FB_Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "NROWS = None\n",
    "\n",
    "posts = pd.read_csv('/Users/Shared/fb/link_posts.csv', nrows=NROWS, quotechar='\"', escapechar='\\\\')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>page_id</th>\n",
       "      <th>facebook_id</th>\n",
       "      <th>name</th>\n",
       "      <th>share</th>\n",
       "      <th>comment</th>\n",
       "      <th>like</th>\n",
       "      <th>love</th>\n",
       "      <th>haha</th>\n",
       "      <th>wow</th>\n",
       "      <th>...</th>\n",
       "      <th>source</th>\n",
       "      <th>created_time</th>\n",
       "      <th>updated_time</th>\n",
       "      <th>createdAt</th>\n",
       "      <th>updatedAt</th>\n",
       "      <th>id.1</th>\n",
       "      <th>fan_count</th>\n",
       "      <th>share_ratio</th>\n",
       "      <th>like_ratio</th>\n",
       "      <th>comment_ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>177964</td>\n",
       "      <td>1885</td>\n",
       "      <td>142474049098533_1474788722533719</td>\n",
       "      <td>Boeing's 787 Dreamliner Is Made Of Parts From ...</td>\n",
       "      <td>110196</td>\n",
       "      <td>10514</td>\n",
       "      <td>114884</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9105.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-17 19:28:36</td>\n",
       "      <td>2017-02-25 22:51:41</td>\n",
       "      <td>2017-02-26 12:49:55</td>\n",
       "      <td>2017-02-26 12:49:55</td>\n",
       "      <td>1885</td>\n",
       "      <td>2096549</td>\n",
       "      <td>0.052561</td>\n",
       "      <td>0.054797</td>\n",
       "      <td>5.014908e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1940645</td>\n",
       "      <td>20163</td>\n",
       "      <td>131180673952_10155037642073953</td>\n",
       "      <td>Papa sugere que é “melhor ser ateu do que cató...</td>\n",
       "      <td>96104</td>\n",
       "      <td>3426</td>\n",
       "      <td>86598</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2352.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-26 08:59:00</td>\n",
       "      <td>2017-02-26 16:15:01</td>\n",
       "      <td>2017-02-26 16:18:01</td>\n",
       "      <td>2017-02-26 16:18:01</td>\n",
       "      <td>20163</td>\n",
       "      <td>4035108</td>\n",
       "      <td>0.023817</td>\n",
       "      <td>0.021461</td>\n",
       "      <td>8.490479e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>645038</td>\n",
       "      <td>6729</td>\n",
       "      <td>52107727250_10154120507997251</td>\n",
       "      <td>Fallece Pablo Ráez tras una lucha titánica con...</td>\n",
       "      <td>92376</td>\n",
       "      <td>5999</td>\n",
       "      <td>3824</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1034.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-25 18:11:45</td>\n",
       "      <td>2017-02-26 14:09:17</td>\n",
       "      <td>2017-02-26 14:11:12</td>\n",
       "      <td>2017-02-26 14:11:12</td>\n",
       "      <td>6729</td>\n",
       "      <td>239639</td>\n",
       "      <td>0.385480</td>\n",
       "      <td>0.015957</td>\n",
       "      <td>2.503349e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>269158</td>\n",
       "      <td>2860</td>\n",
       "      <td>9124187907_10155660939257908</td>\n",
       "      <td>House bill would scale back number of free sch...</td>\n",
       "      <td>90349</td>\n",
       "      <td>9684</td>\n",
       "      <td>39706</td>\n",
       "      <td>NaN</td>\n",
       "      <td>156.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-21 18:47:41</td>\n",
       "      <td>2017-02-26 11:49:56</td>\n",
       "      <td>2017-02-26 13:06:18</td>\n",
       "      <td>2017-02-26 13:06:18</td>\n",
       "      <td>2860</td>\n",
       "      <td>6684171</td>\n",
       "      <td>0.013517</td>\n",
       "      <td>0.005940</td>\n",
       "      <td>1.448796e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>269195</td>\n",
       "      <td>2860</td>\n",
       "      <td>9124187907_10155626886227908</td>\n",
       "      <td>Dakota Access Pipeline Approved a Week After C...</td>\n",
       "      <td>86984</td>\n",
       "      <td>4644</td>\n",
       "      <td>63378</td>\n",
       "      <td>NaN</td>\n",
       "      <td>251.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-10 21:51:23</td>\n",
       "      <td>2017-02-22 21:52:41</td>\n",
       "      <td>2017-02-26 13:06:18</td>\n",
       "      <td>2017-02-26 13:06:18</td>\n",
       "      <td>2860</td>\n",
       "      <td>6684171</td>\n",
       "      <td>0.013013</td>\n",
       "      <td>0.009482</td>\n",
       "      <td>6.947758e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>269214</td>\n",
       "      <td>2860</td>\n",
       "      <td>9124187907_10155614787412908</td>\n",
       "      <td>After Trump moves to undo financial regulation...</td>\n",
       "      <td>74276</td>\n",
       "      <td>9754</td>\n",
       "      <td>239914</td>\n",
       "      <td>NaN</td>\n",
       "      <td>743.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-06 15:25:21</td>\n",
       "      <td>2017-02-22 16:26:19</td>\n",
       "      <td>2017-02-26 13:06:18</td>\n",
       "      <td>2017-02-26 13:06:18</td>\n",
       "      <td>2860</td>\n",
       "      <td>6684171</td>\n",
       "      <td>0.011112</td>\n",
       "      <td>0.035893</td>\n",
       "      <td>1.459268e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2805234</td>\n",
       "      <td>29142</td>\n",
       "      <td>165205036869225_1380796198643430</td>\n",
       "      <td>Prefeito destina verba que seria do Carnaval p...</td>\n",
       "      <td>71010</td>\n",
       "      <td>4150</td>\n",
       "      <td>163415</td>\n",
       "      <td>NaN</td>\n",
       "      <td>276.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-22 18:00:34</td>\n",
       "      <td>2017-02-26 16:07:07</td>\n",
       "      <td>2017-02-26 16:39:00</td>\n",
       "      <td>2017-02-26 16:39:00</td>\n",
       "      <td>29142</td>\n",
       "      <td>6745116</td>\n",
       "      <td>0.010528</td>\n",
       "      <td>0.024227</td>\n",
       "      <td>6.152600e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>269235</td>\n",
       "      <td>2860</td>\n",
       "      <td>9124187907_10155597953617908</td>\n",
       "      <td>After meeting with pharma lobbyists, Trump dro...</td>\n",
       "      <td>69586</td>\n",
       "      <td>10346</td>\n",
       "      <td>76792</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1309.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-01-31 22:33:22</td>\n",
       "      <td>2017-02-23 18:58:51</td>\n",
       "      <td>2017-02-26 13:06:18</td>\n",
       "      <td>2017-02-26 13:06:18</td>\n",
       "      <td>2860</td>\n",
       "      <td>6684171</td>\n",
       "      <td>0.010411</td>\n",
       "      <td>0.011489</td>\n",
       "      <td>1.547836e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1472865</td>\n",
       "      <td>15354</td>\n",
       "      <td>1371996966150726_1582954265054994</td>\n",
       "      <td>People Want To Shoot Hibernating Bear Families...</td>\n",
       "      <td>65809</td>\n",
       "      <td>1272</td>\n",
       "      <td>1603</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-17 18:43:00</td>\n",
       "      <td>2017-02-23 01:10:50</td>\n",
       "      <td>2017-02-26 16:07:38</td>\n",
       "      <td>2017-02-26 16:07:38</td>\n",
       "      <td>15354</td>\n",
       "      <td>1177625</td>\n",
       "      <td>0.055883</td>\n",
       "      <td>0.001361</td>\n",
       "      <td>1.080140e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>661976</td>\n",
       "      <td>6901</td>\n",
       "      <td>332968243416537_1398127326900618</td>\n",
       "      <td>REPORT: Aaron Hernandez Says He Too Will Skip ...</td>\n",
       "      <td>61975</td>\n",
       "      <td>3791</td>\n",
       "      <td>40526</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22322.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-10 03:12:57</td>\n",
       "      <td>2017-02-22 13:03:33</td>\n",
       "      <td>2017-02-26 14:14:05</td>\n",
       "      <td>2017-02-26 14:14:05</td>\n",
       "      <td>6901</td>\n",
       "      <td>2793744</td>\n",
       "      <td>0.022183</td>\n",
       "      <td>0.014506</td>\n",
       "      <td>1.356960e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>267907</td>\n",
       "      <td>2847</td>\n",
       "      <td>199870617084581_214145832323726</td>\n",
       "      <td>Republicans begin effort to gut the Endangered...</td>\n",
       "      <td>61145</td>\n",
       "      <td>4824</td>\n",
       "      <td>2907</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-16 14:05:00</td>\n",
       "      <td>2017-02-25 13:27:59</td>\n",
       "      <td>2017-02-26 13:06:04</td>\n",
       "      <td>2017-02-26 13:06:04</td>\n",
       "      <td>2847</td>\n",
       "      <td>1101432</td>\n",
       "      <td>0.055514</td>\n",
       "      <td>0.002639</td>\n",
       "      <td>4.379753e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2202482</td>\n",
       "      <td>22890</td>\n",
       "      <td>104438892938868_1395905253792219</td>\n",
       "      <td>La televisión italiana difunde el drama argent...</td>\n",
       "      <td>57748</td>\n",
       "      <td>827</td>\n",
       "      <td>20158</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-25 00:02:00</td>\n",
       "      <td>2017-02-26 16:19:35</td>\n",
       "      <td>2017-02-26 16:24:04</td>\n",
       "      <td>2017-02-26 16:24:04</td>\n",
       "      <td>22890</td>\n",
       "      <td>16633846</td>\n",
       "      <td>0.003472</td>\n",
       "      <td>0.001212</td>\n",
       "      <td>4.971791e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>269148</td>\n",
       "      <td>2860</td>\n",
       "      <td>9124187907_10155667100922908</td>\n",
       "      <td>The Trump administration just handed the priva...</td>\n",
       "      <td>56783</td>\n",
       "      <td>5552</td>\n",
       "      <td>42038</td>\n",
       "      <td>NaN</td>\n",
       "      <td>162.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-24 01:45:06</td>\n",
       "      <td>2017-02-26 12:31:59</td>\n",
       "      <td>2017-02-26 13:06:18</td>\n",
       "      <td>2017-02-26 13:06:18</td>\n",
       "      <td>2860</td>\n",
       "      <td>6684171</td>\n",
       "      <td>0.008495</td>\n",
       "      <td>0.006289</td>\n",
       "      <td>8.306191e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2601628</td>\n",
       "      <td>27035</td>\n",
       "      <td>110177082404435_1265112300244235</td>\n",
       "      <td>El mismo juzgado que ha absuelto a la infanta ...</td>\n",
       "      <td>55405</td>\n",
       "      <td>1394</td>\n",
       "      <td>3860</td>\n",
       "      <td>NaN</td>\n",
       "      <td>530.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-17 18:46:56</td>\n",
       "      <td>2017-02-23 23:36:20</td>\n",
       "      <td>2017-02-26 16:33:07</td>\n",
       "      <td>2017-02-26 16:33:07</td>\n",
       "      <td>27035</td>\n",
       "      <td>871655</td>\n",
       "      <td>0.063563</td>\n",
       "      <td>0.004428</td>\n",
       "      <td>1.599257e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2532554</td>\n",
       "      <td>26319</td>\n",
       "      <td>997108126967413_1509679769043577</td>\n",
       "      <td>Big Pharma Finally Admits Cannabis Kills Cance...</td>\n",
       "      <td>54969</td>\n",
       "      <td>2612</td>\n",
       "      <td>88968</td>\n",
       "      <td>NaN</td>\n",
       "      <td>364.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-12 22:31:47</td>\n",
       "      <td>2017-02-21 04:37:39</td>\n",
       "      <td>2017-02-26 16:31:31</td>\n",
       "      <td>2017-02-26 16:31:31</td>\n",
       "      <td>26319</td>\n",
       "      <td>6885736</td>\n",
       "      <td>0.007983</td>\n",
       "      <td>0.012921</td>\n",
       "      <td>3.793349e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2678567</td>\n",
       "      <td>27831</td>\n",
       "      <td>169528479736063_1357156890973210</td>\n",
       "      <td>Robert Englund Back for One Last Freddy Film</td>\n",
       "      <td>54699</td>\n",
       "      <td>3737</td>\n",
       "      <td>59160</td>\n",
       "      <td>NaN</td>\n",
       "      <td>127.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-01 22:50:40</td>\n",
       "      <td>2017-02-10 23:57:22</td>\n",
       "      <td>2017-02-26 16:36:12</td>\n",
       "      <td>2017-02-26 16:36:12</td>\n",
       "      <td>27831</td>\n",
       "      <td>667995</td>\n",
       "      <td>0.081885</td>\n",
       "      <td>0.088564</td>\n",
       "      <td>5.594353e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>71088</td>\n",
       "      <td>790</td>\n",
       "      <td>5281959998_10151094045534999</td>\n",
       "      <td>White House Bars Times and 2 Other News Outlet...</td>\n",
       "      <td>51022</td>\n",
       "      <td>8454</td>\n",
       "      <td>9038</td>\n",
       "      <td>NaN</td>\n",
       "      <td>882.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-24 19:33:08</td>\n",
       "      <td>2017-02-26 12:26:14</td>\n",
       "      <td>2017-02-26 12:31:32</td>\n",
       "      <td>2017-02-26 12:31:32</td>\n",
       "      <td>790</td>\n",
       "      <td>13464157</td>\n",
       "      <td>0.003789</td>\n",
       "      <td>0.000671</td>\n",
       "      <td>6.278893e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>40629</td>\n",
       "      <td>470</td>\n",
       "      <td>346937065399354_1439187546174295</td>\n",
       "      <td>Militarized Police Just Evicted The Sioux Trib...</td>\n",
       "      <td>50985</td>\n",
       "      <td>4854</td>\n",
       "      <td>6613</td>\n",
       "      <td>NaN</td>\n",
       "      <td>98.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-23 19:50:00</td>\n",
       "      <td>2017-02-26 10:42:58</td>\n",
       "      <td>2017-02-26 12:26:10</td>\n",
       "      <td>2017-02-26 12:26:10</td>\n",
       "      <td>470</td>\n",
       "      <td>5915082</td>\n",
       "      <td>0.008619</td>\n",
       "      <td>0.001118</td>\n",
       "      <td>8.206142e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2438596</td>\n",
       "      <td>25361</td>\n",
       "      <td>131201286936061_1390301541026023</td>\n",
       "      <td>News from The Associated Press: \"Doomsday Cloc...</td>\n",
       "      <td>49870</td>\n",
       "      <td>10389</td>\n",
       "      <td>112315</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1295.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-01-28 11:45:00</td>\n",
       "      <td>2017-02-24 12:33:20</td>\n",
       "      <td>2017-02-26 16:29:26</td>\n",
       "      <td>2017-02-26 16:29:26</td>\n",
       "      <td>25361</td>\n",
       "      <td>5403968</td>\n",
       "      <td>0.009228</td>\n",
       "      <td>0.020784</td>\n",
       "      <td>1.922476e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1926916</td>\n",
       "      <td>20021</td>\n",
       "      <td>111415578911214_1867516903301064</td>\n",
       "      <td>¡Compartan! Les revelo la increíble fórmula pa...</td>\n",
       "      <td>49771</td>\n",
       "      <td>993</td>\n",
       "      <td>26835</td>\n",
       "      <td>NaN</td>\n",
       "      <td>87.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-14 01:30:07</td>\n",
       "      <td>2017-02-21 16:51:56</td>\n",
       "      <td>2017-02-26 16:17:42</td>\n",
       "      <td>2017-02-26 16:17:42</td>\n",
       "      <td>20021</td>\n",
       "      <td>8699306</td>\n",
       "      <td>0.005721</td>\n",
       "      <td>0.003085</td>\n",
       "      <td>1.141470e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>39376</td>\n",
       "      <td>458</td>\n",
       "      <td>24085780715_10158181697205716</td>\n",
       "      <td>The mysterious disappearance of the biggest sc...</td>\n",
       "      <td>49287</td>\n",
       "      <td>5608</td>\n",
       "      <td>66793</td>\n",
       "      <td>NaN</td>\n",
       "      <td>118.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-09 16:53:01</td>\n",
       "      <td>2017-02-24 19:23:44</td>\n",
       "      <td>2017-02-26 12:25:58</td>\n",
       "      <td>2017-02-26 12:25:58</td>\n",
       "      <td>458</td>\n",
       "      <td>1908514</td>\n",
       "      <td>0.025825</td>\n",
       "      <td>0.034997</td>\n",
       "      <td>2.938412e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>161407</td>\n",
       "      <td>1716</td>\n",
       "      <td>367116489976035_1649023648451973</td>\n",
       "      <td>Republicans Launch Attempt To Repeal Endangere...</td>\n",
       "      <td>48292</td>\n",
       "      <td>5382</td>\n",
       "      <td>12554</td>\n",
       "      <td>NaN</td>\n",
       "      <td>368.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-15 22:15:26</td>\n",
       "      <td>2017-02-23 06:57:40</td>\n",
       "      <td>2017-02-26 12:47:05</td>\n",
       "      <td>2017-02-26 12:47:05</td>\n",
       "      <td>1716</td>\n",
       "      <td>25581111</td>\n",
       "      <td>0.001888</td>\n",
       "      <td>0.000491</td>\n",
       "      <td>2.103896e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2601024</td>\n",
       "      <td>27029</td>\n",
       "      <td>1742306959430702_1746046362390095</td>\n",
       "      <td>House Moves to Encourage Drilling in National ...</td>\n",
       "      <td>47070</td>\n",
       "      <td>3371</td>\n",
       "      <td>13759</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-01 03:04:34</td>\n",
       "      <td>2017-02-08 02:05:29</td>\n",
       "      <td>2017-02-26 16:33:07</td>\n",
       "      <td>2017-02-26 16:33:07</td>\n",
       "      <td>27029</td>\n",
       "      <td>1434940</td>\n",
       "      <td>0.032803</td>\n",
       "      <td>0.009589</td>\n",
       "      <td>2.349227e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>269224</td>\n",
       "      <td>2860</td>\n",
       "      <td>9124187907_10155605794117908</td>\n",
       "      <td>Trump Vows to ‘Destroy’ Law Banning Political ...</td>\n",
       "      <td>46326</td>\n",
       "      <td>10290</td>\n",
       "      <td>72385</td>\n",
       "      <td>NaN</td>\n",
       "      <td>403.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-03 18:05:00</td>\n",
       "      <td>2017-02-25 17:58:57</td>\n",
       "      <td>2017-02-26 13:06:18</td>\n",
       "      <td>2017-02-26 13:06:18</td>\n",
       "      <td>2860</td>\n",
       "      <td>6684171</td>\n",
       "      <td>0.006931</td>\n",
       "      <td>0.010829</td>\n",
       "      <td>1.539458e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1263129</td>\n",
       "      <td>3566</td>\n",
       "      <td>208421665712_10158551640350713</td>\n",
       "      <td>Bill Paxton Dead at 61</td>\n",
       "      <td>46208</td>\n",
       "      <td>3528</td>\n",
       "      <td>5224</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-26 15:19:50</td>\n",
       "      <td>2017-02-26 16:02:43</td>\n",
       "      <td>2017-02-26 16:02:45</td>\n",
       "      <td>2017-02-26 16:02:45</td>\n",
       "      <td>3566</td>\n",
       "      <td>6902151</td>\n",
       "      <td>0.006695</td>\n",
       "      <td>0.000757</td>\n",
       "      <td>5.111450e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2532480</td>\n",
       "      <td>26319</td>\n",
       "      <td>997108126967413_1522487217762832</td>\n",
       "      <td>This MAN Healed 5000 People from Cancer: This ...</td>\n",
       "      <td>45983</td>\n",
       "      <td>2063</td>\n",
       "      <td>55254</td>\n",
       "      <td>NaN</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-24 19:13:29</td>\n",
       "      <td>2017-02-26 16:20:36</td>\n",
       "      <td>2017-02-26 16:31:31</td>\n",
       "      <td>2017-02-26 16:31:31</td>\n",
       "      <td>26319</td>\n",
       "      <td>6885736</td>\n",
       "      <td>0.006678</td>\n",
       "      <td>0.008024</td>\n",
       "      <td>2.996049e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>41724</td>\n",
       "      <td>482</td>\n",
       "      <td>5550296508_10156134811176509</td>\n",
       "      <td>White House blocks news organizations from pre...</td>\n",
       "      <td>45764</td>\n",
       "      <td>15119</td>\n",
       "      <td>13356</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4232.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-24 19:25:36</td>\n",
       "      <td>2017-02-26 12:25:12</td>\n",
       "      <td>2017-02-26 12:26:22</td>\n",
       "      <td>2017-02-26 12:26:22</td>\n",
       "      <td>482</td>\n",
       "      <td>26716165</td>\n",
       "      <td>0.001713</td>\n",
       "      <td>0.000500</td>\n",
       "      <td>5.659121e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>161361</td>\n",
       "      <td>1716</td>\n",
       "      <td>367116489976035_1658198047534533</td>\n",
       "      <td>Breakthrough In Search For Life As Seven Earth...</td>\n",
       "      <td>45659</td>\n",
       "      <td>4261</td>\n",
       "      <td>120886</td>\n",
       "      <td>NaN</td>\n",
       "      <td>167.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-22 18:08:46</td>\n",
       "      <td>2017-02-25 22:57:23</td>\n",
       "      <td>2017-02-26 12:47:05</td>\n",
       "      <td>2017-02-26 12:47:05</td>\n",
       "      <td>1716</td>\n",
       "      <td>25581111</td>\n",
       "      <td>0.001785</td>\n",
       "      <td>0.004726</td>\n",
       "      <td>1.665682e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2438574</td>\n",
       "      <td>25361</td>\n",
       "      <td>131201286936061_1406133962776114</td>\n",
       "      <td>Trump won't immediately appeal travel ban halt...</td>\n",
       "      <td>45581</td>\n",
       "      <td>7023</td>\n",
       "      <td>98154</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-11 21:28:20</td>\n",
       "      <td>2017-02-26 12:53:53</td>\n",
       "      <td>2017-02-26 16:29:26</td>\n",
       "      <td>2017-02-26 16:29:26</td>\n",
       "      <td>25361</td>\n",
       "      <td>5403968</td>\n",
       "      <td>0.008435</td>\n",
       "      <td>0.018163</td>\n",
       "      <td>1.299601e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>269145</td>\n",
       "      <td>2860</td>\n",
       "      <td>9124187907_10155670306072908</td>\n",
       "      <td>Republican lawmakers introduce bills to curb p...</td>\n",
       "      <td>45461</td>\n",
       "      <td>5624</td>\n",
       "      <td>63092</td>\n",
       "      <td>NaN</td>\n",
       "      <td>249.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-25 01:57:46</td>\n",
       "      <td>2017-02-26 13:05:31</td>\n",
       "      <td>2017-02-26 13:06:18</td>\n",
       "      <td>2017-02-26 13:06:18</td>\n",
       "      <td>2860</td>\n",
       "      <td>6684171</td>\n",
       "      <td>0.006801</td>\n",
       "      <td>0.009439</td>\n",
       "      <td>8.413908e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317668</th>\n",
       "      <td>2807039</td>\n",
       "      <td>29160</td>\n",
       "      <td>316449433298_10154517397403299</td>\n",
       "      <td>TEMPO REAL: Mirassol vs Corinthians - Paulistão</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>138</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-25 22:01:01</td>\n",
       "      <td>2017-02-26 02:04:46</td>\n",
       "      <td>2017-02-26 16:39:03</td>\n",
       "      <td>2017-02-26 16:39:03</td>\n",
       "      <td>29160</td>\n",
       "      <td>998597</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000138</td>\n",
       "      <td>4.005620e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317669</th>\n",
       "      <td>120319</td>\n",
       "      <td>1297</td>\n",
       "      <td>6654472378_10154379232217379</td>\n",
       "      <td>Romantic place names from around the world | S...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-14 15:38:00</td>\n",
       "      <td>2017-02-14 15:38:00</td>\n",
       "      <td>2017-02-26 12:40:02</td>\n",
       "      <td>2017-02-26 12:40:02</td>\n",
       "      <td>1297</td>\n",
       "      <td>1210743</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317670</th>\n",
       "      <td>55039</td>\n",
       "      <td>620</td>\n",
       "      <td>632729473453216_1331043880288435</td>\n",
       "      <td>Blumhouse</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-16 21:33:01</td>\n",
       "      <td>2017-02-16 21:33:01</td>\n",
       "      <td>2017-02-26 12:28:41</td>\n",
       "      <td>2017-02-26 12:28:41</td>\n",
       "      <td>620</td>\n",
       "      <td>455125</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000011</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317671</th>\n",
       "      <td>1956095</td>\n",
       "      <td>20321</td>\n",
       "      <td>147384458624178_1562946923734584</td>\n",
       "      <td>Sunday Times Food</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-23 11:50:25</td>\n",
       "      <td>2017-02-26 13:02:57</td>\n",
       "      <td>2017-02-26 16:18:21</td>\n",
       "      <td>2017-02-26 16:18:21</td>\n",
       "      <td>20321</td>\n",
       "      <td>608617</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>3.286139e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317672</th>\n",
       "      <td>2414847</td>\n",
       "      <td>25114</td>\n",
       "      <td>251934468302503_772753476220597</td>\n",
       "      <td>Eva Herzigova flaunts her age-defying beauty a...</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>49</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-26 13:00:16</td>\n",
       "      <td>2017-02-26 13:28:58</td>\n",
       "      <td>2017-02-26 16:29:03</td>\n",
       "      <td>2017-02-26 16:29:03</td>\n",
       "      <td>25114</td>\n",
       "      <td>1015465</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000048</td>\n",
       "      <td>3.939082e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317673</th>\n",
       "      <td>121855</td>\n",
       "      <td>1312</td>\n",
       "      <td>252062638385_10154559744913386</td>\n",
       "      <td>Jim Cantore (@JimCantore) posted a photo on Tw...</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-16 18:49:32</td>\n",
       "      <td>2017-02-17 06:07:30</td>\n",
       "      <td>2017-02-26 12:40:17</td>\n",
       "      <td>2017-02-26 12:40:17</td>\n",
       "      <td>1312</td>\n",
       "      <td>261084</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000115</td>\n",
       "      <td>1.149055e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317674</th>\n",
       "      <td>449535</td>\n",
       "      <td>4729</td>\n",
       "      <td>8684858250_10154443986778251</td>\n",
       "      <td>Nova 96.9</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-16 07:48:32</td>\n",
       "      <td>2017-02-16 12:49:26</td>\n",
       "      <td>2017-02-26 13:37:40</td>\n",
       "      <td>2017-02-26 13:37:40</td>\n",
       "      <td>4729</td>\n",
       "      <td>957151</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>4.179069e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317675</th>\n",
       "      <td>2153471</td>\n",
       "      <td>22374</td>\n",
       "      <td>168619349359_10154978151134360</td>\n",
       "      <td>Ayesha Takia on makeover: Some vicious people ...</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>248</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>2017-02-26 04:46:46</td>\n",
       "      <td>2017-02-26 06:04:06</td>\n",
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       "      <td>8.115128e-07</td>\n",
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       "    <tr>\n",
       "      <th>317676</th>\n",
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       "      <td>22376</td>\n",
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       "      <td>Live in green neighbourhood to cut depression,...</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>2017-02-26 06:26:00</td>\n",
       "      <td>2017-02-26 06:26:00</td>\n",
       "      <td>2017-02-26 16:22:57</td>\n",
       "      <td>2017-02-26 16:22:57</td>\n",
       "      <td>22376</td>\n",
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       "    <tr>\n",
       "      <th>317677</th>\n",
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       "      <td>NaN</td>\n",
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       "      <td>2017-02-24 21:19:00</td>\n",
       "      <td>2017-02-24 21:19:00</td>\n",
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       "      <td>2017-02-26 16:15:28</td>\n",
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       "    <tr>\n",
       "      <th>317678</th>\n",
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       "      <td>Fichardt wins Joburg Open with last-hole birdie</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>2017-02-26 15:54:35</td>\n",
       "      <td>2017-02-26 15:54:35</td>\n",
       "      <td>2017-02-26 16:22:57</td>\n",
       "      <td>2017-02-26 16:22:57</td>\n",
       "      <td>22382</td>\n",
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       "    <tr>\n",
       "      <th>317679</th>\n",
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       "      <td>Los últimos serán los primeros</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-25 19:00:02</td>\n",
       "      <td>2017-02-25 19:00:02</td>\n",
       "      <td>2017-02-26 16:25:56</td>\n",
       "      <td>2017-02-26 16:25:56</td>\n",
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       "    <tr>\n",
       "      <th>317680</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-26 12:33:00</td>\n",
       "      <td>2017-02-26 12:33:00</td>\n",
       "      <td>2017-02-26 16:27:26</td>\n",
       "      <td>2017-02-26 16:27:26</td>\n",
       "      <td>24444</td>\n",
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       "    <tr>\n",
       "      <th>317681</th>\n",
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       "      <td>18992</td>\n",
       "      <td>36841737921_10155151180622922</td>\n",
       "      <td>Sydney Comedy Festival 2017</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-22 01:30:02</td>\n",
       "      <td>2017-02-22 01:30:02</td>\n",
       "      <td>2017-02-26 16:15:29</td>\n",
       "      <td>2017-02-26 16:15:29</td>\n",
       "      <td>18992</td>\n",
       "      <td>660576</td>\n",
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       "      <td>0.000005</td>\n",
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       "      <th>317682</th>\n",
       "      <td>320255</td>\n",
       "      <td>3390</td>\n",
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       "      <td>Riverdales Trevor Stines Wants In On a Certain...</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-20 15:00:04</td>\n",
       "      <td>2017-02-21 18:38:50</td>\n",
       "      <td>2017-02-26 13:15:13</td>\n",
       "      <td>2017-02-26 13:15:13</td>\n",
       "      <td>3390</td>\n",
       "      <td>229782</td>\n",
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       "      <td>0.000022</td>\n",
       "      <td>3.046366e-05</td>\n",
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       "    <tr>\n",
       "      <th>317683</th>\n",
       "      <td>255231</td>\n",
       "      <td>2716</td>\n",
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       "      <td>Who Made the Cut? James Wrights Sets the Crew ...</td>\n",
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       "      <td>2</td>\n",
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       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-07 19:00:00</td>\n",
       "      <td>2017-02-09 22:00:24</td>\n",
       "      <td>2017-02-26 13:03:53</td>\n",
       "      <td>2017-02-26 13:03:53</td>\n",
       "      <td>2716</td>\n",
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       "      <td>4.520080e-06</td>\n",
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       "      <th>317684</th>\n",
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       "      <td>25824</td>\n",
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       "      <td>gph.is</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-26 03:14:00</td>\n",
       "      <td>2017-02-26 03:14:00</td>\n",
       "      <td>2017-02-26 16:30:27</td>\n",
       "      <td>2017-02-26 16:30:27</td>\n",
       "      <td>25824</td>\n",
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       "    <tr>\n",
       "      <th>317685</th>\n",
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       "      <td>23091</td>\n",
       "      <td>50842855867_10154234591625868</td>\n",
       "      <td>Óscar Ibáñez es el nuevo técnico de Comerciant...</td>\n",
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       "      <td>2</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-26 04:38:21</td>\n",
       "      <td>2017-02-26 04:59:34</td>\n",
       "      <td>2017-02-26 16:24:30</td>\n",
       "      <td>2017-02-26 16:24:30</td>\n",
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       "      <td>2.386524e-06</td>\n",
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       "      <td>All the It Girls Are Embracing This \"Faux Pas\"...</td>\n",
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       "      <td>2017-02-25 03:00:00</td>\n",
       "      <td>2017-02-25 03:00:00</td>\n",
       "      <td>2017-02-26 16:18:28</td>\n",
       "      <td>2017-02-26 16:18:28</td>\n",
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       "      <td>1978250</td>\n",
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       "      <td>5.054973e-07</td>\n",
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       "    <tr>\n",
       "      <th>317687</th>\n",
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       "      <td>23099</td>\n",
       "      <td>210152225666581_1663647563650366</td>\n",
       "      <td>GANA UN DESAYUNO GRATIS DE KeBurros</td>\n",
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       "      <td>2017-02-24 17:26:29</td>\n",
       "      <td>2017-02-24 17:26:29</td>\n",
       "      <td>2017-02-26 16:24:31</td>\n",
       "      <td>2017-02-26 16:24:31</td>\n",
       "      <td>23099</td>\n",
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       "      <td>0</td>\n",
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       "      <td>...</td>\n",
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       "      <td>2017-02-26 00:00:02</td>\n",
       "      <td>2017-02-26 00:00:02</td>\n",
       "      <td>2017-02-26 16:14:06</td>\n",
       "      <td>2017-02-26 16:14:06</td>\n",
       "      <td>18360</td>\n",
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       "      <td>Scientists Warn Parents To Keep Children Away ...</td>\n",
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       "      <td>2017-02-25 14:44:24</td>\n",
       "      <td>2017-02-25 14:44:24</td>\n",
       "      <td>2017-02-26 13:38:41</td>\n",
       "      <td>2017-02-26 13:38:41</td>\n",
       "      <td>4789</td>\n",
       "      <td>384580</td>\n",
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       "    <tr>\n",
       "      <th>317690</th>\n",
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       "      <td>14988</td>\n",
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       "      <td>Dark and Purple by Jennifer E</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>2017-02-23 21:00:02</td>\n",
       "      <td>2017-02-23 21:00:02</td>\n",
       "      <td>2017-02-26 16:06:50</td>\n",
       "      <td>2017-02-26 16:06:50</td>\n",
       "      <td>14988</td>\n",
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       "      <td>0.000000e+00</td>\n",
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       "      <th>317691</th>\n",
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       "      <td>YRF Music</td>\n",
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       "      <td>...</td>\n",
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       "      <td>2017-02-09 07:48:51</td>\n",
       "      <td>2017-02-13 14:49:38</td>\n",
       "      <td>2017-02-26 16:37:46</td>\n",
       "      <td>2017-02-26 16:37:46</td>\n",
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       "      <td>2.693100e-06</td>\n",
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       "      <td>2017-02-24 12:23:39</td>\n",
       "      <td>2017-02-25 13:26:29</td>\n",
       "      <td>2017-02-26 16:32:00</td>\n",
       "      <td>2017-02-26 16:32:00</td>\n",
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       "      <td>1.042560e-06</td>\n",
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       "      <td>...</td>\n",
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       "      <td>2017-02-12 06:04:50</td>\n",
       "      <td>2017-02-13 03:30:06</td>\n",
       "      <td>2017-02-26 13:04:49</td>\n",
       "      <td>2017-02-26 13:04:49</td>\n",
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       "      <td>1.245283e-05</td>\n",
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       "      <td>Jessa Duggar's New Baby Henry Is So Cute, We C...</td>\n",
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       "      <td>2017-02-20 13:09:24</td>\n",
       "      <td>2017-02-20 13:09:24</td>\n",
       "      <td>2017-02-26 14:01:35</td>\n",
       "      <td>2017-02-26 14:01:35</td>\n",
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       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-07 16:00:05</td>\n",
       "      <td>2017-02-12 16:15:07</td>\n",
       "      <td>2017-02-26 16:21:36</td>\n",
       "      <td>2017-02-26 16:21:36</td>\n",
       "      <td>21771</td>\n",
       "      <td>14193439</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>7.045509e-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317696</th>\n",
       "      <td>2358271</td>\n",
       "      <td>24522</td>\n",
       "      <td>127784247269485_1208121299235769</td>\n",
       "      <td>Like a Lord</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-17 10:30:00</td>\n",
       "      <td>2017-02-17 18:38:09</td>\n",
       "      <td>2017-02-26 16:27:36</td>\n",
       "      <td>2017-02-26 16:27:36</td>\n",
       "      <td>24522</td>\n",
       "      <td>876148</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000019</td>\n",
       "      <td>1.141360e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317697</th>\n",
       "      <td>1637887</td>\n",
       "      <td>17047</td>\n",
       "      <td>108237029260557_1237793119638270</td>\n",
       "      <td>TV8</td>\n",
       "      <td>0</td>\n",
       "      <td>47</td>\n",
       "      <td>750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-18 16:40:08</td>\n",
       "      <td>2017-02-24 21:22:01</td>\n",
       "      <td>2017-02-26 16:11:16</td>\n",
       "      <td>2017-02-26 16:11:16</td>\n",
       "      <td>17047</td>\n",
       "      <td>792533</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000946</td>\n",
       "      <td>5.930352e-05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>317698 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             id  page_id                        facebook_id  \\\n",
       "0        177964     1885   142474049098533_1474788722533719   \n",
       "1       1940645    20163     131180673952_10155037642073953   \n",
       "2        645038     6729      52107727250_10154120507997251   \n",
       "3        269158     2860       9124187907_10155660939257908   \n",
       "4        269195     2860       9124187907_10155626886227908   \n",
       "5        269214     2860       9124187907_10155614787412908   \n",
       "6       2805234    29142   165205036869225_1380796198643430   \n",
       "7        269235     2860       9124187907_10155597953617908   \n",
       "8       1472865    15354  1371996966150726_1582954265054994   \n",
       "9        661976     6901   332968243416537_1398127326900618   \n",
       "10       267907     2847    199870617084581_214145832323726   \n",
       "11      2202482    22890   104438892938868_1395905253792219   \n",
       "12       269148     2860       9124187907_10155667100922908   \n",
       "13      2601628    27035   110177082404435_1265112300244235   \n",
       "14      2532554    26319   997108126967413_1509679769043577   \n",
       "15      2678567    27831   169528479736063_1357156890973210   \n",
       "16        71088      790       5281959998_10151094045534999   \n",
       "17        40629      470   346937065399354_1439187546174295   \n",
       "18      2438596    25361   131201286936061_1390301541026023   \n",
       "19      1926916    20021   111415578911214_1867516903301064   \n",
       "20        39376      458      24085780715_10158181697205716   \n",
       "21       161407     1716   367116489976035_1649023648451973   \n",
       "22      2601024    27029  1742306959430702_1746046362390095   \n",
       "23       269224     2860       9124187907_10155605794117908   \n",
       "24      1263129     3566     208421665712_10158551640350713   \n",
       "25      2532480    26319   997108126967413_1522487217762832   \n",
       "26        41724      482       5550296508_10156134811176509   \n",
       "27       161361     1716   367116489976035_1658198047534533   \n",
       "28      2438574    25361   131201286936061_1406133962776114   \n",
       "29       269145     2860       9124187907_10155670306072908   \n",
       "...         ...      ...                                ...   \n",
       "317668  2807039    29160     316449433298_10154517397403299   \n",
       "317669   120319     1297       6654472378_10154379232217379   \n",
       "317670    55039      620   632729473453216_1331043880288435   \n",
       "317671  1956095    20321   147384458624178_1562946923734584   \n",
       "317672  2414847    25114    251934468302503_772753476220597   \n",
       "317673   121855     1312     252062638385_10154559744913386   \n",
       "317674   449535     4729       8684858250_10154443986778251   \n",
       "317675  2153471    22374     168619349359_10154978151134360   \n",
       "317676  2153727    22376   157671354275436_1488857234490168   \n",
       "317677  1826559    18984   159163487447469_1447022521994886   \n",
       "317678  2154239    22382   270813539617588_1426211830744414   \n",
       "317679  2285311    23751      68463351073_10154296078011074   \n",
       "317680  2350847    24444   145019618847447_1643076752375052   \n",
       "317681  1827327    18992      36841737921_10155151180622922   \n",
       "317682   320255     3390   310387089028039_1349644481768956   \n",
       "317683   255231     2716      27124644923_10155116134784924   \n",
       "317684  2483711    25824      60265161373_10154538703786374   \n",
       "317685  2222335    23091      50842855867_10154234591625868   \n",
       "317686  1960447    20368      57356766562_10155040253031563   \n",
       "317687  2223103    23099   210152225666581_1663647563650366   \n",
       "317688  1765887    18360   196329073799810_1184851578280883   \n",
       "317689   455423     4789      56969128673_10155033242658674   \n",
       "317690  1438975    14988   176835515721658_1383679228370608   \n",
       "317691  2749695    28564    150458898489106_620828468118811   \n",
       "317692  2554111    26542      81592120902_10154917001160903   \n",
       "317693   260607     2772     168926019255_10155730437064256   \n",
       "317694   588287     6154   122147017804101_1414935258525264   \n",
       "317695  2095615    21771      54394619188_10155092938129189   \n",
       "317696  2358271    24522   127784247269485_1208121299235769   \n",
       "317697  1637887    17047   108237029260557_1237793119638270   \n",
       "\n",
       "                                                     name   share  comment  \\\n",
       "0       Boeing's 787 Dreamliner Is Made Of Parts From ...  110196    10514   \n",
       "1       Papa sugere que é “melhor ser ateu do que cató...   96104     3426   \n",
       "2       Fallece Pablo Ráez tras una lucha titánica con...   92376     5999   \n",
       "3       House bill would scale back number of free sch...   90349     9684   \n",
       "4       Dakota Access Pipeline Approved a Week After C...   86984     4644   \n",
       "5       After Trump moves to undo financial regulation...   74276     9754   \n",
       "6       Prefeito destina verba que seria do Carnaval p...   71010     4150   \n",
       "7       After meeting with pharma lobbyists, Trump dro...   69586    10346   \n",
       "8       People Want To Shoot Hibernating Bear Families...   65809     1272   \n",
       "9       REPORT: Aaron Hernandez Says He Too Will Skip ...   61975     3791   \n",
       "10      Republicans begin effort to gut the Endangered...   61145     4824   \n",
       "11      La televisión italiana difunde el drama argent...   57748      827   \n",
       "12      The Trump administration just handed the priva...   56783     5552   \n",
       "13      El mismo juzgado que ha absuelto a la infanta ...   55405     1394   \n",
       "14      Big Pharma Finally Admits Cannabis Kills Cance...   54969     2612   \n",
       "15           Robert Englund Back for One Last Freddy Film   54699     3737   \n",
       "16      White House Bars Times and 2 Other News Outlet...   51022     8454   \n",
       "17      Militarized Police Just Evicted The Sioux Trib...   50985     4854   \n",
       "18      News from The Associated Press: \"Doomsday Cloc...   49870    10389   \n",
       "19      ¡Compartan! Les revelo la increíble fórmula pa...   49771      993   \n",
       "20      The mysterious disappearance of the biggest sc...   49287     5608   \n",
       "21      Republicans Launch Attempt To Repeal Endangere...   48292     5382   \n",
       "22      House Moves to Encourage Drilling in National ...   47070     3371   \n",
       "23      Trump Vows to ‘Destroy’ Law Banning Political ...   46326    10290   \n",
       "24                                 Bill Paxton Dead at 61   46208     3528   \n",
       "25      This MAN Healed 5000 People from Cancer: This ...   45983     2063   \n",
       "26      White House blocks news organizations from pre...   45764    15119   \n",
       "27      Breakthrough In Search For Life As Seven Earth...   45659     4261   \n",
       "28      Trump won't immediately appeal travel ban halt...   45581     7023   \n",
       "29      Republican lawmakers introduce bills to curb p...   45461     5624   \n",
       "...                                                   ...     ...      ...   \n",
       "317668    TEMPO REAL: Mirassol vs Corinthians - Paulistão       0        4   \n",
       "317669  Romantic place names from around the world | S...       0        0   \n",
       "317670                                          Blumhouse       0        0   \n",
       "317671                                  Sunday Times Food       0        2   \n",
       "317672  Eva Herzigova flaunts her age-defying beauty a...       0        4   \n",
       "317673  Jim Cantore (@JimCantore) posted a photo on Tw...       0        3   \n",
       "317674                                          Nova 96.9       0        4   \n",
       "317675  Ayesha Takia on makeover: Some vicious people ...       0        2   \n",
       "317676  Live in green neighbourhood to cut depression,...       0        0   \n",
       "317677  Sydney go 11 clear with City A-League romp - F...       0        0   \n",
       "317678    Fichardt wins Joburg Open with last-hole birdie       0        0   \n",
       "317679                     Los últimos serán los primeros       0        0   \n",
       "317680  Video:  Dating-Portal deckt auf - So sieht für...       0        0   \n",
       "317681                        Sydney Comedy Festival 2017       0        0   \n",
       "317682  Riverdales Trevor Stines Wants In On a Certain...       0        7   \n",
       "317683  Who Made the Cut? James Wrights Sets the Crew ...       0        2   \n",
       "317684                                             gph.is       0        0   \n",
       "317685  Óscar Ibáñez es el nuevo técnico de Comerciant...       0        2   \n",
       "317686  All the It Girls Are Embracing This \"Faux Pas\"...       0        1   \n",
       "317687                GANA UN DESAYUNO GRATIS DE KeBurros       0        0   \n",
       "317688  Receita: ovos gratinados são opção delícia par...       0        0   \n",
       "317689  Scientists Warn Parents To Keep Children Away ...       0        0   \n",
       "317690                      Dark and Purple by Jennifer E       0        0   \n",
       "317691                                          YRF Music       0        3   \n",
       "317692                                           ABP Live       0        1   \n",
       "317693  A Romantic Valentine's Day Dinner for 2 That's...       0        3   \n",
       "317694  Jessa Duggar's New Baby Henry Is So Cute, We C...       0        0   \n",
       "317695                                          giphy.com       0        1   \n",
       "317696                                        Like a Lord       0        1   \n",
       "317697                                                TV8       0       47   \n",
       "\n",
       "          like  love     haha     wow      ...       source  \\\n",
       "0       114884   NaN      NaN  9105.0      ...          NaN   \n",
       "1        86598   NaN   2352.0     NaN      ...          NaN   \n",
       "2         3824   NaN      NaN  1034.0      ...          NaN   \n",
       "3        39706   NaN    156.0     NaN      ...          NaN   \n",
       "4        63378   NaN    251.0     NaN      ...          NaN   \n",
       "5       239914   NaN    743.0     NaN      ...          NaN   \n",
       "6       163415   NaN    276.0     NaN      ...          NaN   \n",
       "7        76792   NaN   1309.0     NaN      ...          NaN   \n",
       "8         1603   NaN      9.0     NaN      ...          NaN   \n",
       "9        40526   NaN  22322.0     NaN      ...          NaN   \n",
       "10        2907   NaN     26.0     NaN      ...          NaN   \n",
       "11       20158   NaN     25.0     NaN      ...          NaN   \n",
       "12       42038   NaN    162.0     NaN      ...          NaN   \n",
       "13        3860   NaN    530.0     NaN      ...          NaN   \n",
       "14       88968   NaN    364.0     NaN      ...          NaN   \n",
       "15       59160   NaN    127.0     NaN      ...          NaN   \n",
       "16        9038   NaN    882.0     NaN      ...          NaN   \n",
       "17        6613   NaN     98.0     NaN      ...          NaN   \n",
       "18      112315   NaN   1295.0     NaN      ...          NaN   \n",
       "19       26835   NaN     87.0     NaN      ...          NaN   \n",
       "20       66793   NaN    118.0     NaN      ...          NaN   \n",
       "21       12554   NaN    368.0     NaN      ...          NaN   \n",
       "22       13759   NaN     24.0     NaN      ...          NaN   \n",
       "23       72385   NaN    403.0     NaN      ...          NaN   \n",
       "24        5224   NaN     47.0     NaN      ...          NaN   \n",
       "25       55254   NaN     80.0     NaN      ...          NaN   \n",
       "26       13356   NaN   4232.0     NaN      ...          NaN   \n",
       "27      120886   NaN    167.0     NaN      ...          NaN   \n",
       "28       98154   NaN     54.0     NaN      ...          NaN   \n",
       "29       63092   NaN    249.0     NaN      ...          NaN   \n",
       "...        ...   ...      ...     ...      ...          ...   \n",
       "317668     138   NaN      0.0     NaN      ...          NaN   \n",
       "317669       0   NaN      0.0     NaN      ...          NaN   \n",
       "317670       5   NaN      NaN     0.0      ...          NaN   \n",
       "317671       9   NaN      0.0     NaN      ...          NaN   \n",
       "317672      49   NaN      0.0     NaN      ...          NaN   \n",
       "317673      30   NaN      NaN    11.0      ...          NaN   \n",
       "317674      10   NaN      0.0     NaN      ...          NaN   \n",
       "317675     248   NaN      1.0     NaN      ...          NaN   \n",
       "317676      18   NaN      0.0     NaN      ...          NaN   \n",
       "317677       7   NaN      0.0     NaN      ...          NaN   \n",
       "317678      18   NaN      0.0     NaN      ...          NaN   \n",
       "317679      11   NaN      0.0     NaN      ...          NaN   \n",
       "317680       3   NaN      0.0     NaN      ...          NaN   \n",
       "317681       3   NaN      0.0     NaN      ...          NaN   \n",
       "317682       5   NaN      NaN     0.0      ...          NaN   \n",
       "317683      34   NaN      NaN     0.0      ...          NaN   \n",
       "317684      24   NaN      0.0     NaN      ...          NaN   \n",
       "317685      40   NaN      2.0     NaN      ...          NaN   \n",
       "317686      15   NaN      0.0     NaN      ...          NaN   \n",
       "317687       0   NaN      0.0     NaN      ...          NaN   \n",
       "317688      10   NaN      0.0     NaN      ...          NaN   \n",
       "317689       4   NaN      NaN     0.0      ...          NaN   \n",
       "317690       6   NaN      0.0     NaN      ...          NaN   \n",
       "317691      31   NaN      0.0     NaN      ...          NaN   \n",
       "317692     206   NaN      2.0     NaN      ...          NaN   \n",
       "317693      16   NaN      NaN     0.0      ...          NaN   \n",
       "317694      25   NaN      NaN     1.0      ...          NaN   \n",
       "317695      95   NaN      1.0     NaN      ...          NaN   \n",
       "317696      17   NaN      0.0     NaN      ...          NaN   \n",
       "317697     750   NaN     52.0     NaN      ...          NaN   \n",
       "\n",
       "               created_time         updated_time            createdAt  \\\n",
       "0       2017-02-17 19:28:36  2017-02-25 22:51:41  2017-02-26 12:49:55   \n",
       "1       2017-02-26 08:59:00  2017-02-26 16:15:01  2017-02-26 16:18:01   \n",
       "2       2017-02-25 18:11:45  2017-02-26 14:09:17  2017-02-26 14:11:12   \n",
       "3       2017-02-21 18:47:41  2017-02-26 11:49:56  2017-02-26 13:06:18   \n",
       "4       2017-02-10 21:51:23  2017-02-22 21:52:41  2017-02-26 13:06:18   \n",
       "5       2017-02-06 15:25:21  2017-02-22 16:26:19  2017-02-26 13:06:18   \n",
       "6       2017-02-22 18:00:34  2017-02-26 16:07:07  2017-02-26 16:39:00   \n",
       "7       2017-01-31 22:33:22  2017-02-23 18:58:51  2017-02-26 13:06:18   \n",
       "8       2017-02-17 18:43:00  2017-02-23 01:10:50  2017-02-26 16:07:38   \n",
       "9       2017-02-10 03:12:57  2017-02-22 13:03:33  2017-02-26 14:14:05   \n",
       "10      2017-02-16 14:05:00  2017-02-25 13:27:59  2017-02-26 13:06:04   \n",
       "11      2017-02-25 00:02:00  2017-02-26 16:19:35  2017-02-26 16:24:04   \n",
       "12      2017-02-24 01:45:06  2017-02-26 12:31:59  2017-02-26 13:06:18   \n",
       "13      2017-02-17 18:46:56  2017-02-23 23:36:20  2017-02-26 16:33:07   \n",
       "14      2017-02-12 22:31:47  2017-02-21 04:37:39  2017-02-26 16:31:31   \n",
       "15      2017-02-01 22:50:40  2017-02-10 23:57:22  2017-02-26 16:36:12   \n",
       "16      2017-02-24 19:33:08  2017-02-26 12:26:14  2017-02-26 12:31:32   \n",
       "17      2017-02-23 19:50:00  2017-02-26 10:42:58  2017-02-26 12:26:10   \n",
       "18      2017-01-28 11:45:00  2017-02-24 12:33:20  2017-02-26 16:29:26   \n",
       "19      2017-02-14 01:30:07  2017-02-21 16:51:56  2017-02-26 16:17:42   \n",
       "20      2017-02-09 16:53:01  2017-02-24 19:23:44  2017-02-26 12:25:58   \n",
       "21      2017-02-15 22:15:26  2017-02-23 06:57:40  2017-02-26 12:47:05   \n",
       "22      2017-02-01 03:04:34  2017-02-08 02:05:29  2017-02-26 16:33:07   \n",
       "23      2017-02-03 18:05:00  2017-02-25 17:58:57  2017-02-26 13:06:18   \n",
       "24      2017-02-26 15:19:50  2017-02-26 16:02:43  2017-02-26 16:02:45   \n",
       "25      2017-02-24 19:13:29  2017-02-26 16:20:36  2017-02-26 16:31:31   \n",
       "26      2017-02-24 19:25:36  2017-02-26 12:25:12  2017-02-26 12:26:22   \n",
       "27      2017-02-22 18:08:46  2017-02-25 22:57:23  2017-02-26 12:47:05   \n",
       "28      2017-02-11 21:28:20  2017-02-26 12:53:53  2017-02-26 16:29:26   \n",
       "29      2017-02-25 01:57:46  2017-02-26 13:05:31  2017-02-26 13:06:18   \n",
       "...                     ...                  ...                  ...   \n",
       "317668  2017-02-25 22:01:01  2017-02-26 02:04:46  2017-02-26 16:39:03   \n",
       "317669  2017-02-14 15:38:00  2017-02-14 15:38:00  2017-02-26 12:40:02   \n",
       "317670  2017-02-16 21:33:01  2017-02-16 21:33:01  2017-02-26 12:28:41   \n",
       "317671  2017-02-23 11:50:25  2017-02-26 13:02:57  2017-02-26 16:18:21   \n",
       "317672  2017-02-26 13:00:16  2017-02-26 13:28:58  2017-02-26 16:29:03   \n",
       "317673  2017-02-16 18:49:32  2017-02-17 06:07:30  2017-02-26 12:40:17   \n",
       "317674  2017-02-16 07:48:32  2017-02-16 12:49:26  2017-02-26 13:37:40   \n",
       "317675  2017-02-26 04:46:46  2017-02-26 06:04:06  2017-02-26 16:22:56   \n",
       "317676  2017-02-26 06:26:00  2017-02-26 06:26:00  2017-02-26 16:22:57   \n",
       "317677  2017-02-24 21:19:00  2017-02-24 21:19:00  2017-02-26 16:15:28   \n",
       "317678  2017-02-26 15:54:35  2017-02-26 15:54:35  2017-02-26 16:22:57   \n",
       "317679  2017-02-25 19:00:02  2017-02-25 19:00:02  2017-02-26 16:25:56   \n",
       "317680  2017-02-26 12:33:00  2017-02-26 12:33:00  2017-02-26 16:27:26   \n",
       "317681  2017-02-22 01:30:02  2017-02-22 01:30:02  2017-02-26 16:15:29   \n",
       "317682  2017-02-20 15:00:04  2017-02-21 18:38:50  2017-02-26 13:15:13   \n",
       "317683  2017-02-07 19:00:00  2017-02-09 22:00:24  2017-02-26 13:03:53   \n",
       "317684  2017-02-26 03:14:00  2017-02-26 03:14:00  2017-02-26 16:30:27   \n",
       "317685  2017-02-26 04:38:21  2017-02-26 04:59:34  2017-02-26 16:24:30   \n",
       "317686  2017-02-25 03:00:00  2017-02-25 03:00:00  2017-02-26 16:18:28   \n",
       "317687  2017-02-24 17:26:29  2017-02-24 17:26:29  2017-02-26 16:24:31   \n",
       "317688  2017-02-26 00:00:02  2017-02-26 00:00:02  2017-02-26 16:14:06   \n",
       "317689  2017-02-25 14:44:24  2017-02-25 14:44:24  2017-02-26 13:38:41   \n",
       "317690  2017-02-23 21:00:02  2017-02-23 21:00:02  2017-02-26 16:06:50   \n",
       "317691  2017-02-09 07:48:51  2017-02-13 14:49:38  2017-02-26 16:37:46   \n",
       "317692  2017-02-24 12:23:39  2017-02-25 13:26:29  2017-02-26 16:32:00   \n",
       "317693  2017-02-12 06:04:50  2017-02-13 03:30:06  2017-02-26 13:04:49   \n",
       "317694  2017-02-20 13:09:24  2017-02-20 13:09:24  2017-02-26 14:01:35   \n",
       "317695  2017-02-07 16:00:05  2017-02-12 16:15:07  2017-02-26 16:21:36   \n",
       "317696  2017-02-17 10:30:00  2017-02-17 18:38:09  2017-02-26 16:27:36   \n",
       "317697  2017-02-18 16:40:08  2017-02-24 21:22:01  2017-02-26 16:11:16   \n",
       "\n",
       "                  updatedAt   id.1 fan_count share_ratio like_ratio  \\\n",
       "0       2017-02-26 12:49:55   1885   2096549    0.052561   0.054797   \n",
       "1       2017-02-26 16:18:01  20163   4035108    0.023817   0.021461   \n",
       "2       2017-02-26 14:11:12   6729    239639    0.385480   0.015957   \n",
       "3       2017-02-26 13:06:18   2860   6684171    0.013517   0.005940   \n",
       "4       2017-02-26 13:06:18   2860   6684171    0.013013   0.009482   \n",
       "5       2017-02-26 13:06:18   2860   6684171    0.011112   0.035893   \n",
       "6       2017-02-26 16:39:00  29142   6745116    0.010528   0.024227   \n",
       "7       2017-02-26 13:06:18   2860   6684171    0.010411   0.011489   \n",
       "8       2017-02-26 16:07:38  15354   1177625    0.055883   0.001361   \n",
       "9       2017-02-26 14:14:05   6901   2793744    0.022183   0.014506   \n",
       "10      2017-02-26 13:06:04   2847   1101432    0.055514   0.002639   \n",
       "11      2017-02-26 16:24:04  22890  16633846    0.003472   0.001212   \n",
       "12      2017-02-26 13:06:18   2860   6684171    0.008495   0.006289   \n",
       "13      2017-02-26 16:33:07  27035    871655    0.063563   0.004428   \n",
       "14      2017-02-26 16:31:31  26319   6885736    0.007983   0.012921   \n",
       "15      2017-02-26 16:36:12  27831    667995    0.081885   0.088564   \n",
       "16      2017-02-26 12:31:32    790  13464157    0.003789   0.000671   \n",
       "17      2017-02-26 12:26:10    470   5915082    0.008619   0.001118   \n",
       "18      2017-02-26 16:29:26  25361   5403968    0.009228   0.020784   \n",
       "19      2017-02-26 16:17:42  20021   8699306    0.005721   0.003085   \n",
       "20      2017-02-26 12:25:58    458   1908514    0.025825   0.034997   \n",
       "21      2017-02-26 12:47:05   1716  25581111    0.001888   0.000491   \n",
       "22      2017-02-26 16:33:07  27029   1434940    0.032803   0.009589   \n",
       "23      2017-02-26 13:06:18   2860   6684171    0.006931   0.010829   \n",
       "24      2017-02-26 16:02:45   3566   6902151    0.006695   0.000757   \n",
       "25      2017-02-26 16:31:31  26319   6885736    0.006678   0.008024   \n",
       "26      2017-02-26 12:26:22    482  26716165    0.001713   0.000500   \n",
       "27      2017-02-26 12:47:05   1716  25581111    0.001785   0.004726   \n",
       "28      2017-02-26 16:29:26  25361   5403968    0.008435   0.018163   \n",
       "29      2017-02-26 13:06:18   2860   6684171    0.006801   0.009439   \n",
       "...                     ...    ...       ...         ...        ...   \n",
       "317668  2017-02-26 16:39:03  29160    998597    0.000000   0.000138   \n",
       "317669  2017-02-26 12:40:02   1297   1210743    0.000000   0.000000   \n",
       "317670  2017-02-26 12:28:41    620    455125    0.000000   0.000011   \n",
       "317671  2017-02-26 16:18:21  20321    608617    0.000000   0.000015   \n",
       "317672  2017-02-26 16:29:03  25114   1015465    0.000000   0.000048   \n",
       "317673  2017-02-26 12:40:17   1312    261084    0.000000   0.000115   \n",
       "317674  2017-02-26 13:37:40   4729    957151    0.000000   0.000010   \n",
       "317675  2017-02-26 16:22:56  22374   2464533    0.000000   0.000101   \n",
       "317676  2017-02-26 16:22:57  22376   1427983    0.000000   0.000013   \n",
       "317677  2017-02-26 16:15:28  18984    702450    0.000000   0.000010   \n",
       "317678  2017-02-26 16:22:57  22382   1482682    0.000000   0.000012   \n",
       "317679  2017-02-26 16:25:56  23751   1657326    0.000000   0.000007   \n",
       "317680  2017-02-26 16:27:26  24444    710181    0.000000   0.000004   \n",
       "317681  2017-02-26 16:15:29  18992    660576    0.000000   0.000005   \n",
       "317682  2017-02-26 13:15:13   3390    229782    0.000000   0.000022   \n",
       "317683  2017-02-26 13:03:53   2716    442470    0.000000   0.000077   \n",
       "317684  2017-02-26 16:30:27  25824   3542032    0.000000   0.000007   \n",
       "317685  2017-02-26 16:24:30  23091    838039    0.000000   0.000048   \n",
       "317686  2017-02-26 16:18:28  20368   1978250    0.000000   0.000008   \n",
       "317687  2017-02-26 16:24:31  23099    637499    0.000000   0.000000   \n",
       "317688  2017-02-26 16:14:06  18360    576546    0.000000   0.000017   \n",
       "317689  2017-02-26 13:38:41   4789    384580    0.000000   0.000010   \n",
       "317690  2017-02-26 16:06:50  14988   1702744    0.000000   0.000004   \n",
       "317691  2017-02-26 16:37:46  28564   1113958    0.000000   0.000028   \n",
       "317692  2017-02-26 16:32:00  26542    959177    0.000000   0.000215   \n",
       "317693  2017-02-26 13:04:49   2772    240909    0.000000   0.000066   \n",
       "317694  2017-02-26 14:01:35   6154   1467173    0.000000   0.000017   \n",
       "317695  2017-02-26 16:21:36  21771  14193439    0.000000   0.000007   \n",
       "317696  2017-02-26 16:27:36  24522    876148    0.000000   0.000019   \n",
       "317697  2017-02-26 16:11:16  17047    792533    0.000000   0.000946   \n",
       "\n",
       "       comment_ratio  \n",
       "0       5.014908e-03  \n",
       "1       8.490479e-04  \n",
       "2       2.503349e-02  \n",
       "3       1.448796e-03  \n",
       "4       6.947758e-04  \n",
       "5       1.459268e-03  \n",
       "6       6.152600e-04  \n",
       "7       1.547836e-03  \n",
       "8       1.080140e-03  \n",
       "9       1.356960e-03  \n",
       "10      4.379753e-03  \n",
       "11      4.971791e-05  \n",
       "12      8.306191e-04  \n",
       "13      1.599257e-03  \n",
       "14      3.793349e-04  \n",
       "15      5.594353e-03  \n",
       "16      6.278893e-04  \n",
       "17      8.206142e-04  \n",
       "18      1.922476e-03  \n",
       "19      1.141470e-04  \n",
       "20      2.938412e-03  \n",
       "21      2.103896e-04  \n",
       "22      2.349227e-03  \n",
       "23      1.539458e-03  \n",
       "24      5.111450e-04  \n",
       "25      2.996049e-04  \n",
       "26      5.659121e-04  \n",
       "27      1.665682e-04  \n",
       "28      1.299601e-03  \n",
       "29      8.413908e-04  \n",
       "...              ...  \n",
       "317668  4.005620e-06  \n",
       "317669  0.000000e+00  \n",
       "317670  0.000000e+00  \n",
       "317671  3.286139e-06  \n",
       "317672  3.939082e-06  \n",
       "317673  1.149055e-05  \n",
       "317674  4.179069e-06  \n",
       "317675  8.115128e-07  \n",
       "317676  0.000000e+00  \n",
       "317677  0.000000e+00  \n",
       "317678  0.000000e+00  \n",
       "317679  0.000000e+00  \n",
       "317680  0.000000e+00  \n",
       "317681  0.000000e+00  \n",
       "317682  3.046366e-05  \n",
       "317683  4.520080e-06  \n",
       "317684  0.000000e+00  \n",
       "317685  2.386524e-06  \n",
       "317686  5.054973e-07  \n",
       "317687  0.000000e+00  \n",
       "317688  0.000000e+00  \n",
       "317689  0.000000e+00  \n",
       "317690  0.000000e+00  \n",
       "317691  2.693100e-06  \n",
       "317692  1.042560e-06  \n",
       "317693  1.245283e-05  \n",
       "317694  0.000000e+00  \n",
       "317695  7.045509e-08  \n",
       "317696  1.141360e-06  \n",
       "317697  5.930352e-05  \n",
       "\n",
       "[317698 rows x 30 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "posts['share_ratio'] = posts['share'] / posts['fan_count']\n",
    "posts['like_ratio'] = posts['like'] / posts['fan_count']\n",
    "posts['comment_ratio'] = posts['comment'] / posts['fan_count']\n",
    "posts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from numpy.random import normal\n",
    "\n",
    "x = np.linspace(0.0000001, 0.0002, 1000)\n",
    "plt.hist(posts['share_ratio'], bins=x)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "x = np.linspace(0.0000001, 0.002, 1000)\n",
    "plt.hist(posts['like_ratio'], bins=x)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "x = np.linspace(0.0000001, 0.0002, 1000)\n",
    "plt.hist(posts['comment_ratio'], bins=x)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(317698, 30)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "link_posts = posts[posts['type'] == 'link']\n",
    "link_posts.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import langid\n",
    "\n",
    "def isEng(x):\n",
    "    try:\n",
    "        return langid.classify(x['message'])[0] == 'en'\n",
    "    except:\n",
    "        try:\n",
    "            return detect(x['description'])[0] == 'en'\n",
    "        except:\n",
    "            try:\n",
    "                return detect(x['name'])[0] == 'en'\n",
    "            except:\n",
    "                return False\n",
    "    \n",
    "\n",
    "eng_link_posts = link_posts[link_posts.apply(isEng, axis=1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'I just watched Trump give a speech at South Carolina\\'s Boeing facility where the new 787 “Dreamliner\" is being unveiled. Trump said it was “built right here” in South Carolina, and that “our goal as a nation must be to rely less on imports and more on products made here in the U.S.A.\" \\n\\nHe also called for \"a very substantial penalty to be paid when they fire their people and move to another country, make the product, and think that they are going to sell it back.” And said he\\'ll lower taxes and get rid of regulations that send our jobs to those other countries. \"We want products made by our workers in our factories stamped by those four magnificent words, \\'Made in the U.S.A.\\'\"\\n\\nAll fantasy. In fact, almost a third of Boeing’s Dreamliner comes from abroad -- from countries with high taxes and high regulations, good wages, strong unions, excellent schools including technical education, and universally-available health care. \\n\\n1.The Italian firm Alenia Aeronautica makes the center fuselage. \\n\\n2. French firm Messier-Dowty makes the aircraft\\'s landing-gear system.\\n\\n3. German firm Diehl Luftfahrt Elektronik supplies the main cabin lighting. \\n\\n4. Swedish firm Saab Aerostructures manufactures the access doors.\\n\\n5. Japanese company Jamco makes parts for the lavatories, flight deck interiors and galleys. \\n\\n6. French firm Thales makes its electrical power conversion system. \\n\\n7. Thales selected GS Yuasa, a Japanese firm, in 2005 to supply it with the system\\'s lithium-ion batteries. \\n\\nOh, and the first delivery of the Dreamliner is scheduled to take place next year – to Singapore Airlines. Currently there are 149 orders for it from worldwide customers including British Airways and Air France. \\n\\nIn other words, contrary to Trump, the Boeing Dreamliner is made all over the world and will be sold all over the world. \\n\\nHis \"America First\" economics is total demagoguery. We get a first-class workforce by investing in their education, training, infrastructure, and healthcare -- not xenophobic grandstanding. \\n\\nWhat do you think?'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eng_link_posts.shape\n",
    "backup = eng_link_posts\n",
    "data = eng_link_posts\n",
    "eng_link_posts.iloc[0]['message']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from langdetect import detect\n",
    "\n",
    "def isEng(x):\n",
    "    try:\n",
    "        return detect(x['message']) == 'en'\n",
    "    except:\n",
    "        try:\n",
    "            return detect(x['description']) == 'en'\n",
    "        except:\n",
    "            try:\n",
    "                return detect(x['name']) == 'en'\n",
    "            except:\n",
    "                return False\n",
    "\n",
    "eng_link_posts = link_posts[link_posts.apply(isEng, axis=1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import csv\n",
    "eng_link_posts.to_csv('/Users/Shared/fb/eng_link_posts.csv', doublequote=False, quotechar='\"', escapechar='\\\\')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "test = pd.read_csv('/Users/Shared/fb/eng_link_posts.csv', nrows=10000, error_bad_lines=False, doublequote=False, quotechar='\"', escapechar='\\\\')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "eng_link_posts[['name']].to_csv('/Users/Shared/fb/eng_link_posts_name.csv', index=False, header=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "eng_link_posts['data'] = eng_link_posts['name'].astype(str)\n",
    "eng_link_posts['share_ratio'].describe()\n",
    "eng_link_posts['good'] = eng_link_posts['share_ratio'].apply(lambda x: 1 if x >= 0.0001 else 0)\n",
    "eng_link_posts['good'].describe()\n",
    "data = eng_link_posts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from codeDump.testHeadline import tokenize\n",
    "tokenize(data['data'])\n",
    "#test_data(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# train word vector by fasttext"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data = eng_link_posts[['like', 'facebook_id', 'name', 'like_ratio']]\n",
    "data['like_ratio'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data['good'] = data['like_ratio'].apply(lambda x: 1 if x > 0.0005 else 0)\n",
    "data['good'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data[\"name\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from keras.preprocessing.text import Tokenizer\n",
    "from keras.preprocessing.sequence import pad_sequences\n",
    "\n",
    "data[\"name\"] = data[\"name\"].astype('str')\n",
    "\n",
    "tokenizer = Tokenizer()\n",
    "tokenizer.fit_on_texts(data[\"name\"])\n",
    "word_index = tokenizer.word_index\n",
    "print('Found %s unique tokens.' % len(word_index))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "\n",
    "embeddings_index = {}\n",
    "f = open(os.path.join('/Users/Shared/fb/eng_link_posts_name_model.vec'))\n",
    "for line in f:\n",
    "    values = line.split()\n",
    "    word = values[0]\n",
    "    coefs = np.asarray(values[1:], dtype='float32')\n",
    "    embeddings_index[word] = coefs\n",
    "f.close()\n",
    "\n",
    "print('Found %s word vectors.' % len(embeddings_index))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "EMBEDDING_DIM = 100\n",
    "\n",
    "embedding_matrix = np.zeros((len(word_index) + 1, EMBEDDING_DIM))\n",
    "for word, i in word_index.items():\n",
    "    embedding_vector = embeddings_index.get(word)\n",
    "    if embedding_vector is not None:\n",
    "        # words not found in embedding index will be all-zeros.\n",
    "        embedding_matrix[i] = embedding_vector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def prepareData(df):    \n",
    "    good = df[df[\"good\"] == 1]\n",
    "    bad = df[df[\"good\"] == 0]\n",
    "    bad = bad.sample(n=good.shape[0])\n",
    "    data = good.append(bad)\n",
    "    data = data.sample(frac=1).reset_index(drop=True)\n",
    "    \n",
    "    y_train = np.zeros((data.shape[0], 2), dtype=int)\n",
    "    for i in range(0, data.shape[0]):\n",
    "        y_train[i, 1] = 1 if data.iloc[i]['good'] == 1 else 0\n",
    "        y_train[i, 0] = 1 if data.iloc[i]['good'] == 0 else 0\n",
    "        \n",
    "    sequences = tokenizer.texts_to_sequences(data[\"name\"])\n",
    "    x_train = pad_sequences(sequences, maxlen=25)\n",
    "\n",
    "    return x_train, y_train, data['good'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "x_full, y_full, y2_full = prepareData(eng_link_posts)\n",
    "x_train, y_train, y2_train = prepareData(train)\n",
    "x_test, y_test, y2_test = prepareData(test)\n",
    "\n",
    "print(y2_full)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.metrics import precision_score, recall_score\n",
    "\n",
    "def validate(model, x_test, y_test):\n",
    "    test_truth = np.apply_along_axis(lambda x: np.argmax(x), 1, y_test)\n",
    "    test_pred = model.predict(x_test)\n",
    "    test_pred = np.apply_along_axis(lambda x: np.argmax(x), 1, test_pred)\n",
    "    precision = precision_score(test_truth, test_pred)\n",
    "    recall = recall_score(test_truth, test_pred)\n",
    "    print(precision)\n",
    "    print(recall)\n",
    "    return precision, recall\n",
    "\n",
    "def validate_2(truth, pred):\n",
    "    truth = np.apply_along_axis(lambda x: np.argmax(x), 1, truth)\n",
    "    pred = np.apply_along_axis(lambda x: np.argmax(x), 1, pred)\n",
    "    precision = precision_score(truth, pred)\n",
    "    recall = recall_score(truth, pred)\n",
    "    print(precision)\n",
    "    print(recall)\n",
    "    return precision, recall"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "rf = RandomForestClassifier(n_estimators=500, n_jobs=-1, criterion=\"entropy\", random_state=1)\n",
    "rf.fit(x_train, y2_train)\n",
    "\n",
    "res = rf.predict(x_test)\n",
    "\n",
    "#validate_2(y_test, res)\n",
    "precision = precision_score(y2_test, res)\n",
    "recall = recall_score(y2_test, res)\n",
    "print(precision)\n",
    "print(recall)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "origin = pd.read_csv('/Users/Shared/data/HN_posts_year_to_Sep_26_2016.csv')\n",
    "origin_1 = origin[['id', 'num_points']]\n",
    "data = pd.merge(title_vec, origin_1, how='inner', on=['id'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "origin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "'''\n",
    "sentence_length = pd.read_csv('sentence_length.csv', header=None, )\n",
    "sentence_length.rename(columns={0: 'id', 1:'length'}, inplace=True)\n",
    "data = pd.merge(data, sentence_length, how='inner', on=['id'])\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "GOOD_THRESHOLD = 10\n",
    "\n",
    "data['good'] = data['num_points'].apply(lambda x: 1 if x >= GOOD_THRESHOLD else 0)\n",
    "data['good'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data = data.drop(['id', 'num_points'], 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "train = data.sample(frac=0.8)\n",
    "test = data.drop(train.index)\n",
    "\n",
    "abnormal = data.loc[data['good'] == 1]\n",
    "abnormal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "m = train[list(range(0, 1200))].as_matrix()\n",
    "u, s, v = np.linalg.svd(m, full_matrices=False)\n",
    "plt.plot(s[0:400])\n",
    "plt.show()\n",
    "\n",
    "print(u.shape, s.shape, v.shape)\n",
    "print(m[0].shape, v.transpose().shape)\n",
    "\n",
    "transform = np.delete(v, range(2, v.shape[0]), 0)\n",
    "print(transform.shape)\n",
    "\n",
    "def reduce(vec):\n",
    "    return np.dot(vec, transform.transpose())\n",
    "\n",
    "def to_coor(matrix):\n",
    "    coor = np.apply_along_axis(reduce, 1, matrix).transpose()\n",
    "    print(matrix.shape, coor.shape)\n",
    "    return (coor[0], coor[1])\n",
    "    \n",
    "normal_x, normal_y = to_coor(m)\n",
    "\n",
    "m2 = abnormal[list(range(0,1200))].as_matrix()\n",
    "\n",
    "ab_x, ab_y = to_coor(m2)\n",
    "\n",
    "print(ab_x.shape)\n",
    "print(ab_y.shape)\n",
    "\n",
    "plt.scatter(normal_x, normal_y)\n",
    "plt.scatter(ab_x, ab_y, color = 'red')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "m2 = abnormal.as_matrix()\n",
    "u, s, v = np.linalg.svd(m2)\n",
    "plt.plot(s[0:400])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "origin['num_points']\n",
    "\n",
    "plot_data = origin[origin['num_points'] >= 0 ]['num_points'].values\n",
    "\n",
    "x = np.array(list(range(100, 1001)))\n",
    "y, x = np.histogram(plot_data, bins=x)\n",
    "x_bin = np.delete(x, 0)\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "plt.plot(x_bin, y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from scipy.optimize import curve_fit\n",
    "def func(x, a, b):\n",
    "    return a * np.exp(-b * x)\n",
    "\n",
    "xdata = x_bin\n",
    "ydata = y\n",
    "\n",
    "print(xdata.shape)\n",
    "print(ydata.shape)\n",
    "\n",
    "popt, pcov = curve_fit(func, xdata, ydata, p0=[0.0007, 0.0004])\n",
    "\n",
    "print(popt)\n",
    "print(pcov)\n",
    "plt.plot(x_bin, func(x_bin,*popt), color='g', linewidth=10)\n",
    "plt.plot(x_bin, y, color='r')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "from scipy.stats import expon\n",
    "loc, lamb = expon.fit(plot_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from numpy.random import normal\n",
    "\n",
    "plt.hist(plot_data, bins=x_bin)\n",
    "plt.plot(x_bin, func(x_bin,*popt), color='g', linewidth=3)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "a = np.array([1,2,3,4,5])\n",
    "a[(a>1) & (a<5)]=0\n",
    "a\n",
    "\n",
    "np.log(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Study double / triple exponential behaviour of the distribution\n",
    "\n",
    "x = np.linspace(0.0000001, 1, 100000)\n",
    "\n",
    "def log_tower(plot_data, k):\n",
    "    for i in range(0, k):\n",
    "        plot_data[plot_data < 1] = 1.\n",
    "        plot_data = np.log(plot_data)\n",
    "    #plot_data[plot_data < 1] = 0.\n",
    "    return plot_data\n",
    "\n",
    "ln_plot_data = log_tower(np.array(plot_data), 3)\n",
    "\n",
    "print(ln_plot_data.shape)\n",
    "\n",
    "y, x = np.histogram(ln_plot_data, bins=x)\n",
    "x_bin = np.delete(x, 0)\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "plt.plot(x_bin, y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Compute the elbow of exponential curve\n",
    "\n",
    "x = np.linspace(0, 100, 10000)\n",
    "y, x = np.histogram(plot_data, bins=x)\n",
    "x_bin = np.delete(x, 0)\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "plt.plot(x_bin, y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#1. Compute the derivative\n",
    "\n",
    "def derivative(np_array):\n",
    "    a = np.delete(np_array, len(np_array)-1)\n",
    "    b = np.delete(np_array, 0)\n",
    "    return a-b\n",
    "\n",
    "d_y = derivative(derivative(y))\n",
    "d_x_bin = np.linspace(0, len(d_y), len(d_y))\n",
    "\n",
    "print(x_bin.shape)\n",
    "print(d_y.shape)\n",
    "print(d_x_bin.shape)\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "plt.plot(d_x_bin, d_y)\n",
    "plt.show()\n",
    "\n",
    "print(np.argmax(d_y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Find elbow from curve estimate\n",
    "\n",
    "origin['num_points']\n",
    "\n",
    "plot_data = origin[origin['num_points'] >= 0 ]['num_points'].values\n",
    "\n",
    "x = np.linspace(0, 20, 20)\n",
    "y, x = np.histogram(plot_data, bins=x)\n",
    "x_bin = np.delete(x, 0)\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "plt.plot(x_bin, y)\n",
    "plt.show()\n",
    "\n",
    "import numpy as np\n",
    "from scipy.optimize import curve_fit\n",
    "def func(x, a, b):\n",
    "    return a * np.exp(-b * x)\n",
    "\n",
    "xdata = x_bin\n",
    "ydata = y\n",
    "\n",
    "print(xdata.shape)\n",
    "print(ydata.shape)\n",
    "\n",
    "popt, pcov = curve_fit(func, xdata, ydata, p0=[0.0007, 0.0004])\n",
    "\n",
    "print(popt)\n",
    "print(pcov)\n",
    "plt.plot(x_bin, func(x_bin,*popt), color='g', linewidth=10)\n",
    "plt.plot(x_bin, y, color='r')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "a, b = popt\n",
    "print(a)\n",
    "print(b)\n",
    "\n",
    "# second derivative of a * e^(-bx) is ab^2e^(-bx)\n",
    "\n",
    "def firstD(a,b,x):\n",
    "    return - a * b * np.exp(-b * x)\n",
    "\n",
    "\n",
    "def secondD(a,b,x):\n",
    "    return a * np.square(b) * np.exp(-b * x)\n",
    "\n",
    "plt.plot(x_bin, secondD(a,b,x_bin))\n",
    "plt.plot(x_bin, firstD(a,b,x_bin))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "from keras.layers import Input, LSTM, RepeatVector, Dense\n",
    "from keras.models import Model, Sequential\n",
    "\n",
    "input_dim = 50\n",
    "timesteps = 24\n",
    "latent_dim = 200\n",
    "\n",
    "predictor = Sequential()\n",
    "predictor.add(LSTM(100, input_shape=(timesteps, input_dim)))\n",
    "predictor.add(Dense(100, init='normal', activation='tanh'))\n",
    "predictor.add(Dense(1, init='normal', activation='sigmoid'))\n",
    "\n",
    "'''\n",
    "decoded = RepeatVector(timesteps)(encoded)\n",
    "#decoded = LSTM(input_dim, return_sequences=True)(encoded)\n",
    "decoded = LSTM(input_dim, return_sequences=True)(decoded)\n",
    "\n",
    "sequence_autoencoder = Model(inputs, decoded)\n",
    "encoder = Model(inputs, encoded)\n",
    "'''"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "X = train.drop(['good'], axis=1)\n",
    "Y = test.drop(['good'], axis=1)\n",
    "\n",
    "X = X.as_matrix().reshape(train.shape[0], 24, 50)\n",
    "Y = Y.as_matrix().reshape(test.shape[0], 24, 50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "predictor.compile(loss='binary_crossentropy', optimizer='Adam', metrics=['accuracy', 'precision', 'recall', 'fmeasure'])\n",
    "predictor.fit(X, train['good'], validation_data=(Y, test['good']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "sequence_autoencoder.evaluate(Y,test['good'])"
   ]
  }
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