'american': 615,\n",
       " 'art': 5453,\n",
       " 'artist': 1395,\n",
       " 'artistic': 2976,\n",
       " 'artistic director': 2415,\n",
       " 'artists': 1861,\n",
       " 'arts': 3693,\n",
       " 'center': 1307,\n",
       " 'chairman': 752,\n",
       " 'chief': 1016,\n",
       " 'chief executive': 878,\n",
       " 'company': 1112,\n",
       " 'director': 5547,\n",
       " 'executive': 4857,\n",
       " 'executive director': 2054,\n",
       " 'founder': 2493,\n",
       " 'general': 812,\n",
       " 'like': 648,\n",
       " 'manager': 2647,\n",
       " 'mr.': 1152,\n",
       " 'museum': 1378,\n",
       " 'music': 834,\n",
       " 'new': 2446,\n",
       " 'new york': 1106,\n",
       " 'presented': 619,\n",
       " 'president': 962,\n",
       " 'producer': 654,\n",
       " 'production': 632,\n",
       " 'said': 2229,\n",
       " 'theater': 1217,\n",
       " 'york': 1137}"
      ]
     },
     "execution_count": 258,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nyt_dict = dict(nyttt)\n",
    "nyt_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 259,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'also': 144,\n",
       " 'apple': 136,\n",
       " 'art': 1307,\n",
       " 'artist': 340,\n",
       " 'artistic': 162,\n",
       " 'artists': 488,\n",
       " 'arts': 628,\n",
       " 'business': 217,\n",
       " 'ceo': 237,\n",
       " 'chairman': 440,\n",
       " 'chief': 860,\n",
       " 'chief executive': 805,\n",
       " 'co-founder': 168,\n",
       " 'company': 279,\n",
       " 'contemporary': 137,\n",
       " 'director': 283,\n",
       " 'electronic': 159,\n",
       " 'electronic arts': 154,\n",
       " 'entrepreneur': 133,\n",
       " 'executive': 1128,\n",
       " 'first': 144,\n",
       " 'former': 257,\n",
       " 'founder': 483,\n",
       " 'google': 136,\n",
       " 'group': 253,\n",
       " 'last': 136,\n",
       " 'london': 167,\n",
       " 'manager': 285,\n",
       " 'mr.': 155,\n",
       " 'music': 248,\n",
       " 'new': 392,\n",
       " 'one': 222,\n",
       " 'president': 203,\n",
       " 'quot': 158,\n",
       " 'said': 358,\n",
       " 'says': 367,\n",
       " 'us': 140,\n",
       " 'would': 154,\n",
       " 'year': 206}"
      ]
     },
     "execution_count": 259,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ft_dict = dict(fttt)\n",
    "ft_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 260,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "nyt_dict = dict(nyttt)\n",
    "ft_dict = dict(fttt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 261,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "nyt_sr = pd.Series(nyt_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 262,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "ft_sr = pd.Series(ft_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 263,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "news_df = pd.DataFrame({\n",
    "        'The New York Times': nyt_sr,\n",
    "        'The Financial Times': ft_sr,\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 264,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "matplotlib.rcParams['figure.figsize'] = (12, 6)\n",
    "matplotlib.rcParams.update({'figure.autolayout': True})\n",
    "font = {'size': 12}\n",
    "matplotlib.rc('font', **font)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 265,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7ff2a27207b8>"
      ]
     },
     "execution_count": 265,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/antonio/.virtualenvs/nytimes/lib/python3.4/site-packages/matplotlib/figure.py:1653: UserWarning: This figure includes Axes that are not compatible with tight_layout, so its results might be incorrect.\n",
      "  warnings.warn(\"This figure includes Axes that are not \"\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA1QAAAGkCAYAAAA2bGRtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nP2Laf1Eaxee0AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff2a26f3198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "news_df.plot(kind='bar', color=['r', 'b'], title='The New York Times vs. The Financial Times: top 50 keywords (absolute values)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 266,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "norm_ft_dict = {}\n",
    "for k in ft_dict:\n",
    "    norm_ft_dict[k] = ft_dict[k] * 4 / 6000\n",
    "\n",
    "norm_nyt_dict = {}\n",
    "for k in nyt_dict:\n",
    "    norm_nyt_dict[k] = nyt_dict[k] / 6000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 267,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "norm_nyt_sr = pd.Series(norm_nyt_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 268,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "norm_ft_sr = pd.Series(norm_ft_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 269,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "norm_news_df = pd.DataFrame({\n",
    "        'The New York Times': norm_nyt_sr,\n",
    "        'The Financial Times': norm_ft_sr,\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 270,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7ff2a24e16d8>"
      ]
     },
     "execution_count": 270,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/antonio/.virtualenvs/nytimes/lib/python3.4/site-packages/matplotlib/figure.py:1653: UserWarning: This figure includes Axes that are not compatible with tight_layout, so its results might be incorrect.\n",
      "  warnings.warn(\"This figure includes Axes that are not \"\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA1QAAAGkCAYAAAA2bGRtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff2a2521978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "norm_news_df.plot(kind='bar', color=['r', 'b'], title='The New York Times vs. The Financial Times: top 50 keywords (normalized values)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "53"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(set(nyt_dict.keys()).union(ft_dict.keys()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## ARTSY & TWITTER"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "hashtags_data = pd.read_csv('art_twitter_top_hashtags.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>hashtag</th>\n",
       "      <th>deg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>art</td>\n",
       "      <td>1900909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>photography</td>\n",
       "      <td>242065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>painting</td>\n",
       "      <td>226498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>photo</td>\n",
       "      <td>148847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>streetart</td>\n",
       "      <td>126865</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       hashtag      deg\n",
       "0          art  1900909\n",
       "1  photography   242065\n",
       "2     painting   226498\n",
       "3        photo   148847\n",
       "4    streetart   126865"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hashtags_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "with open('gene_freqs.pickle', 'rb') as f:\n",
    "    gene_freqs = pickle.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "with open('total_gene_freqs.pickle', 'rb') as f:\n",
    "    total_gene_freqs = pickle.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "443"
      ]
     },
     "execution_count": 219,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(gene_freqs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "560"
      ]
     },
     "execution_count": 220,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(total_gene_freqs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "560"
      ]
     },
     "execution_count": 223,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(set(total_gene_freqs.keys()).union(gene_freqs.keys()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "with open('gene_list.pickle', 'rb') as f:\n",
    "    gene_list = pickle.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "gene_freqs_data = pd.DataFrame(list(gene_freqs.items()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "443"
      ]
     },
     "execution_count": 225,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(gene_freqs_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Classical Mythology</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Earth Tones</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Northern Renaissance</td>\n",
       "      <td>139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Silver</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>History Painting</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      0    1\n",
       "0   Classical Mythology   58\n",
       "1           Earth Tones   14\n",
       "2  Northern Renaissance  139\n",
       "3                Silver    2\n",
       "4      History Painting   27"
      ]
     },
     "execution_count": 226,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gene_freqs_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "hashtag_dict = {}\n",
    "for index, row in hashtags_data[1:51].iterrows():\n",
    "    hashtag_dict[row['hashtag']] = row['deg']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "gene_dict = {}\n",
    "for index, row in gene_freqs_data.sort([1], ascending=[0])[:50].iterrows():\n",
    "    gene_dict[row[0].lower()] = row[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7ff2a30da438>"
      ]
     },
     "execution_count": 232,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/antonio/.virtualenvs/nytimes/lib/python3.4/site-packages/matplotlib/figure.py:1653: UserWarning: This figure includes Axes that are not compatible with tight_layout, so its results might be incorrect.\n",
      "  warnings.warn(\"This figure includes Axes that are not \"\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA1QAAAGkCAYAAAA2bGRtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff2a311edd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "matplotlib.rcParams['figure.figsize'] = (12, 6)\n",
    "pd.Series(hashtag_dict).plot(kind='bar', title='Twitter\\'s top 50 hashtags')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7ff2a31ec3c8>"
      ]
     },
     "execution_count": 230,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/antonio/.virtualenvs/nytimes/lib/python3.4/site-packages/matplotlib/figure.py:1653: UserWarning: This figure includes Axes that are not compatible with tight_layout, so its results might be incorrect.\n",
      "  warnings.warn(\"This figure includes Axes that are not \"\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA1QAAAGkCAYAAAA2bGRtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff2a3231cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "matplotlib.rcParams['figure.figsize'] = (12, 6)\n",
    "pd.Series(gene_dict).plot(kind='bar', title='Artsy\\'s top 50 genes')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'drawing', 'nature', 'painting', 'photography'}"
      ]
     },
     "execution_count": 231,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "set(gene_dict.keys()).intersection(hashtag_dict.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.4.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}