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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd\n",
      "import numpy\n",
      "from collections import defaultdict\n",
      "from matplotlib.pylab import style\n",
      "import json\n",
      "style.use('fivethirtyeight')\n",
      "%pylab inline\n",
      "java_min_int = -2147483648"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Populating the interactive namespace from numpy and matplotlib\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pywikibot\n",
      "#Tranforming QIDs into English labels.\n",
      "enwp = pywikibot.Site('en','wikipedia')\n",
      "wikidata = enwp.data_repository()\n",
      "\n",
      "retrieved = dict()\n",
      "\n",
      "def english_label(qid):\n",
      "    if qid:\n",
      "        if type(qid) is float:\n",
      "            if math.isnan(qid):\n",
      "                return None\n",
      "        #first see if we've done it\n",
      "        try:\n",
      "            return retrieved[qid]\n",
      "        except KeyError:\n",
      "            try:\n",
      "                page = pywikibot.ItemPage(wikidata, qid)\n",
      "                data = page.get()\n",
      "                lab = data['labels']['en']\n",
      "                retrieved[qid] = lab\n",
      "                return lab\n",
      "            except KeyError:\n",
      "                retrieved[qid] = qid\n",
      "                return qid\n",
      "            except:\n",
      "                return qid\n",
      "    return qid\n",
      "\n",
      "lang_map = json.load(open('helpers/wiki_code_map.json','r'))\n",
      "def lookup_lang(lang):\n",
      "    try:\n",
      "            full= lang_map[lang]\n",
      "            if full.split()[-1].lower() == 'wikipedia':\n",
      "                return ' '.join(full.split()[:-1])\n",
      "            else: return full\n",
      "    except:\n",
      "        return lang"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 106
    },
    {
     "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": [
      "allrecs.head(5)"
     ],
     "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",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "    qid   dob   dod      gender ethnic_group citizenship place_of_birth  \\\n",
        "0   Q23  1732  1799  [Q6581097]          NaN        Q30|       Q494413|   \n",
        "1   Q42  1952  2001  [Q6581097]          NaN       Q145|          Q350|   \n",
        "2  Q207  1946   NaN  [Q6581097]          NaN        Q30|        Q49145|   \n",
        "3  Q297   NaN  1660  [Q6581097]          NaN        Q29|         Q8717|   \n",
        "4  Q326  1942   NaN  [Q6581097]          NaN   Q298|Q39|         Q2887|   \n",
        "\n",
        "                                          site_links  \n",
        "0  [zhwiki, kywiki, euwiki, plwiki, bswiki, angwi...  \n",
        "1  [zhwiki, jvwiki, euwiki, plwiki, bswiki, eswik...  \n",
        "2  [uzwiki, eswiki, kowikiquote, huwiki, liwikiqu...  \n",
        "3  [zhwiki, kywiki, plwiki, euwiki, bswiki, uzwik...  \n",
        "4  [zhwiki, plwiki, euwiki, kowiki, frwiki, eswik...  "
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for row in allrecs.iterrows():\n",
      "    print(row[1][3])\n",
      "    break"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "['Q6581097']\n"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def makedict():\n",
      "    return defaultdict(int)\n",
      "\n",
      "single = defaultdict(makedict)\n",
      "many = defaultdict(makedict)\n",
      "\n",
      "\n",
      "for index, row in allrecs.iterrows():\n",
      "    try:\n",
      "        gender = row[3][0]\n",
      "    except:\n",
      "        gender = None\n",
      "    wikiname_list = row[7]\n",
      "    if isinstance(wikiname_list, list):\n",
      "        if len(wikiname_list) == 1:\n",
      "            single[wikiname_list[0]][gender] += 1\n",
      "        else:\n",
      "            for wikiname in wikiname_list:\n",
      "                many[wikiname][gender] += 1"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 32
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def makedf(indict):\n",
      "    df = pd.DataFrame.from_dict(indict, orient='index')\n",
      "    df.columns = map(english_label, df.columns)\n",
      "    df['human_total'] = df.sum(axis=1)\n",
      "    df['gendered_total'] = df['human_total'] - df[float('nan')]\n",
      "    df['nonbin_total'] = df['gendered_total'] - df['female'] - df['male']\n",
      "    df['fem_per'] = df['female'] / df['gendered_total']\n",
      "    df['nonbin_per'] = df['nonbin_total'] / df['gendered_total']\n",
      "    return df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 59
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sdf = makedf(single)\n",
      "mdf = makedf(many)\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 60
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tdf = sdf.join(mdf, how='inner', lsuffix='_single', rsuffix='_many')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 61
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tdf.fillna(0, inplace=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 62
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tdf.columns"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 65,
       "text": [
        "Index([u'male_single', u'female_single', u'None_single', u'male animal_single', u'intersex_single', u'transgender female_single', u'woman', u'transgender male_single', u'genderqueer_single', u'female animal', u'human_total_single', u'gendered_total_single', u'nonbin_total_single', u'fem_per_single', u'nonbin_per_single', u'intersex_many', u'kathoey', u'transgender male_many', u'genderqueer_many', u'transgender female_many', u'None_many', u'male_many', u'female_many', u'fa'afafine', u'male animal_many', u'human_total_many', u'gendered_total_many', u'nonbin_total_many', u'fem_per_many', u'nonbin_per_many'], dtype='object')"
       ]
      }
     ],
     "prompt_number": 65
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tdf['fem_per_diff'] = tdf['fem_per_single'] - tdf['fem_per_many']"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 68
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tdf[tdf['gendered_total_single']>7310].sort('fem_per_diff',ascending=False)[['fem_per_diff','fem_per_single','female_single','gendered_total_single','fem_per_many']]"
     ],
     "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>fem_per_diff</th>\n",
        "      <th>fem_per_single</th>\n",
        "      <th>female_single</th>\n",
        "      <th>gendered_total_single</th>\n",
        "      <th>fem_per_many</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>jawiki</th>\n",
        "      <td> 0.413549</td>\n",
        "      <td> 0.603585</td>\n",
        "      <td> 13434</td>\n",
        "      <td>  22257</td>\n",
        "      <td> 0.190037</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>hewiki</th>\n",
        "      <td> 0.060952</td>\n",
        "      <td> 0.216555</td>\n",
        "      <td>  2386</td>\n",
        "      <td>  11018</td>\n",
        "      <td> 0.155602</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>dawiki</th>\n",
        "      <td> 0.036127</td>\n",
        "      <td> 0.181383</td>\n",
        "      <td>  2233</td>\n",
        "      <td>  12311</td>\n",
        "      <td> 0.145256</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>nowiki</th>\n",
        "      <td> 0.029112</td>\n",
        "      <td> 0.227961</td>\n",
        "      <td>  4277</td>\n",
        "      <td>  18762</td>\n",
        "      <td> 0.198849</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>svwiki</th>\n",
        "      <td> 0.020537</td>\n",
        "      <td> 0.213389</td>\n",
        "      <td>  8772</td>\n",
        "      <td>  41108</td>\n",
        "      <td> 0.192852</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ukwiki</th>\n",
        "      <td> 0.001318</td>\n",
        "      <td> 0.137714</td>\n",
        "      <td>  2953</td>\n",
        "      <td>  21443</td>\n",
        "      <td> 0.136396</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>fiwiki</th>\n",
        "      <td>-0.000251</td>\n",
        "      <td> 0.167975</td>\n",
        "      <td>  3145</td>\n",
        "      <td>  18723</td>\n",
        "      <td> 0.168226</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>dewiki</th>\n",
        "      <td>-0.000691</td>\n",
        "      <td> 0.149034</td>\n",
        "      <td> 30335</td>\n",
        "      <td> 203544</td>\n",
        "      <td> 0.149725</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>plwiki</th>\n",
        "      <td>-0.008691</td>\n",
        "      <td> 0.149597</td>\n",
        "      <td> 10353</td>\n",
        "      <td>  69206</td>\n",
        "      <td> 0.158288</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>frwiki</th>\n",
        "      <td>-0.012200</td>\n",
        "      <td> 0.142818</td>\n",
        "      <td> 14247</td>\n",
        "      <td>  99756</td>\n",
        "      <td> 0.155018</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>nlwiki</th>\n",
        "      <td>-0.012330</td>\n",
        "      <td> 0.148959</td>\n",
        "      <td>  5482</td>\n",
        "      <td>  36802</td>\n",
        "      <td> 0.161290</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>enwiki</th>\n",
        "      <td>-0.015220</td>\n",
        "      <td> 0.146669</td>\n",
        "      <td> 80262</td>\n",
        "      <td> 547233</td>\n",
        "      <td> 0.161889</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>itwiki</th>\n",
        "      <td>-0.018435</td>\n",
        "      <td> 0.129315</td>\n",
        "      <td>  7102</td>\n",
        "      <td>  54920</td>\n",
        "      <td> 0.147751</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>eswiki</th>\n",
        "      <td>-0.021227</td>\n",
        "      <td> 0.143191</td>\n",
        "      <td>  7851</td>\n",
        "      <td>  54829</td>\n",
        "      <td> 0.164418</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ptwiki</th>\n",
        "      <td>-0.021357</td>\n",
        "      <td> 0.143572</td>\n",
        "      <td>  4678</td>\n",
        "      <td>  32583</td>\n",
        "      <td> 0.164929</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>etwiki</th>\n",
        "      <td>-0.022251</td>\n",
        "      <td> 0.127290</td>\n",
        "      <td>  1042</td>\n",
        "      <td>   8186</td>\n",
        "      <td> 0.149541</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>cswiki</th>\n",
        "      <td>-0.024574</td>\n",
        "      <td> 0.136172</td>\n",
        "      <td>  2453</td>\n",
        "      <td>  18014</td>\n",
        "      <td> 0.160746</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ruwiki</th>\n",
        "      <td>-0.044208</td>\n",
        "      <td> 0.105331</td>\n",
        "      <td>  8083</td>\n",
        "      <td>  76739</td>\n",
        "      <td> 0.149539</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 121,
       "text": [
        "        fem_per_diff  fem_per_single  female_single  gendered_total_single  \\\n",
        "jawiki      0.413549        0.603585          13434                  22257   \n",
        "hewiki      0.060952        0.216555           2386                  11018   \n",
        "dawiki      0.036127        0.181383           2233                  12311   \n",
        "nowiki      0.029112        0.227961           4277                  18762   \n",
        "svwiki      0.020537        0.213389           8772                  41108   \n",
        "ukwiki      0.001318        0.137714           2953                  21443   \n",
        "fiwiki     -0.000251        0.167975           3145                  18723   \n",
        "dewiki     -0.000691        0.149034          30335                 203544   \n",
        "plwiki     -0.008691        0.149597          10353                  69206   \n",
        "frwiki     -0.012200        0.142818          14247                  99756   \n",
        "nlwiki     -0.012330        0.148959           5482                  36802   \n",
        "enwiki     -0.015220        0.146669          80262                 547233   \n",
        "itwiki     -0.018435        0.129315           7102                  54920   \n",
        "eswiki     -0.021227        0.143191           7851                  54829   \n",
        "ptwiki     -0.021357        0.143572           4678                  32583   \n",
        "etwiki     -0.022251        0.127290           1042                   8186   \n",
        "cswiki     -0.024574        0.136172           2453                  18014   \n",
        "ruwiki     -0.044208        0.105331           8083                  76739   \n",
        "\n",
        "        fem_per_many  \n",
        "jawiki      0.190037  \n",
        "hewiki      0.155602  \n",
        "dawiki      0.145256  \n",
        "nowiki      0.198849  \n",
        "svwiki      0.192852  \n",
        "ukwiki      0.136396  \n",
        "fiwiki      0.168226  \n",
        "dewiki      0.149725  \n",
        "plwiki      0.158288  \n",
        "frwiki      0.155018  \n",
        "nlwiki      0.161290  \n",
        "enwiki      0.161889  \n",
        "itwiki      0.147751  \n",
        "eswiki      0.164418  \n",
        "ptwiki      0.164929  \n",
        "etwiki      0.149541  \n",
        "cswiki      0.160746  \n",
        "ruwiki      0.149539  "
       ]
      }
     ],
     "prompt_number": 121
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fig, ax = plt.subplots(1,1,figsize=(8,8))\n",
      "tdf[tdf['gendered_total_single']>2500][['gendered_total_single','fem_per_diff']].plot(kind='scatter', x='gendered_total_single', y='fem_per_diff', logx=True, ax=ax, c='#74bc3a')\n",
      "\n",
      "ax.yaxis.set_major_formatter(matplotlib.ticker.FuncFormatter(lambda x, y: '{:.0%}'.format(x )))\n",
      "ax.xaxis.set_major_formatter(matplotlib.ticker.FuncFormatter(lambda x, y: '{:,.0f}'.format(x )))\n",
      "\n",
      "ax.set_xlim(min(tdf['gendered_total_single']) * 0.6, max(tdf['gendered_total_single']) *3)\n",
      "#ax.set_ylim(min(tdf['fem_per_diff']) * 0.85, max(tdf['fem_per_diff']) *1.15)\n",
      "\n",
      "for label, x, y in zip(tdf.index, tdf['gendered_total_single'], tdf['fem_per_diff']):\n",
      "    plt.annotate(\n",
      "        label, \n",
      "        xy = (x, y), xytext = (5,2),\n",
      "        textcoords = 'offset points', ha = 'left', va = 'bottom')\n",
      "        #bbox = dict(boxstyle = 'round,pad=0.5', fc = 'yellow', alpha = 0.5),\n",
      "        #arrowprops = dict(arrowstyle = '->', connectionstyle = 'arc3,rad=0'))\n",
      "\n",
      "plt.annotate(\"\", xy=(10000,0.5), xytext=(0,0)) \n",
      "plt.title('Differnce in Female Ratio, of \"Language-Unique\" Articles vs Others \\n by Language-Unique Articles\"', fontsize=24)\n",
      "plt.xlabel('Number of Unique Biographies Recorded')\n",
      "plt.ylabel('Composition of Biographies Which Are Female')\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 94,
       "text": [
        "<matplotlib.text.Text at 0x7f83e125f9d0>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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OWrVqJRu2c+fOCA4OxqVLlxAbG4vNmzfDzs4ODx48kO2Hqo3Y3PjVq1dFz0/y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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f83e0b3eb10>"
       ]
      }
     ],
     "prompt_number": 94
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ptdf = tdf[tdf['gendered_total_single']>730].sort('fem_per_diff')\n",
      "\n",
      "maxbio = max(ptdf['gendered_total_single'])\n",
      "bios_size = ptdf['gendered_total_single'].apply(lambda x: math.log(x)/math.log(maxbio)) \n",
      "\n",
      "my_colors = [(x/2, x, 0.75) for x in bios_size]\n",
      "        \n",
      "fig, ax = plt.subplots(1,1,figsize=(8,6))\n",
      "ptdf['fem_per_diff'].plot(kind='bar', ax=ax, colors=my_colors)\n",
      "ax.yaxis.set_major_formatter(matplotlib.ticker.FuncFormatter(lambda x, y: '{:.0%}'.format(x )))\n",
      "\n",
      "wikilabels = ax.get_xticklabels()\n",
      "wikinames = map(lambda x: x.get_text().split('wiki')[0], wikilabels)\n",
      "fullnames = map(lookup_lang, wikinames)\n",
      "ax.set_xticklabels(fullnames)\n",
      "\n",
      "ax.set_title('Difference in Female Ratio \\n by language-unique and language-many articles \\n by Wikipedia Language', size=24)\n",
      "ax.set_ylabel('[language-unique female ratio] - [language-many female ratio]')\n",
      "ax.set_xlabel('Wikipedia Language | Darker Colours indicate more absolute lanuage-unique articles')\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 137,
       "text": [
        "<matplotlib.text.Text at 0x7f83cc7db590>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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YjJcuXaKQkBBijNFzzz1HBQUFivnLYa3uiO2k1+tJo9HQd999R9nZ2URU2Ddi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\nAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f83ccd10650>"
       ]
      }
     ],
     "prompt_number": 137
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}