gistfile1.txt

{
 "metadata": {
  "name": "Seans-data"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd\n",
      "from collections import Counter\n",
      "import datetime"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def parse(arg):\n",
      "    try:\n",
      "        y, mo, d, h, mn = tuple([int(x) for x in arg.split()])\n",
      "        return datetime.datetime(y, mo, d, h - 1, mn)\n",
      "    except ValueError as e:\n",
      "        print e, arg\n",
      "        return datetime.datetime(1980,1,1)\n",
      "df = pd.read_csv(\"twitter_only_by_datetime/twitter_only_by_datetime.csv\", parse_dates=[[\"year\",\"month\",\"day\",\"hour\",\"minute\"]], date_parser=parse, index_col=\"article_id\")\n",
      "df = df.drop([\"view_count\",\"comment_count\",\"unique_commenters\",\"engagement\",\"likes_and_votes\",\"inbound_links\"], axis=1)\n",
      "df.rename(columns={\"year_month_day_hour_minute\":\"date\"},inplace=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "C:\\Anaconda\\lib\\site-packages\\pandas\\core\\frame.py:3576: FutureWarning: rename with inplace=True  will return None from pandas 0.11 onward\n",
        "  \" from pandas 0.11 onward\", FutureWarning)\n"
       ]
      },
      {
       "output_type": "pyout",
       "prompt_number": 2,
       "text": [
        "<class 'pandas.core.frame.DataFrame'>\n",
        "Index: 2254504 entries, 455100000.0 to 1.148e+11\n",
        "Data columns:\n",
        "date         2254504  non-null values\n",
        "headline     2254504  non-null values\n",
        "author       2254499  non-null values\n",
        "content      2251098  non-null values\n",
        "following    2254504  non-null values\n",
        "followers    2254504  non-null values\n",
        "updates      2254504  non-null values\n",
        "dtypes: int64(3), object(4)"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Number of tweets"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "len(df)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "2254504"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Number of unique authors"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "author_counter = Counter(df[\"author\"])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 39
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "len(author_counter)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 40,
       "text": [
        "451033"
       ]
      }
     ],
     "prompt_number": 40
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "author_counter.most_common(10)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 41,
       "text": [
        "[('VAPORGODLLC', 88424),\n",
        " ('ECIGARETTESSAL', 50719),\n",
        " ('FUTBOLHACOAJ', 41033),\n",
        " ('JUSTFOUND1', 36695),\n",
        " ('ZUNUSILU', 32142),\n",
        " ('OHUBAGUP', 24006),\n",
        " ('YWAMIXIC', 22803),\n",
        " ('ADISEARCH1', 21072),\n",
        " ('THEVAPEBOOK', 18796),\n",
        " ('YPERINI', 18209)]"
       ]
      }
     ],
     "prompt_number": 41
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for author in [x[0] for x in author_counter.most_common(5)]:\n",
      "    vgllc_df = df[df.author == author]\n",
      "    vgllc_df.sort(\"date\",inplace=True,ascending=True)\n",
      "    vgllc_df.index = vgllc_df.date\n",
      "    vgllc_df[[\"followers\",\"following\"]].plot()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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u+bMi2xO6B46mLbDXtwWuXNF2NIyx0uDkz4rs1yu/wi5xOmzfAxo31nY0jLHS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\n+AshxDgkxV8IIcYhKf5CCDEO/ReH5519cXxZaAAAAABJRU5ErkJggg==\n"
      },
      {
       "output_type": "display_data",
       "png": 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YatcGnj1TnJeerlgtw5i6cJ08K3aICN//8z3GtxqPb099i4vhFxWWe7l4wbGe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\nLDaiop1/PXv2pMDAQLEqM2s7ZSb4opx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      },
      {
       "output_type": "display_data",
       "png": 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DR/55kNPGPOKM6SqdTeTy7nyzZmV9rmlTMXXsjRuKuVAePsz5WHfvAi4uoseL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\n4OBAK1euLNBBAT179qQVK1YQkWqjVd26denQoUN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      },
      {
       "output_type": "display_data",
       "png": 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zqTBvZki/qRSkkhNKlBApWFesyPk58gLJ3DRsmOZ9VYN/evfWnUwMYyiwIldB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\nbEoZN24c7d+/n9zd3ally5ZyDofIyEiyt7eXR8V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      },
      {
       "output_type": "display_data",
       "png": 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xHP/4x533qLpTBw7w4GzZcC8UAqGhDWceIMRpMCezf/9+duLECZaQkGA69sIL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\n7/j/I+S2ahHmN90AAAAASUVORK5CYII=\n"
      }
     ],
     "prompt_number": 66
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Number of authors with only a single tweet"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "authors_with_single_tweet = len([x for x in author_counter.most_common() if x[1] == 1])\n",
      "print authors_with_single_tweet\n",
      "print authors_with_single_tweet / (len(df) * 1.0)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "301101\n",
        "0.133555318598\n"
       ]
      }
     ],
     "prompt_number": 67
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "num_tweets_counter = Counter([x[1] for x in author_counter.most_common()])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 68
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "num_tweets_df = pd.DataFrame(num_tweets_counter.most_common(), columns=(\"num tweets by author\", \"num authors\"))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 69
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "num_tweets_df.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>num tweets by author</th>\n",
        "      <th>num authors</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0 </th>\n",
        "      <td>  1</td>\n",
        "      <td> 301101</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1 </th>\n",
        "      <td>  2</td>\n",
        "      <td>  66277</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2 </th>\n",
        "      <td>  3</td>\n",
        "      <td>  26215</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3 </th>\n",
        "      <td>  4</td>\n",
        "      <td>  13365</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4 </th>\n",
        "      <td>  5</td>\n",
        "      <td>   7750</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5 </th>\n",
        "      <td>  6</td>\n",
        "      <td>   5180</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6 </th>\n",
        "      <td>  7</td>\n",
        "      <td>   3528</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7 </th>\n",
        "      <td>  8</td>\n",
        "      <td>   2591</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8 </th>\n",
        "      <td>  9</td>\n",
        "      <td>   2388</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9 </th>\n",
        "      <td> 10</td>\n",
        "      <td>   2211</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td> 11</td>\n",
        "      <td>   1837</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>11</th>\n",
        "      <td> 12</td>\n",
        "      <td>   1526</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>12</th>\n",
        "      <td> 13</td>\n",
        "      <td>   1290</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>13</th>\n",
        "      <td> 14</td>\n",
        "      <td>   1148</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>14</th>\n",
        "      <td> 15</td>\n",
        "      <td>    978</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>15</th>\n",
        "      <td> 16</td>\n",
        "      <td>    970</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>16</th>\n",
        "      <td> 18</td>\n",
        "      <td>    773</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>17</th>\n",
        "      <td> 19</td>\n",
        "      <td>    772</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>18</th>\n",
        "      <td> 20</td>\n",
        "      <td>    761</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>19</th>\n",
        "      <td> 17</td>\n",
        "      <td>    754</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "output_type": "pyout",
       "prompt_number": 70,
       "text": [
        "    num tweets by author  num authors\n",
        "0                      1       301101\n",
        "1                      2        66277\n",
        "2                      3        26215\n",
        "3                      4        13365\n",
        "4                      5         7750\n",
        "5                      6         5180\n",
        "6                      7         3528\n",
        "7                      8         2591\n",
        "8                      9         2388\n",
        "9                     10         2211\n",
        "10                    11         1837\n",
        "11                    12         1526\n",
        "12                    13         1290\n",
        "13                    14         1148\n",
        "14                    15          978\n",
        "15                    16          970\n",
        "16                    18          773\n",
        "17                    19          772\n",
        "18                    20          761\n",
        "19                    17          754"
       ]
      }
     ],
     "prompt_number": 70
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Find most frequently occuring words"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import nltk, re, itertools, urlparse, httplib"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def stripUrlFromString(s):\n",
      "    try:\n",
      "        return re.sub(r'\\w+:\\/{2}[\\d\\w-]+(\\.[\\d\\w-]+)*(?:(?:\\/[^\\s/]*))*', '', s)\n",
      "    except:\n",
      "        return \"\"\n",
      "def stripStopWordsFromString(s):\n",
      "    try:\n",
      "        return ' '.join(re.findall(r'\\w+', str(s),flags = re.UNICODE | re.LOCALE))\n",
      "    except:\n",
      "        return \"\"\n",
      "def getUrl(s):\n",
      "    GRUBER_URLINTEXT_PAT = re.compile(ur'(?i)\\b((?:https?://|www\\d{0,3}[.]|[a-z0-9.\\-]+[.][a-z]{2,4}/)(?:[^\\s()<>]+|\\(([^\\s()<>]+|(\\([^\\s()<>]+\\)))*\\))+(?:\\(([^\\s()<>]+|(\\([^\\s()<>]+\\)))*\\)|[^\\s`!()\\[\\]{};:\\'\".,<>?\\xab\\xbb\\u201c\\u201d\\u2018\\u2019]))')\n",
      "    out = GRUBER_URLINTEXT_PAT.findall(str(s))\n",
      "    if len(out) == 0:\n",
      "        return \"\"\n",
      "    else: \n",
      "        try:\n",
      "            return out[0][0]\n",
      "        except:\n",
      "            return out[0][0]\n",
      "def getTweetAndUrl(s):\n",
      "    s = str(s).lower()\n",
      "    url = getUrl(s)\n",
      "    if url is not \"\":\n",
      "        s = s.replace(url, \"\")\n",
      "        return (s, url)\n",
      "    else:\n",
      "        return (s, \"\")\n",
      "def unshorten_url(url):\n",
      "    try:\n",
      "        parsed = urlparse.urlparse(url)\n",
      "        h = httplib.HTTPConnection(parsed.netloc)\n",
      "        resource = parsed.path\n",
      "        if parsed.query != \"\":\n",
      "            resource += \"?\" + parsed.query\n",
      "        h.request('HEAD', resource )\n",
      "        response = h.getresponse()\n",
      "        if response.status/100 == 3 and response.getheader('Location'):\n",
      "            return unshorten_url(response.getheader('Location')) # changed to process chains of short urls\n",
      "        else:\n",
      "            return url\n",
      "    except:\n",
      "        return url"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "stripped = len(df) * [None]\n",
      "for i, s in enumerate(df[\"content\"]):\n",
      "    if i % 200000 == 0: print str(i),\n",
      "    s = getTweetAndUrl(s)\n",
      "    stripped[i] = (stripStopWordsFromString(str(s[0])), s[1])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "0 "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "200000 "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "400000 "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "600000 "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "800000 "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "1000000 "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "1200000 "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "1400000 "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "1600000 "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "1800000 "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "2000000 "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "2200000\n"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df[\"content_stripped\"] = [x[0] for x in stripped]\n",
      "df[\"original_url\"] = [x[1] for x in stripped]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "unique_urls = unique(df.original_url)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "with open(\"urls.txt\", \"a\") as myfile:\n",
      "    for url in unique_urls:\n",
      "        newurl = unshorten_url(url)\n",
      "        print url, newurl\n",
      "        myfile.write(url + \", \" + newurl + \"\\n\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " \n",
        "0z.fr/aejcl"
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      {
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