{
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   "cell_type": "markdown",
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    "## Attribution of Responsibility and Blame Regarding a Man-made Disaster: #FlintWaterCrisis\n",
    "\n",
    "by [Talha Oz](http://talhaoz.com) and [Halil Bisgin](http://halilbisgin.com) \n",
    "\n",
    "*Presented this work in the 4th International Workshop on Social Web for Disaster Management (SWDM'16), co-located with CIKM 2016; here is the [paper](https://arxiv.org/abs/1610.03480).*\n",
    "\n",
    "<center>**Abstract**</center>\n",
    "Attribution of responsibility and blame are important topics in political science especially as individuals tend to think of political issues in terms of questions of responsibility, and as blame carries far more weight in voting behavior than that of credit. However, surprisingly, there is a paucity of studies on the attribution of responsibility and blame in the field of disaster research.\n",
    "\n",
    "The Flint water crisis is a story of government failure at all levels. By studying microblog posts about it, we understand how citizens assign responsibility and blame regarding such a man-made disaster online. We form hypotheses based on social scientific theories in disaster research and then operationalize them on unobtrusive, observational social media data. In particular, we investigate the following phenomena: the source for blame; the partisan predisposition; the concerned geographies; and the contagion of complaining.\n",
    "\n",
    "This paper adds to the sociology of disasters research by exploiting a new, rarely used data source (the social web), and by employing new computational methods (such as sentiment analysis and retrospective cohort study design) on this new form of data. In this regard, this work should be seen as the first step toward drawing more challenging inferences on the sociology of disasters from \"big social data\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "run_control": {
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   "source": [
    "# read the JSON data and save it to Flint.pkl once,\n",
    "# whenever want to read the data, read the pickle,\n",
    "# instead of the raw JSON files. \n",
    "# This code block is here just to show how we created the pickle (.pkl) file.\n",
    "import pandas as pd\n",
    "import json\n",
    "from glob import glob\n",
    "from datetime import datetime\n",
    "tw = []\n",
    "for f in glob(\"data/TweetCollection/*.json\"):\n",
    "    with open(f, 'r',encoding='utf-8') as fin:\n",
    "        for line in fin:\n",
    "            a = json.loads(line)\n",
    "            tw.append({'id':a['id_str'],\n",
    "                       'created_at':datetime.strptime(a['created_at'],'%a %b %d %H:%M:%S +0000 %Y'),\n",
    "                       'hashtagged':any(['flintwatercrisis' in h['text'].lower() for h in a['entities']['hashtags']]),\n",
    "                       'screen_name':a['user']['screen_name'],\n",
    "                       'location':a['user']['location'],\n",
    "                       'followers':a['user']['followers_count'],\n",
    "                       'verified':bool(a['user']['verified']),\n",
    "                       'text':a['text']})\n",
    "df = pd.DataFrame(tw).set_index('id').drop_duplicates()\n",
    "#df.to_pickle('data/Flint.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "run_control": {
     "frozen": false,
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    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>created_at</th>\n",
       "      <th>followers</th>\n",
       "      <th>hashtagged</th>\n",
       "      <th>location</th>\n",
       "      <th>screen_name</th>\n",
       "      <th>text</th>\n",
       "      <th>verified</th>\n",
       "      <th>latlon</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>2016-01-15 21:00:24</td>\n",
       "      <td>265</td>\n",
       "      <td>True</td>\n",
       "      <td>Sugar Land, Texas</td>\n",
       "      <td>zachsciba</td>\n",
       "      <td>RT @TheDailyShow: #FlintWaterCrisis could have been prevented by an easy $100/day solution.  https://t.co/4Jf7oH20EX https://t.co/7fLogvuwrx</td>\n",
       "      <td>False</td>\n",
       "      <td>(29.599580, -95.614089)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2016-01-15 21:00:07</td>\n",
       "      <td>968</td>\n",
       "      <td>True</td>\n",
       "      <td>None</td>\n",
       "      <td>scootey</td>\n",
       "      <td>You can thank the Republican party for this #Michigan #FlintWaterCrisis #GOP #Uniteblue https://t.co/wK7IFvkk8k</td>\n",
       "      <td>False</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2016-01-15 21:00:30</td>\n",
       "      <td>189</td>\n",
       "      <td>True</td>\n",
       "      <td>s. pasadena,ca</td>\n",
       "      <td>steve1204</td>\n",
       "      <td>RT @TheDailyShow: #FlintWaterCrisis could have been prevented by an easy $100/day solution.  https://t.co/4Jf7oH20EX https://t.co/7fLogvuwrx</td>\n",
       "      <td>False</td>\n",
       "      <td>(34.112958, -118.155778)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2016-01-15 21:00:09</td>\n",
       "      <td>8053</td>\n",
       "      <td>True</td>\n",
       "      <td>Lansing, Michigan</td>\n",
       "      <td>ProgressMich</td>\n",
       "      <td>Snyder still won’t say when he knew about #FlintWaterCrisis. Protest with us on Tuesday to demand answers: https://t.co/aRfLc99QUy #MISOTS</td>\n",
       "      <td>False</td>\n",
       "      <td>(42.717585, -84.554916)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2016-01-15 21:00:35</td>\n",
       "      <td>7</td>\n",
       "      <td>True</td>\n",
       "      <td>None</td>\n",
       "      <td>marcgilbert77</td>\n",
       "      <td>RT @TheDailyShow: #FlintWaterCrisis could have been prevented by an easy $100/day solution.  https://t.co/4Jf7oH20EX https://t.co/7fLogvuwrx</td>\n",
       "      <td>False</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "pd.set_option('max_colwidth',200)\n",
    "df = pd.read_pickle('../data/Flint.pkl')\n",
    "\n",
    "from utilities.geocoder import Geocoder\n",
    "gc = Geocoder('utilities/geodata/state_abbr_file', 'utilities/geodata/city_file')\n",
    "df['latlon'] = df.location.str.strip().apply(gc.geocode)\n",
    "\n",
    "from IPython.display import HTML\n",
    "HTML(df.head().to_html(index=False)) #how the data looks like"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total tw: 664775 \n",
      "unique tw: 344384\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>text</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>274256</th>\n",
       "      <td>RT @xoShakarra: Friendly reminder that it STILL takes one hour and 23 gallons of water to take a bath in Flint. #FlintWaterCrisis https://t…</td>\n",
       "      <td>7093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202990</th>\n",
       "      <td>RT @BernieSanders: How do we have so much money to go to war in Iraq but somehow not enough money to provide clean drinking water to Flint?…</td>\n",
       "      <td>5825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261826</th>\n",
       "      <td>RT @markmobility: #FlintWaterCrisis \\n- 99,000 residents\\n- 57% Black\\n- 40% Poor\\n- 9,000 kids with lead poisoning\\nFlint HOSPITAL Water: https…</td>\n",
       "      <td>4710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>265544</th>\n",
       "      <td>RT @opinionatedcxnt: Saw this on Tumblr &amp;amp; it made me cringe. The Flint crisis is a horrific nightmare\\nhttps://t.co/j6sT5c5p3O</td>\n",
       "      <td>2354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204672</th>\n",
       "      <td>RT @BuzzFeedVideo: People See What Flint Water Looks Like\\nhttps://t.co/3fV2EZFz21</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                                                                                     text  \\\n",
       "274256       RT @xoShakarra: Friendly reminder that it STILL takes one hour and 23 gallons of water to take a bath in Flint. #FlintWaterCrisis https://t…   \n",
       "202990       RT @BernieSanders: How do we have so much money to go to war in Iraq but somehow not enough money to provide clean drinking water to Flint?…   \n",
       "261826  RT @markmobility: #FlintWaterCrisis \\n- 99,000 residents\\n- 57% Black\\n- 40% Poor\\n- 9,000 kids with lead poisoning\\nFlint HOSPITAL Water: https…   \n",
       "265544                 RT @opinionatedcxnt: Saw this on Tumblr &amp; it made me cringe. The Flint crisis is a horrific nightmare\\nhttps://t.co/j6sT5c5p3O   \n",
       "204672                                                                 RT @BuzzFeedVideo: People See What Flint Water Looks Like\\nhttps://t.co/3fV2EZFz21   \n",
       "\n",
       "         cnt  \n",
       "274256  7093  \n",
       "202990  5825  \n",
       "261826  4710  \n",
       "265544  2354  \n",
       "204672  1950  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "g = df.groupby('text').size().reset_index()\n",
    "g.columns = ['text','cnt']\n",
    "g = g.sort_values('cnt',ascending=False)\n",
    "print('total tw:',len(df),'\\nunique tw:',len(g))\n",
    "g.head() #most popular tweets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(01-22,01-25) (02-13,02-15) (02-16,02-20) (02-20,02-29) (02-29,03-03) (04-27,05-04) (05-06,05-08) (05-12,05-26) "
     ]
    }
   ],
   "source": [
    "# the original dates are in UTC/GMT, convert them to EST.\n",
    "# also, as given in footnote #4, report the missing dates\n",
    "\n",
    "import pytz\n",
    "eastern = pytz.timezone('US/Eastern')\n",
    "# group tweets by day\n",
    "df.created_at = df.created_at.dt.tz_localize(pytz.utc).dt.tz_convert(eastern)\n",
    "\n",
    "# print missing date intervals in our dataset\n",
    "day = df.groupby(df.created_at.dt.strftime('%m-%d'))['created_at'].count()\n",
    "days = day.index.tolist()\n",
    "for i in range(len(days)-1):\n",
    "    m1,d1 = days[i].split('-')\n",
    "    m2,d2 = days[i+1].split('-')\n",
    "    if m1 == m2:\n",
    "        if int(d1) == int(d2) - 1:\n",
    "            continue\n",
    "    else:\n",
    "        if d2 == '01':\n",
    "            continue\n",
    "    print('('+days[i]+','+days[i+1]+')',end=' ')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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gwYNaX3FxcdKajW/y8fFBmTJlZI91i4+Px+PHj9GpU6cS92vbtm0QBAGDBg2SlXt5eSEw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\nq1ZpzK2SP3RbYeecRZnHt2zZkit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      "text/plain": [
       "<matplotlib.figure.Figure at 0x13b27d8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Figure 1\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "matplotlib.style.use('fivethirtyeight')\n",
    "matplotlib.style.use('ggplot')\n",
    "plt.rcParams['axes.facecolor']='w'\n",
    "plt.rcParams['savefig.facecolor']='w'\n",
    "matplotlib.rcParams['font.size'] = 14\n",
    "#plot daily activity\n",
    "ax = day.plot(kind=\"bar\",figsize=(18, 4)) #,title='#FlintWaterCrisis Activity on Twitter'\n",
    "#ax.set_xlabel('Days After Flint Became a Federal State of Emergency on 2016-01-16', fontsize=14)\n",
    "ax.set_ylabel('Tweets in the 1% sample', fontsize=14)\n",
    "\n",
    "for label in ax.xaxis.get_ticklabels()[::2]:\n",
    "    label.set_visible(False)\n",
    "ax.annotate('Federal State of Emergency', xy=(0, 31000))\n",
    "ax.annotate('Gov. Rick Snyder holds a news conf.\\n'\\\n",
    "            'Groups file a federal lawsuit', xy=(12, 41000),ha='center')\n",
    "ax.annotate('First Flint hearing in Congress\\n'\\\n",
    "            'Hillary visits Flint', xy=(22, 9000),ha='center')\n",
    "ax.annotate('GOP debate in Detroit,MI\\nRubio defends MI governor', xy=(31, 23000),ha='center')\n",
    "ax.annotate('DEM debate in Flint,MI\\nBoth candidates calls Snyder to resign', xy=(36, 45000),ha='center')\n",
    "ax.annotate('MI primaries\\nfor both parties', xy=(40, 33000),ha='center')\n",
    "ax.annotate('Gov Snyder & EPA admin McCarthy\\ntestify before Congress', xy=(47, 11000),ha='center')\n",
    "ax.annotate('A local\\'s complaining tweet goes viral\\nGov Snyder asks the lawsuit be dismissed', xy=(69, 9000),ha='center')\n",
    "ax.annotate('Obama visits Flint', xy=(88, 10000),ha='center')\n",
    "ax.set_xlim([-1, 93])\n",
    "ax.set_xlabel('');\n",
    "ax.get_figure().savefig('../figs/daily.pdf',dpi=150,bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._axes.Axes at 0x126bd5d68>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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EQRCEYk2ioZHvV345OTmhpaXFrVv/LSJ+8+ZNKlSooLKvpaWlyozER48eUa5c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\nxebCl/S7AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x126c40f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Figure 2\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "\n",
    "#matplotlib.style.use('fivethirtyeight')\n",
    "matplotlib.style.use('ggplot')\n",
    "\n",
    "plt.rcParams['axes.facecolor']='w'\n",
    "plt.rcParams['savefig.facecolor']='w'\n",
    "matplotlib.rcParams['font.size'] = 14\n",
    "\n",
    "\n",
    "l = pd.DataFrame()\n",
    "for i in range(5):\n",
    "    r = pd.read_csv('../data/training/Flint'+str(i+1)+'_train.csv')\n",
    "    r['rater'] = i\n",
    "    l = l.append(r)\n",
    "l = l.fillna('missing')\n",
    "\n",
    "l['label'] = l.c.replace({',.*':'','missing':10},regex=True).astype(int) #removes multiple labels\n",
    "\n",
    "#get pairwise kappas\n",
    "from itertools import combinations\n",
    "from statsmodels.stats.inter_rater import fleiss_kappa\n",
    "from statsmodels.stats.inter_rater import aggregate_raters\n",
    "\n",
    "kappa = []\n",
    "for r1,r2 in combinations(range(5), 2):\n",
    "    rr = l[l.rater==r1].merge(l[l.rater==r2],on='text')[['label_x','label_y']]\n",
    "    k = fleiss_kappa(aggregate_raters(rr,n_cat=11)[0])\n",
    "    kappa.append(('r'+str(r1),'r'+str(r2),k))\n",
    "    kappa.append(('r'+str(r2),'r'+str(r1),k)) #(r2,r1,k)\n",
    "\n",
    "a = pd.DataFrame(kappa).pivot(0,1,2) #pairwise inter-rater fleiss-kappa \n",
    "a.index.name = None\n",
    "a.columns.name = None\n",
    "\n",
    "\n",
    "plt.figure(num=None, figsize=(6, 4), facecolor='w', edgecolor='w')\n",
    "\n",
    "labels = ['No blame','MI Governor','POTUS','Flint Mayor',\n",
    "          'EPA','Emergency M.','Republicans','Democrats','Government','Other indiv.', 'Unsure']\n",
    "cnt = [len(l[l.c.str.contains(str(i))]) for i in range(10)] #count of each label\n",
    "cnt.append(len(l[l.c.str.contains('missing')]))\n",
    "ax = plt.subplot()\n",
    "ax.margins(0, 0)\n",
    "colors = '#777777 #E24A33 #348ABD #348ABD #348ABD #E24A33 #E24A33 #348ABD #FBC15E #8EBA42 #FFB5B8'.split()\n",
    "#[color['color'] for color in list(plt.rcParams['axes.prop_cycle'])]\n",
    "ax.barh(range(len(cnt)),cnt,tick_label=labels,align='center',color=colors)\n",
    "#ax.set(xlabel='Manually coded tweets'); #title='Attribution of Blame/Responsibility',\n",
    "#ax.grid(color='grey', linestyle='dotted', linewidth=0.5)\n",
    "\n",
    "\n",
    "plt.axes([.4, .33, .55, .55])\n",
    "sns.heatmap(a,annot=True,vmin=0,vmax=1,cmap='RdBu_r',annot_kws={'size':12})\n",
    "#ax.get_figure().savefig('../figs/coders.pdf',dpi=150,bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{tabular}{lll}\n",
      "\\toprule\n",
      "{} &                Cities &           Counties \\\\\n",
      "\\midrule\n",
      "1  &             Flint, MI &        Genesee, MI \\\\\n",
      "2  &           Gaylord, MI &  Dist Columbia, DC \\\\\n",
      "3  &       Grand Blanc, MI &         Otsego, MI \\\\\n",
      "4  &      Mount Morris, MI &          Wayne, MI \\\\\n",
      "5  &  Bloomfield Hills, MI &         Ingham, MI \\\\\n",
      "6  &           Lansing, MI &      Washtenaw, MI \\\\\n",
      "7  &            Sedona, AZ &       Multiple, GA \\\\\n",
      "8  &           Davison, MI &           Kent, MI \\\\\n",
      "9  &     Traverse City, MI &       Coconino, AZ \\\\\n",
      "10 &         Ann Arbor, MI &           Cook, IL \\\\\n",
      "\\bottomrule\n",
      "\\end{tabular}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#Table 1\n",
    "df1 = pd.read_csv('../data/us-city-populations.csv',usecols=['CityST','2000','2010','LAT','LON','County_Name'])\n",
    "df2 = pd.read_csv('../data/city_file.csv',dtype={'lat':str,'lon':str})\n",
    "df2['CityST'] = df2.city + ', ' + df2.state\n",
    "cities = df1.merge(df2, on = 'CityST', how = 'inner')\n",
    "cities['latlon'] = cities[['lat','lon']].apply(tuple, axis=1)\n",
    "cnt = pd.DataFrame(df.groupby(by='latlon').size().reset_index().rename(columns={0:'cnt'}))\n",
    "cities = cities.merge(cnt,on='latlon',how='inner').rename(columns={'2010':'cpop','County_Name':'county'})\n",
    "cities = cities[cities.cnt>=3]\n",
    "cities.loc[cities.cpop.isnull(),'cpop'] = cities[cities.cpop.isnull()]['2000']\n",
    "cities = cities.sort_values('cnt',ascending=False).reset_index().drop(['index','LAT','LON','2000'],1)\n",
    "cities.cpop = cities.cpop.astype(int)\n",
    "#cities.to_csv('data/cities.csv',index=False)\n",
    "cities.head(10) #tweet counts without normalization\n",
    "\n",
    "fil = cities[cities.cpop>88].copy()\n",
    "fil['normalized'] = fil.cnt * 1000 / fil.cpop\n",
    "fil = fil[fil.normalized>=1]\n",
    "fil.sort_values('normalized',ascending=False).head(10) #normalized\n",
    "\n",
    "city10 = fil.sort_values('normalized',ascending=False).head(10).reset_index()\n",
    "city10 = city10.rename(columns={'CityST':'Cities'})\n",
    "\n",
    "cofil = fil.groupby(['county','state']).sum()\n",
    "cofil.normalized = cofil.cnt / np.sqrt(cofil.cpop)\n",
    "county10 = cofil.sort_values(by='normalized',ascending=False).head(10).reset_index()\n",
    "county10['Counties'] = county10.county +', '+county10.state\n",
    "\n",
    "cc = pd.concat([city10.Cities,county10.Counties],axis=1)\n",
    "cc.index += 1\n",
    "print(cc.to_latex())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[97577, 6028, 11609]\n"
     ]
    }
   ],
   "source": [
    "from nltk.sentiment.vader import SentimentIntensityAnalyzer\n",
    "sid = SentimentIntensityAnalyzer()\n",
    "\n",
    "snyder = df.text.str.contains('governor|nyder|onetoughnerd',case=False)\n",
    "EM = df.text.str.contains('mgr|manager|Darnell|Earley|Kurtz',case=False)\n",
    "mayor = df.text.str.contains('Dayne|Walling|ayor',case=False)\n",
    "\n",
    "print([len(df[x]) for x in [snyder,EM,mayor]]) #Footnote 10."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
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       "MAAAGD4AACJGAAAnPwAAJIIAACAuAAAamAAAIHEAACH7AAAi4wAAG40AACJsAAAjXgAAHNkAACka\n",
       "AAAmKAAAGBYAABTvAAAoOwAAIekAACK0AAAodAAAJFcAAB/cAAATCgAAEbwAACT1AAAAFHN0Y28A\n",
       "AAAAAAAAAQAAACwAAABidWR0YQAAAFptZXRhAAAAAAAAACFoZGxyAAAAAAAAAABtZGlyYXBwbAAA\n",
       "AAAAAAAAAAAAAC1pbHN0AAAAJal0b28AAAAdZGF0YQAAAAEAAAAATGF2ZjU3LjQxLjEwMA==\n",
       "\">\n",
       "  Your browser does not support the video tag.\n",
       "</video>"
      ],
      "text/plain": [
       "<matplotlib.animation.FuncAnimation at 0x11b083ac8>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from matplotlib import animation,font_manager\n",
    "import matplotlib.pyplot as plt\n",
    "from html import unescape\n",
    "import os\n",
    "\n",
    "plt.rcParams['savefig.dpi']=150\n",
    "plt.rcParams['animation.html'] = 'html5'\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(6, 1))\n",
    "ax.set_axis_off()\n",
    "\n",
    "plt.subplots_adjust(left=0.1, right=0.9, top=0.9, bottom=0.1)\n",
    "prop = font_manager.FontProperties(fname='Quivira.otf') # 'Symbola.ttf'\n",
    "text = ax.text(.5, .5, '', fontsize=11, va='center', ha='center', wrap=True, fontproperties = prop)\n",
    "\n",
    "txt = list(g.head(30).text) #g is a pandas dataframe\n",
    "\n",
    "def animate(i):\n",
    "    text.set_text('('+str(i+1)+') '+unescape(txt[i]))\n",
    "    return (text,)\n",
    "\n",
    "anim = animation.FuncAnimation(fig, animate, frames=len(txt), interval=2000, blit=True)\n",
    "anim.save('top30.mp4') #matplotlib can save as mp4, but not as gif yet.\n",
    "os.system(\"convert -delay 200 top30.mp4 top30.gif\") #imagemagick's convert\n",
    "anim #eye candy for the presentation :-)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "62 24\n"
     ]
    },
    {
     "data": {
      "image/png": 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wlJeXG0Z8b98Y5vZVMTIyMhrtSxCEBlfRMGdHzqaWltKP6N/+OBoakdHTP+6qqipR8RCR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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x124475e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Figure 3 (new)\n",
    "c = pd.DataFrame()\n",
    "for i in range(5):\n",
    "    r = pd.read_csv('../data/training/Flint'+str(i+1)+'_train.csv')\n",
    "    r['rater'] = i\n",
    "    c = c.append(r)\n",
    "c = c.dropna()\n",
    "print(len(c[c.c.str.contains('6')]),len(c[c.c.str.contains('7')]))\n",
    "\n",
    "r = df.screen_name[df.text.isin(c[c.c.str.contains('6')].text)]\n",
    "d = df.screen_name[df.text.isin(c[c.c.str.contains('7')].text)]\n",
    "\n",
    "m  = mayoronly[mayoronly.cmpnd!=0]\n",
    "s  = snyderonly[snyderonly.cmpnd!=0]\n",
    "\n",
    "\n",
    "#matplotlib.style.use('fivethirtyeight')\n",
    "matplotlib.style.use('ggplot')\n",
    "plt.rcParams['axes.facecolor']='w'\n",
    "plt.rcParams['savefig.facecolor']='w'\n",
    "matplotlib.rcParams['xtick.labelsize'] = 16\n",
    "matplotlib.rcParams['ytick.labelsize'] = 16\n",
    "matplotlib.rcParams['axes.titlesize'] = 18\n",
    "\n",
    "co = {'color':'black'}\n",
    "ma = {'color':'black','linestyle':'-'}\n",
    "boxprops = dict(linestyle='-', color='black')\n",
    "\n",
    "f, ax = plt.subplots(1, 2, sharey=True,figsize=(8,3))\n",
    "titles = ['Governor','Mayor']\n",
    "for i,a in enumerate([s,m]):\n",
    "    bp = ax[i].boxplot([a[a.screen_name.isin(d)].cmpnd,a[a.screen_name.isin(r)].cmpnd], patch_artist=True,\n",
    "             whiskerprops=co,capprops=co,medianprops=ma,boxprops=boxprops,labels=['Blaming R','Blaming D'])\n",
    "    for box, color in zip(bp['boxes'], ['#348ABD','#E24A33']):\n",
    "        box.set_color('black')\n",
    "        box.set_facecolor(color)\n",
    "\n",
    "    ax[i].set_title(titles[i],y=.9)\n",
    "    ax[i].yaxis.grid(True, linestyle='-', which='major', color='lightgrey', alpha=0.5)\n",
    "ax[0].set_ylabel('Sentiment score',fontsize=18);\n",
    "f.savefig('../figs/box-partisanship.pdf',dpi=150,bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true,
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "snyderonly = df[snyder&~mayor&~EM].copy()\n",
    "mayoronly=df[mayor&~snyder&~EM].copy()\n",
    "a = pd.DataFrame(list(snyderonly.text.apply(sid.polarity_scores)))\n",
    "snyderonly = pd.concat([snyderonly.reset_index(),a.rename(columns={'compound':'cmpnd'})],axis=1)\n",
    "a = pd.DataFrame(list(mayoronly.text.apply(sid.polarity_scores)))\n",
    "mayoronly = pd.concat([mayoronly.reset_index(),a.rename(columns={'compound':'cmpnd'})],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ks_2sampResult(statistic=0.36016301579215487, pvalue=3.4967160958746161e-06)\n",
      "0.27806837264879597\n",
      "Ks_2sampResult(statistic=0.33333333333333337, pvalue=0.71191004965601257)\n",
      "1.0148121747397396\n"
     ]
    }
   ],
   "source": [
    "from scipy.stats import ks_2samp\n",
    "from math import sqrt\n",
    "c_a = 1.95 #coefficient c_a is 1.36 for alpha 0.05 and 1.95 for alpha 0.001\n",
    "for i,a in enumerate([s,m]):\n",
    "    print(ks_2samp(a[a.screen_name.isin(d)].cmpnd,a[a.screen_name.isin(r)].cmpnd))\n",
    "    n1 = len(a[a.screen_name.isin(d)])\n",
    "    n2 = len(a[a.screen_name.isin(r)])\n",
    "    print('Critical value D_a:',c_a*sqrt((n1+n2)/(n1*n2)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "262\n"
     ]
    },
    {
     "data": {
      "image/png": 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TAAAg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\nIiIiIiIiIiIiIrKI/wOMDmWPdg0+bgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1282184e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#now the contagion \"experiment\"\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "#matplotlib.style.use('fivethirtyeight')\n",
    "matplotlib.style.use('ggplot')\n",
    "plt.rcParams['axes.facecolor']='w'\n",
    "plt.rcParams['savefig.facecolor']='w'\n",
    "plt.rcParams['savefig.dpi']=227 #DPI of my 13.3 MacBook Pro Retina\n",
    "f = df[df.latlon == gc.geocode(\"Flint, MI\")].groupby('screen_name').size()\n",
    "f.sort_values(ascending=False).plot(ylim=(0,30),linestyle=\"None\",marker='.',figsize=(10,5))\n",
    "f2 = list(f[(f>2)&(f<20)].index.values)\n",
    "print(len(f2)) #Natural selection: Flinters who tweeted 2<x<20 times "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying EzE_2o11_\n",
      "trying FGCofC\n",
      "\"['id_str' 'screen_name' 'name' 'location' 'description' 'created_at'\\n 'friends_count' 'followers_count' 'statuses_count' 'favourites_count'] not in index\"\n",
      "trying FYINation\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 404 Error (Not Found)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying FaithGiddings2\n",
      "trying FiggaDaKID\n",
      "trying FitLifeAmber\n",
      "trying Flint4Bernie\n",
      "trying FlintCoalition\n",
      "trying FlintDDA\n",
      "trying FlintFWDProject\n",
      "trying FlintHandmade\n",
      "trying FlintHorrorCon\n",
      "trying FlintLocal432\n",
      "trying FlintMI1\n",
      "trying FlintPoliceOps\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 429 Error (Rate Limit Exceeded)\n",
      "Retrying in 15 minutes...ZzZ...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying FlintRoguesRFC\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "...ZzZ...Awake now and trying again.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying FlintStitch\n",
      "trying FlintWaterDoc\n",
      "trying FlintWaterPrjct\n",
      "trying Flint_NC\n",
      "trying Flintrainbowmom\n",
      "trying FlintstoneQue10\n",
      "\"['id_str' 'screen_name' 'name' 'location' 'description' 'created_at'\\n 'friends_count' 'followers_count' 'statuses_count' 'favourites_count'] not in index\"\n",
      "trying ForgeFlint\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 404 Error (Not Found)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying FreeChoppa\n",
      "trying GCHD_MI\n",
      "trying GEARup2LEAD\n",
      "trying GREGJOSLIN\n",
      "trying Gnicole15\n",
      "Twitter sent status 404 for URL: 1.1/users/lookup.json using parameters: (oauth_consumer_key=gWPAsZSr8Vff6oNEGIcZgA&oauth_nonce=1267690250305170804&oauth_signature_method=HMAC-SHA1&oauth_timestamp=1477284134&oauth_token=2184712454-gAtpJPWGyiGMjbqXz3S0ycmKqFMDPSyBAXutBub&oauth_version=1.0&user_id=%5B50896539%2C%2051228255%5D&oauth_signature=Q551rY1rRrdYXmgvYHRafGaKxqo%3D)\n",
      "details: {'errors': [{'message': 'No user matches for specified terms.', 'code': 17}]}\n",
      "trying GrFlintHealthCo\n",
      "trying Hashtag_Flint\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 429 Error (Rate Limit Exceeded)\n",
      "Retrying in 15 minutes...ZzZ...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying HipHopMarauder\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "...ZzZ...Awake now and trying again.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying HoodRichCain\n",
      "\"['id_str' 'screen_name' 'name' 'location' 'description' 'created_at'\\n 'friends_count' 'followers_count' 'statuses_count' 'favourites_count'] not in index\"\n",
      "trying HurleyMedical\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 404 Error (Not Found)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying ILikeFootball7\n",
      "\"['id_str' 'screen_name' 'name' 'location' 'description' 'created_at'\\n 'friends_count' 'followers_count' 'statuses_count' 'favourites_count'] not in index\"\n",
      "trying ITJBrown\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 404 Error (Not Found)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying JM3_4_INT\n",
      "\"['id_str' 'screen_name' 'name' 'location' 'description' 'created_at'\\n 'friends_count' 'followers_count' 'statuses_count' 'favourites_count'] not in index\"\n",
      "trying JackTriple91\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 404 Error (Not Found)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying JakeCarah\n",
      "trying JamirWorld_\n",
      "trying JayeMonet\n",
      "trying Jaylen_22_\n",
      "trying JessycaMathews\n",
      "trying Jmaddy31\n",
      "\"['id_str' 'screen_name' 'name' 'location' 'description' 'created_at'\\n 'friends_count' 'followers_count' 'statuses_count' 'favourites_count'] not in index\"\n",
      "trying JoeBoo3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 404 Error (Not Found)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying JonConnorMusic\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 429 Error (Rate Limit Exceeded)\n",
      "Retrying in 15 minutes...ZzZ...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying Kasey_Posa\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "...ZzZ...Awake now and trying again.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying KearsleyAD\n",
      "trying KennediDiane\n",
      "trying KetteringU\n",
      "trying KidsPriority\n",
      "trying Kiki2720\n",
      "trying KodaPayne\n",
      "trying LGilkey3\n",
      "trying LHonestAvery\n",
      "trying LWVFA\n",
      "trying Leonard_Solano\n",
      "trying Leonspencer1\n",
      "trying Live4Gr8ness\n",
      "trying Lucci2x_\n",
      "trying MDOC_FOA_R6\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 429 Error (Rate Limit Exceeded)\n",
      "Retrying in 15 minutes...ZzZ...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying MIGlutenFreeGal\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "...ZzZ...Awake now and trying again.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying MMLakers\n",
      "trying MVincent810\n",
      "trying MakMichigan\n",
      "trying MarseilleAllen\n",
      "trying MattF810\n",
      "trying McLovinsTwin\n",
      "trying MindonGlory\n",
      "\"['id_str' 'screen_name' 'name' 'location' 'description' 'created_at'\\n 'friends_count' 'followers_count' 'statuses_count' 'favourites_count'] not in index\"\n",
      "trying MistaFLintastic\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 404 Error (Not Found)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying MonaHannaA\n",
      "trying MoneyBall_Sam\n",
      "\"['id_str' 'screen_name' 'name' 'location' 'description' 'created_at'\\n 'friends_count' 'followers_count' 'statuses_count' 'favourites_count'] not in index\"\n",
      "trying MoneyMusicHeart\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 404 Error (Not Found)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying Motivated_Icon\n",
      "trying MrAllinger\n",
      "trying NeuvooFlint\n",
      "\"['id_str' 'screen_name' 'name' 'location' 'description' 'created_at'\\n 'friends_count' 'followers_count' 'statuses_count' 'favourites_count'] not in index\"\n",
      "trying NotSafeToDrink\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 401 Error (Not Authorized)\n",
      "Encountered 429 Error (Rate Limit Exceeded)\n",
      "Retrying in 15 minutes...ZzZ...\n",
      "...ZzZ...Awake now and trying again.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying NotYourAvgSarah\n",
      "trying ProjectFWC\n",
      "trying QGroce\n",
      "trying RandyConat\n",
      "trying ReactionDJA\n",
      "trying Region6PTAC\n",
      "trying ReinvestFlint\n",
      "trying Rev__Church_Boy\n",
      "trying Rhas_Dukes\n",
      "trying RickThompsonTCC\n",
      "trying Rob810\n",
      "trying RobinInFlint\n",
      "trying RotatinMy_Tires\n",
      "trying SamandFamilyy\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 429 Error (Rate Limit Exceeded)\n",
      "Retrying in 15 minutes...ZzZ...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying SantinoGuerra\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "...ZzZ...Awake now and trying again.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying Shemy\n",
      "trying Simply_Jonny13\n",
      "trying SkytzoBeatz\n",
      "trying SloanMuseum\n",
      "trying SlopeTastic\n",
      "trying Spectacle_tv\n",
      "trying Stoneywoney23\n",
      "trying Supernova1177\n",
      "trying TGreene32\n",
      "trying THFtweets\n",
      "trying TeacherBeard\n",
      "trying TeamRevelationM\n",
      "trying TeeTee45thST\n",
      "trying ThaLadiesMan\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 429 Error (Rate Limit Exceeded)\n",
      "Retrying in 15 minutes...ZzZ...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying TheMarcusJones\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "...ZzZ...Awake now and trying again.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying The_X_Ray\n",
      "trying ThisIsSkyy\n",
      "trying ThomasJean\n",
      "trying TidesOfTheSun\n",
      "trying TreTaylorMusic\n",
      "trying TrendingFandG\n",
      "\"['id_str' 'screen_name' 'name' 'location' 'description' 'created_at'\\n 'friends_count' 'followers_count' 'statuses_count' 'favourites_count'] not in index\"\n",
      "trying Trillustrator\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 404 Error (Not Found)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying Tye_Mf_Allen\n",
      "trying UMFlint\n",
      "trying UWGeneseeCo\n",
      "trying UncleDepri\n",
      "trying VideoManJamal\n",
      "trying VoodooHoney\n",
      "trying WCRZFM\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 429 Error (Rate Limit Exceeded)\n",
      "Retrying in 15 minutes...ZzZ...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying WEYIKyle\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "...ZzZ...Awake now and trying again.\n",
      "Encountered 404 Error (Not Found)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\"['id_str' 'screen_name' 'name' 'location' 'description' 'created_at'\\n 'friends_count' 'followers_count' 'statuses_count' 'favourites_count'] not in index\"\n",
      "trying WeAreFlint\n",
      "trying Z927WDZZ\n",
      "trying _AfterSummer\n",
      "trying _HighlightReel2\n",
      "trying _ImFvmousHoe\n",
      "trying _JustSwangin\n",
      "trying _RAMONYEA\n",
      "trying _RJack1_\n",
      "trying __DKA\n",
      "trying __JayBenz\n",
      "\"['id_str' 'screen_name' 'name' 'location' 'description' 'created_at'\\n 'friends_count' 'followers_count' 'statuses_count' 'favourites_count'] not in index\"\n",
      "trying __mere02\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 404 Error (Not Found)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying _itsreallyher_\n",
      "trying _jayyd0ll\n",
      "\"['id_str' 'screen_name' 'name' 'location' 'description' 'created_at'\\n 'friends_count' 'followers_count' 'statuses_count' 'favourites_count'] not in index\"\n",
      "trying _ruizadrianna\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 404 Error (Not Found)\n",
      "Encountered 429 Error (Rate Limit Exceeded)\n",
      "Retrying in 15 minutes...ZzZ...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying _tiffmonique\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "...ZzZ...Awake now and trying again.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying agerald68\n",
      "trying ajl18_\n",
      "trying alliwant_isyou\n",
      "\"['id_str' 'screen_name' 'name' 'location' 'description' 'created_at'\\n 'friends_count' 'followers_count' 'statuses_count' 'favourites_count'] not in index\"\n",
      "trying alynb76\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 401 Error (Not Authorized)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying andrewspeaight\n",
      "trying arlrbrtsn\n",
      "trying banana1015radio\n",
      "trying bikermom2005\n",
      "trying br14n_70\n",
      "trying cacavaliers\n",
      "trying callmetavis\n",
      "trying car_rocky\n",
      "trying cdayflint\n",
      "trying cityofflintpr\n",
      "\"['id_str' 'screen_name' 'name' 'location' 'description' 'created_at'\\n 'friends_count' 'followers_count' 'statuses_count' 'favourites_count'] not in index\"\n",
      "trying deadlocke96\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 401 Error (Not Authorized)\n",
      "Encountered 429 Error (Rate Limit Exceeded)\n",
      "Retrying in 15 minutes...ZzZ...\n",
      "...ZzZ...Awake now and trying again.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying dessi_WORLD\n",
      "trying ernestoalaniz\n",
      "trying fieticeira\n",
      "\"['id_str' 'screen_name' 'name' 'location' 'description' 'created_at'\\n 'friends_count' 'followers_count' 'statuses_count' 'favourites_count'] not in index\"\n",
      "trying firsttrinitymbc\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 404 Error (Not Found)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying fixflintfirst1\n",
      "trying flintcitychurch\n",
      "trying flintlibrary\n",
      "trying flintsnewstalk\n",
      "trying flinttownboy\n",
      "trying fuck__Yu\n",
      "trying get_it_cocoa\n",
      "\"['id_str' 'screen_name' 'name' 'location' 'description' 'created_at'\\n 'friends_count' 'followers_count' 'statuses_count' 'favourites_count'] not in index\"\n",
      "trying gggouten\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 401 Error (Not Authorized)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying goodboi021\n",
      "trying gr8_bambino\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 429 Error (Rate Limit Exceeded)\n",
      "Retrying in 15 minutes...ZzZ...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying graysam13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "...ZzZ...Awake now and trying again.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying grigg_nancy\n",
      "trying grimringler\n",
      "trying ididsocnu\n",
      "trying itsA_Zthang\n",
      "trying itstravis\n",
      "trying jackfrizza\n",
      "trying janathanrobinso\n",
      "trying jaymarcellus\n",
      "trying jem181818\n",
      "\"['id_str' 'screen_name' 'name' 'location' 'description' 'created_at'\\n 'friends_count' 'followers_count' 'statuses_count' 'favourites_count'] not in index\"\n",
      "trying jesssssicab\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 404 Error (Not Found)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying kevinastarnes\n",
      "trying keysasmith\n",
      "trying kjchristian\n",
      "Twitter sent status 404 for URL: 1.1/users/lookup.json using parameters: (oauth_consumer_key=gWPAsZSr8Vff6oNEGIcZgA&oauth_nonce=13523515237202840127&oauth_signature_method=HMAC-SHA1&oauth_timestamp=1477294253&oauth_token=2184712454-gAtpJPWGyiGMjbqXz3S0ycmKqFMDPSyBAXutBub&oauth_version=1.0&user_id=%5B11245382%2C%2014096845%5D&oauth_signature=oz7O5iNVXt6fa1LOFBMIPuin2rM%3D)\n",
      "details: {'errors': [{'message': 'No user matches for specified terms.', 'code': 17}]}\n",
      "trying kurtneiswender\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 429 Error (Rate Limit Exceeded)\n",
      "Retrying in 15 minutes...ZzZ...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying ladytdiva1187\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "...ZzZ...Awake now and trying again.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying laylaymitchell_\n",
      "trying leftinflint\n",
      "trying magmagcity\n",
      "trying mariano411\n",
      "trying megisomeso\n",
      "trying mikenstephanie\n",
      "trying mona_haydar\n",
      "trying mottdean\n",
      "trying najladw\n",
      "trying nienie_strangep\n",
      "trying novaprime79\n",
      "trying orochiburenso\n",
      "trying overall3171\n",
      "trying p85rice\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 429 Error (Rate Limit Exceeded)\n",
      "Retrying in 15 minutes...ZzZ...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying pageiv\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "...ZzZ...Awake now and trying again.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying patandaj\n",
      "trying peoplevssnyder\n",
      "trying planetofboom\n",
      "trying rappolee\n",
      "trying ronfonger\n",
      "trying rubosuave\n",
      "\"['id_str' 'screen_name' 'name' 'location' 'description' 'created_at'\\n 'friends_count' 'followers_count' 'statuses_count' 'favourites_count'] not in index\"\n",
      "trying seonthompson\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 404 Error (Not Found)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying sexynacole\n",
      "trying sharrington2016\n",
      "trying simply1m3\n",
      "\"['id_str' 'screen_name' 'name' 'location' 'description' 'created_at'\\n 'friends_count' 'followers_count' 'statuses_count' 'favourites_count'] not in index\"\n",
      "trying smhodges4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 401 Error (Not Authorized)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying standupflint\n",
      "trying stevemintline\n",
      "trying swaydalyricist\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Encountered 429 Error (Rate Limit Exceeded)\n",
      "Retrying in 15 minutes...ZzZ...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying tammy_loren\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "...ZzZ...Awake now and trying again.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying tdgalbraith\n",
      "trying teenagev0w\n",
      "trying tenacitybrewing\n",
      "trying theTOMTOMSmusic\n",
      "trying whitingflint\n",
      "trying xojassx\n",
      "trying yrnmg\n",
      "trying zachizz1476\n"
     ]
    }
   ],
   "source": [
    "import twitter as t\n",
    "from functools import partial\n",
    "import sys, time\n",
    "#friends = {}\n",
    "#auth = t.oauth.OAuth(\"\", \"\", \"\", \"\")\n",
    "#twitter_api = t.Twitter(auth=auth)\n",
    "for i,u in enumerate(f2):\n",
    "    print(i+j,'trying',u)\n",
    "    try:\n",
    "        friends[u] = get_friends(u,twitter_api)\n",
    "    except Exception as e:\n",
    "        print(e)\n",
    "        continue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "from nltk.sentiment.vader import SentimentIntensityAnalyzer\n",
    "sid = SentimentIntensityAnalyzer()\n",
    "\n",
    "ff = pd.concat(friends.values(), keys=friends.keys(),names=['flinter'])\n",
    "#ff.to_csv('../data/ff.csv')\n",
    "fr = ff.screen_name.unique()\n",
    "sents = pd.DataFrame(list(df[df.screen_name.isin(fr)].text.apply(sid.polarity_scores)))['compound']\n",
    "fs = pd.concat([df[df.screen_name.isin(fr)].screen_name.reset_index(), sents],axis=1,ignore_index=True)\n",
    "fs.columns = ['twid','screen_name','cmpnd']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "101 115\n"
     ]
    }
   ],
   "source": [
    "ffdf = pd.read_csv('../data/ffdf.csv')\n",
    "ffdf.columns = ['screen_name'] + list(ffdf.columns[1:])\n",
    "#ffdf.head() #fsent is missing\n",
    "print(len(ffdf[ffdf.usent>0]),len(ffdf[ffdf.usent<0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
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       "      <th>AmourNiyy_</th>\n",
       "      <td>4</td>\n",
       "      <td>0.411850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AmylHovey</th>\n",
       "      <td>8</td>\n",
       "      <td>0.001463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AnthonyWJRT</th>\n",
       "      <td>14</td>\n",
       "      <td>-0.036036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AqueousEye</th>\n",
       "      <td>6</td>\n",
       "      <td>0.552383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Area72ENT</th>\n",
       "      <td>5</td>\n",
       "      <td>0.362420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AsmoovMF</th>\n",
       "      <td>5</td>\n",
       "      <td>-0.255680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DJJayBig</th>\n",
       "      <td>5</td>\n",
       "      <td>0.123320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DaHoodsOrnament</th>\n",
       "      <td>12</td>\n",
       "      <td>-0.212075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DannyDeadhack</th>\n",
       "      <td>9</td>\n",
       "      <td>0.338244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DerekDohrman</th>\n",
       "      <td>3</td>\n",
       "      <td>-0.026333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DesireeDuell</th>\n",
       "      <td>5</td>\n",
       "      <td>0.478120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Domanyce_Da_1</th>\n",
       "      <td>16</td>\n",
       "      <td>0.069812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DortEventCenter</th>\n",
       "      <td>5</td>\n",
       "      <td>0.519600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DoubtingTomFYI</th>\n",
       "      <td>14</td>\n",
       "      <td>0.057836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DylanLuna1931</th>\n",
       "      <td>10</td>\n",
       "      <td>0.049650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EmilyDoerr</th>\n",
       "      <td>7</td>\n",
       "      <td>0.379657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EricRob229</th>\n",
       "      <td>5</td>\n",
       "      <td>-0.169580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EzE_2o11_</th>\n",
       "      <td>3</td>\n",
       "      <td>0.031433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FYINation</th>\n",
       "      <td>10</td>\n",
       "      <td>-0.040650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FaithGiddings2</th>\n",
       "      <td>5</td>\n",
       "      <td>-0.126800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FiggaDaKID</th>\n",
       "      <td>14</td>\n",
       "      <td>-0.187557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mona_haydar</th>\n",
       "      <td>7</td>\n",
       "      <td>-0.082043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mottdean</th>\n",
       "      <td>4</td>\n",
       "      <td>-0.037375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>najladw</th>\n",
       "      <td>4</td>\n",
       "      <td>0.075150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nienie_strangep</th>\n",
       "      <td>4</td>\n",
       "      <td>-0.157050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>novaprime79</th>\n",
       "      <td>13</td>\n",
       "      <td>0.234992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orochiburenso</th>\n",
       "      <td>5</td>\n",
       "      <td>-0.125580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>overall3171</th>\n",
       "      <td>8</td>\n",
       "      <td>-0.020588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>p85rice</th>\n",
       "      <td>11</td>\n",
       "      <td>-0.166100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pageiv</th>\n",
       "      <td>3</td>\n",
       "      <td>0.277000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>patandaj</th>\n",
       "      <td>13</td>\n",
       "      <td>-0.118046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>peoplevssnyder</th>\n",
       "      <td>4</td>\n",
       "      <td>0.199250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>planetofboom</th>\n",
       "      <td>19</td>\n",
       "      <td>0.049321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rappolee</th>\n",
       "      <td>9</td>\n",
       "      <td>-0.013789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ronfonger</th>\n",
       "      <td>16</td>\n",
       "      <td>-0.342650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>seonthompson</th>\n",
       "      <td>3</td>\n",
       "      <td>0.743100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sexynacole</th>\n",
       "      <td>6</td>\n",
       "      <td>0.711350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sharrington2016</th>\n",
       "      <td>3</td>\n",
       "      <td>0.320367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>smhodges4</th>\n",
       "      <td>9</td>\n",
       "      <td>-0.195844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>standupflint</th>\n",
       "      <td>12</td>\n",
       "      <td>0.140400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stevemintline</th>\n",
       "      <td>8</td>\n",
       "      <td>0.102813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>swaydalyricist</th>\n",
       "      <td>5</td>\n",
       "      <td>0.178440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tammy_loren</th>\n",
       "      <td>19</td>\n",
       "      <td>0.023889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tdgalbraith</th>\n",
       "      <td>5</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>teenagev0w</th>\n",
       "      <td>3</td>\n",
       "      <td>-0.290533</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tenacitybrewing</th>\n",
       "      <td>3</td>\n",
       "      <td>-0.058700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>theTOMTOMSmusic</th>\n",
       "      <td>4</td>\n",
       "      <td>0.281325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>whitingflint</th>\n",
       "      <td>4</td>\n",
       "      <td>0.463100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>xojassx</th>\n",
       "      <td>6</td>\n",
       "      <td>-0.029650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yrnmg</th>\n",
       "      <td>3</td>\n",
       "      <td>0.323100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zachizz1476</th>\n",
       "      <td>5</td>\n",
       "      <td>0.066800</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>223 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 utwcnt     usent\n",
       "1Goal1Passion         7  0.096586\n",
       "1_namillionme37      10 -0.215550\n",
       "810DIRTVILLE          4  0.000000\n",
       "AD16Gaming            6  0.128550\n",
       "AdamBiggers81         8  0.315200\n",
       "AliciaRoose           6  0.078383\n",
       "AllahnaSteve          3 -0.467833\n",
       "AmandaEmeryNews      19 -0.415800\n",
       "Americans4Flint       5  0.265980\n",
       "AmourNiyy_            4  0.411850\n",
       "AmylHovey             8  0.001463\n",
       "AnthonyWJRT          14 -0.036036\n",
       "AqueousEye            6  0.552383\n",
       "Area72ENT             5  0.362420\n",
       "AsmoovMF              5 -0.255680\n",
       "DJJayBig              5  0.123320\n",
       "DaHoodsOrnament      12 -0.212075\n",
       "DannyDeadhack         9  0.338244\n",
       "DerekDohrman          3 -0.026333\n",
       "DesireeDuell          5  0.478120\n",
       "Domanyce_Da_1        16  0.069812\n",
       "DortEventCenter       5  0.519600\n",
       "DoubtingTomFYI       14  0.057836\n",
       "DylanLuna1931        10  0.049650\n",
       "EmilyDoerr            7  0.379657\n",
       "EricRob229            5 -0.169580\n",
       "EzE_2o11_             3  0.031433\n",
       "FYINation            10 -0.040650\n",
       "FaithGiddings2        5 -0.126800\n",
       "FiggaDaKID           14 -0.187557\n",
       "...                 ...       ...\n",
       "mona_haydar           7 -0.082043\n",
       "mottdean              4 -0.037375\n",
       "najladw               4  0.075150\n",
       "nienie_strangep       4 -0.157050\n",
       "novaprime79          13  0.234992\n",
       "orochiburenso         5 -0.125580\n",
       "overall3171           8 -0.020588\n",
       "p85rice              11 -0.166100\n",
       "pageiv                3  0.277000\n",
       "patandaj             13 -0.118046\n",
       "peoplevssnyder        4  0.199250\n",
       "planetofboom         19  0.049321\n",
       "rappolee              9 -0.013789\n",
       "ronfonger            16 -0.342650\n",
       "seonthompson          3  0.743100\n",
       "sexynacole            6  0.711350\n",
       "sharrington2016       3  0.320367\n",
       "smhodges4             9 -0.195844\n",
       "standupflint         12  0.140400\n",
       "stevemintline         8  0.102813\n",
       "swaydalyricist        5  0.178440\n",
       "tammy_loren          19  0.023889\n",
       "tdgalbraith           5  0.000000\n",
       "teenagev0w            3 -0.290533\n",
       "tenacitybrewing       3 -0.058700\n",
       "theTOMTOMSmusic       4  0.281325\n",
       "whitingflint          4  0.463100\n",
       "xojassx               6 -0.029650\n",
       "yrnmg                 3  0.323100\n",
       "zachizz1476           5  0.066800\n",
       "\n",
       "[223 rows x 2 columns]"
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "udf = {}\n",
    "for u in ffdf.index.values:\n",
    "    usent = pd.DataFrame(list(df[df.screen_name == u].text.apply(sid.polarity_scores)))['compound']\n",
    "    udf[u] = {'utwcnt':len(usent),'usent':usent.mean()}\n",
    "usdf = pd.DataFrame.from_dict(udf,orient='index')\n",
    "usdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": 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>fsent</th>\n",
       "      <th>tfcnt</th>\n",
       "      <th>ftwcnt</th>\n",
       "      <th>dfcnt</th>\n",
       "      <th>utwcnt</th>\n",
       "      <th>usent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1Goal1Passion</th>\n",
       "      <td>-0.118901</td>\n",
       "      <td>505</td>\n",
       "      <td>2330</td>\n",
       "      <td>124</td>\n",
       "      <td>7</td>\n",
       "      <td>0.096586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1_namillionme37</th>\n",
       "      <td>-0.154041</td>\n",
       "      <td>634</td>\n",
       "      <td>458</td>\n",
       "      <td>37</td>\n",
       "      <td>10</td>\n",
       "      <td>-0.215550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>810DIRTVILLE</th>\n",
       "      <td>-0.050515</td>\n",
       "      <td>987</td>\n",
       "      <td>2607</td>\n",
       "      <td>86</td>\n",
       "      <td>4</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AD16Gaming</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>53</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>0.128550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AdamBiggers81</th>\n",
       "      <td>-0.082383</td>\n",
       "      <td>1327</td>\n",
       "      <td>1219</td>\n",
       "      <td>154</td>\n",
       "      <td>8</td>\n",
       "      <td>0.315200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AliciaRoose</th>\n",
       "      <td>-0.096432</td>\n",
       "      <td>918</td>\n",
       "      <td>319</td>\n",
       "      <td>44</td>\n",
       "      <td>6</td>\n",
       "      <td>0.078383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AllahnaSteve</th>\n",
       "      <td>-0.081462</td>\n",
       "      <td>70</td>\n",
       "      <td>50</td>\n",
       "      <td>19</td>\n",
       "      <td>3</td>\n",
       "      <td>-0.467833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AmandaEmeryNews</th>\n",
       "      <td>-0.103015</td>\n",
       "      <td>468</td>\n",
       "      <td>3682</td>\n",
       "      <td>197</td>\n",
       "      <td>19</td>\n",
       "      <td>-0.415800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Americans4Flint</th>\n",
       "      <td>-0.097908</td>\n",
       "      <td>354</td>\n",
       "      <td>3374</td>\n",
       "      <td>90</td>\n",
       "      <td>5</td>\n",
       "      <td>0.265980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AmourNiyy_</th>\n",
       "      <td>-0.043152</td>\n",
       "      <td>265</td>\n",
       "      <td>148</td>\n",
       "      <td>41</td>\n",
       "      <td>4</td>\n",
       "      <td>0.411850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AmylHovey</th>\n",
       "      <td>-0.073058</td>\n",
       "      <td>422</td>\n",
       "      <td>2684</td>\n",
       "      <td>166</td>\n",
       "      <td>8</td>\n",
       "      <td>0.001463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AnthonyWJRT</th>\n",
       "      <td>-0.127652</td>\n",
       "      <td>260</td>\n",
       "      <td>2542</td>\n",
       "      <td>94</td>\n",
       "      <td>14</td>\n",
       "      <td>-0.036036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AqueousEye</th>\n",
       "      <td>-0.116753</td>\n",
       "      <td>85</td>\n",
       "      <td>514</td>\n",
       "      <td>24</td>\n",
       "      <td>6</td>\n",
       "      <td>0.552383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Area72ENT</th>\n",
       "      <td>-0.137371</td>\n",
       "      <td>343</td>\n",
       "      <td>214</td>\n",
       "      <td>39</td>\n",
       "      <td>5</td>\n",
       "      <td>0.362420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AsmoovMF</th>\n",
       "      <td>-0.068034</td>\n",
       "      <td>191</td>\n",
       "      <td>282</td>\n",
       "      <td>57</td>\n",
       "      <td>5</td>\n",
       "      <td>-0.255680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DJJayBig</th>\n",
       "      <td>-0.045407</td>\n",
       "      <td>4900</td>\n",
       "      <td>943</td>\n",
       "      <td>343</td>\n",
       "      <td>5</td>\n",
       "      <td>0.123320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DaHoodsOrnament</th>\n",
       "      <td>-0.081913</td>\n",
       "      <td>3396</td>\n",
       "      <td>12086</td>\n",
       "      <td>157</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.212075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DannyDeadhack</th>\n",
       "      <td>-0.060800</td>\n",
       "      <td>1078</td>\n",
       "      <td>1591</td>\n",
       "      <td>146</td>\n",
       "      <td>9</td>\n",
       "      <td>0.338244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DerekDohrman</th>\n",
       "      <td>-0.097318</td>\n",
       "      <td>335</td>\n",
       "      <td>579</td>\n",
       "      <td>48</td>\n",
       "      <td>3</td>\n",
       "      <td>-0.026333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DesireeDuell</th>\n",
       "      <td>-0.103413</td>\n",
       "      <td>2000</td>\n",
       "      <td>21260</td>\n",
       "      <td>364</td>\n",
       "      <td>5</td>\n",
       "      <td>0.478120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Domanyce_Da_1</th>\n",
       "      <td>-0.072672</td>\n",
       "      <td>1090</td>\n",
       "      <td>521</td>\n",
       "      <td>98</td>\n",
       "      <td>16</td>\n",
       "      <td>0.069812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DortEventCenter</th>\n",
       "      <td>-0.070818</td>\n",
       "      <td>511</td>\n",
       "      <td>2093</td>\n",
       "      <td>127</td>\n",
       "      <td>5</td>\n",
       "      <td>0.519600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DoubtingTomFYI</th>\n",
       "      <td>-0.189894</td>\n",
       "      <td>1107</td>\n",
       "      <td>6066</td>\n",
       "      <td>454</td>\n",
       "      <td>14</td>\n",
       "      <td>0.057836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DylanLuna1931</th>\n",
       "      <td>-0.068016</td>\n",
       "      <td>766</td>\n",
       "      <td>1890</td>\n",
       "      <td>139</td>\n",
       "      <td>10</td>\n",
       "      <td>0.049650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EmilyDoerr</th>\n",
       "      <td>-0.067301</td>\n",
       "      <td>1139</td>\n",
       "      <td>3705</td>\n",
       "      <td>263</td>\n",
       "      <td>7</td>\n",
       "      <td>0.379657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EricRob229</th>\n",
       "      <td>-0.171226</td>\n",
       "      <td>205</td>\n",
       "      <td>325</td>\n",
       "      <td>18</td>\n",
       "      <td>5</td>\n",
       "      <td>-0.169580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EzE_2o11_</th>\n",
       "      <td>-0.109453</td>\n",
       "      <td>446</td>\n",
       "      <td>327</td>\n",
       "      <td>23</td>\n",
       "      <td>3</td>\n",
       "      <td>0.031433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FYINation</th>\n",
       "      <td>-0.128731</td>\n",
       "      <td>51</td>\n",
       "      <td>193</td>\n",
       "      <td>25</td>\n",
       "      <td>10</td>\n",
       "      <td>-0.040650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FaithGiddings2</th>\n",
       "      <td>-0.092667</td>\n",
       "      <td>246</td>\n",
       "      <td>1734</td>\n",
       "      <td>60</td>\n",
       "      <td>5</td>\n",
       "      <td>-0.126800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FiggaDaKID</th>\n",
       "      <td>-0.055347</td>\n",
       "      <td>752</td>\n",
       "      <td>600</td>\n",
       "      <td>112</td>\n",
       "      <td>14</td>\n",
       "      <td>-0.187557</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mona_haydar</th>\n",
       "      <td>-0.093202</td>\n",
       "      <td>414</td>\n",
       "      <td>1482</td>\n",
       "      <td>107</td>\n",
       "      <td>7</td>\n",
       "      <td>-0.082043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mottdean</th>\n",
       "      <td>-0.097917</td>\n",
       "      <td>363</td>\n",
       "      <td>669</td>\n",
       "      <td>34</td>\n",
       "      <td>4</td>\n",
       "      <td>-0.037375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>najladw</th>\n",
       "      <td>-0.121085</td>\n",
       "      <td>904</td>\n",
       "      <td>1378</td>\n",
       "      <td>117</td>\n",
       "      <td>4</td>\n",
       "      <td>0.075150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nienie_strangep</th>\n",
       "      <td>-0.222324</td>\n",
       "      <td>419</td>\n",
       "      <td>715</td>\n",
       "      <td>67</td>\n",
       "      <td>4</td>\n",
       "      <td>-0.157050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>novaprime79</th>\n",
       "      <td>-0.291021</td>\n",
       "      <td>63</td>\n",
       "      <td>62</td>\n",
       "      <td>8</td>\n",
       "      <td>13</td>\n",
       "      <td>0.234992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orochiburenso</th>\n",
       "      <td>-0.020238</td>\n",
       "      <td>344</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>-0.125580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>overall3171</th>\n",
       "      <td>-0.168117</td>\n",
       "      <td>448</td>\n",
       "      <td>407</td>\n",
       "      <td>65</td>\n",
       "      <td>8</td>\n",
       "      <td>-0.020588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>p85rice</th>\n",
       "      <td>-0.085477</td>\n",
       "      <td>1108</td>\n",
       "      <td>305</td>\n",
       "      <td>60</td>\n",
       "      <td>11</td>\n",
       "      <td>-0.166100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pageiv</th>\n",
       "      <td>-0.114743</td>\n",
       "      <td>613</td>\n",
       "      <td>3945</td>\n",
       "      <td>150</td>\n",
       "      <td>3</td>\n",
       "      <td>0.277000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>patandaj</th>\n",
       "      <td>-0.061967</td>\n",
       "      <td>944</td>\n",
       "      <td>803</td>\n",
       "      <td>85</td>\n",
       "      <td>13</td>\n",
       "      <td>-0.118046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>peoplevssnyder</th>\n",
       "      <td>-0.029003</td>\n",
       "      <td>34</td>\n",
       "      <td>749</td>\n",
       "      <td>17</td>\n",
       "      <td>4</td>\n",
       "      <td>0.199250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>planetofboom</th>\n",
       "      <td>-0.155146</td>\n",
       "      <td>161</td>\n",
       "      <td>383</td>\n",
       "      <td>23</td>\n",
       "      <td>19</td>\n",
       "      <td>0.049321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rappolee</th>\n",
       "      <td>-0.170460</td>\n",
       "      <td>432</td>\n",
       "      <td>283</td>\n",
       "      <td>36</td>\n",
       "      <td>9</td>\n",
       "      <td>-0.013789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ronfonger</th>\n",
       "      <td>-0.098598</td>\n",
       "      <td>876</td>\n",
       "      <td>6638</td>\n",
       "      <td>263</td>\n",
       "      <td>16</td>\n",
       "      <td>-0.342650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>seonthompson</th>\n",
       "      <td>-0.140791</td>\n",
       "      <td>1381</td>\n",
       "      <td>811</td>\n",
       "      <td>109</td>\n",
       "      <td>3</td>\n",
       "      <td>0.743100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sexynacole</th>\n",
       "      <td>-0.083383</td>\n",
       "      <td>243</td>\n",
       "      <td>116</td>\n",
       "      <td>23</td>\n",
       "      <td>6</td>\n",
       "      <td>0.711350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sharrington2016</th>\n",
       "      <td>-0.059061</td>\n",
       "      <td>104</td>\n",
       "      <td>1031</td>\n",
       "      <td>33</td>\n",
       "      <td>3</td>\n",
       "      <td>0.320367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>smhodges4</th>\n",
       "      <td>-0.105832</td>\n",
       "      <td>1143</td>\n",
       "      <td>6310</td>\n",
       "      <td>269</td>\n",
       "      <td>9</td>\n",
       "      <td>-0.195844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>standupflint</th>\n",
       "      <td>-0.086806</td>\n",
       "      <td>442</td>\n",
       "      <td>8344</td>\n",
       "      <td>285</td>\n",
       "      <td>12</td>\n",
       "      <td>0.140400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stevemintline</th>\n",
       "      <td>-0.088749</td>\n",
       "      <td>270</td>\n",
       "      <td>2122</td>\n",
       "      <td>104</td>\n",
       "      <td>8</td>\n",
       "      <td>0.102813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>swaydalyricist</th>\n",
       "      <td>-0.137180</td>\n",
       "      <td>822</td>\n",
       "      <td>86</td>\n",
       "      <td>22</td>\n",
       "      <td>5</td>\n",
       "      <td>0.178440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tammy_loren</th>\n",
       "      <td>-0.074358</td>\n",
       "      <td>257</td>\n",
       "      <td>4216</td>\n",
       "      <td>113</td>\n",
       "      <td>19</td>\n",
       "      <td>0.023889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tdgalbraith</th>\n",
       "      <td>-0.113630</td>\n",
       "      <td>62</td>\n",
       "      <td>326</td>\n",
       "      <td>24</td>\n",
       "      <td>5</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>teenagev0w</th>\n",
       "      <td>-0.064114</td>\n",
       "      <td>748</td>\n",
       "      <td>450</td>\n",
       "      <td>30</td>\n",
       "      <td>3</td>\n",
       "      <td>-0.290533</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tenacitybrewing</th>\n",
       "      <td>-0.061528</td>\n",
       "      <td>1202</td>\n",
       "      <td>2968</td>\n",
       "      <td>258</td>\n",
       "      <td>3</td>\n",
       "      <td>-0.058700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>theTOMTOMSmusic</th>\n",
       "      <td>-0.007381</td>\n",
       "      <td>595</td>\n",
       "      <td>296</td>\n",
       "      <td>59</td>\n",
       "      <td>4</td>\n",
       "      <td>0.281325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>whitingflint</th>\n",
       "      <td>-0.040434</td>\n",
       "      <td>436</td>\n",
       "      <td>3165</td>\n",
       "      <td>151</td>\n",
       "      <td>4</td>\n",
       "      <td>0.463100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>xojassx</th>\n",
       "      <td>-0.068348</td>\n",
       "      <td>1269</td>\n",
       "      <td>972</td>\n",
       "      <td>334</td>\n",
       "      <td>6</td>\n",
       "      <td>-0.029650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yrnmg</th>\n",
       "      <td>-0.097200</td>\n",
       "      <td>1146</td>\n",
       "      <td>736</td>\n",
       "      <td>132</td>\n",
       "      <td>3</td>\n",
       "      <td>0.323100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zachizz1476</th>\n",
       "      <td>0.139836</td>\n",
       "      <td>27</td>\n",
       "      <td>25</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>0.066800</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>223 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    fsent  tfcnt  ftwcnt  dfcnt  utwcnt     usent\n",
       "1Goal1Passion   -0.118901    505    2330    124       7  0.096586\n",
       "1_namillionme37 -0.154041    634     458     37      10 -0.215550\n",
       "810DIRTVILLE    -0.050515    987    2607     86       4  0.000000\n",
       "AD16Gaming       0.000000     53       1      1       6  0.128550\n",
       "AdamBiggers81   -0.082383   1327    1219    154       8  0.315200\n",
       "AliciaRoose     -0.096432    918     319     44       6  0.078383\n",
       "AllahnaSteve    -0.081462     70      50     19       3 -0.467833\n",
       "AmandaEmeryNews -0.103015    468    3682    197      19 -0.415800\n",
       "Americans4Flint -0.097908    354    3374     90       5  0.265980\n",
       "AmourNiyy_      -0.043152    265     148     41       4  0.411850\n",
       "AmylHovey       -0.073058    422    2684    166       8  0.001463\n",
       "AnthonyWJRT     -0.127652    260    2542     94      14 -0.036036\n",
       "AqueousEye      -0.116753     85     514     24       6  0.552383\n",
       "Area72ENT       -0.137371    343     214     39       5  0.362420\n",
       "AsmoovMF        -0.068034    191     282     57       5 -0.255680\n",
       "DJJayBig        -0.045407   4900     943    343       5  0.123320\n",
       "DaHoodsOrnament -0.081913   3396   12086    157      12 -0.212075\n",
       "DannyDeadhack   -0.060800   1078    1591    146       9  0.338244\n",
       "DerekDohrman    -0.097318    335     579     48       3 -0.026333\n",
       "DesireeDuell    -0.103413   2000   21260    364       5  0.478120\n",
       "Domanyce_Da_1   -0.072672   1090     521     98      16  0.069812\n",
       "DortEventCenter -0.070818    511    2093    127       5  0.519600\n",
       "DoubtingTomFYI  -0.189894   1107    6066    454      14  0.057836\n",
       "DylanLuna1931   -0.068016    766    1890    139      10  0.049650\n",
       "EmilyDoerr      -0.067301   1139    3705    263       7  0.379657\n",
       "EricRob229      -0.171226    205     325     18       5 -0.169580\n",
       "EzE_2o11_       -0.109453    446     327     23       3  0.031433\n",
       "FYINation       -0.128731     51     193     25      10 -0.040650\n",
       "FaithGiddings2  -0.092667    246    1734     60       5 -0.126800\n",
       "FiggaDaKID      -0.055347    752     600    112      14 -0.187557\n",
       "...                   ...    ...     ...    ...     ...       ...\n",
       "mona_haydar     -0.093202    414    1482    107       7 -0.082043\n",
       "mottdean        -0.097917    363     669     34       4 -0.037375\n",
       "najladw         -0.121085    904    1378    117       4  0.075150\n",
       "nienie_strangep -0.222324    419     715     67       4 -0.157050\n",
       "novaprime79     -0.291021     63      62      8      13  0.234992\n",
       "orochiburenso   -0.020238    344       8      7       5 -0.125580\n",
       "overall3171     -0.168117    448     407     65       8 -0.020588\n",
       "p85rice         -0.085477   1108     305     60      11 -0.166100\n",
       "pageiv          -0.114743    613    3945    150       3  0.277000\n",
       "patandaj        -0.061967    944     803     85      13 -0.118046\n",
       "peoplevssnyder  -0.029003     34     749     17       4  0.199250\n",
       "planetofboom    -0.155146    161     383     23      19  0.049321\n",
       "rappolee        -0.170460    432     283     36       9 -0.013789\n",
       "ronfonger       -0.098598    876    6638    263      16 -0.342650\n",
       "seonthompson    -0.140791   1381     811    109       3  0.743100\n",
       "sexynacole      -0.083383    243     116     23       6  0.711350\n",
       "sharrington2016 -0.059061    104    1031     33       3  0.320367\n",
       "smhodges4       -0.105832   1143    6310    269       9 -0.195844\n",
       "standupflint    -0.086806    442    8344    285      12  0.140400\n",
       "stevemintline   -0.088749    270    2122    104       8  0.102813\n",
       "swaydalyricist  -0.137180    822      86     22       5  0.178440\n",
       "tammy_loren     -0.074358    257    4216    113      19  0.023889\n",
       "tdgalbraith     -0.113630     62     326     24       5  0.000000\n",
       "teenagev0w      -0.064114    748     450     30       3 -0.290533\n",
       "tenacitybrewing -0.061528   1202    2968    258       3 -0.058700\n",
       "theTOMTOMSmusic -0.007381    595     296     59       4  0.281325\n",
       "whitingflint    -0.040434    436    3165    151       4  0.463100\n",
       "xojassx         -0.068348   1269     972    334       6 -0.029650\n",
       "yrnmg           -0.097200   1146     736    132       3  0.323100\n",
       "zachizz1476      0.139836     27      25      5       5  0.066800\n",
       "\n",
       "[223 rows x 6 columns]"
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fdf = {}\n",
    "for k,v in friends.items():\n",
    "    fsk = fs[fs.screen_name.isin(v.screen_name)]\n",
    "    fsent = fsk.cmpnd.mean()\n",
    "    fdf[k] = {'ftwcnt':len(fsk),'dfcnt':len(fsk.screen_name.unique()),'tfcnt':len(v),'fsent':fsent}\n",
    "ffdf = pd.DataFrame.from_dict(fdf,orient='index')\n",
    "ffdf = ffdf.join(usdf)\n",
    "#ffdf.to_csv('../data/ffdf.csv')\n",
    "ffdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(122953, 8339)"
      ]
     },
     "execution_count": 207,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(fr),df[df.screen_name.isin(fr)].screen_name.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "101 115 15 206\n"
     ]
    }
   ],
   "source": [
    "print(len(ffdf[ffdf.usent>0]),len(ffdf[ffdf.usent<0]),len(ffdf[ffdf.fsent>0]),len(ffdf[ffdf.fsent<0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": 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>fsent</th>\n",
       "      <th>tfcnt</th>\n",
       "      <th>ftwcnt</th>\n",
       "      <th>dfcnt</th>\n",
       "      <th>utwcnt</th>\n",
       "      <th>usent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>fsent</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.041997</td>\n",
       "      <td>-0.011399</td>\n",
       "      <td>0.044034</td>\n",
       "      <td>-0.128727</td>\n",
       "      <td>0.161092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tfcnt</th>\n",
       "      <td>-0.041997</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.150289</td>\n",
       "      <td>0.588166</td>\n",
       "      <td>0.023542</td>\n",
       "      <td>-0.076660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ftwcnt</th>\n",
       "      <td>-0.011399</td>\n",
       "      <td>0.150289</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.487535</td>\n",
       "      <td>0.185268</td>\n",
       "      <td>-0.001390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dfcnt</th>\n",
       "      <td>0.044034</td>\n",
       "      <td>0.588166</td>\n",
       "      <td>0.487535</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.094961</td>\n",
       "      <td>0.030336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>utwcnt</th>\n",
       "      <td>-0.128727</td>\n",
       "      <td>0.023542</td>\n",
       "      <td>0.185268</td>\n",
       "      <td>0.094961</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.108274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>usent</th>\n",
       "      <td>0.161092</td>\n",
       "      <td>-0.076660</td>\n",
       "      <td>-0.001390</td>\n",
       "      <td>0.030336</td>\n",
       "      <td>-0.108274</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           fsent     tfcnt    ftwcnt     dfcnt    utwcnt     usent\n",
       "fsent   1.000000 -0.041997 -0.011399  0.044034 -0.128727  0.161092\n",
       "tfcnt  -0.041997  1.000000  0.150289  0.588166  0.023542 -0.076660\n",
       "ftwcnt -0.011399  0.150289  1.000000  0.487535  0.185268 -0.001390\n",
       "dfcnt   0.044034  0.588166  0.487535  1.000000  0.094961  0.030336\n",
       "utwcnt -0.128727  0.023542  0.185268  0.094961  1.000000 -0.108274\n",
       "usent   0.161092 -0.076660 -0.001390  0.030336 -0.108274  1.000000"
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ffdf.corr(method='pearson') #.loc['fsent','usent'] = .16"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.074941076829484934, -0.10539607280382769)"
      ]
     },
     "execution_count": 211,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ffdf[ffdf.usent>0].fsent.mean(),ffdf[ffdf.usent<0].fsent.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-0.105396072804 -0.0749410768295\n"
     ]
    },
    {
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GbPnq13e57S94tOp8OjR48QHx8vOzHj5s2bmDVrFmbPnl0h3wGi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\nAJga9fzu/BNLAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x124275ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "colorm = dict(boxes='lightgreen', whiskers='black', medians='black', caps='black')\n",
    "#ax=compare[['followers','population']].plot(kind='box', patch_artist=True, showfliers=False)\n",
    "boxprops = dict(linestyle='-', color='black')\n",
    "\n",
    "matplotlib.style.use('ggplot')\n",
    "plt.rcParams['axes.facecolor']='w'\n",
    "plt.rcParams['savefig.facecolor']='w'\n",
    "matplotlib.rcParams['xtick.labelsize'] = 20\n",
    "matplotlib.rcParams['ytick.labelsize'] = 18\n",
    "matplotlib.rcParams['axes.titlesize'] = 14\n",
    "\n",
    "co = {'color':'black'}\n",
    "ma = {'color':'black','linestyle':'-'}\n",
    "\n",
    "plt.figure(figsize=(9,3))\n",
    "cohort = ffdf[ffdf.usent<0].fsent #ffdf[ffdf.fsent<0].usent \n",
    "control= ffdf[ffdf.usent>0].fsent.dropna() #ffdf[ffdf.fsent>0].usent\n",
    "print(cohort.mean(),control.mean())\n",
    "bp = plt.boxplot([cohort,control],patch_artist=True, showfliers=False,\n",
    "                 whiskerprops=co,capprops=co,medianprops=ma,boxprops=boxprops,labels=['Friends of the cohort','Friends of the control'])\n",
    "\n",
    "ax = plt.gca()\n",
    "for patch, color in zip(bp['boxes'], ['magenta','lightgreen']):\n",
    "    patch.set_facecolor(color)\n",
    "ax.set_ylabel('Sentiment score',fontsize=22)\n",
    "ax.set_ylim(-.23,.08)\n",
    "#plt.yticks(np.arange(-.6, .6, .1))\n",
    "ax.yaxis.grid(True, linestyle='-', which='major', color='lightgrey', alpha=0.5)\n",
    "ax.get_figure().savefig('../figs/contagion-exp2.pdf', bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ks_2sampResult(statistic=0.37184466019417473, pvalue=0.030545168312102647)\n",
      "Critical value D_a (ks statistic (D) should be greater than this): 0.3637104720012413\n"
     ]
    }
   ],
   "source": [
    "from scipy.stats import ks_2samp\n",
    "from math import sqrt\n",
    "c_a = 1.36 #coefficient c_a is 1.36 for alpha 0.05 and 1.95 for alpha 0.001\n",
    "print(ks_2samp(ffdf[ffdf.fsent<0].usent,ffdf[ffdf.fsent>0].usent))\n",
    "n1 = len(ffdf[ffdf.fsent<0])\n",
    "n2 = len(ffdf[ffdf.fsent>0])\n",
    "print('Critical value D_a (ks statistic (D) should be greater than this):',c_a*sqrt((n1+n2)/(n1*n2)))\n",
    "#that is the case for 95% confidence level: https://daithiocrualaoich.github.io/kolmogorov_smirnov/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ks_2sampResult(statistic=0.20619888075764092, pvalue=0.01743249763074449)\n",
      "Critical value D_a (ks statistic (D) should be greater than this): 0.1854625286897552\n"
     ]
    }
   ],
   "source": [
    "from scipy.stats import ks_2samp\n",
    "from math import sqrt\n",
    "c_a = 1.36 #coefficient c_a is 1.36 for alpha 0.05 and 1.95 for alpha 0.001\n",
    "print(ks_2samp(ffdf[ffdf.usent<0].fsent,ffdf[ffdf.usent>0].fsent))\n",
    "n1 = len(ffdf[ffdf.usent<0])\n",
    "n2 = len(ffdf[ffdf.usent>0])\n",
    "print('Critical value D_a (ks statistic (D) should be greater than this):',c_a*sqrt((n1+n2)/(n1*n2)))\n",
    "#that is the case for 95% confidence level: https://daithiocrualaoich.github.io/kolmogorov_smirnov/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": true,
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "def get_friends(screen_name,twitter_api,limit=5000):\n",
    "    get_followers_ids = partial(make_twitter_request,twitter_api.friends.ids, count=5000)\n",
    "    ids = []\n",
    "\n",
    "    cursor = -1\n",
    "    while cursor != 0:\n",
    "        response = get_followers_ids(screen_name=screen_name, cursor=cursor)\n",
    "\n",
    "        if response is not None:\n",
    "            ids += response['ids']\n",
    "            cursor = response['next_cursor']\n",
    "\n",
    "        # print('Fetched {0} total {1} ids for {2}. next_cursor: {3}'.format(\n",
    "        #    len(ids), label, screen_name, cursor))\n",
    "\n",
    "        if len(ids) >= limit or response is None:\n",
    "            break\n",
    "\n",
    "    return ids_to_snames(twitter_api,ids[:limit],screen_name=screen_name)\n",
    "\n",
    "\n",
    "def ids_to_snames(twitter_api,fids,screen_name='tozcss'):\n",
    "    get_snames = partial(make_twitter_request,twitter_api.users.lookup)\n",
    "    resp = []\n",
    "    for i in range(1+(len(fids)-1)//100):\n",
    "        resp.extend(get_snames(user_id=fids[100*i:100*(i+1)]))\n",
    "    header = ['id_str','screen_name', 'name', 'location', 'description', 'created_at', \\\n",
    "        'friends_count','followers_count','statuses_count','favourites_count']\n",
    "    df = pd.DataFrame.from_dict(resp)[header].set_index('id_str')\n",
    "    return df\n",
    "\n",
    "def make_twitter_request(twitter_api_func, max_errors=10, *args, **kw):\n",
    "\n",
    "    # A nested helper function that handles common HTTPErrors. Return an updated\n",
    "    # value for wait_period if the problem is a 500 level error. Block until the\n",
    "    # rate limit is reset if it's a rate limiting issue (429 error). Returns None\n",
    "    # for 401 and 404 errors, which requires special handling by the caller.\n",
    "    def handle_twitter_http_error(e, wait_period=2, sleep_when_rate_limited=True):\n",
    "\n",
    "        if wait_period > 3600: # Seconds\n",
    "            print ('Too many retries. Quitting.',file=sys.stderr)\n",
    "            raise e\n",
    "\n",
    "        # See https://dev.twitter.com/docs/error-codes-responses for common codes\n",
    "\n",
    "        if e.e.code == 401:\n",
    "            print ('Encountered 401 Error (Not Authorized)',file=sys.stderr)\n",
    "            return None\n",
    "        elif e.e.code == 404:\n",
    "            print ('Encountered 404 Error (Not Found)',file=sys.stderr)\n",
    "            return None\n",
    "        elif e.e.code == 429:\n",
    "            print ('Encountered 429 Error (Rate Limit Exceeded)',file=sys.stderr)\n",
    "            if sleep_when_rate_limited:\n",
    "                print (\"Retrying in 15 minutes...ZzZ...\",file=sys.stderr)\n",
    "                sys.stderr.flush()\n",
    "                time.sleep(60*15 + 5)\n",
    "                print ('...ZzZ...Awake now and trying again.',file=sys.stderr)\n",
    "                return 2\n",
    "            else:\n",
    "                raise e # Caller must handle the rate limiting issue\n",
    "        elif e.e.code in (500, 502, 503, 504):\n",
    "            print ('Encountered',e.e.code,'Error. Retrying in',wait_period,'seconds',file=sys.stderr)\n",
    "            time.sleep(wait_period)\n",
    "            wait_period *= 1.5\n",
    "            return wait_period\n",
    "        else:\n",
    "            raise e\n",
    "\n",
    "    # End of nested helper function\n",
    "\n",
    "    wait_period = 2\n",
    "    error_count = 0\n",
    "\n",
    "    while True:\n",
    "        try:\n",
    "            return twitter_api_func(*args, **kw)\n",
    "        except t.api.TwitterHTTPError as e:\n",
    "            error_count = 0\n",
    "            wait_period = handle_twitter_http_error(e, wait_period)\n",
    "            if wait_period is None:\n",
    "                return\n",
    "        except URLError as e:\n",
    "            error_count += 1\n",
    "            time.sleep(wait_period)\n",
    "            wait_period *= 1.5\n",
    "            print (\"URLError encountered. Continuing.\",file = sys.stderr)\n",
    "            if error_count > max_errors:\n",
    "                print (\"Too many consecutive errors...bailing out.\",file=sys.stderr)\n",
    "                raise\n",
    "        except BadStatusLine as e:\n",
    "            error_count += 1\n",
    "            time.sleep(wait_period)\n",
    "            wait_period *= 1.5\n",
    "            print (\"BadStatusLine encountered. Continuing.\",file=sys.stderr)\n",
    "            if error_count > max_errors:\n",
    "                print (\"Too many consecutive errors...bailing out.\",file=sys.stderr)\n",
    "                raise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "import subprocess #the table that went into the presentation\n",
    "template = r'''\\documentclass[preview]{{standalone}}\n",
    "\\usepackage{{booktabs}}\n",
    "\\usepackage[vcentering,dvips]{{geometry}}\n",
    "\\geometry{{total={{3.05in}}}}\n",
    "\\begin{{document}}\n",
    "{}\n",
    "\\end{{document}}\n",
    "'''\n",
    "filename=\"../figs/concerned_geo.tex\"\n",
    "with open(filename, 'w') as f:\n",
    "    f.write(template.format(cc.to_latex()))\n",
    "subprocess.call(['pdflatex', filename],cwd=r'../figs');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "# The rest is not used in the paper"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
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IiLRsjnPLeXl55OTkNHI0Iq4xmUy0bdvWtbZGJtq0aRN2ux2TycSsWbO4+eabq23fr18/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\nR4GOiIiIiIj0OAp0RERERESkx/kfC3sAC0gYm2gAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11d131898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Figure 4 of version1\n",
    "compare = pd.read_table('../data/popVSfollower1000.txt',header=0, sep=\"\\t\")\n",
    "colorm = dict(boxes='lightgreen', whiskers='black', medians='black', caps='black')\n",
    "#ax=compare[['followers','population']].plot(kind='box', patch_artist=True, showfliers=False)\n",
    "boxprops = dict(linestyle='-', color='black')\n",
    "\n",
    "matplotlib.style.use('ggplot')\n",
    "plt.rcParams['axes.facecolor']='w'\n",
    "plt.rcParams['savefig.facecolor']='w'\n",
    "matplotlib.rcParams['xtick.labelsize'] = 20\n",
    "matplotlib.rcParams['ytick.labelsize'] = 18\n",
    "matplotlib.rcParams['axes.titlesize'] = 14\n",
    "\n",
    "co = {'color':'black'}\n",
    "ma = {'color':'black','linestyle':'-'}\n",
    "\n",
    "plt.figure(figsize=(9,3))\n",
    "bp = plt.boxplot([compare.followers,compare.population],patch_artist=True, showfliers=False,\n",
    "                 whiskerprops=co,capprops=co,medianprops=ma,boxprops=boxprops,labels=['mayor','governor'])\n",
    "\n",
    "ax = plt.gca()\n",
    "for patch, color in zip(bp['boxes'], ['magenta','lightgreen']):\n",
    "    patch.set_facecolor(color)\n",
    "ax.xaxis.set_ticklabels(['Cohort','Control'])\n",
    "ax.set_ylabel('Sentiment score',fontsize=22)\n",
    "#ax.set_ylim([-.23, -.12])\n",
    "ax.yaxis.grid(True, linestyle='-', which='major', color='lightgrey', alpha=0.5)\n",
    "ax.get_figure().savefig('../figs/contagion-exp.pdf', bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-0.122567031844\n",
      "-0.312806395394\n"
     ]
    },
    {
     "data": {
      "image/png": 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3xpTNmDFDubm5Sk1N1axZsxQXF6eIiIhGt4+OjnY7IAAAQCBwq5QFBwdrwIAB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\nVTVByp4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117b591d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Figure 3\n",
    "mayonly_avgsent=pd.DataFrame(mayoronly.groupby(['screen_name'],as_index=False).mean()['sent'])\n",
    "snyderonly_avgsent=pd.DataFrame(snyderonly.groupby(['screen_name'],as_index=False).mean()['sent'])\n",
    "\n",
    "\n",
    "print(mayonly_avgsent.sent.mean())\n",
    "print(snyderonly_avgsent.sent.mean())\n",
    "\n",
    "# fig, axes = plt.subplots(nrows=1, ncols=2, sharey=True)\n",
    "colorm = dict(boxes='magenta', whiskers='black', medians='black', caps='black')\n",
    "colorg = dict(boxes='lightgreen', whiskers='black', medians='black', caps='black')\n",
    "\n",
    "#matplotlib.style.use('fivethirtyeight')\n",
    "matplotlib.style.use('ggplot')\n",
    "plt.rcParams['axes.facecolor']='w'\n",
    "plt.rcParams['savefig.facecolor']='w'\n",
    "matplotlib.rcParams['font.size'] = 14\n",
    "#plt.figure(num=None, figsize=(12, 8), facecolor='w', edgecolor='w')\n",
    "\n",
    "c = {'color':'black'}\n",
    "m = {'color':'black','linestyle':'-'}\n",
    "boxprops = dict(linestyle='-', color='black')\n",
    "bp = plt.boxplot([mayonly_avgsent,snyderonly_avgsent], patch_artist=True,\n",
    "                 whiskerprops=c,capprops=c,medianprops=m,boxprops=boxprops,labels=['Mayor','Governor'])\n",
    "\n",
    "for patch, color in zip(bp['boxes'], ['#348ABD','#E24A33']):\n",
    "    patch.set_facecolor(color)\n",
    "\n",
    "ax = plt.gca()\n",
    "ax.set_ylabel('Sentiment score')\n",
    "ax.yaxis.grid(True, linestyle='-', which='major', color='lightgrey', alpha=0.5)\n",
    "ax.get_figure().savefig('../figs/box-mayor-gov.pdf',dpi=150,bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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szOFsbW6Q12cYhndpMzG3FOVV3OVUQtoCCs4IIYQ0S6VShYRHpZx2fbM06+IL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n8e5eXlSEpKQlRUFNq0aQORSIQ777wTALB79268++67uH79OkJCQhAbGwuO43DmzBns2bMHQUFB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\nJJwJIYQQQrgRCWdCCCGEEG7kH/hb07dKmMBCAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1237fb2e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Figure 4\n",
    "mayonly_avgsent=pd.DataFrame(mayoronly.groupby(['screen_name'],as_index=False)['sent'].mean())\n",
    "snyderonly_avgsent=pd.DataFrame(snyderonly.groupby(['screen_name'],as_index=False)['sent'].mean())\n",
    "\n",
    "pro_may_avgent = mayonly_avgsent[mayonly_avgsent.sent>0].screen_name.unique()\n",
    "comment_both = snyderonly_avgsent[snyderonly_avgsent.screen_name.isin(pro_may_avgent)].screen_name.unique()\n",
    "\n",
    "ax=mayonly_avgsent[mayonly_avgsent.screen_name.isin(comment_both) & mayonly_avgsent.sent!=0].sent.plot(kind='density', xlim=(-1,1),color='#348ABD')\n",
    "snyderonly_avgsent[snyderonly_avgsent.screen_name.isin(comment_both) & snyderonly_avgsent.sent!=0 ].sent.plot(kind='density', ax=ax, xlim=(-1,1), color = '#E24A33')\n",
    "ax.legend(['Mayor','Governor'],loc=2)\n",
    "ax.set_xlabel('Sentiment score')\n",
    "ax.get_figure().savefig('../figs/pro_mayors_gov.pdf', bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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+fLk2btwop9OpwYMHa+rUqRo1alRiowYABJUJwYpZy3ZoZ22z9/PoCocenzam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\nIUPBm6Mc1QEAAHNChQkAACg504/uhG6MxPQ5mY6jOgAAYLY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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1363036a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(num=None, figsize=(12, 6), facecolor='w', edgecolor='w')\n",
    "fil.cnt.plot(loglog=True,linestyle='',marker='.')\n",
    "fil.cpop.plot(loglog=True,linestyle='',marker='.')\n",
    "#fil.normalized.plot(loglog=True,linestyle='',marker='.')\n",
    "plt.legend(['tweet count','city population']);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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2bNlC1apVgZwKpFGjRhEeHk6zZs2YOXMmAwcO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\n0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ff3l32lWrVqRWpqKqdPn5bX0zSNiIgITCbTTb/TcePGyUyxW3njjTewWq00a9bspmMm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\nlJv/AyIm0T0m+ihHAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12313c400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = fil.plot.scatter(x='cnt',y='cpop',figsize=(12,5))\n",
    "fil[['cnt','cpop','CityST']].apply(lambda x: ax.text(*x),axis=1);\n",
    "plt.xlim(0,20000);\n",
    "plt.ylim(0,3000000);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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u5ykIfdUfgtBPiMD80H3gsyRgzSqUYeWlyCqt9xMEQRCELqq3e76mTJmC6dOnw9fXFw8f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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112d8df28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#compare the sentiments of blame and no-blame tweets\n",
    "from nltk.sentiment.vader import SentimentIntensityAnalyzer\n",
    "\n",
    "sid = SentimentIntensityAnalyzer()\n",
    "nobl = pd.DataFrame(list(l[l.c=='1'].text.apply(sid.polarity_scores)))['compound']\n",
    "blame = pd.DataFrame(list(l[l.c!='2'].text.apply(sid.polarity_scores)))['compound']\n",
    "\n",
    "nobl.plot.density()\n",
    "blame.plot.density()\n",
    "plt.legend(['no blame','blame'])\n",
    "plt.xlim(-1,1);\n",
    "plt.gcf().set_size_inches(6,2)\n",
    "#plt.gcf().savefig('../figs/blame-sentiment.pdf',dpi=150,bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Pno3PP/8cqamKHqns7GxMmTIFR48exeLFizFjxgycO3cOABASEoLVq1dj5syZmD59OhYv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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11e5a7780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "blamers = [df[df.text.isin(l[l.c.str.contains(str(i))].text.unique())].screen_name.unique() for i in range(10)]\n",
    "blamers.append(df[df.text.isin(l[l.c == 'missing'].text.unique())].screen_name.unique())\n",
    "blamers = pd.DataFrame(blamers).transpose()\n",
    "blamers.columns = labels\n",
    "blamers.apply(pd.Series.nunique) #number of (unique) blamers\n",
    "\n",
    "from collections import defaultdict\n",
    "from itertools import permutations\n",
    "r = defaultdict(dict)\n",
    "for a1,a2 in permutations(range(1,10), 2):\n",
    "    s1 = set(df[df.screen_name.isin(blamers[labels[a1]])].text.unique())\n",
    "    s2 = set(df[df.screen_name.isin(blamers[labels[a2]])].text.unique())\n",
    "    r[labels[a1]][labels[a2]] = len(s1 & s2) / len(s2)\n",
    "plt.figure(num=None, figsize=(12, 8), facecolor='w', edgecolor='w')\n",
    "z = pd.DataFrame.from_dict(r) #what percentage of blamers of x also blame y\n",
    "sns.heatmap(z,annot=True,vmin=0,vmax=1,cmap='RdBu_r',annot_kws={'size':12});"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{ 'accountable': {'accountable'},\n",
      "  'accuse': {'accuse', 'criminate', 'charge', 'incriminate', 'impeach'},\n",
      "  'blame': {'goddamn', 'darned', 'damn', 'incrimination', 'goddamned', 'inculpation', 'fault', 'damned', 'blamed', 'charge', 'goddam', 'find_fault', 'deuced', 'blame', 'blasted', 'infernal', 'rap', 'pick', 'blessed'},\n",
      "  'cause': {'causa', 'effort', 'movement', 'cause', 'suit', 'causal_agent', 'do', 'make', 'stimulate', 'drive', 'crusade', 'reason', 'campaign', 'case', 'lawsuit', 'induce', 'get', 'causal_agency', 'have', 'grounds'},\n",
      "  'fail': {'give_way', 'give_out', 'run_out', 'miscarry', 'go_wrong', 'die', 'fail', 'flush_it', 'bomb', 'break', 'neglect', 'conk_out', 'go_bad', 'flunk', 'betray', 'go', 'break_down'},\n",
      "  'fault': {'shift', 'error', 'faulting', 'mistake', 'geological_fault', 'defect', 'break', 'fault', 'flaw', 'demerit', 'fracture', 'blame'},\n",
      "  'jail': {'lag', 'poky', 'jail', 'jailhouse', 'incarcerate', 'remand', 'clink', 'slammer', 'imprison', 'immure', 'pokey', 'jug', 'put_behind_bars', 'gaol', 'put_away'},\n",
      "  'liable': {'liable', 'unresistant', 'nonresistant', 'nonimmune', 'apt'},\n",
      "  'poison': {'poisonous_substance', 'toxicant', 'poison', 'envenom'},\n",
      "  'prison': {'prison', 'prison_house'},\n",
      "  'resign': {'free', 'vacate', 'give_up', 'submit', 'release', 'quit', 'leave_office', 'resign', 'step_down', 'relinquish', 'renounce', 'reconcile'},\n",
      "  'responsible': {'creditworthy', 'responsible_for', 'responsible'},\n",
      "  'sentence': {'sentence', 'time', 'doom', 'conviction', 'condemn', 'judgment_of_conviction', 'condemnation', 'prison_term'},\n",
      "  'treason': {'perfidy', 'subversiveness', 'treason', 'betrayal', 'lese_majesty', 'high_treason', 'treachery', 'traitorousness'}}\n"
     ]
    }
   ],
   "source": [
    "#import nltk\n",
    "#nltk.download('wordnet')\n",
    "from nltk.corpus import wordnet as wn\n",
    "from collections import defaultdict\n",
    "\n",
    "synonyms = defaultdict(set)\n",
    "words = 'blame fault responsible fail resign jail prison sentence accountable liable cause accuse treason poison'\n",
    "for w in words.split():\n",
    "    for synset in wn.synsets(w):\n",
    "        synonyms[w].update([lemma.name() for lemma in synset.lemmas()])\n",
    "from pprint import pprint\n",
    "pprint(dict(synonyms),indent=2,width=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{tabular}{ll}\n",
      "\\toprule\n",
      "{} &                                       blame words per category \\\\\n",
      "\\midrule\n",
      "fault       &                                       fault error mistake flaw \\\\\n",
      "poison      &                                                         poison \\\\\n",
      "betrayed    &                                         betray traitor treason \\\\\n",
      "responsible &             account responsible blame accus[ie] \\textbackslashsliab \\textbackslashscause \\\\\n",
      "sentenced   &                   arrest convict jail jug bars prison sentence \\\\\n",
      "resign      &           resign quit remove.+office leave.+office step\\textbackslashs down \\\\\n",
      "reason      &  ignor negl[ie] accident discriminat intention ideology decisi \\\\\n",
      "\\bottomrule\n",
      "\\end{tabular}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "blame_words = {'responsible': 'account responsible blame accus[ie] \\sliab \\scause',\n",
    "    'fault': 'fault error mistake flaw',\n",
    "    'reason': 'ignor negl[ie] accident discriminat intention ideology decisi',\n",
    "    'sentenced': 'arrest convict jail jug bars prison sentence',\n",
    "    'betrayed': 'betray traitor treason',\n",
    "    'resign': 'resign quit remove.+office leave.+office step\\sdown',\n",
    "    'poison': 'poison'}\n",
    "bw = {}\n",
    "for k,v in blame_words.items():\n",
    "    bw[k] = v.split()\n",
    "bw = pd.DataFrame.from_dict(blame_words, orient='index').rename(columns={0:'blame words per category'})\n",
    "\n",
    "print(bw.to_latex())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": 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>betrayed</th>\n",
       "      <th>fault</th>\n",
       "      <th>poison</th>\n",
       "      <th>reason</th>\n",
       "      <th>resign</th>\n",
       "      <th>responsible</th>\n",
       "      <th>sentenced</th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>tweets in the dataset (RTs count)</th>\n",
       "      <td>400</td>\n",
       "      <td>6047</td>\n",
       "      <td>51513</td>\n",
       "      <td>9233</td>\n",
       "      <td>17224</td>\n",
       "      <td>20961</td>\n",
       "      <td>20809</td>\n",
       "      <td>113340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th># of tweets w/ unique text</th>\n",
       "      <td>292</td>\n",
       "      <td>2851</td>\n",
       "      <td>19338</td>\n",
       "      <td>4288</td>\n",
       "      <td>7795</td>\n",
       "      <td>11886</td>\n",
       "      <td>9663</td>\n",
       "      <td>50700</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   betrayed  fault  poison  reason  resign  \\\n",
       "tweets in the dataset (RTs count)       400   6047   51513    9233   17224   \n",
       "# of tweets w/ unique text              292   2851   19338    4288    7795   \n",
       "\n",
       "                                   responsible  sentenced   total  \n",
       "tweets in the dataset (RTs count)        20961      20809  113340  \n",
       "# of tweets w/ unique text               11886       9663   50700  "
      ]
     },
     "execution_count": 212,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "blame_words = {'responsible': 'account responsible blame accus[ie] \\sliab \\scause',\n",
    "    'fault': 'fault error mistake flaw',\n",
    "    'reason': 'ignor negl[ie] accident discriminat intention ideology decision',\n",
    "    'sentenced': 'arrest convict jail jug bars prison sentence',\n",
    "    'betrayed': 'betray traitor treason',\n",
    "    'resign': 'resign quit remove.+office leave.+office step\\sdown',\n",
    "    'poison': 'poison'}\n",
    "blame_tw = {} #unique text\n",
    "blame_rt = {} #rt matters\n",
    "total = set()\n",
    "for k,v in blame_words.items():\n",
    "    indices = set.union(*[set(df[df.text.str.contains(w,case=False)].index) for w in v.split()])\n",
    "    blame_tw[k] = df.loc[indices,].text.nunique()\n",
    "    blame_rt[k] = len(indices)\n",
    "    total.update(indices)\n",
    "blame_rt['total'] = len(total)\n",
    "blame_tw['total'] = df.loc[total,].text.nunique()\n",
    "pd.DataFrame([blame_rt,blame_tw],index=['tweets in the dataset (RTs count)','# of tweets w/ unique text'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "l = [v.split() for v in blame_words.values()]\n",
    "blame_filter = '|'.join([item for sublist in l for item in sublist])\n",
    "blames = df[df.text.str.contains(blame_filter,case=False)].copy()\n",
    "blames = blames.replace({'\\r': ' ','\\n': ' '}, regex=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "# group by tweet text\n",
    "grouped = blames.groupby('text').size()\n",
    "g = grouped.reset_index().rename(columns={0:'RT'})\n",
    "g = g.sort_values('RT',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {
    "collapsed": true,
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "\"\"\"\n",
    "sample = g.sample(n=2000,random_state=3).sort_values('RT',ascending=False).copy()\n",
    "s1 = sample.sample(n=200,random_state=5)\n",
    "s2 = sample.sample(n=200,random_state=7)\n",
    "s3 = sample.sample(n=200,random_state=9)\n",
    "s4 = sample.sample(n=200,random_state=11)\n",
    "s5 = sample.sample(n=200,random_state=13)\n",
    "s6 = sample.sample(n=200,random_state=15)\n",
    "\n",
    "from itertools import combinations\n",
    "for p,q in combinations(range(1,5),2):\n",
    "    p = 's'+str(p)\n",
    "    q = 's'+str(q)\n",
    "    print('|'+p+'|','∩','|'+q+'|','=',len(set(eval(p).index)&set(eval(q).index)))\n",
    "\n",
    "s1.to_csv('data/s1.csv',index=False)\n",
    "s2.to_csv('data/s2.csv',index=False)\n",
    "s3.to_csv('data/s3.csv',index=False)\n",
    "s4.to_csv('data/s4.csv',index=False)\n",
    "s5.to_csv('data/s5.csv',index=False)\n",
    "s6.to_csv('data/s6.csv',index=False)\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true,
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "snyder = blames.text.str.contains('gov|nyder|onetoughnerd|bern',case=False)\n",
    "em = blames.text.str.contains('mgr|manager|Darnell|Earley|Kurtz',case=False)\n",
    "mayor = blames.text.str.contains('Dayne|Walling|ayor',case=False)\n",
    "obama = blames.text.str.contains('obama|POTUS',case=False)\n",
    "obama = obama & ~blames.text.str.contains('pledge|announc|nyder|governor',case=False)\n",
    "epa = blames.text.str.contains('\\sEPA\\s',case=False)\n",
    "republic = blames.text.str.contains('republic',case=False)\n",
    "democrat = blames.text.str.contains('democrat',case=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "def perform(fun, *args):\n",
    "    return fun(*args)\n",
    "\n",
    "def meetmin(x,y):\n",
    "    x = blames[x].screen_name\n",
    "    y = blames[y].screen_name\n",
    "    return 100 * len(set(x) & set(y)) / min(len(set(x)), len(set(y)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": 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>EM</th>\n",
       "      <th>EPA</th>\n",
       "      <th>Mayor</th>\n",
       "      <th>President</th>\n",
       "      <th>Snyder</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Also blame Snyder</th>\n",
       "      <td>33.592881</td>\n",
       "      <td>18.976198</td>\n",
       "      <td>20.074349</td>\n",
       "      <td>30.438675</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Also blame EPA</th>\n",
       "      <td>7.730812</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>8.550186</td>\n",
       "      <td>15.219338</td>\n",
       "      <td>18.976198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Also blame President</th>\n",
       "      <td>6.893465</td>\n",
       "      <td>15.219338</td>\n",
       "      <td>6.195787</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>30.438675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Also blame Mayor</th>\n",
       "      <td>9.293680</td>\n",
       "      <td>8.550186</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>6.195787</td>\n",
       "      <td>20.074349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Also blame EM</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>7.730812</td>\n",
       "      <td>9.293680</td>\n",
       "      <td>6.893465</td>\n",
       "      <td>33.592881</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              EM         EPA       Mayor   President  \\\n",
       "Also blame Snyder      33.592881   18.976198   20.074349   30.438675   \n",
       "Also blame EPA          7.730812  100.000000    8.550186   15.219338   \n",
       "Also blame President    6.893465   15.219338    6.195787  100.000000   \n",
       "Also blame Mayor        9.293680    8.550186  100.000000    6.195787   \n",
       "Also blame EM         100.000000    7.730812    9.293680    6.893465   \n",
       "\n",
       "                          Snyder  \n",
       "Also blame Snyder     100.000000  \n",
       "Also blame EPA         18.976198  \n",
       "Also blame President   30.438675  \n",
       "Also blame Mayor       20.074349  \n",
       "Also blame EM          33.592881  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scores = []\n",
    "s = snyder& ~(epa|obama|mayor|em)\n",
    "for y in [s,epa,obama,mayor,em]:\n",
    "    for f in [meetmin]:\n",
    "        scores.append({'EM':perform(f,em,y),\n",
    "                      'Mayor':perform(f,mayor,y),\n",
    "                      'President':perform(f,obama,y),\n",
    "                      'EPA':perform(f,epa,y),\n",
    "                      'Snyder':perform(f,s,y)})\n",
    "pd.DataFrame(scores,index=['Also blame Snyder','Also blame EPA','Also blame President','Also blame Mayor','Also blame EM'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "### Crowdsourcing\n",
    "\n",
    "We filtered our dataset using blame words and labeled one percent sample of the tweets manually regarding who the blame is attributed to. \n",
    "\n",
    "- 0: not a blame tweet\n",
    "- 1: MI Gov. Rick Snyder @onetoughnerd\n",
    "- 2: POTUS Obama\n",
    "- 3: Flint Mayor Dayne Walling\n",
    "- 4: EPA / Gina McCarthy\n",
    "- 5: Emergency Managers: Darnell|Earley|Kurtz\n",
    "- 6: Republicans (help crisis grow)\n",
    "- 7: Democrats (help crisis grow)\n",
    "- 8: Government\n",
    "- 9: Other specified (not among the listed above).\n",
    "\n",
    "Reviwers also identified whether they were confused or unsure about who the tweet assigns blame to.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "l = pd.DataFrame()\n",
    "for i in range(5):\n",
    "    r = pd.read_csv('data/training/Flint'+str(i+1)+'_train.csv')\n",
    "    r['rater'] = i\n",
    "    l = l.append(r)\n",
    "l = l.fillna('missing')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "19.1 2.5079872408\n"
     ]
    }
   ],
   "source": [
    "from mpl_toolkits.axes_grid.inset_locator import inset_axes\n",
    "inset_axes = inset_axes(parent_axes,\n",
    "                    width=\"30%\", # width = 30% of parent_bbox\n",
    "                    height=1., # height : 1 inch\n",
    "                    loc=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv('data/us-city-populations.csv',usecols=['CityST','2010','LAT','LON'])\n",
    "df2 = pd.read_csv('data/city_file.csv',dtype={'lat':str,'lon':str})\n",
    "df2['CityST'] = df2.city + ', ' + df2.state\n",
    "merged = df.merge(df2, on = 'CityST', how = 'inner')\n",
    "merged['latlon'] = merged[['lat','lon']].apply(tuple, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": 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>CityST</th>\n",
       "      <th>2010</th>\n",
       "      <th>LAT</th>\n",
       "      <th>LON</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>lat</th>\n",
       "      <th>lon</th>\n",
       "      <th>latlon</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Anchorage, AK</td>\n",
       "      <td>291826.0</td>\n",
       "      <td>61.177549</td>\n",
       "      <td>-149.274354</td>\n",
       "      <td>Anchorage</td>\n",
       "      <td>AK</td>\n",
       "      <td>61.191900</td>\n",
       "      <td>-149.762097</td>\n",
       "      <td>(61.191900, -149.762097)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Barrow, AK</td>\n",
       "      <td>4212.0</td>\n",
       "      <td>71.254083</td>\n",
       "      <td>-156.798949</td>\n",
       "      <td>Barrow</td>\n",
       "      <td>AK</td>\n",
       "      <td>71.300371</td>\n",
       "      <td>-156.735840</td>\n",
       "      <td>(71.300371, -156.735840)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Bethel, AK</td>\n",
       "      <td>6080.0</td>\n",
       "      <td>60.792913</td>\n",
       "      <td>-161.793405</td>\n",
       "      <td>Bethel</td>\n",
       "      <td>AK</td>\n",
       "      <td>60.789724</td>\n",
       "      <td>-161.779332</td>\n",
       "      <td>(60.789724, -161.779332)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Fairbanks, AK</td>\n",
       "      <td>31535.0</td>\n",
       "      <td>64.836531</td>\n",
       "      <td>-147.651745</td>\n",
       "      <td>Fairbanks</td>\n",
       "      <td>AK</td>\n",
       "      <td>64.838092</td>\n",
       "      <td>-147.726378</td>\n",
       "      <td>(64.838092, -147.726378)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Homer, AK</td>\n",
       "      <td>5003.0</td>\n",
       "      <td>59.639985</td>\n",
       "      <td>-151.511234</td>\n",
       "      <td>Homer</td>\n",
       "      <td>AK</td>\n",
       "      <td>59.643059</td>\n",
       "      <td>-151.525900</td>\n",
       "      <td>(59.643059, -151.525900)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          CityST      2010        LAT         LON       city state        lat  \\\n",
       "0  Anchorage, AK  291826.0  61.177549 -149.274354  Anchorage    AK  61.191900   \n",
       "1     Barrow, AK    4212.0  71.254083 -156.798949     Barrow    AK  71.300371   \n",
       "2     Bethel, AK    6080.0  60.792913 -161.793405     Bethel    AK  60.789724   \n",
       "3  Fairbanks, AK   31535.0  64.836531 -147.651745  Fairbanks    AK  64.838092   \n",
       "4      Homer, AK    5003.0  59.639985 -151.511234      Homer    AK  59.643059   \n",
       "\n",
       "           lon                    latlon  \n",
       "0  -149.762097  (61.191900, -149.762097)  \n",
       "1  -156.735840  (71.300371, -156.735840)  \n",
       "2  -161.779332  (60.789724, -161.779332)  \n",
       "3  -147.726378  (64.838092, -147.726378)  \n",
       "4  -151.525900  (59.643059, -151.525900)  "
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 260,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": 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>em</th>\n",
       "      <th>epa</th>\n",
       "      <th>mayor</th>\n",
       "      <th>obama</th>\n",
       "      <th>s</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>pos tw unique</th>\n",
       "      <td>137.000000</td>\n",
       "      <td>309.000000</td>\n",
       "      <td>102.000000</td>\n",
       "      <td>183.000000</td>\n",
       "      <td>1454.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>neg tw unique</th>\n",
       "      <td>94.000000</td>\n",
       "      <td>245.000000</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>320.000000</td>\n",
       "      <td>2266.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-0.295925</td>\n",
       "      <td>-0.366463</td>\n",
       "      <td>-0.160341</td>\n",
       "      <td>-0.344728</td>\n",
       "      <td>-0.342608</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       em         epa       mayor       obama            s\n",
       "pos tw unique  137.000000  309.000000  102.000000  183.000000  1454.000000\n",
       "neg tw unique   94.000000  245.000000  120.000000  320.000000  2266.000000\n",
       "mean            -0.295925   -0.366463   -0.160341   -0.344728    -0.342608"
      ]
     },
     "execution_count": 260,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pos = {}\n",
    "neg = {}\n",
    "mean = {}\n",
    "for g in ('s','epa','obama','mayor','em'):\n",
    "    pos[g]=len(blames[(blames.sp>0) & eval(g)].text.unique())\n",
    "    neg[g]=len(blames[(blames.sp<0) & eval(g)].text.unique())\n",
    "    mean[g] = blames[(blames.sp<0) & eval(g)].sp.mean()\n",
    "pd.DataFrame([pos,neg,mean],index=['pos tw unique','neg tw unique','mean'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "id\n",
      "RT @NolanHack: Navajo Blame EPA Inaction For Suicides\\n\\n#FlintWaterCrisis \\nhttps://t.co/wgPjnIGRIg #StopNati...\n",
      "MidwestViews: #FlintWaterCrisis Politics as usual BernieSanders &amp; Dems want onetoughnerd resign but not ep...\n",
      "@billmaher\\nAfter the Flint disaster, you may accept the fact that EPA never implemented the CWA due to a faul...\n",
      "@MaddowBlog\\nAfter the Flint disaster,you may accept the fact that EPA never implemented the CWA due to a faul...\n",
      "@chrislhayes\\nAfter Flint disaster, you may accept the fact that EPA never implemented the CWA due to a faulty...\n",
      "RT @VickiMasterson2: @owillis Interesting how Fournier was strangely quiet about Flint until he found an angle...\n",
      "RT @VickiMasterson2: @owillis Interesting how Fournier was strangely quiet about Flint until he found an angle...\n",
      "RT @VickiMasterson2: @owillis Interesting how Fournier was strangely quiet about Flint until he found an angle...\n",
      "                                 Government #EPA has failed #FlintWaterCrisis   Obama is a failure. EPA knew!!!!!\n",
      "RT @VickiMasterson2: @owillis Interesting how Fournier was strangely quiet about Flint until he found an angle...\n",
      "@meredithshiner\\nAfter Flint disaster,you may accept the fact that EPA never implemented the CWA due to a faul...\n",
      "@sganim\\nAfter the Flint disaster, you may accept the fact that EPA never implemented the CWA due to a faulty ...\n",
      "@janelleNBC\\nAfter Flint disaster, you may accept the fact that EPA never implemented the CWA due to a faulty ...\n",
      "@CaseyWianCNN\\nAfter Flint disaster, you may accept the fact that EPA never implemented the CWA due to a fault...\n",
      "@cnnsara\\nAfter the Flint disaster, you may accept the fact that EPA never implemented the CWA due to a faulty...\n",
      "The rats will somehow blame the EPA &amp; @potus later. EM and Gov knowingly poisoned people for $$ #FlintWate...\n",
      "@maddow If it's fair to blame Snyder for the Flint River, then it's fair to blame Obama for what his EPA did h...\n",
      "RT @NolanHack: Navajo Blame EPA Inaction For Suicides\\n\\n#FlintWaterCrisis \\nhttps://t.co/wgPjnIGRIg #StopNati...\n",
      "MidwestViews: #FlintWaterCrisis Politics as usual BernieSanders &amp; Dems want onetoughnerd resign but not ep...\n",
      "@billmaher\\nAfter the Flint disaster, you may accept the fact that EPA never implemented the CWA due to a faul...\n",
      "@MaddowBlog\\nAfter the Flint disaster,you may accept the fact that EPA never implemented the CWA due to a faul...\n",
      "@chrislhayes\\nAfter Flint disaster, you may accept the fact that EPA never implemented the CWA due to a faulty...\n",
      "RT @VickiMasterson2: @owillis Interesting how Fournier was strangely quiet about Flint until he found an angle...\n",
      "RT @VickiMasterson2: @owillis Interesting how Fournier was strangely quiet about Flint until he found an angle...\n",
      "RT @VickiMasterson2: @owillis Interesting how Fournier was strangely quiet about Flint until he found an angle...\n",
      "                                 Government #EPA has failed #FlintWaterCrisis   Obama is a failure. EPA knew!!!!!\n",
      "RT @VickiMasterson2: @owillis Interesting how Fournier was strangely quiet about Flint until he found an angle...\n",
      "@meredithshiner\\nAfter Flint disaster,you may accept the fact that EPA never implemented the CWA due to a faul...\n",
      "@sganim\\nAfter the Flint disaster, you may accept the fact that EPA never implemented the CWA due to a faulty ...\n",
      "@janelleNBC\\nAfter Flint disaster, you may accept the fact that EPA never implemented the CWA due to a faulty ...\n"
     ]
    }
   ],
   "source": [
    "with pd.option_context('display.max_colwidth', 114):\n",
    "    print(blames[epa].text[:30].to_string(index=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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TyghScqdxUVoHAKy62EqrTW9molXNP9ycE82/JaNrNH1tegkAJYbkK7R1FQ+Tlnt1i/26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\nRCKRpEAqSolEIknB/wMHQQLkaku2mwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x18a7110b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from wordcloud import WordCloud, STOPWORDS\n",
    "from scipy.misc import imread\n",
    "from PIL import Image\n",
    "import numpy as np\n",
    "import calendar\n",
    "#mask = imread('twitter_mask.png', flatten=True)\n",
    "mask = np.array(Image.open(\"twitter_mask.png\"))\n",
    "wc = WordCloud(mask=mask,background_color='white',stopwords=STOPWORDS,width=2200,height=1400).generate(words)\n",
    "plt.figure().suptitle(calendar.month_name[month]+', 2016')\n",
    "plt.axis('off')\n",
    "plt.imshow(wc)\n",
    "plt.savefig('figs/wc_'+calendar.month_name[month]+'.png', dpi=300, bbox_inches='tight')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}