tax_votes/president_counties.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Presidential Vote by County by Income Level\n",
    "-----\n",
    "I found a dataset of how each county voted in the 2016 election, and wanted to join it with data from the IRS that has county-level tax return information. I want to see what the trend really was like for voting at the county level, especially as compared to income. If I get a chance, or find another relevant dataest, I might also join this to congressional results by county-level and see if there is an income-based trend especially for places with close congressional races, or where the district split its presidential and congressional votes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Running cell of libraries to import\n",
    "import pandas as pd\n",
    "pd.options.display.max_rows = 200\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# I managed to erase my code for the ct dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def rescue_code(function):\n",
    "    import inspect\n",
    "    get_ipython().set_next_input(\"\".join(inspect.getsourcelines(function)[0]))\n",
    "\n",
    "# This is from when I broke everything"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# County-level pres vote\n",
    "ct = pd.read_csv('../datasets/ct.csv',dtype={'FIPS':object})\n",
    "# Load in income level data from IRS\n",
    "cols = ['STATEFIPS','STATE','COUNTYFIPS','agi_stub','N1','NUMDEP','A00100','TCE','N02650','A02650']\n",
    "dtype_dic = {'STATEFIPS':str,'STATE':str,'COUNTYFIPS':str}\n",
    "inc = pd.read_csv('../datasets/14incyallagi.csv',dtype=dtype_dic)\n",
    "inc.rename(columns = {'N1':'num_returns','NUMDEP':'num_dependents',\n",
    "                     'A00100':'AGI','N02650':'num_tot_inc','A02650':'tot_inc_amt',}, inplace=True)\n",
    "inc['FIPS'] = inc.STATEFIPS + inc.COUNTYFIPS\n",
    "inc['people'] = inc.num_returns+inc.num_dependents\n",
    "inc_fips = inc.groupby('FIPS').sum() # make a groupby b/c IRS summarizes by AGI stub\n",
    "inc_fips['FIPS'] = inc_fips.index\n",
    "descr = pd.read_csv('IRS_data_var_descriptions.csv')\n",
    "descr_dict = {d['VARIABLENAME']: d['DESCRIPTION'] for d in descr.to_dict(orient='records')}\n",
    "\n",
    "# Join dataframes together into a single presidential one\n",
    "\n",
    "prescols = ['FIPS','countyname','state', 'clinton','trump','johnson',\"ind_cand\", 'mcmullin','total_votes', \n",
    "            'AGI','num_returns','num_dependents','num_tot_inc','tot_inc_amt','people']\n",
    "pres_county = pd.merge(ct,inc_fips, on='FIPS') # helpfully, this takes care of my \"state total\" problem\n",
    "pres_county['clinton_win'] = pres_county.clinton>pres_county.trump\n",
    "pres = pres_county[prescols]\n",
    "pres.to_csv('../datasets/president_counties.csv',index=False)\n",
    "pres = pd.read_csv('../datasets/president_counties.csv',dtype={'FIPS':object})\n",
    "pres['agi_per_person'] = pres.AGI/pres.people\n",
    "pres['inc_per_person'] = pres.tot_inc_amt/pres.num_tot_inc\n",
    "pres['turnout']=pres.total_votes/pres.people\n",
    "pres['clinton_pct']=pres.clinton/pres.total_votes\n",
    "pres['trump_pct'] = pres.trump/pres.total_votes\n",
    "pres['ind_cand_pct']=pres.ind_cand/pres.total_votes\n",
    "pres['clinton_margin'] = pres.clinton-pres.trump\n",
    "pres['taxpayers_clinton'] = pres.clinton_pct*pres.num_returns\n",
    "pres['taxpayers_trump'] = pres.trump_pct*pres.num_returns\n",
    "pres['clinton_win'] = pres.clinton_margin>0\n",
    "pres['County winner']=['Clinton' if x==True else 'Trump' for x in pres.clinton_win]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>agi_stub</th>\n",
       "      <th>num_returns</th>\n",
       "      <th>mars1</th>\n",
       "      <th>MARS2</th>\n",
       "      <th>MARS4</th>\n",
       "      <th>PREP</th>\n",
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       "      <th>num_dependents</th>\n",
       "      <th>TOTAL_VITA</th>\n",
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       "      <td>17910.0</td>\n",
       "      <td>510.0</td>\n",
       "      <td>150.0</td>\n",
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       "      <td>110.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>415.0</td>\n",
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       "      <td>18990.0</td>\n",
       "      <td>53147.0</td>\n",
       "      <td>41730.0</td>\n",
       "      <td>01001</td>\n",
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       "      <td>37140.0</td>\n",
       "      <td>38890.0</td>\n",
       "      <td>12790.0</td>\n",
       "      <td>47460.0</td>\n",
       "      <td>179880.0</td>\n",
       "      <td>55660.0</td>\n",
       "      <td>1620.0</td>\n",
       "      <td>400.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1240.0</td>\n",
       "      <td>1707.0</td>\n",
       "      <td>1630.0</td>\n",
       "      <td>4836.0</td>\n",
       "      <td>20450.0</td>\n",
       "      <td>108558.0</td>\n",
       "      <td>64600.0</td>\n",
       "      <td>180864.0</td>\n",
       "      <td>146550.0</td>\n",
       "      <td>01003</td>\n",
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       "    <tr>\n",
       "      <th>01005</th>\n",
       "      <td>36</td>\n",
       "      <td>9730.0</td>\n",
       "      <td>3540.0</td>\n",
       "      <td>3090.0</td>\n",
       "      <td>2980.0</td>\n",
       "      <td>6940.0</td>\n",
       "      <td>20300.0</td>\n",
       "      <td>7860.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>...</td>\n",
       "      <td>30.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>1360.0</td>\n",
       "      <td>4785.0</td>\n",
       "      <td>7990.0</td>\n",
       "      <td>24707.0</td>\n",
       "      <td>17590.0</td>\n",
       "      <td>01005</td>\n",
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       "    <tr>\n",
       "      <th>01007</th>\n",
       "      <td>36</td>\n",
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       "      <td>1720.0</td>\n",
       "      <td>4880.0</td>\n",
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       "      <td>6340.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>30.0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>56.0</td>\n",
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       "      <td>5526.0</td>\n",
       "      <td>6600.0</td>\n",
       "      <td>19513.0</td>\n",
       "      <td>14320.0</td>\n",
       "      <td>01007</td>\n",
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       "<p>5 rows × 126 columns</p>\n",
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      "text/plain": [
       "       agi_stub  num_returns     mars1     MARS2     MARS4       PREP  \\\n",
       "FIPS                                                                    \n",
       "01000        36    2046400.0  822280.0  765870.0  418380.0  1196960.0   \n",
       "01001        36      23820.0    9100.0    9960.0    4230.0    11260.0   \n",
       "01003        36      90890.0   37140.0   38890.0   12790.0    47460.0   \n",
       "01005        36       9730.0    3540.0    3090.0    2980.0     6940.0   \n",
       "01007        36       7980.0    2760.0    3350.0    1720.0     4880.0   \n",
       "\n",
       "              N2  num_dependents  TOTAL_VITA     VITA  ...     N85530  \\\n",
       "FIPS                                                   ...              \n",
       "01000  4183470.0       1486080.0     45780.0  29720.0  ...    21810.0   \n",
       "01001    50060.0         17910.0       510.0    150.0  ...      110.0   \n",
       "01003   179880.0         55660.0      1620.0    400.0  ...     1240.0   \n",
       "01005    20300.0          7860.0        40.0     40.0  ...       30.0   \n",
       "01007    17320.0          6340.0        30.0     30.0  ...        0.0   \n",
       "\n",
       "        A85530   N85300    A85300    N11901     A11901     N11902     A11902  \\\n",
       "FIPS                                                                           \n",
       "01000  37075.0  28130.0  104788.0  354820.0  1648754.0  1607350.0  4832504.0   \n",
       "01001     91.0    150.0     415.0    4120.0    14000.0    18990.0    53147.0   \n",
       "01003   1707.0   1630.0    4836.0   20450.0   108558.0    64600.0   180864.0   \n",
       "01005     48.0     50.0      90.0    1360.0     4785.0     7990.0    24707.0   \n",
       "01007      0.0     30.0      56.0    1130.0     5526.0     6600.0    19513.0   \n",
       "\n",
       "          people   FIPS  \n",
       "FIPS                     \n",
       "01000  3532480.0  01000  \n",
       "01001    41730.0  01001  \n",
       "01003   146550.0  01003  \n",
       "01005    17590.0  01005  \n",
       "01007    14320.0  01007  \n",
       "\n",
       "[5 rows x 126 columns]"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inc_fips.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FIPS</th>\n",
       "      <th>fips_county</th>\n",
       "      <th>countyname</th>\n",
       "      <th>Reporting</th>\n",
       "      <th>trump</th>\n",
       "      <th>clinton</th>\n",
       "      <th>johnson</th>\n",
       "      <th>Others</th>\n",
       "      <th>stein</th>\n",
       "      <th>Darrell Castle</th>\n",
       "      <th>...</th>\n",
       "      <th>N85530</th>\n",
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       "      <th>clinton_win</th>\n",
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       "  </thead>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>02000</td>\n",
       "      <td>AK</td>\n",
       "      <td>Alaska, AK</td>\n",
       "      <td>99.55</td>\n",
       "      <td>130415</td>\n",
       "      <td>93007</td>\n",
       "      <td>14593</td>\n",
       "      <td>0</td>\n",
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       "      <td>423804.0</td>\n",
       "      <td>251670.0</td>\n",
       "      <td>716625.0</td>\n",
       "      <td>570390.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>01107</td>\n",
       "      <td>Pickens County, AL</td>\n",
       "      <td>Pickens, AL</td>\n",
       "      <td>100.00</td>\n",
       "      <td>5456</td>\n",
       "      <td>3972</td>\n",
       "      <td>49</td>\n",
       "      <td>46</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>1180.0</td>\n",
       "      <td>3655.0</td>\n",
       "      <td>6050.0</td>\n",
       "      <td>18890.0</td>\n",
       "      <td>13530.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>01007</td>\n",
       "      <td>Bibb County, AL</td>\n",
       "      <td>Bibb, AL</td>\n",
       "      <td>100.00</td>\n",
       "      <td>6738</td>\n",
       "      <td>1874</td>\n",
       "      <td>124</td>\n",
       "      <td>66</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>1130.0</td>\n",
       "      <td>5526.0</td>\n",
       "      <td>6600.0</td>\n",
       "      <td>19513.0</td>\n",
       "      <td>14320.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>01079</td>\n",
       "      <td>Lawrence County, AL</td>\n",
       "      <td>Lawrence, AL</td>\n",
       "      <td>100.00</td>\n",
       "      <td>10833</td>\n",
       "      <td>3627</td>\n",
       "      <td>250</td>\n",
       "      <td>88</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>30.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>2080.0</td>\n",
       "      <td>6493.0</td>\n",
       "      <td>11050.0</td>\n",
       "      <td>31151.0</td>\n",
       "      <td>22550.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>01115</td>\n",
       "      <td>St. Clair County, AL</td>\n",
       "      <td>St. Clair, AL</td>\n",
       "      <td>100.00</td>\n",
       "      <td>31651</td>\n",
       "      <td>5589</td>\n",
       "      <td>684</td>\n",
       "      <td>346</td>\n",
       "      <td>130</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>180.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>260.0</td>\n",
       "      <td>459.0</td>\n",
       "      <td>6000.0</td>\n",
       "      <td>20343.0</td>\n",
       "      <td>28000.0</td>\n",
       "      <td>78071.0</td>\n",
       "      <td>59630.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
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       "<p>5 rows × 159 columns</p>\n",
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      "text/plain": [
       "    FIPS           fips_county     countyname  Reporting   trump  clinton  \\\n",
       "0  02000                    AK     Alaska, AK      99.55  130415    93007   \n",
       "1  01107    Pickens County, AL    Pickens, AL     100.00    5456     3972   \n",
       "2  01007       Bibb County, AL       Bibb, AL     100.00    6738     1874   \n",
       "3  01079   Lawrence County, AL   Lawrence, AL     100.00   10833     3627   \n",
       "4  01115  St. Clair County, AL  St. Clair, AL     100.00   31651     5589   \n",
       "\n",
       "   johnson  Others  stein  Darrell Castle     ...       N85530  A85530  \\\n",
       "0    14593       0   4445            3156     ...       6280.0  8691.0   \n",
       "1       49      46     19               0     ...          0.0     0.0   \n",
       "2      124      66     17               0     ...          0.0     0.0   \n",
       "3      250      88     31               0     ...         30.0    24.0   \n",
       "4      684     346    130               0     ...        180.0   230.0   \n",
       "\n",
       "   N85300   A85300   N11901    A11901    N11902    A11902    people  \\\n",
       "0  7510.0  20891.0  93110.0  423804.0  251670.0  716625.0  570390.0   \n",
       "1    40.0    152.0   1180.0    3655.0    6050.0   18890.0   13530.0   \n",
       "2    30.0     56.0   1130.0    5526.0    6600.0   19513.0   14320.0   \n",
       "3    50.0    147.0   2080.0    6493.0   11050.0   31151.0   22550.0   \n",
       "4   260.0    459.0   6000.0   20343.0   28000.0   78071.0   59630.0   \n",
       "\n",
       "   clinton_win  \n",
       "0        False  \n",
       "1        False  \n",
       "2        False  \n",
       "3        False  \n",
       "4        False  \n",
       "\n",
       "[5 rows x 159 columns]"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pres_county.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
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       "      <td>AL</td>\n",
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       "      <td>0.764032</td>\n",
       "      <td>0.023472</td>\n",
       "      <td>-4864</td>\n",
       "      <td>1695.716068</td>\n",
       "      <td>6096.976982</td>\n",
       "      <td>False</td>\n",
       "      <td>Trump</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>01079</td>\n",
       "      <td>Lawrence, AL</td>\n",
       "      <td>AL</td>\n",
       "      <td>3627</td>\n",
       "      <td>10833</td>\n",
       "      <td>250</td>\n",
       "      <td>369</td>\n",
       "      <td>0</td>\n",
       "      <td>14829</td>\n",
       "      <td>601382.0</td>\n",
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       "      <td>0.244588</td>\n",
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       "      <td>0.024884</td>\n",
       "      <td>-7206</td>\n",
       "      <td>3311.725673</td>\n",
       "      <td>9891.349383</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>01115</td>\n",
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       "      <td>31651</td>\n",
       "      <td>684</td>\n",
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       "      <td>38400</td>\n",
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       "      <td>0.030208</td>\n",
       "      <td>-26062</td>\n",
       "      <td>5127.616406</td>\n",
       "      <td>29038.144010</td>\n",
       "      <td>False</td>\n",
       "      <td>Trump</td>\n",
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       "<p>5 rows × 26 columns</p>\n",
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      ],
      "text/plain": [
       "    FIPS     countyname state  clinton   trump  johnson  ind_cand  mcmullin  \\\n",
       "0  02000     Alaska, AK    AK    93007  130415    14593     23166         0   \n",
       "1  01107    Pickens, AL    AL     3972    5456       49       114         0   \n",
       "2  01007       Bibb, AL    AL     1874    6738      124       207         0   \n",
       "3  01079   Lawrence, AL    AL     3627   10833      250       369         0   \n",
       "4  01115  St. Clair, AL    AL     5589   31651      684      1160         0   \n",
       "\n",
       "   total_votes         AGI      ...        inc_per_person   turnout  \\\n",
       "0       246588  24270413.0      ...             68.275258  0.432315   \n",
       "1         9542    301640.0      ...             40.679067  0.705248   \n",
       "2         8819    365681.0      ...             46.397739  0.615852   \n",
       "3        14829    601382.0      ...             44.925537  0.657605   \n",
       "4        38400   1794459.0      ...             51.635828  0.643971   \n",
       "\n",
       "   clinton_pct  trump_pct  ind_cand_pct  clinton_margin  taxpayers_clinton  \\\n",
       "0     0.377176   0.528878      0.093946          -37408      136201.914813   \n",
       "1     0.416265   0.571788      0.011947           -1484        3134.474953   \n",
       "2     0.212496   0.764032      0.023472           -4864        1695.716068   \n",
       "3     0.244588   0.730528      0.024884           -7206        3311.725673   \n",
       "4     0.145547   0.824245      0.030208          -26062        5127.616406   \n",
       "\n",
       "   taxpayers_trump  clinton_win  County winner  \n",
       "0    190983.181055        False          Trump  \n",
       "1      4305.562775        False          Trump  \n",
       "2      6096.976982        False          Trump  \n",
       "3      9891.349383        False          Trump  \n",
       "4     29038.144010        False          Trump  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pres.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
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      "text/plain": [
       "    FIPS           fips_county     countyname  Reporting   trump  clinton  \\\n",
       "0  02000                    AK     Alaska, AK      99.55  130415    93007   \n",
       "1  01107    Pickens County, AL    Pickens, AL     100.00    5456     3972   \n",
       "2  01007       Bibb County, AL       Bibb, AL     100.00    6738     1874   \n",
       "3  01079   Lawrence County, AL   Lawrence, AL     100.00   10833     3627   \n",
       "4  01115  St. Clair County, AL  St. Clair, AL     100.00   31651     5589   \n",
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       "\n",
       "[5 rows x 33 columns]"
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     },
     "execution_count": 143,
     "metadata": {},
     "output_type": "execute_result"
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   ],
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    "ct.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {
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   "outputs": [
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       "      <td>664.611765</td>\n",
       "      <td>True</td>\n",
       "      <td>Clinton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1512</th>\n",
       "      <td>28051</td>\n",
       "      <td>Holmes, MS</td>\n",
       "      <td>MS</td>\n",
       "      <td>6689</td>\n",
       "      <td>1309</td>\n",
       "      <td>25</td>\n",
       "      <td>78</td>\n",
       "      <td>0</td>\n",
       "      <td>8076</td>\n",
       "      <td>212509.0</td>\n",
       "      <td>...</td>\n",
       "      <td>28.645273</td>\n",
       "      <td>0.536611</td>\n",
       "      <td>0.828257</td>\n",
       "      <td>0.162085</td>\n",
       "      <td>0.009658</td>\n",
       "      <td>5380</td>\n",
       "      <td>6253.337048</td>\n",
       "      <td>1223.743190</td>\n",
       "      <td>True</td>\n",
       "      <td>Clinton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>360</th>\n",
       "      <td>13003</td>\n",
       "      <td>Atkinson, GA</td>\n",
       "      <td>GA</td>\n",
       "      <td>697</td>\n",
       "      <td>1878</td>\n",
       "      <td>35</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>2610</td>\n",
       "      <td>91005.0</td>\n",
       "      <td>...</td>\n",
       "      <td>29.875974</td>\n",
       "      <td>0.414286</td>\n",
       "      <td>0.267050</td>\n",
       "      <td>0.719540</td>\n",
       "      <td>0.013410</td>\n",
       "      <td>-1181</td>\n",
       "      <td>825.183908</td>\n",
       "      <td>2223.379310</td>\n",
       "      <td>False</td>\n",
       "      <td>Trump</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>388</th>\n",
       "      <td>13061</td>\n",
       "      <td>Clay, GA</td>\n",
       "      <td>GA</td>\n",
       "      <td>697</td>\n",
       "      <td>566</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>1273</td>\n",
       "      <td>31446.0</td>\n",
       "      <td>...</td>\n",
       "      <td>26.939831</td>\n",
       "      <td>0.586636</td>\n",
       "      <td>0.547526</td>\n",
       "      <td>0.444619</td>\n",
       "      <td>0.007855</td>\n",
       "      <td>131</td>\n",
       "      <td>646.080126</td>\n",
       "      <td>524.650432</td>\n",
       "      <td>True</td>\n",
       "      <td>Clinton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>408</th>\n",
       "      <td>13101</td>\n",
       "      <td>Echols, GA</td>\n",
       "      <td>GA</td>\n",
       "      <td>156</td>\n",
       "      <td>1007</td>\n",
       "      <td>13</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>1182</td>\n",
       "      <td>41017.0</td>\n",
       "      <td>...</td>\n",
       "      <td>30.248175</td>\n",
       "      <td>0.420641</td>\n",
       "      <td>0.131980</td>\n",
       "      <td>0.851946</td>\n",
       "      <td>0.016074</td>\n",
       "      <td>-851</td>\n",
       "      <td>182.131980</td>\n",
       "      <td>1175.685279</td>\n",
       "      <td>False</td>\n",
       "      <td>Trump</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>637</th>\n",
       "      <td>16033</td>\n",
       "      <td>Clark, ID</td>\n",
       "      <td>ID</td>\n",
       "      <td>44</td>\n",
       "      <td>203</td>\n",
       "      <td>4</td>\n",
       "      <td>36</td>\n",
       "      <td>23</td>\n",
       "      <td>283</td>\n",
       "      <td>10150.0</td>\n",
       "      <td>...</td>\n",
       "      <td>32.015625</td>\n",
       "      <td>0.410145</td>\n",
       "      <td>0.155477</td>\n",
       "      <td>0.717314</td>\n",
       "      <td>0.127208</td>\n",
       "      <td>-159</td>\n",
       "      <td>49.752650</td>\n",
       "      <td>229.540636</td>\n",
       "      <td>False</td>\n",
       "      <td>Trump</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2707</th>\n",
       "      <td>48427</td>\n",
       "      <td>Starr, TX</td>\n",
       "      <td>TX</td>\n",
       "      <td>9289</td>\n",
       "      <td>2224</td>\n",
       "      <td>159</td>\n",
       "      <td>227</td>\n",
       "      <td>0</td>\n",
       "      <td>11740</td>\n",
       "      <td>776303.0</td>\n",
       "      <td>...</td>\n",
       "      <td>32.345938</td>\n",
       "      <td>0.228050</td>\n",
       "      <td>0.791227</td>\n",
       "      <td>0.189438</td>\n",
       "      <td>0.019336</td>\n",
       "      <td>7065</td>\n",
       "      <td>19218.893526</td>\n",
       "      <td>4601.444634</td>\n",
       "      <td>True</td>\n",
       "      <td>Clinton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1919</th>\n",
       "      <td>35031</td>\n",
       "      <td>McKinley, NM</td>\n",
       "      <td>NM</td>\n",
       "      <td>13576</td>\n",
       "      <td>5104</td>\n",
       "      <td>2412</td>\n",
       "      <td>3023</td>\n",
       "      <td>173</td>\n",
       "      <td>21703</td>\n",
       "      <td>1037508.0</td>\n",
       "      <td>...</td>\n",
       "      <td>32.579078</td>\n",
       "      <td>0.321098</td>\n",
       "      <td>0.625536</td>\n",
       "      <td>0.235175</td>\n",
       "      <td>0.139289</td>\n",
       "      <td>8472</td>\n",
       "      <td>20192.290467</td>\n",
       "      <td>7591.444501</td>\n",
       "      <td>True</td>\n",
       "      <td>Clinton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1767</th>\n",
       "      <td>38085</td>\n",
       "      <td>Sioux, ND</td>\n",
       "      <td>ND</td>\n",
       "      <td>758</td>\n",
       "      <td>260</td>\n",
       "      <td>25</td>\n",
       "      <td>214</td>\n",
       "      <td>0</td>\n",
       "      <td>1232</td>\n",
       "      <td>43918.0</td>\n",
       "      <td>...</td>\n",
       "      <td>33.680303</td>\n",
       "      <td>0.432281</td>\n",
       "      <td>0.615260</td>\n",
       "      <td>0.211039</td>\n",
       "      <td>0.173701</td>\n",
       "      <td>498</td>\n",
       "      <td>812.142857</td>\n",
       "      <td>278.571429</td>\n",
       "      <td>True</td>\n",
       "      <td>Clinton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1546</th>\n",
       "      <td>28119</td>\n",
       "      <td>Quitman, MS</td>\n",
       "      <td>MS</td>\n",
       "      <td>2312</td>\n",
       "      <td>1001</td>\n",
       "      <td>20</td>\n",
       "      <td>52</td>\n",
       "      <td>0</td>\n",
       "      <td>3365</td>\n",
       "      <td>85593.0</td>\n",
       "      <td>...</td>\n",
       "      <td>30.969395</td>\n",
       "      <td>0.608499</td>\n",
       "      <td>0.687073</td>\n",
       "      <td>0.297474</td>\n",
       "      <td>0.015453</td>\n",
       "      <td>1311</td>\n",
       "      <td>1944.416048</td>\n",
       "      <td>841.851412</td>\n",
       "      <td>True</td>\n",
       "      <td>Clinton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>01063</td>\n",
       "      <td>Greene, AL</td>\n",
       "      <td>AL</td>\n",
       "      <td>4013</td>\n",
       "      <td>838</td>\n",
       "      <td>13</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>4880</td>\n",
       "      <td>105220.0</td>\n",
       "      <td>...</td>\n",
       "      <td>30.619020</td>\n",
       "      <td>0.722963</td>\n",
       "      <td>0.822336</td>\n",
       "      <td>0.171721</td>\n",
       "      <td>0.005943</td>\n",
       "      <td>3175</td>\n",
       "      <td>2861.729508</td>\n",
       "      <td>597.590164</td>\n",
       "      <td>True</td>\n",
       "      <td>Clinton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1538</th>\n",
       "      <td>28103</td>\n",
       "      <td>Noxubee, MS</td>\n",
       "      <td>MS</td>\n",
       "      <td>4347</td>\n",
       "      <td>1200</td>\n",
       "      <td>12</td>\n",
       "      <td>27</td>\n",
       "      <td>0</td>\n",
       "      <td>5574</td>\n",
       "      <td>141105.0</td>\n",
       "      <td>...</td>\n",
       "      <td>30.774946</td>\n",
       "      <td>0.616593</td>\n",
       "      <td>0.779871</td>\n",
       "      <td>0.215285</td>\n",
       "      <td>0.004844</td>\n",
       "      <td>3147</td>\n",
       "      <td>3712.185145</td>\n",
       "      <td>1024.757804</td>\n",
       "      <td>True</td>\n",
       "      <td>Clinton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1497</th>\n",
       "      <td>28021</td>\n",
       "      <td>Claiborne, MS</td>\n",
       "      <td>MS</td>\n",
       "      <td>3708</td>\n",
       "      <td>540</td>\n",
       "      <td>7</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>4272</td>\n",
       "      <td>111975.0</td>\n",
       "      <td>...</td>\n",
       "      <td>32.003672</td>\n",
       "      <td>0.603390</td>\n",
       "      <td>0.867978</td>\n",
       "      <td>0.126404</td>\n",
       "      <td>0.005618</td>\n",
       "      <td>3168</td>\n",
       "      <td>3090.000000</td>\n",
       "      <td>450.000000</td>\n",
       "      <td>True</td>\n",
       "      <td>Clinton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>01105</td>\n",
       "      <td>Perry, AL</td>\n",
       "      <td>AL</td>\n",
       "      <td>3824</td>\n",
       "      <td>1407</td>\n",
       "      <td>23</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "      <td>5278</td>\n",
       "      <td>115099.0</td>\n",
       "      <td>...</td>\n",
       "      <td>31.238874</td>\n",
       "      <td>0.728000</td>\n",
       "      <td>0.724517</td>\n",
       "      <td>0.266578</td>\n",
       "      <td>0.008905</td>\n",
       "      <td>2417</td>\n",
       "      <td>2709.693066</td>\n",
       "      <td>997.002653</td>\n",
       "      <td>True</td>\n",
       "      <td>Clinton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>647</th>\n",
       "      <td>16053</td>\n",
       "      <td>Jerome, ID</td>\n",
       "      <td>ID</td>\n",
       "      <td>1329</td>\n",
       "      <td>4644</td>\n",
       "      <td>218</td>\n",
       "      <td>778</td>\n",
       "      <td>419</td>\n",
       "      <td>6751</td>\n",
       "      <td>314573.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35.225806</td>\n",
       "      <td>0.347810</td>\n",
       "      <td>0.196860</td>\n",
       "      <td>0.687898</td>\n",
       "      <td>0.115242</td>\n",
       "      <td>-3315</td>\n",
       "      <td>1836.701229</td>\n",
       "      <td>6418.089172</td>\n",
       "      <td>False</td>\n",
       "      <td>Trump</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2738</th>\n",
       "      <td>48489</td>\n",
       "      <td>Willacy, TX</td>\n",
       "      <td>TX</td>\n",
       "      <td>3422</td>\n",
       "      <td>1547</td>\n",
       "      <td>95</td>\n",
       "      <td>126</td>\n",
       "      <td>0</td>\n",
       "      <td>5095</td>\n",
       "      <td>243651.0</td>\n",
       "      <td>...</td>\n",
       "      <td>33.305795</td>\n",
       "      <td>0.339667</td>\n",
       "      <td>0.671639</td>\n",
       "      <td>0.303631</td>\n",
       "      <td>0.024730</td>\n",
       "      <td>1875</td>\n",
       "      <td>4996.993131</td>\n",
       "      <td>2259.014720</td>\n",
       "      <td>True</td>\n",
       "      <td>Clinton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1037</th>\n",
       "      <td>21147</td>\n",
       "      <td>McCreary, KY</td>\n",
       "      <td>KY</td>\n",
       "      <td>664</td>\n",
       "      <td>5012</td>\n",
       "      <td>59</td>\n",
       "      <td>100</td>\n",
       "      <td>19</td>\n",
       "      <td>5776</td>\n",
       "      <td>145357.0</td>\n",
       "      <td>...</td>\n",
       "      <td>30.249691</td>\n",
       "      <td>0.646085</td>\n",
       "      <td>0.114958</td>\n",
       "      <td>0.867729</td>\n",
       "      <td>0.017313</td>\n",
       "      <td>-4348</td>\n",
       "      <td>558.698061</td>\n",
       "      <td>4217.160665</td>\n",
       "      <td>False</td>\n",
       "      <td>Trump</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3002</th>\n",
       "      <td>55078</td>\n",
       "      <td>Menominee, WI</td>\n",
       "      <td>WI</td>\n",
       "      <td>1002</td>\n",
       "      <td>267</td>\n",
       "      <td>12</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "      <td>1308</td>\n",
       "      <td>56538.0</td>\n",
       "      <td>...</td>\n",
       "      <td>32.468000</td>\n",
       "      <td>0.381341</td>\n",
       "      <td>0.766055</td>\n",
       "      <td>0.204128</td>\n",
       "      <td>0.029817</td>\n",
       "      <td>735</td>\n",
       "      <td>1340.596330</td>\n",
       "      <td>357.224771</td>\n",
       "      <td>True</td>\n",
       "      <td>Clinton</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       FIPS         countyname state  clinton  trump  johnson  ind_cand  \\\n",
       "2383  46102  Oglala Lakota, SD    SD     2510    241      106       154   \n",
       "2340  46017        Buffalo, SD    SD      296    171       18        23   \n",
       "2392  46121           Todd, SD    SD     1505    487       96       133   \n",
       "1512  28051         Holmes, MS    MS     6689   1309       25        78   \n",
       "360   13003       Atkinson, GA    GA      697   1878       35        35   \n",
       "388   13061           Clay, GA    GA      697    566        8        10   \n",
       "408   13101         Echols, GA    GA      156   1007       13        19   \n",
       "637   16033          Clark, ID    ID       44    203        4        36   \n",
       "2707  48427          Starr, TX    TX     9289   2224      159       227   \n",
       "1919  35031       McKinley, NM    NM    13576   5104     2412      3023   \n",
       "1767  38085          Sioux, ND    ND      758    260       25       214   \n",
       "1546  28119        Quitman, MS    MS     2312   1001       20        52   \n",
       "37    01063         Greene, AL    AL     4013    838       13        29   \n",
       "1538  28103        Noxubee, MS    MS     4347   1200       12        27   \n",
       "1497  28021      Claiborne, MS    MS     3708    540        7        24   \n",
       "47    01105          Perry, AL    AL     3824   1407       23        47   \n",
       "647   16053         Jerome, ID    ID     1329   4644      218       778   \n",
       "2738  48489        Willacy, TX    TX     3422   1547       95       126   \n",
       "1037  21147       McCreary, KY    KY      664   5012       59       100   \n",
       "3002  55078      Menominee, WI    WI     1002    267       12        39   \n",
       "\n",
       "      mcmullin  total_votes        AGI      ...        inc_per_person  \\\n",
       "2383         0         2905   117051.0      ...             30.088776   \n",
       "2340         0          490    20527.0      ...             29.404225   \n",
       "2392         0         2125    87410.0      ...             30.558131   \n",
       "1512         0         8076   212509.0      ...             28.645273   \n",
       "360          0         2610    91005.0      ...             29.875974   \n",
       "388          0         1273    31446.0      ...             26.939831   \n",
       "408          0         1182    41017.0      ...             30.248175   \n",
       "637         23          283    10150.0      ...             32.015625   \n",
       "2707         0        11740   776303.0      ...             32.345938   \n",
       "1919       173        21703  1037508.0      ...             32.579078   \n",
       "1767         0         1232    43918.0      ...             33.680303   \n",
       "1546         0         3365    85593.0      ...             30.969395   \n",
       "37           0         4880   105220.0      ...             30.619020   \n",
       "1538         0         5574   141105.0      ...             30.774946   \n",
       "1497         0         4272   111975.0      ...             32.003672   \n",
       "47           0         5278   115099.0      ...             31.238874   \n",
       "647        419         6751   314573.0      ...             35.225806   \n",
       "2738         0         5095   243651.0      ...             33.305795   \n",
       "1037        19         5776   145357.0      ...             30.249691   \n",
       "3002         0         1308    56538.0      ...             32.468000   \n",
       "\n",
       "       turnout  clinton_pct  trump_pct  ind_cand_pct  clinton_margin  \\\n",
       "2383  0.296429     0.864028   0.082960      0.053012            2269   \n",
       "2340  0.291667     0.604082   0.348980      0.046939             125   \n",
       "2392  0.324924     0.708235   0.229176      0.062588            1018   \n",
       "1512  0.536611     0.828257   0.162085      0.009658            5380   \n",
       "360   0.414286     0.267050   0.719540      0.013410           -1181   \n",
       "388   0.586636     0.547526   0.444619      0.007855             131   \n",
       "408   0.420641     0.131980   0.851946      0.016074            -851   \n",
       "637   0.410145     0.155477   0.717314      0.127208            -159   \n",
       "2707  0.228050     0.791227   0.189438      0.019336            7065   \n",
       "1919  0.321098     0.625536   0.235175      0.139289            8472   \n",
       "1767  0.432281     0.615260   0.211039      0.173701             498   \n",
       "1546  0.608499     0.687073   0.297474      0.015453            1311   \n",
       "37    0.722963     0.822336   0.171721      0.005943            3175   \n",
       "1538  0.616593     0.779871   0.215285      0.004844            3147   \n",
       "1497  0.603390     0.867978   0.126404      0.005618            3168   \n",
       "47    0.728000     0.724517   0.266578      0.008905            2417   \n",
       "647   0.347810     0.196860   0.687898      0.115242           -3315   \n",
       "2738  0.339667     0.671639   0.303631      0.024730            1875   \n",
       "1037  0.646085     0.114958   0.867729      0.017313           -4348   \n",
       "3002  0.381341     0.766055   0.204128      0.029817             735   \n",
       "\n",
       "      taxpayers_clinton  taxpayers_trump  clinton_win  County winner  \n",
       "2383        3395.628227       326.034423         True        Clinton  \n",
       "2340         428.897959       247.775510         True        Clinton  \n",
       "2392        2053.882353       664.611765         True        Clinton  \n",
       "1512        6253.337048      1223.743190         True        Clinton  \n",
       "360          825.183908      2223.379310        False          Trump  \n",
       "388          646.080126       524.650432         True        Clinton  \n",
       "408          182.131980      1175.685279        False          Trump  \n",
       "637           49.752650       229.540636        False          Trump  \n",
       "2707       19218.893526      4601.444634         True        Clinton  \n",
       "1919       20192.290467      7591.444501         True        Clinton  \n",
       "1767         812.142857       278.571429         True        Clinton  \n",
       "1546        1944.416048       841.851412         True        Clinton  \n",
       "37          2861.729508       597.590164         True        Clinton  \n",
       "1538        3712.185145      1024.757804         True        Clinton  \n",
       "1497        3090.000000       450.000000         True        Clinton  \n",
       "47          2709.693066       997.002653         True        Clinton  \n",
       "647         1836.701229      6418.089172        False          Trump  \n",
       "2738        4996.993131      2259.014720         True        Clinton  \n",
       "1037         558.698061      4217.160665        False          Trump  \n",
       "3002        1340.596330       357.224771         True        Clinton  \n",
       "\n",
       "[20 rows x 26 columns]"
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# sandbox for checking top values of various columns\n",
    "dial = 'agi_per_person'\n",
    "pres.sort_values(by=dial, ascending=True).head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAuMAAABECAYAAAAr+zvbAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11b939690>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABECAYAAAD+xS3TAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nJAgAgOoPaNomxy1Tk44AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11b939d10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.color_palette(\"RdBu\", 13))\n",
    "sns.palplot(sns.color_palette(\"RdBu\", 9))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAH4AAABECAYAAABHwoFDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAAO5JREFUeJzt3bGNAjEQQFGMLoAO6L+67eDIhgoWEmB1999LLUsjfdmS\nI6+ZOdFzPnoAjiF8lPBRwkcJH/XzbHHu91mXy7dm4f3W7sKL59xsa3fvn3ebOV3XdvQYH/M7t914\nrvoo4aOEjxI+Svgo4aOEjxI+Svgo4aOEjxI+Svgo4aOEjxI+Svgo4aOEjxI+Svgo4aOEjxI+Svgo\n4aOEjxI+Svgo4aOEjxI+Svgo4aOEjxI+Svgo4aOEjxI+Svgo4aOEjxI+Svgo4aOEjxI+Svgo4aOE\njxI+SvioV79Q8U858VHCRwkfJXyU8FHCRz0AqGAUf31MajcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12a4e7490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "color_code = ['#e70000','#0800e7']\n",
    "sns.set_palette(color_code)\n",
    "sns.palplot(sns.color_palette())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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cMJL7eODP3H3Y3b9LaM56HyGQPxs4z91LHsHq7rsJo36fSyhNfwK4zN2vLPKwbxFqqHcQ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\nmyXJUu1gfT/wYBSc7zezA4SadUYLcGiii3R25q8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8aXrgeV8guM8qu6lUwVrczpZ0kMpy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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11bb8aa50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# x = pres.clinton\n",
    "# ax = sns.regplot(x=x, y=y, marker=\"+\")\n",
    "\n",
    "# agi_pp = sns.FacetGrid(pres, hue='clinton_win', size=7.5,palette='RdBu')\n",
    "# agi_pp.map(plt.scatter, 'clinton', 'agi_per_person').add_legend()\n",
    "# agi_pp.ax.set_title('Clinton votes per individual gross income')\n",
    "\n",
    "agi_pp = sns.lmplot(x='clinton_pct',y='agi_per_person',data=pres,hue='County winner',\n",
    "                    palette=['#e70000','#140ebd'],size=6,scatter_kws={'alpha':0.3})\n",
    "agi_pp.ax.set_title('Income per person about the same for Trump and Clinton counties',fontsize=14)\n",
    "agi_pp.set(xlabel='Percentage of votes for Clinton', ylabel='Income per person (000s)')\n",
    "agi_pp.savefig('../austinbrian.github.io/images/agi_pp_vs_clinton.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "top_votes = pres.sort_values(by='total_votes',ascending=False).head(50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "clinton_lose = pres.clinton_win==False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "136242200.0 106693130.0\n"
     ]
    }
   ],
   "source": [
    "clinton_win = pres.clinton_win\n",
    "people_clinton_win = pres[clinton_win].people.sum()\n",
    "people_clinton_lost = pres[clinton_lose].people.sum()\n",
    "print people_clinton_win, people_clinton_lost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "31.937467482006458"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(pres.agi_per_person)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "82267630.0 64781090.0\n"
     ]
    }
   ],
   "source": [
    "taxpayers_clinton_win = pres[clinton_win].num_returns.sum()\n",
    "taxpayers_clinton_lost = pres[clinton_lose].num_returns.sum()\n",
    "print taxpayers_clinton_win, taxpayers_clinton_lost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "72049899.5493 66231346.7672\n"
     ]
    }
   ],
   "source": [
    "print pres.taxpayers_clinton.sum(), pres.taxpayers_trump.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2623 490\n"
     ]
    }
   ],
   "source": [
    "print pres[clinton_lose].FIPS.count(),pres[clinton_win].FIPS.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8425955669771924"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pres[clinton_lose].FIPS.count()/pres.FIPS.count().astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Important features of taxpayers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'A00100': 'Adjust gross income (AGI) [4]',\n",
       " 'A00101': 'Amount of AGI for itemized returns',\n",
       " 'A00200': 'Salaries and wages amount',\n",
       " 'A00300': 'Taxable interest amount',\n",
       " 'A00600': 'Ordinary dividends amount',\n",
       " 'A00650': 'Qualified dividends amount [5]',\n",
       " 'A00700': 'State and local income tax refunds amount',\n",
       " 'A00900': 'Business or professional net income (less loss) amount',\n",
       " 'A01000': 'Net capital gain (less loss) amount',\n",
       " 'A01400': 'Taxable individual retirement arrangements distributions amount',\n",
       " 'A01700': 'Taxable pensions and annuities amount',\n",
       " 'A02300': 'Unemployment compensation amount [6]',\n",
       " 'A02500': 'Taxable Social Security benefits amount',\n",
       " 'A02650': 'Total income amount',\n",
       " 'A02900': 'Total statutory adjustments amount',\n",
       " 'A03150': 'IRA payments amount',\n",
       " 'A03210': 'Student loan interest deduction amount',\n",
       " 'A03220': 'Educator expenses amount',\n",
       " 'A03230': 'Tuition and fees deduction amount',\n",
       " 'A03240': 'Domestic production activities deduction amount',\n",
       " 'A03270': 'Self-employment health insurance deduction amount',\n",
       " 'A03300': 'Self-employment retirement plans amount',\n",
       " 'A04470': 'Total itemized deductions amount',\n",
       " 'A04800': 'Taxable income amount',\n",
       " 'A05780': 'Excess advance premium tax credit repayment amount',\n",
       " 'A05800': 'Income tax before credits amount',\n",
       " 'A06500': 'Income tax amount [9]  ',\n",
       " 'A07100': 'Total tax credits amount',\n",
       " 'A07180': 'Child and dependent care credit amount',\n",
       " 'A07220': 'Child tax credit amount',\n",
       " 'A07230': 'Nonrefundable education credit amount',\n",
       " 'A07240': 'Retirement savings contribution credit amount',\n",
       " 'A07260': 'Residential energy tax credit amount',\n",
       " 'A07300': 'Foreign tax credit amount',\n",
       " 'A09400': 'Self-employment tax amount',\n",
       " 'A09600': 'Alternative minimum tax amount',\n",
       " 'A09750': 'Health care individual responsibility payment amount',\n",
       " 'A10300': 'Total tax liability amount [10]  ',\n",
       " 'A10600': 'Total tax payments amount',\n",
       " 'A10960': 'Refundable education credit amount',\n",
       " 'A11070': 'Additional child tax credit amount',\n",
       " 'A11560': 'Net premium tax credit amount',\n",
       " 'A11901': 'Tax due at time of filing amount [11]  ',\n",
       " 'A11902': 'Overpayments refunded amount [12]  ',\n",
       " 'A18300': 'Taxes paid amount',\n",
       " 'A18425': 'State and local income taxes amount',\n",
       " 'A18450': 'State and local general sales tax amount',\n",
       " 'A18500': 'Real estate taxes amount',\n",
       " 'A19300': 'Mortgage interest paid amount',\n",
       " 'A19700': 'Contributions amount',\n",
       " 'A26270': 'Partnership/S-corp net income (less loss) amount',\n",
       " 'A59660': 'Earned income credit amount [7]  ',\n",
       " 'A59720': 'Excess earned income credit (refundable) amount [8]  ',\n",
       " 'A85300': 'Net investment income tax amount',\n",
       " 'A85530': 'Additional Medicare tax amount',\n",
       " 'A85770': 'Total premium tax credit amount',\n",
       " 'A85775': 'Advance premium tax credit amount',\n",
       " 'AGI_STUB': '  Size of adjusted gross income',\n",
       " 'COUNTYFIPS': '  3-digit County FIPS code [2]',\n",
       " 'COUNTYNAME': '  County name',\n",
       " 'MARS1': 'Number of single returns',\n",
       " 'MARS2': 'Number of joint returns',\n",
       " 'MARS4': 'Number of head of household returns',\n",
       " 'N00200': 'Number of returns with salaries and wages',\n",
       " 'N00300': 'Number of returns with taxable interest',\n",
       " 'N00600': 'Number of returns with ordinary dividends ',\n",
       " 'N00650': 'Number of returns with qualified dividends',\n",
       " 'N00700': 'Number of returns with state and local income tax refunds',\n",
       " 'N00900': 'Number of returns with business or professional net income (less loss)',\n",
       " 'N01000': 'Number of returns with net capital gain (less loss)',\n",
       " 'N01400': 'Number of returns with taxable individual retirement arrangements distributions',\n",
       " 'N01700': 'Number of returns with taxable pensions and annuities',\n",
       " 'N02300': 'Number of returns with unemployment compensation',\n",
       " 'N02500': 'Number of returns with taxable Social Security benefits',\n",
       " 'N02650': 'Number of returns with total income',\n",
       " 'N02900': 'Number of returns with total statutory adjustments',\n",
       " 'N03150': 'Number of returns with IRA payments',\n",
       " 'N03210': 'Number of returns with student loan interest deduction',\n",
       " 'N03220': 'Number of returns with educator expenses',\n",
       " 'N03230': 'Number of returns with tuition and fees deduction',\n",
       " 'N03240': 'Returns with domestic production activities deduction',\n",
       " 'N03270': 'Number of returns with self-employment health insurance deduction',\n",
       " 'N03300': 'Number of returns with self-employment retirement plans',\n",
       " 'N04470': 'Number of returns with itemized deductions',\n",
       " 'N04800': 'Number of returns with taxable income',\n",
       " 'N05780': 'Number of returns with excess advance premium tax credit repayment',\n",
       " 'N05800': 'Number of returns with income tax before credits',\n",
       " 'N06500': 'Number of returns with income tax',\n",
       " 'N07100': 'Number of returns with total tax credits',\n",
       " 'N07180': 'Number of returns with child and dependent care credit',\n",
       " 'N07220': 'Number of returns with child tax credit',\n",
       " 'N07230': 'Number of returns with nonrefundable education credit',\n",
       " 'N07240': 'Number of returns with retirement savings contribution credit',\n",
       " 'N07260': 'Number of returns with residential energy tax credit',\n",
       " 'N07300': 'Number of returns with foreign tax credit',\n",
       " 'N09400': 'Number of returns with self-employment tax',\n",
       " 'N09600': 'Number of returns with alternative minimum tax ',\n",
       " 'N09750': 'Number of returns with health care individual responsibility payment',\n",
       " 'N1': 'Number of returns',\n",
       " 'N10300': 'Number of returns with tax liability',\n",
       " 'N10600': 'Number of returns with total tax payments',\n",
       " 'N10960': 'Number of returns with refundable education credit',\n",
       " 'N11070': 'Number of returns with additional child tax credit',\n",
       " 'N11560': 'Number of returns with net premium tax credit',\n",
       " 'N11901': 'Number of returns with tax due at time of filing',\n",
       " 'N11902': 'Number of returns with overpayments refunded',\n",
       " 'N18300': 'Number of returns with taxes paid',\n",
       " 'N18425': 'Number of returns with State and local income taxes',\n",
       " 'N18450': 'Number of returns with State and local general sales tax',\n",
       " 'N18500': 'Number of returns with real estate taxes',\n",
       " 'N19300': 'Number of returns with mortgage interest paid',\n",
       " 'N19700': 'Number of returns with contributions',\n",
       " 'N2': 'Number of exemptions',\n",
       " 'N26270': 'Number of returns with partnership/S-corp net income (less loss)',\n",
       " 'N59660': 'Number of returns with earned income credit',\n",
       " 'N59720': 'Number of returns with excess earned income credit',\n",
       " 'N85300': 'Number of returns with net investment income tax',\n",
       " 'N85530': 'Number of returns with additional Medicare tax',\n",
       " 'N85770': 'Number of returns with total premium tax credit',\n",
       " 'N85775': 'Number of returns with advance premium tax credit',\n",
       " 'NUMDEP': 'Number of dependents',\n",
       " 'PREP': \"Number of returns with paid preparer's signature\",\n",
       " 'SCHF': 'Number of farm returns',\n",
       " 'STATE': '  The State associated with the ZIP code',\n",
       " 'STATEFIPS': '  The State Federal Information Processing System (FIPS) code',\n",
       " 'TCE': 'Number of tax counseling for the elderly (TCE) prepared returns [3]',\n",
       " 'TOTAL_VITA': 'Total number of volunteer prepared returns [3]',\n",
       " 'VITA': 'Number of volunteer income tax assistance (VITA) prepared returns [3]'}"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "descr= pd.read_csv('IRS_data_var_descriptions.csv')\n",
    "descr_dict = {d['VARIABLENAME']: d['DESCRIPTION'] for d in descr.to_dict(orient='records')}\n",
    "descr_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11adb4710>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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6CwYMIKrf+iatooweC0tfJWzcWNn9iMg2rdNmLnfPAl/aYvJzefPvAu4qYh3c/Xniq762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\nep9FsNWOOgZsd8K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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a4bf950>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(top_votes['total_votes'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([u'num_returns', u'mars1', u'MARS2', u'MARS4', u'PREP', u'N2',\n",
       "       u'num_dependents', u'TOTAL_VITA', u'VITA', u'TCE',\n",
       "       ...\n",
       "       u'N85530', u'A85530', u'N85300', u'A85300', u'N11901', u'A11901',\n",
       "       u'N11902', u'A11902', u'people', u'FIPS'],\n",
       "      dtype='object', length=125)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inc_fips.columns[1:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier,AdaBoostClassifier\n",
    "from sklearn.model_selection import train_test_split # in case I use this later but at first I won't\n",
    "from sklearn.tree import DecisionTreeClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.metrics import accuracy_score, confusion_matrix, classification_report\n",
    "from sklearn.model_selection import cross_val_score\n",
    "def evaluate_model(m):\n",
    "    model = m.fit(X_train,y_train)\n",
    "    y_pred = model.predict(X_test)\n",
    "    score = accuracy_score(y_test, y_pred)\n",
    "    conf_matrix = confusion_matrix(y_test,y_pred,labels =[0,1])\n",
    "    class_report = classification_report\n",
    "    print m,'\\n'\n",
    "    print \"Accuracy Score:\\t{:0.3}\".format(score.round(3)),'\\n\\n'\n",
    "    crossval = cross_val_score(m, X, y,cv=10)\n",
    "    print \"Cross Val Scores:\", crossval,'\\n'\n",
    "    print \"Avg cross val:\", np.mean(crossval),'\\n'\n",
    "    print \"Predicted Totals:\" # Predicted totals for all y\n",
    "    for i,v in enumerate(np.bincount(y)):\n",
    "        print \"class \"+str(i)+':' , v\n",
    "    print \"\\nConfusion Matrix:\"\n",
    "    conmat = np.array(confusion_matrix(y_test, y_pred, labels=[1,0]))\n",
    "    confusion = pd.DataFrame(conmat, index=['Actual 1', 'Actual 0'],\n",
    "                         columns=['Predicted 1','Predicted 0'])\n",
    "    print(confusion),'\\n'\n",
    "    print \"Classification Report:\"\n",
    "    print(classification_report(y_test, y_pred, target_names=['Clinton Lose','Clinton Win']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>agi_stub</th>\n",
       "      <th>num_returns</th>\n",
       "      <th>mars1</th>\n",
       "      <th>MARS2</th>\n",
       "      <th>MARS4</th>\n",
       "      <th>PREP</th>\n",
       "      <th>N2</th>\n",
       "      <th>num_dependents</th>\n",
       "      <th>TOTAL_VITA</th>\n",
       "      <th>VITA</th>\n",
       "      <th>...</th>\n",
       "      <th>N85530</th>\n",
       "      <th>A85530</th>\n",
       "      <th>N85300</th>\n",
       "      <th>A85300</th>\n",
       "      <th>N11901</th>\n",
       "      <th>A11901</th>\n",
       "      <th>N11902</th>\n",
       "      <th>A11902</th>\n",
       "      <th>people</th>\n",
       "      <th>FIPS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FIPS</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>01000</th>\n",
       "      <td>36</td>\n",
       "      <td>2046400.0</td>\n",
       "      <td>822280.0</td>\n",
       "      <td>765870.0</td>\n",
       "      <td>418380.0</td>\n",
       "      <td>1196960.0</td>\n",
       "      <td>4183470.0</td>\n",
       "      <td>1486080.0</td>\n",
       "      <td>45780.0</td>\n",
       "      <td>29720.0</td>\n",
       "      <td>...</td>\n",
       "      <td>21810.0</td>\n",
       "      <td>37075.0</td>\n",
       "      <td>28130.0</td>\n",
       "      <td>104788.0</td>\n",
       "      <td>354820.0</td>\n",
       "      <td>1648754.0</td>\n",
       "      <td>1607350.0</td>\n",
       "      <td>4832504.0</td>\n",
       "      <td>3532480.0</td>\n",
       "      <td>01000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>01001</th>\n",
       "      <td>36</td>\n",
       "      <td>23820.0</td>\n",
       "      <td>9100.0</td>\n",
       "      <td>9960.0</td>\n",
       "      <td>4230.0</td>\n",
       "      <td>11260.0</td>\n",
       "      <td>50060.0</td>\n",
       "      <td>17910.0</td>\n",
       "      <td>510.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>...</td>\n",
       "      <td>110.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>415.0</td>\n",
       "      <td>4120.0</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>18990.0</td>\n",
       "      <td>53147.0</td>\n",
       "      <td>41730.0</td>\n",
       "      <td>01001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>01003</th>\n",
       "      <td>36</td>\n",
       "      <td>90890.0</td>\n",
       "      <td>37140.0</td>\n",
       "      <td>38890.0</td>\n",
       "      <td>12790.0</td>\n",
       "      <td>47460.0</td>\n",
       "      <td>179880.0</td>\n",
       "      <td>55660.0</td>\n",
       "      <td>1620.0</td>\n",
       "      <td>400.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1240.0</td>\n",
       "      <td>1707.0</td>\n",
       "      <td>1630.0</td>\n",
       "      <td>4836.0</td>\n",
       "      <td>20450.0</td>\n",
       "      <td>108558.0</td>\n",
       "      <td>64600.0</td>\n",
       "      <td>180864.0</td>\n",
       "      <td>146550.0</td>\n",
       "      <td>01003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>01005</th>\n",
       "      <td>36</td>\n",
       "      <td>9730.0</td>\n",
       "      <td>3540.0</td>\n",
       "      <td>3090.0</td>\n",
       "      <td>2980.0</td>\n",
       "      <td>6940.0</td>\n",
       "      <td>20300.0</td>\n",
       "      <td>7860.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>...</td>\n",
       "      <td>30.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>1360.0</td>\n",
       "      <td>4785.0</td>\n",
       "      <td>7990.0</td>\n",
       "      <td>24707.0</td>\n",
       "      <td>17590.0</td>\n",
       "      <td>01005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>01007</th>\n",
       "      <td>36</td>\n",
       "      <td>7980.0</td>\n",
       "      <td>2760.0</td>\n",
       "      <td>3350.0</td>\n",
       "      <td>1720.0</td>\n",
       "      <td>4880.0</td>\n",
       "      <td>17320.0</td>\n",
       "      <td>6340.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>1130.0</td>\n",
       "      <td>5526.0</td>\n",
       "      <td>6600.0</td>\n",
       "      <td>19513.0</td>\n",
       "      <td>14320.0</td>\n",
       "      <td>01007</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 126 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       agi_stub  num_returns     mars1     MARS2     MARS4       PREP  \\\n",
       "FIPS                                                                    \n",
       "01000        36    2046400.0  822280.0  765870.0  418380.0  1196960.0   \n",
       "01001        36      23820.0    9100.0    9960.0    4230.0    11260.0   \n",
       "01003        36      90890.0   37140.0   38890.0   12790.0    47460.0   \n",
       "01005        36       9730.0    3540.0    3090.0    2980.0     6940.0   \n",
       "01007        36       7980.0    2760.0    3350.0    1720.0     4880.0   \n",
       "\n",
       "              N2  num_dependents  TOTAL_VITA     VITA  ...     N85530  \\\n",
       "FIPS                                                   ...              \n",
       "01000  4183470.0       1486080.0     45780.0  29720.0  ...    21810.0   \n",
       "01001    50060.0         17910.0       510.0    150.0  ...      110.0   \n",
       "01003   179880.0         55660.0      1620.0    400.0  ...     1240.0   \n",
       "01005    20300.0          7860.0        40.0     40.0  ...       30.0   \n",
       "01007    17320.0          6340.0        30.0     30.0  ...        0.0   \n",
       "\n",
       "        A85530   N85300    A85300    N11901     A11901     N11902     A11902  \\\n",
       "FIPS                                                                           \n",
       "01000  37075.0  28130.0  104788.0  354820.0  1648754.0  1607350.0  4832504.0   \n",
       "01001     91.0    150.0     415.0    4120.0    14000.0    18990.0    53147.0   \n",
       "01003   1707.0   1630.0    4836.0   20450.0   108558.0    64600.0   180864.0   \n",
       "01005     48.0     50.0      90.0    1360.0     4785.0     7990.0    24707.0   \n",
       "01007      0.0     30.0      56.0    1130.0     5526.0     6600.0    19513.0   \n",
       "\n",
       "          people   FIPS  \n",
       "FIPS                     \n",
       "01000  3532480.0  01000  \n",
       "01001    41730.0  01001  \n",
       "01003   146550.0  01003  \n",
       "01005    17590.0  01005  \n",
       "01007    14320.0  01007  \n",
       "\n",
       "[5 rows x 126 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inc_fips.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',\n",
       "            max_depth=None, max_features='auto', max_leaf_nodes=None,\n",
       "            min_impurity_split=1e-07, min_samples_leaf=1,\n",
       "            min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
       "            n_estimators=10, n_jobs=1, oob_score=False, random_state=None,\n",
       "            verbose=0, warm_start=False)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_cols = inc_fips.columns[1:-1]\n",
    "X = pres_county[X_cols]\n",
    "y = pres_county.clinton_win\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, stratify=y)\n",
    "clf = RandomForestClassifier()\n",
    "# clf = DecisionTreeClassifier(max_depth=10)\n",
    "# clf = AdaBoostClassifier()\n",
    "clf.fit(X, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',\n",
      "            max_depth=None, max_features='auto', max_leaf_nodes=None,\n",
      "            min_impurity_split=1e-07, min_samples_leaf=1,\n",
      "            min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
      "            n_estimators=10, n_jobs=1, oob_score=False, random_state=None,\n",
      "            verbose=0, warm_start=False) \n",
      "\n",
      "Accuracy Score:\t0.89 \n",
      "\n",
      "\n",
      "Cross Val Scores: [ 0.86538462  0.88782051  0.89423077  0.90996785  0.90996785  0.90032154\n",
      "  0.88424437  0.87459807  0.87459807  0.86173633] \n",
      "\n",
      "Avg cross val: 0.886286998104 \n",
      "\n",
      "Predicted Totals:\n",
      "class 0: 2623\n",
      "class 1: 490\n",
      "\n",
      "Confusion Matrix:\n",
      "          Predicted 1  Predicted 0\n",
      "Actual 1           52           71\n",
      "Actual 0           15          641 \n",
      "\n",
      "Classification Report:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "Clinton Lose       0.90      0.98      0.94       656\n",
      " Clinton Win       0.78      0.42      0.55       123\n",
      "\n",
      " avg / total       0.88      0.89      0.88       779\n",
      "\n"
     ]
    }
   ],
   "source": [
    "evaluate_model(clf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "A09600_med = np.median(pres_county['A09600'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "417.0"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A09600_med"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.4432691731634192"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trump_test = sum(pres_county.trump[pres_county['A09600']>A09600_med])\n",
    "tot_test = sum(pres_county.total_votes[pres_county['A09600']>A09600_med])\n",
    "float(trump_test)/float(tot_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def trait_percentile(col=X,percentile=90):\n",
    "    avg_clinton_per_trait = []\n",
    "    avg_trump_per_trait = []\n",
    "    ind_avg_per_trait = []\n",
    "    for i in X.columns:\n",
    "        trait_percentile = np.percentile(pres_county[i],percentile)\n",
    "        county_above_percentile = pres_county[i]>trait_percentile\n",
    "        clinton_vote = sum(pres_county.clinton[county_above_percentile])\n",
    "        trump_vote = sum(pres_county.trump[county_above_percentile])\n",
    "        ind_vote = sum((pres_county.total_votes[county_above_percentile]-\n",
    "                        pres_county.clinton[county_above_percentile]-\n",
    "                        pres_county.trump[county_above_percentile]))\n",
    "        total_vote = sum(pres_county.total_votes[county_above_percentile])\n",
    "        c = float(clinton_vote)/float(total_vote)\n",
    "        t = float(trump_vote)/float(total_vote)\n",
    "        i = float(ind_vote)/float(total_vote)\n",
    "        avg_clinton_per_trait.append(c)\n",
    "        avg_trump_per_trait.append(t)\n",
    "        ind_avg_per_trait.append(i)\n",
    "    return avg_clinton_per_trait,avg_trump_per_trait,ind_avg_per_trait"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>% Clinton</th>\n",
       "      <th>% Trump</th>\n",
       "      <th>Description</th>\n",
       "      <th>Feature</th>\n",
       "      <th>Importance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>0.527065</td>\n",
       "      <td>0.410748</td>\n",
       "      <td>Number of returns with tuition and fees deduction</td>\n",
       "      <td>N03230</td>\n",
       "      <td>0.054240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>0.525344</td>\n",
       "      <td>0.413157</td>\n",
       "      <td>Number of returns with refundable education cr...</td>\n",
       "      <td>N10960</td>\n",
       "      <td>0.053645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>0.480150</td>\n",
       "      <td>0.454758</td>\n",
       "      <td>Number of farm returns</td>\n",
       "      <td>SCHF</td>\n",
       "      <td>0.038331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>0.525386</td>\n",
       "      <td>0.412867</td>\n",
       "      <td>Number of returns with nonrefundable education...</td>\n",
       "      <td>N07230</td>\n",
       "      <td>0.031493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>0.527663</td>\n",
       "      <td>0.410190</td>\n",
       "      <td>Number of returns with unemployment compensation</td>\n",
       "      <td>N02300</td>\n",
       "      <td>0.026453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>0.527142</td>\n",
       "      <td>0.410792</td>\n",
       "      <td>Tuition and fees deduction amount</td>\n",
       "      <td>A03230</td>\n",
       "      <td>0.026133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>0.525485</td>\n",
       "      <td>0.412815</td>\n",
       "      <td>Self-employment tax amount</td>\n",
       "      <td>A09400</td>\n",
       "      <td>0.025870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>0.528961</td>\n",
       "      <td>0.409053</td>\n",
       "      <td>Number of returns with self-employment retirem...</td>\n",
       "      <td>N03300</td>\n",
       "      <td>0.024909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>0.524173</td>\n",
       "      <td>0.414184</td>\n",
       "      <td>Number of returns with total tax payments</td>\n",
       "      <td>N10600</td>\n",
       "      <td>0.024192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>0.528301</td>\n",
       "      <td>0.409467</td>\n",
       "      <td>Taxes paid amount</td>\n",
       "      <td>A18300</td>\n",
       "      <td>0.019412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.523210</td>\n",
       "      <td>0.415068</td>\n",
       "      <td>Number of joint returns</td>\n",
       "      <td>MARS2</td>\n",
       "      <td>0.016679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>0.524729</td>\n",
       "      <td>0.414356</td>\n",
       "      <td>Number of returns with excess earned income cr...</td>\n",
       "      <td>N59720</td>\n",
       "      <td>0.015676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.526395</td>\n",
       "      <td>0.412904</td>\n",
       "      <td>Number of head of household returns</td>\n",
       "      <td>MARS4</td>\n",
       "      <td>0.015454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>0.528336</td>\n",
       "      <td>0.409922</td>\n",
       "      <td>Residential energy tax credit amount</td>\n",
       "      <td>A07260</td>\n",
       "      <td>0.015139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.524383</td>\n",
       "      <td>0.413797</td>\n",
       "      <td>Taxable individual retirement arrangements dis...</td>\n",
       "      <td>A01400</td>\n",
       "      <td>0.015051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>0.525717</td>\n",
       "      <td>0.413612</td>\n",
       "      <td>Earned income credit amount [7]</td>\n",
       "      <td>A59660</td>\n",
       "      <td>0.013256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.524905</td>\n",
       "      <td>0.413125</td>\n",
       "      <td>Number of returns with ordinary dividends</td>\n",
       "      <td>N00600</td>\n",
       "      <td>0.013238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>0.526076</td>\n",
       "      <td>0.413261</td>\n",
       "      <td>Excess earned income credit (refundable) amoun...</td>\n",
       "      <td>A59720</td>\n",
       "      <td>0.010959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>0.524614</td>\n",
       "      <td>0.414062</td>\n",
       "      <td>Health care individual responsibility payment ...</td>\n",
       "      <td>A09750</td>\n",
       "      <td>0.010835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>0.525474</td>\n",
       "      <td>0.413487</td>\n",
       "      <td>Number of returns with earned income credit</td>\n",
       "      <td>N59660</td>\n",
       "      <td>0.010693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.524545</td>\n",
       "      <td>0.414081</td>\n",
       "      <td>NaN</td>\n",
       "      <td>num_dependents</td>\n",
       "      <td>0.010433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>0.529974</td>\n",
       "      <td>0.407750</td>\n",
       "      <td>Alternative minimum tax amount</td>\n",
       "      <td>A09600</td>\n",
       "      <td>0.010200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.528440</td>\n",
       "      <td>0.409446</td>\n",
       "      <td>Qualified dividends amount [5]</td>\n",
       "      <td>A00650</td>\n",
       "      <td>0.009852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.528176</td>\n",
       "      <td>0.409705</td>\n",
       "      <td>Ordinary dividends amount</td>\n",
       "      <td>A00600</td>\n",
       "      <td>0.009617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>0.524297</td>\n",
       "      <td>0.413988</td>\n",
       "      <td>Number of returns with total tax credits</td>\n",
       "      <td>N07100</td>\n",
       "      <td>0.009604</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.523935</td>\n",
       "      <td>0.414445</td>\n",
       "      <td>Number of exemptions</td>\n",
       "      <td>N2</td>\n",
       "      <td>0.009532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>0.525373</td>\n",
       "      <td>0.413204</td>\n",
       "      <td>Refundable education credit amount</td>\n",
       "      <td>A10960</td>\n",
       "      <td>0.009455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.535880</td>\n",
       "      <td>0.403436</td>\n",
       "      <td>Number of volunteer income tax assistance (VIT...</td>\n",
       "      <td>VITA</td>\n",
       "      <td>0.009252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.530980</td>\n",
       "      <td>0.407374</td>\n",
       "      <td>State and local income tax refunds amount</td>\n",
       "      <td>A00700</td>\n",
       "      <td>0.008957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.525789</td>\n",
       "      <td>0.412075</td>\n",
       "      <td>Taxable interest amount</td>\n",
       "      <td>A00300</td>\n",
       "      <td>0.008816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>0.528739</td>\n",
       "      <td>0.409395</td>\n",
       "      <td>Net premium tax credit amount</td>\n",
       "      <td>A11560</td>\n",
       "      <td>0.008769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.527538</td>\n",
       "      <td>0.410180</td>\n",
       "      <td>Net capital gain (less loss) amount</td>\n",
       "      <td>A01000</td>\n",
       "      <td>0.008450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>0.529315</td>\n",
       "      <td>0.408825</td>\n",
       "      <td>Foreign tax credit amount</td>\n",
       "      <td>A07300</td>\n",
       "      <td>0.008439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>0.523234</td>\n",
       "      <td>0.413780</td>\n",
       "      <td>Domestic production activities deduction amount</td>\n",
       "      <td>A03240</td>\n",
       "      <td>0.008309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.525391</td>\n",
       "      <td>0.413023</td>\n",
       "      <td>Taxable pensions and annuities amount</td>\n",
       "      <td>A01700</td>\n",
       "      <td>0.008263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.532158</td>\n",
       "      <td>0.405909</td>\n",
       "      <td>Number of returns with state and local income ...</td>\n",
       "      <td>N00700</td>\n",
       "      <td>0.008150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>0.523654</td>\n",
       "      <td>0.414671</td>\n",
       "      <td>Number of returns with child tax credit</td>\n",
       "      <td>N07220</td>\n",
       "      <td>0.008089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.524935</td>\n",
       "      <td>0.412849</td>\n",
       "      <td>Number of returns with net capital gain (less ...</td>\n",
       "      <td>N01000</td>\n",
       "      <td>0.008071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.523638</td>\n",
       "      <td>0.414901</td>\n",
       "      <td>Number of returns with paid preparer's signature</td>\n",
       "      <td>PREP</td>\n",
       "      <td>0.008011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>0.525761</td>\n",
       "      <td>0.412227</td>\n",
       "      <td>Partnership/S-corp net income (less loss) amount</td>\n",
       "      <td>A26270</td>\n",
       "      <td>0.007801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.525143</td>\n",
       "      <td>0.412856</td>\n",
       "      <td>Number of returns with qualified dividends</td>\n",
       "      <td>N00650</td>\n",
       "      <td>0.007716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.525143</td>\n",
       "      <td>0.413158</td>\n",
       "      <td>Business or professional net income (less loss...</td>\n",
       "      <td>A00900</td>\n",
       "      <td>0.007708</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>0.525451</td>\n",
       "      <td>0.412304</td>\n",
       "      <td>Self-employment health insurance deduction amount</td>\n",
       "      <td>A03270</td>\n",
       "      <td>0.007395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>0.525437</td>\n",
       "      <td>0.412819</td>\n",
       "      <td>Number of returns with contributions</td>\n",
       "      <td>N19700</td>\n",
       "      <td>0.007286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>0.525147</td>\n",
       "      <td>0.413229</td>\n",
       "      <td>Total tax payments amount</td>\n",
       "      <td>A10600</td>\n",
       "      <td>0.007267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.524896</td>\n",
       "      <td>0.413113</td>\n",
       "      <td>Number of returns with taxable interest</td>\n",
       "      <td>N00300</td>\n",
       "      <td>0.007247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>0.523396</td>\n",
       "      <td>0.415059</td>\n",
       "      <td>Retirement savings contribution credit amount</td>\n",
       "      <td>A07240</td>\n",
       "      <td>0.007126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>0.525947</td>\n",
       "      <td>0.411802</td>\n",
       "      <td>Number of returns with student loan interest d...</td>\n",
       "      <td>N03210</td>\n",
       "      <td>0.006685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>0.525694</td>\n",
       "      <td>0.412227</td>\n",
       "      <td>Total statutory adjustments amount</td>\n",
       "      <td>A02900</td>\n",
       "      <td>0.006563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>0.524326</td>\n",
       "      <td>0.414046</td>\n",
       "      <td>Number of returns with taxable Social Security...</td>\n",
       "      <td>N02500</td>\n",
       "      <td>0.006414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>0.525472</td>\n",
       "      <td>0.413243</td>\n",
       "      <td>Educator expenses amount</td>\n",
       "      <td>A03220</td>\n",
       "      <td>0.006403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>0.523266</td>\n",
       "      <td>0.415269</td>\n",
       "      <td>Number of returns with retirement savings cont...</td>\n",
       "      <td>N07240</td>\n",
       "      <td>0.006381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>0.524546</td>\n",
       "      <td>0.413556</td>\n",
       "      <td>Number of returns with tax due at time of filing</td>\n",
       "      <td>N11901</td>\n",
       "      <td>0.006319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0.524963</td>\n",
       "      <td>0.413236</td>\n",
       "      <td>Taxable Social Security benefits amount</td>\n",
       "      <td>A02500</td>\n",
       "      <td>0.006137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>0.525189</td>\n",
       "      <td>0.413570</td>\n",
       "      <td>Number of returns with excess advance premium ...</td>\n",
       "      <td>N05780</td>\n",
       "      <td>0.006127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>0.526169</td>\n",
       "      <td>0.411687</td>\n",
       "      <td>Number of returns with foreign tax credit</td>\n",
       "      <td>N07300</td>\n",
       "      <td>0.006108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>0.522919</td>\n",
       "      <td>0.415210</td>\n",
       "      <td>Child tax credit amount</td>\n",
       "      <td>A07220</td>\n",
       "      <td>0.005841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>0.525323</td>\n",
       "      <td>0.412923</td>\n",
       "      <td>Nonrefundable education credit amount</td>\n",
       "      <td>A07230</td>\n",
       "      <td>0.005683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>0.524131</td>\n",
       "      <td>0.414964</td>\n",
       "      <td>Number of returns with advance premium tax credit</td>\n",
       "      <td>N85775</td>\n",
       "      <td>0.005654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>0.524348</td>\n",
       "      <td>0.413620</td>\n",
       "      <td>Number of returns with partnership/S-corp net ...</td>\n",
       "      <td>N26270</td>\n",
       "      <td>0.005598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>0.524927</td>\n",
       "      <td>0.413309</td>\n",
       "      <td>Taxable income amount</td>\n",
       "      <td>A04800</td>\n",
       "      <td>0.005575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>0.528826</td>\n",
       "      <td>0.409171</td>\n",
       "      <td>Self-employment retirement plans amount</td>\n",
       "      <td>A03300</td>\n",
       "      <td>0.005529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0.525522</td>\n",
       "      <td>0.413054</td>\n",
       "      <td>Number of returns with educator expenses</td>\n",
       "      <td>N03220</td>\n",
       "      <td>0.005495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.524221</td>\n",
       "      <td>0.414290</td>\n",
       "      <td>Number of returns with taxable pensions and an...</td>\n",
       "      <td>N01700</td>\n",
       "      <td>0.005333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>0.525887</td>\n",
       "      <td>0.412749</td>\n",
       "      <td>Child and dependent care credit amount</td>\n",
       "      <td>A07180</td>\n",
       "      <td>0.005282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>0.525862</td>\n",
       "      <td>0.412051</td>\n",
       "      <td>Mortgage interest paid amount</td>\n",
       "      <td>A19300</td>\n",
       "      <td>0.005249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>0.525193</td>\n",
       "      <td>0.414373</td>\n",
       "      <td>Number of returns with State and local general...</td>\n",
       "      <td>N18450</td>\n",
       "      <td>0.005086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>0.525020</td>\n",
       "      <td>0.413301</td>\n",
       "      <td>Contributions amount</td>\n",
       "      <td>A19700</td>\n",
       "      <td>0.005038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.524198</td>\n",
       "      <td>0.414160</td>\n",
       "      <td>Number of returns with salaries and wages</td>\n",
       "      <td>N00200</td>\n",
       "      <td>0.004912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>0.525755</td>\n",
       "      <td>0.411986</td>\n",
       "      <td>IRA payments amount</td>\n",
       "      <td>A03150</td>\n",
       "      <td>0.004904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>0.525694</td>\n",
       "      <td>0.412317</td>\n",
       "      <td>Number of returns with real estate taxes</td>\n",
       "      <td>N18500</td>\n",
       "      <td>0.004894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>0.526395</td>\n",
       "      <td>0.411485</td>\n",
       "      <td>Number of returns with net investment income tax</td>\n",
       "      <td>N85300</td>\n",
       "      <td>0.004880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>0.525952</td>\n",
       "      <td>0.411901</td>\n",
       "      <td>Number of returns with IRA payments</td>\n",
       "      <td>N03150</td>\n",
       "      <td>0.004862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>0.525362</td>\n",
       "      <td>0.412932</td>\n",
       "      <td>Income tax before credits amount</td>\n",
       "      <td>A05800</td>\n",
       "      <td>0.004802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>0.525115</td>\n",
       "      <td>0.414041</td>\n",
       "      <td>Number of returns with total premium tax credit</td>\n",
       "      <td>N85770</td>\n",
       "      <td>0.004750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>0.525645</td>\n",
       "      <td>0.413423</td>\n",
       "      <td>Additional child tax credit amount</td>\n",
       "      <td>A11070</td>\n",
       "      <td>0.004711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>0.531848</td>\n",
       "      <td>0.405695</td>\n",
       "      <td>Number of returns with State and local income ...</td>\n",
       "      <td>N18425</td>\n",
       "      <td>0.004696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.529936</td>\n",
       "      <td>0.408283</td>\n",
       "      <td>Total number of volunteer prepared returns [3]</td>\n",
       "      <td>TOTAL_VITA</td>\n",
       "      <td>0.004556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>0.531872</td>\n",
       "      <td>0.405933</td>\n",
       "      <td>State and local income taxes amount</td>\n",
       "      <td>A18425</td>\n",
       "      <td>0.004534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>0.525549</td>\n",
       "      <td>0.413523</td>\n",
       "      <td>Number of returns with additional child tax cr...</td>\n",
       "      <td>N11070</td>\n",
       "      <td>0.004510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>0.523181</td>\n",
       "      <td>0.416107</td>\n",
       "      <td>Advance premium tax credit amount</td>\n",
       "      <td>A85775</td>\n",
       "      <td>0.004481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>0.528606</td>\n",
       "      <td>0.409173</td>\n",
       "      <td>Real estate taxes amount</td>\n",
       "      <td>A18500</td>\n",
       "      <td>0.004375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.524609</td>\n",
       "      <td>0.413499</td>\n",
       "      <td>NaN</td>\n",
       "      <td>tot_inc_amt</td>\n",
       "      <td>0.004311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>0.524113</td>\n",
       "      <td>0.414130</td>\n",
       "      <td>Number of returns with income tax before credits</td>\n",
       "      <td>N05800</td>\n",
       "      <td>0.004246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>0.524756</td>\n",
       "      <td>0.413674</td>\n",
       "      <td>Number of returns with self-employment tax</td>\n",
       "      <td>N09400</td>\n",
       "      <td>0.004195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>0.530311</td>\n",
       "      <td>0.407280</td>\n",
       "      <td>Unemployment compensation amount [6]</td>\n",
       "      <td>A02300</td>\n",
       "      <td>0.004146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>0.526119</td>\n",
       "      <td>0.411655</td>\n",
       "      <td>Student loan interest deduction amount</td>\n",
       "      <td>A03210</td>\n",
       "      <td>0.003977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.529124</td>\n",
       "      <td>0.408502</td>\n",
       "      <td>Number of tax counseling for the elderly (TCE)...</td>\n",
       "      <td>TCE</td>\n",
       "      <td>0.003847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.524169</td>\n",
       "      <td>0.413999</td>\n",
       "      <td>Salaries and wages amount</td>\n",
       "      <td>A00200</td>\n",
       "      <td>0.003810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>0.527904</td>\n",
       "      <td>0.410056</td>\n",
       "      <td>Number of returns with alternative minimum tax</td>\n",
       "      <td>N09600</td>\n",
       "      <td>0.003800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>0.523901</td>\n",
       "      <td>0.414841</td>\n",
       "      <td>Number of returns with health care individual ...</td>\n",
       "      <td>N09750</td>\n",
       "      <td>0.003767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>0.525886</td>\n",
       "      <td>0.412484</td>\n",
       "      <td>Number of returns with residential energy tax ...</td>\n",
       "      <td>N07260</td>\n",
       "      <td>0.003731</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>0.523910</td>\n",
       "      <td>0.414364</td>\n",
       "      <td>Number of returns with tax liability</td>\n",
       "      <td>N10300</td>\n",
       "      <td>0.003709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>0.524050</td>\n",
       "      <td>0.414404</td>\n",
       "      <td>Number of returns with overpayments refunded</td>\n",
       "      <td>N11902</td>\n",
       "      <td>0.003688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>0.526993</td>\n",
       "      <td>0.411331</td>\n",
       "      <td>Additional Medicare tax amount</td>\n",
       "      <td>A85530</td>\n",
       "      <td>0.003550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>0.527493</td>\n",
       "      <td>0.412072</td>\n",
       "      <td>State and local general sales tax amount</td>\n",
       "      <td>A18450</td>\n",
       "      <td>0.003462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>0.525587</td>\n",
       "      <td>0.412653</td>\n",
       "      <td>Total tax liability amount [10]</td>\n",
       "      <td>A10300</td>\n",
       "      <td>0.003403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>0.525937</td>\n",
       "      <td>0.412217</td>\n",
       "      <td>Tax due at time of filing amount [11]</td>\n",
       "      <td>A11901</td>\n",
       "      <td>0.003383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.524149</td>\n",
       "      <td>0.414218</td>\n",
       "      <td>NaN</td>\n",
       "      <td>num_tot_inc</td>\n",
       "      <td>0.003375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>0.524242</td>\n",
       "      <td>0.414400</td>\n",
       "      <td>Overpayments refunded amount [12]</td>\n",
       "      <td>A11902</td>\n",
       "      <td>0.003296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>0.526630</td>\n",
       "      <td>0.411569</td>\n",
       "      <td>Number of returns with additional Medicare tax</td>\n",
       "      <td>N85530</td>\n",
       "      <td>0.003286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>0.525431</td>\n",
       "      <td>0.412807</td>\n",
       "      <td>Income tax amount [9]</td>\n",
       "      <td>A06500</td>\n",
       "      <td>0.003074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>0.524066</td>\n",
       "      <td>0.415190</td>\n",
       "      <td>Total premium tax credit amount</td>\n",
       "      <td>A85770</td>\n",
       "      <td>0.003069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.524562</td>\n",
       "      <td>0.413694</td>\n",
       "      <td>Number of returns with taxable individual reti...</td>\n",
       "      <td>N01400</td>\n",
       "      <td>0.002894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.524656</td>\n",
       "      <td>0.413733</td>\n",
       "      <td>NaN</td>\n",
       "      <td>mars1</td>\n",
       "      <td>0.002866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>0.526736</td>\n",
       "      <td>0.412184</td>\n",
       "      <td>Number of returns with net premium tax credit</td>\n",
       "      <td>N11560</td>\n",
       "      <td>0.002828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>0.525549</td>\n",
       "      <td>0.412998</td>\n",
       "      <td>Number of returns with child and dependent car...</td>\n",
       "      <td>N07180</td>\n",
       "      <td>0.002805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>0.525607</td>\n",
       "      <td>0.412492</td>\n",
       "      <td>Number of returns with itemized deductions</td>\n",
       "      <td>N04470</td>\n",
       "      <td>0.002691</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>0.525394</td>\n",
       "      <td>0.412322</td>\n",
       "      <td>Number of returns with self-employment health ...</td>\n",
       "      <td>N03270</td>\n",
       "      <td>0.002674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.524609</td>\n",
       "      <td>0.413499</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AGI</td>\n",
       "      <td>0.002642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>0.525694</td>\n",
       "      <td>0.412324</td>\n",
       "      <td>Amount of AGI for itemized returns</td>\n",
       "      <td>A00101</td>\n",
       "      <td>0.002579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>0.530065</td>\n",
       "      <td>0.406226</td>\n",
       "      <td>Returns with domestic production activities de...</td>\n",
       "      <td>N03240</td>\n",
       "      <td>0.002384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>0.525515</td>\n",
       "      <td>0.412583</td>\n",
       "      <td>Number of returns with taxes paid</td>\n",
       "      <td>N18300</td>\n",
       "      <td>0.002312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>0.524370</td>\n",
       "      <td>0.413710</td>\n",
       "      <td>Total tax credits amount</td>\n",
       "      <td>A07100</td>\n",
       "      <td>0.002224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>0.529699</td>\n",
       "      <td>0.408113</td>\n",
       "      <td>Net investment income tax amount</td>\n",
       "      <td>A85300</td>\n",
       "      <td>0.002049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>0.524106</td>\n",
       "      <td>0.414223</td>\n",
       "      <td>Number of returns with income tax</td>\n",
       "      <td>N06500</td>\n",
       "      <td>0.001989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.524511</td>\n",
       "      <td>0.414036</td>\n",
       "      <td>Number of returns with business or professiona...</td>\n",
       "      <td>N00900</td>\n",
       "      <td>0.001956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>0.524865</td>\n",
       "      <td>0.413570</td>\n",
       "      <td>Excess advance premium tax credit repayment am...</td>\n",
       "      <td>A05780</td>\n",
       "      <td>0.001844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.524149</td>\n",
       "      <td>0.414218</td>\n",
       "      <td>NaN</td>\n",
       "      <td>num_returns</td>\n",
       "      <td>0.001487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>0.526012</td>\n",
       "      <td>0.412092</td>\n",
       "      <td>Total itemized deductions amount</td>\n",
       "      <td>A04470</td>\n",
       "      <td>0.001201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>0.524053</td>\n",
       "      <td>0.414329</td>\n",
       "      <td>NaN</td>\n",
       "      <td>people</td>\n",
       "      <td>0.001089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>0.525645</td>\n",
       "      <td>0.412404</td>\n",
       "      <td>Number of returns with mortgage interest paid</td>\n",
       "      <td>N19300</td>\n",
       "      <td>0.001084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>0.524837</td>\n",
       "      <td>0.413291</td>\n",
       "      <td>Number of returns with total statutory adjustm...</td>\n",
       "      <td>N02900</td>\n",
       "      <td>0.000835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>0.524135</td>\n",
       "      <td>0.414103</td>\n",
       "      <td>Number of returns with taxable income</td>\n",
       "      <td>N04800</td>\n",
       "      <td>0.000599</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     % Clinton   % Trump                                        Description  \\\n",
       "50    0.527065  0.410748  Number of returns with tuition and fees deduction   \n",
       "107   0.525344  0.413157  Number of returns with refundable education cr...   \n",
       "31    0.480150  0.454758                             Number of farm returns   \n",
       "83    0.525386  0.412867  Number of returns with nonrefundable education...   \n",
       "32    0.527663  0.410190   Number of returns with unemployment compensation   \n",
       "51    0.527142  0.410792                  Tuition and fees deduction amount   \n",
       "92    0.525485  0.412815                         Self-employment tax amount   \n",
       "42    0.528961  0.409053  Number of returns with self-employment retirem...   \n",
       "99    0.524173  0.414184          Number of returns with total tax payments   \n",
       "64    0.528301  0.409467                                  Taxes paid amount   \n",
       "2     0.523210  0.415068                            Number of joint returns   \n",
       "103   0.524729  0.414356  Number of returns with excess earned income cr...   \n",
       "3     0.526395  0.412904                Number of head of household returns   \n",
       "90    0.528336  0.409922               Residential energy tax credit amount   \n",
       "28    0.524383  0.413797  Taxable individual retirement arrangements dis...   \n",
       "102   0.525717  0.413612                  Earned income credit amount [7]     \n",
       "17    0.524905  0.413125         Number of returns with ordinary dividends    \n",
       "104   0.526076  0.413261  Excess earned income credit (refundable) amoun...   \n",
       "98    0.524614  0.414062  Health care individual responsibility payment ...   \n",
       "101   0.525474  0.413487        Number of returns with earned income credit   \n",
       "6     0.524545  0.414081                                                NaN   \n",
       "74    0.529974  0.407750                     Alternative minimum tax amount   \n",
       "20    0.528440  0.409446                     Qualified dividends amount [5]   \n",
       "18    0.528176  0.409705                          Ordinary dividends amount   \n",
       "77    0.524297  0.413988           Number of returns with total tax credits   \n",
       "5     0.523935  0.414445                               Number of exemptions   \n",
       "108   0.525373  0.413204                 Refundable education credit amount   \n",
       "8     0.535880  0.403436  Number of volunteer income tax assistance (VIT...   \n",
       "22    0.530980  0.407374          State and local income tax refunds amount   \n",
       "16    0.525789  0.412075                            Taxable interest amount   \n",
       "110   0.528739  0.409395                      Net premium tax credit amount   \n",
       "26    0.527538  0.410180                Net capital gain (less loss) amount   \n",
       "80    0.529315  0.408825                          Foreign tax credit amount   \n",
       "53    0.523234  0.413780    Domestic production activities deduction amount   \n",
       "30    0.525391  0.413023              Taxable pensions and annuities amount   \n",
       "21    0.532158  0.405909  Number of returns with state and local income ...   \n",
       "87    0.523654  0.414671            Number of returns with child tax credit   \n",
       "25    0.524935  0.412849  Number of returns with net capital gain (less ...   \n",
       "4     0.523638  0.414901   Number of returns with paid preparer's signature   \n",
       "37    0.525761  0.412227   Partnership/S-corp net income (less loss) amount   \n",
       "19    0.525143  0.412856         Number of returns with qualified dividends   \n",
       "24    0.525143  0.413158  Business or professional net income (less loss...   \n",
       "45    0.525451  0.412304  Self-employment health insurance deduction amount   \n",
       "67    0.525437  0.412819               Number of returns with contributions   \n",
       "100   0.525147  0.413229                          Total tax payments amount   \n",
       "15    0.524896  0.413113            Number of returns with taxable interest   \n",
       "86    0.523396  0.415059      Retirement savings contribution credit amount   \n",
       "48    0.525947  0.411802  Number of returns with student loan interest d...   \n",
       "39    0.525694  0.412227                 Total statutory adjustments amount   \n",
       "34    0.524326  0.414046  Number of returns with taxable Social Security...   \n",
       "41    0.525472  0.413243                           Educator expenses amount   \n",
       "85    0.523266  0.415269  Number of returns with retirement savings cont...   \n",
       "119   0.524546  0.413556   Number of returns with tax due at time of filing   \n",
       "35    0.524963  0.413236            Taxable Social Security benefits amount   \n",
       "75    0.525189  0.413570  Number of returns with excess advance premium ...   \n",
       "79    0.526169  0.411687          Number of returns with foreign tax credit   \n",
       "88    0.522919  0.415210                            Child tax credit amount   \n",
       "84    0.525323  0.412923              Nonrefundable education credit amount   \n",
       "95    0.524131  0.414964  Number of returns with advance premium tax credit   \n",
       "36    0.524348  0.413620  Number of returns with partnership/S-corp net ...   \n",
       "70    0.524927  0.413309                              Taxable income amount   \n",
       "43    0.528826  0.409171            Self-employment retirement plans amount   \n",
       "40    0.525522  0.413054           Number of returns with educator expenses   \n",
       "29    0.524221  0.414290  Number of returns with taxable pensions and an...   \n",
       "82    0.525887  0.412749             Child and dependent care credit amount   \n",
       "66    0.525862  0.412051                      Mortgage interest paid amount   \n",
       "59    0.525193  0.414373  Number of returns with State and local general...   \n",
       "68    0.525020  0.413301                               Contributions amount   \n",
       "13    0.524198  0.414160          Number of returns with salaries and wages   \n",
       "47    0.525755  0.411986                                IRA payments amount   \n",
       "61    0.525694  0.412317           Number of returns with real estate taxes   \n",
       "117   0.526395  0.411485   Number of returns with net investment income tax   \n",
       "46    0.525952  0.411901                Number of returns with IRA payments   \n",
       "72    0.525362  0.412932                   Income tax before credits amount   \n",
       "93    0.525115  0.414041    Number of returns with total premium tax credit   \n",
       "106   0.525645  0.413423                 Additional child tax credit amount   \n",
       "57    0.531848  0.405695  Number of returns with State and local income ...   \n",
       "7     0.529936  0.408283     Total number of volunteer prepared returns [3]   \n",
       "58    0.531872  0.405933                State and local income taxes amount   \n",
       "105   0.525549  0.413523  Number of returns with additional child tax cr...   \n",
       "96    0.523181  0.416107                  Advance premium tax credit amount   \n",
       "62    0.528606  0.409173                           Real estate taxes amount   \n",
       "12    0.524609  0.413499                                                NaN   \n",
       "71    0.524113  0.414130   Number of returns with income tax before credits   \n",
       "91    0.524756  0.413674         Number of returns with self-employment tax   \n",
       "33    0.530311  0.407280               Unemployment compensation amount [6]   \n",
       "49    0.526119  0.411655             Student loan interest deduction amount   \n",
       "9     0.529124  0.408502  Number of tax counseling for the elderly (TCE)...   \n",
       "14    0.524169  0.413999                          Salaries and wages amount   \n",
       "73    0.527904  0.410056    Number of returns with alternative minimum tax    \n",
       "97    0.523901  0.414841  Number of returns with health care individual ...   \n",
       "89    0.525886  0.412484  Number of returns with residential energy tax ...   \n",
       "113   0.523910  0.414364               Number of returns with tax liability   \n",
       "121   0.524050  0.414404       Number of returns with overpayments refunded   \n",
       "116   0.526993  0.411331                     Additional Medicare tax amount   \n",
       "60    0.527493  0.412072           State and local general sales tax amount   \n",
       "114   0.525587  0.412653                  Total tax liability amount [10]     \n",
       "120   0.525937  0.412217            Tax due at time of filing amount [11]     \n",
       "11    0.524149  0.414218                                                NaN   \n",
       "122   0.524242  0.414400                Overpayments refunded amount [12]     \n",
       "115   0.526630  0.411569     Number of returns with additional Medicare tax   \n",
       "112   0.525431  0.412807                            Income tax amount [9]     \n",
       "94    0.524066  0.415190                    Total premium tax credit amount   \n",
       "27    0.524562  0.413694  Number of returns with taxable individual reti...   \n",
       "1     0.524656  0.413733                                                NaN   \n",
       "109   0.526736  0.412184      Number of returns with net premium tax credit   \n",
       "81    0.525549  0.412998  Number of returns with child and dependent car...   \n",
       "54    0.525607  0.412492         Number of returns with itemized deductions   \n",
       "44    0.525394  0.412322  Number of returns with self-employment health ...   \n",
       "10    0.524609  0.413499                                                NaN   \n",
       "56    0.525694  0.412324                 Amount of AGI for itemized returns   \n",
       "52    0.530065  0.406226  Returns with domestic production activities de...   \n",
       "63    0.525515  0.412583                  Number of returns with taxes paid   \n",
       "78    0.524370  0.413710                           Total tax credits amount   \n",
       "118   0.529699  0.408113                   Net investment income tax amount   \n",
       "111   0.524106  0.414223                  Number of returns with income tax   \n",
       "23    0.524511  0.414036  Number of returns with business or professiona...   \n",
       "76    0.524865  0.413570  Excess advance premium tax credit repayment am...   \n",
       "0     0.524149  0.414218                                                NaN   \n",
       "55    0.526012  0.412092                   Total itemized deductions amount   \n",
       "123   0.524053  0.414329                                                NaN   \n",
       "65    0.525645  0.412404      Number of returns with mortgage interest paid   \n",
       "38    0.524837  0.413291  Number of returns with total statutory adjustm...   \n",
       "69    0.524135  0.414103              Number of returns with taxable income   \n",
       "\n",
       "            Feature  Importance  \n",
       "50           N03230    0.054240  \n",
       "107          N10960    0.053645  \n",
       "31             SCHF    0.038331  \n",
       "83           N07230    0.031493  \n",
       "32           N02300    0.026453  \n",
       "51           A03230    0.026133  \n",
       "92           A09400    0.025870  \n",
       "42           N03300    0.024909  \n",
       "99           N10600    0.024192  \n",
       "64           A18300    0.019412  \n",
       "2             MARS2    0.016679  \n",
       "103          N59720    0.015676  \n",
       "3             MARS4    0.015454  \n",
       "90           A07260    0.015139  \n",
       "28           A01400    0.015051  \n",
       "102          A59660    0.013256  \n",
       "17           N00600    0.013238  \n",
       "104          A59720    0.010959  \n",
       "98           A09750    0.010835  \n",
       "101          N59660    0.010693  \n",
       "6    num_dependents    0.010433  \n",
       "74           A09600    0.010200  \n",
       "20           A00650    0.009852  \n",
       "18           A00600    0.009617  \n",
       "77           N07100    0.009604  \n",
       "5                N2    0.009532  \n",
       "108          A10960    0.009455  \n",
       "8              VITA    0.009252  \n",
       "22           A00700    0.008957  \n",
       "16           A00300    0.008816  \n",
       "110          A11560    0.008769  \n",
       "26           A01000    0.008450  \n",
       "80           A07300    0.008439  \n",
       "53           A03240    0.008309  \n",
       "30           A01700    0.008263  \n",
       "21           N00700    0.008150  \n",
       "87           N07220    0.008089  \n",
       "25           N01000    0.008071  \n",
       "4              PREP    0.008011  \n",
       "37           A26270    0.007801  \n",
       "19           N00650    0.007716  \n",
       "24           A00900    0.007708  \n",
       "45           A03270    0.007395  \n",
       "67           N19700    0.007286  \n",
       "100          A10600    0.007267  \n",
       "15           N00300    0.007247  \n",
       "86           A07240    0.007126  \n",
       "48           N03210    0.006685  \n",
       "39           A02900    0.006563  \n",
       "34           N02500    0.006414  \n",
       "41           A03220    0.006403  \n",
       "85           N07240    0.006381  \n",
       "119          N11901    0.006319  \n",
       "35           A02500    0.006137  \n",
       "75           N05780    0.006127  \n",
       "79           N07300    0.006108  \n",
       "88           A07220    0.005841  \n",
       "84           A07230    0.005683  \n",
       "95           N85775    0.005654  \n",
       "36           N26270    0.005598  \n",
       "70           A04800    0.005575  \n",
       "43           A03300    0.005529  \n",
       "40           N03220    0.005495  \n",
       "29           N01700    0.005333  \n",
       "82           A07180    0.005282  \n",
       "66           A19300    0.005249  \n",
       "59           N18450    0.005086  \n",
       "68           A19700    0.005038  \n",
       "13           N00200    0.004912  \n",
       "47           A03150    0.004904  \n",
       "61           N18500    0.004894  \n",
       "117          N85300    0.004880  \n",
       "46           N03150    0.004862  \n",
       "72           A05800    0.004802  \n",
       "93           N85770    0.004750  \n",
       "106          A11070    0.004711  \n",
       "57           N18425    0.004696  \n",
       "7        TOTAL_VITA    0.004556  \n",
       "58           A18425    0.004534  \n",
       "105          N11070    0.004510  \n",
       "96           A85775    0.004481  \n",
       "62           A18500    0.004375  \n",
       "12      tot_inc_amt    0.004311  \n",
       "71           N05800    0.004246  \n",
       "91           N09400    0.004195  \n",
       "33           A02300    0.004146  \n",
       "49           A03210    0.003977  \n",
       "9               TCE    0.003847  \n",
       "14           A00200    0.003810  \n",
       "73           N09600    0.003800  \n",
       "97           N09750    0.003767  \n",
       "89           N07260    0.003731  \n",
       "113          N10300    0.003709  \n",
       "121          N11902    0.003688  \n",
       "116          A85530    0.003550  \n",
       "60           A18450    0.003462  \n",
       "114          A10300    0.003403  \n",
       "120          A11901    0.003383  \n",
       "11      num_tot_inc    0.003375  \n",
       "122          A11902    0.003296  \n",
       "115          N85530    0.003286  \n",
       "112          A06500    0.003074  \n",
       "94           A85770    0.003069  \n",
       "27           N01400    0.002894  \n",
       "1             mars1    0.002866  \n",
       "109          N11560    0.002828  \n",
       "81           N07180    0.002805  \n",
       "54           N04470    0.002691  \n",
       "44           N03270    0.002674  \n",
       "10              AGI    0.002642  \n",
       "56           A00101    0.002579  \n",
       "52           N03240    0.002384  \n",
       "63           N18300    0.002312  \n",
       "78           A07100    0.002224  \n",
       "118          A85300    0.002049  \n",
       "111          N06500    0.001989  \n",
       "23           N00900    0.001956  \n",
       "76           A05780    0.001844  \n",
       "0       num_returns    0.001487  \n",
       "55           A04470    0.001201  \n",
       "123          people    0.001089  \n",
       "65           N19300    0.001084  \n",
       "38           N02900    0.000835  \n",
       "69           N04800    0.000599  "
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features = pd.DataFrame({'Feature':X.columns,\n",
    "                         'Importance':np.round(clf.feature_importances_,6),\n",
    "                        'Description': pd.Series(X.columns).map(descr_dict),\n",
    "                        '% Clinton':trait_percentile(X,80)[0],'% Trump':trait_percentile(X,80)[1]})\n",
    "features.sort_values(by='Importance',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(124, 5)"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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We0SSJElLSN9kaw9g88y8qGUwkiRJS03f0Yi/AZa3DESSJGkp6tuytQI4KSJOAC6Z+WVm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\nSZI69F/rTuEiB0TVXAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12a5141d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,8))\n",
    "disp_features = features[features.Importance>np.mean(features.Importance)].sort_values(by='Importance',ascending=False)\n",
    "disp_features['Importance'] /=1e-2\n",
    "feat_plot = sns.barplot(x='Feature',y='Importance',data=disp_features,color='% Clinton',palette='Blues_r')\n",
    "# plt.xticks(features, features.Description, rotation=65)\n",
    "plt.setp(feat_plot.get_xticklabels(), rotation=65)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "lr = LogisticRegression()\n",
    "lr.fit(X,y)\n",
    "coef = lr.coef_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.89559910054609704"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr.score(X,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>% Clinton</th>\n",
       "      <th>% Trump</th>\n",
       "      <th>Coefs</th>\n",
       "      <th>Description</th>\n",
       "      <th>Feature</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.557095</td>\n",
       "      <td>0.381532</td>\n",
       "      <td>1.000068</td>\n",
       "      <td>NaN</td>\n",
       "      <td>mars1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>0.559517</td>\n",
       "      <td>0.378480</td>\n",
       "      <td>1.000045</td>\n",
       "      <td>Unemployment compensation amount [6]</td>\n",
       "      <td>A02300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>0.556979</td>\n",
       "      <td>0.382764</td>\n",
       "      <td>1.000032</td>\n",
       "      <td>Earned income credit amount [7]</td>\n",
       "      <td>A59660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>0.556924</td>\n",
       "      <td>0.382844</td>\n",
       "      <td>1.000031</td>\n",
       "      <td>Excess earned income credit (refundable) amoun...</td>\n",
       "      <td>A59720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>0.555545</td>\n",
       "      <td>0.383121</td>\n",
       "      <td>1.000030</td>\n",
       "      <td>Number of returns with total tax payments</td>\n",
       "      <td>N10600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.556458</td>\n",
       "      <td>0.382366</td>\n",
       "      <td>1.000029</td>\n",
       "      <td>Business or professional net income (less loss...</td>\n",
       "      <td>A00900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.555386</td>\n",
       "      <td>0.383316</td>\n",
       "      <td>1.000026</td>\n",
       "      <td>Number of returns with salaries and wages</td>\n",
       "      <td>N00200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.555327</td>\n",
       "      <td>0.383339</td>\n",
       "      <td>1.000025</td>\n",
       "      <td>NaN</td>\n",
       "      <td>num_returns</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>0.554267</td>\n",
       "      <td>0.384360</td>\n",
       "      <td>1.000024</td>\n",
       "      <td>Number of returns with income tax before credits</td>\n",
       "      <td>N05800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>0.554267</td>\n",
       "      <td>0.384360</td>\n",
       "      <td>1.000024</td>\n",
       "      <td>Number of returns with taxable income</td>\n",
       "      <td>N04800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.555327</td>\n",
       "      <td>0.383339</td>\n",
       "      <td>1.000024</td>\n",
       "      <td>NaN</td>\n",
       "      <td>num_tot_inc</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>0.548515</td>\n",
       "      <td>0.392280</td>\n",
       "      <td>1.000024</td>\n",
       "      <td>State and local general sales tax amount</td>\n",
       "      <td>A18450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>0.559640</td>\n",
       "      <td>0.378784</td>\n",
       "      <td>1.000023</td>\n",
       "      <td>Self-employment retirement plans amount</td>\n",
       "      <td>A03300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.557897</td>\n",
       "      <td>0.382283</td>\n",
       "      <td>1.000022</td>\n",
       "      <td>Number of head of household returns</td>\n",
       "      <td>MARS4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>0.555762</td>\n",
       "      <td>0.382986</td>\n",
       "      <td>1.000021</td>\n",
       "      <td>Number of returns with overpayments refunded</td>\n",
       "      <td>N11902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>0.555960</td>\n",
       "      <td>0.382262</td>\n",
       "      <td>1.000021</td>\n",
       "      <td>Student loan interest deduction amount</td>\n",
       "      <td>A03210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.558946</td>\n",
       "      <td>0.380034</td>\n",
       "      <td>1.000019</td>\n",
       "      <td>Ordinary dividends amount</td>\n",
       "      <td>A00600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>0.554494</td>\n",
       "      <td>0.383368</td>\n",
       "      <td>1.000017</td>\n",
       "      <td>Mortgage interest paid amount</td>\n",
       "      <td>A19300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>0.554967</td>\n",
       "      <td>0.383371</td>\n",
       "      <td>1.000017</td>\n",
       "      <td>Income tax before credits amount</td>\n",
       "      <td>A05800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>0.553580</td>\n",
       "      <td>0.384920</td>\n",
       "      <td>1.000017</td>\n",
       "      <td>Number of returns with income tax</td>\n",
       "      <td>N06500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>0.555819</td>\n",
       "      <td>0.382424</td>\n",
       "      <td>1.000017</td>\n",
       "      <td>Number of returns with student loan interest d...</td>\n",
       "      <td>N03210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>0.554329</td>\n",
       "      <td>0.384468</td>\n",
       "      <td>1.000017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>people</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>0.554849</td>\n",
       "      <td>0.383774</td>\n",
       "      <td>1.000014</td>\n",
       "      <td>Number of returns with tax liability</td>\n",
       "      <td>N10300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.552220</td>\n",
       "      <td>0.386811</td>\n",
       "      <td>1.000014</td>\n",
       "      <td>Taxable individual retirement arrangements dis...</td>\n",
       "      <td>A01400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>0.556546</td>\n",
       "      <td>0.382829</td>\n",
       "      <td>1.000012</td>\n",
       "      <td>Number of returns with earned income credit</td>\n",
       "      <td>N59660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>0.557409</td>\n",
       "      <td>0.382064</td>\n",
       "      <td>1.000012</td>\n",
       "      <td>Number of returns with excess earned income cr...</td>\n",
       "      <td>N59720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>0.555659</td>\n",
       "      <td>0.383464</td>\n",
       "      <td>1.000012</td>\n",
       "      <td>Additional child tax credit amount</td>\n",
       "      <td>A11070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.557219</td>\n",
       "      <td>0.380958</td>\n",
       "      <td>1.000011</td>\n",
       "      <td>Total number of volunteer prepared returns [3]</td>\n",
       "      <td>TOTAL_VITA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>0.555831</td>\n",
       "      <td>0.382536</td>\n",
       "      <td>1.000011</td>\n",
       "      <td>Foreign tax credit amount</td>\n",
       "      <td>A07300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>0.556088</td>\n",
       "      <td>0.382963</td>\n",
       "      <td>1.000010</td>\n",
       "      <td>Number of returns with refundable education cr...</td>\n",
       "      <td>N10960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>0.549205</td>\n",
       "      <td>0.391103</td>\n",
       "      <td>1.000010</td>\n",
       "      <td>Number of returns with State and local general...</td>\n",
       "      <td>N18450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>0.554129</td>\n",
       "      <td>0.384417</td>\n",
       "      <td>1.000010</td>\n",
       "      <td>Number of returns with total tax credits</td>\n",
       "      <td>N07100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>0.556511</td>\n",
       "      <td>0.381983</td>\n",
       "      <td>1.000010</td>\n",
       "      <td>Number of returns with foreign tax credit</td>\n",
       "      <td>N07300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>0.556157</td>\n",
       "      <td>0.382525</td>\n",
       "      <td>1.000009</td>\n",
       "      <td>Number of returns with nonrefundable education...</td>\n",
       "      <td>N07230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>0.559997</td>\n",
       "      <td>0.377643</td>\n",
       "      <td>1.000009</td>\n",
       "      <td>Alternative minimum tax amount</td>\n",
       "      <td>A09600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>0.560268</td>\n",
       "      <td>0.377639</td>\n",
       "      <td>1.000009</td>\n",
       "      <td>Tuition and fees deduction amount</td>\n",
       "      <td>A03230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>0.555631</td>\n",
       "      <td>0.383632</td>\n",
       "      <td>1.000009</td>\n",
       "      <td>Number of returns with additional child tax cr...</td>\n",
       "      <td>N11070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>0.555695</td>\n",
       "      <td>0.383522</td>\n",
       "      <td>1.000009</td>\n",
       "      <td>Refundable education credit amount</td>\n",
       "      <td>A10960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>0.555585</td>\n",
       "      <td>0.383004</td>\n",
       "      <td>1.000008</td>\n",
       "      <td>Number of returns with total statutory adjustm...</td>\n",
       "      <td>N02900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>0.555985</td>\n",
       "      <td>0.382360</td>\n",
       "      <td>1.000008</td>\n",
       "      <td>Contributions amount</td>\n",
       "      <td>A19700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>0.557930</td>\n",
       "      <td>0.379726</td>\n",
       "      <td>1.000008</td>\n",
       "      <td>Taxes paid amount</td>\n",
       "      <td>A18300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.565663</td>\n",
       "      <td>0.373424</td>\n",
       "      <td>1.000008</td>\n",
       "      <td>Number of volunteer income tax assistance (VIT...</td>\n",
       "      <td>VITA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.553695</td>\n",
       "      <td>0.384690</td>\n",
       "      <td>1.000008</td>\n",
       "      <td>Number of returns with ordinary dividends</td>\n",
       "      <td>N00600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.553945</td>\n",
       "      <td>0.384489</td>\n",
       "      <td>1.000007</td>\n",
       "      <td>Number of returns with qualified dividends</td>\n",
       "      <td>N00650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>0.554111</td>\n",
       "      <td>0.384040</td>\n",
       "      <td>1.000007</td>\n",
       "      <td>Number of returns with itemized deductions</td>\n",
       "      <td>N04470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>0.553953</td>\n",
       "      <td>0.384142</td>\n",
       "      <td>1.000007</td>\n",
       "      <td>Number of returns with taxes paid</td>\n",
       "      <td>N18300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>0.553895</td>\n",
       "      <td>0.384037</td>\n",
       "      <td>1.000007</td>\n",
       "      <td>Number of returns with mortgage interest paid</td>\n",
       "      <td>N19300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>0.555051</td>\n",
       "      <td>0.383148</td>\n",
       "      <td>1.000006</td>\n",
       "      <td>Number of returns with contributions</td>\n",
       "      <td>N19700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>0.554604</td>\n",
       "      <td>0.384111</td>\n",
       "      <td>1.000006</td>\n",
       "      <td>Nonrefundable education credit amount</td>\n",
       "      <td>A07230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.555978</td>\n",
       "      <td>0.382008</td>\n",
       "      <td>1.000006</td>\n",
       "      <td>Net capital gain (less loss) amount</td>\n",
       "      <td>A01000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>0.558005</td>\n",
       "      <td>0.380295</td>\n",
       "      <td>1.000006</td>\n",
       "      <td>Number of returns with unemployment compensation</td>\n",
       "      <td>N02300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>0.554834</td>\n",
       "      <td>0.383638</td>\n",
       "      <td>1.000006</td>\n",
       "      <td>Income tax amount [9]</td>\n",
       "      <td>A06500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>0.553808</td>\n",
       "      <td>0.384114</td>\n",
       "      <td>1.000006</td>\n",
       "      <td>Number of returns with real estate taxes</td>\n",
       "      <td>N18500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>0.554705</td>\n",
       "      <td>0.383853</td>\n",
       "      <td>1.000005</td>\n",
       "      <td>Total tax payments amount</td>\n",
       "      <td>A10600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>0.553822</td>\n",
       "      <td>0.384464</td>\n",
       "      <td>1.000005</td>\n",
       "      <td>Total tax credits amount</td>\n",
       "      <td>A07100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>0.557833</td>\n",
       "      <td>0.380013</td>\n",
       "      <td>1.000004</td>\n",
       "      <td>Residential energy tax credit amount</td>\n",
       "      <td>A07260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>0.550159</td>\n",
       "      <td>0.387809</td>\n",
       "      <td>1.000004</td>\n",
       "      <td>Partnership/S-corp net income (less loss) amount</td>\n",
       "      <td>A26270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.554193</td>\n",
       "      <td>0.384317</td>\n",
       "      <td>1.000004</td>\n",
       "      <td>Taxable pensions and annuities amount</td>\n",
       "      <td>A01700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>0.552915</td>\n",
       "      <td>0.385461</td>\n",
       "      <td>1.000004</td>\n",
       "      <td>Number of returns with tax due at time of filing</td>\n",
       "      <td>N11901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>0.553765</td>\n",
       "      <td>0.384706</td>\n",
       "      <td>1.000004</td>\n",
       "      <td>Taxable income amount</td>\n",
       "      <td>A04800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>0.556275</td>\n",
       "      <td>0.381799</td>\n",
       "      <td>1.000004</td>\n",
       "      <td>Amount of AGI for itemized returns</td>\n",
       "      <td>A00101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.555192</td>\n",
       "      <td>0.383714</td>\n",
       "      <td>1.000003</td>\n",
       "      <td>Number of tax counseling for the elderly (TCE)...</td>\n",
       "      <td>TCE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.553864</td>\n",
       "      <td>0.384665</td>\n",
       "      <td>1.000003</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AGI</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>0.559731</td>\n",
       "      <td>0.377927</td>\n",
       "      <td>1.000003</td>\n",
       "      <td>Number of returns with tuition and fees deduction</td>\n",
       "      <td>N03230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.554231</td>\n",
       "      <td>0.383999</td>\n",
       "      <td>1.000003</td>\n",
       "      <td>Salaries and wages amount</td>\n",
       "      <td>A00200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.553627</td>\n",
       "      <td>0.384645</td>\n",
       "      <td>1.000003</td>\n",
       "      <td>Number of returns with net capital gain (less ...</td>\n",
       "      <td>N01000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>0.551051</td>\n",
       "      <td>0.388033</td>\n",
       "      <td>1.000002</td>\n",
       "      <td>Number of returns with advance premium tax credit</td>\n",
       "      <td>N85775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>0.553870</td>\n",
       "      <td>0.384922</td>\n",
       "      <td>1.000002</td>\n",
       "      <td>Number of returns with child and dependent car...</td>\n",
       "      <td>N07180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>0.551008</td>\n",
       "      <td>0.388349</td>\n",
       "      <td>1.000002</td>\n",
       "      <td>Number of returns with total premium tax credit</td>\n",
       "      <td>N85770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>0.551296</td>\n",
       "      <td>0.387718</td>\n",
       "      <td>1.000002</td>\n",
       "      <td>Number of returns with excess advance premium ...</td>\n",
       "      <td>N05780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>0.550122</td>\n",
       "      <td>0.389674</td>\n",
       "      <td>1.000002</td>\n",
       "      <td>Advance premium tax credit amount</td>\n",
       "      <td>A85775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>0.549258</td>\n",
       "      <td>0.389728</td>\n",
       "      <td>1.000002</td>\n",
       "      <td>Excess advance premium tax credit repayment am...</td>\n",
       "      <td>A05780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>0.552789</td>\n",
       "      <td>0.386256</td>\n",
       "      <td>1.000001</td>\n",
       "      <td>Number of returns with net premium tax credit</td>\n",
       "      <td>N11560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>0.561260</td>\n",
       "      <td>0.377721</td>\n",
       "      <td>1.000001</td>\n",
       "      <td>Number of returns with self-employment retirem...</td>\n",
       "      <td>N03300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>0.556589</td>\n",
       "      <td>0.381481</td>\n",
       "      <td>1.000001</td>\n",
       "      <td>Number of returns with net investment income tax</td>\n",
       "      <td>N85300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>0.554644</td>\n",
       "      <td>0.383512</td>\n",
       "      <td>1.000001</td>\n",
       "      <td>Number of returns with IRA payments</td>\n",
       "      <td>N03150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>0.554552</td>\n",
       "      <td>0.384180</td>\n",
       "      <td>1.000001</td>\n",
       "      <td>Child and dependent care credit amount</td>\n",
       "      <td>A07180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>0.553579</td>\n",
       "      <td>0.385114</td>\n",
       "      <td>1.000001</td>\n",
       "      <td>Net premium tax credit amount</td>\n",
       "      <td>A11560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>0.556501</td>\n",
       "      <td>0.381765</td>\n",
       "      <td>1.000001</td>\n",
       "      <td>Number of returns with additional Medicare tax</td>\n",
       "      <td>N85530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>0.550983</td>\n",
       "      <td>0.388895</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Total premium tax credit amount</td>\n",
       "      <td>A85770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>0.557026</td>\n",
       "      <td>0.380951</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Number of returns with alternative minimum tax</td>\n",
       "      <td>N09600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>0.553899</td>\n",
       "      <td>0.384174</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>IRA payments amount</td>\n",
       "      <td>A03150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>0.554915</td>\n",
       "      <td>0.383765</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Retirement savings contribution credit amount</td>\n",
       "      <td>A07240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>0.550182</td>\n",
       "      <td>0.387861</td>\n",
       "      <td>0.999999</td>\n",
       "      <td>Number of returns with residential energy tax ...</td>\n",
       "      <td>N07260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>0.554644</td>\n",
       "      <td>0.384145</td>\n",
       "      <td>0.999999</td>\n",
       "      <td>Number of returns with retirement savings cont...</td>\n",
       "      <td>N07240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>0.554356</td>\n",
       "      <td>0.384691</td>\n",
       "      <td>0.999999</td>\n",
       "      <td>Educator expenses amount</td>\n",
       "      <td>A03220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>0.557519</td>\n",
       "      <td>0.380934</td>\n",
       "      <td>0.999999</td>\n",
       "      <td>Additional Medicare tax amount</td>\n",
       "      <td>A85530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>0.555691</td>\n",
       "      <td>0.382330</td>\n",
       "      <td>0.999999</td>\n",
       "      <td>Total itemized deductions amount</td>\n",
       "      <td>A04470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>0.553438</td>\n",
       "      <td>0.385290</td>\n",
       "      <td>0.999998</td>\n",
       "      <td>Health care individual responsibility payment ...</td>\n",
       "      <td>A09750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.554116</td>\n",
       "      <td>0.383742</td>\n",
       "      <td>0.999998</td>\n",
       "      <td>Number of returns with taxable interest</td>\n",
       "      <td>N00300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>0.551748</td>\n",
       "      <td>0.383513</td>\n",
       "      <td>0.999997</td>\n",
       "      <td>Returns with domestic production activities de...</td>\n",
       "      <td>N03240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.550230</td>\n",
       "      <td>0.388271</td>\n",
       "      <td>0.999997</td>\n",
       "      <td>Number of returns with taxable individual reti...</td>\n",
       "      <td>N01400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0.554480</td>\n",
       "      <td>0.384576</td>\n",
       "      <td>0.999997</td>\n",
       "      <td>Number of returns with educator expenses</td>\n",
       "      <td>N03220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>0.558168</td>\n",
       "      <td>0.380137</td>\n",
       "      <td>0.999996</td>\n",
       "      <td>Net investment income tax amount</td>\n",
       "      <td>A85300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>0.552694</td>\n",
       "      <td>0.384929</td>\n",
       "      <td>0.999996</td>\n",
       "      <td>Number of returns with self-employment health ...</td>\n",
       "      <td>N03270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>0.558008</td>\n",
       "      <td>0.378402</td>\n",
       "      <td>0.999996</td>\n",
       "      <td>Number of returns with State and local income ...</td>\n",
       "      <td>N18425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>0.554055</td>\n",
       "      <td>0.384712</td>\n",
       "      <td>0.999995</td>\n",
       "      <td>Number of returns with health care individual ...</td>\n",
       "      <td>N09750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>0.558079</td>\n",
       "      <td>0.379781</td>\n",
       "      <td>0.999994</td>\n",
       "      <td>Real estate taxes amount</td>\n",
       "      <td>A18500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.555805</td>\n",
       "      <td>0.382975</td>\n",
       "      <td>0.999994</td>\n",
       "      <td>Number of returns with business or professiona...</td>\n",
       "      <td>N00900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>0.551861</td>\n",
       "      <td>0.386257</td>\n",
       "      <td>0.999993</td>\n",
       "      <td>Number of returns with partnership/S-corp net ...</td>\n",
       "      <td>N26270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>0.555803</td>\n",
       "      <td>0.382912</td>\n",
       "      <td>0.999992</td>\n",
       "      <td>Number of returns with self-employment tax</td>\n",
       "      <td>N09400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.554367</td>\n",
       "      <td>0.384420</td>\n",
       "      <td>0.999992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>num_dependents</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>0.561679</td>\n",
       "      <td>0.375594</td>\n",
       "      <td>0.999992</td>\n",
       "      <td>State and local income taxes amount</td>\n",
       "      <td>A18425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>0.552039</td>\n",
       "      <td>0.386629</td>\n",
       "      <td>0.999992</td>\n",
       "      <td>Number of returns with taxable Social Security...</td>\n",
       "      <td>N02500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.552935</td>\n",
       "      <td>0.385787</td>\n",
       "      <td>0.999991</td>\n",
       "      <td>Number of returns with taxable pensions and an...</td>\n",
       "      <td>N01700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>0.552279</td>\n",
       "      <td>0.386424</td>\n",
       "      <td>0.999990</td>\n",
       "      <td>Number of returns with child tax credit</td>\n",
       "      <td>N07220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.555932</td>\n",
       "      <td>0.382404</td>\n",
       "      <td>0.999987</td>\n",
       "      <td>Taxable interest amount</td>\n",
       "      <td>A00300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.553864</td>\n",
       "      <td>0.384665</td>\n",
       "      <td>0.999987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>tot_inc_amt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.557839</td>\n",
       "      <td>0.378627</td>\n",
       "      <td>0.999987</td>\n",
       "      <td>Number of returns with state and local income ...</td>\n",
       "      <td>N00700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.559563</td>\n",
       "      <td>0.379433</td>\n",
       "      <td>0.999986</td>\n",
       "      <td>Qualified dividends amount [5]</td>\n",
       "      <td>A00650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>0.546641</td>\n",
       "      <td>0.390312</td>\n",
       "      <td>0.999986</td>\n",
       "      <td>Domestic production activities deduction amount</td>\n",
       "      <td>A03240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>0.555221</td>\n",
       "      <td>0.382987</td>\n",
       "      <td>0.999984</td>\n",
       "      <td>Total statutory adjustments amount</td>\n",
       "      <td>A02900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.562289</td>\n",
       "      <td>0.375841</td>\n",
       "      <td>0.999980</td>\n",
       "      <td>State and local income tax refunds amount</td>\n",
       "      <td>A00700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>0.555600</td>\n",
       "      <td>0.383292</td>\n",
       "      <td>0.999978</td>\n",
       "      <td>Overpayments refunded amount [12]</td>\n",
       "      <td>A11902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>0.549556</td>\n",
       "      <td>0.388923</td>\n",
       "      <td>0.999978</td>\n",
       "      <td>Child tax credit amount</td>\n",
       "      <td>A07220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>0.500946</td>\n",
       "      <td>0.433870</td>\n",
       "      <td>0.999973</td>\n",
       "      <td>Number of farm returns</td>\n",
       "      <td>SCHF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>0.554999</td>\n",
       "      <td>0.383393</td>\n",
       "      <td>0.999972</td>\n",
       "      <td>Total tax liability amount [10]</td>\n",
       "      <td>A10300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>0.556743</td>\n",
       "      <td>0.381694</td>\n",
       "      <td>0.999971</td>\n",
       "      <td>Self-employment tax amount</td>\n",
       "      <td>A09400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0.551303</td>\n",
       "      <td>0.387195</td>\n",
       "      <td>0.999967</td>\n",
       "      <td>Taxable Social Security benefits amount</td>\n",
       "      <td>A02500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>0.552667</td>\n",
       "      <td>0.385139</td>\n",
       "      <td>0.999966</td>\n",
       "      <td>Self-employment health insurance deduction amount</td>\n",
       "      <td>A03270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.553870</td>\n",
       "      <td>0.384830</td>\n",
       "      <td>0.999961</td>\n",
       "      <td>Number of exemptions</td>\n",
       "      <td>N2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>0.552910</td>\n",
       "      <td>0.385465</td>\n",
       "      <td>0.999953</td>\n",
       "      <td>Tax due at time of filing amount [11]</td>\n",
       "      <td>A11901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.554995</td>\n",
       "      <td>0.384150</td>\n",
       "      <td>0.999942</td>\n",
       "      <td>Number of returns with paid preparer's signature</td>\n",
       "      <td>PREP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.549716</td>\n",
       "      <td>0.388609</td>\n",
       "      <td>0.999937</td>\n",
       "      <td>Number of joint returns</td>\n",
       "      <td>MARS2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     % Clinton   % Trump     Coefs  \\\n",
       "1     0.557095  0.381532  1.000068   \n",
       "33    0.559517  0.378480  1.000045   \n",
       "102   0.556979  0.382764  1.000032   \n",
       "104   0.556924  0.382844  1.000031   \n",
       "99    0.555545  0.383121  1.000030   \n",
       "24    0.556458  0.382366  1.000029   \n",
       "13    0.555386  0.383316  1.000026   \n",
       "0     0.555327  0.383339  1.000025   \n",
       "71    0.554267  0.384360  1.000024   \n",
       "69    0.554267  0.384360  1.000024   \n",
       "11    0.555327  0.383339  1.000024   \n",
       "60    0.548515  0.392280  1.000024   \n",
       "43    0.559640  0.378784  1.000023   \n",
       "3     0.557897  0.382283  1.000022   \n",
       "121   0.555762  0.382986  1.000021   \n",
       "49    0.555960  0.382262  1.000021   \n",
       "18    0.558946  0.380034  1.000019   \n",
       "66    0.554494  0.383368  1.000017   \n",
       "72    0.554967  0.383371  1.000017   \n",
       "111   0.553580  0.384920  1.000017   \n",
       "48    0.555819  0.382424  1.000017   \n",
       "123   0.554329  0.384468  1.000017   \n",
       "113   0.554849  0.383774  1.000014   \n",
       "28    0.552220  0.386811  1.000014   \n",
       "101   0.556546  0.382829  1.000012   \n",
       "103   0.557409  0.382064  1.000012   \n",
       "106   0.555659  0.383464  1.000012   \n",
       "7     0.557219  0.380958  1.000011   \n",
       "80    0.555831  0.382536  1.000011   \n",
       "107   0.556088  0.382963  1.000010   \n",
       "59    0.549205  0.391103  1.000010   \n",
       "77    0.554129  0.384417  1.000010   \n",
       "79    0.556511  0.381983  1.000010   \n",
       "83    0.556157  0.382525  1.000009   \n",
       "74    0.559997  0.377643  1.000009   \n",
       "51    0.560268  0.377639  1.000009   \n",
       "105   0.555631  0.383632  1.000009   \n",
       "108   0.555695  0.383522  1.000009   \n",
       "38    0.555585  0.383004  1.000008   \n",
       "68    0.555985  0.382360  1.000008   \n",
       "64    0.557930  0.379726  1.000008   \n",
       "8     0.565663  0.373424  1.000008   \n",
       "17    0.553695  0.384690  1.000008   \n",
       "19    0.553945  0.384489  1.000007   \n",
       "54    0.554111  0.384040  1.000007   \n",
       "63    0.553953  0.384142  1.000007   \n",
       "65    0.553895  0.384037  1.000007   \n",
       "67    0.555051  0.383148  1.000006   \n",
       "84    0.554604  0.384111  1.000006   \n",
       "26    0.555978  0.382008  1.000006   \n",
       "32    0.558005  0.380295  1.000006   \n",
       "112   0.554834  0.383638  1.000006   \n",
       "61    0.553808  0.384114  1.000006   \n",
       "100   0.554705  0.383853  1.000005   \n",
       "78    0.553822  0.384464  1.000005   \n",
       "90    0.557833  0.380013  1.000004   \n",
       "37    0.550159  0.387809  1.000004   \n",
       "30    0.554193  0.384317  1.000004   \n",
       "119   0.552915  0.385461  1.000004   \n",
       "70    0.553765  0.384706  1.000004   \n",
       "56    0.556275  0.381799  1.000004   \n",
       "9     0.555192  0.383714  1.000003   \n",
       "10    0.553864  0.384665  1.000003   \n",
       "50    0.559731  0.377927  1.000003   \n",
       "14    0.554231  0.383999  1.000003   \n",
       "25    0.553627  0.384645  1.000003   \n",
       "95    0.551051  0.388033  1.000002   \n",
       "81    0.553870  0.384922  1.000002   \n",
       "93    0.551008  0.388349  1.000002   \n",
       "75    0.551296  0.387718  1.000002   \n",
       "96    0.550122  0.389674  1.000002   \n",
       "76    0.549258  0.389728  1.000002   \n",
       "109   0.552789  0.386256  1.000001   \n",
       "42    0.561260  0.377721  1.000001   \n",
       "117   0.556589  0.381481  1.000001   \n",
       "46    0.554644  0.383512  1.000001   \n",
       "82    0.554552  0.384180  1.000001   \n",
       "110   0.553579  0.385114  1.000001   \n",
       "115   0.556501  0.381765  1.000001   \n",
       "94    0.550983  0.388895  1.000000   \n",
       "73    0.557026  0.380951  1.000000   \n",
       "47    0.553899  0.384174  1.000000   \n",
       "86    0.554915  0.383765  1.000000   \n",
       "89    0.550182  0.387861  0.999999   \n",
       "85    0.554644  0.384145  0.999999   \n",
       "41    0.554356  0.384691  0.999999   \n",
       "116   0.557519  0.380934  0.999999   \n",
       "55    0.555691  0.382330  0.999999   \n",
       "98    0.553438  0.385290  0.999998   \n",
       "15    0.554116  0.383742  0.999998   \n",
       "52    0.551748  0.383513  0.999997   \n",
       "27    0.550230  0.388271  0.999997   \n",
       "40    0.554480  0.384576  0.999997   \n",
       "118   0.558168  0.380137  0.999996   \n",
       "44    0.552694  0.384929  0.999996   \n",
       "57    0.558008  0.378402  0.999996   \n",
       "97    0.554055  0.384712  0.999995   \n",
       "62    0.558079  0.379781  0.999994   \n",
       "23    0.555805  0.382975  0.999994   \n",
       "36    0.551861  0.386257  0.999993   \n",
       "91    0.555803  0.382912  0.999992   \n",
       "6     0.554367  0.384420  0.999992   \n",
       "58    0.561679  0.375594  0.999992   \n",
       "34    0.552039  0.386629  0.999992   \n",
       "29    0.552935  0.385787  0.999991   \n",
       "87    0.552279  0.386424  0.999990   \n",
       "16    0.555932  0.382404  0.999987   \n",
       "12    0.553864  0.384665  0.999987   \n",
       "21    0.557839  0.378627  0.999987   \n",
       "20    0.559563  0.379433  0.999986   \n",
       "53    0.546641  0.390312  0.999986   \n",
       "39    0.555221  0.382987  0.999984   \n",
       "22    0.562289  0.375841  0.999980   \n",
       "122   0.555600  0.383292  0.999978   \n",
       "88    0.549556  0.388923  0.999978   \n",
       "31    0.500946  0.433870  0.999973   \n",
       "114   0.554999  0.383393  0.999972   \n",
       "92    0.556743  0.381694  0.999971   \n",
       "35    0.551303  0.387195  0.999967   \n",
       "45    0.552667  0.385139  0.999966   \n",
       "5     0.553870  0.384830  0.999961   \n",
       "120   0.552910  0.385465  0.999953   \n",
       "4     0.554995  0.384150  0.999942   \n",
       "2     0.549716  0.388609  0.999937   \n",
       "\n",
       "                                           Description         Feature  \n",
       "1                                                  NaN           mars1  \n",
       "33                Unemployment compensation amount [6]          A02300  \n",
       "102                  Earned income credit amount [7]            A59660  \n",
       "104  Excess earned income credit (refundable) amoun...          A59720  \n",
       "99           Number of returns with total tax payments          N10600  \n",
       "24   Business or professional net income (less loss...          A00900  \n",
       "13           Number of returns with salaries and wages          N00200  \n",
       "0                                                  NaN     num_returns  \n",
       "71    Number of returns with income tax before credits          N05800  \n",
       "69               Number of returns with taxable income          N04800  \n",
       "11                                                 NaN     num_tot_inc  \n",
       "60            State and local general sales tax amount          A18450  \n",
       "43             Self-employment retirement plans amount          A03300  \n",
       "3                  Number of head of household returns           MARS4  \n",
       "121       Number of returns with overpayments refunded          N11902  \n",
       "49              Student loan interest deduction amount          A03210  \n",
       "18                           Ordinary dividends amount          A00600  \n",
       "66                       Mortgage interest paid amount          A19300  \n",
       "72                    Income tax before credits amount          A05800  \n",
       "111                  Number of returns with income tax          N06500  \n",
       "48   Number of returns with student loan interest d...          N03210  \n",
       "123                                                NaN          people  \n",
       "113               Number of returns with tax liability          N10300  \n",
       "28   Taxable individual retirement arrangements dis...          A01400  \n",
       "101        Number of returns with earned income credit          N59660  \n",
       "103  Number of returns with excess earned income cr...          N59720  \n",
       "106                 Additional child tax credit amount          A11070  \n",
       "7       Total number of volunteer prepared returns [3]      TOTAL_VITA  \n",
       "80                           Foreign tax credit amount          A07300  \n",
       "107  Number of returns with refundable education cr...          N10960  \n",
       "59   Number of returns with State and local general...          N18450  \n",
       "77            Number of returns with total tax credits          N07100  \n",
       "79           Number of returns with foreign tax credit          N07300  \n",
       "83   Number of returns with nonrefundable education...          N07230  \n",
       "74                      Alternative minimum tax amount          A09600  \n",
       "51                   Tuition and fees deduction amount          A03230  \n",
       "105  Number of returns with additional child tax cr...          N11070  \n",
       "108                 Refundable education credit amount          A10960  \n",
       "38   Number of returns with total statutory adjustm...          N02900  \n",
       "68                                Contributions amount          A19700  \n",
       "64                                   Taxes paid amount          A18300  \n",
       "8    Number of volunteer income tax assistance (VIT...            VITA  \n",
       "17          Number of returns with ordinary dividends           N00600  \n",
       "19          Number of returns with qualified dividends          N00650  \n",
       "54          Number of returns with itemized deductions          N04470  \n",
       "63                   Number of returns with taxes paid          N18300  \n",
       "65       Number of returns with mortgage interest paid          N19300  \n",
       "67                Number of returns with contributions          N19700  \n",
       "84               Nonrefundable education credit amount          A07230  \n",
       "26                 Net capital gain (less loss) amount          A01000  \n",
       "32    Number of returns with unemployment compensation          N02300  \n",
       "112                            Income tax amount [9]            A06500  \n",
       "61            Number of returns with real estate taxes          N18500  \n",
       "100                          Total tax payments amount          A10600  \n",
       "78                            Total tax credits amount          A07100  \n",
       "90                Residential energy tax credit amount          A07260  \n",
       "37    Partnership/S-corp net income (less loss) amount          A26270  \n",
       "30               Taxable pensions and annuities amount          A01700  \n",
       "119   Number of returns with tax due at time of filing          N11901  \n",
       "70                               Taxable income amount          A04800  \n",
       "56                  Amount of AGI for itemized returns          A00101  \n",
       "9    Number of tax counseling for the elderly (TCE)...             TCE  \n",
       "10                                                 NaN             AGI  \n",
       "50   Number of returns with tuition and fees deduction          N03230  \n",
       "14                           Salaries and wages amount          A00200  \n",
       "25   Number of returns with net capital gain (less ...          N01000  \n",
       "95   Number of returns with advance premium tax credit          N85775  \n",
       "81   Number of returns with child and dependent car...          N07180  \n",
       "93     Number of returns with total premium tax credit          N85770  \n",
       "75   Number of returns with excess advance premium ...          N05780  \n",
       "96                   Advance premium tax credit amount          A85775  \n",
       "76   Excess advance premium tax credit repayment am...          A05780  \n",
       "109      Number of returns with net premium tax credit          N11560  \n",
       "42   Number of returns with self-employment retirem...          N03300  \n",
       "117   Number of returns with net investment income tax          N85300  \n",
       "46                 Number of returns with IRA payments          N03150  \n",
       "82              Child and dependent care credit amount          A07180  \n",
       "110                      Net premium tax credit amount          A11560  \n",
       "115     Number of returns with additional Medicare tax          N85530  \n",
       "94                     Total premium tax credit amount          A85770  \n",
       "73     Number of returns with alternative minimum tax           N09600  \n",
       "47                                 IRA payments amount          A03150  \n",
       "86       Retirement savings contribution credit amount          A07240  \n",
       "89   Number of returns with residential energy tax ...          N07260  \n",
       "85   Number of returns with retirement savings cont...          N07240  \n",
       "41                            Educator expenses amount          A03220  \n",
       "116                     Additional Medicare tax amount          A85530  \n",
       "55                    Total itemized deductions amount          A04470  \n",
       "98   Health care individual responsibility payment ...          A09750  \n",
       "15             Number of returns with taxable interest          N00300  \n",
       "52   Returns with domestic production activities de...          N03240  \n",
       "27   Number of returns with taxable individual reti...          N01400  \n",
       "40            Number of returns with educator expenses          N03220  \n",
       "118                   Net investment income tax amount          A85300  \n",
       "44   Number of returns with self-employment health ...          N03270  \n",
       "57   Number of returns with State and local income ...          N18425  \n",
       "97   Number of returns with health care individual ...          N09750  \n",
       "62                            Real estate taxes amount          A18500  \n",
       "23   Number of returns with business or professiona...          N00900  \n",
       "36   Number of returns with partnership/S-corp net ...          N26270  \n",
       "91          Number of returns with self-employment tax          N09400  \n",
       "6                                                  NaN  num_dependents  \n",
       "58                 State and local income taxes amount          A18425  \n",
       "34   Number of returns with taxable Social Security...          N02500  \n",
       "29   Number of returns with taxable pensions and an...          N01700  \n",
       "87             Number of returns with child tax credit          N07220  \n",
       "16                             Taxable interest amount          A00300  \n",
       "12                                                 NaN     tot_inc_amt  \n",
       "21   Number of returns with state and local income ...          N00700  \n",
       "20                      Qualified dividends amount [5]          A00650  \n",
       "53     Domestic production activities deduction amount          A03240  \n",
       "39                  Total statutory adjustments amount          A02900  \n",
       "22           State and local income tax refunds amount          A00700  \n",
       "122                Overpayments refunded amount [12]            A11902  \n",
       "88                             Child tax credit amount          A07220  \n",
       "31                              Number of farm returns            SCHF  \n",
       "114                  Total tax liability amount [10]            A10300  \n",
       "92                          Self-employment tax amount          A09400  \n",
       "35             Taxable Social Security benefits amount          A02500  \n",
       "45   Self-employment health insurance deduction amount          A03270  \n",
       "5                                 Number of exemptions              N2  \n",
       "120            Tax due at time of filing amount [11]            A11901  \n",
       "4     Number of returns with paid preparer's signature            PREP  \n",
       "2                              Number of joint returns           MARS2  "
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features = pd.DataFrame({'Feature':X.columns,\n",
    "                         'Coefs':np.exp(coef),                        \n",
    "                        'Description': pd.Series(X.columns).map(descr_dict),\n",
    "                        '% Clinton':trait_percentile(X,90)[0],\n",
    "                         '% Trump':trait_percentile(X,90)[1]})\n",
    "features.sort_values(by='Coefs',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3113, 159)"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pres_county.shape"
   ]
  }
 ],
 "metadata": {
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    "name": "ipython",
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   "name": "python",
   "nbconvert_exporter": "python",
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