Twitter errors over time.ipynb

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   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd\n",
      "import re\n",
      "import json\n",
      "import sqlite3 as lite\n",
      "from datetime import datetime \n",
      "\n",
      "# Set some Pandas options\n",
      "pd.set_option('display.notebook_repr_html', False)\n",
      "pd.set_option('display.max_columns', 20)\n",
      "pd.set_option('display.max_rows', 25)\n",
      "\n",
      "import matplotlib.pyplot as plt\n",
      "plt.style.use('ggplot')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "litecon = lite.connect('data/twitter.db')\n",
      "\n",
      "df = pd.read_sql(\"SELECT tweet_id, old_screen_name, max_tweet_time, stratum, tweet, error, modified FROM sample\", litecon, index_col='tweet_id')\n",
      "df['tweet'] = df.tweet.apply(lambda x: json.loads(x) if x is not None else None)\n",
      "df['user_id'] = df.tweet.apply(lambda x: int(x['user']['id']) if x else None)\n",
      "df['max_tweet_time'] = pd.to_datetime(df.max_tweet_time)\n",
      "df['modified'] = pd.to_datetime(df.modified)\n",
      "\n",
      "user_df = pd.read_sql(\"SELECT user_id, screen_name, user_object, timeline, timeline_error, timeline_modified, user_modified FROM users\", litecon, index_col='user_id')\n",
      "user_df.index = user_df.index.astype(int)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "DatabaseError",
       "evalue": "Execution failed on sql 'SELECT tweet_id, old_screen_name, max_tweet_time, stratum, tweet, error, modified FROM sample': no such column: max_tweet_time",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mDatabaseError\u001b[0m                             Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-2-84365c73a291>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mlitecon\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlite\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'data/twitter.db'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mdf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_sql\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"SELECT tweet_id, old_screen_name, max_tweet_time, stratum, tweet, error, modified FROM sample\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlitecon\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindex_col\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'tweet_id'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'tweet'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtweet\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mjson\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloads\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mNone\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'user_id'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtweet\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'user'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'id'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/usr/local/lib/python2.7/site-packages/pandas/io/sql.pyc\u001b[0m in \u001b[0;36mread_sql\u001b[0;34m(sql, con, index_col, coerce_float, params, parse_dates, columns, chunksize)\u001b[0m\n\u001b[1;32m    497\u001b[0m             \u001b[0msql\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindex_col\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindex_col\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    498\u001b[0m             \u001b[0mcoerce_float\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcoerce_float\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparse_dates\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mparse_dates\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 499\u001b[0;31m             chunksize=chunksize)\n\u001b[0m\u001b[1;32m    500\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    501\u001b[0m     \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/usr/local/lib/python2.7/site-packages/pandas/io/sql.pyc\u001b[0m in \u001b[0;36mread_query\u001b[0;34m(self, sql, index_col, coerce_float, params, parse_dates, chunksize)\u001b[0m\n\u001b[1;32m   1597\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1598\u001b[0m         \u001b[0margs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_convert_params\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msql\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1599\u001b[0;31m         \u001b[0mcursor\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1600\u001b[0m         \u001b[0mcolumns\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mcol_desc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mcol_desc\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mcursor\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdescription\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1601\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/usr/local/lib/python2.7/site-packages/pandas/io/sql.pyc\u001b[0m in \u001b[0;36mexecute\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1574\u001b[0m             ex = DatabaseError(\n\u001b[1;32m   1575\u001b[0m                 \"Execution failed on sql '%s': %s\" % (args[0], exc))\n\u001b[0;32m-> 1576\u001b[0;31m             \u001b[0mraise_with_traceback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mex\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1577\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1578\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mstaticmethod\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/usr/local/lib/python2.7/site-packages/pandas/io/sql.pyc\u001b[0m in \u001b[0;36mexecute\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1562\u001b[0m                 \u001b[0mcur\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1563\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1564\u001b[0;31m                 \u001b[0mcur\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1565\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mcur\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1566\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;31mDatabaseError\u001b[0m: Execution failed on sql 'SELECT tweet_id, old_screen_name, max_tweet_time, stratum, tweet, error, modified FROM sample': no such column: max_tweet_time"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tweets = df.merge(user_df, left_on='user_id', right_index=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tweets['screen_name_changed'] = tweets.apply(lambda row: row['old_screen_name'].lower() != row['screen_name'].lower(), axis=1)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tweets['error'] = tweets.error.map(str) # convert None to 'None'"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "gb = df.set_index('max_tweet_time').groupby([pd.TimeGrouper(freq='M'), 'error'])\n",
      "gb.size().unstack().plot()\n",
      "\n",
      "plt.title('Errors trying to retrieve Tweet Over Tweet Age')\n",
      "lgd = plt.legend(loc='upper center', bbox_to_anchor=(0.5, -.2))\n",
      "plt.savefig('figures/errors.png', bbox_extra_artists=(lgd,), bbox_inches='tight')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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0bPc2CPePgau3t02+20pFr/4QL5yGIuZ+o+flcjmUSuVd9sp5qdi6AdUlxfB4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\nZ4/JZGLz5s1ce+21hIWF9bqtn58flZWV2O32bn26paWlKJVKRo8e3a+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V8i7Xss1i58Rl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\nAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x1671fca90>"
       ]
      }
     ],
     "prompt_number": 88
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "gb = tweets[tweets['screen_name_changed'] == True].set_index('max_tweet_time').groupby([pd.TimeGrouper(freq='M'), 'screen_name_changed'])\n",
      "gb.size().unstack().plot(legend=False)\n",
      "\n",
      "plt.title('Screen Name Changes Over Tweet Age')\n",
      "plt.savefig('figures/screen_name_changes.png')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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RT4EO7i2zTZ3yb0Oe/xGExhti6P9BKLQTeovOPSFv/1+lx2cpdHgfRMtwvWWC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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x16734f510>"
       ]
      }
     ],
     "prompt_number": 90
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "gb = tweets.set_index('max_tweet_time').groupby([pd.TimeGrouper(freq='M'), 'screen_name_changed'])['screen_name_changed']\n",
      "gb = gb.size().multiply(100.0).divide(gb.size().sum(level=0))\n",
      "df2 = gb.reset_index()\n",
      "df2 = df2[df2['screen_name_changed'] == True]\n",
      "df2 = df2.set_index('max_tweet_time')\n",
      "df2[0].plot()\n",
      "\n",
      "plt.title('Screen Name Changes Over Tweet Age\\n(percent of valid tweets)')\n",
      "plt.savefig('figures/screen_name_changes.png')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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FYcyYMRrbli5dildeeQVTpkxBfHw8lixZUmYBVmQlLZRbkuHDh0OpVPLcKRbE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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x108bdbc50>"
       ]
      }
     ],
     "prompt_number": 122
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tweets['is_reply'] = tweets.tweet.map(lambda x: x['in_reply_to_status_id'] is not None)\n",
      "gb = tweets.set_index('max_tweet_time').groupby([pd.TimeGrouper(freq='M'), 'is_reply'])['is_reply']\n",
      "gb = gb.size().multiply(100.0).divide(gb.size().sum(level=0))\n",
      "df2 = gb.reset_index()\n",
      "df2 = df2[df2['is_reply'] == True]\n",
      "df2 = df2.set_index('max_tweet_time')\n",
      "df2[0].plot(legend=False)\n",
      "\n",
      "plt.title('Percent of Tweets that are replies')\n",
      "plt.savefig('figures/is_reply.png')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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RMUDn7qDdW68+WWZfF4jRlaVS6exp0L/fhfTE3GbXqLaH8A8AkjoCeRb6rX/b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\nkzVjjHmB/w9pnyZBZ9btdwAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x165a64d10>"
       ]
      }
     ],
     "prompt_number": 93
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tweets['lang'] = tweets.tweet.map(lambda x: x['lang'])\n",
      "gb = tweets.set_index('max_tweet_time').groupby([pd.TimeGrouper(freq='M'), 'lang'])\n",
      "gb2 = gb.size().multiply(100.0).divide(gb.size().sum(level=0))\n",
      "more_than_5p_langs = list(gb2[gb2 > 5].reset_index().lang.unique())\n",
      "more_than_5p_langs.append('und')\n",
      "more_than_5p_langs\n",
      "all_langs = set(gb.size().unstack().columns)\n",
      "gb2 = gb.size().unstack()[more_than_5p_langs]\n",
      "gb2['other'] = gb.size().unstack()[list(all_langs.difference(more_than_5p_langs))].sum(axis=1)\n",
      "\n",
      "gb2.plot.bar(stacked=True)\n",
      "lgd = plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5))\n",
      "\n",
      "plt.title('Number of Tweets by Language')\n",
      "plt.savefig('figures/languages.png', bbox_extra_artists=(lgd,), bbox_inches='tight')\n",
      "# gb = tweets.set_index('max_tweet_time').groupby([pd.TimeGrouper(freq='M'), 'lang'])['lang']\n",
      "# gb = gb.size().multiply(100.0).divide(gb.size().sum(level=0))\n",
      "# df2 = gb.reset_index()\n",
      "# df2 = df2[df2['is_retweet'] == True]\n",
      "# df2 = df2.set_index('max_tweet_time')\n",
      "# df2[0].plot(legend=False)\n",
      "\n",
      "# plt.title('Percent of Tweets that are replies')\n",
      "# plt.savefig('figures/is_reply.png')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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RExOD8vJydOjQAVOnTq013mQyqVWlQ3TVPGUcvMJTBpQPJiH1frBwmSt3+TmV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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x16577a0d0>"
       ]
      }
     ],
     "prompt_number": 94
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ax = gb2.apply(lambda x: x*100/x.sum(), axis=1).plot.bar(stacked=True)\n",
      "plt.ylim(0,100)\n",
      "lgd = plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5))\n",
      "plt.title('Tweets by Language\\n(as percent of valid tweets)')\n",
      "plt.savefig('figures/languages.png', bbox_extra_artists=(lgd,), bbox_inches='tight')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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uU0uHkC5u/4tXSwdAWC4eVYgqi6ScAiFnYoDcP1ZKFSQ1FhEl/2ArOUpU6vc/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\niyQhhBBiAC2ShBBCiAG0SBJCCCEG/AeP2NtP4Vrm5wAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x168237a50>"
       ]
      }
     ],
     "prompt_number": 123
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "NameError",
       "evalue": "name 'dates' is not defined",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-104-ffb9d72d02f5>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mxaxis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_major_formatter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdates\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDateFormatter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'%m %Y'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[0;31mNameError\u001b[0m: name 'dates' is not defined"
       ]
      }
     ],
     "prompt_number": 104
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "gb2.plot.bar(stacked=True)\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 79,
       "text": [
        "<matplotlib.legend.Legend at 0x165661050>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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stTp5whARUTfXbLaeu5zEi8uXa+nSpXj00UexadMmTJgwAbfeemu78eefYPT0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\n+0uSWjFqL4u8rKt3fdvT0NAgNTQ0ePx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       "text": [
        "<matplotlib.figure.Figure at 0x10793f8d0>"
       ]
      }
     ],
     "prompt_number": 79
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tweets.ix['208388272223813632'].tweet"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 177,
       "text": [
        "{u'contributors': None,\n",
        " u'coordinates': None,\n",
        " u'created_at': u'Fri Jun 01 02:43:30 +0000 2012',\n",
        " u'entities': {u'hashtags': [{u'indices': [73, 82], u'text': u'onmylist'}],\n",
        "  u'symbols': [],\n",
        "  u'urls': [{u'display_url': u'annualreviews.org/doi/full/10.11\\u2026',\n",
        "    u'expanded_url': u'http://www.annualreviews.org/doi/full/10.1146/annurev-polisci-030810-110815',\n",
        "    u'indices': [52, 72],\n",
        "    u'url': u'http://t.co/rvxsjYzF'}],\n",
        "  u'user_mentions': [{u'id': 6366042,\n",
        "    u'id_str': u'6366042',\n",
        "    u'indices': [3, 12],\n",
        "    u'name': u'Vincent Raynauld',\n",
        "    u'screen_name': u'VincentR'}]},\n",
        " u'favorite_count': 0,\n",
        " u'favorited': False,\n",
        " u'geo': None,\n",
        " u'id': 208388272223813632,\n",
        " u'id_str': u'208388272223813632',\n",
        " u'in_reply_to_screen_name': None,\n",
        " u'in_reply_to_status_id': None,\n",
        " u'in_reply_to_status_id_str': None,\n",
        " u'in_reply_to_user_id': None,\n",
        " u'in_reply_to_user_id_str': None,\n",
        " u'is_quote_status': False,\n",
        " u'lang': u'en',\n",
        " u'place': None,\n",
        " u'possibly_sensitive': False,\n",
        " u'retweet_count': 2,\n",
        " u'retweeted': False,\n",
        " u'retweeted_status': {u'contributors': None,\n",
        "  u'coordinates': None,\n",
        "  u'created_at': u'Thu May 31 21:12:33 +0000 2012',\n",
        "  u'entities': {u'hashtags': [{u'indices': [59, 68], u'text': u'onmylist'}],\n",
        "   u'symbols': [],\n",
        "   u'urls': [{u'display_url': u'annualreviews.org/doi/full/10.11\\u2026',\n",
        "     u'expanded_url': u'http://www.annualreviews.org/doi/full/10.1146/annurev-polisci-030810-110815',\n",
        "     u'indices': [38, 58],\n",
        "     u'url': u'http://t.co/rvxsjYzF'}],\n",
        "   u'user_mentions': []},\n",
        "  u'favorite_count': 1,\n",
        "  u'favorited': False,\n",
        "  u'geo': None,\n",
        "  u'id': 208304984213823490,\n",
        "  u'id_str': u'208304984213823490',\n",
        "  u'in_reply_to_screen_name': None,\n",
        "  u'in_reply_to_status_id': None,\n",
        "  u'in_reply_to_status_id_str': None,\n",
        "  u'in_reply_to_user_id': None,\n",
        "  u'in_reply_to_user_id_str': None,\n",
        "  u'is_quote_status': False,\n",
        "  u'lang': u'en',\n",
        "  u'place': None,\n",
        "  u'possibly_sensitive': False,\n",
        "  u'retweet_count': 2,\n",
        "  u'retweeted': False,\n",
        "  u'source': u'<a href=\"http://twitter.com\" rel=\"nofollow\">Twitter Web Client</a>',\n",
        "  u'text': u\"The Internet's influence on politics: http://t.co/rvxsjYzF #onmylist\",\n",
        "  u'truncated': False,\n",
        "  u'user': {u'contributors_enabled': False,\n",
        "   u'created_at': u'Sun May 27 17:14:29 +0000 2007',\n",
        "   u'default_profile': False,\n",
        "   u'default_profile_image': False,\n",
        "   u'description': u'Asst. Prof., @EmersonCollege; Research Associate, @GRCPlaval; Adviser, @SamaraCDA / E-politics, pol comm, journalism / RT \\u2260 Endorsement / My views are my own',\n",
        "   u'entities': {u'description': {u'urls': []},\n",
        "    u'url': {u'urls': [{u'display_url': u'emerson.academia.edu/VincentRaynauld',\n",
        "       u'expanded_url': u'https://emerson.academia.edu/VincentRaynauld',\n",
        "       u'indices': [0, 23],\n",
        "       u'url': u'https://t.co/BEt7ZM3xMI'}]}},\n",
        "   u'favourites_count': 256,\n",
        "   u'follow_request_sent': False,\n",
        "   u'followers_count': 1385,\n",
        "   u'following': False,\n",
        "   u'friends_count': 896,\n",
        "   u'geo_enabled': True,\n",
        "   u'has_extended_profile': False,\n",
        "   u'id': 6366042,\n",
        "   u'id_str': u'6366042',\n",
        "   u'is_translation_enabled': False,\n",
        "   u'is_translator': False,\n",
        "   u'lang': u'en',\n",
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