Jupyter_Metrics_Final_Project_5_SentimentAnalysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Sentiment Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "source": [
    "# VADER: (Valence Aware Dictionary and sEntiment Reasoner)\n",
    "\n",
    "### The best way to understand VADER is to look at the source code\n",
    "(Although it is a little unpolished) https://github.com/cjhutto/vaderSentiment\n",
    "\n",
    "Also see the actual dictionary at https://github.com/cjhutto/vaderSentiment/blob/master/vaderSentiment/vader_sentiment_lexicon.txt.\n",
    "\n",
    "You can install the code using `pip install vaderSentiment` but it might be better to download it so you can more easily modify it.\n",
    "\n",
    "### VADER doesn't run in Python 3 because of line 23 in vaderSentiment.py\n",
    "See issue 11 for a fix: https://github.com/cjhutto/vaderSentiment/issues/11"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Resources:**  \n",
    "https://stackoverflow.com/questions/40325980/how-is-the-vader-compound-polarity-score-calculated-in-python-nltk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# You have to do this weird import in iPython notebook (Jupyter)\n",
    "# because of the line \"reload(sys)\" in vaderSentiment.py\n",
    "# See issue 7 for a simple fix: https://github.com/cjhutto/vaderSentiment/issues/7\n",
    "import sys\n",
    "import pandas as pd\n",
    "nb_stdout = sys.stdout\n",
    "from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer\n",
    "sys.stdout = nb_stdout"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'neg': 0.0, 'neu': 0.508, 'pos': 0.492, 'compound': 0.4404}\n",
      "0.4404\n"
     ]
    }
   ],
   "source": [
    "analyzer = SentimentIntensityAnalyzer()\n",
    "vs = analyzer.polarity_scores(\"this is a good example\")\n",
    "print(str(vs))\n",
    "print(str(vs[\"compound\"]))\n",
    "# A statement without sentiment\n",
    "#print(sentiment('Bob is a man.'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv('issue_comments_jupyter_copy.csv')\n",
    "df['org'] = df['org'].astype('str')\n",
    "df['repo'] = df['repo'].astype('str')\n",
    "df['comments'] = df['comments'].astype('str')\n",
    "df['user'] = df['user'].astype('str')\n",
    "\n",
    "# below from http://t-redactyl.io/blog/2017/04/applying-sentiment-analysis-with-vader-and-the-twitter-api.html\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    colaboratory\n",
      "1    colaboratory\n",
      "2    colaboratory\n",
      "3    colaboratory\n",
      "4    colaboratory\n",
      "Name: repo, dtype: object\n"
     ]
    }
   ],
   "source": [
    "print df.repo.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "## below from http://t-redactyl.io/blog/2017/04/applying-sentiment-analysis-with-vader-and-the-twitter-api.html\n",
    "from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer\n",
    "analyzer = SentimentIntensityAnalyzer()\n",
    "vs_comment = []\n",
    "vs_compound = []\n",
    "vs_pos = []\n",
    "vs_neu = []\n",
    "vs_neg = []\n",
    "vs_repo = []\n",
    "vs_user = []\n",
    "for i in range(0, len(df.comments)):\n",
    "    vs_user.append(df.user[i])\n",
    "    vs_repo.append(df.repo[i])\n",
    "    vs_comment.append(df.comments[i])\n",
    "    vs_compound.append(analyzer.polarity_scores(df.comments[i])['compound'])\n",
    "    vs_pos.append(analyzer.polarity_scores(df.comments[i])['pos'])\n",
    "    vs_neu.append(analyzer.polarity_scores(df.comments[i])['neu'])\n",
    "    vs_neg.append(analyzer.polarity_scores(df.comments[i])['neg'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "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>User</th>\n",
       "      <th>Repo</th>\n",
       "      <th>Comment</th>\n",
       "      <th>Compound</th>\n",
       "      <th>Positive</th>\n",
       "      <th>Neutral</th>\n",
       "      <th>Negative</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>wernight</td>\n",
       "      <td>colaboratory</td>\n",
       "      <td>Thanks !\\n</td>\n",
       "      <td>0.4926</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>kakitone</td>\n",
       "      <td>colaboratory</td>\n",
       "      <td>Oops. i got it. I have to uninstall ipython3 a...</td>\n",
       "      <td>0.6597</td>\n",
       "      <td>0.153</td>\n",
       "      <td>0.847</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>magdalenat</td>\n",
       "      <td>colaboratory</td>\n",
       "      <td>same issue\\n</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>magdalenat</td>\n",
       "      <td>colaboratory</td>\n",
       "      <td>FWIW a workaround is to share from Google Driv...</td>\n",
       "      <td>0.2960</td>\n",
       "      <td>0.121</td>\n",
       "      <td>0.879</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>jackiekazil</td>\n",
       "      <td>colaboratory</td>\n",
       "      <td>At some point, I'll probably hack on a Rethink...</td>\n",
       "      <td>0.6808</td>\n",
       "      <td>0.142</td>\n",
       "      <td>0.813</td>\n",
       "      <td>0.046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>jackiekazil</td>\n",
       "      <td>colaboratory</td>\n",
       "      <td>Also, if you just want storage (not the realti...</td>\n",
       "      <td>0.8934</td>\n",
       "      <td>0.278</td>\n",
       "      <td>0.722</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>jackiekazil</td>\n",
       "      <td>colaboratory</td>\n",
       "      <td>Was looking for the realtime. :-) \\nTy for the...</td>\n",
       "      <td>0.8020</td>\n",
       "      <td>0.387</td>\n",
       "      <td>0.613</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>jackiekazil</td>\n",
       "      <td>colaboratory</td>\n",
       "      <td>Note that SageMathCloud also lets you collabor...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>jackiekazil</td>\n",
       "      <td>colaboratory</td>\n",
       "      <td>Thanks for bringing that up! My head was burie...</td>\n",
       "      <td>0.6593</td>\n",
       "      <td>0.136</td>\n",
       "      <td>0.810</td>\n",
       "      <td>0.055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>jackiekazil</td>\n",
       "      <td>colaboratory</td>\n",
       "      <td>@rgbkrk let me know if you ever want to chat m...</td>\n",
       "      <td>0.0772</td>\n",
       "      <td>0.030</td>\n",
       "      <td>0.970</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>jackiekazil</td>\n",
       "      <td>colaboratory</td>\n",
       "      <td>Note that in addition to using SageMathCloud a...</td>\n",
       "      <td>0.1280</td>\n",
       "      <td>0.030</td>\n",
       "      <td>0.970</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Carreau</td>\n",
       "      <td>design</td>\n",
       "      <td>http://nbviewer.ipython.org/gist/damianavila/d...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Carreau</td>\n",
       "      <td>design</td>\n",
       "      <td>Cute.\\n</td>\n",
       "      <td>0.4588</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>Here is the sticker that Leah did for NumFOCUS...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>We already have Jupyter stickers. @takluyver i...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>I am talking with Leah and Thomas about this o...</td>\n",
       "      <td>0.4404</td>\n",
       "      <td>0.071</td>\n",
       "      <td>0.929</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>Yes you should. Pinged you in gitter. \\n</td>\n",
       "      <td>0.4019</td>\n",
       "      <td>0.310</td>\n",
       "      <td>0.690</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>We also might want to look at setting up our s...</td>\n",
       "      <td>0.6249</td>\n",
       "      <td>0.179</td>\n",
       "      <td>0.821</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>These are two designs that I have mocked up in...</td>\n",
       "      <td>-0.8614</td>\n",
       "      <td>0.088</td>\n",
       "      <td>0.668</td>\n",
       "      <td>0.244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>I should mention that I told @cameronoelsen th...</td>\n",
       "      <td>0.4436</td>\n",
       "      <td>0.097</td>\n",
       "      <td>0.864</td>\n",
       "      <td>0.040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>The bottom one is preferable, but I think I'd ...</td>\n",
       "      <td>0.4497</td>\n",
       "      <td>0.129</td>\n",
       "      <td>0.871</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>I tend to agree with @takluyer. If we use sema...</td>\n",
       "      <td>0.7996</td>\n",
       "      <td>0.226</td>\n",
       "      <td>0.774</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>&gt; I think I'd still be more likely to pick up ...</td>\n",
       "      <td>0.3182</td>\n",
       "      <td>0.133</td>\n",
       "      <td>0.867</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>I ordered 600 from a new project.jupyter@gmail...</td>\n",
       "      <td>0.2732</td>\n",
       "      <td>0.043</td>\n",
       "      <td>0.957</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>I have also created a projectjupyter@gmail.com...</td>\n",
       "      <td>-0.6124</td>\n",
       "      <td>0.063</td>\n",
       "      <td>0.750</td>\n",
       "      <td>0.188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>You mean 6000, right? 600 wouldn't last very l...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>and are they being delivered to the hotel for ...</td>\n",
       "      <td>0.2732</td>\n",
       "      <td>0.160</td>\n",
       "      <td>0.840</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>@cameronoelsen Why not stick with a standard l...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>@neilpanchal We stuck with the original circul...</td>\n",
       "      <td>0.2732</td>\n",
       "      <td>0.177</td>\n",
       "      <td>0.736</td>\n",
       "      <td>0.087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>@cameronoelsen cool, cool, cool. :+1: \\n</td>\n",
       "      <td>0.7096</td>\n",
       "      <td>0.775</td>\n",
       "      <td>0.225</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>Yes, 6000\\n\\nSent from my iPhone\\n\\n&gt; On Jun 2...</td>\n",
       "      <td>0.4019</td>\n",
       "      <td>0.070</td>\n",
       "      <td>0.930</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>These were shipping faster so they are coming ...</td>\n",
       "      <td>0.2732</td>\n",
       "      <td>0.034</td>\n",
       "      <td>0.966</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>Any way of making one that's just the \"jupyter...</td>\n",
       "      <td>-0.4215</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.872</td>\n",
       "      <td>0.128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>I like this idea - @cameronoelsen can this be ...</td>\n",
       "      <td>-0.3421</td>\n",
       "      <td>0.023</td>\n",
       "      <td>0.936</td>\n",
       "      <td>0.041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>But @rgbkrk - I will also have @cameronoelsen ...</td>\n",
       "      <td>0.3612</td>\n",
       "      <td>0.205</td>\n",
       "      <td>0.699</td>\n",
       "      <td>0.096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>&gt; do a special one for you that is just chompy...</td>\n",
       "      <td>0.4199</td>\n",
       "      <td>0.274</td>\n",
       "      <td>0.605</td>\n",
       "      <td>0.121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>Do you think we should have slightly different...</td>\n",
       "      <td>0.2023</td>\n",
       "      <td>0.073</td>\n",
       "      <td>0.927</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>We could definitely explore something like tha...</td>\n",
       "      <td>0.8360</td>\n",
       "      <td>0.098</td>\n",
       "      <td>0.902</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>Could I request that we make some t-shirts in ...</td>\n",
       "      <td>0.4497</td>\n",
       "      <td>0.076</td>\n",
       "      <td>0.924</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>We can and should definitely do that!\\n\\nOn Mo...</td>\n",
       "      <td>0.4574</td>\n",
       "      <td>0.048</td>\n",
       "      <td>0.952</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>Do we try to make T-Shirt for SciPy ? If so sh...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>We all agree we should have t-shirts: but what...</td>\n",
       "      <td>0.6486</td>\n",
       "      <td>0.187</td>\n",
       "      <td>0.813</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>Pretty sure black is the only color of shirt f...</td>\n",
       "      <td>0.6996</td>\n",
       "      <td>0.326</td>\n",
       "      <td>0.674</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>I was thinking a darker charcoal gray (nearing...</td>\n",
       "      <td>0.2263</td>\n",
       "      <td>0.213</td>\n",
       "      <td>0.787</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>Here is my first rendering of what the t-shirt...</td>\n",
       "      <td>0.4738</td>\n",
       "      <td>0.067</td>\n",
       "      <td>0.933</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>We should ask the Julia folks what their thoug...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>I wonder if the top row of the logo grid shoul...</td>\n",
       "      <td>0.8288</td>\n",
       "      <td>0.101</td>\n",
       "      <td>0.876</td>\n",
       "      <td>0.023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>Yeah, we are going to make a pass at reorganiz...</td>\n",
       "      <td>0.8817</td>\n",
       "      <td>0.084</td>\n",
       "      <td>0.902</td>\n",
       "      <td>0.014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>&gt; Pretty sure black is the only color of shirt...</td>\n",
       "      <td>0.9423</td>\n",
       "      <td>0.154</td>\n",
       "      <td>0.846</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>ellisonbg</td>\n",
       "      <td>design</td>\n",
       "      <td>The logo are just in the order, and the one I ...</td>\n",
       "      <td>-0.1227</td>\n",
       "      <td>0.072</td>\n",
       "      <td>0.849</td>\n",
       "      <td>0.080</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           User          Repo  \\\n",
       "0      wernight  colaboratory   \n",
       "1      kakitone  colaboratory   \n",
       "2    magdalenat  colaboratory   \n",
       "3    magdalenat  colaboratory   \n",
       "4   jackiekazil  colaboratory   \n",
       "5   jackiekazil  colaboratory   \n",
       "6   jackiekazil  colaboratory   \n",
       "7   jackiekazil  colaboratory   \n",
       "8   jackiekazil  colaboratory   \n",
       "9   jackiekazil  colaboratory   \n",
       "10  jackiekazil  colaboratory   \n",
       "11      Carreau        design   \n",
       "12      Carreau        design   \n",
       "13    ellisonbg        design   \n",
       "14    ellisonbg        design   \n",
       "15    ellisonbg        design   \n",
       "16    ellisonbg        design   \n",
       "17    ellisonbg        design   \n",
       "18    ellisonbg        design   \n",
       "19    ellisonbg        design   \n",
       "20    ellisonbg        design   \n",
       "21    ellisonbg        design   \n",
       "22    ellisonbg        design   \n",
       "23    ellisonbg        design   \n",
       "24    ellisonbg        design   \n",
       "25    ellisonbg        design   \n",
       "26    ellisonbg        design   \n",
       "27    ellisonbg        design   \n",
       "28    ellisonbg        design   \n",
       "29    ellisonbg        design   \n",
       "30    ellisonbg        design   \n",
       "31    ellisonbg        design   \n",
       "32    ellisonbg        design   \n",
       "33    ellisonbg        design   \n",
       "34    ellisonbg        design   \n",
       "35    ellisonbg        design   \n",
       "36    ellisonbg        design   \n",
       "37    ellisonbg        design   \n",
       "38    ellisonbg        design   \n",
       "39    ellisonbg        design   \n",
       "40    ellisonbg        design   \n",
       "41    ellisonbg        design   \n",
       "42    ellisonbg        design   \n",
       "43    ellisonbg        design   \n",
       "44    ellisonbg        design   \n",
       "45    ellisonbg        design   \n",
       "46    ellisonbg        design   \n",
       "47    ellisonbg        design   \n",
       "48    ellisonbg        design   \n",
       "49    ellisonbg        design   \n",
       "\n",
       "                                              Comment  Compound  Positive  \\\n",
       "0                                          Thanks !\\n    0.4926     1.000   \n",
       "1   Oops. i got it. I have to uninstall ipython3 a...    0.6597     0.153   \n",
       "2                                        same issue\\n    0.0000     0.000   \n",
       "3   FWIW a workaround is to share from Google Driv...    0.2960     0.121   \n",
       "4   At some point, I'll probably hack on a Rethink...    0.6808     0.142   \n",
       "5   Also, if you just want storage (not the realti...    0.8934     0.278   \n",
       "6   Was looking for the realtime. :-) \\nTy for the...    0.8020     0.387   \n",
       "7   Note that SageMathCloud also lets you collabor...    0.0000     0.000   \n",
       "8   Thanks for bringing that up! My head was burie...    0.6593     0.136   \n",
       "9   @rgbkrk let me know if you ever want to chat m...    0.0772     0.030   \n",
       "10  Note that in addition to using SageMathCloud a...    0.1280     0.030   \n",
       "11  http://nbviewer.ipython.org/gist/damianavila/d...    0.0000     0.000   \n",
       "12                                            Cute.\\n    0.4588     1.000   \n",
       "13  Here is the sticker that Leah did for NumFOCUS...    0.0000     0.000   \n",
       "14  We already have Jupyter stickers. @takluyver i...    0.0000     0.000   \n",
       "15  I am talking with Leah and Thomas about this o...    0.4404     0.071   \n",
       "16           Yes you should. Pinged you in gitter. \\n    0.4019     0.310   \n",
       "17  We also might want to look at setting up our s...    0.6249     0.179   \n",
       "18  These are two designs that I have mocked up in...   -0.8614     0.088   \n",
       "19  I should mention that I told @cameronoelsen th...    0.4436     0.097   \n",
       "20  The bottom one is preferable, but I think I'd ...    0.4497     0.129   \n",
       "21  I tend to agree with @takluyer. If we use sema...    0.7996     0.226   \n",
       "22  > I think I'd still be more likely to pick up ...    0.3182     0.133   \n",
       "23  I ordered 600 from a new project.jupyter@gmail...    0.2732     0.043   \n",
       "24  I have also created a projectjupyter@gmail.com...   -0.6124     0.063   \n",
       "25  You mean 6000, right? 600 wouldn't last very l...    0.0000     0.000   \n",
       "26  and are they being delivered to the hotel for ...    0.2732     0.160   \n",
       "27  @cameronoelsen Why not stick with a standard l...    0.0000     0.000   \n",
       "28  @neilpanchal We stuck with the original circul...    0.2732     0.177   \n",
       "29           @cameronoelsen cool, cool, cool. :+1: \\n    0.7096     0.775   \n",
       "30  Yes, 6000\\n\\nSent from my iPhone\\n\\n> On Jun 2...    0.4019     0.070   \n",
       "31  These were shipping faster so they are coming ...    0.2732     0.034   \n",
       "32  Any way of making one that's just the \"jupyter...   -0.4215     0.000   \n",
       "33  I like this idea - @cameronoelsen can this be ...   -0.3421     0.023   \n",
       "34  But @rgbkrk - I will also have @cameronoelsen ...    0.3612     0.205   \n",
       "35  > do a special one for you that is just chompy...    0.4199     0.274   \n",
       "36  Do you think we should have slightly different...    0.2023     0.073   \n",
       "37  We could definitely explore something like tha...    0.8360     0.098   \n",
       "38  Could I request that we make some t-shirts in ...    0.4497     0.076   \n",
       "39  We can and should definitely do that!\\n\\nOn Mo...    0.4574     0.048   \n",
       "40  Do we try to make T-Shirt for SciPy ? If so sh...    0.0000     0.000   \n",
       "41  We all agree we should have t-shirts: but what...    0.6486     0.187   \n",
       "42  Pretty sure black is the only color of shirt f...    0.6996     0.326   \n",
       "43  I was thinking a darker charcoal gray (nearing...    0.2263     0.213   \n",
       "44  Here is my first rendering of what the t-shirt...    0.4738     0.067   \n",
       "45  We should ask the Julia folks what their thoug...    0.0000     0.000   \n",
       "46  I wonder if the top row of the logo grid shoul...    0.8288     0.101   \n",
       "47  Yeah, we are going to make a pass at reorganiz...    0.8817     0.084   \n",
       "48  > Pretty sure black is the only color of shirt...    0.9423     0.154   \n",
       "49  The logo are just in the order, and the one I ...   -0.1227     0.072   \n",
       "\n",
       "    Neutral  Negative  \n",
       "0     0.000     0.000  \n",
       "1     0.847     0.000  \n",
       "2     1.000     0.000  \n",
       "3     0.879     0.000  \n",
       "4     0.813     0.046  \n",
       "5     0.722     0.000  \n",
       "6     0.613     0.000  \n",
       "7     1.000     0.000  \n",
       "8     0.810     0.055  \n",
       "9     0.970     0.000  \n",
       "10    0.970     0.000  \n",
       "11    1.000     0.000  \n",
       "12    0.000     0.000  \n",
       "13    1.000     0.000  \n",
       "14    1.000     0.000  \n",
       "15    0.929     0.000  \n",
       "16    0.690     0.000  \n",
       "17    0.821     0.000  \n",
       "18    0.668     0.244  \n",
       "19    0.864     0.040  \n",
       "20    0.871     0.000  \n",
       "21    0.774     0.000  \n",
       "22    0.867     0.000  \n",
       "23    0.957     0.000  \n",
       "24    0.750     0.188  \n",
       "25    1.000     0.000  \n",
       "26    0.840     0.000  \n",
       "27    1.000     0.000  \n",
       "28    0.736     0.087  \n",
       "29    0.225     0.000  \n",
       "30    0.930     0.000  \n",
       "31    0.966     0.000  \n",
       "32    0.872     0.128  \n",
       "33    0.936     0.041  \n",
       "34    0.699     0.096  \n",
       "35    0.605     0.121  \n",
       "36    0.927     0.000  \n",
       "37    0.902     0.000  \n",
       "38    0.924     0.000  \n",
       "39    0.952     0.000  \n",
       "40    1.000     0.000  \n",
       "41    0.813     0.000  \n",
       "42    0.674     0.000  \n",
       "43    0.787     0.000  \n",
       "44    0.933     0.000  \n",
       "45    1.000     0.000  \n",
       "46    0.876     0.023  \n",
       "47    0.902     0.014  \n",
       "48    0.846     0.000  \n",
       "49    0.849     0.080  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sentiment_df = pd.DataFrame({\n",
    "                        'User': vs_user,\n",
    "                        'Repo': vs_repo,\n",
    "                        'Comment': vs_comment,\n",
    "                        'Compound': vs_compound,\n",
    "                        'Positive': vs_pos,\n",
    "                        'Neutral': vs_neu,\n",
    "                        'Negative': vs_neg})\n",
    "sentiment_df = sentiment_df[['User','Repo','Comment', 'Compound', 'Positive', 'Neutral', 'Negative']]\n",
    "\n",
    "# Have a look at the top 5 results.\n",
    "sentiment_df.head(50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "new = sentiment_df.groupby('Repo')[['Compound']].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "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>Compound</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Repo</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>colaboratory</th>\n",
       "      <td>0.426273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>design</th>\n",
       "      <td>0.370388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>docker-demo-images</th>\n",
       "      <td>0.246400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>jupyter-drive</th>\n",
       "      <td>0.208903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>jupyter.github.io</th>\n",
       "      <td>0.296174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>jupyter_client</th>\n",
       "      <td>0.229926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>jupyter_core</th>\n",
       "      <td>0.149977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nature-demo</th>\n",
       "      <td>0.197575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nbcache</th>\n",
       "      <td>0.211920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nbconvert-examples</th>\n",
       "      <td>0.152714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nbformat</th>\n",
       "      <td>0.278750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nbgrader</th>\n",
       "      <td>0.288290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nbviewer</th>\n",
       "      <td>0.266490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nbviewer-deploy</th>\n",
       "      <td>0.096133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>notebook</th>\n",
       "      <td>0.212759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>testpath</th>\n",
       "      <td>0.433544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tmpnb</th>\n",
       "      <td>0.279224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tmpnb-deploy</th>\n",
       "      <td>0.174564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tmpnb-redirector</th>\n",
       "      <td>0.280300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>try.jupyter.org</th>\n",
       "      <td>0.222421</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Compound\n",
       "Repo                        \n",
       "colaboratory        0.426273\n",
       "design              0.370388\n",
       "docker-demo-images  0.246400\n",
       "jupyter-drive       0.208903\n",
       "jupyter.github.io   0.296174\n",
       "jupyter_client      0.229926\n",
       "jupyter_core        0.149977\n",
       "nature-demo         0.197575\n",
       "nbcache             0.211920\n",
       "nbconvert-examples  0.152714\n",
       "nbformat            0.278750\n",
       "nbgrader            0.288290\n",
       "nbviewer            0.266490\n",
       "nbviewer-deploy     0.096133\n",
       "notebook            0.212759\n",
       "testpath            0.433544\n",
       "tmpnb               0.279224\n",
       "tmpnb-deploy        0.174564\n",
       "tmpnb-redirector    0.280300\n",
       "try.jupyter.org     0.222421"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " colaboratory 0.426272727273\n",
      "design 0.370388205128\n",
      "docker-demo-images 0.246399673203\n",
      "jupyter-drive 0.208903092784\n",
      "jupyter.github.io 0.296174388254\n",
      "jupyter_client 0.229926077586\n",
      "jupyter_core 0.149976603774\n",
      "nature-demo 0.197575\n",
      "nbcache 0.21192\n",
      "nbconvert-examples 0.152714285714\n",
      "nbformat 0.278749589041\n",
      "nbgrader 0.28829013209\n",
      "nbviewer 0.266490162272\n",
      "nbviewer-deploy 0.0961333333333\n",
      "notebook 0.212759463857\n",
      "testpath 0.433544444444\n",
      "tmpnb 0.279224289406\n",
      "tmpnb-deploy 0.174564\n",
      "tmpnb-redirector 0.2803\n",
      "try.jupyter.org 0.222421276596\n"
     ]
    }
   ],
   "source": [
    "for index, row in new.iterrows():\n",
    "    print index, row[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "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>Compound</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Repo</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>colaboratory</th>\n",
       "      <td>0.426273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>design</th>\n",
       "      <td>0.370388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>docker-demo-images</th>\n",
       "      <td>0.246400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>jupyter-drive</th>\n",
       "      <td>0.208903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>jupyter.github.io</th>\n",
       "      <td>0.296174</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Compound\n",
       "Repo                        \n",
       "colaboratory        0.426273\n",
       "design              0.370388\n",
       "docker-demo-images  0.246400\n",
       "jupyter-drive       0.208903\n",
       "jupyter.github.io   0.296174"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "user_new = sentiment_df.groupby('User').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "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>Compound</th>\n",
       "      <th>Positive</th>\n",
       "      <th>Neutral</th>\n",
       "      <th>Negative</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>User</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>rgap</th>\n",
       "      <td>0.976400</td>\n",
       "      <td>0.334000</td>\n",
       "      <td>0.666000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>selvaransuresh</th>\n",
       "      <td>0.967900</td>\n",
       "      <td>0.175000</td>\n",
       "      <td>0.780000</td>\n",
       "      <td>0.045000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>reflectionalist</th>\n",
       "      <td>0.961600</td>\n",
       "      <td>0.142000</td>\n",
       "      <td>0.846000</td>\n",
       "      <td>0.011000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>matthias-johnson</th>\n",
       "      <td>0.953900</td>\n",
       "      <td>0.090000</td>\n",
       "      <td>0.899000</td>\n",
       "      <td>0.011000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alnilam</th>\n",
       "      <td>0.950400</td>\n",
       "      <td>0.140000</td>\n",
       "      <td>0.860000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>edublancas</th>\n",
       "      <td>0.931300</td>\n",
       "      <td>0.156000</td>\n",
       "      <td>0.776000</td>\n",
       "      <td>0.068000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sethrj</th>\n",
       "      <td>0.922100</td>\n",
       "      <td>0.283000</td>\n",
       "      <td>0.664000</td>\n",
       "      <td>0.053000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yrevar</th>\n",
       "      <td>0.919267</td>\n",
       "      <td>0.132333</td>\n",
       "      <td>0.862667</td>\n",
       "      <td>0.005333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JasonSanchez</th>\n",
       "      <td>0.913600</td>\n",
       "      <td>0.114000</td>\n",
       "      <td>0.872000</td>\n",
       "      <td>0.014000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>connercowling</th>\n",
       "      <td>0.904200</td>\n",
       "      <td>0.104000</td>\n",
       "      <td>0.847000</td>\n",
       "      <td>0.049000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alexgarel</th>\n",
       "      <td>0.885600</td>\n",
       "      <td>0.195000</td>\n",
       "      <td>0.805000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>jackjameshoward</th>\n",
       "      <td>0.876400</td>\n",
       "      <td>0.178000</td>\n",
       "      <td>0.822000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tonycpsu</th>\n",
       "      <td>0.872000</td>\n",
       "      <td>0.712000</td>\n",
       "      <td>0.288000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DanielLenz</th>\n",
       "      <td>0.871300</td>\n",
       "      <td>0.159000</td>\n",
       "      <td>0.819000</td>\n",
       "      <td>0.022000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bryanwweber</th>\n",
       "      <td>0.860825</td>\n",
       "      <td>0.495500</td>\n",
       "      <td>0.504500</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>smeylan</th>\n",
       "      <td>0.840200</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VelizarVESSELINOV</th>\n",
       "      <td>0.831600</td>\n",
       "      <td>0.173000</td>\n",
       "      <td>0.827000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>kalbhairab</th>\n",
       "      <td>0.828633</td>\n",
       "      <td>0.360333</td>\n",
       "      <td>0.605000</td>\n",
       "      <td>0.034667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ctk3b</th>\n",
       "      <td>0.821700</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mburke05</th>\n",
       "      <td>0.813300</td>\n",
       "      <td>0.347500</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>0.052000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>uolter</th>\n",
       "      <td>0.811200</td>\n",
       "      <td>0.262000</td>\n",
       "      <td>0.738000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>jreynolds01</th>\n",
       "      <td>0.807000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SnarkBoojum</th>\n",
       "      <td>0.800550</td>\n",
       "      <td>0.161000</td>\n",
       "      <td>0.819500</td>\n",
       "      <td>0.019000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>casdidier</th>\n",
       "      <td>0.795000</td>\n",
       "      <td>0.237000</td>\n",
       "      <td>0.763000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mmarchetti</th>\n",
       "      <td>0.790100</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>metatl</th>\n",
       "      <td>0.785100</td>\n",
       "      <td>0.191833</td>\n",
       "      <td>0.806500</td>\n",
       "      <td>0.001833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fbagirov</th>\n",
       "      <td>0.783900</td>\n",
       "      <td>0.059000</td>\n",
       "      <td>0.922000</td>\n",
       "      <td>0.020000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>marcozmonteiro</th>\n",
       "      <td>0.780800</td>\n",
       "      <td>0.136000</td>\n",
       "      <td>0.855000</td>\n",
       "      <td>0.009000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ConstantinoSchillebeeckx</th>\n",
       "      <td>0.775500</td>\n",
       "      <td>0.097000</td>\n",
       "      <td>0.884000</td>\n",
       "      <td>0.019000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dipugee</th>\n",
       "      <td>0.774450</td>\n",
       "      <td>0.138500</td>\n",
       "      <td>0.847000</td>\n",
       "      <td>0.014500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ericdill</th>\n",
       "      <td>0.649689</td>\n",
       "      <td>0.341667</td>\n",
       "      <td>0.658333</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>burkesquires</th>\n",
       "      <td>0.648000</td>\n",
       "      <td>0.309333</td>\n",
       "      <td>0.690667</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jan-Ko</th>\n",
       "      <td>0.647150</td>\n",
       "      <td>0.179000</td>\n",
       "      <td>0.726250</td>\n",
       "      <td>0.094750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yarmenti</th>\n",
       "      <td>0.645200</td>\n",
       "      <td>0.298000</td>\n",
       "      <td>0.684500</td>\n",
       "      <td>0.017500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rmanly</th>\n",
       "      <td>0.644200</td>\n",
       "      <td>0.251714</td>\n",
       "      <td>0.731286</td>\n",
       "      <td>0.017000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alginon</th>\n",
       "      <td>0.644150</td>\n",
       "      <td>0.196500</td>\n",
       "      <td>0.774500</td>\n",
       "      <td>0.029000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beto9</th>\n",
       "      <td>0.643350</td>\n",
       "      <td>0.131000</td>\n",
       "      <td>0.841000</td>\n",
       "      <td>0.028500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>donaldbraman</th>\n",
       "      <td>0.638757</td>\n",
       "      <td>0.093571</td>\n",
       "      <td>0.905286</td>\n",
       "      <td>0.001143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stsievert</th>\n",
       "      <td>0.637125</td>\n",
       "      <td>0.150750</td>\n",
       "      <td>0.832750</td>\n",
       "      <td>0.016250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bshlgrs</th>\n",
       "      <td>0.636900</td>\n",
       "      <td>0.634000</td>\n",
       "      <td>0.366000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pleabargain</th>\n",
       "      <td>0.636900</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fjanks</th>\n",
       "      <td>0.636100</td>\n",
       "      <td>0.357000</td>\n",
       "      <td>0.603000</td>\n",
       "      <td>0.040000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>choldgraf</th>\n",
       "      <td>0.630400</td>\n",
       "      <td>0.125429</td>\n",
       "      <td>0.855143</td>\n",
       "      <td>0.019429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>holgersson32644</th>\n",
       "      <td>0.624900</td>\n",
       "      <td>0.154000</td>\n",
       "      <td>0.846000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>spolakh</th>\n",
       "      <td>0.623740</td>\n",
       "      <td>0.179000</td>\n",
       "      <td>0.794200</td>\n",
       "      <td>0.026600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Summersa</th>\n",
       "      <td>0.621440</td>\n",
       "      <td>0.441000</td>\n",
       "      <td>0.559000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>anjefu</th>\n",
       "      <td>0.620950</td>\n",
       "      <td>0.069000</td>\n",
       "      <td>0.904750</td>\n",
       "      <td>0.026250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>jslmann</th>\n",
       "      <td>0.619733</td>\n",
       "      <td>0.481333</td>\n",
       "      <td>0.476000</td>\n",
       "      <td>0.042667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mmngreco</th>\n",
       "      <td>0.615500</td>\n",
       "      <td>0.377000</td>\n",
       "      <td>0.605000</td>\n",
       "      <td>0.018000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>jaredly</th>\n",
       "      <td>0.612400</td>\n",
       "      <td>0.185000</td>\n",
       "      <td>0.815000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Carpetfizz</th>\n",
       "      <td>0.612400</td>\n",
       "      <td>0.147000</td>\n",
       "      <td>0.853000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tfors</th>\n",
       "      <td>0.610300</td>\n",
       "      <td>0.363000</td>\n",
       "      <td>0.637000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>iamaris</th>\n",
       "      <td>0.607214</td>\n",
       "      <td>0.165429</td>\n",
       "      <td>0.826286</td>\n",
       "      <td>0.008143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nunocalaim</th>\n",
       "      <td>0.606300</td>\n",
       "      <td>0.077000</td>\n",
       "      <td>0.896500</td>\n",
       "      <td>0.027000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dubourg</th>\n",
       "      <td>0.605900</td>\n",
       "      <td>0.166000</td>\n",
       "      <td>0.834000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tanyaschlusser</th>\n",
       "      <td>0.601967</td>\n",
       "      <td>0.424667</td>\n",
       "      <td>0.575333</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>szsdk</th>\n",
       "      <td>0.599150</td>\n",
       "      <td>0.293500</td>\n",
       "      <td>0.706500</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Simon4john</th>\n",
       "      <td>0.595200</td>\n",
       "      <td>0.134000</td>\n",
       "      <td>0.832000</td>\n",
       "      <td>0.034000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>jeffnappi</th>\n",
       "      <td>0.593667</td>\n",
       "      <td>0.191667</td>\n",
       "      <td>0.797333</td>\n",
       "      <td>0.011000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ricardoduarte</th>\n",
       "      <td>0.588033</td>\n",
       "      <td>0.312333</td>\n",
       "      <td>0.687667</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Compound  Positive   Neutral  Negative\n",
       "User                                                            \n",
       "rgap                      0.976400  0.334000  0.666000  0.000000\n",
       "selvaransuresh            0.967900  0.175000  0.780000  0.045000\n",
       "reflectionalist           0.961600  0.142000  0.846000  0.011000\n",
       "matthias-johnson          0.953900  0.090000  0.899000  0.011000\n",
       "Alnilam                   0.950400  0.140000  0.860000  0.000000\n",
       "edublancas                0.931300  0.156000  0.776000  0.068000\n",
       "sethrj                    0.922100  0.283000  0.664000  0.053000\n",
       "yrevar                    0.919267  0.132333  0.862667  0.005333\n",
       "JasonSanchez              0.913600  0.114000  0.872000  0.014000\n",
       "connercowling             0.904200  0.104000  0.847000  0.049000\n",
       "alexgarel                 0.885600  0.195000  0.805000  0.000000\n",
       "jackjameshoward           0.876400  0.178000  0.822000  0.000000\n",
       "tonycpsu                  0.872000  0.712000  0.288000  0.000000\n",
       "DanielLenz                0.871300  0.159000  0.819000  0.022000\n",
       "bryanwweber               0.860825  0.495500  0.504500  0.000000\n",
       "smeylan                   0.840200  0.500000  0.500000  0.000000\n",
       "VelizarVESSELINOV         0.831600  0.173000  0.827000  0.000000\n",
       "kalbhairab                0.828633  0.360333  0.605000  0.034667\n",
       "ctk3b                     0.821700  1.000000  0.000000  0.000000\n",
       "mburke05                  0.813300  0.347500  0.600000  0.052000\n",
       "uolter                    0.811200  0.262000  0.738000  0.000000\n",
       "jreynolds01               0.807000  1.000000  0.000000  0.000000\n",
       "SnarkBoojum               0.800550  0.161000  0.819500  0.019000\n",
       "casdidier                 0.795000  0.237000  0.763000  0.000000\n",
       "mmarchetti                0.790100  1.000000  0.000000  0.000000\n",
       "metatl                    0.785100  0.191833  0.806500  0.001833\n",
       "fbagirov                  0.783900  0.059000  0.922000  0.020000\n",
       "marcozmonteiro            0.780800  0.136000  0.855000  0.009000\n",
       "ConstantinoSchillebeeckx  0.775500  0.097000  0.884000  0.019000\n",
       "Dipugee                   0.774450  0.138500  0.847000  0.014500\n",
       "...                            ...       ...       ...       ...\n",
       "ericdill                  0.649689  0.341667  0.658333  0.000000\n",
       "burkesquires              0.648000  0.309333  0.690667  0.000000\n",
       "Jan-Ko                    0.647150  0.179000  0.726250  0.094750\n",
       "yarmenti                  0.645200  0.298000  0.684500  0.017500\n",
       "rmanly                    0.644200  0.251714  0.731286  0.017000\n",
       "alginon                   0.644150  0.196500  0.774500  0.029000\n",
       "beto9                     0.643350  0.131000  0.841000  0.028500\n",
       "donaldbraman              0.638757  0.093571  0.905286  0.001143\n",
       "stsievert                 0.637125  0.150750  0.832750  0.016250\n",
       "bshlgrs                   0.636900  0.634000  0.366000  0.000000\n",
       "pleabargain               0.636900  1.000000  0.000000  0.000000\n",
       "Fjanks                    0.636100  0.357000  0.603000  0.040000\n",
       "choldgraf                 0.630400  0.125429  0.855143  0.019429\n",
       "holgersson32644           0.624900  0.154000  0.846000  0.000000\n",
       "spolakh                   0.623740  0.179000  0.794200  0.026600\n",
       "Summersa                  0.621440  0.441000  0.559000  0.000000\n",
       "anjefu                    0.620950  0.069000  0.904750  0.026250\n",
       "jslmann                   0.619733  0.481333  0.476000  0.042667\n",
       "mmngreco                  0.615500  0.377000  0.605000  0.018000\n",
       "jaredly                   0.612400  0.185000  0.815000  0.000000\n",
       "Carpetfizz                0.612400  0.147000  0.853000  0.000000\n",
       "tfors                     0.610300  0.363000  0.637000  0.000000\n",
       "iamaris                   0.607214  0.165429  0.826286  0.008143\n",
       "nunocalaim                0.606300  0.077000  0.896500  0.027000\n",
       "dubourg                   0.605900  0.166000  0.834000  0.000000\n",
       "tanyaschlusser            0.601967  0.424667  0.575333  0.000000\n",
       "szsdk                     0.599150  0.293500  0.706500  0.000000\n",
       "Simon4john                0.595200  0.134000  0.832000  0.034000\n",
       "jeffnappi                 0.593667  0.191667  0.797333  0.011000\n",
       "ricardoduarte             0.588033  0.312333  0.687667  0.000000\n",
       "\n",
       "[100 rows x 4 columns]"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_new.sort_values(['Compound'], ascending=False).head(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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