traffic_model_comp_20180121.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import statsmodels.api as sm # import statsmodels\n",
    "from sklearn import tree\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.cross_validation import cross_val_score\n",
    "from sklearn.cross_validation import KFold\n",
    "crossvalidation = KFold(n=X.shape[0], n_folds=5,\n",
    " shuffle=True, random_state=1)\n",
    "import graphviz \n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dui_tax_short = pd.DataFrame.from_csv('dui_tax_short.csv', index_col=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>ACC_MIL</th>\n",
       "      <th>ACH_MIL</th>\n",
       "      <th>YEAR</th>\n",
       "      <th>STATE_SHORT</th>\n",
       "      <th>POP_MIL</th>\n",
       "      <th>SUSPEND</th>\n",
       "      <th>INTERLOCK_1ST</th>\n",
       "      <th>INTERLOCK_REPEAT</th>\n",
       "      <th>GALLONS_ALCOHOL_PER_CAP_21</th>\n",
       "      <th>BEER_TAX</th>\n",
       "      <th>PERCENT_POVERTY</th>\n",
       "      <th>MEDIAN_INCOME</th>\n",
       "      <th>PERCENT_UNINSURE</th>\n",
       "      <th>LESS_HS_P</th>\n",
       "      <th>HS_P</th>\n",
       "      <th>SOME_C_P</th>\n",
       "      <th>BACHELORS_P</th>\n",
       "      <th>GRAD_PROF_P</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>806.136433</td>\n",
       "      <td>48.569874</td>\n",
       "      <td>2011</td>\n",
       "      <td>AL</td>\n",
       "      <td>4.858979</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>22331</td>\n",
       "      <td>1.05</td>\n",
       "      <td>19.1</td>\n",
       "      <td>41427</td>\n",
       "      <td>16.6</td>\n",
       "      <td>0.180897</td>\n",
       "      <td>0.314334</td>\n",
       "      <td>0.285068</td>\n",
       "      <td>0.139643</td>\n",
       "      <td>0.080058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>806.136433</td>\n",
       "      <td>46.100220</td>\n",
       "      <td>2012</td>\n",
       "      <td>AL</td>\n",
       "      <td>4.858979</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>22656</td>\n",
       "      <td>1.05</td>\n",
       "      <td>19.0</td>\n",
       "      <td>41610</td>\n",
       "      <td>15.8</td>\n",
       "      <td>0.174023</td>\n",
       "      <td>0.313100</td>\n",
       "      <td>0.290229</td>\n",
       "      <td>0.141521</td>\n",
       "      <td>0.081127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>806.136433</td>\n",
       "      <td>44.042174</td>\n",
       "      <td>2013</td>\n",
       "      <td>AL</td>\n",
       "      <td>4.858979</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>22491</td>\n",
       "      <td>1.05</td>\n",
       "      <td>18.9</td>\n",
       "      <td>42882</td>\n",
       "      <td>15.9</td>\n",
       "      <td>0.168852</td>\n",
       "      <td>0.310562</td>\n",
       "      <td>0.294274</td>\n",
       "      <td>0.143547</td>\n",
       "      <td>0.082766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>806.136433</td>\n",
       "      <td>47.952461</td>\n",
       "      <td>2014</td>\n",
       "      <td>AL</td>\n",
       "      <td>4.858979</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>22481</td>\n",
       "      <td>1.05</td>\n",
       "      <td>19.2</td>\n",
       "      <td>42917</td>\n",
       "      <td>14.2</td>\n",
       "      <td>0.162953</td>\n",
       "      <td>0.310687</td>\n",
       "      <td>0.295833</td>\n",
       "      <td>0.144587</td>\n",
       "      <td>0.085940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>398.140926</td>\n",
       "      <td>24.375975</td>\n",
       "      <td>2011</td>\n",
       "      <td>AK</td>\n",
       "      <td>0.738432</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>32713</td>\n",
       "      <td>1.07</td>\n",
       "      <td>10.8</td>\n",
       "      <td>65699</td>\n",
       "      <td>21.7</td>\n",
       "      <td>0.086375</td>\n",
       "      <td>0.272442</td>\n",
       "      <td>0.369075</td>\n",
       "      <td>0.176662</td>\n",
       "      <td>0.095446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>398.140926</td>\n",
       "      <td>20.313313</td>\n",
       "      <td>2012</td>\n",
       "      <td>AK</td>\n",
       "      <td>0.738432</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>32236</td>\n",
       "      <td>1.07</td>\n",
       "      <td>10.8</td>\n",
       "      <td>66503</td>\n",
       "      <td>22.3</td>\n",
       "      <td>0.084130</td>\n",
       "      <td>0.270973</td>\n",
       "      <td>0.370134</td>\n",
       "      <td>0.177505</td>\n",
       "      <td>0.097258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>398.140926</td>\n",
       "      <td>20.313313</td>\n",
       "      <td>2013</td>\n",
       "      <td>AK</td>\n",
       "      <td>0.738432</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>31277</td>\n",
       "      <td>1.07</td>\n",
       "      <td>10.1</td>\n",
       "      <td>70058</td>\n",
       "      <td>20.8</td>\n",
       "      <td>0.083634</td>\n",
       "      <td>0.273077</td>\n",
       "      <td>0.368287</td>\n",
       "      <td>0.177079</td>\n",
       "      <td>0.097924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>398.140926</td>\n",
       "      <td>35.209742</td>\n",
       "      <td>2014</td>\n",
       "      <td>AK</td>\n",
       "      <td>0.738432</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>31696</td>\n",
       "      <td>1.07</td>\n",
       "      <td>11.4</td>\n",
       "      <td>70898</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0.081900</td>\n",
       "      <td>0.275051</td>\n",
       "      <td>0.366203</td>\n",
       "      <td>0.178704</td>\n",
       "      <td>0.098143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>555.501449</td>\n",
       "      <td>28.265695</td>\n",
       "      <td>2011</td>\n",
       "      <td>AZ</td>\n",
       "      <td>6.828065</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>27228</td>\n",
       "      <td>0.16</td>\n",
       "      <td>19.0</td>\n",
       "      <td>46710</td>\n",
       "      <td>19.6</td>\n",
       "      <td>0.148176</td>\n",
       "      <td>0.247291</td>\n",
       "      <td>0.340564</td>\n",
       "      <td>0.168360</td>\n",
       "      <td>0.095609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>555.501449</td>\n",
       "      <td>28.705058</td>\n",
       "      <td>2012</td>\n",
       "      <td>AZ</td>\n",
       "      <td>6.828065</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>27627</td>\n",
       "      <td>0.16</td>\n",
       "      <td>18.7</td>\n",
       "      <td>47796</td>\n",
       "      <td>20.4</td>\n",
       "      <td>0.145577</td>\n",
       "      <td>0.243979</td>\n",
       "      <td>0.344151</td>\n",
       "      <td>0.169160</td>\n",
       "      <td>0.097133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>555.501449</td>\n",
       "      <td>29.583784</td>\n",
       "      <td>2013</td>\n",
       "      <td>AZ</td>\n",
       "      <td>6.828065</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>26677</td>\n",
       "      <td>0.16</td>\n",
       "      <td>18.6</td>\n",
       "      <td>48504</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.143056</td>\n",
       "      <td>0.245064</td>\n",
       "      <td>0.343135</td>\n",
       "      <td>0.170197</td>\n",
       "      <td>0.098547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>555.501449</td>\n",
       "      <td>25.190153</td>\n",
       "      <td>2014</td>\n",
       "      <td>AZ</td>\n",
       "      <td>6.828065</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>26819</td>\n",
       "      <td>0.16</td>\n",
       "      <td>18.2</td>\n",
       "      <td>50036</td>\n",
       "      <td>16.1</td>\n",
       "      <td>0.141056</td>\n",
       "      <td>0.245072</td>\n",
       "      <td>0.342895</td>\n",
       "      <td>0.171268</td>\n",
       "      <td>0.099709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>799.475120</td>\n",
       "      <td>54.059426</td>\n",
       "      <td>2011</td>\n",
       "      <td>AR</td>\n",
       "      <td>2.978204</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>19519</td>\n",
       "      <td>0.24</td>\n",
       "      <td>19.3</td>\n",
       "      <td>38889</td>\n",
       "      <td>20.1</td>\n",
       "      <td>0.173465</td>\n",
       "      <td>0.352003</td>\n",
       "      <td>0.278698</td>\n",
       "      <td>0.130271</td>\n",
       "      <td>0.065563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>799.475120</td>\n",
       "      <td>51.373244</td>\n",
       "      <td>2012</td>\n",
       "      <td>AR</td>\n",
       "      <td>2.978204</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>20435</td>\n",
       "      <td>0.24</td>\n",
       "      <td>19.6</td>\n",
       "      <td>40151</td>\n",
       "      <td>19.4</td>\n",
       "      <td>0.166937</td>\n",
       "      <td>0.351238</td>\n",
       "      <td>0.283841</td>\n",
       "      <td>0.131480</td>\n",
       "      <td>0.066503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>799.475120</td>\n",
       "      <td>40.292740</td>\n",
       "      <td>2013</td>\n",
       "      <td>AR</td>\n",
       "      <td>2.978204</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>20398</td>\n",
       "      <td>0.24</td>\n",
       "      <td>19.4</td>\n",
       "      <td>40605</td>\n",
       "      <td>18.8</td>\n",
       "      <td>0.162692</td>\n",
       "      <td>0.350798</td>\n",
       "      <td>0.285475</td>\n",
       "      <td>0.132791</td>\n",
       "      <td>0.068245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>799.475120</td>\n",
       "      <td>38.613876</td>\n",
       "      <td>2014</td>\n",
       "      <td>AR</td>\n",
       "      <td>2.978204</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>20203</td>\n",
       "      <td>0.24</td>\n",
       "      <td>18.7</td>\n",
       "      <td>41335</td>\n",
       "      <td>13.8</td>\n",
       "      <td>0.157028</td>\n",
       "      <td>0.349982</td>\n",
       "      <td>0.286530</td>\n",
       "      <td>0.135028</td>\n",
       "      <td>0.071433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>357.493040</td>\n",
       "      <td>19.057439</td>\n",
       "      <td>2011</td>\n",
       "      <td>CA</td>\n",
       "      <td>39.144818</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>25718</td>\n",
       "      <td>0.20</td>\n",
       "      <td>16.6</td>\n",
       "      <td>57275</td>\n",
       "      <td>20.2</td>\n",
       "      <td>0.191818</td>\n",
       "      <td>0.211169</td>\n",
       "      <td>0.294672</td>\n",
       "      <td>0.192582</td>\n",
       "      <td>0.109759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>357.493040</td>\n",
       "      <td>20.283655</td>\n",
       "      <td>2012</td>\n",
       "      <td>CA</td>\n",
       "      <td>39.144818</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>26742</td>\n",
       "      <td>0.20</td>\n",
       "      <td>17.0</td>\n",
       "      <td>58322</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.189801</td>\n",
       "      <td>0.206846</td>\n",
       "      <td>0.298819</td>\n",
       "      <td>0.193536</td>\n",
       "      <td>0.110998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>357.493040</td>\n",
       "      <td>20.462479</td>\n",
       "      <td>2013</td>\n",
       "      <td>CA</td>\n",
       "      <td>39.144818</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>26373</td>\n",
       "      <td>0.20</td>\n",
       "      <td>16.8</td>\n",
       "      <td>60185</td>\n",
       "      <td>19.4</td>\n",
       "      <td>0.187580</td>\n",
       "      <td>0.207157</td>\n",
       "      <td>0.298534</td>\n",
       "      <td>0.194375</td>\n",
       "      <td>0.112353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>357.493040</td>\n",
       "      <td>20.743486</td>\n",
       "      <td>2014</td>\n",
       "      <td>CA</td>\n",
       "      <td>39.144818</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>26200</td>\n",
       "      <td>0.20</td>\n",
       "      <td>16.4</td>\n",
       "      <td>61927</td>\n",
       "      <td>14.1</td>\n",
       "      <td>0.185113</td>\n",
       "      <td>0.207242</td>\n",
       "      <td>0.297625</td>\n",
       "      <td>0.195872</td>\n",
       "      <td>0.114148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>408.681345</td>\n",
       "      <td>26.023655</td>\n",
       "      <td>2011</td>\n",
       "      <td>CO</td>\n",
       "      <td>5.456574</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>30797</td>\n",
       "      <td>0.08</td>\n",
       "      <td>13.4</td>\n",
       "      <td>55530</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.103172</td>\n",
       "      <td>0.229340</td>\n",
       "      <td>0.304557</td>\n",
       "      <td>0.232747</td>\n",
       "      <td>0.130185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>408.681345</td>\n",
       "      <td>25.290594</td>\n",
       "      <td>2012</td>\n",
       "      <td>CO</td>\n",
       "      <td>5.456574</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>31076</td>\n",
       "      <td>0.08</td>\n",
       "      <td>13.6</td>\n",
       "      <td>56880</td>\n",
       "      <td>16.7</td>\n",
       "      <td>0.100773</td>\n",
       "      <td>0.223595</td>\n",
       "      <td>0.308869</td>\n",
       "      <td>0.234469</td>\n",
       "      <td>0.132294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>408.681345</td>\n",
       "      <td>26.756716</td>\n",
       "      <td>2013</td>\n",
       "      <td>CO</td>\n",
       "      <td>5.456574</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>31606</td>\n",
       "      <td>0.08</td>\n",
       "      <td>12.9</td>\n",
       "      <td>58942</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.098276</td>\n",
       "      <td>0.221388</td>\n",
       "      <td>0.310048</td>\n",
       "      <td>0.235905</td>\n",
       "      <td>0.134382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>408.681345</td>\n",
       "      <td>28.039572</td>\n",
       "      <td>2014</td>\n",
       "      <td>CO</td>\n",
       "      <td>5.456574</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>31067</td>\n",
       "      <td>0.08</td>\n",
       "      <td>12.1</td>\n",
       "      <td>61324</td>\n",
       "      <td>11.7</td>\n",
       "      <td>0.096208</td>\n",
       "      <td>0.219880</td>\n",
       "      <td>0.309300</td>\n",
       "      <td>0.237353</td>\n",
       "      <td>0.137259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>336.407227</td>\n",
       "      <td>20.329245</td>\n",
       "      <td>2011</td>\n",
       "      <td>CT</td>\n",
       "      <td>3.590886</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>26710</td>\n",
       "      <td>0.24</td>\n",
       "      <td>10.8</td>\n",
       "      <td>65822</td>\n",
       "      <td>10.1</td>\n",
       "      <td>0.114309</td>\n",
       "      <td>0.281284</td>\n",
       "      <td>0.247303</td>\n",
       "      <td>0.201377</td>\n",
       "      <td>0.155727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>336.407227</td>\n",
       "      <td>22.557107</td>\n",
       "      <td>2012</td>\n",
       "      <td>CT</td>\n",
       "      <td>3.590886</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>27104</td>\n",
       "      <td>0.24</td>\n",
       "      <td>10.6</td>\n",
       "      <td>67275</td>\n",
       "      <td>10.5</td>\n",
       "      <td>0.110414</td>\n",
       "      <td>0.278551</td>\n",
       "      <td>0.249469</td>\n",
       "      <td>0.203261</td>\n",
       "      <td>0.158304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>336.407227</td>\n",
       "      <td>25.620418</td>\n",
       "      <td>2013</td>\n",
       "      <td>CT</td>\n",
       "      <td>3.590886</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>26925</td>\n",
       "      <td>0.24</td>\n",
       "      <td>10.7</td>\n",
       "      <td>67262</td>\n",
       "      <td>10.9</td>\n",
       "      <td>0.108196</td>\n",
       "      <td>0.277593</td>\n",
       "      <td>0.249642</td>\n",
       "      <td>0.203835</td>\n",
       "      <td>0.160734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>336.407227</td>\n",
       "      <td>20.607727</td>\n",
       "      <td>2014</td>\n",
       "      <td>CT</td>\n",
       "      <td>3.590886</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>26800</td>\n",
       "      <td>0.24</td>\n",
       "      <td>10.8</td>\n",
       "      <td>70007</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.104664</td>\n",
       "      <td>0.276060</td>\n",
       "      <td>0.249281</td>\n",
       "      <td>0.206331</td>\n",
       "      <td>0.163664</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>557.121321</td>\n",
       "      <td>37.000467</td>\n",
       "      <td>2011</td>\n",
       "      <td>DE</td>\n",
       "      <td>0.945934</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>40172</td>\n",
       "      <td>0.16</td>\n",
       "      <td>12.6</td>\n",
       "      <td>58159</td>\n",
       "      <td>11.2</td>\n",
       "      <td>0.126456</td>\n",
       "      <td>0.317028</td>\n",
       "      <td>0.276797</td>\n",
       "      <td>0.166855</td>\n",
       "      <td>0.112864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>557.121321</td>\n",
       "      <td>40.171936</td>\n",
       "      <td>2012</td>\n",
       "      <td>DE</td>\n",
       "      <td>0.945934</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>40456</td>\n",
       "      <td>0.16</td>\n",
       "      <td>12.7</td>\n",
       "      <td>58326</td>\n",
       "      <td>10.3</td>\n",
       "      <td>0.123231</td>\n",
       "      <td>0.316354</td>\n",
       "      <td>0.275192</td>\n",
       "      <td>0.170918</td>\n",
       "      <td>0.114305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>407.547623</td>\n",
       "      <td>24.323792</td>\n",
       "      <td>2013</td>\n",
       "      <td>OR</td>\n",
       "      <td>4.028977</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>29684</td>\n",
       "      <td>0.08</td>\n",
       "      <td>16.5</td>\n",
       "      <td>50228</td>\n",
       "      <td>17.2</td>\n",
       "      <td>0.106105</td>\n",
       "      <td>0.245972</td>\n",
       "      <td>0.350890</td>\n",
       "      <td>0.187199</td>\n",
       "      <td>0.109834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>407.547623</td>\n",
       "      <td>24.323792</td>\n",
       "      <td>2014</td>\n",
       "      <td>OR</td>\n",
       "      <td>4.028977</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>30044</td>\n",
       "      <td>0.08</td>\n",
       "      <td>16.4</td>\n",
       "      <td>51088</td>\n",
       "      <td>11.6</td>\n",
       "      <td>0.105186</td>\n",
       "      <td>0.245435</td>\n",
       "      <td>0.348683</td>\n",
       "      <td>0.188916</td>\n",
       "      <td>0.111780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>447.568729</td>\n",
       "      <td>29.994135</td>\n",
       "      <td>2011</td>\n",
       "      <td>PA</td>\n",
       "      <td>12.802503</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>25977</td>\n",
       "      <td>0.08</td>\n",
       "      <td>13.7</td>\n",
       "      <td>50221</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.121028</td>\n",
       "      <td>0.375537</td>\n",
       "      <td>0.236739</td>\n",
       "      <td>0.164546</td>\n",
       "      <td>0.102150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>447.568729</td>\n",
       "      <td>30.775232</td>\n",
       "      <td>2012</td>\n",
       "      <td>PA</td>\n",
       "      <td>12.802503</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>26390</td>\n",
       "      <td>0.08</td>\n",
       "      <td>13.7</td>\n",
       "      <td>51225</td>\n",
       "      <td>11.7</td>\n",
       "      <td>0.117085</td>\n",
       "      <td>0.372147</td>\n",
       "      <td>0.240308</td>\n",
       "      <td>0.166197</td>\n",
       "      <td>0.104263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>447.568729</td>\n",
       "      <td>28.275721</td>\n",
       "      <td>2013</td>\n",
       "      <td>PA</td>\n",
       "      <td>12.802503</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>26238</td>\n",
       "      <td>0.08</td>\n",
       "      <td>13.7</td>\n",
       "      <td>52005</td>\n",
       "      <td>11.6</td>\n",
       "      <td>0.113376</td>\n",
       "      <td>0.370489</td>\n",
       "      <td>0.240716</td>\n",
       "      <td>0.168503</td>\n",
       "      <td>0.106917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>447.568729</td>\n",
       "      <td>25.385661</td>\n",
       "      <td>2014</td>\n",
       "      <td>PA</td>\n",
       "      <td>12.802503</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>26305</td>\n",
       "      <td>0.08</td>\n",
       "      <td>13.6</td>\n",
       "      <td>53224</td>\n",
       "      <td>10.2</td>\n",
       "      <td>0.110304</td>\n",
       "      <td>0.367517</td>\n",
       "      <td>0.241189</td>\n",
       "      <td>0.171392</td>\n",
       "      <td>0.109598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>679.363162</td>\n",
       "      <td>34.998414</td>\n",
       "      <td>2011</td>\n",
       "      <td>TN</td>\n",
       "      <td>6.600299</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>23006</td>\n",
       "      <td>1.29</td>\n",
       "      <td>18.4</td>\n",
       "      <td>41691</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.168184</td>\n",
       "      <td>0.332755</td>\n",
       "      <td>0.268751</td>\n",
       "      <td>0.148954</td>\n",
       "      <td>0.081356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>679.363162</td>\n",
       "      <td>41.210254</td>\n",
       "      <td>2012</td>\n",
       "      <td>TN</td>\n",
       "      <td>6.600299</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>22535</td>\n",
       "      <td>1.29</td>\n",
       "      <td>18.0</td>\n",
       "      <td>42743</td>\n",
       "      <td>16.2</td>\n",
       "      <td>0.161234</td>\n",
       "      <td>0.329632</td>\n",
       "      <td>0.274200</td>\n",
       "      <td>0.151694</td>\n",
       "      <td>0.083239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>679.363162</td>\n",
       "      <td>35.604448</td>\n",
       "      <td>2013</td>\n",
       "      <td>TN</td>\n",
       "      <td>6.600299</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>22440</td>\n",
       "      <td>1.29</td>\n",
       "      <td>17.8</td>\n",
       "      <td>44268</td>\n",
       "      <td>16.2</td>\n",
       "      <td>0.156058</td>\n",
       "      <td>0.330730</td>\n",
       "      <td>0.274774</td>\n",
       "      <td>0.153056</td>\n",
       "      <td>0.085382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>679.363162</td>\n",
       "      <td>35.604448</td>\n",
       "      <td>2014</td>\n",
       "      <td>TN</td>\n",
       "      <td>6.600299</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>22627</td>\n",
       "      <td>1.29</td>\n",
       "      <td>18.2</td>\n",
       "      <td>44357</td>\n",
       "      <td>14.1</td>\n",
       "      <td>0.150539</td>\n",
       "      <td>0.330769</td>\n",
       "      <td>0.274813</td>\n",
       "      <td>0.156002</td>\n",
       "      <td>0.087877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>552.766281</td>\n",
       "      <td>31.926767</td>\n",
       "      <td>2011</td>\n",
       "      <td>TX</td>\n",
       "      <td>27.469114</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>26060</td>\n",
       "      <td>0.19</td>\n",
       "      <td>18.5</td>\n",
       "      <td>49390</td>\n",
       "      <td>25.7</td>\n",
       "      <td>0.195739</td>\n",
       "      <td>0.256603</td>\n",
       "      <td>0.287076</td>\n",
       "      <td>0.174431</td>\n",
       "      <td>0.086151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>552.766281</td>\n",
       "      <td>31.708340</td>\n",
       "      <td>2012</td>\n",
       "      <td>TX</td>\n",
       "      <td>27.469114</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>26133</td>\n",
       "      <td>0.19</td>\n",
       "      <td>17.9</td>\n",
       "      <td>50747</td>\n",
       "      <td>25.2</td>\n",
       "      <td>0.192273</td>\n",
       "      <td>0.252877</td>\n",
       "      <td>0.292256</td>\n",
       "      <td>0.175141</td>\n",
       "      <td>0.087453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>552.766281</td>\n",
       "      <td>31.817553</td>\n",
       "      <td>2013</td>\n",
       "      <td>TX</td>\n",
       "      <td>27.469114</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>25757</td>\n",
       "      <td>0.19</td>\n",
       "      <td>17.5</td>\n",
       "      <td>51714</td>\n",
       "      <td>24.8</td>\n",
       "      <td>0.188320</td>\n",
       "      <td>0.253148</td>\n",
       "      <td>0.291995</td>\n",
       "      <td>0.177269</td>\n",
       "      <td>0.089268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>552.766281</td>\n",
       "      <td>33.200925</td>\n",
       "      <td>2014</td>\n",
       "      <td>TX</td>\n",
       "      <td>27.469114</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>25532</td>\n",
       "      <td>0.19</td>\n",
       "      <td>17.2</td>\n",
       "      <td>53067</td>\n",
       "      <td>21.4</td>\n",
       "      <td>0.184172</td>\n",
       "      <td>0.252350</td>\n",
       "      <td>0.292602</td>\n",
       "      <td>0.179484</td>\n",
       "      <td>0.091392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>436.072979</td>\n",
       "      <td>33.544075</td>\n",
       "      <td>2011</td>\n",
       "      <td>VT</td>\n",
       "      <td>0.626042</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>31776</td>\n",
       "      <td>0.27</td>\n",
       "      <td>11.9</td>\n",
       "      <td>52033</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.089917</td>\n",
       "      <td>0.316640</td>\n",
       "      <td>0.254980</td>\n",
       "      <td>0.205277</td>\n",
       "      <td>0.133185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>436.072979</td>\n",
       "      <td>38.336086</td>\n",
       "      <td>2012</td>\n",
       "      <td>VT</td>\n",
       "      <td>0.626042</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>33253</td>\n",
       "      <td>0.27</td>\n",
       "      <td>11.9</td>\n",
       "      <td>52700</td>\n",
       "      <td>7.9</td>\n",
       "      <td>0.087464</td>\n",
       "      <td>0.312187</td>\n",
       "      <td>0.258295</td>\n",
       "      <td>0.207282</td>\n",
       "      <td>0.134772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>436.072979</td>\n",
       "      <td>36.738749</td>\n",
       "      <td>2013</td>\n",
       "      <td>VT</td>\n",
       "      <td>0.626042</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>34084</td>\n",
       "      <td>0.27</td>\n",
       "      <td>12.3</td>\n",
       "      <td>52511</td>\n",
       "      <td>8.7</td>\n",
       "      <td>0.086112</td>\n",
       "      <td>0.307729</td>\n",
       "      <td>0.258061</td>\n",
       "      <td>0.210161</td>\n",
       "      <td>0.137937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>436.072979</td>\n",
       "      <td>19.168043</td>\n",
       "      <td>2014</td>\n",
       "      <td>VT</td>\n",
       "      <td>0.626042</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>34580</td>\n",
       "      <td>0.27</td>\n",
       "      <td>12.0</td>\n",
       "      <td>54153</td>\n",
       "      <td>6.1</td>\n",
       "      <td>0.083576</td>\n",
       "      <td>0.305799</td>\n",
       "      <td>0.258603</td>\n",
       "      <td>0.212294</td>\n",
       "      <td>0.139728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>413.575438</td>\n",
       "      <td>26.601478</td>\n",
       "      <td>2011</td>\n",
       "      <td>VA</td>\n",
       "      <td>8.382993</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>23944</td>\n",
       "      <td>0.28</td>\n",
       "      <td>11.6</td>\n",
       "      <td>61877</td>\n",
       "      <td>14.3</td>\n",
       "      <td>0.134065</td>\n",
       "      <td>0.256356</td>\n",
       "      <td>0.266047</td>\n",
       "      <td>0.201592</td>\n",
       "      <td>0.141939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>413.575438</td>\n",
       "      <td>23.261382</td>\n",
       "      <td>2012</td>\n",
       "      <td>VA</td>\n",
       "      <td>8.382993</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>23952</td>\n",
       "      <td>0.28</td>\n",
       "      <td>11.8</td>\n",
       "      <td>61782</td>\n",
       "      <td>14.2</td>\n",
       "      <td>0.130504</td>\n",
       "      <td>0.252465</td>\n",
       "      <td>0.270246</td>\n",
       "      <td>0.202661</td>\n",
       "      <td>0.144124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>413.575438</td>\n",
       "      <td>26.840056</td>\n",
       "      <td>2013</td>\n",
       "      <td>VA</td>\n",
       "      <td>8.382993</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>23606</td>\n",
       "      <td>0.28</td>\n",
       "      <td>11.7</td>\n",
       "      <td>62745</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.125496</td>\n",
       "      <td>0.251583</td>\n",
       "      <td>0.270847</td>\n",
       "      <td>0.205210</td>\n",
       "      <td>0.146863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>413.575438</td>\n",
       "      <td>24.334984</td>\n",
       "      <td>2014</td>\n",
       "      <td>VA</td>\n",
       "      <td>8.382993</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>23688</td>\n",
       "      <td>0.28</td>\n",
       "      <td>11.8</td>\n",
       "      <td>64923</td>\n",
       "      <td>12.4</td>\n",
       "      <td>0.121138</td>\n",
       "      <td>0.250080</td>\n",
       "      <td>0.271114</td>\n",
       "      <td>0.207390</td>\n",
       "      <td>0.150277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>445.304095</td>\n",
       "      <td>33.441125</td>\n",
       "      <td>2011</td>\n",
       "      <td>WI</td>\n",
       "      <td>5.771337</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>33659</td>\n",
       "      <td>0.06</td>\n",
       "      <td>13.1</td>\n",
       "      <td>50401</td>\n",
       "      <td>10.3</td>\n",
       "      <td>0.101934</td>\n",
       "      <td>0.336491</td>\n",
       "      <td>0.301222</td>\n",
       "      <td>0.172603</td>\n",
       "      <td>0.087750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>445.304095</td>\n",
       "      <td>33.614395</td>\n",
       "      <td>2012</td>\n",
       "      <td>WI</td>\n",
       "      <td>5.771337</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>34159</td>\n",
       "      <td>0.06</td>\n",
       "      <td>13.2</td>\n",
       "      <td>51063</td>\n",
       "      <td>10.4</td>\n",
       "      <td>0.098449</td>\n",
       "      <td>0.331277</td>\n",
       "      <td>0.306291</td>\n",
       "      <td>0.174702</td>\n",
       "      <td>0.089281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>445.304095</td>\n",
       "      <td>31.535154</td>\n",
       "      <td>2013</td>\n",
       "      <td>WI</td>\n",
       "      <td>5.771337</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>33823</td>\n",
       "      <td>0.06</td>\n",
       "      <td>13.5</td>\n",
       "      <td>51474</td>\n",
       "      <td>10.6</td>\n",
       "      <td>0.095845</td>\n",
       "      <td>0.328345</td>\n",
       "      <td>0.307582</td>\n",
       "      <td>0.177467</td>\n",
       "      <td>0.090761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>445.304095</td>\n",
       "      <td>28.936103</td>\n",
       "      <td>2014</td>\n",
       "      <td>WI</td>\n",
       "      <td>5.771337</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>33562</td>\n",
       "      <td>0.06</td>\n",
       "      <td>13.2</td>\n",
       "      <td>52632</td>\n",
       "      <td>8.6</td>\n",
       "      <td>0.092493</td>\n",
       "      <td>0.323815</td>\n",
       "      <td>0.309515</td>\n",
       "      <td>0.181003</td>\n",
       "      <td>0.093175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>967.400150</td>\n",
       "      <td>66.540751</td>\n",
       "      <td>2011</td>\n",
       "      <td>WY</td>\n",
       "      <td>0.586107</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>30024</td>\n",
       "      <td>0.02</td>\n",
       "      <td>11.3</td>\n",
       "      <td>56044</td>\n",
       "      <td>17.3</td>\n",
       "      <td>0.081287</td>\n",
       "      <td>0.304649</td>\n",
       "      <td>0.371959</td>\n",
       "      <td>0.160454</td>\n",
       "      <td>0.081651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>967.400150</td>\n",
       "      <td>68.246924</td>\n",
       "      <td>2012</td>\n",
       "      <td>WY</td>\n",
       "      <td>0.586107</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>30778</td>\n",
       "      <td>0.02</td>\n",
       "      <td>11.9</td>\n",
       "      <td>55104</td>\n",
       "      <td>17.3</td>\n",
       "      <td>0.079190</td>\n",
       "      <td>0.305455</td>\n",
       "      <td>0.372747</td>\n",
       "      <td>0.161713</td>\n",
       "      <td>0.080896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>967.400150</td>\n",
       "      <td>49.479020</td>\n",
       "      <td>2013</td>\n",
       "      <td>WY</td>\n",
       "      <td>0.586107</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>30008</td>\n",
       "      <td>0.02</td>\n",
       "      <td>10.9</td>\n",
       "      <td>58424</td>\n",
       "      <td>15.8</td>\n",
       "      <td>0.076491</td>\n",
       "      <td>0.299698</td>\n",
       "      <td>0.377063</td>\n",
       "      <td>0.164787</td>\n",
       "      <td>0.081962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>967.400150</td>\n",
       "      <td>73.365444</td>\n",
       "      <td>2014</td>\n",
       "      <td>WY</td>\n",
       "      <td>0.586107</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>30552</td>\n",
       "      <td>0.02</td>\n",
       "      <td>11.2</td>\n",
       "      <td>58291</td>\n",
       "      <td>14.2</td>\n",
       "      <td>0.077056</td>\n",
       "      <td>0.294103</td>\n",
       "      <td>0.377617</td>\n",
       "      <td>0.167980</td>\n",
       "      <td>0.083244</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>152 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        ACC_MIL    ACH_MIL  YEAR STATE_SHORT    POP_MIL SUSPEND INTERLOCK_1ST  \\\n",
       "0    806.136433  48.569874  2011          AL   4.858979     yes            no   \n",
       "1    806.136433  46.100220  2012          AL   4.858979     yes            no   \n",
       "2    806.136433  44.042174  2013          AL   4.858979     yes            no   \n",
       "3    806.136433  47.952461  2014          AL   4.858979     yes            no   \n",
       "4    398.140926  24.375975  2011          AK   0.738432     yes            no   \n",
       "5    398.140926  20.313313  2012          AK   0.738432     yes            no   \n",
       "6    398.140926  20.313313  2013          AK   0.738432     yes            no   \n",
       "7    398.140926  35.209742  2014          AK   0.738432     yes            no   \n",
       "8    555.501449  28.265695  2011          AZ   6.828065     yes            no   \n",
       "9    555.501449  28.705058  2012          AZ   6.828065     yes            no   \n",
       "10   555.501449  29.583784  2013          AZ   6.828065     yes            no   \n",
       "11   555.501449  25.190153  2014          AZ   6.828065     yes            no   \n",
       "12   799.475120  54.059426  2011          AR   2.978204     yes            no   \n",
       "13   799.475120  51.373244  2012          AR   2.978204     yes            no   \n",
       "14   799.475120  40.292740  2013          AR   2.978204     yes            no   \n",
       "15   799.475120  38.613876  2014          AR   2.978204     yes            no   \n",
       "16   357.493040  19.057439  2011          CA  39.144818     yes            no   \n",
       "17   357.493040  20.283655  2012          CA  39.144818     yes            no   \n",
       "18   357.493040  20.462479  2013          CA  39.144818     yes            no   \n",
       "19   357.493040  20.743486  2014          CA  39.144818     yes            no   \n",
       "20   408.681345  26.023655  2011          CO   5.456574     yes            no   \n",
       "21   408.681345  25.290594  2012          CO   5.456574     yes            no   \n",
       "22   408.681345  26.756716  2013          CO   5.456574     yes            no   \n",
       "23   408.681345  28.039572  2014          CO   5.456574     yes            no   \n",
       "24   336.407227  20.329245  2011          CT   3.590886     yes            no   \n",
       "25   336.407227  22.557107  2012          CT   3.590886     yes            no   \n",
       "26   336.407227  25.620418  2013          CT   3.590886     yes            no   \n",
       "27   336.407227  20.607727  2014          CT   3.590886     yes            no   \n",
       "28   557.121321  37.000467  2011          DE   0.945934     yes            no   \n",
       "29   557.121321  40.171936  2012          DE   0.945934     yes            no   \n",
       "..          ...        ...   ...         ...        ...     ...           ...   \n",
       "122  407.547623  24.323792  2013          OR   4.028977     yes            no   \n",
       "123  407.547623  24.323792  2014          OR   4.028977     yes            no   \n",
       "124  447.568729  29.994135  2011          PA  12.802503      no            no   \n",
       "125  447.568729  30.775232  2012          PA  12.802503      no            no   \n",
       "126  447.568729  28.275721  2013          PA  12.802503      no            no   \n",
       "127  447.568729  25.385661  2014          PA  12.802503      no            no   \n",
       "128  679.363162  34.998414  2011          TN   6.600299      no            no   \n",
       "129  679.363162  41.210254  2012          TN   6.600299      no            no   \n",
       "130  679.363162  35.604448  2013          TN   6.600299      no            no   \n",
       "131  679.363162  35.604448  2014          TN   6.600299      no            no   \n",
       "132  552.766281  31.926767  2011          TX  27.469114     yes            no   \n",
       "133  552.766281  31.708340  2012          TX  27.469114     yes            no   \n",
       "134  552.766281  31.817553  2013          TX  27.469114     yes            no   \n",
       "135  552.766281  33.200925  2014          TX  27.469114     yes            no   \n",
       "136  436.072979  33.544075  2011          VT   0.626042     yes            no   \n",
       "137  436.072979  38.336086  2012          VT   0.626042     yes            no   \n",
       "138  436.072979  36.738749  2013          VT   0.626042     yes            no   \n",
       "139  436.072979  19.168043  2014          VT   0.626042     yes            no   \n",
       "140  413.575438  26.601478  2011          VA   8.382993     yes            no   \n",
       "141  413.575438  23.261382  2012          VA   8.382993     yes            no   \n",
       "142  413.575438  26.840056  2013          VA   8.382993     yes            no   \n",
       "143  413.575438  24.334984  2014          VA   8.382993     yes            no   \n",
       "144  445.304095  33.441125  2011          WI   5.771337     yes            no   \n",
       "145  445.304095  33.614395  2012          WI   5.771337     yes            no   \n",
       "146  445.304095  31.535154  2013          WI   5.771337     yes            no   \n",
       "147  445.304095  28.936103  2014          WI   5.771337     yes            no   \n",
       "148  967.400150  66.540751  2011          WY   0.586107     yes            no   \n",
       "149  967.400150  68.246924  2012          WY   0.586107     yes            no   \n",
       "150  967.400150  49.479020  2013          WY   0.586107     yes            no   \n",
       "151  967.400150  73.365444  2014          WY   0.586107     yes            no   \n",
       "\n",
       "    INTERLOCK_REPEAT  GALLONS_ALCOHOL_PER_CAP_21  BEER_TAX  PERCENT_POVERTY  \\\n",
       "0                yes                       22331      1.05             19.1   \n",
       "1                yes                       22656      1.05             19.0   \n",
       "2                yes                       22491      1.05             18.9   \n",
       "3                yes                       22481      1.05             19.2   \n",
       "4                yes                       32713      1.07             10.8   \n",
       "5                yes                       32236      1.07             10.8   \n",
       "6                yes                       31277      1.07             10.1   \n",
       "7                yes                       31696      1.07             11.4   \n",
       "8                yes                       27228      0.16             19.0   \n",
       "9                yes                       27627      0.16             18.7   \n",
       "10               yes                       26677      0.16             18.6   \n",
       "11               yes                       26819      0.16             18.2   \n",
       "12               yes                       19519      0.24             19.3   \n",
       "13               yes                       20435      0.24             19.6   \n",
       "14               yes                       20398      0.24             19.4   \n",
       "15               yes                       20203      0.24             18.7   \n",
       "16               yes                       25718      0.20             16.6   \n",
       "17               yes                       26742      0.20             17.0   \n",
       "18               yes                       26373      0.20             16.8   \n",
       "19               yes                       26200      0.20             16.4   \n",
       "20               yes                       30797      0.08             13.4   \n",
       "21               yes                       31076      0.08             13.6   \n",
       "22               yes                       31606      0.08             12.9   \n",
       "23               yes                       31067      0.08             12.1   \n",
       "24               yes                       26710      0.24             10.8   \n",
       "25               yes                       27104      0.24             10.6   \n",
       "26               yes                       26925      0.24             10.7   \n",
       "27               yes                       26800      0.24             10.8   \n",
       "28               yes                       40172      0.16             12.6   \n",
       "29               yes                       40456      0.16             12.7   \n",
       "..               ...                         ...       ...              ...   \n",
       "122              yes                       29684      0.08             16.5   \n",
       "123              yes                       30044      0.08             16.4   \n",
       "124              yes                       25977      0.08             13.7   \n",
       "125              yes                       26390      0.08             13.7   \n",
       "126              yes                       26238      0.08             13.7   \n",
       "127              yes                       26305      0.08             13.6   \n",
       "128              yes                       23006      1.29             18.4   \n",
       "129              yes                       22535      1.29             18.0   \n",
       "130              yes                       22440      1.29             17.8   \n",
       "131              yes                       22627      1.29             18.2   \n",
       "132              yes                       26060      0.19             18.5   \n",
       "133              yes                       26133      0.19             17.9   \n",
       "134              yes                       25757      0.19             17.5   \n",
       "135              yes                       25532      0.19             17.2   \n",
       "136              yes                       31776      0.27             11.9   \n",
       "137              yes                       33253      0.27             11.9   \n",
       "138              yes                       34084      0.27             12.3   \n",
       "139              yes                       34580      0.27             12.0   \n",
       "140              yes                       23944      0.28             11.6   \n",
       "141              yes                       23952      0.28             11.8   \n",
       "142              yes                       23606      0.28             11.7   \n",
       "143              yes                       23688      0.28             11.8   \n",
       "144              yes                       33659      0.06             13.1   \n",
       "145              yes                       34159      0.06             13.2   \n",
       "146              yes                       33823      0.06             13.5   \n",
       "147              yes                       33562      0.06             13.2   \n",
       "148              yes                       30024      0.02             11.3   \n",
       "149              yes                       30778      0.02             11.9   \n",
       "150              yes                       30008      0.02             10.9   \n",
       "151              yes                       30552      0.02             11.2   \n",
       "\n",
       "     MEDIAN_INCOME  PERCENT_UNINSURE  LESS_HS_P      HS_P  SOME_C_P  \\\n",
       "0            41427              16.6   0.180897  0.314334  0.285068   \n",
       "1            41610              15.8   0.174023  0.313100  0.290229   \n",
       "2            42882              15.9   0.168852  0.310562  0.294274   \n",
       "3            42917              14.2   0.162953  0.310687  0.295833   \n",
       "4            65699              21.7   0.086375  0.272442  0.369075   \n",
       "5            66503              22.3   0.084130  0.270973  0.370134   \n",
       "6            70058              20.8   0.083634  0.273077  0.368287   \n",
       "7            70898              19.0   0.081900  0.275051  0.366203   \n",
       "8            46710              19.6   0.148176  0.247291  0.340564   \n",
       "9            47796              20.4   0.145577  0.243979  0.344151   \n",
       "10           48504              20.0   0.143056  0.245064  0.343135   \n",
       "11           50036              16.1   0.141056  0.245072  0.342895   \n",
       "12           38889              20.1   0.173465  0.352003  0.278698   \n",
       "13           40151              19.4   0.166937  0.351238  0.283841   \n",
       "14           40605              18.8   0.162692  0.350798  0.285475   \n",
       "15           41335              13.8   0.157028  0.349982  0.286530   \n",
       "16           57275              20.2   0.191818  0.211169  0.294672   \n",
       "17           58322              20.0   0.189801  0.206846  0.298819   \n",
       "18           60185              19.4   0.187580  0.207157  0.298534   \n",
       "19           61927              14.1   0.185113  0.207242  0.297625   \n",
       "20           55530              17.0   0.103172  0.229340  0.304557   \n",
       "21           56880              16.7   0.100773  0.223595  0.308869   \n",
       "22           58942              16.0   0.098276  0.221388  0.310048   \n",
       "23           61324              11.7   0.096208  0.219880  0.309300   \n",
       "24           65822              10.1   0.114309  0.281284  0.247303   \n",
       "25           67275              10.5   0.110414  0.278551  0.249469   \n",
       "26           67262              10.9   0.108196  0.277593  0.249642   \n",
       "27           70007               8.0   0.104664  0.276060  0.249281   \n",
       "28           58159              11.2   0.126456  0.317028  0.276797   \n",
       "29           58326              10.3   0.123231  0.316354  0.275192   \n",
       "..             ...               ...        ...       ...       ...   \n",
       "122          50228              17.2   0.106105  0.245972  0.350890   \n",
       "123          51088              11.6   0.105186  0.245435  0.348683   \n",
       "124          50221              12.0   0.121028  0.375537  0.236739   \n",
       "125          51225              11.7   0.117085  0.372147  0.240308   \n",
       "126          52005              11.6   0.113376  0.370489  0.240716   \n",
       "127          53224              10.2   0.110304  0.367517  0.241189   \n",
       "128          41691              17.0   0.168184  0.332755  0.268751   \n",
       "129          42743              16.2   0.161234  0.329632  0.274200   \n",
       "130          44268              16.2   0.156058  0.330730  0.274774   \n",
       "131          44357              14.1   0.150539  0.330769  0.274813   \n",
       "132          49390              25.7   0.195739  0.256603  0.287076   \n",
       "133          50747              25.2   0.192273  0.252877  0.292256   \n",
       "134          51714              24.8   0.188320  0.253148  0.291995   \n",
       "135          53067              21.4   0.184172  0.252350  0.292602   \n",
       "136          52033               8.0   0.089917  0.316640  0.254980   \n",
       "137          52700               7.9   0.087464  0.312187  0.258295   \n",
       "138          52511               8.7   0.086112  0.307729  0.258061   \n",
       "139          54153               6.1   0.083576  0.305799  0.258603   \n",
       "140          61877              14.3   0.134065  0.256356  0.266047   \n",
       "141          61782              14.2   0.130504  0.252465  0.270246   \n",
       "142          62745              14.0   0.125496  0.251583  0.270847   \n",
       "143          64923              12.4   0.121138  0.250080  0.271114   \n",
       "144          50401              10.3   0.101934  0.336491  0.301222   \n",
       "145          51063              10.4   0.098449  0.331277  0.306291   \n",
       "146          51474              10.6   0.095845  0.328345  0.307582   \n",
       "147          52632               8.6   0.092493  0.323815  0.309515   \n",
       "148          56044              17.3   0.081287  0.304649  0.371959   \n",
       "149          55104              17.3   0.079190  0.305455  0.372747   \n",
       "150          58424              15.8   0.076491  0.299698  0.377063   \n",
       "151          58291              14.2   0.077056  0.294103  0.377617   \n",
       "\n",
       "     BACHELORS_P  GRAD_PROF_P  \n",
       "0       0.139643     0.080058  \n",
       "1       0.141521     0.081127  \n",
       "2       0.143547     0.082766  \n",
       "3       0.144587     0.085940  \n",
       "4       0.176662     0.095446  \n",
       "5       0.177505     0.097258  \n",
       "6       0.177079     0.097924  \n",
       "7       0.178704     0.098143  \n",
       "8       0.168360     0.095609  \n",
       "9       0.169160     0.097133  \n",
       "10      0.170197     0.098547  \n",
       "11      0.171268     0.099709  \n",
       "12      0.130271     0.065563  \n",
       "13      0.131480     0.066503  \n",
       "14      0.132791     0.068245  \n",
       "15      0.135028     0.071433  \n",
       "16      0.192582     0.109759  \n",
       "17      0.193536     0.110998  \n",
       "18      0.194375     0.112353  \n",
       "19      0.195872     0.114148  \n",
       "20      0.232747     0.130185  \n",
       "21      0.234469     0.132294  \n",
       "22      0.235905     0.134382  \n",
       "23      0.237353     0.137259  \n",
       "24      0.201377     0.155727  \n",
       "25      0.203261     0.158304  \n",
       "26      0.203835     0.160734  \n",
       "27      0.206331     0.163664  \n",
       "28      0.166855     0.112864  \n",
       "29      0.170918     0.114305  \n",
       "..           ...          ...  \n",
       "122     0.187199     0.109834  \n",
       "123     0.188916     0.111780  \n",
       "124     0.164546     0.102150  \n",
       "125     0.166197     0.104263  \n",
       "126     0.168503     0.106917  \n",
       "127     0.171392     0.109598  \n",
       "128     0.148954     0.081356  \n",
       "129     0.151694     0.083239  \n",
       "130     0.153056     0.085382  \n",
       "131     0.156002     0.087877  \n",
       "132     0.174431     0.086151  \n",
       "133     0.175141     0.087453  \n",
       "134     0.177269     0.089268  \n",
       "135     0.179484     0.091392  \n",
       "136     0.205277     0.133185  \n",
       "137     0.207282     0.134772  \n",
       "138     0.210161     0.137937  \n",
       "139     0.212294     0.139728  \n",
       "140     0.201592     0.141939  \n",
       "141     0.202661     0.144124  \n",
       "142     0.205210     0.146863  \n",
       "143     0.207390     0.150277  \n",
       "144     0.172603     0.087750  \n",
       "145     0.174702     0.089281  \n",
       "146     0.177467     0.090761  \n",
       "147     0.181003     0.093175  \n",
       "148     0.160454     0.081651  \n",
       "149     0.161713     0.080896  \n",
       "150     0.164787     0.081962  \n",
       "151     0.167980     0.083244  \n",
       "\n",
       "[152 rows x 18 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dui_tax_short"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "features = pd.DataFrame(dui_tax_short)\n",
    "features = features.drop('ACH_MIL', axis=1)\n",
    "features = features.drop('ACC_MIL', axis=1)\n",
    "\n",
    "targets = dui_tax_short.ACH_MIL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn import preprocessing\n",
    "le = preprocessing.LabelEncoder()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['YEAR', 'STATE_SHORT', 'POP_MIL', 'SUSPEND', 'INTERLOCK_1ST',\n",
       "       'INTERLOCK_REPEAT', 'GALLONS_ALCOHOL_PER_CAP_21', 'BEER_TAX',\n",
       "       'PERCENT_POVERTY', 'MEDIAN_INCOME', 'PERCENT_UNINSURE', 'LESS_HS_P',\n",
       "       'HS_P', 'SOME_C_P', 'BACHELORS_P', 'GRAD_PROF_P'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "range(0, 16)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "range(len(features.columns))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#rf in python cannot take strings\n",
    "#range(len(features.columns)\n",
    "for i in [1,3,4,5]:\n",
    "    features.iloc[:,i] = le.fit_transform(features.iloc[:,i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>YEAR</th>\n",
       "      <th>STATE_SHORT</th>\n",
       "      <th>POP_MIL</th>\n",
       "      <th>SUSPEND</th>\n",
       "      <th>INTERLOCK_1ST</th>\n",
       "      <th>INTERLOCK_REPEAT</th>\n",
       "      <th>GALLONS_ALCOHOL_PER_CAP_21</th>\n",
       "      <th>BEER_TAX</th>\n",
       "      <th>PERCENT_POVERTY</th>\n",
       "      <th>MEDIAN_INCOME</th>\n",
       "      <th>PERCENT_UNINSURE</th>\n",
       "      <th>LESS_HS_P</th>\n",
       "      <th>HS_P</th>\n",
       "      <th>SOME_C_P</th>\n",
       "      <th>BACHELORS_P</th>\n",
       "      <th>GRAD_PROF_P</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2011</td>\n",
       "      <td>1</td>\n",
       "      <td>4.858979</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>22331</td>\n",
       "      <td>1.05</td>\n",
       "      <td>19.1</td>\n",
       "      <td>41427</td>\n",
       "      <td>16.6</td>\n",
       "      <td>0.180897</td>\n",
       "      <td>0.314334</td>\n",
       "      <td>0.285068</td>\n",
       "      <td>0.139643</td>\n",
       "      <td>0.080058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2012</td>\n",
       "      <td>1</td>\n",
       "      <td>4.858979</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>22656</td>\n",
       "      <td>1.05</td>\n",
       "      <td>19.0</td>\n",
       "      <td>41610</td>\n",
       "      <td>15.8</td>\n",
       "      <td>0.174023</td>\n",
       "      <td>0.313100</td>\n",
       "      <td>0.290229</td>\n",
       "      <td>0.141521</td>\n",
       "      <td>0.081127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013</td>\n",
       "      <td>1</td>\n",
       "      <td>4.858979</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>22491</td>\n",
       "      <td>1.05</td>\n",
       "      <td>18.9</td>\n",
       "      <td>42882</td>\n",
       "      <td>15.9</td>\n",
       "      <td>0.168852</td>\n",
       "      <td>0.310562</td>\n",
       "      <td>0.294274</td>\n",
       "      <td>0.143547</td>\n",
       "      <td>0.082766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014</td>\n",
       "      <td>1</td>\n",
       "      <td>4.858979</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>22481</td>\n",
       "      <td>1.05</td>\n",
       "      <td>19.2</td>\n",
       "      <td>42917</td>\n",
       "      <td>14.2</td>\n",
       "      <td>0.162953</td>\n",
       "      <td>0.310687</td>\n",
       "      <td>0.295833</td>\n",
       "      <td>0.144587</td>\n",
       "      <td>0.085940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2011</td>\n",
       "      <td>0</td>\n",
       "      <td>0.738432</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>32713</td>\n",
       "      <td>1.07</td>\n",
       "      <td>10.8</td>\n",
       "      <td>65699</td>\n",
       "      <td>21.7</td>\n",
       "      <td>0.086375</td>\n",
       "      <td>0.272442</td>\n",
       "      <td>0.369075</td>\n",
       "      <td>0.176662</td>\n",
       "      <td>0.095446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2012</td>\n",
       "      <td>0</td>\n",
       "      <td>0.738432</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>32236</td>\n",
       "      <td>1.07</td>\n",
       "      <td>10.8</td>\n",
       "      <td>66503</td>\n",
       "      <td>22.3</td>\n",
       "      <td>0.084130</td>\n",
       "      <td>0.270973</td>\n",
       "      <td>0.370134</td>\n",
       "      <td>0.177505</td>\n",
       "      <td>0.097258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2013</td>\n",
       "      <td>0</td>\n",
       "      <td>0.738432</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>31277</td>\n",
       "      <td>1.07</td>\n",
       "      <td>10.1</td>\n",
       "      <td>70058</td>\n",
       "      <td>20.8</td>\n",
       "      <td>0.083634</td>\n",
       "      <td>0.273077</td>\n",
       "      <td>0.368287</td>\n",
       "      <td>0.177079</td>\n",
       "      <td>0.097924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2014</td>\n",
       "      <td>0</td>\n",
       "      <td>0.738432</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>31696</td>\n",
       "      <td>1.07</td>\n",
       "      <td>11.4</td>\n",
       "      <td>70898</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0.081900</td>\n",
       "      <td>0.275051</td>\n",
       "      <td>0.366203</td>\n",
       "      <td>0.178704</td>\n",
       "      <td>0.098143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2011</td>\n",
       "      <td>3</td>\n",
       "      <td>6.828065</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>27228</td>\n",
       "      <td>0.16</td>\n",
       "      <td>19.0</td>\n",
       "      <td>46710</td>\n",
       "      <td>19.6</td>\n",
       "      <td>0.148176</td>\n",
       "      <td>0.247291</td>\n",
       "      <td>0.340564</td>\n",
       "      <td>0.168360</td>\n",
       "      <td>0.095609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2012</td>\n",
       "      <td>3</td>\n",
       "      <td>6.828065</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>27627</td>\n",
       "      <td>0.16</td>\n",
       "      <td>18.7</td>\n",
       "      <td>47796</td>\n",
       "      <td>20.4</td>\n",
       "      <td>0.145577</td>\n",
       "      <td>0.243979</td>\n",
       "      <td>0.344151</td>\n",
       "      <td>0.169160</td>\n",
       "      <td>0.097133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2013</td>\n",
       "      <td>3</td>\n",
       "      <td>6.828065</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>26677</td>\n",
       "      <td>0.16</td>\n",
       "      <td>18.6</td>\n",
       "      <td>48504</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.143056</td>\n",
       "      <td>0.245064</td>\n",
       "      <td>0.343135</td>\n",
       "      <td>0.170197</td>\n",
       "      <td>0.098547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2014</td>\n",
       "      <td>3</td>\n",
       "      <td>6.828065</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>26819</td>\n",
       "      <td>0.16</td>\n",
       "      <td>18.2</td>\n",
       "      <td>50036</td>\n",
       "      <td>16.1</td>\n",
       "      <td>0.141056</td>\n",
       "      <td>0.245072</td>\n",
       "      <td>0.342895</td>\n",
       "      <td>0.171268</td>\n",
       "      <td>0.099709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2011</td>\n",
       "      <td>2</td>\n",
       "      <td>2.978204</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>19519</td>\n",
       "      <td>0.24</td>\n",
       "      <td>19.3</td>\n",
       "      <td>38889</td>\n",
       "      <td>20.1</td>\n",
       "      <td>0.173465</td>\n",
       "      <td>0.352003</td>\n",
       "      <td>0.278698</td>\n",
       "      <td>0.130271</td>\n",
       "      <td>0.065563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2012</td>\n",
       "      <td>2</td>\n",
       "      <td>2.978204</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>20435</td>\n",
       "      <td>0.24</td>\n",
       "      <td>19.6</td>\n",
       "      <td>40151</td>\n",
       "      <td>19.4</td>\n",
       "      <td>0.166937</td>\n",
       "      <td>0.351238</td>\n",
       "      <td>0.283841</td>\n",
       "      <td>0.131480</td>\n",
       "      <td>0.066503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2013</td>\n",
       "      <td>2</td>\n",
       "      <td>2.978204</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>20398</td>\n",
       "      <td>0.24</td>\n",
       "      <td>19.4</td>\n",
       "      <td>40605</td>\n",
       "      <td>18.8</td>\n",
       "      <td>0.162692</td>\n",
       "      <td>0.350798</td>\n",
       "      <td>0.285475</td>\n",
       "      <td>0.132791</td>\n",
       "      <td>0.068245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2014</td>\n",
       "      <td>2</td>\n",
       "      <td>2.978204</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>20203</td>\n",
       "      <td>0.24</td>\n",
       "      <td>18.7</td>\n",
       "      <td>41335</td>\n",
       "      <td>13.8</td>\n",
       "      <td>0.157028</td>\n",
       "      <td>0.349982</td>\n",
       "      <td>0.286530</td>\n",
       "      <td>0.135028</td>\n",
       "      <td>0.071433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2011</td>\n",
       "      <td>4</td>\n",
       "      <td>39.144818</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>25718</td>\n",
       "      <td>0.20</td>\n",
       "      <td>16.6</td>\n",
       "      <td>57275</td>\n",
       "      <td>20.2</td>\n",
       "      <td>0.191818</td>\n",
       "      <td>0.211169</td>\n",
       "      <td>0.294672</td>\n",
       "      <td>0.192582</td>\n",
       "      <td>0.109759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2012</td>\n",
       "      <td>4</td>\n",
       "      <td>39.144818</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>26742</td>\n",
       "      <td>0.20</td>\n",
       "      <td>17.0</td>\n",
       "      <td>58322</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.189801</td>\n",
       "      <td>0.206846</td>\n",
       "      <td>0.298819</td>\n",
       "      <td>0.193536</td>\n",
       "      <td>0.110998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2013</td>\n",
       "      <td>4</td>\n",
       "      <td>39.144818</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>26373</td>\n",
       "      <td>0.20</td>\n",
       "      <td>16.8</td>\n",
       "      <td>60185</td>\n",
       "      <td>19.4</td>\n",
       "      <td>0.187580</td>\n",
       "      <td>0.207157</td>\n",
       "      <td>0.298534</td>\n",
       "      <td>0.194375</td>\n",
       "      <td>0.112353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2014</td>\n",
       "      <td>4</td>\n",
       "      <td>39.144818</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>26200</td>\n",
       "      <td>0.20</td>\n",
       "      <td>16.4</td>\n",
       "      <td>61927</td>\n",
       "      <td>14.1</td>\n",
       "      <td>0.185113</td>\n",
       "      <td>0.207242</td>\n",
       "      <td>0.297625</td>\n",
       "      <td>0.195872</td>\n",
       "      <td>0.114148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2011</td>\n",
       "      <td>5</td>\n",
       "      <td>5.456574</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>30797</td>\n",
       "      <td>0.08</td>\n",
       "      <td>13.4</td>\n",
       "      <td>55530</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.103172</td>\n",
       "      <td>0.229340</td>\n",
       "      <td>0.304557</td>\n",
       "      <td>0.232747</td>\n",
       "      <td>0.130185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2012</td>\n",
       "      <td>5</td>\n",
       "      <td>5.456574</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>31076</td>\n",
       "      <td>0.08</td>\n",
       "      <td>13.6</td>\n",
       "      <td>56880</td>\n",
       "      <td>16.7</td>\n",
       "      <td>0.100773</td>\n",
       "      <td>0.223595</td>\n",
       "      <td>0.308869</td>\n",
       "      <td>0.234469</td>\n",
       "      <td>0.132294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2013</td>\n",
       "      <td>5</td>\n",
       "      <td>5.456574</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>31606</td>\n",
       "      <td>0.08</td>\n",
       "      <td>12.9</td>\n",
       "      <td>58942</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.098276</td>\n",
       "      <td>0.221388</td>\n",
       "      <td>0.310048</td>\n",
       "      <td>0.235905</td>\n",
       "      <td>0.134382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2014</td>\n",
       "      <td>5</td>\n",
       "      <td>5.456574</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>31067</td>\n",
       "      <td>0.08</td>\n",
       "      <td>12.1</td>\n",
       "      <td>61324</td>\n",
       "      <td>11.7</td>\n",
       "      <td>0.096208</td>\n",
       "      <td>0.219880</td>\n",
       "      <td>0.309300</td>\n",
       "      <td>0.237353</td>\n",
       "      <td>0.137259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2011</td>\n",
       "      <td>6</td>\n",
       "      <td>3.590886</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>26710</td>\n",
       "      <td>0.24</td>\n",
       "      <td>10.8</td>\n",
       "      <td>65822</td>\n",
       "      <td>10.1</td>\n",
       "      <td>0.114309</td>\n",
       "      <td>0.281284</td>\n",
       "      <td>0.247303</td>\n",
       "      <td>0.201377</td>\n",
       "      <td>0.155727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2012</td>\n",
       "      <td>6</td>\n",
       "      <td>3.590886</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>27104</td>\n",
       "      <td>0.24</td>\n",
       "      <td>10.6</td>\n",
       "      <td>67275</td>\n",
       "      <td>10.5</td>\n",
       "      <td>0.110414</td>\n",
       "      <td>0.278551</td>\n",
       "      <td>0.249469</td>\n",
       "      <td>0.203261</td>\n",
       "      <td>0.158304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2013</td>\n",
       "      <td>6</td>\n",
       "      <td>3.590886</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>26925</td>\n",
       "      <td>0.24</td>\n",
       "      <td>10.7</td>\n",
       "      <td>67262</td>\n",
       "      <td>10.9</td>\n",
       "      <td>0.108196</td>\n",
       "      <td>0.277593</td>\n",
       "      <td>0.249642</td>\n",
       "      <td>0.203835</td>\n",
       "      <td>0.160734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2014</td>\n",
       "      <td>6</td>\n",
       "      <td>3.590886</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>26800</td>\n",
       "      <td>0.24</td>\n",
       "      <td>10.8</td>\n",
       "      <td>70007</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.104664</td>\n",
       "      <td>0.276060</td>\n",
       "      <td>0.249281</td>\n",
       "      <td>0.206331</td>\n",
       "      <td>0.163664</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2011</td>\n",
       "      <td>7</td>\n",
       "      <td>0.945934</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>40172</td>\n",
       "      <td>0.16</td>\n",
       "      <td>12.6</td>\n",
       "      <td>58159</td>\n",
       "      <td>11.2</td>\n",
       "      <td>0.126456</td>\n",
       "      <td>0.317028</td>\n",
       "      <td>0.276797</td>\n",
       "      <td>0.166855</td>\n",
       "      <td>0.112864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2012</td>\n",
       "      <td>7</td>\n",
       "      <td>0.945934</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>40456</td>\n",
       "      <td>0.16</td>\n",
       "      <td>12.7</td>\n",
       "      <td>58326</td>\n",
       "      <td>10.3</td>\n",
       "      <td>0.123231</td>\n",
       "      <td>0.316354</td>\n",
       "      <td>0.275192</td>\n",
       "      <td>0.170918</td>\n",
       "      <td>0.114305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>2013</td>\n",
       "      <td>30</td>\n",
       "      <td>4.028977</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>29684</td>\n",
       "      <td>0.08</td>\n",
       "      <td>16.5</td>\n",
       "      <td>50228</td>\n",
       "      <td>17.2</td>\n",
       "      <td>0.106105</td>\n",
       "      <td>0.245972</td>\n",
       "      <td>0.350890</td>\n",
       "      <td>0.187199</td>\n",
       "      <td>0.109834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>2014</td>\n",
       "      <td>30</td>\n",
       "      <td>4.028977</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>30044</td>\n",
       "      <td>0.08</td>\n",
       "      <td>16.4</td>\n",
       "      <td>51088</td>\n",
       "      <td>11.6</td>\n",
       "      <td>0.105186</td>\n",
       "      <td>0.245435</td>\n",
       "      <td>0.348683</td>\n",
       "      <td>0.188916</td>\n",
       "      <td>0.111780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>2011</td>\n",
       "      <td>31</td>\n",
       "      <td>12.802503</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>25977</td>\n",
       "      <td>0.08</td>\n",
       "      <td>13.7</td>\n",
       "      <td>50221</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.121028</td>\n",
       "      <td>0.375537</td>\n",
       "      <td>0.236739</td>\n",
       "      <td>0.164546</td>\n",
       "      <td>0.102150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>2012</td>\n",
       "      <td>31</td>\n",
       "      <td>12.802503</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>26390</td>\n",
       "      <td>0.08</td>\n",
       "      <td>13.7</td>\n",
       "      <td>51225</td>\n",
       "      <td>11.7</td>\n",
       "      <td>0.117085</td>\n",
       "      <td>0.372147</td>\n",
       "      <td>0.240308</td>\n",
       "      <td>0.166197</td>\n",
       "      <td>0.104263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>2013</td>\n",
       "      <td>31</td>\n",
       "      <td>12.802503</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>26238</td>\n",
       "      <td>0.08</td>\n",
       "      <td>13.7</td>\n",
       "      <td>52005</td>\n",
       "      <td>11.6</td>\n",
       "      <td>0.113376</td>\n",
       "      <td>0.370489</td>\n",
       "      <td>0.240716</td>\n",
       "      <td>0.168503</td>\n",
       "      <td>0.106917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>2014</td>\n",
       "      <td>31</td>\n",
       "      <td>12.802503</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>26305</td>\n",
       "      <td>0.08</td>\n",
       "      <td>13.6</td>\n",
       "      <td>53224</td>\n",
       "      <td>10.2</td>\n",
       "      <td>0.110304</td>\n",
       "      <td>0.367517</td>\n",
       "      <td>0.241189</td>\n",
       "      <td>0.171392</td>\n",
       "      <td>0.109598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>2011</td>\n",
       "      <td>32</td>\n",
       "      <td>6.600299</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>23006</td>\n",
       "      <td>1.29</td>\n",
       "      <td>18.4</td>\n",
       "      <td>41691</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.168184</td>\n",
       "      <td>0.332755</td>\n",
       "      <td>0.268751</td>\n",
       "      <td>0.148954</td>\n",
       "      <td>0.081356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>2012</td>\n",
       "      <td>32</td>\n",
       "      <td>6.600299</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>22535</td>\n",
       "      <td>1.29</td>\n",
       "      <td>18.0</td>\n",
       "      <td>42743</td>\n",
       "      <td>16.2</td>\n",
       "      <td>0.161234</td>\n",
       "      <td>0.329632</td>\n",
       "      <td>0.274200</td>\n",
       "      <td>0.151694</td>\n",
       "      <td>0.083239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>2013</td>\n",
       "      <td>32</td>\n",
       "      <td>6.600299</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>22440</td>\n",
       "      <td>1.29</td>\n",
       "      <td>17.8</td>\n",
       "      <td>44268</td>\n",
       "      <td>16.2</td>\n",
       "      <td>0.156058</td>\n",
       "      <td>0.330730</td>\n",
       "      <td>0.274774</td>\n",
       "      <td>0.153056</td>\n",
       "      <td>0.085382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>2014</td>\n",
       "      <td>32</td>\n",
       "      <td>6.600299</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>22627</td>\n",
       "      <td>1.29</td>\n",
       "      <td>18.2</td>\n",
       "      <td>44357</td>\n",
       "      <td>14.1</td>\n",
       "      <td>0.150539</td>\n",
       "      <td>0.330769</td>\n",
       "      <td>0.274813</td>\n",
       "      <td>0.156002</td>\n",
       "      <td>0.087877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>2011</td>\n",
       "      <td>33</td>\n",
       "      <td>27.469114</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>26060</td>\n",
       "      <td>0.19</td>\n",
       "      <td>18.5</td>\n",
       "      <td>49390</td>\n",
       "      <td>25.7</td>\n",
       "      <td>0.195739</td>\n",
       "      <td>0.256603</td>\n",
       "      <td>0.287076</td>\n",
       "      <td>0.174431</td>\n",
       "      <td>0.086151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>2012</td>\n",
       "      <td>33</td>\n",
       "      <td>27.469114</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>26133</td>\n",
       "      <td>0.19</td>\n",
       "      <td>17.9</td>\n",
       "      <td>50747</td>\n",
       "      <td>25.2</td>\n",
       "      <td>0.192273</td>\n",
       "      <td>0.252877</td>\n",
       "      <td>0.292256</td>\n",
       "      <td>0.175141</td>\n",
       "      <td>0.087453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>2013</td>\n",
       "      <td>33</td>\n",
       "      <td>27.469114</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>25757</td>\n",
       "      <td>0.19</td>\n",
       "      <td>17.5</td>\n",
       "      <td>51714</td>\n",
       "      <td>24.8</td>\n",
       "      <td>0.188320</td>\n",
       "      <td>0.253148</td>\n",
       "      <td>0.291995</td>\n",
       "      <td>0.177269</td>\n",
       "      <td>0.089268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>2014</td>\n",
       "      <td>33</td>\n",
       "      <td>27.469114</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>25532</td>\n",
       "      <td>0.19</td>\n",
       "      <td>17.2</td>\n",
       "      <td>53067</td>\n",
       "      <td>21.4</td>\n",
       "      <td>0.184172</td>\n",
       "      <td>0.252350</td>\n",
       "      <td>0.292602</td>\n",
       "      <td>0.179484</td>\n",
       "      <td>0.091392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>2011</td>\n",
       "      <td>35</td>\n",
       "      <td>0.626042</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>31776</td>\n",
       "      <td>0.27</td>\n",
       "      <td>11.9</td>\n",
       "      <td>52033</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.089917</td>\n",
       "      <td>0.316640</td>\n",
       "      <td>0.254980</td>\n",
       "      <td>0.205277</td>\n",
       "      <td>0.133185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>2012</td>\n",
       "      <td>35</td>\n",
       "      <td>0.626042</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>33253</td>\n",
       "      <td>0.27</td>\n",
       "      <td>11.9</td>\n",
       "      <td>52700</td>\n",
       "      <td>7.9</td>\n",
       "      <td>0.087464</td>\n",
       "      <td>0.312187</td>\n",
       "      <td>0.258295</td>\n",
       "      <td>0.207282</td>\n",
       "      <td>0.134772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>2013</td>\n",
       "      <td>35</td>\n",
       "      <td>0.626042</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>34084</td>\n",
       "      <td>0.27</td>\n",
       "      <td>12.3</td>\n",
       "      <td>52511</td>\n",
       "      <td>8.7</td>\n",
       "      <td>0.086112</td>\n",
       "      <td>0.307729</td>\n",
       "      <td>0.258061</td>\n",
       "      <td>0.210161</td>\n",
       "      <td>0.137937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>2014</td>\n",
       "      <td>35</td>\n",
       "      <td>0.626042</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>34580</td>\n",
       "      <td>0.27</td>\n",
       "      <td>12.0</td>\n",
       "      <td>54153</td>\n",
       "      <td>6.1</td>\n",
       "      <td>0.083576</td>\n",
       "      <td>0.305799</td>\n",
       "      <td>0.258603</td>\n",
       "      <td>0.212294</td>\n",
       "      <td>0.139728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>2011</td>\n",
       "      <td>34</td>\n",
       "      <td>8.382993</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>23944</td>\n",
       "      <td>0.28</td>\n",
       "      <td>11.6</td>\n",
       "      <td>61877</td>\n",
       "      <td>14.3</td>\n",
       "      <td>0.134065</td>\n",
       "      <td>0.256356</td>\n",
       "      <td>0.266047</td>\n",
       "      <td>0.201592</td>\n",
       "      <td>0.141939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>2012</td>\n",
       "      <td>34</td>\n",
       "      <td>8.382993</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>23952</td>\n",
       "      <td>0.28</td>\n",
       "      <td>11.8</td>\n",
       "      <td>61782</td>\n",
       "      <td>14.2</td>\n",
       "      <td>0.130504</td>\n",
       "      <td>0.252465</td>\n",
       "      <td>0.270246</td>\n",
       "      <td>0.202661</td>\n",
       "      <td>0.144124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>2013</td>\n",
       "      <td>34</td>\n",
       "      <td>8.382993</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>23606</td>\n",
       "      <td>0.28</td>\n",
       "      <td>11.7</td>\n",
       "      <td>62745</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.125496</td>\n",
       "      <td>0.251583</td>\n",
       "      <td>0.270847</td>\n",
       "      <td>0.205210</td>\n",
       "      <td>0.146863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>2014</td>\n",
       "      <td>34</td>\n",
       "      <td>8.382993</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>23688</td>\n",
       "      <td>0.28</td>\n",
       "      <td>11.8</td>\n",
       "      <td>64923</td>\n",
       "      <td>12.4</td>\n",
       "      <td>0.121138</td>\n",
       "      <td>0.250080</td>\n",
       "      <td>0.271114</td>\n",
       "      <td>0.207390</td>\n",
       "      <td>0.150277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>2011</td>\n",
       "      <td>36</td>\n",
       "      <td>5.771337</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>33659</td>\n",
       "      <td>0.06</td>\n",
       "      <td>13.1</td>\n",
       "      <td>50401</td>\n",
       "      <td>10.3</td>\n",
       "      <td>0.101934</td>\n",
       "      <td>0.336491</td>\n",
       "      <td>0.301222</td>\n",
       "      <td>0.172603</td>\n",
       "      <td>0.087750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>2012</td>\n",
       "      <td>36</td>\n",
       "      <td>5.771337</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>34159</td>\n",
       "      <td>0.06</td>\n",
       "      <td>13.2</td>\n",
       "      <td>51063</td>\n",
       "      <td>10.4</td>\n",
       "      <td>0.098449</td>\n",
       "      <td>0.331277</td>\n",
       "      <td>0.306291</td>\n",
       "      <td>0.174702</td>\n",
       "      <td>0.089281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>2013</td>\n",
       "      <td>36</td>\n",
       "      <td>5.771337</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>33823</td>\n",
       "      <td>0.06</td>\n",
       "      <td>13.5</td>\n",
       "      <td>51474</td>\n",
       "      <td>10.6</td>\n",
       "      <td>0.095845</td>\n",
       "      <td>0.328345</td>\n",
       "      <td>0.307582</td>\n",
       "      <td>0.177467</td>\n",
       "      <td>0.090761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>2014</td>\n",
       "      <td>36</td>\n",
       "      <td>5.771337</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>33562</td>\n",
       "      <td>0.06</td>\n",
       "      <td>13.2</td>\n",
       "      <td>52632</td>\n",
       "      <td>8.6</td>\n",
       "      <td>0.092493</td>\n",
       "      <td>0.323815</td>\n",
       "      <td>0.309515</td>\n",
       "      <td>0.181003</td>\n",
       "      <td>0.093175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>2011</td>\n",
       "      <td>37</td>\n",
       "      <td>0.586107</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>30024</td>\n",
       "      <td>0.02</td>\n",
       "      <td>11.3</td>\n",
       "      <td>56044</td>\n",
       "      <td>17.3</td>\n",
       "      <td>0.081287</td>\n",
       "      <td>0.304649</td>\n",
       "      <td>0.371959</td>\n",
       "      <td>0.160454</td>\n",
       "      <td>0.081651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>2012</td>\n",
       "      <td>37</td>\n",
       "      <td>0.586107</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>30778</td>\n",
       "      <td>0.02</td>\n",
       "      <td>11.9</td>\n",
       "      <td>55104</td>\n",
       "      <td>17.3</td>\n",
       "      <td>0.079190</td>\n",
       "      <td>0.305455</td>\n",
       "      <td>0.372747</td>\n",
       "      <td>0.161713</td>\n",
       "      <td>0.080896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>2013</td>\n",
       "      <td>37</td>\n",
       "      <td>0.586107</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>30008</td>\n",
       "      <td>0.02</td>\n",
       "      <td>10.9</td>\n",
       "      <td>58424</td>\n",
       "      <td>15.8</td>\n",
       "      <td>0.076491</td>\n",
       "      <td>0.299698</td>\n",
       "      <td>0.377063</td>\n",
       "      <td>0.164787</td>\n",
       "      <td>0.081962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>2014</td>\n",
       "      <td>37</td>\n",
       "      <td>0.586107</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>30552</td>\n",
       "      <td>0.02</td>\n",
       "      <td>11.2</td>\n",
       "      <td>58291</td>\n",
       "      <td>14.2</td>\n",
       "      <td>0.077056</td>\n",
       "      <td>0.294103</td>\n",
       "      <td>0.377617</td>\n",
       "      <td>0.167980</td>\n",
       "      <td>0.083244</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>152 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     YEAR  STATE_SHORT    POP_MIL  SUSPEND  INTERLOCK_1ST  INTERLOCK_REPEAT  \\\n",
       "0    2011            1   4.858979        1              0                 2   \n",
       "1    2012            1   4.858979        1              0                 2   \n",
       "2    2013            1   4.858979        1              0                 2   \n",
       "3    2014            1   4.858979        1              0                 2   \n",
       "4    2011            0   0.738432        1              0                 2   \n",
       "5    2012            0   0.738432        1              0                 2   \n",
       "6    2013            0   0.738432        1              0                 2   \n",
       "7    2014            0   0.738432        1              0                 2   \n",
       "8    2011            3   6.828065        1              0                 2   \n",
       "9    2012            3   6.828065        1              0                 2   \n",
       "10   2013            3   6.828065        1              0                 2   \n",
       "11   2014            3   6.828065        1              0                 2   \n",
       "12   2011            2   2.978204        1              0                 2   \n",
       "13   2012            2   2.978204        1              0                 2   \n",
       "14   2013            2   2.978204        1              0                 2   \n",
       "15   2014            2   2.978204        1              0                 2   \n",
       "16   2011            4  39.144818        1              0                 2   \n",
       "17   2012            4  39.144818        1              0                 2   \n",
       "18   2013            4  39.144818        1              0                 2   \n",
       "19   2014            4  39.144818        1              0                 2   \n",
       "20   2011            5   5.456574        1              0                 2   \n",
       "21   2012            5   5.456574        1              0                 2   \n",
       "22   2013            5   5.456574        1              0                 2   \n",
       "23   2014            5   5.456574        1              0                 2   \n",
       "24   2011            6   3.590886        1              0                 2   \n",
       "25   2012            6   3.590886        1              0                 2   \n",
       "26   2013            6   3.590886        1              0                 2   \n",
       "27   2014            6   3.590886        1              0                 2   \n",
       "28   2011            7   0.945934        1              0                 2   \n",
       "29   2012            7   0.945934        1              0                 2   \n",
       "..    ...          ...        ...      ...            ...               ...   \n",
       "122  2013           30   4.028977        1              0                 2   \n",
       "123  2014           30   4.028977        1              0                 2   \n",
       "124  2011           31  12.802503        0              0                 2   \n",
       "125  2012           31  12.802503        0              0                 2   \n",
       "126  2013           31  12.802503        0              0                 2   \n",
       "127  2014           31  12.802503        0              0                 2   \n",
       "128  2011           32   6.600299        0              0                 2   \n",
       "129  2012           32   6.600299        0              0                 2   \n",
       "130  2013           32   6.600299        0              0                 2   \n",
       "131  2014           32   6.600299        0              0                 2   \n",
       "132  2011           33  27.469114        1              0                 2   \n",
       "133  2012           33  27.469114        1              0                 2   \n",
       "134  2013           33  27.469114        1              0                 2   \n",
       "135  2014           33  27.469114        1              0                 2   \n",
       "136  2011           35   0.626042        1              0                 2   \n",
       "137  2012           35   0.626042        1              0                 2   \n",
       "138  2013           35   0.626042        1              0                 2   \n",
       "139  2014           35   0.626042        1              0                 2   \n",
       "140  2011           34   8.382993        1              0                 2   \n",
       "141  2012           34   8.382993        1              0                 2   \n",
       "142  2013           34   8.382993        1              0                 2   \n",
       "143  2014           34   8.382993        1              0                 2   \n",
       "144  2011           36   5.771337        1              0                 2   \n",
       "145  2012           36   5.771337        1              0                 2   \n",
       "146  2013           36   5.771337        1              0                 2   \n",
       "147  2014           36   5.771337        1              0                 2   \n",
       "148  2011           37   0.586107        1              0                 2   \n",
       "149  2012           37   0.586107        1              0                 2   \n",
       "150  2013           37   0.586107        1              0                 2   \n",
       "151  2014           37   0.586107        1              0                 2   \n",
       "\n",
       "     GALLONS_ALCOHOL_PER_CAP_21  BEER_TAX  PERCENT_POVERTY  MEDIAN_INCOME  \\\n",
       "0                         22331      1.05             19.1          41427   \n",
       "1                         22656      1.05             19.0          41610   \n",
       "2                         22491      1.05             18.9          42882   \n",
       "3                         22481      1.05             19.2          42917   \n",
       "4                         32713      1.07             10.8          65699   \n",
       "5                         32236      1.07             10.8          66503   \n",
       "6                         31277      1.07             10.1          70058   \n",
       "7                         31696      1.07             11.4          70898   \n",
       "8                         27228      0.16             19.0          46710   \n",
       "9                         27627      0.16             18.7          47796   \n",
       "10                        26677      0.16             18.6          48504   \n",
       "11                        26819      0.16             18.2          50036   \n",
       "12                        19519      0.24             19.3          38889   \n",
       "13                        20435      0.24             19.6          40151   \n",
       "14                        20398      0.24             19.4          40605   \n",
       "15                        20203      0.24             18.7          41335   \n",
       "16                        25718      0.20             16.6          57275   \n",
       "17                        26742      0.20             17.0          58322   \n",
       "18                        26373      0.20             16.8          60185   \n",
       "19                        26200      0.20             16.4          61927   \n",
       "20                        30797      0.08             13.4          55530   \n",
       "21                        31076      0.08             13.6          56880   \n",
       "22                        31606      0.08             12.9          58942   \n",
       "23                        31067      0.08             12.1          61324   \n",
       "24                        26710      0.24             10.8          65822   \n",
       "25                        27104      0.24             10.6          67275   \n",
       "26                        26925      0.24             10.7          67262   \n",
       "27                        26800      0.24             10.8          70007   \n",
       "28                        40172      0.16             12.6          58159   \n",
       "29                        40456      0.16             12.7          58326   \n",
       "..                          ...       ...              ...            ...   \n",
       "122                       29684      0.08             16.5          50228   \n",
       "123                       30044      0.08             16.4          51088   \n",
       "124                       25977      0.08             13.7          50221   \n",
       "125                       26390      0.08             13.7          51225   \n",
       "126                       26238      0.08             13.7          52005   \n",
       "127                       26305      0.08             13.6          53224   \n",
       "128                       23006      1.29             18.4          41691   \n",
       "129                       22535      1.29             18.0          42743   \n",
       "130                       22440      1.29             17.8          44268   \n",
       "131                       22627      1.29             18.2          44357   \n",
       "132                       26060      0.19             18.5          49390   \n",
       "133                       26133      0.19             17.9          50747   \n",
       "134                       25757      0.19             17.5          51714   \n",
       "135                       25532      0.19             17.2          53067   \n",
       "136                       31776      0.27             11.9          52033   \n",
       "137                       33253      0.27             11.9          52700   \n",
       "138                       34084      0.27             12.3          52511   \n",
       "139                       34580      0.27             12.0          54153   \n",
       "140                       23944      0.28             11.6          61877   \n",
       "141                       23952      0.28             11.8          61782   \n",
       "142                       23606      0.28             11.7          62745   \n",
       "143                       23688      0.28             11.8          64923   \n",
       "144                       33659      0.06             13.1          50401   \n",
       "145                       34159      0.06             13.2          51063   \n",
       "146                       33823      0.06             13.5          51474   \n",
       "147                       33562      0.06             13.2          52632   \n",
       "148                       30024      0.02             11.3          56044   \n",
       "149                       30778      0.02             11.9          55104   \n",
       "150                       30008      0.02             10.9          58424   \n",
       "151                       30552      0.02             11.2          58291   \n",
       "\n",
       "     PERCENT_UNINSURE  LESS_HS_P      HS_P  SOME_C_P  BACHELORS_P  GRAD_PROF_P  \n",
       "0                16.6   0.180897  0.314334  0.285068     0.139643     0.080058  \n",
       "1                15.8   0.174023  0.313100  0.290229     0.141521     0.081127  \n",
       "2                15.9   0.168852  0.310562  0.294274     0.143547     0.082766  \n",
       "3                14.2   0.162953  0.310687  0.295833     0.144587     0.085940  \n",
       "4                21.7   0.086375  0.272442  0.369075     0.176662     0.095446  \n",
       "5                22.3   0.084130  0.270973  0.370134     0.177505     0.097258  \n",
       "6                20.8   0.083634  0.273077  0.368287     0.177079     0.097924  \n",
       "7                19.0   0.081900  0.275051  0.366203     0.178704     0.098143  \n",
       "8                19.6   0.148176  0.247291  0.340564     0.168360     0.095609  \n",
       "9                20.4   0.145577  0.243979  0.344151     0.169160     0.097133  \n",
       "10               20.0   0.143056  0.245064  0.343135     0.170197     0.098547  \n",
       "11               16.1   0.141056  0.245072  0.342895     0.171268     0.099709  \n",
       "12               20.1   0.173465  0.352003  0.278698     0.130271     0.065563  \n",
       "13               19.4   0.166937  0.351238  0.283841     0.131480     0.066503  \n",
       "14               18.8   0.162692  0.350798  0.285475     0.132791     0.068245  \n",
       "15               13.8   0.157028  0.349982  0.286530     0.135028     0.071433  \n",
       "16               20.2   0.191818  0.211169  0.294672     0.192582     0.109759  \n",
       "17               20.0   0.189801  0.206846  0.298819     0.193536     0.110998  \n",
       "18               19.4   0.187580  0.207157  0.298534     0.194375     0.112353  \n",
       "19               14.1   0.185113  0.207242  0.297625     0.195872     0.114148  \n",
       "20               17.0   0.103172  0.229340  0.304557     0.232747     0.130185  \n",
       "21               16.7   0.100773  0.223595  0.308869     0.234469     0.132294  \n",
       "22               16.0   0.098276  0.221388  0.310048     0.235905     0.134382  \n",
       "23               11.7   0.096208  0.219880  0.309300     0.237353     0.137259  \n",
       "24               10.1   0.114309  0.281284  0.247303     0.201377     0.155727  \n",
       "25               10.5   0.110414  0.278551  0.249469     0.203261     0.158304  \n",
       "26               10.9   0.108196  0.277593  0.249642     0.203835     0.160734  \n",
       "27                8.0   0.104664  0.276060  0.249281     0.206331     0.163664  \n",
       "28               11.2   0.126456  0.317028  0.276797     0.166855     0.112864  \n",
       "29               10.3   0.123231  0.316354  0.275192     0.170918     0.114305  \n",
       "..                ...        ...       ...       ...          ...          ...  \n",
       "122              17.2   0.106105  0.245972  0.350890     0.187199     0.109834  \n",
       "123              11.6   0.105186  0.245435  0.348683     0.188916     0.111780  \n",
       "124              12.0   0.121028  0.375537  0.236739     0.164546     0.102150  \n",
       "125              11.7   0.117085  0.372147  0.240308     0.166197     0.104263  \n",
       "126              11.6   0.113376  0.370489  0.240716     0.168503     0.106917  \n",
       "127              10.2   0.110304  0.367517  0.241189     0.171392     0.109598  \n",
       "128              17.0   0.168184  0.332755  0.268751     0.148954     0.081356  \n",
       "129              16.2   0.161234  0.329632  0.274200     0.151694     0.083239  \n",
       "130              16.2   0.156058  0.330730  0.274774     0.153056     0.085382  \n",
       "131              14.1   0.150539  0.330769  0.274813     0.156002     0.087877  \n",
       "132              25.7   0.195739  0.256603  0.287076     0.174431     0.086151  \n",
       "133              25.2   0.192273  0.252877  0.292256     0.175141     0.087453  \n",
       "134              24.8   0.188320  0.253148  0.291995     0.177269     0.089268  \n",
       "135              21.4   0.184172  0.252350  0.292602     0.179484     0.091392  \n",
       "136               8.0   0.089917  0.316640  0.254980     0.205277     0.133185  \n",
       "137               7.9   0.087464  0.312187  0.258295     0.207282     0.134772  \n",
       "138               8.7   0.086112  0.307729  0.258061     0.210161     0.137937  \n",
       "139               6.1   0.083576  0.305799  0.258603     0.212294     0.139728  \n",
       "140              14.3   0.134065  0.256356  0.266047     0.201592     0.141939  \n",
       "141              14.2   0.130504  0.252465  0.270246     0.202661     0.144124  \n",
       "142              14.0   0.125496  0.251583  0.270847     0.205210     0.146863  \n",
       "143              12.4   0.121138  0.250080  0.271114     0.207390     0.150277  \n",
       "144              10.3   0.101934  0.336491  0.301222     0.172603     0.087750  \n",
       "145              10.4   0.098449  0.331277  0.306291     0.174702     0.089281  \n",
       "146              10.6   0.095845  0.328345  0.307582     0.177467     0.090761  \n",
       "147               8.6   0.092493  0.323815  0.309515     0.181003     0.093175  \n",
       "148              17.3   0.081287  0.304649  0.371959     0.160454     0.081651  \n",
       "149              17.3   0.079190  0.305455  0.372747     0.161713     0.080896  \n",
       "150              15.8   0.076491  0.299698  0.377063     0.164787     0.081962  \n",
       "151              14.2   0.077056  0.294103  0.377617     0.167980     0.083244  \n",
       "\n",
       "[152 rows x 16 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(features, targets, train_size=0.8, random_state=200) #52"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestRegressor(bootstrap=True, criterion='mse', max_depth=None,\n",
       "           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=10000, n_jobs=1, oob_score=True, random_state=200,\n",
       "           verbose=0, warm_start=False)"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rf = RandomForestRegressor(n_estimators=10000, oob_score=True, random_state=200) #52\n",
    "rf.fit(X_train, y_train)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Out-of-bag R-2 score estimate:  0.69\n",
      "Test data R-2 score: 0.773\n",
      "Test data Spearman correlation: 0.927\n",
      "Test data Pearson correlation: 0.916\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import r2_score\n",
    "from scipy.stats import spearmanr, pearsonr\n",
    "predicted_train = rf.predict(X_train)\n",
    "predicted_test = rf.predict(X_test)\n",
    "test_score = r2_score(y_test, predicted_test)\n",
    "spearman = spearmanr(y_test, predicted_test)\n",
    "pearson = pearsonr(y_test, predicted_test)\n",
    "\n",
    "\n",
    "print(f'Out-of-bag R-2 score estimate: {rf.oob_score_:>5.3}')\n",
    "print(f'Test data R-2 score: {test_score:>5.3}')\n",
    "print(f'Test data Spearman correlation: {spearman[0]:.3}')\n",
    "print(f'Test data Pearson correlation: {pearson[0]:.3}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ziW6/I4kNx1N72ZWZDst0QbLZO5eo6m9F5BGazeJpdmfuCekPzxiTCcFFC0lsMIbGPSYT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\nG2NMP2JJ3xhj+hFL+sYY04/8P04SNSHnDBaFAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f736b4f1c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(y_test, predicted_test, \"o\", markersize = 10, alpha = 0.5)\n",
    "plt.ylabel('RF pred. alcohol-involved accidents per mil.')\n",
    "plt.xlabel('Obs. alcohol-involved accidents per mill.')\n",
    "plt.plot([0, 80], [0, 80], color='red', linestyle=':', linewidth=2)\n",
    "\n",
    "plt.savefig('rf_obs_pred_test.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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KozosVPVVmVYtfR94X0Ruxp2Z/ACgyUD1Ki2jg2zboSEcZ/maOiprm7EdB6/H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\nCsoZFEVRFJQzKIqiKIA/ABnfUd6PXhjoAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f736b44a588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(y_train, predicted_train, \"o\", markersize = 10, alpha = 0.5)\n",
    "plt.ylabel('RF pred. alcohol-involved accidents per mil.')\n",
    "plt.xlabel('Obs. alcohol-involved accidents per mill.')\n",
    "plt.plot([0, 100], [0, 100], color='red', linestyle=':', linewidth=2)\n",
    "\n",
    "plt.savefig('rf_obs_pred_train.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#define rmse\n",
    "def rmse(predictions, targets):\n",
    "    return np.sqrt(((predictions - targets) ** 2).mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.9203651575757288"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rmse(predicted_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.8039412205657701"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rmse(predicted_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature ranking:\n",
      "1. feature 11 (0.287167)\n",
      "2. feature 9 (0.182564)\n",
      "3. feature 2 (0.097665)\n",
      "4. feature 12 (0.074040)\n",
      "5. feature 15 (0.072951)\n",
      "6. feature 13 (0.049123)\n",
      "7. feature 14 (0.044082)\n",
      "8. feature 6 (0.043884)\n",
      "9. feature 10 (0.038214)\n",
      "10. feature 8 (0.031325)\n",
      "11. feature 1 (0.029320)\n",
      "12. feature 7 (0.026464)\n",
      "13. feature 5 (0.011630)\n",
      "14. feature 0 (0.007657)\n",
      "15. feature 3 (0.003914)\n",
      "16. feature 4 (0.000000)\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f736c04af28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "importances = rf.feature_importances_\n",
    "std = np.std([tree.feature_importances_ for tree in rf.estimators_],\n",
    "             axis=0)\n",
    "indices = np.argsort(importances)[::-1]\n",
    "\n",
    "# Print the feature ranking\n",
    "print(\"Feature ranking:\")\n",
    "\n",
    "for f in range(X_train.shape[1]):\n",
    "    print(\"%d. feature %d (%f)\" % (f + 1, indices[f], importances[indices[f]]))\n",
    "\n",
    "# Plot the feature importances of the forest\n",
    "plt.figure()\n",
    "plt.title(\"Feature importances\")\n",
    "plt.bar(range(X_train.shape[1]), importances[indices],\n",
    "       color=\"r\", yerr=std[indices], align=\"center\")\n",
    "plt.xticks(range(X_train.shape[1]), indices)\n",
    "plt.xlim([-1, X_train.shape[1]])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['YEAR', 'STATE_SHORT', 'POP_MIL', 'SUSPEND', 'INTERLOCK_1ST',\n",
       "       'INTERLOCK_REPEAT', 'GALLONS_ALCOHOL_PER_CAP_21', 'BEER_TAX',\n",
       "       'PERCENT_POVERTY', 'MEDIAN_INCOME', 'PERCENT_UNINSURE', 'LESS_HS_P',\n",
       "       'HS_P', 'SOME_C_P', 'BACHELORS_P', 'GRAD_PROF_P'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.28716716,  0.18256353,  0.09766523,  0.07404006,  0.07295146,\n",
       "        0.04912283,  0.04408186,  0.04388381,  0.03821388,  0.03132475,\n",
       "        0.02932047,  0.02646401,  0.01163011,  0.0076567 ,  0.00391415,  0.        ])"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "importances[indices]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(range(0, 16),\n",
       " array([ 9, 11,  2, 15, 12, 13, 14, 10,  6,  7,  1,  8,  5,  0,  3,  4]))"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "range(X_train.shape[1]), indices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['MEDIAN_INCOME', 'LESS_HS_P', 'POP_MIL', 'GRAD_PROF_P', 'HS_P',\n",
       "       'SOME_C_P', 'BACHELORS_P', 'PERCENT_UNINSURE',\n",
       "       'GALLONS_ALCOHOL_PER_CAP_21', 'BEER_TAX', 'STATE_SHORT',\n",
       "       'PERCENT_POVERTY', 'INTERLOCK_REPEAT', 'YEAR', 'SUSPEND',\n",
       "       'INTERLOCK_1ST'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features.columns[indices]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Multiple regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>         <td>ACH_MIL</td>     <th>  R-squared:         </th> <td>   0.496</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th> <td>   0.429</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th> <td>   7.451</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>             <td>Sun, 21 Jan 2018</td> <th>  Prob (F-statistic):</th> <td>1.28e-10</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                 <td>18:48:40</td>     <th>  Log-Likelihood:    </th> <td> -447.66</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>      <td>   121</td>      <th>  AIC:               </th> <td>   925.3</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>          <td>   106</td>      <th>  BIC:               </th> <td>   967.3</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>              <td>    14</td>      <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "               <td></td>                 <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th> <th>[95.0% Conf. Int.]</th> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>YEAR</th>                       <td>    2.0399</td> <td>    0.964</td> <td>    2.116</td> <td> 0.037</td> <td>    0.129     3.951</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>STATE_SHORT</th>                <td>    0.1556</td> <td>    0.099</td> <td>    1.564</td> <td> 0.121</td> <td>   -0.042     0.353</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>POP_MIL</th>                    <td>   -1.0440</td> <td>    0.225</td> <td>   -4.642</td> <td> 0.000</td> <td>   -1.490    -0.598</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>SUSPEND</th>                    <td>  -12.2971</td> <td>    3.519</td> <td>   -3.495</td> <td> 0.001</td> <td>  -19.273    -5.321</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>INTERLOCK_1ST</th>              <td>-1.202e-09</td> <td> 5.71e-10</td> <td>   -2.107</td> <td> 0.038</td> <td>-2.33e-09 -7.08e-11</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>INTERLOCK_REPEAT</th>           <td>    3.4216</td> <td>    3.147</td> <td>    1.087</td> <td> 0.279</td> <td>   -2.818     9.661</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>GALLONS_ALCOHOL_PER_CAP_21</th> <td>    0.0004</td> <td>    0.000</td> <td>    1.486</td> <td> 0.140</td> <td>   -0.000     0.001</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>BEER_TAX</th>                   <td>   -6.9784</td> <td>    3.662</td> <td>   -1.906</td> <td> 0.059</td> <td>  -14.238     0.281</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>PERCENT_POVERTY</th>            <td>   -1.6963</td> <td>    1.265</td> <td>   -1.341</td> <td> 0.183</td> <td>   -4.204     0.812</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>MEDIAN_INCOME</th>              <td>   -0.0003</td> <td>    0.000</td> <td>   -0.880</td> <td> 0.381</td> <td>   -0.001     0.000</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>PERCENT_UNINSURE</th>           <td>    1.6191</td> <td>    0.330</td> <td>    4.904</td> <td> 0.000</td> <td>    0.964     2.274</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>LESS_HS_P</th>                  <td>-3969.1171</td> <td> 1919.737</td> <td>   -2.068</td> <td> 0.041</td> <td>-7775.183  -163.051</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>HS_P</th>                       <td>-4023.7569</td> <td> 1933.394</td> <td>   -2.081</td> <td> 0.040</td> <td>-7856.899  -190.615</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>SOME_C_P</th>                   <td>-4118.0165</td> <td> 1933.015</td> <td>   -2.130</td> <td> 0.035</td> <td>-7950.407  -285.626</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>BACHELORS_P</th>                <td>-3955.9117</td> <td> 1934.026</td> <td>   -2.045</td> <td> 0.043</td> <td>-7790.305  -121.518</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>GRAD_PROF_P</th>                <td>-4230.6115</td> <td> 1927.396</td> <td>   -2.195</td> <td> 0.030</td> <td>-8051.862  -409.361</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td>23.721</td> <th>  Durbin-Watson:     </th> <td>   2.059</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th> <td> 0.000</td> <th>  Jarque-Bera (JB):  </th> <td>  34.279</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>          <td> 0.978</td> <th>  Prob(JB):          </th> <td>3.60e-08</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>      <td> 4.724</td> <th>  Cond. No.          </th> <td>1.44e+20</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                            OLS Regression Results                            \n",
       "==============================================================================\n",
       "Dep. Variable:                ACH_MIL   R-squared:                       0.496\n",
       "Model:                            OLS   Adj. R-squared:                  0.429\n",
       "Method:                 Least Squares   F-statistic:                     7.451\n",
       "Date:                Sun, 21 Jan 2018   Prob (F-statistic):           1.28e-10\n",
       "Time:                        18:48:40   Log-Likelihood:                -447.66\n",
       "No. Observations:                 121   AIC:                             925.3\n",
       "Df Residuals:                     106   BIC:                             967.3\n",
       "Df Model:                          14                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "==============================================================================================\n",
       "                                 coef    std err          t      P>|t|      [95.0% Conf. Int.]\n",
       "----------------------------------------------------------------------------------------------\n",
       "YEAR                           2.0399      0.964      2.116      0.037         0.129     3.951\n",
       "STATE_SHORT                    0.1556      0.099      1.564      0.121        -0.042     0.353\n",
       "POP_MIL                       -1.0440      0.225     -4.642      0.000        -1.490    -0.598\n",
       "SUSPEND                      -12.2971      3.519     -3.495      0.001       -19.273    -5.321\n",
       "INTERLOCK_1ST              -1.202e-09   5.71e-10     -2.107      0.038     -2.33e-09 -7.08e-11\n",
       "INTERLOCK_REPEAT               3.4216      3.147      1.087      0.279        -2.818     9.661\n",
       "GALLONS_ALCOHOL_PER_CAP_21     0.0004      0.000      1.486      0.140        -0.000     0.001\n",
       "BEER_TAX                      -6.9784      3.662     -1.906      0.059       -14.238     0.281\n",
       "PERCENT_POVERTY               -1.6963      1.265     -1.341      0.183        -4.204     0.812\n",
       "MEDIAN_INCOME                 -0.0003      0.000     -0.880      0.381        -0.001     0.000\n",
       "PERCENT_UNINSURE               1.6191      0.330      4.904      0.000         0.964     2.274\n",
       "LESS_HS_P                  -3969.1171   1919.737     -2.068      0.041     -7775.183  -163.051\n",
       "HS_P                       -4023.7569   1933.394     -2.081      0.040     -7856.899  -190.615\n",
       "SOME_C_P                   -4118.0165   1933.015     -2.130      0.035     -7950.407  -285.626\n",
       "BACHELORS_P                -3955.9117   1934.026     -2.045      0.043     -7790.305  -121.518\n",
       "GRAD_PROF_P                -4230.6115   1927.396     -2.195      0.030     -8051.862  -409.361\n",
       "==============================================================================\n",
       "Omnibus:                       23.721   Durbin-Watson:                   2.059\n",
       "Prob(Omnibus):                  0.000   Jarque-Bera (JB):               34.279\n",
       "Skew:                           0.978   Prob(JB):                     3.60e-08\n",
       "Kurtosis:                       4.724   Cond. No.                     1.44e+20\n",
       "==============================================================================\n",
       "\n",
       "Warnings:\n",
       "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "[2] The smallest eigenvalue is 2.08e-29. This might indicate that there are\n",
       "strong multicollinearity problems or that the design matrix is singular.\n",
       "\"\"\""
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = X_train\n",
    "y = y_train\n",
    "model = sm.OLS(y, X).fit()\n",
    "mr_predictions_train = model.predict(X)\n",
    "mr_predictions_test = model.predict(X_test)\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11.948340708282453"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rmse(mr_predictions_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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zeoC60pduGBvuaDKVl6R/CvBrYCrOhdx7gYdTGZQxiRZ2NBajum71hJ8QDPiZ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\n9dYj+OknEApR9/SLLL/zPmI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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f736b351710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(y_test, mr_predictions_test, \"o\", markersize = 10, alpha = 0.5)\n",
    "plt.ylabel('LR pred. alcohol-involved accidents per mil.')\n",
    "plt.xlabel('Obs. alcohol-involved accidents per mill.')\n",
    "plt.plot([0, 80], [0, 80], color='red', linestyle=':', linewidth=2)\n",
    "\n",
    "plt.savefig('lr_obs_pred_test.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Regression Tree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean squared error: 143.777\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/rlrognstad/anaconda3/lib/python3.6/site-packages/sklearn/metrics/scorer.py:90: DeprecationWarning: Scoring method mean_squared_error was renamed to neg_mean_squared_error in version 0.18 and will be removed in 0.20.\n",
      "  sample_weight=sample_weight)\n",
      "/home/rlrognstad/anaconda3/lib/python3.6/site-packages/sklearn/metrics/scorer.py:90: DeprecationWarning: Scoring method mean_squared_error was renamed to neg_mean_squared_error in version 0.18 and will be removed in 0.20.\n",
      "  sample_weight=sample_weight)\n",
      "/home/rlrognstad/anaconda3/lib/python3.6/site-packages/sklearn/metrics/scorer.py:90: DeprecationWarning: Scoring method mean_squared_error was renamed to neg_mean_squared_error in version 0.18 and will be removed in 0.20.\n",
      "  sample_weight=sample_weight)\n",
      "/home/rlrognstad/anaconda3/lib/python3.6/site-packages/sklearn/metrics/scorer.py:90: DeprecationWarning: Scoring method mean_squared_error was renamed to neg_mean_squared_error in version 0.18 and will be removed in 0.20.\n",
      "  sample_weight=sample_weight)\n",
      "/home/rlrognstad/anaconda3/lib/python3.6/site-packages/sklearn/metrics/scorer.py:90: DeprecationWarning: Scoring method mean_squared_error was renamed to neg_mean_squared_error in version 0.18 and will be removed in 0.20.\n",
      "  sample_weight=sample_weight)\n"
     ]
    }
   ],
   "source": [
    "regression_tree = tree.DecisionTreeRegressor(\n",
    " min_samples_split=30, min_samples_leaf=10,\n",
    "  random_state=121)\n",
    "regression_tree.fit(X_train,y_train)\n",
    "score = np.mean(cross_val_score(regression_tree, X_train, y_train,\n",
    " scoring='mean_squared_error', cv=crossvalidation,\n",
    "  n_jobs=1))\n",
    "print('Mean squared error: %.3f' % abs(score))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "rt_pred_train = regression_tree.predict(X_train)\n",
    "rt_pred_test = regression_tree.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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K0oYjUb6fswhy8lk5aizVg8pZNXIcCxuhqrqBmOPw5bxK1h9dSvmg/NXbRWOx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\nxBp9Y4wZQKzRN8aYAcQafWOMGUD+H6pEIS9TAhzmAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f736b300c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(y_test, rt_pred_test, \"o\", markersize = 10, alpha = 0.5)\n",
    "plt.ylabel('RT pred. alcohol-involved accidents per mil.')\n",
    "plt.xlabel('Obs. alcohol-involved accidents per mill.')\n",
    "plt.plot([0, 80], [0, 80], color='red', linestyle=':', linewidth=2)\n",
    "\n",
    "plt.savefig('rt_obs_pred_test.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7.9092602398722676"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rmse(rt_pred_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dot_data = tree.export_graphviz(regression_tree, out_file='tree2.dot', feature_names = X.columns, filled = True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#use http://webgraphviz.com/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dot_data = tree.export_graphviz(regression_tree, out_file=None, feature_names = X.columns, filled = True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "ExecutableNotFound",
     "evalue": "failed to execute ['dot', '-Tsvg'], make sure the Graphviz executables are on your systems' PATH",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m/home/rlrognstad/anaconda3/lib/python3.6/site-packages/graphviz/backend.py\u001b[0m in \u001b[0;36mpipe\u001b[0;34m(engine, format, data, quiet)\u001b[0m\n\u001b[1;32m    153\u001b[0m             \u001b[0mstdout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msubprocess\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPIPE\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstderr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msubprocess\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPIPE\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 154\u001b[0;31m             startupinfo=STARTUPINFO)\n\u001b[0m\u001b[1;32m    155\u001b[0m     \u001b[0;32mexcept\u001b[0m \u001b[0mOSError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/rlrognstad/anaconda3/lib/python3.6/subprocess.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, args, bufsize, executable, stdin, stdout, stderr, preexec_fn, close_fds, shell, cwd, env, universal_newlines, startupinfo, creationflags, restore_signals, start_new_session, pass_fds, encoding, errors)\u001b[0m\n\u001b[1;32m    706\u001b[0m                                 \u001b[0merrread\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrwrite\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 707\u001b[0;31m                                 restore_signals, start_new_session)\n\u001b[0m\u001b[1;32m    708\u001b[0m         \u001b[0;32mexcept\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/rlrognstad/anaconda3/lib/python3.6/subprocess.py\u001b[0m in \u001b[0;36m_execute_child\u001b[0;34m(self, args, executable, preexec_fn, close_fds, pass_fds, cwd, env, startupinfo, creationflags, shell, p2cread, p2cwrite, c2pread, c2pwrite, errread, errwrite, restore_signals, start_new_session)\u001b[0m\n\u001b[1;32m   1325\u001b[0m                                 \u001b[0merr_msg\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;34m': '\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mrepr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0morig_executable\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1326\u001b[0;31m                     \u001b[0;32mraise\u001b[0m \u001b[0mchild_exception_type\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0merrno_num\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merr_msg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1327\u001b[0m                 \u001b[0;32mraise\u001b[0m \u001b[0mchild_exception_type\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0merr_msg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'dot'",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mExecutableNotFound\u001b[0m                        Traceback (most recent call last)",
      "\u001b[0;32m/home/rlrognstad/anaconda3/lib/python3.6/site-packages/IPython/core/formatters.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    309\u001b[0m             \u001b[0mmethod\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_real_method\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprint_method\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    310\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mmethod\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 311\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    312\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    313\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/rlrognstad/anaconda3/lib/python3.6/site-packages/graphviz/files.py\u001b[0m in \u001b[0;36m_repr_svg_\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    104\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    105\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_repr_svg_\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 106\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpipe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'svg'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdecode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_encoding\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    107\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    108\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mpipe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mformat\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/rlrognstad/anaconda3/lib/python3.6/site-packages/graphviz/files.py\u001b[0m in \u001b[0;36mpipe\u001b[0;34m(self, format)\u001b[0m\n\u001b[1;32m    123\u001b[0m         \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtext_type\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msource\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mencode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_encoding\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    124\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 125\u001b[0;31m         \u001b[0mouts\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbackend\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpipe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mformat\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    126\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    127\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mouts\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/rlrognstad/anaconda3/lib/python3.6/site-packages/graphviz/backend.py\u001b[0m in \u001b[0;36mpipe\u001b[0;34m(engine, format, data, quiet)\u001b[0m\n\u001b[1;32m    155\u001b[0m     \u001b[0;32mexcept\u001b[0m \u001b[0mOSError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    156\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merrno\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0merrno\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mENOENT\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 157\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mExecutableNotFound\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    158\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m  \u001b[0;31m# pragma: no cover\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    159\u001b[0m             \u001b[0;32mraise\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mExecutableNotFound\u001b[0m: failed to execute ['dot', '-Tsvg'], make sure the Graphviz executables are on your systems' PATH"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<graphviz.files.Source at 0x7f736b281b38>"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "graph = graphviz.Source(dot_data)\n",
    "graph"
   ]
  }
 ],
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