Networks.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "import pandas as pd\n",
    "pd.options.display.float_format = '{:20,.4f}'.format\n",
    "\n",
    "# from  matplotlib import pyplot\n",
    "# import seaborn\n",
    "\n",
    "import sqlite3\n",
    "\n",
    "# pylab.rcParams['figure.figsize'] = (12.0, 8.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "File b'data/BMCevolBioTweetDetails.txt' does not exist",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-3-b5b404d349f9>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtweetdetails\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'data/BMCevolBioTweetDetails.txt'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mencoding\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'utf8'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msep\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"\\t\"\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      2\u001b[0m \u001b[0mtweetdetails\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msort_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minplace\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mdois\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtweetdetails\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdoi\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36mparser_f\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, escapechar, comment, encoding, dialect, tupleize_cols, error_bad_lines, warn_bad_lines, skipfooter, skip_footer, doublequote, delim_whitespace, as_recarray, compact_ints, use_unsigned, low_memory, buffer_lines, memory_map, float_precision)\u001b[0m\n\u001b[1;32m    644\u001b[0m                     skip_blank_lines=skip_blank_lines)\n\u001b[1;32m    645\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 646\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    647\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    648\u001b[0m     \u001b[0mparser_f\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m    387\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    388\u001b[0m     \u001b[0;31m# Create the parser.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 389\u001b[0;31m     \u001b[0mparser\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    390\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    391\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mnrows\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mchunksize\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m    728\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'has_index_names'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'has_index_names'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    729\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 730\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    731\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    732\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_make_engine\u001b[0;34m(self, engine)\u001b[0m\n\u001b[1;32m    921\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mengine\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'c'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    922\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'c'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 923\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCParserWrapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    924\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    925\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'python'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, src, **kwds)\u001b[0m\n\u001b[1;32m   1388\u001b[0m         \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'allow_leading_cols'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex_col\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1389\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1390\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_parser\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTextReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msrc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1391\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1392\u001b[0m         \u001b[0;31m# XXX\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/parser.pyx\u001b[0m in \u001b[0;36mpandas.parser.TextReader.__cinit__ (pandas/parser.c:4184)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/parser.pyx\u001b[0m in \u001b[0;36mpandas.parser.TextReader._setup_parser_source (pandas/parser.c:8449)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mFileNotFoundError\u001b[0m: File b'data/BMCevolBioTweetDetails.txt' does not exist"
     ]
    }
   ],
   "source": [
    "tweetdetails = pd.read_csv('data/BMCevolBioTweetDetails.txt', encoding='utf8', sep=\"\\t\", index_col='tweet_id')\n",
    "tweetdetails.sort_index(inplace=True)\n",
    "\n",
    "dois = list(tweetdetails.doi.unique())\n",
    "\n",
    "tweetdetails['created_at'] = pd.to_datetime(tweetdetails.created_at)\n",
    "tweetdetails['user_id_str'] = tweetdetails.user_id_str.astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "tweetdetails = pd.read_csv('data/BMCBioTweetDetails.txt', encoding='utf8', sep=\"\\t\", index_col='tweet_id')\n",
    "tweetdetails.sort_index(inplace=True)\n",
    "\n",
    "dois = list(tweetdetails.doi.unique())\n",
    "\n",
    "tweetdetails['created_at'] = pd.to_datetime(tweetdetails.created_at)\n",
    "tweetdetails['user_id_str'] = tweetdetails.user_id_str.astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv('data/community_counts1930.txt', sep='\\t', index_col='community')\n",
    "df = df.stack()\n",
    "df.div(df.sum(axis=0, level=0), level=0).multiply(100).unstack()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "edgelist = pd.read_csv('data/evolBioAllFollowers.csv', dtype={'in': str, 'out': str, 'doi': str}).drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "con = sqlite3.connect(\"data/BMCbioSample.db\")\n",
    "friends = pd.read_sql_query(\"SELECT * FROM friends\", con, index_col=\"user_id\")\n",
    "friends.index = friends.index.astype(int)\n",
    "followers = pd.read_sql_query(\"SELECT * FROM followers\", con, index_col=\"user_id\")\n",
    "followers.index = followers.index.astype(int)\n",
    "\n",
    "df = tweetdetails[['doi', 'user_id_str']].drop_duplicates().set_index('user_id_str').join(friends)[['friend_id', 'doi']]\n",
    "# df.index.rename('user_id', inplace=True)\n",
    "\n",
    "edgelist = df.reset_index()\n",
    "edgelist.columns = ['in', 'out', 'doi']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 454,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "allcommunities = pd.read_csv('data/follower_communities.txt', sep='\\t')\n",
    "allcommunities = allcommunities[allcommunities['user_id_str'] != -1]\n",
    "allcommunities['user_id_str'] = allcommunities.user_id_str.astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 1]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "93.44% new users (out of 61)\n",
      "54.10% retweets (out of 61)\n",
      "new user: False, is_retweet: False: *r\n",
      "new user: False, is_retweet: True: *b\n",
      "new user: True, is_retweet: False: or\n",
      "new user: True, is_retweet: True: ob"
     ]
    }
   ],
   "source": [
    "    def check_activation(user_id_str):\n",
    "        global activated\n",
    "        activated.add(user_id_str)\n",
    "        activated = activated.union(edgelist[edgelist['in'] == user_id_str]['out'])\n",
    "        return len(activated)\n",
    "    \n",
    "    \n",
    "    def group_color(name):\n",
    "        if name[1]: \n",
    "            return 'b'\n",
    "        return 'r'\n",
    "    \n",
    "    def group_marker(name):\n",
    "        if name[0]:\n",
    "            return 'o'\n",
    "        return '*'\n",
    "    \n",
    "    def mode(angle):\n",
    "        if angle > 75:\n",
    "            return 1\n",
    "        elif angle > 15:\n",
    "            return 2\n",
    "        else:\n",
    "            return 3\n",
    "\n",
    "    fig, axes = plt.subplots(nrows=2, ncols=2)\n",
    "    plot_map = {0: [0,0], 1: [0,1], 2: [1,0], 3: [1,1]}\n",
    "    for i, doi in enumerate(dois): \n",
    "        tweets = tweetdetails[tweetdetails.doi == doi]\n",
    "    #     communities = allcommunities[(allcommunities.doi == doi)].set_index('user_id_str')\n",
    "        \n",
    "        \n",
    "        activated = set()\n",
    "    #     activated_communities = set()\n",
    "        \n",
    "        num_activated_users = []\n",
    "    #     num_activated_communities = []\n",
    "        \n",
    "        for row in tweets.iterrows():\n",
    "            user_id = row[1]['user_id_str']\n",
    "            num_activated_users.append(check_activation(user_id))\n",
    "        \n",
    "    #         try: \n",
    "    #             activated_communities.add(communities.ix[user_id]['community'])\n",
    "    #         except KeyError:\n",
    "    #             print \"%s not found\" % user_id\n",
    "    #             print \n",
    "    #         num_activated_communities.append(len(activated_communities))\n",
    "        \n",
    "        tweets['activated_users'] = num_activated_users\n",
    "        tweets['activated_users_p'] = tweets['activated_users'].multiply(100.0).div(tweets['activated_users'].max())\n",
    "    #     tweets['activated_communities'] = num_activated_communities\n",
    "    #     tweets['activated_communities_p'] = tweets['activated_communities'].multiply(100.0).div(tweets['activated_communities'].max())\n",
    "        # Create matplotlib figure\n",
    "        ax = axes[plot_map[i][0], plot_map[i][1]]\n",
    "        ax2 = ax.twinx() \n",
    "        \n",
    "        tweets['event_number'] = tweets.index.map(lambda x: tweets.index.get_loc(x))\n",
    "          \n",
    "    #     for name, group in [('odd', 1), ('even', 0)]:\n",
    "    #         tweets[tweets.user_id_str % 2 == group].set_index('created_at').activated_users_p.plot(style='o', ms=12, label=name,ax=ax, alpha=0.5)\n",
    "    #     tweets.set_index('created_at').activated_users.plot(style='o', ms=6,ax=ax, alpha=0.5)    \n",
    "        \n",
    "        \n",
    "        tweets['new_user'] = ~tweets.duplicated('user_id_str', keep='first')\n",
    "        print \"%.2f%% new users (out of %s)\" % (len(tweets[tweets['new_user']])*100./len(tweets), len(tweets))\n",
    "        print \"%.2f%% retweets (out of %s)\" % (len(tweets[tweets['is_retweet']])*100./len(tweets), len(tweets))\n",
    "        groups = ['new_user', 'is_retweet']\n",
    "        for name, group in tweets.set_index('created_at').groupby(groups).activated_users:\n",
    "            print \"new user: %s, is_retweet: %s: %s%s\" % (name[0], name[1], group_marker(name), group_color(name))\n",
    "            group.plot(marker=group_marker(name), color=group_color(name), linestyle=\"\", ms=6, alpha=0.5, ax=ax)\n",
    "#         max is because there are cases with tweets at exact same second\n",
    "    #     df = tweets.activated_users_p.diff(-1).fillna(0).divide(tweets.created_at.diff(-1).fillna(0).map(lambda x: max(x.value/1000000000.0/60/60, 1))).fillna(0)\n",
    "    #     df.index = tweets.created_at\n",
    "        \n",
    "    #     ax.vlines(x=df[df.diff().abs() > df.abs().describe()['mean'] + df.abs().describe()['std']].index, ymin=ymin, ymax=ymax-1, color='r')\n",
    "    \n",
    "        \n",
    "#         df=tweets.set_index('created_at').activated_users_p\n",
    "#         df = df.resample('48H').max().dropna().astype(int) \n",
    "#         df.plot(style='ob', ms=6, ax=ax)\n",
    "        \n",
    "#         activations = df.diff(-1).fillna(0).astype(int)\n",
    "#         days = df.reset_index().created_at.diff(-1).fillna(0).map(lambda x: x.days)\n",
    "#         days.index = df.index\n",
    "        \n",
    "#         angles = np.degrees(np.arctan2(activations, days)) #.map(lambda x: (x+180) % 360)        \n",
    "#         changes = angles.map(mode) != angles.shift(1).map(mode)\n",
    "#         changes = changes[3:]\n",
    "#         changes = changes[changes].shift(-1)\n",
    "#         ymin, ymax = ax.get_ylim()\n",
    "# #         angles.plot(style=\"oy\", ax=ax2)\n",
    "#         ax.vlines(x=changes.index, ymin=ymin, ymax=ymax-1, color='r')\n",
    "        fig.suptitle(doi)\n",
    "#         fig.savefig('figures/%s-activation.png' % doi[doi.find('/')+1:].replace('-', ''))\n",
    "    #     break\n",
    "    \n",
    "    \n",
    "    #     tweets.set_index('event_number').activated_users_p.plot(style='o', ms=12, alpha=0.5)\n",
    "    #     tweets.set_index('event_number').activated_communities.plot(style='s', ms=12, secondary_y=True, alpha=.2)\n",
    "    \n",
    "    \n",
    "    \n",
    "    #     print \"%s total users reached\" % tweets.activated_users.max()\n",
    "    #     print \"%s total communities\" % tweets.activated_communities.max()\n",
    "        fig.savefig('figures/%s-activation-eventnumber.png' % doi.replace('-', '')[-4:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 262,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
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       "      <td>RT @christlet: Buzz Baum has an intriguing \"in...</td>\n",
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       "      <td>An inside-out origin for the eukaryotic cell h...</td>\n",
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       "      <td>34,200.0000</td>\n",
       "      <td>10835</td>\n",
       "      <td>219</td>\n",
       "      <td>Our Mission Is Your Vision</td>\n",
       "      <td>False</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>An inside-out origin for the eukaryotic cell h...</td>\n",
       "      <td>24253</td>\n",
       "      <td>26.2390</td>\n",
       "      <td>37</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527126860581593088</th>\n",
       "      <td>10.1186/s12915-014-0076-2</td>\n",
       "      <td>2014-10-28 15:56:51</td>\n",
       "      <td>Tue</td>\n",
       "      <td>davidcamachoj</td>\n",
       "      <td>146692746</td>\n",
       "      <td>nan</td>\n",
       "      <td>271</td>\n",
       "      <td>413</td>\n",
       "      <td>good news, bad news, and very bad news......</td>\n",
       "      <td>False</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>An inside-out origin for the eukaryotic cell h...</td>\n",
       "      <td>24617</td>\n",
       "      <td>26.6328</td>\n",
       "      <td>38</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527157079937527809</th>\n",
       "      <td>10.1186/s12915-014-0076-2</td>\n",
       "      <td>2014-10-28 17:56:56</td>\n",
       "      <td>Tue</td>\n",
       "      <td>ibridazioni</td>\n",
       "      <td>83836479</td>\n",
       "      <td>7,200.0000</td>\n",
       "      <td>896</td>\n",
       "      <td>1165</td>\n",
       "      <td>Psychologist, Design Research Director at Desi...</td>\n",
       "      <td>False</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>An inside-out origin for the eukaryotic cell h...</td>\n",
       "      <td>25684</td>\n",
       "      <td>27.7872</td>\n",
       "      <td>39</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527166710046945280</th>\n",
       "      <td>10.1186/s12915-014-0076-2</td>\n",
       "      <td>2014-10-28 18:35:12</td>\n",
       "      <td>Tue</td>\n",
       "      <td>ctskennerton</td>\n",
       "      <td>2158831501</td>\n",
       "      <td>-25,200.0000</td>\n",
       "      <td>138</td>\n",
       "      <td>68</td>\n",
       "      <td>Microbiologist, Bioinformatician. More of the ...</td>\n",
       "      <td>True</td>\n",
       "      <td>527,071,887,612,850,176.0000</td>\n",
       "      <td>DrJCThrash</td>\n",
       "      <td>False</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @DrJCThrash: An inside-out origin for the e...</td>\n",
       "      <td>25720</td>\n",
       "      <td>27.8262</td>\n",
       "      <td>40</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527300867972550656</th>\n",
       "      <td>10.1186/s12915-014-0076-2</td>\n",
       "      <td>2014-10-29 03:28:18</td>\n",
       "      <td>Wed</td>\n",
       "      <td>rapiduplift</td>\n",
       "      <td>18282718</td>\n",
       "      <td>19,800.0000</td>\n",
       "      <td>631</td>\n",
       "      <td>153</td>\n",
       "      <td>sedimentary geologist dreaming of a Himalayan ...</td>\n",
       "      <td>False</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interesting! a new hypothesis for the origin o...</td>\n",
       "      <td>25854</td>\n",
       "      <td>27.9711</td>\n",
       "      <td>41</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527364538422026240</th>\n",
       "      <td>10.1186/s12915-014-0076-2</td>\n",
       "      <td>2014-10-29 07:41:18</td>\n",
       "      <td>Wed</td>\n",
       "      <td>flowing</td>\n",
       "      <td>10202432</td>\n",
       "      <td>7,200.0000</td>\n",
       "      <td>145</td>\n",
       "      <td>100</td>\n",
       "      <td>+machine_learning +data_mining +human_rights +...</td>\n",
       "      <td>True</td>\n",
       "      <td>527,029,080,731,176,960.0000</td>\n",
       "      <td>christlet</td>\n",
       "      <td>False</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @christlet: Buzz Baum has an intriguing \"in...</td>\n",
       "      <td>25947</td>\n",
       "      <td>28.0718</td>\n",
       "      <td>42</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527379076902707201</th>\n",
       "      <td>10.1186/s12915-014-0076-2</td>\n",
       "      <td>2014-10-29 08:39:04</td>\n",
       "      <td>Wed</td>\n",
       "      <td>ayuk74</td>\n",
       "      <td>229599040</td>\n",
       "      <td>-36,000.0000</td>\n",
       "      <td>85</td>\n",
       "      <td>302</td>\n",
       "      <td>Phd,PharmD, 2007</td>\n",
       "      <td>False</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Evolution of complex life turns current theori...</td>\n",
       "      <td>26216</td>\n",
       "      <td>28.3628</td>\n",
       "      <td>43</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527398549273985024</th>\n",
       "      <td>10.1186/s12915-014-0076-2</td>\n",
       "      <td>2014-10-29 09:56:27</td>\n",
       "      <td>Wed</td>\n",
       "      <td>BMCBiology</td>\n",
       "      <td>299580552</td>\n",
       "      <td>3,600.0000</td>\n",
       "      <td>1719</td>\n",
       "      <td>362</td>\n",
       "      <td>BMC Biology publishes research and methodology...</td>\n",
       "      <td>True</td>\n",
       "      <td>527,029,080,731,176,960.0000</td>\n",
       "      <td>christlet</td>\n",
       "      <td>False</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @christlet: Buzz Baum has an intriguing \"in...</td>\n",
       "      <td>26216</td>\n",
       "      <td>28.3628</td>\n",
       "      <td>44</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527399468799651840</th>\n",
       "      <td>10.1186/s12915-014-0076-2</td>\n",
       "      <td>2014-10-29 10:00:06</td>\n",
       "      <td>Wed</td>\n",
       "      <td>BioMedCentral</td>\n",
       "      <td>41561657</td>\n",
       "      <td>3,600.0000</td>\n",
       "      <td>41064</td>\n",
       "      <td>1862</td>\n",
       "      <td>The Open Access Publisher of Science, Medicine...</td>\n",
       "      <td>False</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>How did complex life evolve? The answer could ...</td>\n",
       "      <td>27680</td>\n",
       "      <td>29.9467</td>\n",
       "      <td>45</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527400537525067776</th>\n",
       "      <td>10.1186/s12915-014-0076-2</td>\n",
       "      <td>2014-10-29 10:04:21</td>\n",
       "      <td>Wed</td>\n",
       "      <td>HansZauner</td>\n",
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       "      <td>7,200.0000</td>\n",
       "      <td>838</td>\n",
       "      <td>800</td>\n",
       "      <td>Freund der Wissenschaft, gelernter Evolutionsb...</td>\n",
       "      <td>False</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Evolution der eukaryotischen Zelle \"inside out...</td>\n",
       "      <td>28308</td>\n",
       "      <td>30.6261</td>\n",
       "      <td>46</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527418420091162624</th>\n",
       "      <td>10.1186/s12915-014-0076-2</td>\n",
       "      <td>2014-10-29 11:15:24</td>\n",
       "      <td>Wed</td>\n",
       "      <td>Lab_Journal</td>\n",
       "      <td>1060480867</td>\n",
       "      <td>nan</td>\n",
       "      <td>966</td>\n",
       "      <td>215</td>\n",
       "      <td>Forschungsmagazin, Wissenschaftsjournalismus, ...</td>\n",
       "      <td>True</td>\n",
       "      <td>527,400,537,525,067,776.0000</td>\n",
       "      <td>HansZauner</td>\n",
       "      <td>False</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @HansZauner: Evolution der eukaryotischen Z...</td>\n",
       "      <td>28382</td>\n",
       "      <td>30.7061</td>\n",
       "      <td>47</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527418942848262146</th>\n",
       "      <td>10.1186/s12915-014-0076-2</td>\n",
       "      <td>2014-10-29 11:17:29</td>\n",
       "      <td>Wed</td>\n",
       "      <td>Zernunft</td>\n",
       "      <td>223383396</td>\n",
       "      <td>7,200.0000</td>\n",
       "      <td>103</td>\n",
       "      <td>403</td>\n",
       "      <td>My tweets are actually caws. Feminist introver...</td>\n",
       "      <td>True</td>\n",
       "      <td>527,400,537,525,067,776.0000</td>\n",
       "      <td>HansZauner</td>\n",
       "      <td>False</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @HansZauner: Evolution der eukaryotischen Z...</td>\n",
       "      <td>28739</td>\n",
       "      <td>31.0924</td>\n",
       "      <td>48</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527422352502833153</th>\n",
       "      <td>10.1186/s12915-014-0076-2</td>\n",
       "      <td>2014-10-29 11:31:02</td>\n",
       "      <td>Wed</td>\n",
       "      <td>KonSciencePod</td>\n",
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       "      <td>7,200.0000</td>\n",
       "      <td>591</td>\n",
       "      <td>75</td>\n",
       "      <td>Der #Wissenschaft-s-#Podcast aus #Konstanz. Te...</td>\n",
       "      <td>True</td>\n",
       "      <td>527,400,537,525,067,776.0000</td>\n",
       "      <td>HansZauner</td>\n",
       "      <td>False</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RT @HansZauner: Evolution der eukaryotischen Z...</td>\n",
       "      <td>28789</td>\n",
       "      <td>31.1465</td>\n",
       "      <td>49</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          doi          created_at  \\\n",
       "tweet_id                                                            \n",
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       "\n",
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       "527125135640518656                  Tue        pwebmedia    961865077   \n",
       "527126860581593088                  Tue    davidcamachoj    146692746   \n",
       "527157079937527809                  Tue      ibridazioni     83836479   \n",
       "527166710046945280                  Tue     ctskennerton   2158831501   \n",
       "527300867972550656                  Wed      rapiduplift     18282718   \n",
       "527364538422026240                  Wed          flowing     10202432   \n",
       "527379076902707201                  Wed           ayuk74    229599040   \n",
       "527398549273985024                  Wed       BMCBiology    299580552   \n",
       "527399468799651840                  Wed    BioMedCentral     41561657   \n",
       "527400537525067776                  Wed       HansZauner    995259308   \n",
       "527418420091162624                  Wed      Lab_Journal   1060480867   \n",
       "527418942848262146                  Wed         Zernunft    223383396   \n",
       "527422352502833153                  Wed    KonSciencePod   1304229252   \n",
       "\n",
       "                        user_utc_offset  user_followers_count  \\\n",
       "tweet_id                                                        \n",
       "526914690103115776                  nan                     7   \n",
       "526983297050902528                  nan                   128   \n",
       "526983310749077505                  nan                    82   \n",
       "526988363208065025                  nan                   119   \n",
       "527029080731176960           7,200.0000                  1724   \n",
       "527029277519536128           3,600.0000                  2172   \n",
       "527029506834714624           7,200.0000                  1192   \n",
       "527029756517048320                  nan                  1503   \n",
       "527030000827256832           7,200.0000                  1172   \n",
       "527031432259309568           3,600.0000                   236   \n",
       "527031804826746880           7,200.0000                   899   \n",
       "527032599496392704          -7,200.0000                   485   \n",
       "527034739774210048                  nan                   298   \n",
       "527035457637720064           3,600.0000                   236   \n",
       "527039551978885120           7,200.0000                  1273   \n",
       "527039925817188353           3,600.0000                  1719   \n",
       "527040104636768257         -10,800.0000                    12   \n",
       "527040114980323329         -10,800.0000                    12   \n",
       "527062830277591041         -14,400.0000                  2536   \n",
       "527065845110177792                  nan                   527   \n",
       "527067393965977600           7,200.0000                  1079   \n",
       "527067451474075648         -25,200.0000                   687   \n",
       "527071887612850176         -28,800.0000                  4105   \n",
       "527099836890238976          36,000.0000                  1169   \n",
       "527120109215555584           3,600.0000                 13259   \n",
       "527120572069982208         -25,200.0000                  2464   \n",
       "527120967840313344         -18,000.0000                   274   \n",
       "527121083296915456         -10,800.0000                   250   \n",
       "527121112208244736           7,200.0000                   213   \n",
       "527121404370890753          25,200.0000                   331   \n",
       "527121602404966400                  nan                   106   \n",
       "527121703277961217                  nan                   452   \n",
       "527122302002290688         -21,600.0000                  8798   \n",
       "527122727099174912                  nan                   208   \n",
       "527122893709516800         -25,200.0000                 20145   \n",
       "527123824480108545                  nan                    60   \n",
       "527123935440429057           7,200.0000                   451   \n",
       "527125135640518656          34,200.0000                 10835   \n",
       "527126860581593088                  nan                   271   \n",
       "527157079937527809           7,200.0000                   896   \n",
       "527166710046945280         -25,200.0000                   138   \n",
       "527300867972550656          19,800.0000                   631   \n",
       "527364538422026240           7,200.0000                   145   \n",
       "527379076902707201         -36,000.0000                    85   \n",
       "527398549273985024           3,600.0000                  1719   \n",
       "527399468799651840           3,600.0000                 41064   \n",
       "527400537525067776           7,200.0000                   838   \n",
       "527418420091162624                  nan                   966   \n",
       "527418942848262146           7,200.0000                   103   \n",
       "527422352502833153           7,200.0000                   591   \n",
       "\n",
       "                    user_friends_count  \\\n",
       "tweet_id                                 \n",
       "526914690103115776                   8   \n",
       "526983297050902528                 113   \n",
       "526983310749077505                  11   \n",
       "526988363208065025                  30   \n",
       "527029080731176960                 661   \n",
       "527029277519536128                 978   \n",
       "527029506834714624                 811   \n",
       "527029756517048320                 330   \n",
       "527030000827256832                1220   \n",
       "527031432259309568                 786   \n",
       "527031804826746880                 528   \n",
       "527032599496392704                 719   \n",
       "527034739774210048                 520   \n",
       "527035457637720064                 786   \n",
       "527039551978885120                1651   \n",
       "527039925817188353                 362   \n",
       "527040104636768257                  10   \n",
       "527040114980323329                  10   \n",
       "527062830277591041                1709   \n",
       "527065845110177792                 706   \n",
       "527067393965977600                1667   \n",
       "527067451474075648                 130   \n",
       "527071887612850176                 976   \n",
       "527099836890238976                1271   \n",
       "527120109215555584                   1   \n",
       "527120572069982208                2899   \n",
       "527120967840313344                  76   \n",
       "527121083296915456                   0   \n",
       "527121112208244736                   0   \n",
       "527121404370890753                  67   \n",
       "527121602404966400                  37   \n",
       "527121703277961217                 146   \n",
       "527122302002290688                7974   \n",
       "527122727099174912                   0   \n",
       "527122893709516800                   1   \n",
       "527123824480108545                  14   \n",
       "527123935440429057                 384   \n",
       "527125135640518656                 219   \n",
       "527126860581593088                 413   \n",
       "527157079937527809                1165   \n",
       "527166710046945280                  68   \n",
       "527300867972550656                 153   \n",
       "527364538422026240                 100   \n",
       "527379076902707201                 302   \n",
       "527398549273985024                 362   \n",
       "527399468799651840                1862   \n",
       "527400537525067776                 800   \n",
       "527418420091162624                 215   \n",
       "527418942848262146                 403   \n",
       "527422352502833153                  75   \n",
       "\n",
       "                                                     user_description  \\\n",
       "tweet_id                                                                \n",
       "526914690103115776  The latest live science news: medicine, health...   \n",
       "526983297050902528  Cutting edge instrumentation and consumables f...   \n",
       "526983310749077505                                                NaN   \n",
       "526988363208065025                                                NaN   \n",
       "527029080731176960  Researcher #CNRS #univAMU dabbling in #neurobi...   \n",
       "527029277519536128  Cell biologist. My lab researches membrane tra...   \n",
       "527029506834714624  L'information éclairée par la recherche http:/...   \n",
       "527029756517048320  Developmental geneticist who wants to know how...   \n",
       "527030000827256832  Je sers la #science et le #PS10e, et c'est ma ...   \n",
       "527031432259309568  Postdoc in the Baum Lab at the MRC LMCB with a...   \n",
       "527031804826746880                                 centrosome-centred   \n",
       "527032599496392704  Bióloga Molecular y Bioquimica, con suerte en ...   \n",
       "527034739774210048  Underpaid & overworked PhD student who sold he...   \n",
       "527035457637720064  Postdoc in the Baum Lab at the MRC LMCB with a...   \n",
       "527039551978885120  Altbrarian #digitalscholarship #openaccess #op...   \n",
       "527039925817188353  BMC Biology publishes research and methodology...   \n",
       "527040104636768257                                                NaN   \n",
       "527040114980323329                                                NaN   \n",
       "527062830277591041  Nanoblogger scientifique, associate professor ...   \n",
       "527065845110177792  We do not see the world as it is we see the wo...   \n",
       "527067393965977600  dev android application mobile. Wikipédien. Bo...   \n",
       "527067451474075648  How does the brain work? Someday, we'll figure...   \n",
       "527071887612850176  Tweeting microbiology out of the deep South. A...   \n",
       "527099836890238976  Wanting a world that values people over profit...   \n",
       "527120109215555584  Tweets the stories on the front page of Hacker...   \n",
       "527120572069982208  Freelance web designer working on something bi...   \n",
       "527120967840313344  Technology: All over the place. Tips, tricks, ...   \n",
       "527121083296915456          ↪ Hacker News from Ycombinator delivered.   \n",
       "527121112208244736                                                NaN   \n",
       "527121404370890753  Pradeep Bheron Coding | ✈Travelling | Photogra...   \n",
       "527121602404966400  Retweeting WorldWide News Just For You. 1 Acco...   \n",
       "527121703277961217  Drosophila geneticist. Interested in brain siz...   \n",
       "527122302002290688              Making technology ideas come to life!   \n",
       "527122727099174912                                                NaN   \n",
       "527122893709516800  Latest from Hacker News Y Combinator at http:/...   \n",
       "527123824480108545  Interesting links, news, inspiration, and side...   \n",
       "527123935440429057  Visto por última vez dentro de un agujero negr...   \n",
       "527125135640518656                         Our Mission Is Your Vision   \n",
       "527126860581593088       good news, bad news, and very bad news......   \n",
       "527157079937527809  Psychologist, Design Research Director at Desi...   \n",
       "527166710046945280  Microbiologist, Bioinformatician. More of the ...   \n",
       "527300867972550656  sedimentary geologist dreaming of a Himalayan ...   \n",
       "527364538422026240  +machine_learning +data_mining +human_rights +...   \n",
       "527379076902707201                                   Phd,PharmD, 2007   \n",
       "527398549273985024  BMC Biology publishes research and methodology...   \n",
       "527399468799651840  The Open Access Publisher of Science, Medicine...   \n",
       "527400537525067776  Freund der Wissenschaft, gelernter Evolutionsb...   \n",
       "527418420091162624  Forschungsmagazin, Wissenschaftsjournalismus, ...   \n",
       "527418942848262146  My tweets are actually caws. Feminist introver...   \n",
       "527422352502833153  Der #Wissenschaft-s-#Podcast aus #Konstanz. Te...   \n",
       "\n",
       "                   is_retweet     retweet_of_status_id_str  \\\n",
       "tweet_id                                                     \n",
       "526914690103115776      False                          nan   \n",
       "526983297050902528      False                          nan   \n",
       "526983310749077505      False                          nan   \n",
       "526988363208065025      False                          nan   \n",
       "527029080731176960      False                          nan   \n",
       "527029277519536128       True 527,029,080,731,176,960.0000   \n",
       "527029506834714624       True 527,029,080,731,176,960.0000   \n",
       "527029756517048320       True 527,029,080,731,176,960.0000   \n",
       "527030000827256832       True 527,029,080,731,176,960.0000   \n",
       "527031432259309568       True 527,029,080,731,176,960.0000   \n",
       "527031804826746880       True 527,029,080,731,176,960.0000   \n",
       "527032599496392704       True 527,029,080,731,176,960.0000   \n",
       "527034739774210048       True 527,029,080,731,176,960.0000   \n",
       "527035457637720064       True 526,988,363,208,065,024.0000   \n",
       "527039551978885120       True 527,029,080,731,176,960.0000   \n",
       "527039925817188353      False                          nan   \n",
       "527040104636768257      False                          nan   \n",
       "527040114980323329      False                          nan   \n",
       "527062830277591041       True 527,029,080,731,176,960.0000   \n",
       "527065845110177792       True 527,029,080,731,176,960.0000   \n",
       "527067393965977600       True 527,029,080,731,176,960.0000   \n",
       "527067451474075648       True 527,029,080,731,176,960.0000   \n",
       "527071887612850176      False                          nan   \n",
       "527099836890238976      False                          nan   \n",
       "527120109215555584      False                          nan   \n",
       "527120572069982208      False                          nan   \n",
       "527120967840313344      False                          nan   \n",
       "527121083296915456      False                          nan   \n",
       "527121112208244736      False                          nan   \n",
       "527121404370890753      False                          nan   \n",
       "527121602404966400      False                          nan   \n",
       "527121703277961217       True 527,029,080,731,176,960.0000   \n",
       "527122302002290688      False                          nan   \n",
       "527122727099174912      False                          nan   \n",
       "527122893709516800      False                          nan   \n",
       "527123824480108545      False                          nan   \n",
       "527123935440429057      False                          nan   \n",
       "527125135640518656      False                          nan   \n",
       "527126860581593088      False                          nan   \n",
       "527157079937527809      False                          nan   \n",
       "527166710046945280       True 527,071,887,612,850,176.0000   \n",
       "527300867972550656      False                          nan   \n",
       "527364538422026240       True 527,029,080,731,176,960.0000   \n",
       "527379076902707201      False                          nan   \n",
       "527398549273985024       True 527,029,080,731,176,960.0000   \n",
       "527399468799651840      False                          nan   \n",
       "527400537525067776      False                          nan   \n",
       "527418420091162624       True 527,400,537,525,067,776.0000   \n",
       "527418942848262146       True 527,400,537,525,067,776.0000   \n",
       "527422352502833153       True 527,400,537,525,067,776.0000   \n",
       "\n",
       "                   retweet_of_screen_name is_reply  in_reply_to_status_id_str  \\\n",
       "tweet_id                                                                        \n",
       "526914690103115776                    NaN    False                        nan   \n",
       "526983297050902528                    NaN    False                        nan   \n",
       "526983310749077505                    NaN    False                        nan   \n",
       "526988363208065025                    NaN    False                        nan   \n",
       "527029080731176960                    NaN    False                        nan   \n",
       "527029277519536128              christlet    False                        nan   \n",
       "527029506834714624              christlet    False                        nan   \n",
       "527029756517048320              christlet    False                        nan   \n",
       "527030000827256832              christlet    False                        nan   \n",
       "527031432259309568              christlet    False                        nan   \n",
       "527031804826746880              christlet    False                        nan   \n",
       "527032599496392704              christlet    False                        nan   \n",
       "527034739774210048              christlet    False                        nan   \n",
       "527035457637720064               BaumBuzz    False                        nan   \n",
       "527039551978885120              christlet    False                        nan   \n",
       "527039925817188353                    NaN    False                        nan   \n",
       "527040104636768257                    NaN    False                        nan   \n",
       "527040114980323329                    NaN    False                        nan   \n",
       "527062830277591041              christlet    False                        nan   \n",
       "527065845110177792              christlet    False                        nan   \n",
       "527067393965977600              christlet    False                        nan   \n",
       "527067451474075648              christlet    False                        nan   \n",
       "527071887612850176                    NaN    False                        nan   \n",
       "527099836890238976                    NaN    False                        nan   \n",
       "527120109215555584                    NaN    False                        nan   \n",
       "527120572069982208                    NaN    False                        nan   \n",
       "527120967840313344                    NaN    False                        nan   \n",
       "527121083296915456                    NaN    False                        nan   \n",
       "527121112208244736                    NaN    False                        nan   \n",
       "527121404370890753                    NaN    False                        nan   \n",
       "527121602404966400                    NaN    False                        nan   \n",
       "527121703277961217              christlet    False                        nan   \n",
       "527122302002290688                    NaN    False                        nan   \n",
       "527122727099174912                    NaN    False                        nan   \n",
       "527122893709516800                    NaN    False                        nan   \n",
       "527123824480108545                    NaN    False                        nan   \n",
       "527123935440429057                    NaN    False                        nan   \n",
       "527125135640518656                    NaN    False                        nan   \n",
       "527126860581593088                    NaN    False                        nan   \n",
       "527157079937527809                    NaN    False                        nan   \n",
       "527166710046945280             DrJCThrash    False                        nan   \n",
       "527300867972550656                    NaN    False                        nan   \n",
       "527364538422026240              christlet    False                        nan   \n",
       "527379076902707201                    NaN    False                        nan   \n",
       "527398549273985024              christlet    False                        nan   \n",
       "527399468799651840                    NaN    False                        nan   \n",
       "527400537525067776                    NaN    False                        nan   \n",
       "527418420091162624             HansZauner    False                        nan   \n",
       "527418942848262146             HansZauner    False                        nan   \n",
       "527422352502833153             HansZauner    False                        nan   \n",
       "\n",
       "                   in_reply_to_screen_name  \\\n",
       "tweet_id                                     \n",
       "526914690103115776                     NaN   \n",
       "526983297050902528                     NaN   \n",
       "526983310749077505                     NaN   \n",
       "526988363208065025                     NaN   \n",
       "527029080731176960                     NaN   \n",
       "527029277519536128                     NaN   \n",
       "527029506834714624                     NaN   \n",
       "527029756517048320                     NaN   \n",
       "527030000827256832                     NaN   \n",
       "527031432259309568                     NaN   \n",
       "527031804826746880                     NaN   \n",
       "527032599496392704                     NaN   \n",
       "527034739774210048                     NaN   \n",
       "527035457637720064                     NaN   \n",
       "527039551978885120                     NaN   \n",
       "527039925817188353                     NaN   \n",
       "527040104636768257                     NaN   \n",
       "527040114980323329                     NaN   \n",
       "527062830277591041                     NaN   \n",
       "527065845110177792                     NaN   \n",
       "527067393965977600                     NaN   \n",
       "527067451474075648                     NaN   \n",
       "527071887612850176                     NaN   \n",
       "527099836890238976                     NaN   \n",
       "527120109215555584                     NaN   \n",
       "527120572069982208                     NaN   \n",
       "527120967840313344                     NaN   \n",
       "527121083296915456                     NaN   \n",
       "527121112208244736                     NaN   \n",
       "527121404370890753                     NaN   \n",
       "527121602404966400                     NaN   \n",
       "527121703277961217                     NaN   \n",
       "527122302002290688                     NaN   \n",
       "527122727099174912                     NaN   \n",
       "527122893709516800                     NaN   \n",
       "527123824480108545                     NaN   \n",
       "527123935440429057                     NaN   \n",
       "527125135640518656                     NaN   \n",
       "527126860581593088                     NaN   \n",
       "527157079937527809                     NaN   \n",
       "527166710046945280                     NaN   \n",
       "527300867972550656                     NaN   \n",
       "527364538422026240                     NaN   \n",
       "527379076902707201                     NaN   \n",
       "527398549273985024                     NaN   \n",
       "527399468799651840                     NaN   \n",
       "527400537525067776                     NaN   \n",
       "527418420091162624                     NaN   \n",
       "527418942848262146                     NaN   \n",
       "527422352502833153                     NaN   \n",
       "\n",
       "                                                                 text  \\\n",
       "tweet_id                                                                \n",
       "526914690103115776  An inside-out origin for the eukaryotic cell h...   \n",
       "526983297050902528  New theories = new thinking...we love it! http...   \n",
       "526983310749077505  New theories = new thinking...we love it! http...   \n",
       "526988363208065025  An inside-out origin for the eukaryote cell. M...   \n",
       "527029080731176960  Buzz Baum has an intriguing \"inside-out\" hypot...   \n",
       "527029277519536128  RT @christlet: Buzz Baum has an intriguing \"in...   \n",
       "527029506834714624  RT @christlet: Buzz Baum has an intriguing \"in...   \n",
       "527029756517048320  RT @christlet: Buzz Baum has an intriguing \"in...   \n",
       "527030000827256832  RT @christlet: Buzz Baum has an intriguing \"in...   \n",
       "527031432259309568  RT @christlet: Buzz Baum has an intriguing \"in...   \n",
       "527031804826746880  RT @christlet: Buzz Baum has an intriguing \"in...   \n",
       "527032599496392704  RT @christlet: Buzz Baum has an intriguing \"in...   \n",
       "527034739774210048  RT @christlet: Buzz Baum has an intriguing \"in...   \n",
       "527035457637720064  RT @BaumBuzz: An inside-out origin for the euk...   \n",
       "527039551978885120  RT @christlet: Buzz Baum has an intriguing \"in...   \n",
       "527039925817188353  Where did eukaryotes come from? From the insid...   \n",
       "527040104636768257  An inside-out origin for the eukaryotic cell h...   \n",
       "527040114980323329  An inside-out origin for the eukaryotic cell h...   \n",
       "527062830277591041  RT @christlet: Buzz Baum has an intriguing \"in...   \n",
       "527065845110177792  RT @christlet: Buzz Baum has an intriguing \"in...   \n",
       "527067393965977600  RT @christlet: Buzz Baum has an intriguing \"in...   \n",
       "527067451474075648  RT @christlet: Buzz Baum has an intriguing \"in...   \n",
       "527071887612850176  An inside-out origin for the eukaryotic cell h...   \n",
       "527099836890238976  An inside-out origin for the eukaryotic cell h...   \n",
       "527120109215555584  An inside-out origin for the eukaryotic cell: ...   \n",
       "527120572069982208  An inside-out origin for the eukaryotic cell h...   \n",
       "527120967840313344  An inside-out origin for the eukaryotic cell |...   \n",
       "527121083296915456  An inside-out origin for the eukaryotic cell h...   \n",
       "527121112208244736  An inside-out origin for the eukaryotic cell h...   \n",
       "527121404370890753  An inside-out origin for the eukaryotic cell h...   \n",
       "527121602404966400  An inside-out origin for the eukaryotic cell h...   \n",
       "527121703277961217  RT @christlet: Buzz Baum has an intriguing \"in...   \n",
       "527122302002290688  An inside-out origin for the eukaryotic cell h...   \n",
       "527122727099174912  From HN: An inside-out origin for the eukaryot...   \n",
       "527122893709516800  An inside-out origin for the eukaryotic cell h...   \n",
       "527123824480108545  An inside-out origin for the eukaryotic cell h...   \n",
       "527123935440429057  An inside-out origin for the eukaryotic cell h...   \n",
       "527125135640518656  An inside-out origin for the eukaryotic cell h...   \n",
       "527126860581593088  An inside-out origin for the eukaryotic cell h...   \n",
       "527157079937527809  An inside-out origin for the eukaryotic cell h...   \n",
       "527166710046945280  RT @DrJCThrash: An inside-out origin for the e...   \n",
       "527300867972550656  Interesting! a new hypothesis for the origin o...   \n",
       "527364538422026240  RT @christlet: Buzz Baum has an intriguing \"in...   \n",
       "527379076902707201  Evolution of complex life turns current theori...   \n",
       "527398549273985024  RT @christlet: Buzz Baum has an intriguing \"in...   \n",
       "527399468799651840  How did complex life evolve? The answer could ...   \n",
       "527400537525067776  Evolution der eukaryotischen Zelle \"inside out...   \n",
       "527418420091162624  RT @HansZauner: Evolution der eukaryotischen Z...   \n",
       "527418942848262146  RT @HansZauner: Evolution der eukaryotischen Z...   \n",
       "527422352502833153  RT @HansZauner: Evolution der eukaryotischen Z...   \n",
       "\n",
       "                    activated_users    activated_users_p  event_number  \\\n",
       "tweet_id                                                                 \n",
       "526914690103115776                9               0.0097             0   \n",
       "526983297050902528              119               0.1287             1   \n",
       "526983310749077505              130               0.1406             2   \n",
       "526988363208065025              161               0.1742             3   \n",
       "527029080731176960              818               0.8850             4   \n",
       "527029277519536128             1610               1.7418             5   \n",
       "527029506834714624             2367               2.5608             6   \n",
       "527029756517048320             2590               2.8021             7   \n",
       "527030000827256832             3583               3.8764             8   \n",
       "527031432259309568             4223               4.5688             9   \n",
       "527031804826746880             4483               4.8501            10   \n",
       "527032599496392704             5184               5.6085            11   \n",
       "527034739774210048             5565               6.0207            12   \n",
       "527035457637720064             5565               6.0207            13   \n",
       "527039551978885120             7033               7.6089            14   \n",
       "527039925817188353             7234               7.8264            15   \n",
       "527040104636768257             7245               7.8383            16   \n",
       "527040114980323329             7245               7.8383            17   \n",
       "527062830277591041             8441               9.1322            18   \n",
       "527065845110177792             9072               9.8149            19   \n",
       "527067393965977600            10477              11.3349            20   \n",
       "527067451474075648            10555              11.4193            21   \n",
       "527071887612850176            11474              12.4136            22   \n",
       "527099836890238976            12698              13.7378            23   \n",
       "527120109215555584            12700              13.7400            24   \n",
       "527120572069982208            15594              16.8710            25   \n",
       "527120967840313344            15659              16.9413            26   \n",
       "527121083296915456            15661              16.9434            27   \n",
       "527121112208244736            15662              16.9445            28   \n",
       "527121404370890753            15728              17.0159            29   \n",
       "527121602404966400            15764              17.0549            30   \n",
       "527121703277961217            15825              17.1209            31   \n",
       "527122302002290688            23682              25.6213            32   \n",
       "527122727099174912            23683              25.6224            33   \n",
       "527122893709516800            23685              25.6245            34   \n",
       "527123824480108545            23699              25.6397            35   \n",
       "527123935440429057            24049              26.0183            36   \n",
       "527125135640518656            24253              26.2390            37   \n",
       "527126860581593088            24617              26.6328            38   \n",
       "527157079937527809            25684              27.7872            39   \n",
       "527166710046945280            25720              27.8262            40   \n",
       "527300867972550656            25854              27.9711            41   \n",
       "527364538422026240            25947              28.0718            42   \n",
       "527379076902707201            26216              28.3628            43   \n",
       "527398549273985024            26216              28.3628            44   \n",
       "527399468799651840            27680              29.9467            45   \n",
       "527400537525067776            28308              30.6261            46   \n",
       "527418420091162624            28382              30.7061            47   \n",
       "527418942848262146            28739              31.0924            48   \n",
       "527422352502833153            28789              31.1465            49   \n",
       "\n",
       "                   new_user  \n",
       "tweet_id                     \n",
       "526914690103115776     True  \n",
       "526983297050902528     True  \n",
       "526983310749077505     True  \n",
       "526988363208065025     True  \n",
       "527029080731176960     True  \n",
       "527029277519536128     True  \n",
       "527029506834714624     True  \n",
       "527029756517048320     True  \n",
       "527030000827256832     True  \n",
       "527031432259309568     True  \n",
       "527031804826746880     True  \n",
       "527032599496392704     True  \n",
       "527034739774210048     True  \n",
       "527035457637720064    False  \n",
       "527039551978885120     True  \n",
       "527039925817188353     True  \n",
       "527040104636768257     True  \n",
       "527040114980323329    False  \n",
       "527062830277591041     True  \n",
       "527065845110177792     True  \n",
       "527067393965977600     True  \n",
       "527067451474075648     True  \n",
       "527071887612850176     True  \n",
       "527099836890238976     True  \n",
       "527120109215555584     True  \n",
       "527120572069982208     True  \n",
       "527120967840313344     True  \n",
       "527121083296915456     True  \n",
       "527121112208244736     True  \n",
       "527121404370890753     True  \n",
       "527121602404966400     True  \n",
       "527121703277961217     True  \n",
       "527122302002290688     True  \n",
       "527122727099174912     True  \n",
       "527122893709516800     True  \n",
       "527123824480108545     True  \n",
       "527123935440429057     True  \n",
       "527125135640518656     True  \n",
       "527126860581593088     True  \n",
       "527157079937527809     True  \n",
       "527166710046945280     True  \n",
       "527300867972550656     True  \n",
       "527364538422026240     True  \n",
       "527379076902707201     True  \n",
       "527398549273985024    False  \n",
       "527399468799651840     True  \n",
       "527400537525067776     True  \n",
       "527418420091162624     True  \n",
       "527418942848262146     True  \n",
       "527422352502833153     True  "
      ]
     },
     "execution_count": 262,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tweets.iloc[0:50]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.LineCollection at 0x10def0b10>"
      ]
     },
     "execution_count": 244,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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+0+mUr6+v25oTJ040uaa+vl5JSUl6/PHHNWXKlE6Zm8tdAAAA0KeNGzdOpaWlKi8vV11d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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116564310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure() \n",
    "\n",
    "ax = fig.add_subplot(111) \n",
    "ax2 = ax.twinx() \n",
    "df=tweets.set_index('created_at').activated_users_p.head(30)\n",
    "df = df.resample('168H').max().dropna().astype(int) \n",
    "df.plot(style='ob', ms=6, ax=ax)\n",
    "\n",
    "activations = df.diff(1).fillna(0).astype(int)\n",
    "days = df.reset_index().created_at.diff(1).fillna(0).map(lambda x: x.days)\n",
    "days.index = df.index\n",
    "\n",
    "angles = np.degrees(np.arctan2(activations, days)) #.map(lambda x: (x+180) % 360)\n",
    "\n",
    "changes = angles.map(mode) != angles.shift(1).map(mode)\n",
    "changes = changes[3:]\n",
    "changes = changes[changes].shift(-1)\n",
    "ymin, ymax = ax.get_ylim()\n",
    "angles.plot(style=\"oy\", ax=ax2)\n",
    "ax.vlines(x=changes.index, ymin=ymin, ymax=ymax-1, color='r')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "168"
      ]
     },
     "execution_count": 243,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "24*7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "created_at\n",
       "2014-01-31     True\n",
       "2014-02-01     True\n",
       "2014-02-02     True\n",
       "2014-02-03     True\n",
       "2014-02-04     True\n",
       "2014-02-05    False\n",
       "2014-02-06    False\n",
       "2014-02-07      NaN\n",
       "Freq: 24H, Name: activated_users_p, dtype: object"
      ]
     },
     "execution_count": 233,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "created_at\n",
       "2014-01-31                    nan\n",
       "2014-02-01                 0.0000\n",
       "2014-02-02                45.0000\n",
       "2014-02-03                 0.0000\n",
       "2014-02-04                45.0000\n",
       "2014-02-05                71.5651\n",
       "2014-02-06                 0.0000\n",
       "2014-02-07                 0.0000\n",
       "Freq: 24H, Name: activated_users_p, dtype: float64"
      ]
     },
     "execution_count": 231,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "angles.shift(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "created_at\n",
       "2014-01-31     True\n",
       "2014-02-01     True\n",
       "2014-02-02     True\n",
       "2014-02-03     True\n",
       "2014-02-04     True\n",
       "2014-02-05    False\n",
       "2014-02-06    False\n",
       "2014-02-07    False\n",
       "Freq: 24H, Name: activated_users_p, dtype: bool"
      ]
     },
     "execution_count": 221,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "created_at\n",
       "2014-02-25    True\n",
       "2014-03-06    True\n",
       "2014-03-23    True\n",
       "2014-03-25    True\n",
       "2014-05-28    True\n",
       "2014-06-10    True\n",
       "2014-11-21    True\n",
       "2014-11-24    True\n",
       "2015-01-11    True\n",
       "2015-02-21    True\n",
       "dtype: bool"
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}