statisical.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3153, 8)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df= pd.read_csv('2008_all_states.csv')\n",
    "df.head()\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>state</th>\n",
       "      <th>county</th>\n",
       "      <th>total_votes</th>\n",
       "      <th>dem_votes</th>\n",
       "      <th>rep_votes</th>\n",
       "      <th>other_votes</th>\n",
       "      <th>dem_share</th>\n",
       "      <th>east_west</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AK</td>\n",
       "      <td>State House District 8, Denali-University</td>\n",
       "      <td>10320</td>\n",
       "      <td>4995</td>\n",
       "      <td>4983</td>\n",
       "      <td>342</td>\n",
       "      <td>50.06</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AK</td>\n",
       "      <td>State House District 37, Bristol Bay-Aleuti</td>\n",
       "      <td>4665</td>\n",
       "      <td>1868</td>\n",
       "      <td>2661</td>\n",
       "      <td>136</td>\n",
       "      <td>41.24</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AK</td>\n",
       "      <td>State House District 12, Richardson-Glenn H</td>\n",
       "      <td>7589</td>\n",
       "      <td>1914</td>\n",
       "      <td>5467</td>\n",
       "      <td>208</td>\n",
       "      <td>25.93</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AK</td>\n",
       "      <td>State House District 13, Greater Palmer</td>\n",
       "      <td>11526</td>\n",
       "      <td>2800</td>\n",
       "      <td>8432</td>\n",
       "      <td>294</td>\n",
       "      <td>24.93</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AK</td>\n",
       "      <td>State House District 14, Greater Wasilla</td>\n",
       "      <td>10456</td>\n",
       "      <td>2132</td>\n",
       "      <td>8108</td>\n",
       "      <td>216</td>\n",
       "      <td>20.82</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>MN</td>\n",
       "      <td>Lake of the Woods County</td>\n",
       "      <td>2313</td>\n",
       "      <td>971</td>\n",
       "      <td>1278</td>\n",
       "      <td>64</td>\n",
       "      <td>43.18</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>WA</td>\n",
       "      <td>Whatcom County</td>\n",
       "      <td>100339</td>\n",
       "      <td>58236</td>\n",
       "      <td>40205</td>\n",
       "      <td>1898</td>\n",
       "      <td>59.16</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>MT</td>\n",
       "      <td>Valley County</td>\n",
       "      <td>3911</td>\n",
       "      <td>1645</td>\n",
       "      <td>2121</td>\n",
       "      <td>145</td>\n",
       "      <td>43.68</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>MT</td>\n",
       "      <td>Flathead County</td>\n",
       "      <td>43714</td>\n",
       "      <td>16138</td>\n",
       "      <td>25559</td>\n",
       "      <td>2017</td>\n",
       "      <td>38.70</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>ID</td>\n",
       "      <td>Boundary County</td>\n",
       "      <td>4733</td>\n",
       "      <td>1484</td>\n",
       "      <td>3078</td>\n",
       "      <td>171</td>\n",
       "      <td>32.53</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>MT</td>\n",
       "      <td>Phillips County</td>\n",
       "      <td>2123</td>\n",
       "      <td>638</td>\n",
       "      <td>1423</td>\n",
       "      <td>62</td>\n",
       "      <td>30.95</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>ND</td>\n",
       "      <td>Rolette County</td>\n",
       "      <td>4534</td>\n",
       "      <td>3403</td>\n",
       "      <td>1045</td>\n",
       "      <td>86</td>\n",
       "      <td>76.51</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>MT</td>\n",
       "      <td>Lincoln County</td>\n",
       "      <td>9227</td>\n",
       "      <td>3025</td>\n",
       "      <td>5704</td>\n",
       "      <td>498</td>\n",
       "      <td>34.65</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>ND</td>\n",
       "      <td>Bottineau County</td>\n",
       "      <td>3516</td>\n",
       "      <td>1387</td>\n",
       "      <td>2059</td>\n",
       "      <td>70</td>\n",
       "      <td>40.25</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>MT</td>\n",
       "      <td>Glacier County</td>\n",
       "      <td>4970</td>\n",
       "      <td>3423</td>\n",
       "      <td>1451</td>\n",
       "      <td>96</td>\n",
       "      <td>70.23</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>ND</td>\n",
       "      <td>Pembina County</td>\n",
       "      <td>3307</td>\n",
       "      <td>1494</td>\n",
       "      <td>1722</td>\n",
       "      <td>91</td>\n",
       "      <td>46.46</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>MN</td>\n",
       "      <td>Kittson County</td>\n",
       "      <td>2568</td>\n",
       "      <td>1492</td>\n",
       "      <td>1016</td>\n",
       "      <td>60</td>\n",
       "      <td>59.49</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>ND</td>\n",
       "      <td>Towner County</td>\n",
       "      <td>1197</td>\n",
       "      <td>621</td>\n",
       "      <td>536</td>\n",
       "      <td>40</td>\n",
       "      <td>53.67</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>ND</td>\n",
       "      <td>Cavalier County</td>\n",
       "      <td>2130</td>\n",
       "      <td>930</td>\n",
       "      <td>1128</td>\n",
       "      <td>72</td>\n",
       "      <td>45.19</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>WA</td>\n",
       "      <td>Okanogan County</td>\n",
       "      <td>16870</td>\n",
       "      <td>7613</td>\n",
       "      <td>8798</td>\n",
       "      <td>459</td>\n",
       "      <td>46.39</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>WA</td>\n",
       "      <td>Stevens County</td>\n",
       "      <td>22341</td>\n",
       "      <td>8499</td>\n",
       "      <td>13132</td>\n",
       "      <td>710</td>\n",
       "      <td>39.29</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>WA</td>\n",
       "      <td>Pend Oreille County</td>\n",
       "      <td>6552</td>\n",
       "      <td>2562</td>\n",
       "      <td>3717</td>\n",
       "      <td>273</td>\n",
       "      <td>40.80</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>WA</td>\n",
       "      <td>Ferry County</td>\n",
       "      <td>3501</td>\n",
       "      <td>1467</td>\n",
       "      <td>1916</td>\n",
       "      <td>118</td>\n",
       "      <td>43.36</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>MN</td>\n",
       "      <td>Roseau County</td>\n",
       "      <td>7700</td>\n",
       "      <td>3097</td>\n",
       "      <td>4438</td>\n",
       "      <td>165</td>\n",
       "      <td>41.10</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>ID</td>\n",
       "      <td>Bonner County</td>\n",
       "      <td>19547</td>\n",
       "      <td>7840</td>\n",
       "      <td>11145</td>\n",
       "      <td>562</td>\n",
       "      <td>41.30</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>MN</td>\n",
       "      <td>Koochiching County</td>\n",
       "      <td>6802</td>\n",
       "      <td>3649</td>\n",
       "      <td>2962</td>\n",
       "      <td>191</td>\n",
       "      <td>55.20</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>MN</td>\n",
       "      <td>Saint Louis County</td>\n",
       "      <td>118814</td>\n",
       "      <td>77351</td>\n",
       "      <td>38742</td>\n",
       "      <td>2721</td>\n",
       "      <td>66.63</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>MI</td>\n",
       "      <td>Keweenaw County</td>\n",
       "      <td>1410</td>\n",
       "      <td>610</td>\n",
       "      <td>756</td>\n",
       "      <td>44</td>\n",
       "      <td>44.65</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>ID</td>\n",
       "      <td>Shoshone County</td>\n",
       "      <td>5666</td>\n",
       "      <td>2521</td>\n",
       "      <td>2953</td>\n",
       "      <td>192</td>\n",
       "      <td>46.05</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>ID</td>\n",
       "      <td>Kootenai County</td>\n",
       "      <td>61932</td>\n",
       "      <td>22120</td>\n",
       "      <td>38387</td>\n",
       "      <td>1425</td>\n",
       "      <td>36.56</td>\n",
       "      <td>west</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2325</th>\n",
       "      <td>SC</td>\n",
       "      <td>Pickens County</td>\n",
       "      <td>45128</td>\n",
       "      <td>11691</td>\n",
       "      <td>32552</td>\n",
       "      <td>885</td>\n",
       "      <td>26.43</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2334</th>\n",
       "      <td>AL</td>\n",
       "      <td>Lauderdale County</td>\n",
       "      <td>38104</td>\n",
       "      <td>13329</td>\n",
       "      <td>24068</td>\n",
       "      <td>707</td>\n",
       "      <td>35.64</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2336</th>\n",
       "      <td>GA</td>\n",
       "      <td>Rabun County</td>\n",
       "      <td>7599</td>\n",
       "      <td>2001</td>\n",
       "      <td>5487</td>\n",
       "      <td>111</td>\n",
       "      <td>26.70</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2337</th>\n",
       "      <td>AL</td>\n",
       "      <td>Limestone County</td>\n",
       "      <td>33551</td>\n",
       "      <td>9536</td>\n",
       "      <td>23598</td>\n",
       "      <td>417</td>\n",
       "      <td>28.77</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2338</th>\n",
       "      <td>MS</td>\n",
       "      <td>Alcorn County</td>\n",
       "      <td>15182</td>\n",
       "      <td>4130</td>\n",
       "      <td>10805</td>\n",
       "      <td>247</td>\n",
       "      <td>27.65</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2339</th>\n",
       "      <td>MS</td>\n",
       "      <td>Tishomingo County</td>\n",
       "      <td>8419</td>\n",
       "      <td>1962</td>\n",
       "      <td>6249</td>\n",
       "      <td>208</td>\n",
       "      <td>23.89</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2340</th>\n",
       "      <td>MS</td>\n",
       "      <td>Tippah County</td>\n",
       "      <td>9725</td>\n",
       "      <td>2623</td>\n",
       "      <td>6937</td>\n",
       "      <td>165</td>\n",
       "      <td>27.44</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2341</th>\n",
       "      <td>MS</td>\n",
       "      <td>DeSoto County</td>\n",
       "      <td>64323</td>\n",
       "      <td>19627</td>\n",
       "      <td>44222</td>\n",
       "      <td>474</td>\n",
       "      <td>30.74</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2342</th>\n",
       "      <td>MS</td>\n",
       "      <td>Benton County</td>\n",
       "      <td>4638</td>\n",
       "      <td>2227</td>\n",
       "      <td>2329</td>\n",
       "      <td>82</td>\n",
       "      <td>48.88</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2344</th>\n",
       "      <td>GA</td>\n",
       "      <td>Towns County</td>\n",
       "      <td>5739</td>\n",
       "      <td>1391</td>\n",
       "      <td>4292</td>\n",
       "      <td>56</td>\n",
       "      <td>24.44</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2345</th>\n",
       "      <td>AL</td>\n",
       "      <td>Madison County</td>\n",
       "      <td>152899</td>\n",
       "      <td>64117</td>\n",
       "      <td>86965</td>\n",
       "      <td>1817</td>\n",
       "      <td>42.41</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2346</th>\n",
       "      <td>AL</td>\n",
       "      <td>Jackson County</td>\n",
       "      <td>20874</td>\n",
       "      <td>6374</td>\n",
       "      <td>14083</td>\n",
       "      <td>417</td>\n",
       "      <td>31.12</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2347</th>\n",
       "      <td>GA</td>\n",
       "      <td>Murray County</td>\n",
       "      <td>11382</td>\n",
       "      <td>3026</td>\n",
       "      <td>8180</td>\n",
       "      <td>176</td>\n",
       "      <td>27.01</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2348</th>\n",
       "      <td>GA</td>\n",
       "      <td>Fannin County</td>\n",
       "      <td>10584</td>\n",
       "      <td>2611</td>\n",
       "      <td>7807</td>\n",
       "      <td>166</td>\n",
       "      <td>25.08</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2349</th>\n",
       "      <td>GA</td>\n",
       "      <td>Whitfield County</td>\n",
       "      <td>27677</td>\n",
       "      <td>8167</td>\n",
       "      <td>19230</td>\n",
       "      <td>280</td>\n",
       "      <td>29.80</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2361</th>\n",
       "      <td>AL</td>\n",
       "      <td>Colbert County</td>\n",
       "      <td>24843</td>\n",
       "      <td>9703</td>\n",
       "      <td>14739</td>\n",
       "      <td>401</td>\n",
       "      <td>39.74</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2661</th>\n",
       "      <td>LA</td>\n",
       "      <td>Caddo Parish</td>\n",
       "      <td>108660</td>\n",
       "      <td>55536</td>\n",
       "      <td>52228</td>\n",
       "      <td>896</td>\n",
       "      <td>51.53</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2662</th>\n",
       "      <td>LA</td>\n",
       "      <td>Bossier Parish</td>\n",
       "      <td>45835</td>\n",
       "      <td>12703</td>\n",
       "      <td>32713</td>\n",
       "      <td>419</td>\n",
       "      <td>27.97</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2663</th>\n",
       "      <td>LA</td>\n",
       "      <td>Webster Parish</td>\n",
       "      <td>18270</td>\n",
       "      <td>6610</td>\n",
       "      <td>11417</td>\n",
       "      <td>243</td>\n",
       "      <td>36.67</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2664</th>\n",
       "      <td>LA</td>\n",
       "      <td>Claiborne Parish</td>\n",
       "      <td>6841</td>\n",
       "      <td>3025</td>\n",
       "      <td>3750</td>\n",
       "      <td>66</td>\n",
       "      <td>44.65</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2665</th>\n",
       "      <td>LA</td>\n",
       "      <td>Union Parish</td>\n",
       "      <td>10868</td>\n",
       "      <td>3103</td>\n",
       "      <td>7619</td>\n",
       "      <td>146</td>\n",
       "      <td>28.94</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2950</th>\n",
       "      <td>FL</td>\n",
       "      <td>Jackson County</td>\n",
       "      <td>21565</td>\n",
       "      <td>7671</td>\n",
       "      <td>13717</td>\n",
       "      <td>177</td>\n",
       "      <td>35.86</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2952</th>\n",
       "      <td>FL</td>\n",
       "      <td>Escambia County</td>\n",
       "      <td>154447</td>\n",
       "      <td>61572</td>\n",
       "      <td>91411</td>\n",
       "      <td>1464</td>\n",
       "      <td>40.25</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2953</th>\n",
       "      <td>FL</td>\n",
       "      <td>Santa Rosa County</td>\n",
       "      <td>76185</td>\n",
       "      <td>19470</td>\n",
       "      <td>55972</td>\n",
       "      <td>743</td>\n",
       "      <td>25.81</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2956</th>\n",
       "      <td>FL</td>\n",
       "      <td>Okaloosa County</td>\n",
       "      <td>95529</td>\n",
       "      <td>25872</td>\n",
       "      <td>68789</td>\n",
       "      <td>868</td>\n",
       "      <td>27.33</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2958</th>\n",
       "      <td>FL</td>\n",
       "      <td>Holmes County</td>\n",
       "      <td>8589</td>\n",
       "      <td>1446</td>\n",
       "      <td>7033</td>\n",
       "      <td>110</td>\n",
       "      <td>17.06</td>\n",
       "      <td>east</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3136</th>\n",
       "      <td>HI</td>\n",
       "      <td>Kauai County</td>\n",
       "      <td>27224</td>\n",
       "      <td>20416</td>\n",
       "      <td>6245</td>\n",
       "      <td>563</td>\n",
       "      <td>76.58</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3137</th>\n",
       "      <td>HI</td>\n",
       "      <td>Honolulu County</td>\n",
       "      <td>306813</td>\n",
       "      <td>214239</td>\n",
       "      <td>88164</td>\n",
       "      <td>4410</td>\n",
       "      <td>70.84</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3138</th>\n",
       "      <td>HI</td>\n",
       "      <td>Maui County</td>\n",
       "      <td>51789</td>\n",
       "      <td>39727</td>\n",
       "      <td>11154</td>\n",
       "      <td>908</td>\n",
       "      <td>78.08</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3139</th>\n",
       "      <td>HI</td>\n",
       "      <td>Hawaii County</td>\n",
       "      <td>66916</td>\n",
       "      <td>50819</td>\n",
       "      <td>14866</td>\n",
       "      <td>1231</td>\n",
       "      <td>77.36</td>\n",
       "      <td>west</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>248 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     state                                       county  total_votes  \\\n",
       "0       AK    State House District 8, Denali-University        10320   \n",
       "1       AK  State House District 37, Bristol Bay-Aleuti         4665   \n",
       "2       AK  State House District 12, Richardson-Glenn H         7589   \n",
       "3       AK      State House District 13, Greater Palmer        11526   \n",
       "4       AK     State House District 14, Greater Wasilla        10456   \n",
       "40      MN                     Lake of the Woods County         2313   \n",
       "41      WA                               Whatcom County       100339   \n",
       "42      MT                                Valley County         3911   \n",
       "43      MT                              Flathead County        43714   \n",
       "44      ID                              Boundary County         4733   \n",
       "45      MT                              Phillips County         2123   \n",
       "46      ND                               Rolette County         4534   \n",
       "47      MT                               Lincoln County         9227   \n",
       "48      ND                             Bottineau County         3516   \n",
       "49      MT                               Glacier County         4970   \n",
       "53      ND                               Pembina County         3307   \n",
       "54      MN                               Kittson County         2568   \n",
       "55      ND                                Towner County         1197   \n",
       "56      ND                              Cavalier County         2130   \n",
       "57      WA                              Okanogan County        16870   \n",
       "58      WA                               Stevens County        22341   \n",
       "59      WA                          Pend Oreille County         6552   \n",
       "60      WA                                 Ferry County         3501   \n",
       "66      MN                                Roseau County         7700   \n",
       "68      ID                                Bonner County        19547   \n",
       "71      MN                           Koochiching County         6802   \n",
       "75      MN                           Saint Louis County       118814   \n",
       "92      MI                              Keweenaw County         1410   \n",
       "104     ID                              Shoshone County         5666   \n",
       "108     ID                              Kootenai County        61932   \n",
       "...    ...                                          ...          ...   \n",
       "2325    SC                               Pickens County        45128   \n",
       "2334    AL                            Lauderdale County        38104   \n",
       "2336    GA                                 Rabun County         7599   \n",
       "2337    AL                             Limestone County        33551   \n",
       "2338    MS                                Alcorn County        15182   \n",
       "2339    MS                            Tishomingo County         8419   \n",
       "2340    MS                                Tippah County         9725   \n",
       "2341    MS                                DeSoto County        64323   \n",
       "2342    MS                                Benton County         4638   \n",
       "2344    GA                                 Towns County         5739   \n",
       "2345    AL                               Madison County       152899   \n",
       "2346    AL                               Jackson County        20874   \n",
       "2347    GA                                Murray County        11382   \n",
       "2348    GA                                Fannin County        10584   \n",
       "2349    GA                             Whitfield County        27677   \n",
       "2361    AL                               Colbert County        24843   \n",
       "2661    LA                                 Caddo Parish       108660   \n",
       "2662    LA                               Bossier Parish        45835   \n",
       "2663    LA                               Webster Parish        18270   \n",
       "2664    LA                             Claiborne Parish         6841   \n",
       "2665    LA                                 Union Parish        10868   \n",
       "2950    FL                               Jackson County        21565   \n",
       "2952    FL                              Escambia County       154447   \n",
       "2953    FL                            Santa Rosa County        76185   \n",
       "2956    FL                              Okaloosa County        95529   \n",
       "2958    FL                                Holmes County         8589   \n",
       "3136    HI                                 Kauai County        27224   \n",
       "3137    HI                              Honolulu County       306813   \n",
       "3138    HI                                  Maui County        51789   \n",
       "3139    HI                                Hawaii County        66916   \n",
       "\n",
       "      dem_votes  rep_votes  other_votes  dem_share east_west  \n",
       "0          4995       4983          342      50.06      west  \n",
       "1          1868       2661          136      41.24      west  \n",
       "2          1914       5467          208      25.93      west  \n",
       "3          2800       8432          294      24.93      west  \n",
       "4          2132       8108          216      20.82      west  \n",
       "40          971       1278           64      43.18      west  \n",
       "41        58236      40205         1898      59.16      west  \n",
       "42         1645       2121          145      43.68      west  \n",
       "43        16138      25559         2017      38.70      west  \n",
       "44         1484       3078          171      32.53      west  \n",
       "45          638       1423           62      30.95      west  \n",
       "46         3403       1045           86      76.51      west  \n",
       "47         3025       5704          498      34.65      west  \n",
       "48         1387       2059           70      40.25      west  \n",
       "49         3423       1451           96      70.23      west  \n",
       "53         1494       1722           91      46.46      west  \n",
       "54         1492       1016           60      59.49      west  \n",
       "55          621        536           40      53.67      west  \n",
       "56          930       1128           72      45.19      west  \n",
       "57         7613       8798          459      46.39      west  \n",
       "58         8499      13132          710      39.29      west  \n",
       "59         2562       3717          273      40.80      west  \n",
       "60         1467       1916          118      43.36      west  \n",
       "66         3097       4438          165      41.10      west  \n",
       "68         7840      11145          562      41.30      west  \n",
       "71         3649       2962          191      55.20      west  \n",
       "75        77351      38742         2721      66.63      west  \n",
       "92          610        756           44      44.65      east  \n",
       "104        2521       2953          192      46.05      west  \n",
       "108       22120      38387         1425      36.56      west  \n",
       "...         ...        ...          ...        ...       ...  \n",
       "2325      11691      32552          885      26.43      east  \n",
       "2334      13329      24068          707      35.64      east  \n",
       "2336       2001       5487          111      26.70      east  \n",
       "2337       9536      23598          417      28.77      east  \n",
       "2338       4130      10805          247      27.65      east  \n",
       "2339       1962       6249          208      23.89      east  \n",
       "2340       2623       6937          165      27.44      east  \n",
       "2341      19627      44222          474      30.74      east  \n",
       "2342       2227       2329           82      48.88      east  \n",
       "2344       1391       4292           56      24.44      east  \n",
       "2345      64117      86965         1817      42.41      east  \n",
       "2346       6374      14083          417      31.12      east  \n",
       "2347       3026       8180          176      27.01      east  \n",
       "2348       2611       7807          166      25.08      east  \n",
       "2349       8167      19230          280      29.80      east  \n",
       "2361       9703      14739          401      39.74      east  \n",
       "2661      55536      52228          896      51.53      west  \n",
       "2662      12703      32713          419      27.97      west  \n",
       "2663       6610      11417          243      36.67      west  \n",
       "2664       3025       3750           66      44.65      west  \n",
       "2665       3103       7619          146      28.94      west  \n",
       "2950       7671      13717          177      35.86      east  \n",
       "2952      61572      91411         1464      40.25      east  \n",
       "2953      19470      55972          743      25.81      east  \n",
       "2956      25872      68789          868      27.33      east  \n",
       "2958       1446       7033          110      17.06      east  \n",
       "3136      20416       6245          563      76.58      west  \n",
       "3137     214239      88164         4410      70.84      west  \n",
       "3138      39727      11154          908      78.08      west  \n",
       "3139      50819      14866         1231      77.36      west  \n",
       "\n",
       "[248 rows x 8 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_group=df.groupby('state')\n",
    "df_group.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([3.094e+03, 4.200e+01, 1.500e+01, 0.000e+00, 0.000e+00, 0.000e+00,\n",
       "        0.000e+00, 1.000e+00, 0.000e+00, 1.000e+00]),\n",
       " array([8.0000000e+00, 2.2959250e+05, 4.5917700e+05, 6.8876150e+05,\n",
       "        9.1834600e+05, 1.1479305e+06, 1.3775150e+06, 1.6070995e+06,\n",
       "        1.8366840e+06, 2.0662685e+06, 2.2958530e+06]),\n",
       " <a list of 10 Patch objects>)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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KO9k3XXk50ODaSO6rS32o6qfAncAnwGfAVlV9OYvPmxNemkQCe3qoMSafZRN0JEVZ8n/h09XJVXmX+xCRwfijoDHA/kB/EfleirqIyBUiUiMiNfX19amqdFnaOZ34SMdWJTDG5J9sgk4dMCrh/Ug6XqaK13GXsgYCmzvZN135RmCQayO5r6728S1gtarWq2or8Cfga6k+oKrer6oTVHVCRUVF2hPRFZ5mmNNRW3/NGJN/sgk67wKVLqusEH8yvjqpTjVwiXt9ATBHVdWVT3GZZ2OASmB+ujbdPnNdG7g2n+9mH58Ax4tIiZv7OQVYmt1p6TmPEGFJsfaa2JyOMSZ/RTJVUNWoiFwNvISfAfawqi4WkVuBGlWtBh4CnhCRWvzRxxS372IRmQUsAaLAVarqAaRq03V5HTBTRG4DFrq26UYf80TkGeA9V74QuL+7J6qr0iUS7L5Pxy6vGWPyT8agA6Cqs4HZSWU3JbxuAi5Ms+80YFo2bbryVezOPkss704fvwB+kWqfoKVLJCiilTCe3adjjMlLtiJBQNIlEoj4adM77Jk6xpg8ZEEnIOluDgX/Eptlrxlj8pEFnYCkG+kAlEiz3adjjMlLFnQC4hEilCboDGCXZa8ZY/KSBZ2AeISJpB3p2NNDjTH5yYJOAFTbstdSB53+NNujDYwxecmCTgBibmWeVI+rBntktTEmf1nQCYDnTmu6kc4Au7xmjMlTFnQCEHOnNV0iQYmlTBtj8pQFnQBECQOkTSToTxONFKMdV8kxxph9mgWdAHiZRjrShBJil412jDF5xoJOALz4SCf9igRgi34aY/KPBZ0AeG3Za+kur7U93sCSCYwxecaCTgCySSQAbNFPY0zesaATgGwSCcAe5GaMyT8WdAIQ085HOm2X1xrV5nSMMfnFgk4A4iOdNCsS2EjHGJOvLOgEIGPKdNucjtqcjjEmv1jQCUAsY/ZaM4CtSmCMyTsWdAKQOZFgF4CtNG2MyTsWdAKQKWW6kCgRonafjjEm72QVdERkkogsF5FaEbk+xfYiEXnabZ8nIqMTtk115ctF5PRMbYrIGNfGCtdmYQ/6GCQiz4jIMhFZKiIndO30dE80w4oEIlBiz9QxxuShjEFHRMLA3cAZQBVwsYhUJVW7DNiiqocAM4Dpbt8qYApwGDAJuEdEwhnanA7MUNVKYItru8t9uH3+E/irqo4FjgSWZntieiJTIgHsXvTTGGPySTYjnWOBWlVdpaotwExgclKdycBj7vUzwCkiIq58pqo2q+pqoNa1l7JNt8/Jrg1cm+d2pw8RKQMmAg8BqGqLqjZkd1p6JtPzdABGyCaWxg7qjcMxxpg9RjZB5wBgXcL7OleWso6qRoGtQHkn+6YrLwcaXBvJfXW1j4OBeuAREVkoIg+KSP8sPm+PeZo56JwZnsdHOoaVsRG9cUjGGLNHyCboSIqy5CfBpKuTq/Lu9BEBjgbuVdWjgEagw3wUgIhcISI1IlJTX1+fqkqXtCUShCV90Dk7/DZCjGrvaz3uzxhj9hbZBJ06YFTC+5HA+nR1RCQCDAQ2d7JvuvKNwCDXRnJf3emjTlXnufJn8INQB6p6v6pOUNUJFRUVKU9CV2RKJAAYLg2cEFpCdexr9jA3Y0zeyCbovAtUuqyyQvxJ++qkOtXAJe71BcAcVVVXPsVlno0BKoH56dp0+8x1beDafL47fajq58A6EfmK2+cUYEkWn7fHMqVMt5kceovVOoIPdUxvHJYxxvS5jEHHzZ9cDbyEn/01S1UXi8itInKOq/YQUC4itcDPcJexVHUxMAv/l/1fgatU1UvXpmvrOuBnrq1y13aX+3D7/D/gSRH5ABgH/FtXT1B3RN1pTXdzaJtJ4XcpIGqX2IwxeSOSuQqo6mxgdlLZTQmvm4AL0+w7DZiWTZuufBV+dltyeXf6WARMSLVPkLJJmQYYKI18M7SIF7wT+JfIfxMSu85mjNm32YoEAYhlkTLd5vjQEr5gCFvplcQ6Y4zpUxZ0ApBNIkGbMnYCtuK0MSY/WNAJQLaJBACl4i/+ud0eXW2MyQMWdAKQbSIBQKkb6WynJNBjMsaYPYEFnQDEH1fdyc2hbQa4kY5dXjPG5AMLOgHIZu21NgPcs3V22OU1Y0wesKATgLZEgnAWiQSl4i6v2UjHGJMHLOgEoCsp06W0JRLYnI4xZt9nQScAXUkkKKaFMJ7N6Rhj8oIFnQB0JWVaxJ/XsTkdY0w+sKATgK4kEoA/r7Nd7fKaMWbfZ0EnAF4XEgnAH+nYzaHGmHxgQScAXR7p2OU1Y0yesKATgGgWj6tOVCo7LZHAGJMXLOgEIEaIEDEk1YO0U/Avr9mcjjFm32dBJwAeoaxHOeAvhWMjHWNMPrCgEwCPcNZJBODP6VgigTEmH1jQCUBXRzqlspNmCmnRcIBHZYwxfc+CTgC6fHktvuinzesYY/ZtFnQC0J05HbDHGxhj9n0WdAIQJdy1y2vY00ONMfkhq6AjIpNEZLmI1IrI9Sm2F4nI0277PBEZnbBtqitfLiKnZ2pTRMa4Nla4Ngu724fbFhaRhSLy5+xPS8/ECHUxkcB/vIHdIGqM2ddlDDoiEgbuBs4AqoCLRaQqqdplwBZVPQSYAUx3+1YBU4DDgEnAPS4IdNbmdGCGqlYCW1zbXe4j4dh+AizN7nTkRncvr9n6a8aYfV02I51jgVpVXaWqLcBMYHJSncnAY+71M8ApIiKufKaqNqvqaqDWtZeyTbfPya4NXJvndrMPRGQk8G3gwexOR254GiKcxaOq29jTQ40x+SKboHMAsC7hfZ0rS1lHVaPAVqC8k33TlZcDDa6N5L662gfAXcA/Q+fDDhG5QkRqRKSmvr6+s6pZ6U7KNNjTQ40x+75sgk6qxVw0yzq5Ku9yHyJyFrBBVRek2N6+sur9qjpBVSdUVFRkqp5Rd24OBUskMMbs+7IJOnXAqIT3I4H16eqISAQYCGzuZN905RuBQa6N5L662seJwDkisgb/8t3JIvJfWXzeHuvqSKeIViJE2WFzOsaYfVw2QeddoNJllRXiT9pXJ9WpBi5xry8A5qiquvIpLvNsDFAJzE/XpttnrmsD1+bz3elDVaeq6khVHe3an6Oq38vyvPSI5xb8zJaIPd7AGJMfIpkqqGpURK4GXgLCwMOqulhEbgVqVLUaeAh4QkRq8UcfU9y+i0VkFrAEiAJXqaoHkKpN1+V1wEwRuQ1Y6NqmO330FY8QkS4EHbBFP40x+SFj0AFQ1dnA7KSymxJeNwEXptl3GjAtmzZd+Spc9llSeZf7SNj+KvBquu251tXLawAD2Mk2G+kYY/ZxtiJBALqaSAB2ec0Ykx8s6ASgOyOdUtlliQTGmH2eBZ0AeNq1RALwbxC1kY4xZl9nQScAHiEiXViRAPxEArs51Bizr7OgE4CupkyDn0hgN4caY/Z1FnQC4BEm0sVEgjLZRQuFNGuEt7wqqr0TAjo6Y4zpO1mlTJuu6V7K9O5FP2+M/pBmCjgn/HYQh2eMMX3Ggk4AYt25vOYeb/BubCwr9QBKaAri0Iwxpk/Z5bUARLuxIkHbg9ye9E4BYCfFNGlBzo/NGGP6kgWdAHRrpOMur70e+2p83y2U5vzYjDGmL1nQCUC0G4kEpe7yGsBpoRoANqsFHWPMvsWCTgC6e3MoQDHNXBR+FbCgY4zZ91jQCYBH1x5XDbufHnpK6D1GyQYANtvlNWPMPsay1wLQnUcbDGE73w+/zJTwXIbIdgC22EjHGLOPsaATgO4kEoRE+WXBowB4Kggxu7xmjNnn2OW1AHQnkSBRWJRBNLKZshwelTHG9D0LOgHozkgn2WDZ3unltZgKd7R+l7WxYT3qxxhjepMFnQBEu7EMTrJytnWaSPCplnO3dy6zY8f1qB9jjOlNFnQC4K+91v3La5B5pLOBwQA06IAe9WOMMb3Jgk4AYoQIoz1qY4hsZ1NnQUcHAbDJ5n2MMXuRrIKOiEwSkeUiUisi16fYXiQiT7vt80RkdMK2qa58uYicnqlNERnj2ljh2izsTh8iMkpE5orIUhFZLCI/6frp6Z4okR4lEgAMZjtbKEXTxK4v1B/pWFq1MWZvkjHoiEgYuBs4A6gCLhaRqqRqlwFbVPUQYAYw3e1bBUwBDgMmAfeISDhDm9OBGapaCWxxbXe5DyAK/JOqHgocD1yV4rhzLqYCQKiLN4cmK5ftRImkfbDbBhd0LK3aGLM3yWakcyxQq6qrVLUFmAlMTqozGXjMvX4GOEVExJXPVNVmVV0N1Lr2Urbp9jnZtYFr89zu9KGqn6nqewCquh1YChyQ3Wnpvqg7pT0e6STdIHpZy7XcHd192r9wl9cSFwVVhXdjX0k7OjLGmL6WTdA5AFiX8L6Ojr+843VUNQpsBco72TddeTnQ4NpI7qurfcS5S3FHAfMyftoeirlT2tOU6SH4QWcTZTRpAa/GjuTN2GHx7W2JBIkjnTdih3Nhyy94Tyt71LcxxgQlm6AjKcqS/y+drk6uyrvTh7+TyADgj8A1qrotRV1E5AoRqRGRmvr6+lRVsua5U9rTRILEkU6t7o9HmE909z05bXM62+hPq4YBWOe2L40d2KO+jTEmKNkEnTpgVML7kcD6dHVEJAIMBDZ3sm+68o3AINdGcl9d7QMRKcAPOE+q6p/SfUBVvV9VJ6jqhIqKinTVshLFDwA9TZkux4+Pm7WU5eoHkfU6NB5gNuggCvAHhA3098vwL7nVauBXEY0xpluyCTrvApUuq6wQf9K+OqlONXCJe30BMEdV1ZVPcZlnY4BKYH66Nt0+c10buDaf704fbr7nIWCpqv462xPSU7H4SKfnKxIAbKaMj2Mj422v13KatIAGSvmS+PG4bd6nLY3ago4xZk+VccFPVY2KyNXAS0AYeFhVF4vIrUCNqlbj/3J/QkRq8UcfU9y+i0VkFrAEP5vsKlX1AFK16bq8DpgpIrcBC13bdLUPEfk68H3gQxFZ5Nr4F1Wd3b1TlZ1cJRL0p4lCWtmsA1imowgRI0aIdTqMkLt0N1Y+YZkeGF+5oC2jbUXMgo4xZs+U1SrT7hf17KSymxJeNwEXptl3GjAtmzZd+Sr87Lbk8i71oapvkHq+J1C5SiQQ2X2vzvLYKI6RZczTKj7RYfSTZgDGhj6BWMeRzhcMYZv2oyzhaaTGGLMnsBUJcszL0eU1gCGyjTWx/ficcr4Rfp8Conyiw+JJBF8RP2lvc0LQGeLmglbq/j3u3xhjcs2ep5NjnrYlEuQi6OxgfmwsAIfKJxwgG1mnFQzXLQCMDflBZwulxFSoZxCTQu/yl9jxrIiN5KjQyh4fw76qtbWVuro6mpqa+vpQ9lnFxcWMHDmSgoKCvj4UswexoJNj8ZFOD1ckAP/yWqv7KxobWsco2cA6HcaBuoECogxnCwPYyWYtZROleIQZH/qYV2LjbaSTQV1dHaWlpYwePRo/58TkkqqyadMm6urqGDNmTF8fjtmD2OW1HMtVyjQQf2x1GY3sx2YOlA3xy2vD2EJIlMGygy1aGk8i2F82cbB81mkG2wYdSJ0O7fHx7c2ampooLy+3gBMQEaG8vNxGkqYDCzo5FnO5C7ma0wE/S00ERskGGihlpe5PhTT4ddjOJsriSQQV0sCX5FNWdBJ0bmi9jB+2/HOPj29vZwEnWHZ+TSoWdHJs90gnB0HHLYXzFTd3c6BsAGCxjma4+PM6bc/daRvpDGMLh8h61mkFTZr6WvoKHckKHRlfv80YY3qLBZ0c+bfZS3n4jdU5uzkUdt8g2pal1hZ0okQYnjDS2ayl8dUIhkkDlaE6lBCrdESHNls1HL+09k7s0B4fo8mNm2++mTvvvLOvD4OGhgbuueeevj4Msw+zoJMj76zaxJxlG3KaMv0lWU8Yj/GhjwEYJbvXhRuWONKhlA06iEFsp0iiHOJWKkh1iW29lhN1yQnvxAJ/0oPZy1jQMUGz7LUcGTWkhA/WNeQ0kaAq9AnvF/0DA8SfjB0ojZTRyDb6Mww30pHt7KSYT3QYw9zoZ4x8RogYK2MH4A4nbo3u5+/HNubZSAeAW15YzJL1KdeC7baq/cv4xdmHdVpn2rRpPP7444waNYqKigrGjx/PypUrueqqq6ivr6chgfwRAAAVZ0lEQVSkpIQHHniAsWPHcumll9KvXz+WLVvG2rVreeSRR3jsscd4++23Oe6443j00UdT9nHvvfeyevVqfvWrXwHw6KOPsmDBAn7729/y61//mocffhiAyy+/nGuuuYbrr7+elStXMm7cOE499VTuuOMO7rjjDmbNmkVzczPnnXcet9xyC42NjXz3u9+lrq4Oz/O48cYbueiii3J6Ds2+yYJOjhw4pIS/fvg5zRF/HiUXIx0gHnDi/cgGPtIxu+d03LzP8tgoDgn5I5wiiVIpddTolzu0t1aHA/Cd8Gs84J3FFzoofqnO9J4FCxYwc+ZMFi5cSDQa5eijj2b8+PFcccUV/P73v6eyspJ58+Zx5ZVXMmfOHAC2bNnCnDlzqK6u5uyzz+bNN9/kwQcf5JhjjmHRokWMGzeuQz8XXHABJ5xwQjzoPP3009xwww0sWLCARx55hHnz5qGqHHfccXzjG9/g9ttv56OPPmLRIn/lqJdffpkVK1Ywf/58VJVzzjmH1157jfr6evbff3/+8pe/ALB169ZeOnNmb2dBJ0dGDe6Hp0qd+qtU5yroJGsLOm2X19rSqj+nnK+xOF7v5NBC7vfOYqv2Z6A0xsvX6nCKaeac8Ns84J3FO7EqJoffCuRY9xaZRiRBeP311znvvPMoKSkB4JxzzqGpqYm33nqLCy/cvdpTc3Nz/PXZZ5+NiHDEEUcwfPhwjjjiCAAOO+ww1qxZkzLoVFRUcPDBB/POO+9QWVnJ8uXLOfHEE/nNb37DeeedR//+/grl559/Pq+//jrnnHNOu/1ffvllXn75ZY466igAduzYwYoVKzjppJO49tprue666zjrrLM46aSTcnuCzD7Lgk6OHFju//Jom7zPxc2hqYxyyQTxRALZfVloWMKI5dTwAu71JvNq7Mh2QWWtDme0fEGVrKGURgs6fSg5pTgWizFo0KD4KCNZUVERAKFQKP667X00Gk25D8BFF13ErFmzGDt2LOeddx4igmb5eFlVZerUqfzoRz/qsG3BggXMnj2bqVOnctppp3HTTTelaMGY9iyRIEcOHOIHndVuziSokc53wq/xk/Af45fV2tKqoX3QGScrGUoDL3vj2+2/RodzkHxOWJTjQsssg62PTJw4kWeffZZdu3axfft2XnjhBUpKShgzZgx/+MMfAP8X/vvvv9/jvs4//3yee+45nnrqqfi8y8SJE3nuuefYuXMnjY2NPPvss5x00kmUlpayffvu79Tpp5/Oww8/zI4dOwD49NNP2bBhA+vXr6ekpITvfe97XHvttbz33ns9Pk6TH2ykkyPDS4spCAurY26kk4NEglS+HPqUL4f+GH/fllYNxOd5AEKifCv8Hn/2jqdFwxSKh6fCJzqcU0ILATg+tJT/iY7ncx3Mfgn7muAdffTRXHTRRYwbN46DDjoofnnqySef5Mc//jG33XYbra2tTJkyhSOPPLJHfQ0ePJiqqiqWLFnCscceG+//0ksvjb+//PLL45fQTjzxRA4//HDOOOMM7rjjDpYuXcoJJ5wAwIABA/iv//ovamtr+fnPf04oFKKgoIB77723R8do8odkO8zOFxMmTNCampou79fqxfjmHa9S37CVFgqpLryBr4ZWB3CE7UU1RGXz4ygh/lB4C8eElse3/c07istaf87jBf/OxPCHfKrlnNj8W/4t8iB/H5nDstgoJrVMj7/fq9zcs4nrpUuXcuihNsoLWo/P880Dc3cwXeq3jxIj+urzQo8/s4gsUNUJmerZ5bUcqigtooVCoOfP08lWRGIMxE8UGEb70cqJoY/oRxOvxPxLbGtjfubaaPkc8G86PVC+4KXY7u9JkxawMtbxptIg3dL6fX7ReknmisaYvZ4FnRwaXlYcfx3ppaADuzPYhiWlPhdLKxNDH/CKNx5PJX6PzkGhLwD/QXGnh97lrdjhbNN+ANwS/QFntvx7/H0mTVpAbaz7K1rv0kKe8k7mv71T2Kr9u92OgeOOO45x48a1+/nwww/7+rDMHuy7zTfy761TerVPCzo5NLxsd0ZRUIkEqQxmO6U00k9aOmw7L/wGn1POs7Gvs1aHU0gLI9gc3356uIZWIrwaG8cXOog/ehNpppA3Y4dn1fdt0e/xrZY7+Y/WC/G06ws8vhb7Kk0U0UqEl7yMI3PTiXnz5rFo0aJ2P21p1cYkWxsbxnw9lGe9k4h1499ud1nQyaFhpbtHOkElEqSyn2xhZMISOYlOD9XwVVnJjNYL+FhHcqBsICS75/GOlhUMpYGXvAk8HD2DKGFKaGJurOM9H8l2ahHPeScylAZ+653Hpa3XdXnU87I3noHsYJRs4IXYCV3at6dsPjNYdn73bHNifuLIBgazWEf3Wr8WdHKor0Y6NxY8wT0Fv0m5TQSui8zkUyqYGzuK0fJFu+0hUU4NL+DV2Die9E7hrNDb/F1oEa9648j0O2N27Fh2UMI9hf/J7ZH7mRcby7da7uTC5pt408t8w2VUQ/wtdjSnhBZyTugt3oodxkYt61Bvm/bjjtbvcnTT73ndy24ElklxcTGbNm2yX4wBaXuIW3FxcebKGduCt7wqmtWSbXuiSQvij7YHP+iMYBNCjL+5ANQb7G8xh9qNdAK6OTSV/WQLdDI6PjG8mJO8D3g99lUOSgo6AKeFanjKOwWAH0X+zJLYQfwldjxL9CAOk7UAxFQQlMT7GWdFv8nBsp5jZDnHRpZzSvg9/uRN5AnvW/x/rdfweugaBiWshpDs3dhXaKCUU8M1jJHPuds7lxe9Y/l+5H/idf7X+yo/bb2SzZRRQhP/Eb2Qr4c+6uzjZmXkyJHU1dVRX596hGh6ru1x1T31YuxYrmy9hivCf+ZfCv47B0eWf1Th+y1TWavDmVP0TwDMix3KpeGXqIl9mbneUVzTS8eSVdARkUnAf+IvH/mgqt6etL0IeBwYD2wCLlLVNW7bVOAywAP+UVVf6qxNERkDzASGAO8B31fVllz2EZTCSIjhbOYLhvTqSCcb/xx5mjdbDo8/JiHR10KLKaORo0IrOCy01n9AXBRejR3JWPmEq1v/kRdjxwH+U0xvKXiUI2Ul8/VQros8FQ9EFbKNH0X+zMTQ+5zZ8u/cFz2L6wqebtfXLi1kJ0WUy3Zejk2gkBYmhj6ghGYqpY4XvBPiQWeLDuBnrT9mqGzlsYLpvB87mH+NXsbbsSq+1sPzUVBQYI9R3gu0apg7ov4NrY96p3FJ5CUOkE19fFR7vre9Q3ku9nVuijxOf2nmxdixvKtjAbgvejaHhVbTQgEnh9+jTBq5M3oRG7Y3tfuPc1AyXl4TkTBwN3AGUAVcLCLJa+JfBmxR1UOAGcB0t28VMAU4DJgE3CMi4QxtTgdmqGolsMW1nes+AtM2ktjTgs4RodX8b+FPOT/8eodtRRLlT4W/YEaBf4PfMNnK4bKaV71x3BW9gBdjx3Fx+G/8JPxHviLr+GnrVVzW+nPCeHwn/FqH9g4NreOc0Ns84k1igw6iRcM8ED2TC5tv4qvNDzKh+V7+vuVf+LN3PCeFPqK/NCMC54TfYr4eyv94RwMwLfp/2Ep//rPgdxwRWs0F4deoYAv3eJODPVlmjzHL+wardQS3Rh4B4K7od/r4iHpXVEPtJvk9FV70juFTLY+Xvegdw6nNv2K259/ouyw2in9o/See9v6Of2z9f+zSQm6PXsxX5BO+HXqbB7wzeco7mTIaGS8rONndLP7qst4Z9Wcz0jkWqFXVVQAiMhOYDCxJqDMZuNm9fgb4nfgLS00GZqpqM7BaRGpde6RqU0SWAicDf+/qPObavTdXfSQdd84dGNrAfO/QXk0kyNaoUPovVdsK1W2+GVrE3d5k3vXG8t3wXP4t8hAicLU+x/ToFB70vs23QjUMk9Q3lP0s8gf+0nIc/9r6Q9ZpBUt1NF+Vlfzf8GyKaOXZ2EnUM5gzwzPj+3w//AqveOP5h9afcVHsVZ7xvsHV4Wc51D05tVhauSzyIrdH/563V26ipDDMhu3NHFRewujy/hRGOv8/lBdTWr0YheEQoZC//tiuVo9oTOlfGCEcEryYsr2pFRFhQJFf1hz12N4UpSgSon9hBBHY1eqxozlK/8IIJYVhVGFHS5SmVo+y4gKKIiFiCtt2tRKNKQP7FVAYCdESjbGtqZWQCGXFESLhEE2tHtuaWimKhCkt8ttvbPFobI7SvyhCf9f+9qYoTVG//eKCEF5MadjVSiymDCwpoCgSpqnVY+uuVsIhYWC/AiIhobHFL+tXEGZgvwIE2NbUyvamKGXFBZT1i+DFlM07W2hujTGopIABRRGaozHqtzejCkNLC+lXEGZ7c5QN25opioSoKC2iMBxi445mNmxvpqy4gOEDi1CFTxt2sWlHC/uVFTNiUDGNzVFWbNjB1p2tHFzRn5GDS1i9sZEFa7egKEcfOJjhZcVUL/qU6vfXs9/AYs47aiR3Rb/DMbKM74dfYZ1W8JB3JieFPuTN2OEsiFXyrdB7XByeQ5Qw78QOZQuljJePGRdayWc6hA91DAIcIas5QOpZo/vxsY5kII0cGvqEAexihY5kjQ5nf9nEl6WOGMLSVZv4YlsTX6oYwCHDBrBlZwsffbqNHc2tVI0YyJih/VmzqZH31zUQCQtHjhzEiIH9WLSugUXrGhheVsQxo4fQrzDMm7Ub+aBuK4eOKOOkyqE07Gzlrx99Tm39Dr5+SDl/N3YYiz5pYFbNOrY238S54TeYGPqQP3gTedSbxAB2cUXkz1SF1nJr6w/4SMfQjyZ+EvkTTRRyV/QCSmjiytZr+FHsBf7sHU9/mrg8Mpu7ohcwueWXfKLDeazgdg6W9bzSMoH/jY3j7NBbFIjHoXzCCDbxt2Vf8N1jRmX3y6QHsgk6BwCJ12TqgOPS1VHVqIhsBcpd+TtJ+7Y9WSxVm+VAg6pGU9TPVR+BEGBAUSQ+0onsgUGnK/4uvIjfeedxhKzi1sij8UtoBeLxrwVPckZ4fsr5oTYHhTZwUfhVnvS+xVAaeKDgTk4N716f6xr9E6t1Pw6Wz+Jlg6SRpwt/yU9br2SmdzIHy3qujjzXrt3/E/4b90Qnc/ED77QrD4eEwnAIRVElngQhAiHxg0mLt3v0WRQJ0erFiCXkERRFQjRH249QC8OhdvuJQFiEaMKOkZAQU23XVkFYaPXaJykkt5WqXrr2PdV2iR09ab/tfLRpC7ad7dd2HNGkeqn2FaHdsYYEYl3I1xgztD8r6xuZ/eHnwGB+X3AXInBlpJqZ7n/v/WjiCFnNA963+b13TsY20xFiaKoLPve/07GsB5LPkwCDSgp44f3d/9kbUlLIUPpzQ/TyeNmpoRoadAA3Ry8F/BvAp0fu55XY0dwe9f9vfn7oNW4peIxboj/gPu9s+tHEHwpv5fDQGnZoPx70vs3E0Pt8I/wBAD8M/5X7vLM5OeyPcETg5PBCnl0xjOaoR1Ek6SFcOZZN0Ek1Z5v8FUpXJ115qv+SdlY/l310ICJXAFe4tztEZHmqelkaCo9vHNSDBvYMC4CzWAukvk10QaYGhsJdG+Eu1gKnpaySbtmNWwHS9L0N2KseFjYU2NjXB7EHyPo8rE16v/vurfZ/98tycFB9IO15SP7cAA+mqOPfylkdL5vhfuAO9wO77866F7iXJ4An4mX3AfdxfruW7wLuoviXGY+/MwdlUymboFMHJI65RgLr09SpE5EIMBDYnGHfVOUbgUEiEnGjncT6ueqjA1W9H7g/1bauEpGabNYf2tfZefDZefDZefDZecjuPp13gUoRGSMihfiBtjqpTjXQtnjWBcAc9W+AqAamiEiRy0qrBOana9PtM9e1gWvz+Vz2kd1pMcYYE4SMIx03f3I18BJ+6vHDqrpYRG4FalS1GngIeMJN4m/GjQBdvVn4k/dR4CpV9QBStem6vA6YKSK3AQtd2+S4D2OMMX3AHm2QYyJyhbtcl9fsPPjsPPjsPPjsPFjQMcYY04ts7TVjjDG9xoJOjojIJBFZLiK1InJ9Xx9PT4jIGhH5UEQWiUiNKxsiIq+IyAr352BXLiLyG/e5PxCRoxPaucTVXyEilySUj3ft17p9pbM+evFzPywiG0Tko4SyPvvcnfXRB+fhZhH51H0nFonImQnbprpjXC4ipyeUp/w34ZJ75rnP+7RL9MElAz3t6s8TkdGZ+gjwHIwSkbkislREFovIT1x53n0fck5V7aeHP/iJCiuBg4FC4H2gqq+PqwefZw0wNKnsV8D17vX1wHT3+kzgRfz7pY4H5rnyIcAq9+dg93qw2zYfOMHt8yJwRmd99OLnnggcDXy0J3zudH300Xm4Gbg2Rd0q930vAsa4fwfhzv5NALOAKe7174Efu9dXAr93r6cAT3fWR8DnYARwtHtdCnzsjiPvvg85P7d9fQD7wo/74ryU8H4qMLWvj6sHn2cNHYPOcmCEez0CWO5e3wdcnFwPuBi4L6H8Plc2AliWUB6vl66PXv7so5N+2fbZ507XRx+dh5tJHXTafdfxs0VPSPdvwv3C3AhEXHm8Xtu+7nXE1ZN0ffTy9+J54NR8/T7k8scur+VGqqWCDkhTd2+gwMsiskD81RoAhqvqZwDuz2GuPN1n76y8LkV5Z330pb783Hva9+pqd1nn4YRLn109D1kvdYW/ZEV5J231CneZ7yhgHvZ96DELOrmRzVJBe5MTVfVo/BW6rxKRiZ3U7eryRPvKueqNz70nnat7gS8B44DPgP9w5bk8D3vcd0ZEBgB/BK5R1W2dVU1Rti9/H7rNgk5uZLNU0F5DVde7PzcAz+Kv2v2FiIwAcH9ucNXTffbOykemKKeTPvpSX37uPeZ7papfqKqnqjHgAXav5N7V8xBf6iqpvF1bkv1SV4ERkQL8gPOkqv7JFdv3oYcs6OTGPrPkjoj0F5HSttf4a3V+RPtliJKXJ/qBy6w5HtjqLgm8BJwmIoPdpZjT8K/dfwZsF5HjXbbOD0i91FFiH32pLz93uj56XdsvQec8/O8E9O1SV4Fxf0cPAUtV9dcJm+z70FN9Pam0r/zgZ5Z8jJ9Zc0NfH08PPsfB+JlC7wOL2z4L/rX1vwEr3J9DXLngPyxvJfAhMCGhrf8L1LqfHyaUT8D/pbUS+B27b1JO2Ucvfvan8C8dteL/r/KyvvzcnfXRB+fhCXcMH+D/8huRUP8Gd4zLcRlYnf2bcN+x+e78/AEocuXF7n2t235wpj4CPAdfx7909QGwyP2cmY/fh1z/2IoExhhjeo1dXjPGGNNrLOgYY4zpNRZ0jDHG9BoLOsYYY3qNBR1jjDG9xoKOMcaYXmNBxxhjTK+xoGOMMabX/P8DALykXSpQwgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ef7c550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.kdeplot(df['dem_votes'],shade=True)\n",
    "plt.hist(df['dem_votes'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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QJUcmLWDn9A+hgVL+6Y0xZuwo5bfWemCxiMwH9uENoriuX501wI3Ac8DVwNOqqiKyBnhYRL6ON+hiMfAC3pnUSTHdPs+4GKtdzMcH6pwbRfhL4CFV/Vm/bdNVtdndT7sKeL1QDF+pkuhp4XDeGdSQSICeWAM9sQYO87bjxaHMMRIuiU3qbqK+4xU6E/M5VP320+y4McaMrkH/pHdnOrcAa4EtwKOquklE7hSRK121+4E6N6jiVuB2t+8m4FG8ARpPAp9R1WyxmC7WbcCtLladi42IvFNEmoBrgO+LSF/9jwKXAJ8oMHz9JyLyGvAaMAX4yhCO0YiK9B4hlEvSHZs2IvEzoUkcmbSQ5il/wbbZ19ATqaOhbf2ItGWMMSOppOtCqvoE8ES/si/mLSfxEkmhfe8C7iolpivfwYmRhPnl6/EuEfYv/zHw4yJtX1qofCxJuAEXXSOUsN5ChAO1y5nXspZ4TzPdFdNHvk1jjBkmNtOFz+LJZhShJzZ1VNo7VP0OshJiatuGUWnPGGOGiyUsnyV6WuiJTiE3Sl8KzgZjHJ78NuqOvEYw2zMqbRpjzHCwhOWzRLJlxO5fFXOgdjlBzbxlBKExxox1lrB8FMp0EckcHZ37V3m6K6ZztGIWDW0bbN5CY0zZsITlo0TS+5pYd8XoJizwzrIq0m1Ude0c9baNMWYoLGH5KN4ziiME+2mrWkJvMM5UG+JujCkTlrB8lEi2kAxXkw1WjHrbGghxsGYZNUffJNJ7ZNTbN8aYU2UJy0dxHwZc5DtQsxxQGtpe9K0PxhhTKktYPglkU1Sk23y5HNgnHammY9Ji6jteRHJZ3/phjDGlsITlk3jyAODPgIt8B2qXE8l0UXN0i6/9MMaYwVjC8smoTsk0gCOTFpEM19jMF8aYMc8Slk/iyRZ6gwl6Q5X+dkSEA7XnU9W9hwp31meMMWORJSyfJJItdFVMGxOPtz9UvYycBJnattHvrhhjTFGWsHwguQwVyVZfRwjmy4TiHJ58DlOOvEqo95jf3THGmIIsYfmgInWQADnf71/lO1CznGAuzfz9/9fvrhhjTEGWsHwwVgZc5OuKz+RYbAaL9zxi8wsaY8YkS1g+iCdbyAYipCK1fnflLQ7ULqf62HZvUlxjjBljSkpYIrJCRLaKSKOI3F5ge1REHnHb14nIvLxtd7jyrSJyxWAxRWS+i7HNxYy48ktE5EURyYjI1f3av9HV3yYiN+aVny8ir7k2viUyBkY4AImeZrpiU8fEgIt8bZOXkgpXsXjPar+7YowxJxk0YYlIEPgO8AFgCfAxEVnSr9pNQLuqLgLuAe52+y4BVgFLgRXAd0UkOEjMu4F7VHUx0O5iA+wBPgE83K9/tcCXgAuBC4AviUiN23wvcDOw2L1WDPbzjjjNEU8doDs29h5PnwuE2THzKmYfeJqKZKvf3THGmLco5QzrAqBRVXeoahpYDazsV2cl8KBbfgx4nzubWQmsVtWUqu4EGl28gjHdPpe6GLiYVwGo6i5VfRXI9Wv7CuApVW1T1XbgKWCFiEwHqlT1OVVV4KG+WH6KpdsI5nrH1P2rfI1zPkpAMyzc+3O/u2KMMW9RSsKaCezNW29yZQXrqGoGOALUDbBvsfI6oMPFKNZWqf2b6ZYH6jcAInKziGwQkQ0dnV2DNHd64m7Ahd9TMhVzNDGX/VMuZtHex5Bcr9/dMcaY40pJWIVutPQfRlasznCVD+S0Y6nqfaq6XFWXV1clBmnu9CR6mslJkJ5o/Yi2czq2zbmWeKqVWa3P+t0VY4w5rpSE1QTMzlufBewvVkdEQsBkoG2AfYuVHwKqXYxibZXavya3PFC/R10i2UJPtAGVoN9dKWp/wyV0xaZ7Q9yNMWaMKCVhrQcWu9F7EbxBFGv61VkD9I3Ouxp42t03WgOscqMI5+MNfHihWEy3zzMuBi7m44P0by1wuYjUuMEWlwNrVbUZOCoiF7l7YzeUEGtkqRJPtozZ+1d9VIJsm3MN0w6vo+rYDr+7Y4wxQAkJy91PugUvMWwBHlXVTSJyp4hc6ardD9SJSCNwK3C723cT8CiwGXgS+IyqZovFdLFuA251sepcbETknSLSBFwDfF9ENrk22oB/xEuC64E7XRnAp4B/xRvssR347RCO0bCJZDoJZ3vGzJRMA9k+6z+RlRCL9zzqd1eMMQaA0OBVQFWfAJ7oV/bFvOUkXiIptO9dwF2lxHTlO/BGEfYvX89bL/Hlb3sAeKBA+QbgnEL7+CHe42a4GKMDLvKlonXsnXY58/c9zitnfJZMKO53l4wxE5zNdDGKEskWFOiOTvW7KyV5c+4qIpljzN3/G7+7YowxlrBGUzzZQjJSRy4Y8bsrJTlUvYz2yjM4Y89qm1/QGOM7S1ijKFEGAy7eQoQ356yi5uibTOl4xe/eGGMmOEtYoySU6Sbae4TuirE3JdNAds/4EOnQJM7Y/VO/u2KMmeAsYY2S+Bh8pEgpMqE4O2deyeyW3xFNHfa7O8aYCcwS1ijpewZWOQxp72/bnGsJaoaFTb/0uyvGmAnMEtYoiSdbSIWrynJ4eOekBbTUXcjiPY8imvW7O8aYCcoS1ihJ9LSU5dlVn21zriWRbGZG65/87ooxZoKyhDUKArk0sfShsrt/la+p4T10RxtsfkFjjG8sYY2CePIAAmPyoY2l0kCYxtlXM+PQn5nUtcfv7hhjJiBLWKOgXEcI9rd99l+RkxCL99r8gsaY0WcJaxQkelroDVaQDlf53ZXT0hNrYO/US1nQ9EuC2R6/u2OMmWAsYY2CRNINuJBCz5QsL9vmrCLa28nc5if97ooxZoKxhDXCRLNUpFrL/nJgn9ba5XRMWmiDL4wxo84S1girSB0koNmym5KpKBG2zbmWuiObqO143e/eGGMmEEtYI+z4M7DGyRkWwM4ZH6E3WMEZe2x+QWPM6LGENcISyRayEiYZqfW7K8MmE57ErhkfYW7zk0TSHX53xxgzQZSUsERkhYhsFZFGEbm9wPaoiDzitq8TkXl52+5w5VtF5IrBYorIfBdjm4sZGagNEfm4iLyc98qJyDK37VnXRt+2hqEdpqGLJ1vojk0FGV9/G2yb81GCuTQLmn7ld1eMMRPEoL9FRSQIfAf4ALAE+JiILOlX7SagXVUXAfcAd7t9lwCrgKXACuC7IhIcJObdwD2quhhod7GLtqGqP1HVZaq6DLge2KWqL+f17eN921W1teQjMxxUT4wQHGc6qs6kteY8b/CF5vzujjFmAijlz/4LgEZV3aGqaWA1sLJfnZXAg275MeB9IiKufLWqplR1J9Do4hWM6fa51MXAxbxqkDbyfQwYMzdWoul2grk0XRXjL2GBN8S9sqeJ6Yf+7HdXjDETQCkJayawN2+9yZUVrKOqGeAIUDfAvsXK64AOF6N/W8XayHctJyesH7jLgV8okOBGVOL4DBfjZIRgP3unvZ+eSC1n7LYh7saYkVdKwir0S15LrDNc5YP2Q0QuBLpVNX+s9cdV9W3Au93r+gIxEJGbRWSDiGzo6OwqVGVIEslmcgToidYPW8yxJBcIs332XzHj4J9IdO/zuzvGmHGulITVBMzOW58F7C9WR0RCwGSgbYB9i5UfAqpdjP5tFWujzyr6nV2p6j73fhR4GO9S5ElU9T5VXa6qy6urEoWqDEk82UJPrB4NhAavXKYaZ1+DIiza+zO/u2KMGedKSVjrgcVu9F4ELzGs6VdnDXCjW74aeFpV1ZWvciP85gOLgReKxXT7PONi4GI+PkgbiEgAuAbvXhiuLCQiU9xyGPgwMHrfdFUt+2dglaK7Yjr7pr6HhXt/QSCb8rs7xphxbNCE5e4X3QKsBbYAj6rqJhG5U0SudNXuB+pEpBG4Fbjd7bsJeBTYDDwJfEZVs8Viuli3Abe6WHUudtE2nEuAJlXdkVcWBdaKyKvAy8A+4F9KPC6nLZw5RjjbNa6+MFzMtjnXEuttZ07L7/zuijFmHCvpWpWqPgE80a/si3nLSbwznEL73gXcVUpMV76DApfuBmnjWeCifmVdwPmF6o+GRLIZYNyfYQG01F1EZ3wui/c8wq6ZH/G7O8aYcWp8fZt1DOl7BtZESFhIgG1zPkp9xyvUHNnid2+MMeOUJawRkuhpIRmpJRuM+t2VUbFj1koygZjN4m6MGTGWsEZIPNkyIe5f9ekNT2bXjA8yb/9vCPd2+t0dY8w4ZAlrBASzPcR6OyZUwgJv8EUol2TBvv6DSI0x5vRZwhoBfTNcdI/TKZmKaZ+8hEOT3+7mF+z/3XJjjDk9lrBGwIlnYI3PKZkG8ubcVVR17WLq4ef97ooxZpyxhDUCEskW0qFKMqHhmzWjXOyZdjnJcA3nvfHPdi/LGDOsLGGNgIk24CJfLhjluXf8b6qO7eA9Gz5NKNPtd5eMMeOEJaxhJrleKlKHJsb3r4porr+Y/7fsa9R1vMYlL37WpmwyxgwLS1jDLJ5sRdBx+wysUu2ddhnr3nYn0w6v4+KX/xbJ9frdJWNMmbOENcwSE2mGi0HsnLWSDUvuYHbrM1z02hfsycTGmNMyfp974ZN4soVMIEYqXO13V8aEN+deRyjTxbI3v0UmmGD90n+A0X2OpjFmnLCENcwSyWbvcqD9Uj5u84L/QjhzjKU7HqA3lODlM//Gjo8x5pRZwhpOmiOebOVA7XK/ezK2iPDKGZ8jnOliyc4fkA5Xsnnhf/W7V8aYMmMJaxhVpA4R0MyEHdI+IBE2LPn/CB+/PBjnzXkf97tXxpgyYglrGNmAi0FIgOff9o+Est0s3/JVekMJds66yu9eGWPKhI0SHEbxZDM5CdETneJ3V8YsDYT48zv+iea6i7jwtS8xu+Upv7tkjCkTlrCGUaKnhe5YA4gd1oHkghH+dN43OVz9dv7i5b9j+sF/97tLxpgyUNJvVhFZISJbRaRRRG4vsD0qIo+47etEZF7etjtc+VYRuWKwmCIy38XY5mJGBmpDROaJSI+IvOxe38uLdb6IvOb2+ZbICA5NUyWePDAhJ7wdimwozrPLv8ORSYt494t/Q33bRr+7ZIwZ4wa9hyUiQeA7wGVAE7BeRNao6ua8ajcB7aq6SERWAXcD14rIEmAVsBSYAfxeRM5w+xSLeTdwj6qudsnnJuDeYm24WNtVdVmB7t8L3Aw8DzwBrAB+W9KROUXR3g5CuWTZ379auOdno9rezhkfYsnOH3Lp+pvZMu8GuipmjGr7/W2fc42v7RtjiivlDOsCoFFVd6hqGlgNrOxXZyXwoFt+DHifO5tZCaxW1ZSq7gQaXbyCMd0+l7oYuJhXDdJGQSIyHahS1edUVYGH8mINu7gbcDHRp2Q6VZlQgjfmXU8mWMGZu39CRbLV7y4ZY8aoUhLWTGBv3nqTKytYR1UzwBGgboB9i5XXAR0uRv+2irUBMF9EXhKRP4rIu/PqNw3SbwBE5GYR2SAiGzo6uwpVGVSipxlF6I5OHdL+E1k6XMWWedejEuSs3T8mmm73u0vGmDGolIRV6Cym/+Nki9UZrvKB2mgG5qjqucCtwMMiUlViv71C1ftUdbmqLq+uGtozrOLJFnqi9WjAvikwFKlILW/M/WtEs5y160f2LC1jzElKSVhNwOy89VnA/mJ1RCQETAbaBti3WPkhoNrF6N9WwTbc5cbDAKq6EdgOnOHqzxqk38MmMYGfgTVcemINbJ37ccLZbs7e9WNCmaGd7RpjxqdSEtZ6YLEbvRfBG0Sxpl+dNcCNbvlq4Gl332gNsMqN8JsPLAZeKBbT7fOMi4GL+fhAbYhIvRsYgogscG3sUNVm4KiIXOTudd2QF2tYhTLHiGSOlf2Ai7Ggq2IGW+d8jGhvB2ft/gnBbNLvLhljxohBE5a7X3QLsBbYAjyqqptE5E4RudJVux+oE5FGvMtyt7t9NwGPApuBJ4HPqGq2WEwX6zbgVherzsUu2gZwCfCqiLyCNxjjv6lqm9v2KeBf8QZ7bGeERggmemzAxXA6mpjLm7M/SkWqlTP3/JRALu13l4wxY4B4JzWmz9kLZ+sPv/q5U9pnxsF/Z3br02w46+/IBmMj1LOJp/bIZhY1/ZzOxHy2zlk1KvcHR2tY+3UXzhmVdowZLSKyUVVHdOZvm5JhGMR1ljgiAAAbFUlEQVSTLSTD1Zashlnb5CXsmPERJnftYFHTL+wBkMZMcJawhkEi2WL3r0bIoZpl7Jp2BbVH32DBvjVgVwSMmbBsDPZpCmaTxNJtHKx+h99dGbcO1F1IMJdiduuz5AIRdk3/gD0A0pgJyBLWaYonDwDYkPYRtn/KuwlmU8w4/BzZYJS9U9/nd5eMMaPMEtZpitszsEaHCHunvp9gLs2MQ38mG4iyv/4/+N0rY8wosoR1mhLJFtKhBL3hSr+7Mv6JsGv6B93lwafJBiIcqLvA714ZY0aJJazTFO+xARejSoQdM1cSzKWZ1/IkDe0bOVy1lLbJS0lG6wbf3xhTtixhnQbJZahIHaSjcpHfXZlQVIJsm3U19R0vUXdkE7MPPsvsg8/SFZvmktcSUpEav7tpjBlmlrBOQ0WqlQA5uu2hjaNOAyFaa99Ja+07ifR2UntkM3Wdm5jT+gfmtP6BYxUzjp95pcNVfnfXGDMMLGGdhkTfM7DskqCv0uEqWqZcRMuUi4ikO6jr3ETdkU3MPfAUcw88RWd8Nm1VS2mrWkJveJLf3TXGDJElrNOQ6GkhG4jY5acxJB2ppnnKxTRPuZho6rBLXpuZ1/Ikc1vW0pmYy+GqpbRXnU0mFPe7u8aYU2AJ6zTEk83e2ZV9iXVMSkXr2F9/CfvrL6Ei2UqtS14Lmn+DNj/BkUkLXPI6y6bVMqYMWMIaKs0RT7bSWnOe3z0xJeiJNbAv1sC++vcQTx6grnMTtUc2sXD/GnLNv+HIpIUcrlrK7hkfJBMa2kM8jTEjyxLWEMXShwlqL932SJHyIkJ3xTS6K6axt+FSEj37XfLaTM3RN5nX/AT769/N7ukr2N9wCdlghd89NsY4lrCG6PgzsGzARfkSoSs+k674TPZMvYxJ3XsJaYo5zb9jzoHf0xusYF/De9g9/YPsr78YDYT97rExE5olrCGKJ1vISZBkdIrfXTHDQYRjiTlsn3MNL559G/VtG5nb/CSzW55iXvNv6YnUsWvmh9kxcyVHKhf73VtjJiRLWEOUSLbQHW1AJeh3V8wwUwnSWncBrXUXsGHJHcw4+O8s2Pcrztz1E87e+SCHJy9lx8yV7J7+QdKRyX5315gJo6TnYYnIChHZKiKNInJ7ge1REXnEbV8nIvPytt3hyreKyBWDxRSR+S7GNhczMlAbInKZiGwUkdfc+6V5sZ51bbzsXg2nfogKUCVuz8CaEDQQZt/U9/Jv532TX773D2w86+8I5Hp55+b/xX98+r1c/NL/YPrBf0NyGb+7asy4N+gZlogEge8AlwFNwHoRWaOqm/Oq3QS0q+oiEVkF3A1cKyJLgFXAUmAG8HsROcPtUyzm3cA9qrpaRL7nYt9brA3gEPARVd0vIucAa4GZeX37uKpuGMKxKSrS20k420OXDbiYUFLRWrbOv56t86+nuvMNFjb9irn7f8Pclt/RHa1n14wPs2PWVXROWuB3V40Zl0o5w7oAaFTVHaqaBlYDK/vVWQk86JYfA94nIuLKV6tqSlV3Ao0uXsGYbp9LXQxczKsGakNVX1LV/a58ExATkWipB2AoEslmAJuSaQLrqDqLjUtu51eXPs2fzr2HtslLOWvXQ3z431Zy+f/7OIv2PEq4t9PvbhozrpRyD2smsDdvvQm4sFgdVc2IyBGgzpU/32/fvrOfQjHrgA5VzRSoX6yNQ3lx/gp4SVVTeWU/EJEs8HPgK6onP2NdRG4GbgaYNmXwWSviyRYUoTs2ddC6ZnzLBcI0TXs/TdPeTyx1iHn7f8OCpl9xwaZ/5LwtX6Np6qXsmHkVB6ZcaPc7jTlNpSSsQtM49P+lX6xOsfJCZ3YD1R+0HyKyFO8y4eV52z+uqvtEpBIvYV0PPHRSENX7gPsAzl44+6SE1l8i2UIyWkfOhjmbPMnoFN6YfyNvzLuB2s7NLGj6FXObn2Be82/pik1l58wr2TnzSo4m5vndVWPKUikJqwmYnbc+C9hfpE6TiISAyUDbIPsWKj8EVItIyJ1l5dcv1gYiMgv4JXCDqm7vC6qq+9z7URF5GO9S5EkJ61TFe1o4mphzumHMeCVC22RvpvgXz/o8M1ufZeG+X7Fk+/2cs/1faK05F0KfhKX/EWI2k7wxpSolYa0HFovIfGAf3iCK6/rVWQPcCDwHXA08raoqImuAh0Xk63iDLhYDL+CdLZ0U0+3zjIux2sV8fJA2qoHfAHeo6p/7OuSSWrWqHhKRMPBh4PencGwKCmW6iWY6abERguPSwj0/G5G4exsupaXmnUzpeJX6jlfg/34WfvM/YPo7YPYFULcIpKRBuyNr+Sf97oExRQ2asNz9olvwRt8FgQdUdZOI3AlsUNU1wP3Aj0SkEe+sZ5Xbd5OIPApsBjLAZ1Q1C1AopmvyNmC1iHwFeMnFplgbwC3AIuALIvIFV3Y50AWsdckqiJes/uWUj1A/8eMDLixhmVPTG66kuf5imqf8BRfWHIW9L8D+F2HfBohWQUUNhGIQjnnvfa9wRd5ygfJgxCZgNhOCFBiDMKGdvXC2/vCrnyu6ffqhPzPnwB/YcObfkg3ZPHNmaC6cX+stZNPQ8joceB16u6A3CZnkifdsauBA4J2ZhWIQikKool9S61t2yS0xxTubCxa5/2pnWGaIRGSjqi4fyTZspotTFO9pIRWebMnKDI9gBGae570K0dxbE9jx5Z6TyzNJ6O2BTApSnXCs9UR5/hebA2GYcgY0nA0NSyBeOzo/qzGnyRLWKUokW2zCWzN6JADhuPc6HdmMl+SONEHrZvdyV+Erp0H9Ei+BZXuLn30Z4zNLWKcgkE0TSx/m8ORz/O6KMacmGIJgpTurOhv0P0FXq0tcW2DnH2HH0/DSj2Dhe2Hx5bDoMqi07xqascMS1imIp1oQsCmZTPkTgUlTvdeC93qXDQ++CZqBbU/BZjc4d/oyL3mdcQXMOBcC9uVn4x9LWKeg7xlYNiWTGXdCMZj+dm/QhSq0vAbbfuclr3/7Z/jT1yBeB4ve7yWwhZfavS8z6ixhnYJ4soXeYJx0qNLvrphRpgq9KvTmhF4V0rnA8fV0TkhrwNtWZHtv33b11h85GCOVE1JZ98rh3oVU9uTlgEBtNEdNNEdtRKmJ5qiJ5KiJ6PHy/PXaaI7YUE+GRLzkNf3tcMnnobsNtj8Nb671Etirj3j31mZdAGdc7iWwqefY0Hoz4ixhnYJE3yNF7D+mb1ThaCZI2v3i73WJIe2SQW/OSwzpvqSRlyR685JKWk/sm59U0seTTiAvprd+usKSIxJQwqJM6hZiQSUaVKIBiAa9JBQNKNEgrtwtB5TenNCeFtrTAdpTAfZ1h2hLBTjSW7xfsaBSGzmR5KqjubesH09y0RP1YoUCxWvhbVd7r1wW9r0I29Z6Z2B/uNN7Vc6AxZd5yWvBX0LU/qgzw88SVokkl6Ui1UpL7UV+d2VCae8N0thVwfauGNu7KtjeHaMrO7RTh5DkCIt6SSOghCVHOKBExFuvCGaZHPKWIwW2hwN5+4u33rccCeRczH77urKQ6Fv+zjn+PazTlMlBR1roSAdoSwVoSwvtqcDxxJa/vtcluc4BklzFr5+kNhGhJhGmJh6hJh7x1uMRahNhquMRahPzqTnrs9Se/3mqs4eJ7XraS16v/wJefNA7+4pVe9NOxSZ7X4qOTT7xOr7ef3uVt1+0yhskYkw/9qkoUUXqIAHN2YCLEdSdDbC9K0ZjV4zt3V6Sauv1hlgHUOZUpLioppPZFWlixxNELi+BuCTSt+wSSSTgJYzAODwxDgVgSkyZEssC2ZL26Uty7S7JeclNaEsHaK9+G23daTq6e2nrSrOnrZu2rjRHk8UfUBmP1FMT/yQNk/4zF4S2cW72dWrlKFXSzaRMN/H0MaIdB4j0HiXYe5RA+tjgnQwniiS0vPXK6TB1KdSf6X1p2ox7lrBKFE/2DbiwhDUc0jlhd0807+wpxv7UiV8606Npzq7sZlE8yaJED/PiKSIBm5VlOAyc5NYV3Ke3L8mlArSlA+6M7sR6u9v2/NEGfpt+P+1p4WiRM7kAOaaGupgZ7mJm5BgNoS6mhrqpC3RRG+iiWrqplG7i2kMs10Pk2BHCnS0EMz2Ie5HL67cEvNGOVTO8S5NV7hWtOvXL9zbTx5hmCatEiWQz2UCYZKTO766UnZzCvmTkRHLqjrG7J0ZWvV8m1aEMixI9vLuuk0WJHhbEk0wK5XzutckXDkB9TKk/hTO5dA46+s7eUi7J9SW9VJCO9GTa0jXsSgVoOxagIyUczQx8rzAsSmVYqQslWRg6yNmBvSxmD3NTe5nVspPJ+zYer5sKTqI7PpP0pBlQOZNQ9XQqqqdSEQ75fxs6l4PuQ3C0GY4e8MqmneOdNfreubHLElaJbMBFaVThYDrM9u7Y8ftOO7qjJHPefaeKQJaFiSQfntrGongPCxNJasOZCXdY1+1s87sLoyoA1AK1AsTcq4BMDo5mgxzNhOjKBOjOBujOBt17gJ6+5VyA1mwduzL1/Dy7/HidcLaHs2QvZwX2cHZmN2f17uHMzj9TIWkvvgbYpjN4k9nsYhZ7AjPZH5xFMjiJipDS++LzxEIBYuEg0bD3HgsFifUth4PEQgEioQBS4EMrmiWabqcieZCKlHslW6lIHaIi1erWDxJLHyagJyf+ZKSW9qqzaKs6i45K7/1oYu6QZvK/7sLx9wgkS1ilUCWePMDB6nf43ZMxpzMTPHHfyQ2K6Mx4H6uQ5JgXT/GX7sxpYSLJ9Gh6XN5LMsMjFICaQJaacGlncf3lFJK5IN3ZhXRnF/NKNsi6DETSbVSlDlDb20xD737elX2DD+tz3k5Z6MhOYltqNpuPzee17Gy25ObQqDNJEQG8y5h1dNIg7TRIB9OknenBI0wPdDBVOmiQduq0nVptJ8jJVwe6QtV0hes4Gq2ntWYh6Vg9qYqpJGP19ETrCWiGms43jr/O2vkQQffg9d5gBR2VZ7pEdjbtVWdyZNJicsHI0A5yGbOEVYJYuo1gLj3h718ls8KO7hMDIrZ3xWhNe/9pBGVmLM25k4+xKJFkUbyHORUpQmPgEU9m4ggIxIM54sH+SaMCmAfM4xjQCOzM9hBPthJPHiCePMDZqQOcl/wdwYCXKHIE6ArXEMz1EsseI1AgEXUyiTaqOayT2aln06LV7M/V0pSrpSVXwwGt4SDV9Bb4VSsosUCOeDBLRVCJBxcRlEUIHyISzDCX/SzQPSzUvSw4sof5Hb/kDFYDkCHAPpnOrsBsdrvXnsAs0oEKBEWA116OIuINWAqId2zEHaMAEHAjVwN9ZQIyYxkB8b73FwiIt71vXQTJWw4Ibl1G7Y9QS1gl6BtwMZEmvc0o7OmJemdN7gyqKRl1/xWgPtLLgngPl9V3sCjRw/x4ioqTfkkYM3ZlgxUcTcz1Lrn10RyxdJtLZC1UpA/TE4jSHppEb6iSdLiS3tAk0iHvXfOmqqp1ryX0fdE8R3e2ne5s5/FLmn2XLnv6XerszgbpyXopUVVIEmaLzmUz81AgJwDKdD3IInazmD0s0r2ck93MX2afP96HvdrAm8zhDZ1LY9c8tjCPQ1pDTiEHZNXrm7cu5PrW8cp0y7ZROPJDZwmrBIlkMzkJ0BNt8LsrIyKn0JIKH7+k19hVwa7u6PEvy1YGMyxMJLmg5ph3aS+eZPIQL9kYM6ZJgGR0CsnoFNomLxl6GIGIKJFAluph/7/S4F7LaQR29x4lnmwh4V4X92znfb0bTlSPVULVTO8VjHiPrEG9d815Gcst65QzvfdcFs1lQd17LovmMpDLoeqtk8ueWNYiXzofZpawShDvaaEn2vCWv6bKWVs6dHxQRGNXBTvyvowbDeSYH09yuTtzWphI0hDpnXCDIowpF73hSo6EKzlSufh4WTCbdJc6vSQW72yh4uCbxy9rKqAEQOQt77p3AxBA31IuIAEUQSUA7t0rd/uN0i+IkhKWiKwAvon3qPl/VdWv9tseBR4CzgcOA9eq6i637Q7gJryxsJ9V1bUDxRSR+cBqvLPrF4HrVTU9nG0MJJhNIppFxSUnVRLJFtorzyjlUI05XZnAiRF73RU0dsVoL/Bl3EWJJIsSSWbGUgQtORlT1rLBWMHLnR4ZodHOnx+BmG81aMISkSDwHeAyoAlYLyJrVHVzXrWbgHZVXSQiq4C7gWtFZAmwClgKzAB+LyJ9v/mLxbwbuEdVV4vI91zse4e5jaJi6TbOeeObbJ+0nB2Vy5FAgHC2m5bQTA6mQgQFQqIERQkFvPcgY2O0ezon7OqOHh8U0dgVo7nfl3GXVnaz0L6Ma8zEM4Sh8WNNKWdYFwCNqroDQERWAyuB/F/8K4Evu+XHgG+L9yWFlcBqVU0BO0Wk0cWjUEwR2QJcClzn6jzo4t47XG306/dJduk0/tx7Jpce+SNv63yWN3MzIQB37jufDU2Liu4XdPPFBfuSmSgh4S3rg5UHXXkokB+Lfvu+tTyjwu7uKI3dFezpjpLlrV/GvcS+jGuMGSdKSVgzgb15603AhcXqqGpGRI4Ada78+X77znTLhWLWAR2qmilQf7jaOImI3Azc7FZTl39l/+sntna695E/3R1Ou4FXTj/MFODQ6YcZF+xYnGDH4gQ7FiecOdINlJKwCl3s6n8dqVidYuWFzk0Hqj+cbZxcqHofcB+AiGxQ1eWF6k00dixOsGNxgh2LE+xYnCAiGwavdXpKuajZBMzOW58F7C9WR0RCwGSgbYB9i5UfAqpdjP5tDVcbxhhjylApCWs9sFhE5otIBG+Aw5p+ddYAN7rlq4GnVVVd+SoRibrRf4uBF4rFdPs842LgYj4+nG2UdliMMcaMNYNeEnT3i24B1uIND39AVTeJyJ3ABlVdA9wP/MgNeGjDSw64eo/iDXTIAJ9R9WZ8LBTTNXkbsFpEvgK85GIzzG0M5L4S6kwUdixOsGNxgh2LE+xYnDDix0K8kxRjjDFmbCv/gfnGGGMmBEtYxhhjyoIlLEdEVojIVhFpFJHb/e7PcBGR2SLyjIhsEZFNIvLfXXmtiDwlItvce40rFxH5ljsOr4rIeXmxbnT1t4nIjXnl54vIa26fb0mhJ9uNISISFJGXROTXbn2+iKxzP9cjbpAObiDPI+7nWici8/Ji3OHKt4rIFXnlZfM5EpFqEXlMRN5wn493TdTPhYj8jfv/8bqI/FREYhPlcyEiD4hIq4i8nlc24p+DYm0MSFUn/AtvUMZ2YAEQwfvO7RK/+zVMP9t04Dy3XAm8ifcEhK8Bt7vy24G73fIHgd/ifb/tImCdK68Fdrj3Grdc47a9ALzL7fNb4AN+/9yDHJNbgYeBX7v1R4FVbvl7wKfc8qeB77nlVcAjbnmJ+4xEgfnusxMst88R3kwy/8UtR4Dqifi5wJtoYCdQkfd5+MRE+VwAlwDnAa/nlY3456BYGwP21e+DNRZe7mCuzVu/A7jD736N0M/6ON78iluB6a5sOrDVLX8f+Fhe/a1u+8eA7+eVf9+VTQfeyCt/S72x9sL7Pt4f8KYA+7X7T3QICPX/LOCNMH2XWw65etL/89FXr5w+R0CV+yUt/con3OeCE7Po1Lp/518DV0ykzwXe0y3zE9aIfw6KtTHQyy4JegpNPzWzSN2y5S5dnAusA6aqajOAe+972FexYzFQeVOB8rHqG8DfwfHHx5Y8HRiQPx3YqRyjsWgBcBD4gbs8+q8ikmACfi5UdR/wz8AeoBnv33kjE/Nz0Wc0PgfF2ijKEpanlOmnypqITAJ+DnxOVTsHqlqgbKApsMrm2InIh4FWVd2YX1yg6lCnAyubY4F3ZnAecK+qngt04V2WKWbcHgt372Ql3mW8GUAC+ECBqhPhczEYX392S1iecT2Nk4iE8ZLVT1T1F674gIhMd9unA62u/FSnumpyy/3Lx6KLgStFZBfeM9cuxTvjmojTgTUBTaq6zq0/hpfAJuLn4v3ATlU9qKq9wC+Av2Bifi76jMbnoFgbRVnC8ozbaZzciJz7gS2q+vW8TflTXfWfAusGNxroIuCIO11fC1wuIjXuL9LL8a7LNwNHReQi19YNebHGFFW9Q1Vnqeo8vH/jp1X140zA6cBUtQXYKyJ9M2y/D2+2mAn3ucC7FHiRiMRdX/uOxYT7XOQZjc9BsTaK8/tm31h54Y1+eRNvNM/f+92fYfy5/gPeKfirwMvu9UG8a+5/ALa591pXX/AefLkdeA1YnhfrPwON7vXJvPLlwOtun2/T70b+WHwB7+HEKMEFeL9YGoGfAVFXHnPrjW77grz9/979vFvJG/1WTp8jYBmwwX02foU3umtCfi6A/wm84fr7I7yRfhPicwH8FO/eXS/eGdFNo/E5KNbGQC+bmskYY0xZsEuCxhhjyoIlLGOMMWXBEpYxxpiyYAnLGGNMWbCEZYwxpixYwjJmnBGRT4jIDL/7Ycxws4RlzAhxX6704//YJ/CmGDJmXLGEZcwwEpF54j1b6rvAi8D1IvKciLwoIj9zczoiIrtE5G4RecG9FhWJN9nVDbj1uIjsFZGwiCwTkefdc4l+6WYZuBrvi5o/EZGXRaTCPY/ojyKyUUTW5k2H81kR2ez2Xz06R8iYobOEZczwOxN4CO8xLjcB71fV8/Bmlbg1r16nql6A9+3/bxQKpKpH8J6f9Jeu6CN4U970ujZuU9W348068CVVfcy183FVXQZkgP8DXK2q5wMPAHe5WLcD57r9/9uw/OTGjKDQ4FWMMadot6o+72aHXwL82T1kNQI8l1fvp3nv9wwQ7xHgWry57VYB3xWRyUC1qv7R1XkQb7qg/s4EzgGecn0I4k3DA96UTD8RkV/hTc1kzJhmCcuY4dfl3gV4SlU/VqSeFlnubw3wv0WkFjgfeBqYVGJfBNikqu8qsO1DeE+bvRL4gogs1RPPfzJmzLFLgsaMnOeBi/vuT7n7T2fkbb827/25/jv3UdVjeJOsfhNvwt6su1TYLiLvdtWuB/rOto4ClW55K1AvIu9yfQiLyFJ3T2y2qj6D90DLakpPgsb4ws6wjBkhqnpQRD4B/FREoq74H/Bm7QaIisg6vD8ci52F9XkE75Lfe/LKbgS+JyJxYAfwSVf+Q1feg/d49quBb7nLiCG8+2VvAj92ZQLco6odQ/xRjRkVNlu7MT5wD5FcrqqH/O6LMeXCLgkaY4wpC3aGZcwYISJ/D1zTr/hnqnpXofrGTDSWsIwxxpQFuyRojDGmLFjCMsYYUxYsYRljjCkLlrCMMcaUBUtYxhhjysL/Dx3u6pQrnK1eAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f7f8748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(df['dem_votes'],label='奥巴马')\n",
    "sns.distplot(df['rep_votes'],label='谁啊')\n",
    "plt.xlim(0,100000)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f548048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set()\n",
    "\n",
    "sns.distplot(df['dem_share'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>gender</th>\n",
       "      <th>split</th>\n",
       "      <th>final</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>33</td>\n",
       "      <td>M</td>\n",
       "      <td>01:05:38</td>\n",
       "      <td>02:08:51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>32</td>\n",
       "      <td>M</td>\n",
       "      <td>01:06:26</td>\n",
       "      <td>02:09:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>31</td>\n",
       "      <td>M</td>\n",
       "      <td>01:06:49</td>\n",
       "      <td>02:10:42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>38</td>\n",
       "      <td>M</td>\n",
       "      <td>01:06:16</td>\n",
       "      <td>02:13:45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>31</td>\n",
       "      <td>M</td>\n",
       "      <td>01:06:32</td>\n",
       "      <td>02:13:59</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age gender     split     final\n",
       "0   33      M  01:05:38  02:08:51\n",
       "1   32      M  01:06:26  02:09:28\n",
       "2   31      M  01:06:49  02:10:42\n",
       "3   38      M  01:06:16  02:13:45\n",
       "4   31      M  01:06:32  02:13:59"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "data= pd.read_csv('marathon-data.csv')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "age       False\n",
       "gender    False\n",
       "split     False\n",
       "final     False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "def permutation_sample(data1, data2):\n",
    "    concat_df=np.concatenate((data1,data1))\n",
    "    permut_df=np.random.permutation(concat_df)\n",
    "    sample1=permut_df[:len(df1)]\n",
    "    sample2=permut_df[len(df1):]\n",
    "    return sample1,sample2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0183\n"
     ]
    }
   ],
   "source": [
    "df1=np.array(df.dem_votes[df.state=='MN'])\n",
    "df2=np.array(df.dem_votes[df.state=='AK'])\n",
    "diff=np.empty(10000)\n",
    "for i in range(10000):\n",
    "    perm_sample_1,perm_sample_2=permutation_sample(df1,df2)\n",
    "    diff[i]=np.mean(perm_sample_1)-np.mean(perm_sample_2)\n",
    "t_mean=np.mean(df1)-np.mean(df2)\n",
    "p=np.sum(diff>=t_mean)/10000\n",
    "print(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "40       971\n",
       "54      1492\n",
       "66      3097\n",
       "71      3649\n",
       "75     77351\n",
       "79      2311\n",
       "83     12019\n",
       "91      2019\n",
       "93      4174\n",
       "96      7850\n",
       "97      3394\n",
       "107     1877\n",
       "110     1120\n",
       "115    13460\n",
       "136     1436\n",
       "137     2129\n",
       "139     7276\n",
       "143     4872\n",
       "159     7687\n",
       "160    16666\n",
       "165     4595\n",
       "176     2882\n",
       "177    15859\n",
       "182    11501\n",
       "191    13856\n",
       "204     1550\n",
       "220     7084\n",
       "225     5277\n",
       "226     6547\n",
       "237     6072\n",
       "       ...  \n",
       "10      5657\n",
       "11      4161\n",
       "12      2351\n",
       "13      2645\n",
       "14      3596\n",
       "15      3233\n",
       "16      2046\n",
       "17      2684\n",
       "18      3486\n",
       "19      3380\n",
       "20      2474\n",
       "21      3337\n",
       "22      3130\n",
       "23      3647\n",
       "24      4075\n",
       "25      3642\n",
       "26      5176\n",
       "27      3095\n",
       "28      4472\n",
       "29      2264\n",
       "30      2549\n",
       "31      2089\n",
       "32      4254\n",
       "33      1920\n",
       "34      2805\n",
       "35      2074\n",
       "36      1924\n",
       "37      4283\n",
       "38      3393\n",
       "39      2597\n",
       "Name: dem_votes, Length: 127, dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.3029 0.2729 0.1679 0.5839 0.4859 0.1529 0.6329 0.4039 0.8509 0.7129\n",
      " 0.3289 0.3289 0.7279 0.6469 0.9459 0.5329 0.7359 0.8419 0.7449 0.5989]\n"
     ]
    }
   ],
   "source": [
    "force_b=np.array([ 0.172,  0.142,  0.037,  0.453,  0.355,  0.022,  0.502,  0.273,\n",
    "        0.72 ,  0.582,  0.198,  0.198,  0.597,  0.516,  0.815,  0.402,\n",
    "        0.605,  0.711,  0.614,  0.468])\n",
    "shift_b=force_b-np.mean(force_b)+0.55\n",
    "print(shift_b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def draw_bs_reps(data,func,size=1):\n",
    "    re_samples=np.empty(size)\n",
    "    for i in range(size):\n",
    "        re_samples[i]=func(np.random.choice(data,size=len(data)))\n",
    "    return re_samples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.999999\n"
     ]
    }
   ],
   "source": [
    "new_sample=draw_bs_reps(shift_b,np.mean,1000000)\n",
    "p=np.sum(new_sample!=np.mean(force_b))/1000000\n",
    "print(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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