Country Inspector Analysis Generator.ipynb

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  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "What's for those recently in confucian wikipedias, what's "
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd\n",
      "import numpy\n",
      "from collections import defaultdict\n",
      "import json\n",
      "import statsmodels.api as sm\n",
      "from matplotlib.pylab import style\n",
      "style.use('fivethirtyeight')\n",
      "%pylab inline\n",
      "java_min_int = -2147483648\n",
      "WIKIS =('jawiki', 'tlwiki', 'urwiki', 'zhwiki', 'dewiki', 'enwiki','kowiki')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Populating the interactive namespace from numpy and matplotlib\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "WARNING: pylab import has clobbered these variables: ['f']\n",
        "`%matplotlib` prevents importing * from pylab and numpy\n"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "allrecs = pd.read_csv('snapshot_data/2014-10-13/gender-index-data-2014-10-13.csv',na_values=[java_min_int])\n",
      "def split_column(q_str):\n",
      "    if type(q_str) is float:\n",
      "        if numpy.isnan(q_str):\n",
      "            return q_str \n",
      "    if type(q_str) is str:\n",
      "        qs = q_str.split('|')\n",
      "        return qs[:-1] #cos the format will always end with a |\n",
      "\n",
      "for col in ['gender','site_links']:\n",
      "    allrecs[col] = allrecs[col].apply(split_column)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def has(xxwiki):\n",
      "    def has_xx(row):\n",
      "        if isinstance(row['site_links'], list):\n",
      "            return xxwiki in row['site_links']\n",
      "        else: return False\n",
      "    return has_xx"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "generate files"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "allrecs.head(20)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>qid</th>\n",
        "      <th>dob</th>\n",
        "      <th>dod</th>\n",
        "      <th>gender</th>\n",
        "      <th>ethnic_group</th>\n",
        "      <th>citizenship</th>\n",
        "      <th>place_of_birth</th>\n",
        "      <th>site_links</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0 </th>\n",
        "      <td>  Q23</td>\n",
        "      <td> 1732</td>\n",
        "      <td> 1799</td>\n",
        "      <td> [Q6581097]</td>\n",
        "      <td> NaN</td>\n",
        "      <td>                 Q30|</td>\n",
        "      <td>   Q494413|</td>\n",
        "      <td> [zhwiki, kywiki, euwiki, plwiki, bswiki, angwi...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1 </th>\n",
        "      <td>  Q42</td>\n",
        "      <td> 1952</td>\n",
        "      <td> 2001</td>\n",
        "      <td> [Q6581097]</td>\n",
        "      <td> NaN</td>\n",
        "      <td>                Q145|</td>\n",
        "      <td>      Q350|</td>\n",
        "      <td> [zhwiki, jvwiki, euwiki, plwiki, bswiki, eswik...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2 </th>\n",
        "      <td> Q207</td>\n",
        "      <td> 1946</td>\n",
        "      <td>  NaN</td>\n",
        "      <td> [Q6581097]</td>\n",
        "      <td> NaN</td>\n",
        "      <td>                 Q30|</td>\n",
        "      <td>    Q49145|</td>\n",
        "      <td> [uzwiki, eswiki, kowikiquote, huwiki, liwikiqu...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3 </th>\n",
        "      <td> Q297</td>\n",
        "      <td>  NaN</td>\n",
        "      <td> 1660</td>\n",
        "      <td> [Q6581097]</td>\n",
        "      <td> NaN</td>\n",
        "      <td>                 Q29|</td>\n",
        "      <td>     Q8717|</td>\n",
        "      <td> [zhwiki, kywiki, plwiki, euwiki, bswiki, uzwik...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4 </th>\n",
        "      <td> Q326</td>\n",
        "      <td> 1942</td>\n",
        "      <td>  NaN</td>\n",
        "      <td> [Q6581097]</td>\n",
        "      <td> NaN</td>\n",
        "      <td>            Q298|Q39|</td>\n",
        "      <td>     Q2887|</td>\n",
        "      <td> [zhwiki, plwiki, euwiki, kowiki, frwiki, eswik...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5 </th>\n",
        "      <td> Q368</td>\n",
        "      <td> 1915</td>\n",
        "      <td> 2006</td>\n",
        "      <td> [Q6581097]</td>\n",
        "      <td> NaN</td>\n",
        "      <td>                Q298|</td>\n",
        "      <td>    Q33986|</td>\n",
        "      <td> [lbwiki, zhwiki, plwiki, euwiki, bswiki, angwi...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6 </th>\n",
        "      <td> Q377</td>\n",
        "      <td> 1882</td>\n",
        "      <td> 1942</td>\n",
        "      <td> [Q6581097]</td>\n",
        "      <td> NaN</td>\n",
        "      <td> Q34266|Q2895|Q15180|</td>\n",
        "      <td>   Q658871|</td>\n",
        "      <td> [zhwiki, kywiki, ukwikisource, jvwiki, plwiki,...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7 </th>\n",
        "      <td> Q475</td>\n",
        "      <td> 1911</td>\n",
        "      <td> 1982</td>\n",
        "      <td> [Q6581097]</td>\n",
        "      <td> NaN</td>\n",
        "      <td>                Q298|</td>\n",
        "      <td>     Q2887|</td>\n",
        "      <td> [plwiki, euwiki, kowiki, frwiki, eswiki, yowik...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8 </th>\n",
        "      <td> Q501</td>\n",
        "      <td> 1821</td>\n",
        "      <td> 1867</td>\n",
        "      <td> [Q6581097]</td>\n",
        "      <td> NaN</td>\n",
        "      <td>                Q142|</td>\n",
        "      <td>       Q90|</td>\n",
        "      <td> [zhwiki, glwikisource, plwiki, euwiki, bswiki,...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9 </th>\n",
        "      <td> Q530</td>\n",
        "      <td> 1956</td>\n",
        "      <td>  NaN</td>\n",
        "      <td> [Q6581097]</td>\n",
        "      <td> NaN</td>\n",
        "      <td>                 Q34|</td>\n",
        "      <td>   Q499415|</td>\n",
        "      <td> [plwiki, euwiki, frwiki, bswiki, bewiki, eswik...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td> Q555</td>\n",
        "      <td> 1973</td>\n",
        "      <td>  NaN</td>\n",
        "      <td> [Q6581072]</td>\n",
        "      <td> NaN</td>\n",
        "      <td>                 Q30|</td>\n",
        "      <td>  Q1020700|</td>\n",
        "      <td> [zhwiki, eowiki, plwiki, kowiki, ruwiki, frwik...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>11</th>\n",
        "      <td> Q619</td>\n",
        "      <td> 1473</td>\n",
        "      <td> 1543</td>\n",
        "      <td> [Q6581097]</td>\n",
        "      <td> NaN</td>\n",
        "      <td>                 Q36|</td>\n",
        "      <td>    Q47554|</td>\n",
        "      <td> [szlwiki, zhwiki, kywiki, plwiki, euwiki, bswi...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>12</th>\n",
        "      <td> Q633</td>\n",
        "      <td> 1945</td>\n",
        "      <td>  NaN</td>\n",
        "      <td> [Q6581097]</td>\n",
        "      <td> NaN</td>\n",
        "      <td>                 Q16|</td>\n",
        "      <td>      Q172|</td>\n",
        "      <td> [euwikiquote, zhwiki, plwiki, euwiki, eswiki, ...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>13</th>\n",
        "      <td> Q635</td>\n",
        "      <td>  -68</td>\n",
        "      <td>  -29</td>\n",
        "      <td> [Q6581072]</td>\n",
        "      <td> NaN</td>\n",
        "      <td>              Q11768|</td>\n",
        "      <td>       Q87|</td>\n",
        "      <td> [zhwiki, plwiki, euwiki, bswiki, uzwiki, eswik...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>14</th>\n",
        "      <td> Q747</td>\n",
        "      <td> 1606</td>\n",
        "      <td> 1684</td>\n",
        "      <td> [Q6581097]</td>\n",
        "      <td> NaN</td>\n",
        "      <td>              Q70972|</td>\n",
        "      <td>    Q30974|</td>\n",
        "      <td> [lbwiki, zhwiki, plwiki, euwiki, bswiki, eswik...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>15</th>\n",
        "      <td> Q815</td>\n",
        "      <td> 1898</td>\n",
        "      <td> 1980</td>\n",
        "      <td> [Q6581097]</td>\n",
        "      <td> NaN</td>\n",
        "      <td>                Q298|</td>\n",
        "      <td>    Q14467|</td>\n",
        "      <td> [ptwiki, plwiki, ruwiki, kowiki, frwiki, enwik...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>16</th>\n",
        "      <td> Q849</td>\n",
        "      <td> 1431</td>\n",
        "      <td> 1463</td>\n",
        "      <td> [Q6581097]</td>\n",
        "      <td> NaN</td>\n",
        "      <td>              Q70972|</td>\n",
        "      <td>       Q90|</td>\n",
        "      <td> [zhwiki, plwiki, euwiki, ptwikisource, eswiki,...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>17</th>\n",
        "      <td> Q853</td>\n",
        "      <td> 1932</td>\n",
        "      <td> 1986</td>\n",
        "      <td> [Q6581097]</td>\n",
        "      <td> NaN</td>\n",
        "      <td>              Q15180|</td>\n",
        "      <td> Q15651436|</td>\n",
        "      <td> [zhwiki, plwiki, euwiki, eswiki, afwiki, ocwik...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>18</th>\n",
        "      <td> Q859</td>\n",
        "      <td> -427</td>\n",
        "      <td> -347</td>\n",
        "      <td> [Q6581097]</td>\n",
        "      <td> NaN</td>\n",
        "      <td>             Q844930|</td>\n",
        "      <td>  Q1779520|</td>\n",
        "      <td> [uzwiki, bhwiki, eswiki, ptwikisource, huwiki,...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>19</th>\n",
        "      <td> Q873</td>\n",
        "      <td> 1949</td>\n",
        "      <td>  NaN</td>\n",
        "      <td> [Q6581072]</td>\n",
        "      <td> NaN</td>\n",
        "      <td>                 Q30|</td>\n",
        "      <td>  Q1000642|</td>\n",
        "      <td> [lbwiki, zhwiki, jvwiki, plwiki, euwiki, bswik...</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 19,
       "text": [
        "     qid   dob   dod      gender ethnic_group           citizenship  \\\n",
        "0    Q23  1732  1799  [Q6581097]          NaN                  Q30|   \n",
        "1    Q42  1952  2001  [Q6581097]          NaN                 Q145|   \n",
        "2   Q207  1946   NaN  [Q6581097]          NaN                  Q30|   \n",
        "3   Q297   NaN  1660  [Q6581097]          NaN                  Q29|   \n",
        "4   Q326  1942   NaN  [Q6581097]          NaN             Q298|Q39|   \n",
        "5   Q368  1915  2006  [Q6581097]          NaN                 Q298|   \n",
        "6   Q377  1882  1942  [Q6581097]          NaN  Q34266|Q2895|Q15180|   \n",
        "7   Q475  1911  1982  [Q6581097]          NaN                 Q298|   \n",
        "8   Q501  1821  1867  [Q6581097]          NaN                 Q142|   \n",
        "9   Q530  1956   NaN  [Q6581097]          NaN                  Q34|   \n",
        "10  Q555  1973   NaN  [Q6581072]          NaN                  Q30|   \n",
        "11  Q619  1473  1543  [Q6581097]          NaN                  Q36|   \n",
        "12  Q633  1945   NaN  [Q6581097]          NaN                  Q16|   \n",
        "13  Q635   -68   -29  [Q6581072]          NaN               Q11768|   \n",
        "14  Q747  1606  1684  [Q6581097]          NaN               Q70972|   \n",
        "15  Q815  1898  1980  [Q6581097]          NaN                 Q298|   \n",
        "16  Q849  1431  1463  [Q6581097]          NaN               Q70972|   \n",
        "17  Q853  1932  1986  [Q6581097]          NaN               Q15180|   \n",
        "18  Q859  -427  -347  [Q6581097]          NaN              Q844930|   \n",
        "19  Q873  1949   NaN  [Q6581072]          NaN                  Q30|   \n",
        "\n",
        "   place_of_birth                                         site_links  \n",
        "0        Q494413|  [zhwiki, kywiki, euwiki, plwiki, bswiki, angwi...  \n",
        "1           Q350|  [zhwiki, jvwiki, euwiki, plwiki, bswiki, eswik...  \n",
        "2         Q49145|  [uzwiki, eswiki, kowikiquote, huwiki, liwikiqu...  \n",
        "3          Q8717|  [zhwiki, kywiki, plwiki, euwiki, bswiki, uzwik...  \n",
        "4          Q2887|  [zhwiki, plwiki, euwiki, kowiki, frwiki, eswik...  \n",
        "5         Q33986|  [lbwiki, zhwiki, plwiki, euwiki, bswiki, angwi...  \n",
        "6        Q658871|  [zhwiki, kywiki, ukwikisource, jvwiki, plwiki,...  \n",
        "7          Q2887|  [plwiki, euwiki, kowiki, frwiki, eswiki, yowik...  \n",
        "8            Q90|  [zhwiki, glwikisource, plwiki, euwiki, bswiki,...  \n",
        "9        Q499415|  [plwiki, euwiki, frwiki, bswiki, bewiki, eswik...  \n",
        "10      Q1020700|  [zhwiki, eowiki, plwiki, kowiki, ruwiki, frwik...  \n",
        "11        Q47554|  [szlwiki, zhwiki, kywiki, plwiki, euwiki, bswi...  \n",
        "12          Q172|  [euwikiquote, zhwiki, plwiki, euwiki, eswiki, ...  \n",
        "13           Q87|  [zhwiki, plwiki, euwiki, bswiki, uzwiki, eswik...  \n",
        "14        Q30974|  [lbwiki, zhwiki, plwiki, euwiki, bswiki, eswik...  \n",
        "15        Q14467|  [ptwiki, plwiki, ruwiki, kowiki, frwiki, enwik...  \n",
        "16           Q90|  [zhwiki, plwiki, euwiki, ptwikisource, eswiki,...  \n",
        "17     Q15651436|  [zhwiki, plwiki, euwiki, eswiki, afwiki, ocwik...  \n",
        "18      Q1779520|  [uzwiki, bhwiki, eswiki, ptwikisource, huwiki,...  \n",
        "19      Q1000642|  [lbwiki, zhwiki, jvwiki, plwiki, euwiki, bswik...  "
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def makedecades(b,e):\n",
      "    for y in range(b, e, 10):\n",
      "        yield y, y+10\n",
      "        \n",
      "def isfemale(x):\n",
      "    if isinstance(x, list):\n",
      "        return x[0] == 'Q6581072'\n",
      "    else: return False\n",
      "def ismale(x):\n",
      "    if isinstance(x, list):\n",
      "        return x[0] == 'Q6581097'\n",
      "    else: return False\n",
      "def nogender(x):\n",
      "    if not isinstance(x, list):\n",
      "        return True\n",
      "    else: return False\n",
      "        \n",
      "for xxwiki in WIKIS:\n",
      "    has_wiki = has(xxwiki)\n",
      "    recs = allrecs[allrecs.apply(has_wiki, axis=1)]\n",
      "    for gender, gender_test in (('female', isfemale), ('male', ismale), ('nogender', nogender)):\n",
      "        grecs = recs[recs['gender'].apply(gender_test)]\n",
      "\n",
      "        for start_year, stop_year in  makedecades(1930,1990):\n",
      "            modrecs = grecs[(grecs['dob'] >= start_year) &(grecs['dob'] < stop_year)]\n",
      "            #print len(modrecs), xxwiki, start_year\n",
      "            filepath = 'helpers/inspection/{}_{}_{}.json'.format(xxwiki, start_year,gender)\n",
      "            json.dump(list(modrecs['qid']), open(filepath,'w'))\n",
      "            !scp $filepath wmflabs-tools:/home/maximilianklein/inspectionshortcut"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " 772 jawiki 1930\n",
        "1202 jawiki 1940\n",
        "1457 jawiki 1950\n",
        "2194 jawiki 1960\n",
        "3138 jawiki 1970\n",
        "4304 jawiki 1980\n",
        "4718"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " jawiki 1930\n",
        "6520 jawiki 1940\n",
        "6555 jawiki 1950\n",
        "7536 jawiki 1960\n",
        "9715 jawiki 1970\n",
        "11830 jawiki 1980\n",
        "340"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " jawiki 1930\n",
        "422 jawiki 1940\n",
        "379 jawiki 1950\n",
        "376 jawiki 1960\n",
        "379 jawiki 1970\n",
        "305 jawiki 1980\n",
        "177"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " tlwiki 1930\n",
        "235 tlwiki 1940\n",
        "294 tlwiki 1950\n",
        "427 tlwiki 1960\n",
        "625 tlwiki 1970\n",
        "837 tlwiki 1980\n",
        "359 tlwiki 1930\n",
        "480 tlwiki 1940\n",
        "479 tlwiki 1950\n",
        "557 tlwiki 1960\n",
        "598 tlwiki 1970\n",
        "683 tlwiki 1980\n",
        "0 tlwiki 1930\n",
        "1 tlwiki 1940\n",
        "2 tlwiki 1950\n",
        "2 tlwiki 1960\n",
        "6 tlwiki 1970\n",
        "3 tlwiki 1980\n",
        "109"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " urwiki 1930\n",
        "156 urwiki 1940\n",
        "189 urwiki 1950\n",
        "229 urwiki 1960\n",
        "422 urwiki 1970\n",
        "697 urwiki 1980\n",
        "176 urwiki 1930\n",
        "199 urwiki 1940\n",
        "176 urwiki 1950\n",
        "142 urwiki 1960\n",
        "126 urwiki 1970\n",
        "133 urwiki 1980\n",
        "0 urwiki 1930\n",
        "0 urwiki 1940\n",
        "0 urwiki 1950\n",
        "1 urwiki 1960\n",
        "0 urwiki 1970\n",
        "1 urwiki 1980\n",
        "307"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " zhwiki 1930\n",
        "468 zhwiki 1940\n",
        "717 zhwiki 1950\n",
        "996 zhwiki 1960\n",
        "1637 zhwiki 1970\n",
        "3014 zhwiki 1980\n",
        "2448"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " zhwiki 1930\n",
        "3339 zhwiki 1940\n",
        "3495 zhwiki 1950\n",
        "3794 zhwiki 1960\n",
        "4753 zhwiki 1970\n",
        "6477 zhwiki 1980\n",
        "257"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " zhwiki 1930\n",
        "389 zhwiki 1940\n",
        "624 zhwiki 1950\n",
        "543 zhwiki 1960\n",
        "257 zhwiki 1970\n",
        "299 zhwiki 1980\n",
        "4101"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " dewiki 1930\n",
        "7107 dewiki 1940\n",
        "8671 dewiki 1950\n",
        "10194 dewiki 1960\n",
        "10401 dewiki 1970\n",
        "10982 dewiki 1980\n",
        "31003"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " dewiki 1930\n",
        "37919 dewiki 1940\n",
        "35954"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " dewiki 1950\n",
        "33389 dewiki 1960\n",
        "28342"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " dewiki 1970\n",
        "29896 dewiki 1980\n",
        "0"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " dewiki 1930\n",
        "0 dewiki 1940\n",
        "1 dewiki 1950\n",
        "1 dewiki 1960\n",
        "0 dewiki 1970\n",
        "0 dewiki 1980\n",
        "7338"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " enwiki 1930\n",
        "12475 enwiki 1940\n",
        "15750 enwiki 1950\n",
        "17603 enwiki 1960\n",
        "20983"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " enwiki 1970\n",
        "24977 enwiki 1980\n",
        "50168"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " enwiki 1930\n",
        "67619"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " enwiki 1940\n",
        "71683"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " enwiki 1950\n",
        "71914"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " enwiki 1960\n",
        "78598"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " enwiki 1970\n",
        "96430"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " enwiki 1980\n",
        "48"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " enwiki 1930\n",
        "63 enwiki 1940\n",
        "88 enwiki 1950\n",
        "88 enwiki 1960\n",
        "92 enwiki 1970\n",
        "93 enwiki 1980\n",
        "215"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " kowiki 1930\n",
        "397 kowiki 1940\n",
        "552 kowiki 1950\n",
        "920 kowiki 1960\n",
        "1454 kowiki 1970\n",
        "2056 kowiki 1980\n",
        "1405 kowiki 1930\n",
        "2172 kowiki 1940\n",
        "2240 kowiki 1950\n",
        "2913"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " kowiki 1960\n",
        "3851 kowiki 1970\n",
        "5287 kowiki 1980\n",
        "8 kowiki 1930\n",
        "13 kowiki 1940\n",
        "20 kowiki 1950\n",
        "24 kowiki 1960\n",
        "37 kowiki 1970\n",
        "34 kowiki 1980\n"
       ]
      }
     ],
     "prompt_number": 40
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "then wait for the remote 200word summary task on labs under viafbot/inspection"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!mkdir helpers/inspection/expanded_descriptions"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 42
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!scp wmflabs-tools:/home/maximilianklein/inspectionshortcut/output/* helpers/inspection/expanded_descriptions/."
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r\n",
        "If you are having access problems, please see: https://wikitech.wikimedia.org/wiki/Access#Accessing_public_and_private_instances\r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1930_female_descriptions.json            0%    0     0.0KB/s   --:-- ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1930_female_descriptions.json           47%  496KB 496.0KB/s   00:01 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1930_female_descriptions.json          100% 1054KB   1.0MB/s   00:01    \r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1930_male_descriptions.json              0%    0     0.0KB/s   --:-- ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1930_male_descriptions.json             22%  592KB 592.0KB/s   00:03 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1930_male_descriptions.json             46% 1200KB 593.6KB/s   00:02 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1930_male_descriptions.json             70% 1840KB 598.2KB/s   00:01 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1930_male_descriptions.json             95% 2480KB 602.4KB/s   00:00 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1930_male_descriptions.json            100% 2604KB 650.9KB/s   00:04    \r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1940_female_descriptions.json            0%    0     0.0KB/s   --:-- ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1940_female_descriptions.json           23%  432KB 432.0KB/s   00:03 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1940_female_descriptions.json           57% 1040KB 449.6KB/s   00:01 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1940_female_descriptions.json           93% 1712KB 471.8KB/s   00:00 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1940_female_descriptions.json          100% 1824KB 456.0KB/s   00:04    \r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1940_male_descriptions.json              0%    0     0.0KB/s   --:-- ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1940_male_descriptions.json             18%  464KB 464.0KB/s   00:04 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1940_male_descriptions.json             41% 1072KB 478.4KB/s   00:03 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1940_male_descriptions.json             68% 1744KB 497.8KB/s   00:01 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1940_male_descriptions.json             93% 2384KB 512.0KB/s   00:00 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1940_male_descriptions.json            100% 2556KB 638.9KB/s   00:04    \r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1950_female_descriptions.json            0%    0     0.0KB/s   --:-- ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1950_female_descriptions.json           17%  400KB 400.0KB/s   00:04 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1950_female_descriptions.json           45% 1008KB 420.8KB/s   00:02 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1950_female_descriptions.json           74% 1648KB 442.7KB/s   00:01 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1950_female_descriptions.json          100% 2225KB 556.2KB/s   00:04    \r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1950_male_descriptions.json              0%    0     0.0KB/s   --:-- ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1950_male_descriptions.json             18%  464KB 464.0KB/s   00:04 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1950_male_descriptions.json             40% 1040KB 475.2KB/s   00:03 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1950_male_descriptions.json             64% 1648KB 488.5KB/s   00:01 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1950_male_descriptions.json             89% 2288KB 503.6KB/s   00:00 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1950_male_descriptions.json            100% 2562KB 512.3KB/s   00:05    \r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1950_nogender_descriptions.json          0%    0     0.0KB/s   --:-- ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1950_nogender_descriptions.json        100%  263     0.3KB/s   00:00    \r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1960_female_descriptions.json            0%    0     0.0KB/s   --:-- ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1960_female_descriptions.json           18%  464KB 464.0KB/s   00:04 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1960_female_descriptions.json           41% 1072KB 478.4KB/s   00:03 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1960_female_descriptions.json           66% 1712KB 494.6KB/s   00:01 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1960_female_descriptions.json           91% 2352KB 509.1KB/s   00:00 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1960_female_descriptions.json          100% 2563KB 640.8KB/s   00:04    \r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1960_male_descriptions.json              0%    0     0.0KB/s   --:-- ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1960_male_descriptions.json             16%  432KB 432.0KB/s   00:04 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1960_male_descriptions.json             41% 1072KB 452.8KB/s   00:03 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1960_male_descriptions.json             67% 1744KB 474.7KB/s   00:01 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1960_male_descriptions.json             93% 2416KB 494.5KB/s   00:00 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1960_male_descriptions.json            100% 2581KB 645.1KB/s   00:04    \r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1960_nogender_descriptions.json          0%    0     0.0KB/s   --:-- ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1960_nogender_descriptions.json        100%  257     0.3KB/s   00:00    \r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1970_female_descriptions.json            0%    0     0.0KB/s   --:-- ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1970_female_descriptions.json           18%  464KB 464.0KB/s   00:04 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1970_female_descriptions.json           43% 1104KB 481.6KB/s   00:02 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1970_female_descriptions.json           68% 1744KB 497.4KB/s   00:01 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1970_female_descriptions.json           93% 2384KB 511.7KB/s   00:00 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1970_female_descriptions.json          100% 2546KB 636.5KB/s   00:04    \r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1970_male_descriptions.json              0%    0     0.0KB/s   --:-- ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1970_male_descriptions.json             18%  464KB 464.0KB/s   00:04 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1970_male_descriptions.json             41% 1072KB 478.4KB/s   00:03 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1970_male_descriptions.json             65% 1680KB 491.4KB/s   00:01 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1970_male_descriptions.json             90% 2320KB 506.2KB/s   00:00 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1970_male_descriptions.json            100% 2574KB 643.6KB/s   00:04    \r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1980_female_descriptions.json            0%    0     0.0KB/s   --:-- ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1980_female_descriptions.json           18%  464KB 464.0KB/s   00:04 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1980_female_descriptions.json           43% 1104KB 481.6KB/s   00:02 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1980_female_descriptions.json           68% 1744KB 497.4KB/s   00:01 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1980_female_descriptions.json           88% 2256KB 498.9KB/s   00:00 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1980_female_descriptions.json          100% 2544KB 508.7KB/s   00:05    \r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1980_male_descriptions.json              0%    0     0.0KB/s   --:-- ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1980_male_descriptions.json              9%  256KB 128.0KB/s   00:18 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1980_male_descriptions.json             22%  592KB 148.8KB/s   00:13 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1980_male_descriptions.json             37%  976KB 172.3KB/s   00:09 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1980_male_descriptions.json             52% 1360KB 193.5KB/s   00:06 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1980_male_descriptions.json             78% 2032KB 241.3KB/s   00:02 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dewiki_1980_male_descriptions.json            100% 2595KB 432.5KB/s   00:06    \r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "enwiki_1930_female_descriptions.json            0%    0     0.0KB/s   --:-- ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "enwiki_1930_female_descriptions.json           24%  464KB 464.0KB/s   00:03 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "enwiki_1930_female_descriptions.json           61% 1136KB 484.8KB/s   00:01 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "enwiki_1930_female_descriptions.json          100% 1858KB 619.2KB/s   00:03    \r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "enwiki_1930_male_descriptions.json              0%    0     0.0KB/s   --:-- ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "enwiki_1930_male_descriptions.json             21%  528KB 528.0KB/s   00:03 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "enwiki_1930_male_descriptions.json             46% 1168KB 539.2KB/s   00:02 ETA"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "enwiki_1930_male_descriptions.json             76% 1904KB 558.9KB/s   00:01 ETA"
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      {
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        "\r",
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      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
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       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
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       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
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        "\r",
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       ]
      }
     ],
     "prompt_number": 78
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "description_files = !ls helpers/inspection/expanded_descriptions/\n",
      "len(description_files)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 2,
       "text": [
        "117"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "celebrity_dict = {'jawiki': [u'\u4ff3\u512a', u'\u9078\u624b', u'\u6b4c\u624b', u'\u30df\u30e5\u30fc\u30b8\u30b7\u30e3\u30f3', u'\u30e2\u30c7\u30eb', u'\u30a2\u30a4\u30c9\u30eb'], \n",
      "                              'zhwiki': [u'\u6f14\u54e1', u'\u904b\u52d5\u54e1', u'\u6b4c\u624b', u'\u97f3\u4e50\u5bb6', u'\u6a21\u7279\u5152', u'\u5076\u50cf'],\n",
      "                              'tlwiki': [u'artista', 'aktor', u'player', u'mang-aawit', u'musikero', u'modelo', u'idolo'],\n",
      "                              'urwiki': [u'\u0627\u0631\u062f\u0648', u'\u06a9\u06be\u0644\u0627\u0691', u'\u06af\u0644\u0648\u06a9\u0627\u0631' , u'\u0645\u0648\u0633\u06cc\u0642\u0627\u0631' , u'\u0645\u0627\u0688\u0644', u'\u0628\u062a'],\n",
      "                              'dewiki': [u'schauspieler' , u'spieler', u'Musiker', u'S\u00e4nger', u'Modell', u'Idol'],\n",
      "                              'enwiki' :[u'actor', u'actress', u'player', u'singer', u'musician', u'model', u'idol'],\n",
      "                              'kowiki' : [u'\ubc30\uc6b0', u'\uc120\uc218', u'\uac00\uc218', u'\uc74c\uc545\uac00', u'\ubaa8\ub378', u'\uc6b0\uc0c1']}\n",
      "\n",
      "def intext(text, xxwiki):\n",
      "    if text:\n",
      "        text = text.encode('utf-8').lower()\n",
      "        engwords = celebrity_dict['enwiki']\n",
      "        foreignwords = celebrity_dict[xxwiki]\n",
      "        for word in engwords + foreignwords:\n",
      "            if word.encode('utf-8').lower() in text:\n",
      "                return True\n",
      "        #if we get to this point its too late\n",
      "        return False\n",
      "    else: return False\n",
      "\n",
      "\n",
      "celebdf = pd.DataFrame(columns=['wiki','decade','gender','celeb_per'])\n",
      "for f in description_files:\n",
      "    parts = f.split('_')\n",
      "    xxwiki, decade, gender = parts[0], parts[1], parts[2]\n",
      "    df = pd.DataFrame.from_dict(json.load(open('helpers/inspection/expanded_descriptions/{}'.format(f), 'r')), orient='index')\n",
      "    df['celeb'] = df['text'].apply(lambda text: intext(text,xxwiki))\n",
      "    test_per = df['celeb'].sum()/float(len(df))\n",
      "    celebdf = celebdf.append({'wiki':xxwiki, 'decade':int(decade), 'gender':gender, 'celeb_per':test_per}, ignore_index=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dummy_langs = pd.get_dummies(celebdf['wiki'])\n",
      "dummy_gender = pd.get_dummies(celebdf['gender'])\n",
      "dummy_gender = dummy_gender[['male','female','nogender']]\n",
      "print dummy_langs.head(2)\n",
      "print dummy_gender.head(2)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "   dewiki  enwiki  jawiki  kowiki  tlwiki  urwiki  zhwiki\n",
        "0       1       0       0       0       0       0       0\n",
        "1       1       0       0       0       0       0       0\n",
        "   male  female  nogender\n",
        "0     0       1         0\n",
        "1     1       0         0\n"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "catdf = celebdf[['celeb_per','decade']].join(dummy_langs.ix[:,'enwiki':]).join(dummy_gender.ix[:,'female':'female'])\n",
      "catdf['intercept'] = 1.0"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "catdf.corr()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>celeb_per</th>\n",
        "      <th>decade</th>\n",
        "      <th>enwiki</th>\n",
        "      <th>jawiki</th>\n",
        "      <th>kowiki</th>\n",
        "      <th>tlwiki</th>\n",
        "      <th>urwiki</th>\n",
        "      <th>zhwiki</th>\n",
        "      <th>female</th>\n",
        "      <th>intercept</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>celeb_per</th>\n",
        "      <td> 1.000000</td>\n",
        "      <td> 0.284661</td>\n",
        "      <td>-0.290744</td>\n",
        "      <td>-0.079482</td>\n",
        "      <td> 0.125096</td>\n",
        "      <td> 0.606231</td>\n",
        "      <td> 0.017558</td>\n",
        "      <td>-0.154101</td>\n",
        "      <td> 0.460273</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>decade</th>\n",
        "      <td> 0.284661</td>\n",
        "      <td> 1.000000</td>\n",
        "      <td>-0.011882</td>\n",
        "      <td>-0.011882</td>\n",
        "      <td>-0.011882</td>\n",
        "      <td> 0.024452</td>\n",
        "      <td> 0.036556</td>\n",
        "      <td>-0.011882</td>\n",
        "      <td>-0.020852</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>enwiki</th>\n",
        "      <td>-0.290744</td>\n",
        "      <td>-0.011882</td>\n",
        "      <td> 1.000000</td>\n",
        "      <td>-0.181818</td>\n",
        "      <td>-0.181818</td>\n",
        "      <td>-0.175810</td>\n",
        "      <td>-0.157204</td>\n",
        "      <td>-0.181818</td>\n",
        "      <td>-0.022792</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>jawiki</th>\n",
        "      <td>-0.079482</td>\n",
        "      <td>-0.011882</td>\n",
        "      <td>-0.181818</td>\n",
        "      <td> 1.000000</td>\n",
        "      <td>-0.181818</td>\n",
        "      <td>-0.175810</td>\n",
        "      <td>-0.157204</td>\n",
        "      <td>-0.181818</td>\n",
        "      <td>-0.022792</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>kowiki</th>\n",
        "      <td> 0.125096</td>\n",
        "      <td>-0.011882</td>\n",
        "      <td>-0.181818</td>\n",
        "      <td>-0.181818</td>\n",
        "      <td> 1.000000</td>\n",
        "      <td>-0.175810</td>\n",
        "      <td>-0.157204</td>\n",
        "      <td>-0.181818</td>\n",
        "      <td>-0.022792</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>tlwiki</th>\n",
        "      <td> 0.606231</td>\n",
        "      <td> 0.024452</td>\n",
        "      <td>-0.175810</td>\n",
        "      <td>-0.175810</td>\n",
        "      <td>-0.175810</td>\n",
        "      <td> 1.000000</td>\n",
        "      <td>-0.152009</td>\n",
        "      <td>-0.175810</td>\n",
        "      <td>-0.005186</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>urwiki</th>\n",
        "      <td> 0.017558</td>\n",
        "      <td> 0.036556</td>\n",
        "      <td>-0.157204</td>\n",
        "      <td>-0.157204</td>\n",
        "      <td>-0.157204</td>\n",
        "      <td>-0.152009</td>\n",
        "      <td> 1.000000</td>\n",
        "      <td>-0.157204</td>\n",
        "      <td> 0.053489</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>zhwiki</th>\n",
        "      <td>-0.154101</td>\n",
        "      <td>-0.011882</td>\n",
        "      <td>-0.181818</td>\n",
        "      <td>-0.181818</td>\n",
        "      <td>-0.181818</td>\n",
        "      <td>-0.175810</td>\n",
        "      <td>-0.157204</td>\n",
        "      <td> 1.000000</td>\n",
        "      <td>-0.022792</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>female</th>\n",
        "      <td> 0.460273</td>\n",
        "      <td>-0.020852</td>\n",
        "      <td>-0.022792</td>\n",
        "      <td>-0.022792</td>\n",
        "      <td>-0.022792</td>\n",
        "      <td>-0.005186</td>\n",
        "      <td> 0.053489</td>\n",
        "      <td>-0.022792</td>\n",
        "      <td> 1.000000</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>intercept</th>\n",
        "      <td>      NaN</td>\n",
        "      <td>      NaN</td>\n",
        "      <td>      NaN</td>\n",
        "      <td>      NaN</td>\n",
        "      <td>      NaN</td>\n",
        "      <td>      NaN</td>\n",
        "      <td>      NaN</td>\n",
        "      <td>      NaN</td>\n",
        "      <td>      NaN</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "           celeb_per    decade    enwiki    jawiki    kowiki    tlwiki  \\\n",
        "celeb_per   1.000000  0.284661 -0.290744 -0.079482  0.125096  0.606231   \n",
        "decade      0.284661  1.000000 -0.011882 -0.011882 -0.011882  0.024452   \n",
        "enwiki     -0.290744 -0.011882  1.000000 -0.181818 -0.181818 -0.175810   \n",
        "jawiki     -0.079482 -0.011882 -0.181818  1.000000 -0.181818 -0.175810   \n",
        "kowiki      0.125096 -0.011882 -0.181818 -0.181818  1.000000 -0.175810   \n",
        "tlwiki      0.606231  0.024452 -0.175810 -0.175810 -0.175810  1.000000   \n",
        "urwiki      0.017558  0.036556 -0.157204 -0.157204 -0.157204 -0.152009   \n",
        "zhwiki     -0.154101 -0.011882 -0.181818 -0.181818 -0.181818 -0.175810   \n",
        "female      0.460273 -0.020852 -0.022792 -0.022792 -0.022792 -0.005186   \n",
        "intercept        NaN       NaN       NaN       NaN       NaN       NaN   \n",
        "\n",
        "             urwiki    zhwiki    female  intercept  \n",
        "celeb_per  0.017558 -0.154101  0.460273        NaN  \n",
        "decade     0.036556 -0.011882 -0.020852        NaN  \n",
        "enwiki    -0.157204 -0.181818 -0.022792        NaN  \n",
        "jawiki    -0.157204 -0.181818 -0.022792        NaN  \n",
        "kowiki    -0.157204 -0.181818 -0.022792        NaN  \n",
        "tlwiki    -0.152009 -0.175810 -0.005186        NaN  \n",
        "urwiki     1.000000 -0.157204  0.053489        NaN  \n",
        "zhwiki    -0.157204  1.000000 -0.022792        NaN  \n",
        "female     0.053489 -0.022792  1.000000        NaN  \n",
        "intercept       NaN       NaN       NaN        NaN  "
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "train_cols = catdf.columns[1:]\n",
      "logit = sm.Logit(catdf['celeb_per'], catdf[train_cols])\n",
      "result= logit.fit()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Optimization terminated successfully.\n",
        "         Current function value: 0.466279\n",
        "         Iterations 6\n"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "result.summary()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<table class=\"simpletable\">\n",
        "<caption>Logit Regression Results</caption>\n",
        "<tr>\n",
        "  <th>Dep. Variable:</th>     <td>celeb_per</td>    <th>  No. Observations:  </th>  <td>   117</td>  \n",
        "</tr>\n",
        "<tr>\n",
        "  <th>Model:</th>               <td>Logit</td>      <th>  Df Residuals:      </th>  <td>   108</td>  \n",
        "</tr>\n",
        "<tr>\n",
        "  <th>Method:</th>               <td>MLE</td>       <th>  Df Model:          </th>  <td>     8</td>  \n",
        "</tr>\n",
        "<tr>\n",
        "  <th>Date:</th>          <td>Wed, 07 Jan 2015</td> <th>  Pseudo R-squ.:     </th>  <td>0.3079</td>  \n",
        "</tr>\n",
        "<tr>\n",
        "  <th>Time:</th>              <td>11:25:05</td>     <th>  Log-Likelihood:    </th> <td> -54.555</td> \n",
        "</tr>\n",
        "<tr>\n",
        "  <th>converged:</th>           <td>True</td>       <th>  LL-Null:           </th> <td> -78.830</td> \n",
        "</tr>\n",
        "<tr>\n",
        "  <th> </th>                      <td> </td>        <th>  LLR p-value:       </th> <td>7.752e-08</td>\n",
        "</tr>\n",
        "</table>\n",
        "<table class=\"simpletable\">\n",
        "<tr>\n",
        "      <td></td>         <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th> <th>[95.0% Conf. Int.]</th> \n",
        "</tr>\n",
        "<tr>\n",
        "  <th>decade</th>    <td>    0.0236</td> <td>    0.013</td> <td>    1.823</td> <td> 0.068</td> <td>   -0.002     0.049</td>\n",
        "</tr>\n",
        "<tr>\n",
        "  <th>enwiki</th>    <td>    0.0509</td> <td>    0.875</td> <td>    0.058</td> <td> 0.954</td> <td>   -1.664     1.766</td>\n",
        "</tr>\n",
        "<tr>\n",
        "  <th>jawiki</th>    <td>    0.7763</td> <td>    0.837</td> <td>    0.927</td> <td> 0.354</td> <td>   -0.865     2.418</td>\n",
        "</tr>\n",
        "<tr>\n",
        "  <th>kowiki</th>    <td>    1.3834</td> <td>    0.832</td> <td>    1.662</td> <td> 0.097</td> <td>   -0.248     3.015</td>\n",
        "</tr>\n",
        "<tr>\n",
        "  <th>tlwiki</th>    <td>    3.0009</td> <td>    0.945</td> <td>    3.176</td> <td> 0.001</td> <td>    1.149     4.853</td>\n",
        "</tr>\n",
        "<tr>\n",
        "  <th>urwiki</th>    <td>    0.8901</td> <td>    0.869</td> <td>    1.025</td> <td> 0.306</td> <td>   -0.813     2.593</td>\n",
        "</tr>\n",
        "<tr>\n",
        "  <th>zhwiki</th>    <td>    0.5383</td> <td>    0.846</td> <td>    0.637</td> <td> 0.524</td> <td>   -1.119     2.196</td>\n",
        "</tr>\n",
        "<tr>\n",
        "  <th>female</th>    <td>    1.3580</td> <td>    0.453</td> <td>    2.999</td> <td> 0.003</td> <td>    0.471     2.245</td>\n",
        "</tr>\n",
        "<tr>\n",
        "  <th>intercept</th> <td>  -47.9056</td> <td>   25.368</td> <td>   -1.888</td> <td> 0.059</td> <td>  -97.626     1.815</td>\n",
        "</tr>\n",
        "</table>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 19,
       "text": [
        "<class 'statsmodels.iolib.summary.Summary'>\n",
        "\"\"\"\n",
        "                           Logit Regression Results                           \n",
        "==============================================================================\n",
        "Dep. Variable:              celeb_per   No. Observations:                  117\n",
        "Model:                          Logit   Df Residuals:                      108\n",
        "Method:                           MLE   Df Model:                            8\n",
        "Date:                Wed, 07 Jan 2015   Pseudo R-squ.:                  0.3079\n",
        "Time:                        11:25:05   Log-Likelihood:                -54.555\n",
        "converged:                       True   LL-Null:                       -78.830\n",
        "                                        LLR p-value:                 7.752e-08\n",
        "==============================================================================\n",
        "                 coef    std err          z      P>|z|      [95.0% Conf. Int.]\n",
        "------------------------------------------------------------------------------\n",
        "decade         0.0236      0.013      1.823      0.068        -0.002     0.049\n",
        "enwiki         0.0509      0.875      0.058      0.954        -1.664     1.766\n",
        "jawiki         0.7763      0.837      0.927      0.354        -0.865     2.418\n",
        "kowiki         1.3834      0.832      1.662      0.097        -0.248     3.015\n",
        "tlwiki         3.0009      0.945      3.176      0.001         1.149     4.853\n",
        "urwiki         0.8901      0.869      1.025      0.306        -0.813     2.593\n",
        "zhwiki         0.5383      0.846      0.637      0.524        -1.119     2.196\n",
        "female         1.3580      0.453      2.999      0.003         0.471     2.245\n",
        "intercept    -47.9056     25.368     -1.888      0.059       -97.626     1.815\n",
        "==============================================================================\n",
        "\"\"\""
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "subj_list = ['female','male','nogender']\n",
      "\n",
      "fig, axes = plt.subplots(nrows = 1, ncols = len(subj_list), sharex='col', sharey='row')\n",
      "for ax, subj in zip(axes, subj_list):\n",
      "\n",
      "    natlangdf = celebdf[celebdf['gender'] == subj]\n",
      "    natlangpiv = pd.pivot_table(natlangdf, values='celeb_per', rows='decade', cols='wiki')\n",
      "    natlangpiv = natlangpiv[['jawiki','zhwiki','kowiki','tlwiki','urwiki','dewiki','enwiki']]\n",
      "    natlangpiv.columns = ['Japanese', 'Chinese', 'Korean', 'Tagalog', 'Urdu', 'German', 'English']\n",
      "    natlangpiv = natlangpiv * 100\n",
      "    heatmap = ax.pcolor(natlangpiv, cmap='Purples', vmin=0, vmax=100)\n",
      "\n",
      "    ax.set_yticks(np.arange(0.5, len(natlangpiv.index), 1))\n",
      "    ax.set_yticklabels(map(int, natlangpiv.index))\n",
      "    ax.set_xticks(np.arange(0.5, len(natlangpiv.columns), 1))\n",
      "    ax.set_xticklabels(natlangpiv.columns, rotation=90)\n",
      "\n",
      "fig.suptitle('''Heatmap of Celebrity Biography %, By Decade of Birth versus Wikipedia Language by Gender''', fontsize=18)\n",
      "fig.set_size_inches(12,4,dpi=600)\n",
      "#fig.tight_layout()\n",
      "\n",
      "subj_titles = ['Female','Male','Not Recorded or Non-Binary']\n",
      "metric_titles =['Decade'] \n",
      "\n",
      "cbar = plt.colorbar(mappable=heatmap, ax=ax, format=\"%.0f%%\")\n",
      "\n",
      "for i in range(len(subj_titles)):\n",
      "    axes[i].set_title(subj_titles[i])\n",
      "\n",
      "fig.subplots_adjust(wspace=0.0, hspace=0.0, top=0.85)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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00mhnZ4epU6eivLwc169fR1lZGfr16yeyfPb29lBQUMD58+f5zOIaQ1Db4IXx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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7fb1d249e150>"
       ]
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "subplots_adjust"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 17,
       "text": [
        "<function matplotlib.pyplot.subplots_adjust>"
       ]
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "actress_dict = {'jawiki': u'\u4ff3\u512a', 'zhwiki': u'\u6f14\u54e1', 'tlwiki':u'artista', 'urwiki': u'\u0627\u0631\u062f\u0648', 'dewiki': 'schauspieler' , 'enwiki' :'actress'}\n",
      "player_dict =   {'jawiki': u'\u9078\u624b', 'zhwiki': u'\u904b\u52d5\u54e1', 'tlwiki':u'player', 'urwiki': u'\u06a9\u06be\u0644\u0627\u0691',  'dewiki': 'spieler' , 'enwiki' :'player'}\n",
      "\n",
      "\n",
      "\n",
      "def multiword(xxwiki, prof_dict):\n",
      "    def intext(text):\n",
      "        if text:\n",
      "            text = text.lower()\n",
      "            eng = prof_dict['enwiki']\n",
      "            foreign = prof_dict[xxwiki]\n",
      "            if eng in text or foreign in text:\n",
      "                return True\n",
      "            else: return False\n",
      "        else: return False\n",
      "    return intext\n",
      "\n",
      "\n",
      "celeb = defaultdict(dict)\n",
      "for xxwiki in ('jawiki', 'tlwiki', 'urwiki', 'zhwiki', 'enwiki', 'dewiki'):\n",
      "    df = pd.DataFrame.from_dict(json.load(open('helpers/inspection/descriptions/{}_descriptions.json'.format(xxwiki), 'r')), orient='index')\n",
      "    for prof, test in (('actress',  multiword(xxwiki, actress_dict)), ('player',multiword(xxwiki, player_dict))):\n",
      "        df[prof] = df['text'].apply(test)\n",
      "        test_per = df[prof].sum()/float(len(df))\n",
      "        celeb[xxwiki][prof] = test_per\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for xxwiki in ('jawiki', 'tlwiki', 'urwiki', 'zhwiki', 'enwiki', 'dewiki'):\n",
      "    df = pd.DataFrame.from_dict(json.load(open('helpers/inspection/descriptions/{}_descriptions.json'.format(xxwiki), 'r')), orient='index')\n",
      "    df['text'] = df['text'].apply(lambda x: x.replace('\\n',' ') if x else x)\n",
      "    df.to_csv('helpers/inspection/readable/{}_modern_bios_for_inspection.csv'.format(xxwiki), encoding='utf-8')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "celebdf = pd.DataFrame.from_dict(celeb, orient='index')\n",
      "celebdf['either'] = celebdf['player'] + celebdf['actress']\n",
      "celebdf.sort('either')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>player</th>\n",
        "      <th>actress</th>\n",
        "      <th>either</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>enwiki</th>\n",
        "      <td> 0.223995</td>\n",
        "      <td> 0.042483</td>\n",
        "      <td> 0.266478</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>jawiki</th>\n",
        "      <td> 0.198402</td>\n",
        "      <td> 0.090304</td>\n",
        "      <td> 0.288705</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>dewiki</th>\n",
        "      <td> 0.287200</td>\n",
        "      <td> 0.075000</td>\n",
        "      <td> 0.362200</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>zhwiki</th>\n",
        "      <td> 0.251717</td>\n",
        "      <td> 0.121909</td>\n",
        "      <td> 0.373626</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>tlwiki</th>\n",
        "      <td> 0.068075</td>\n",
        "      <td> 0.419601</td>\n",
        "      <td> 0.487676</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>urwiki</th>\n",
        "      <td> 0.016148</td>\n",
        "      <td> 0.741638</td>\n",
        "      <td> 0.757785</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 18,
       "text": [
        "          player   actress    either\n",
        "enwiki  0.223995  0.042483  0.266478\n",
        "jawiki  0.198402  0.090304  0.288705\n",
        "dewiki  0.287200  0.075000  0.362200\n",
        "zhwiki  0.251717  0.121909  0.373626\n",
        "tlwiki  0.068075  0.419601  0.487676\n",
        "urwiki  0.016148  0.741638  0.757785"
       ]
      }
     ],
     "prompt_number": 18
    }
   ],
   "metadata": {}
  }
 ]
}