Scikit - 03 Linear Regression.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.model_selection import train_test_split, cross_val_score\n",
    "import numpy as np\n",
    "\n",
    "import xgboost as xgb\n",
    "\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "from sklearn.preprocessing import PolynomialFeatures, StandardScaler\n",
    "\n",
    "from sklearn.linear_model import LassoCV, Lasso\n",
    "\n",
    "from math import sqrt\n",
    "\n",
    "import seaborn as sns\n",
    "\n",
    "\n",
    "np.set_printoptions(suppress=True, precision=4)\n",
    "plt.rcParams['figure.figsize'] = 10, 6\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>R&amp;D Spend</th>\n",
       "      <th>Administration</th>\n",
       "      <th>Marketing Spend</th>\n",
       "      <th>State</th>\n",
       "      <th>Profit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>165349.20</td>\n",
       "      <td>136897.80</td>\n",
       "      <td>471784.10</td>\n",
       "      <td>New York</td>\n",
       "      <td>192261.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>162597.70</td>\n",
       "      <td>151377.59</td>\n",
       "      <td>443898.53</td>\n",
       "      <td>California</td>\n",
       "      <td>191792.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>153441.51</td>\n",
       "      <td>101145.55</td>\n",
       "      <td>407934.54</td>\n",
       "      <td>Florida</td>\n",
       "      <td>191050.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>144372.41</td>\n",
       "      <td>118671.85</td>\n",
       "      <td>383199.62</td>\n",
       "      <td>New York</td>\n",
       "      <td>182901.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>142107.34</td>\n",
       "      <td>91391.77</td>\n",
       "      <td>366168.42</td>\n",
       "      <td>Florida</td>\n",
       "      <td>166187.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>131876.90</td>\n",
       "      <td>99814.71</td>\n",
       "      <td>362861.36</td>\n",
       "      <td>New York</td>\n",
       "      <td>156991.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>134615.46</td>\n",
       "      <td>147198.87</td>\n",
       "      <td>127716.82</td>\n",
       "      <td>California</td>\n",
       "      <td>156122.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>130298.13</td>\n",
       "      <td>145530.06</td>\n",
       "      <td>323876.68</td>\n",
       "      <td>Florida</td>\n",
       "      <td>155752.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>120542.52</td>\n",
       "      <td>148718.95</td>\n",
       "      <td>311613.29</td>\n",
       "      <td>New York</td>\n",
       "      <td>152211.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>123334.88</td>\n",
       "      <td>108679.17</td>\n",
       "      <td>304981.62</td>\n",
       "      <td>California</td>\n",
       "      <td>149759.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>101913.08</td>\n",
       "      <td>110594.11</td>\n",
       "      <td>229160.95</td>\n",
       "      <td>Florida</td>\n",
       "      <td>146121.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>100671.96</td>\n",
       "      <td>91790.61</td>\n",
       "      <td>249744.55</td>\n",
       "      <td>California</td>\n",
       "      <td>144259.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>93863.75</td>\n",
       "      <td>127320.38</td>\n",
       "      <td>249839.44</td>\n",
       "      <td>Florida</td>\n",
       "      <td>141585.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>91992.39</td>\n",
       "      <td>135495.07</td>\n",
       "      <td>252664.93</td>\n",
       "      <td>California</td>\n",
       "      <td>134307.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>119943.24</td>\n",
       "      <td>156547.42</td>\n",
       "      <td>256512.92</td>\n",
       "      <td>Florida</td>\n",
       "      <td>132602.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>114523.61</td>\n",
       "      <td>122616.84</td>\n",
       "      <td>261776.23</td>\n",
       "      <td>New York</td>\n",
       "      <td>129917.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>78013.11</td>\n",
       "      <td>121597.55</td>\n",
       "      <td>264346.06</td>\n",
       "      <td>California</td>\n",
       "      <td>126992.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>94657.16</td>\n",
       "      <td>145077.58</td>\n",
       "      <td>282574.31</td>\n",
       "      <td>New York</td>\n",
       "      <td>125370.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>91749.16</td>\n",
       "      <td>114175.79</td>\n",
       "      <td>294919.57</td>\n",
       "      <td>Florida</td>\n",
       "      <td>124266.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>86419.70</td>\n",
       "      <td>153514.11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>New York</td>\n",
       "      <td>122776.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>76253.86</td>\n",
       "      <td>113867.30</td>\n",
       "      <td>298664.47</td>\n",
       "      <td>California</td>\n",
       "      <td>118474.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>78389.47</td>\n",
       "      <td>153773.43</td>\n",
       "      <td>299737.29</td>\n",
       "      <td>New York</td>\n",
       "      <td>111313.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>73994.56</td>\n",
       "      <td>122782.75</td>\n",
       "      <td>303319.26</td>\n",
       "      <td>Florida</td>\n",
       "      <td>110352.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>67532.53</td>\n",
       "      <td>105751.03</td>\n",
       "      <td>304768.73</td>\n",
       "      <td>Florida</td>\n",
       "      <td>108733.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>77044.01</td>\n",
       "      <td>99281.34</td>\n",
       "      <td>140574.81</td>\n",
       "      <td>New York</td>\n",
       "      <td>108552.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>64664.71</td>\n",
       "      <td>139553.16</td>\n",
       "      <td>137962.62</td>\n",
       "      <td>California</td>\n",
       "      <td>107404.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>75328.87</td>\n",
       "      <td>144135.98</td>\n",
       "      <td>134050.07</td>\n",
       "      <td>Florida</td>\n",
       "      <td>105733.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>72107.60</td>\n",
       "      <td>127864.55</td>\n",
       "      <td>353183.81</td>\n",
       "      <td>New York</td>\n",
       "      <td>105008.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>66051.52</td>\n",
       "      <td>182645.56</td>\n",
       "      <td>118148.20</td>\n",
       "      <td>Florida</td>\n",
       "      <td>103282.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>65605.48</td>\n",
       "      <td>153032.06</td>\n",
       "      <td>107138.38</td>\n",
       "      <td>New York</td>\n",
       "      <td>101004.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>61994.48</td>\n",
       "      <td>115641.28</td>\n",
       "      <td>91131.24</td>\n",
       "      <td>Florida</td>\n",
       "      <td>99937.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>61136.38</td>\n",
       "      <td>152701.92</td>\n",
       "      <td>88218.23</td>\n",
       "      <td>New York</td>\n",
       "      <td>97483.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>63408.86</td>\n",
       "      <td>129219.61</td>\n",
       "      <td>46085.25</td>\n",
       "      <td>California</td>\n",
       "      <td>97427.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>55493.95</td>\n",
       "      <td>103057.49</td>\n",
       "      <td>214634.81</td>\n",
       "      <td>Florida</td>\n",
       "      <td>96778.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>46426.07</td>\n",
       "      <td>157693.92</td>\n",
       "      <td>210797.67</td>\n",
       "      <td>California</td>\n",
       "      <td>96712.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>46014.02</td>\n",
       "      <td>85047.44</td>\n",
       "      <td>205517.64</td>\n",
       "      <td>New York</td>\n",
       "      <td>96479.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>28663.76</td>\n",
       "      <td>127056.21</td>\n",
       "      <td>201126.82</td>\n",
       "      <td>Florida</td>\n",
       "      <td>90708.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>44069.95</td>\n",
       "      <td>51283.14</td>\n",
       "      <td>197029.42</td>\n",
       "      <td>California</td>\n",
       "      <td>89949.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>20229.59</td>\n",
       "      <td>65947.93</td>\n",
       "      <td>185265.10</td>\n",
       "      <td>New York</td>\n",
       "      <td>81229.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>38558.51</td>\n",
       "      <td>82982.09</td>\n",
       "      <td>174999.30</td>\n",
       "      <td>California</td>\n",
       "      <td>81005.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>28754.33</td>\n",
       "      <td>118546.05</td>\n",
       "      <td>172795.67</td>\n",
       "      <td>California</td>\n",
       "      <td>78239.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>27892.92</td>\n",
       "      <td>84710.77</td>\n",
       "      <td>164470.71</td>\n",
       "      <td>Florida</td>\n",
       "      <td>77798.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>23640.93</td>\n",
       "      <td>96189.63</td>\n",
       "      <td>148001.11</td>\n",
       "      <td>California</td>\n",
       "      <td>71498.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>15505.73</td>\n",
       "      <td>127382.30</td>\n",
       "      <td>35534.17</td>\n",
       "      <td>New York</td>\n",
       "      <td>69758.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>22177.74</td>\n",
       "      <td>154806.14</td>\n",
       "      <td>28334.72</td>\n",
       "      <td>California</td>\n",
       "      <td>65200.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>1000.23</td>\n",
       "      <td>124153.04</td>\n",
       "      <td>1903.93</td>\n",
       "      <td>New York</td>\n",
       "      <td>64926.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>1315.46</td>\n",
       "      <td>115816.21</td>\n",
       "      <td>297114.46</td>\n",
       "      <td>Florida</td>\n",
       "      <td>49490.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>NaN</td>\n",
       "      <td>135426.92</td>\n",
       "      <td>NaN</td>\n",
       "      <td>California</td>\n",
       "      <td>42559.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>542.05</td>\n",
       "      <td>51743.15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>New York</td>\n",
       "      <td>35673.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>NaN</td>\n",
       "      <td>116983.80</td>\n",
       "      <td>45173.06</td>\n",
       "      <td>California</td>\n",
       "      <td>14681.40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    R&D Spend  Administration  Marketing Spend       State     Profit\n",
       "0   165349.20       136897.80        471784.10    New York  192261.83\n",
       "1   162597.70       151377.59        443898.53  California  191792.06\n",
       "2   153441.51       101145.55        407934.54     Florida  191050.39\n",
       "3   144372.41       118671.85        383199.62    New York  182901.99\n",
       "4   142107.34        91391.77        366168.42     Florida  166187.94\n",
       "5   131876.90        99814.71        362861.36    New York  156991.12\n",
       "6   134615.46       147198.87        127716.82  California  156122.51\n",
       "7   130298.13       145530.06        323876.68     Florida  155752.60\n",
       "8   120542.52       148718.95        311613.29    New York  152211.77\n",
       "9   123334.88       108679.17        304981.62  California  149759.96\n",
       "10  101913.08       110594.11        229160.95     Florida  146121.95\n",
       "11  100671.96        91790.61        249744.55  California  144259.40\n",
       "12   93863.75       127320.38        249839.44     Florida  141585.52\n",
       "13   91992.39       135495.07        252664.93  California  134307.35\n",
       "14  119943.24       156547.42        256512.92     Florida  132602.65\n",
       "15  114523.61       122616.84        261776.23    New York  129917.04\n",
       "16   78013.11       121597.55        264346.06  California  126992.93\n",
       "17   94657.16       145077.58        282574.31    New York  125370.37\n",
       "18   91749.16       114175.79        294919.57     Florida  124266.90\n",
       "19   86419.70       153514.11              NaN    New York  122776.86\n",
       "20   76253.86       113867.30        298664.47  California  118474.03\n",
       "21   78389.47       153773.43        299737.29    New York  111313.02\n",
       "22   73994.56       122782.75        303319.26     Florida  110352.25\n",
       "23   67532.53       105751.03        304768.73     Florida  108733.99\n",
       "24   77044.01        99281.34        140574.81    New York  108552.04\n",
       "25   64664.71       139553.16        137962.62  California  107404.34\n",
       "26   75328.87       144135.98        134050.07     Florida  105733.54\n",
       "27   72107.60       127864.55        353183.81    New York  105008.31\n",
       "28   66051.52       182645.56        118148.20     Florida  103282.38\n",
       "29   65605.48       153032.06        107138.38    New York  101004.64\n",
       "30   61994.48       115641.28         91131.24     Florida   99937.59\n",
       "31   61136.38       152701.92         88218.23    New York   97483.56\n",
       "32   63408.86       129219.61         46085.25  California   97427.84\n",
       "33   55493.95       103057.49        214634.81     Florida   96778.92\n",
       "34   46426.07       157693.92        210797.67  California   96712.80\n",
       "35   46014.02        85047.44        205517.64    New York   96479.51\n",
       "36   28663.76       127056.21        201126.82     Florida   90708.19\n",
       "37   44069.95        51283.14        197029.42  California   89949.14\n",
       "38   20229.59        65947.93        185265.10    New York   81229.06\n",
       "39   38558.51        82982.09        174999.30  California   81005.76\n",
       "40   28754.33       118546.05        172795.67  California   78239.91\n",
       "41   27892.92        84710.77        164470.71     Florida   77798.83\n",
       "42   23640.93        96189.63        148001.11  California   71498.49\n",
       "43   15505.73       127382.30         35534.17    New York   69758.98\n",
       "44   22177.74       154806.14         28334.72  California   65200.33\n",
       "45    1000.23       124153.04          1903.93    New York   64926.08\n",
       "46    1315.46       115816.21        297114.46     Florida   49490.75\n",
       "47        NaN       135426.92              NaN  California   42559.73\n",
       "48     542.05        51743.15              NaN    New York   35673.41\n",
       "49        NaN       116983.80         45173.06  California   14681.40"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"https://raw.githubusercontent.com/abulbasar/data/master/startups.csv\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 50 entries, 0 to 49\n",
      "Data columns (total 5 columns):\n",
      "R&D Spend          48 non-null float64\n",
      "Administration     50 non-null float64\n",
      "Marketing Spend    47 non-null float64\n",
      "State              50 non-null object\n",
      "Profit             50 non-null float64\n",
      "dtypes: float64(4), object(1)\n",
      "memory usage: 2.0+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are 50 observations and 5 columns. 4 columns - R&D Spend, Administration and Marketing Spend, and Profile are numeric and one is categorical - State. There is 2 null values in columns R&D Spend feature and and 3 in Marketing Spend. \n",
    "\n",
    "Replace the null values with median for respective state. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>R&amp;D Spend</th>\n",
       "      <th>Administration</th>\n",
       "      <th>Marketing Spend</th>\n",
       "      <th>State</th>\n",
       "      <th>Profit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>86419.70</td>\n",
       "      <td>153514.11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>New York</td>\n",
       "      <td>122776.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>NaN</td>\n",
       "      <td>135426.92</td>\n",
       "      <td>NaN</td>\n",
       "      <td>California</td>\n",
       "      <td>42559.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>542.05</td>\n",
       "      <td>51743.15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>New York</td>\n",
       "      <td>35673.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>NaN</td>\n",
       "      <td>116983.80</td>\n",
       "      <td>45173.06</td>\n",
       "      <td>California</td>\n",
       "      <td>14681.40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    R&D Spend  Administration  Marketing Spend       State     Profit\n",
       "19   86419.70       153514.11              NaN    New York  122776.86\n",
       "47        NaN       135426.92              NaN  California   42559.73\n",
       "48     542.05        51743.15              NaN    New York   35673.41\n",
       "49        NaN       116983.80         45173.06  California   14681.40"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_null_idx = df[df.isnull().sum(axis = 1) > 0].index\n",
    "df.iloc[df_null_idx]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>R&amp;D Spend</th>\n",
       "      <th>Marketing Spend</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>State</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>California</th>\n",
       "      <td>64664.710</td>\n",
       "      <td>186014.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Florida</th>\n",
       "      <td>74661.715</td>\n",
       "      <td>253176.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New York</th>\n",
       "      <td>77044.010</td>\n",
       "      <td>261776.23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            R&D Spend  Marketing Spend\n",
       "State                                 \n",
       "California  64664.710        186014.36\n",
       "Florida     74661.715        253176.18\n",
       "New York    77044.010        261776.23"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "median_values = df.groupby(\"State\")[[\"R&D Spend\", \"Marketing Spend\"]].median()\n",
    "median_values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>R&amp;D Spend</th>\n",
       "      <th>Administration</th>\n",
       "      <th>Marketing Spend</th>\n",
       "      <th>State</th>\n",
       "      <th>Profit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>86419.70</td>\n",
       "      <td>153514.11</td>\n",
       "      <td>261776.23</td>\n",
       "      <td>New York</td>\n",
       "      <td>122776.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>64664.71</td>\n",
       "      <td>135426.92</td>\n",
       "      <td>186014.36</td>\n",
       "      <td>California</td>\n",
       "      <td>42559.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>542.05</td>\n",
       "      <td>51743.15</td>\n",
       "      <td>261776.23</td>\n",
       "      <td>New York</td>\n",
       "      <td>35673.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>64664.71</td>\n",
       "      <td>116983.80</td>\n",
       "      <td>45173.06</td>\n",
       "      <td>California</td>\n",
       "      <td>14681.40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    R&D Spend  Administration  Marketing Spend       State     Profit\n",
       "19   86419.70       153514.11        261776.23    New York  122776.86\n",
       "47   64664.71       135426.92        186014.36  California   42559.73\n",
       "48     542.05        51743.15        261776.23    New York   35673.41\n",
       "49   64664.71       116983.80         45173.06  California   14681.40"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"R&D Spend\"] = df.apply(lambda row: median_values.loc[row[\"State\"], \"R&D Spend\"]  if np.isnan(row[\"R&D Spend\"]) else row[\"R&D Spend\"], axis = 1 )\n",
    "df[\"Marketing Spend\"] = df.apply(lambda row: median_values.loc[row[\"State\"], \"Marketing Spend\"]  if np.isnan(row[\"Marketing Spend\"]) else row[\"Marketing Spend\"], axis = 1 )\n",
    "df.iloc[df_null_idx]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "R&D Spend          0\n",
       "Administration     0\n",
       "Marketing Spend    0\n",
       "State              0\n",
       "Profit             0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check if there are any more null values.\n",
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's see the distribution of the Profit using a histogram plot and see if there is any outliers in the data using bosplot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Hm6lOfZXX1Ed3oApoC3QAzjOzjj+r6H6Pu5e5e1mbNm3SNCUia+3Fa6E6AQddHXUk688M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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a944588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (8, 6))\n",
    "plt.subplot(2, 1, 1)\n",
    "df.Profit.plot.hist(bins = 10, normed = True)\n",
    "df.Profit.plot.kde(title = \"Historgram of Profit\")\n",
    "\n",
    "plt.subplot(2, 1, 2)\n",
    "df.Profit.plot.box(vert = False, title = \"Boxplot of Profit\")\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Profit has one outlier. We can try to take log scale to remove the outlier value before doing any prediction. But for now, let ignore the outlier.\n",
    "\n",
    "Let's plot association between each pair of columns. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x11a8eb630>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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wTvq/mLjsPm51qZQxfUo76XQKMzh2emfRvJT6vgYzo2VP6uR3JajcfeM0FZ2E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1uVR2\nroZpTaxduWTMsWJJvr6RgLJ8KqjURvwp4Ckz+5ew3EnuvnMC63478CFgh5ltC2l/AdwC3GdmVwIv\nAIX25g9AI5mBAAAgAElEQVQDFwPd5Mct/3DIR4+Z/RWwJSz3GXcvXEf5GPA1YDqwMdyosI2GGK99\nbqHN7Ni2s8XjME+f1sxX/rSTo6ZV3142QSM4pFkm4naiba4n26Y8rpnYKin8MYDR+1pG95NMxK1M\nOYrbIOpyqW9wmPVP/II1K97Corkz6d53iPVP/IKP/MeFzJ7Rpj5nMaqm5f1y4PNAK3CymS0hH+Qr\nKr3J3f83pdtnAby7xPIOXFNmXXcDd5dI7wLeWiL9QKltNEqlHapchaXcxCBHtTRX3bluqk4PW09Z\nittyFdFSJnMQiHNSm1r+AGRxP8lS3MrUobh9Q5TlUi7n4M7H372YFw708Wf3bePl1/u59QOnM31a\n04SOFVJ/1Xzja8iPy/lDAHffFno3SxnldqjDg8P09g+XrLDUY5SLJI7gIOkwmYNAo0doKaj1D4D2\nk3RYcON3q1529y3vjTAnItGLqlwqVU7e+oHT+fwjO7nhge3cecVZHH1UNeN2SFSqOUoOuftr+eZV\nUo1yOxQOvf1DfP2j59K97xC3Pd49UmGpx2WpqTo9rEzeZA4ChdhdccbxXHPBopHLntOnRVu41/oH\nQPuJiCRNVOVSqSYpD23dwzUXLOK9a3/EDJ0Bj101v8DTZvZHQLOZLQZWA/832mylW6kdanpLEz19\nA9z04I5R/0q/8OjOkWXqcVlKl5ikFpM5CPQNDLP6XYu4dOl8bnhg+0h8f2nlEt4cYW/7yfx51X4i\nIkkTRbk0fVrTEWXzrR84neOPPSr1TfKyoppTVv8FeAvQD/wL8DpwXZSZyoKxI0j8eijH6vXbRvWI\nvuGB7Vz3e6eMVHo0W6bEqdZRT9qnNfOnbz+ZGx7YPiq+r12/LdKRSJIyq6WISFL1DQwfUTbf8MB2\nDvUPqY6RENX8DZrr7jcDNxcSzOxs3uidLFUod/bupNnt4LpcLunV1GTMPKql4SORqK23iEhlM9pK\nl83HTJ82UveQeFVzRvxBMytMCYuZvYMSPZOlvFzO6e0fYudfX8Sm697BijOOB96YNrawIyRpHGaR\niZjI2emszmopIpIExWVsb/8Qq9+1aNTrhbJZZWUyVHNG/D8BD5nZHwBnAn9DfhxPqUK5HsuL5sxg\n5bm/kfaxi0WA6s9O13uoQ7X1FhF5Q6ky9kuXLwFg7Q+6deUwgcY9crn7FjNbDTxCfpbN97j7/shz\nlhGlRnYoDBk03kyZUUni5CuSbtU2rSo30kmc+4OISFaUKmOvvXcbd15xFh9/9+JJH/NVf6i/shVx\nM/sfQPE143bgNeArZsZ4E/pIXrm24TNCE5R6G28niXPyFcm2as5Olx/ppIUDvQOxxaEOLiKSBePV\nOSZz5XB4OEfvwDAz2lp4/uVDbHp6LyvP/Q3VHyapUhvxzwN/V3S7EvhU0XOpQiNHdihUsq9a18Up\nN2/kqnVdHOgdGGmDm8s5vQNDdMxoZc2Kt3Dx2+aNnJGMcnQLkYJy+0P3vkOxxeHY/ebuH+2qSxt2\nEZFGi6rOUVwJ796Xr4RfunQ+65/4heoPk1T2r5G7/08zawY2ufvvNTBPmdLIkR0qTXDSPq25ZFt1\ngId37FVbdWmIUvtDYZa3qEdZKad4v1lxxvFcunQ+/+mfn9QVIxFJnSjqHLmcc6BvgGvXbxtVbj+0\ndQ8XvnWe6g+TVPEahbsPm1mfmb3J3V9rVKaypJHDElaa4KRvoHRb9TUr3sL+g/2JGdRfTQSyrbA/\n3HnFWbS35s+sfP6RnWx46iXOXzg7ljgs3m+uuWDRyJi7UPRn9opOMBSPIpJoUdQ5+gaHuTbMgwKj\n6w+L5s5sSLmd5bpBNcMXHgZ2mNlXzGxt4RZ1xrKkUcMSVrokVa6SvmjuzMT0oB6vaY1kQ1OTMaO1\nhZ7eAdZseIaHd+yNdQKr4v1m0dyZJfeT6a3NikcRSYV61zkq1R96+4ciL7ezXjeo5i/Md8NNEq5w\nSWr9E7/gwrfOG9lJprc0jVQ2Cv9ooVBJH0rMZfdKTWuScLZe6idJE1gVX8rt3neo5H7Sve9QQ+Mx\ny2d/RCRdDg8O8/3rf5cTO9rp3neI2x7vZv/Bfnr7h5jRGn3ZlPW6QTXDF65rREZk8pqajI72aVx+\n7kmj2nKtXbmUjvZpJduNJWnIuEpNayR7kjIGePGfgunTmvjSyiVHtIX8/CM7gcbEo0Y2EpGkKExI\neNODO0bKo89ddjoz21qY0dpMc3M1DSsmJ+t1g3G/QTNbbGb/amb/Zma7CrdGZE4m7tdDuZG2XEM5\nH/nn+OuhXOJnIWzkCDMixQp/CpqbmnjzjLaR/eS/vf9tI23YoTHxWHz2p3gf1sgEItJo+fJodJ3i\nk/dvp6WpqSGVcMh+3aCab/GrwO3AEHABcA/wz1FmSmrX3trMcce0sem6d/Czv7mYTde9g+OOaaM9\nXD5qRFv1WhWaCJy/cDYtTRZru2GZukbO1DvMaGth/8H+UfE4vaUp0uENs372R0TSIZdzcPj6R89l\n03XvYMUZxwOhPGprXHmU9bpBNRXx6e7+GGDu/gt3XwO8q5qVm9ndZrbPzJ4uSusws0fN7PlwPyuk\nW+gI2m1m283szKL3rArLP29mq4rSzzKzHeE9a83yM+SU28ZUcHhwmE9ceCprNjzDqZ/ayJoNz/CJ\nC0/lcArOphU3EYjrrL1iVgpKxWNH+zR6+gYj7TRUy9kfxa2kkeI2uUY6SN7T9UZdYtmprDjj+Iaf\njU5C3SBKVY2aYmZNwPNm9nEzex8wt8r1fw1YPibtRuAxd18MPBaeA1wELA63q8mfhcfMOoBPA+cC\n5wCfLtppbg/LFt63fJxtZF4uB5+8f/sRl5FyubhzVp0EnLX/GopZCcbG46+HcpE3G6nx7M/XUNxK\n+nwNxW0ilWoid8MD27n+PafEcjY6AXWDyFRTEb+O/PT2q4GzgA8Bqyq+I3D3/wX0jEm+BCh0AF0H\nXFqUfo/n/Rg41szmARcCj7p7j7u/CjwKLA+vHePum93dyTeZuXScbWRee1uZy9oNvIyUZopZqaQR\nzUZqOfujuJU0UtwmV7my7qTZ7Zk6G50E1YyasiU8PAR8uA7bPM7d94Z17zWzwtn1E4AXi5bbE9Iq\npe8pkV5pG5lVPNzZ96//Xb7w6HNHdDDLwjA/MVHMJkicQ/uVHwa0vvtXnUaUUdxKGiluE6BvYJjV\n71o0MhRyYVp71SXqr+y3aWYbKr3R3VfUOS+ljqReQ3r1GzS7mvxlK0466aSJvDVRcjnn4OFBXu0b\n5MSOdgD+8g9+myaDl1/vz1SnhoRpeMxCduK2FnEP7dc+rZkv/8mZI/vaiz19zGqflrb9S3EraaQ6\nQoPkO2k6H3/3Yl440Mef3beNl1/v50uXL2F6S2NGSplKKv2tOZ/8v8z1wBOUDupavGxm88K/0HnA\nvpC+BzixaLn5wEsh/Z1j0n8Y0ueXWL7SNkZx9zuBOwE6OztTO0XT4aFhDpYY5/Nv3vc2cmha7jpI\nTMxCduK2FkmY2GFgODdqX1u7cklDtlsDxe0Us+DGic29t/uW90aUk0lJTNxOxZgtdbKjMJfCtfdu\ny5e1DRq2cKqo9G3+P8BfAG8FvgS8B3jF3f+nu//PSWxzA2+0MV8FfLso/YrQM/o84LVw6WgTsMzM\nZoUOGMuATeG1g2Z2XugJfcWYdZXaRiaV7aDpZK5TQ0wUswkR99B+pcbUXb1+W1LH+FbcShopbmNU\nrpPmNRcs0jCqESl7Csndh4HvAd8zszZgJfBDM/uMu/9DNSs3s/Xk/6m+2cz2kO/ZfAtwn5ldCbwA\nXBYWfxi4GOgG+gjt0d29x8z+Cii0Vf+MuxeOxB8j3+t6OrAx3KiwjUxSB836UcwmW6PaaJcT9x+B\nchS3kkaK2+QpV8YtmjtT/c0iUvHbDBXw95KvhC8A1gIPVrtyd19Z5qV3l1jWgWvKrOdu4O4S6V3k\nz9iPTT9QahtZ1ddfpnLSP8zMo7TDTIRiNtkKQ/uNbSPeqDbacf8RKEdxK2mkuE2ecmXciz196m8W\nkbJNU8xsHfB/gTOB/+ruZ7v7X7n7LxuWO6lKe2sza1cuGTPu8JLYz9KJ1FvcEztkfYY3EZnaSpdx\nS5h7TJuGLYxIpVM4HwJ6gVOA1WFCKsh32nR3PybivEmV8pWTNu5a1RnLkG4ijVSnof1q3nbhj4D2\nNRHJGpVxjVepjbi6xaZInJUTkalE+5qIZJnKuMZSZVtEREREJAaqiIuIiIiIxEAVcRERERGRGKgi\nniG5nNM3MMShw0Pk3PP3uSkxGZhMMbmcc6g/xHl/5TifyLIiIhOVtTIma58n6dQKPyNyOefg4UEO\n9g/xyfu3j5p+e/aMNvV4lswoNQXz2pVLSw6tNZFlJb0mOrW75EX1ve2+5b2RrDeJslbGZO3zpIHO\niGdE3+Awr/YNHjHVfYKn3xapSakpmFev31oyzieyrIjIRGWtjMna50kDVcTrKM7LOe2tzZzY0Z7I\n6bdF6qnaaeZzOQeHr3/0XDZd9w5WnHF82WVFRGpRbXnUKJOthyTt80wFqojXSeFyzlXrujjl5o1c\nta6LA70DDauM9w0M82JPH2cv6BiVXph+WyQrClMwFxsb5yP74z1dnPqpjazZ8AyfWHYqK844XvuE\niNRNNeVRo9SjHpKkzzNVqCJeJ+Uu5xweGm7IWfL2ac3Map/G5y47/cip7jX9tmRINdPMl9ofb3hg\nO9e/55S6TEmvzkwiAtWVR1ErlEcY9PYPMefotpqblSTh80w16qxZJ6Uu5xx3TBu9/UOsXr8t8k4P\nTU3G0UdNY1pLE3dd0Ul7WzN9/cO0t2pqWsmWaqZgLnd59aTZ7eBMap9QZyYRKYh7SvhS5dGtHzgd\ngA1PvTThZiVxf56pSGfE66TU5Zzrfu8UVq/f1rBOD01NRntrCzOPaqHJLH+vnUcyqDAFc5OF+zFx\nXuny6mT3CXVmEpFi45VHUSp39e+aCxYBtTUrifPzTEWqiNdJqcs5J81W50mROER5eVWdmUQkKcqV\nR4vmzlSzkpRQ05Q6KXU5p68/f1Zu864DI8sV/p3ObNNXLxKVKC+vFs62a78WkbiVK49+PTCcL//U\nrCTxdEa8jsZezmlvVacHkbhEdXlVnZlEJCnKlketzWpWkhKZPX1jZsuBLwHNwD+5+y2NzoM6PchE\nJSFupTLt10dS3EoaZSFuVR6lXybPiJtZM3AbcBFwGrDSzE6rdX2TGapMnR6kWvWO26moUcMKar9+\ng+JW0khxK0mRyYo4cA7Q7e673H0AuBe4pJYVxT1Rj0wpdYvbqUj7amwUt5JGmYhblXvpl9WK+AnA\ni0XP94S0CdNQZdJAdYvbqUj7amwUt5JGmYhblXvpl9WKeKnrxEf8PTSzq82sy8y69u/fX3JFGqpM\nGqhucTsVaV+NjeJW0mjcuE1DzKrcS7+sVsT3ACcWPZ8PvDR2IXe/09073b1zzpw5JVdUaWIQkTqr\nW9xORdpXY6O4lTQaN27TELMq99IvqxXxLcBiMzvZzFqBy4ENtaxIQ5VJA9Utbqci7auxUdxKGmUi\nblXupV8mhy909yEz+ziwifywRHe7+zO1rEtDA0mj1DNupyLtq/FQ3EoaZSVuVe6lXyYr4gDu/jDw\ncD3WVRiqDNDMeRKpesbtVKR9NR6KW0mjrMStyr10y2rTFBERERGRRFNFXEREREQkBqqIi4iIiIjE\nQBVxEREREZEYmLumQQUws/3AL8ZZ7M3AKw3ITtLzANnMxyvuvrxO62qIKuI2Kb/TeJTP2ilukyXN\neYfG5T9VcWtmB4GdcecjJmmP6ckY+9nrHreqiE+AmXW5e+dUz4PykR5p+X6UTymW5u85zXmH9Oc/\nKlP5e9Fnj/azq2mKiIiIiEgMVBEXEREREYmBKuITc2fcGSAZeQDlIy3S8v0on1Iszd9zmvMO6c9/\nVKby96LPHiG1ERcRERERiYHOiIuIiIiIxEAV8SqY2XIz22lm3WZ2Y53WudvMdpjZNjPrCmkdZvao\nmT0f7meFdDOztWH7283szKL1rArLP29mq4rSzwrr7w7vtZB+t5ntM7Oni5ZtxHbHbuPrJfKxxsx+\nGb6TbWZ2cdFrN4V17jSzC8f7bczsZDN7Imzvm2bWGtLbwvPu8PqCyf2SjRFXvFSRr6TE06wa86qY\nS5hy328DtnuimT1uZs+a2TNmdm1IT2Q8V/gczWa21cy+E55POC7rFftZEVdMTlaayuc6f+507cvu\nrluFG9AM/AxYCLQCTwGn1WG9u4E3j0n7W+DG8PhG4Nbw+GJgI2DAecATIb0D2BXuZ4XHs8JrPwHO\nD+/ZCFwU0t8BnAk83eDtjt3GN0rkYw3wiRLf1Wnhe28DTg6/R3Ol3wa4D7g8PP4y8LHw+D8DXw6P\nLwe+GXeMJTleqshXUuLp1hrzqphL0K3S99uAbc8DzgyPjwaeC3GQyHiu8DmuB/4F+E4tcVnP2M/C\nLc6YrEPeU1M+1/lzp2pfjj1Qkn4LX/Smouc3ATfVYb27ObJitROYVxRIO8PjO4CVY5cDVgJ3FKXf\nEdLmAf9elD52uQVjdszIt1tqGyXysYbSlaJR3zmwKfwuJX+bsGO8ArSM/Q0L7w2PW8JyFnecJTle\nqshbIuKpxrwq5hJ0K/f9xpSXbwPvSXI8l8jzfOAx4F3Ad2qJy3rGfhZuSYrJGvM/tsxLTTzX8TtI\n9L6spinjOwF4sej5npA2WQ48YmZPmtnVIe04d98LEO7njpOHSul7JpDnRmy33DbG+ni4NHR30SWd\nieZjNvArdx8qkY+R94TXXwvLJ12S4mU8SYqnaijmkiOq8nZCQjONpcATpCuevwj8OZALz2uJy3rG\nfhYkIibrKE3xPGlp2JdVER9fqbayXof1vt3dzwQuAq4xs3fUkIeJpk9Uo7d7O/CbwBJgL/B3EeQj\nqt8zammIl/EkMV+KuWSJ/bsys5nAA8B17v56pUVLpMUWz2b2+8A+d3+yOLnCNuuV/9h/s4hl/fMV\nZO53T8u+rIr4+PYAJxY9nw+8NNmVuvtL4X4f8C3gHOBlM5sHEO73jZOHSunzJ5DnRmy33DZGuPvL\n7j7s7jngLvLfSS35eAU41sxaSuRj5D3h9TcBPUd8IwmTsHgZTyLiqRqKucSJpLytlplNI3/g/oa7\nPxiS0xLPbwdWmNlu4F7yzVO+yMTjsp6xnwWxxmQE0hLPk5KmfVkV8fFtARaHXuGt5Du1bJjMCs1s\nhpkdXXgMLAOeDutdFRZbRb5dEyH9itCz9zzgtXDJYxOwzMxmhUvqy8i3ZdsLHDSz80JP3iuK1lVK\nI7ZbbhvF38u8oqfvC99J4b2XW76X/8nAYvIdJUr+Np5vnPU48MEyn6mQjw8CPwjLJ1YC42U8iYin\naijmEqfu5W21Qox9BXjW3b9Q9FIq4tndb3L3+e6+gPz39gN3/2MmHpf1jP0siC0mI5KKeJ6M1O3L\ncTWeT9ONfI/a58j3nL65DutbSL7n9VPAM4V1km9r9xjwfLjvCOkG3Ba2vwPoLFrXR4DucPtwUXon\n+UrFz4B/hJHJm9aTvwQ/SP5f3ZUN2u7YbTxQIh//HLazPQTzvKL13hzWuZOiET3K/TbhO/5JyN/9\nQFtIPyo87w6vL4w7vpIcL1XkLSnx1FFjXhVzCbuV+34bsN3fIX95eTuwLdwuTmo8j/NZ3skbo6ZM\nOC7rFftZucUVk3XId2rK5zp/7lTty5pZU0REREQkBmqaIiIiIiISA1XERURERERioIq4iIiIiEgM\nVBEXEREREYmBKuIiIiIiIjFQRVxEREREJAaqiIuIiIiIxEAVcRERERGRGKgiLiIiIiISA1XERURE\nRERioIq4iIiIiEgMVBEXEREREYmBKuIiIiIiIjFQRVxEREREJAaqiIuIiIiIxEAVcRERERGRGERW\nETezE83scTN71syeMbNrQ3qHmT1qZs+H+1kh3cxsrZl1m9l2MzuzaF2rwvLPm9mqovSzzGxHeM9a\nM7NK26hk+fLlDug2tW+KW93SeFPc6pbGW6riVjGrW7jVXZRnxIeAP3P33wbOA64xs9OAG4HH3H0x\n8Fh4DnARsDjcrgZuh/zOAnwaOBc4B/h00Q5ze1i28L7lIb3cNsp65ZVXJvVhJTMUt5JGiltJo9TE\nrWJWohJZRdzd97r7T8Pjg8CzwAnAJcC6sNg64NLw+BLgHs/7MXCsmc0DLgQedfced38VeBRYHl47\nxt03u7sD94xZV6ltiFSkuJU0UtxKGiluRRrURtzMFgBLgSeA49x9L+R3QmBuWOwE4MWit+0JaZXS\n95RIp8I2RKqmuJU0UtxKGiluZaqKvCJuZjOBB4Dr3P31SouWSPMa0ieSt6vNrMvMuvbv3z+Rt0rG\nKW4ljRS3kkZJjVvFrDRCpBVxM5tGfuf6hrs/GJJfDpeLCPf7Qvoe4MSit88HXhonfX6J9ErbGMXd\n73T3TnfvnDNnTm0fUjJHcStppLiVNEpy3CpmpRGiHDXFgK8Az7r7F4pe2gCsCo9XAd8uSr8i9Io+\nD3gtXC7aBCwzs1mh88UyYFN47aCZnRe2dcWYdZXahkwxuZxzqH+InIf7XOWTIYrbqWOisZFkiltJ\nApW3IjVw90huwO+QvwS0HdgWbhcDs8n3UH4+3HeE5Q24DfgZsAPoLFrXR4DucPtwUXon8HR4zz8C\nFtJLbqPS7ayzznJJn+HhnB88POjDuXA/nHsj/df59J/vP+TXrv+pX37HZt/3+uGRZUpQ3Mag3G8Y\n9Tb3vX7YL79js//mTd+tJjZiy2sVFLdSN+PFeKUyd4L7VKriVjErQd3ry4WAnPI6Ozu9q6sr7mzI\nBORyzoHeAVav38qW3T2cvaCDtSuX0tE+jZ6+wVHpt37gdD7/yE72H+znrlWdzGxrKbXKUu0JEy3t\ncVvuN5w9o5Wmpuh+jkP9Q1y1rovNuw6MpJ2/cHal2Igtr1VQ3EpdjBfjlV7vGxye6D6VqrhVzEpQ\n97jVzJqSWn2Dw6xev5XNuw4wlHM27zrA6vVbS6bf8MB2rrlgEVt299De2hx31iWo9BtGqb21mS27\ne0aljRcbceVVpFHGi/FKr9eyT4mIKuKSYuUK/hltLSXTF82dydkLOugbUMUpKeI6ePcNDHP2go5R\naePFhioaknXjxXil12vZp0REFXFJsXIFf2//UMn0F3v6WLtyKe3TVHFKirgO3u3Tmlm7cinnL5xN\nS5Nx/sLZ48aGKhqSdePFeKXXa9mnRAS1ES9Q+6/0mUgb8bUrlzCjrYWjWportedNVZtFSH/cxtnu\nOpfzkUvqhYpEpW2qjXj9pD1us2oybcQLr09gn0pV3CpmJah73KoiHmgnS7ZyBfxE08eRqgMDZCNu\na/ytJv3eRuc1QrFnYKKyELdpV2vZWcd9IFVxq5iVoO5xW3p4AJEEGe8sTKFHfnHP/HLpkjy1/lZx\nnKFWXEkW1FKmFmgfEKkvtRGXxNNoFVKK4kKkNtp3RJJDFXFJPI1WIaUoLkRqo31HJDlUEZfE02gV\n/3979x4nd13fe/z12dlLspsASUg4gRADXUgrEDawECiCgBAI2oACx6S1BC+gFk/CodjAQ4+mXqqI\nVcmxRUnhcLNBMaipQCNVUNtiJJh1E7SBFSNEUgKJYnaX7GZ2vueP33c2v53Mfefym5n38/GYx8x8\n5ze/+c7M5/eb73yvko7iQqQ4OnZEokMFcYk8TYsl6SguRIqjY0ckOjTSQiKvqcmY1tHKmmXdUZut\nQqpIcSFSHB07ItGhgrjUBI3Ul3QUFyLF0bEjEg3qmiIiIiIiUgUqiIuIiIiIVIEK4iIiIiIiVaCC\nuEReIuHoH4qTcP464aqdJSmAvj+R6tNxKBJNGqEhkVaNZcyldPT9iVSfjkOR6FKNuESalmKubfr+\nRKpPx6FIdKkgLpGmpZhrm74/kerTcSgSXSqIS6RpKebapu9PpPp0HIpEl/qIS6Qll2JO7duopZhr\ng74/kerTcSiZzLnp4by33f7Zt5YxJ41LBXGJNC3FXNv0/YlUn45DkehS1xSJhOTUWiOJBHv37R8z\nxVZyKeYm89f68agp2b6/qE+pFvX8SWnU+/ecSDgG94+oEC4SQSqIS9WNjCToH4rT3hKjf98I/+/f\nf83xH3mUa+7ZxO6B4br7UZRAckq1a+7ZFMnvOxmXE1tiPPdyP3f9+PlI5U9KI+pxmEuuPxG1/v5E\n6p0K4lJViYRj9+Aw77/vaY7/6KN84P6nuWz+LC45aaam2KpzUZ5SLRyXcz/6KKvWP8Nl82exduNv\nIpE/KZ0ox2Eu+RSya/n9iTQCFcSlIjLV2gzuH2HF2p4xPxIr1/Vy3XmdgKbYqmdRnlItHJeXnDST\nVYtP4KgpE7nqT+cwsUWnzXoS5TjMJHk+xWBgKM70yW0ZC9m1+P5EGknZflHM7C4z22VmW0Npq8zs\nt2bW4y+XhB672cz6zGybmV0USr/Yp/WZ2U2h9GPMbKOZPWdmXzezVp/e5u/3+cfnlOs9Sn6y1dpk\n+pHonDEJqPwUW4rbyonylGrJuFx88pHcuHAuq9Y/w9yPPsoH7/9ZJJv1FbfFi3IcppN6Pr35oS3c\nuHAui08+Eji4kB3l96e4FSlvjfjdwMVp0r/onOvyl0cAzOyNwBLgBP+cfzSzmJnFgH8AFgFvBJb6\nbQFu8fs6Dvgd8F6f/l7gd865TuCLfjuponDTaLJ2cWpHKwPDcfbtT/8j0bernzOPnVaNKbbuRnFb\nEckp1c48dhrNTXbQ913NAXTJwst153Wycl3vmBabFWt7otisfzeK26LkisMoSSQcA8Nxpna0smrx\nCaNd+MKtiKmF7Ii/v7tR3EqDK9v0hc65HxXwL/NS4AHn3BDwazPrA073j/U5554HMLMHgEvN7JfA\n+cCf+23uAVYBt/t9rfLp3wS+bGbmnItWFVYDSa1dXLmuNzSXbRdfedcpfOD+n42m3ba068BUWxUe\n3Q0U/uMAACAASURBVK+4rZxsU6ola/1S5z2e1tFakXhIFl6mdrTWRLO+4rZ4tTK1X7pj4pbL5wHw\nyJaddM6YlLaQHeX3p7gVqU4f8Q+ZWa9vkpri044CXgxts8OnZUqfBvzeORdPSR+zL//4a357KZFC\nayqz1S4uX9tDrKmJNcu6efbTi1izrJvDO9qINTVFbapCxW0ZZJraMFsrSiVqxpOFl8HheGSb9fOk\nuM1DuadILUXrTrpBl8ma8NPmTOX14RHWLOtO+2e1BqeAVdxKw6h0Qfx24I+ALmAn8Pc+Pd1ZwRWR\nnm1fBzGza81sk5lteuWVV7LlW7xipsJK1i52zpiUvnaxLRb1HwnFbYVl6qN97b1PV6yPdlOT0dHa\nHOVm/VwUtxFQqukDs42nWb10Pu2tsaiePwsVmbht1JiVyqpoQdw597JzbsQ5lwDWcKBZaQdwdGjT\nWcBLWdJfBQ4zs+aU9DH78o8fCow9ex3Izx3OuW7nXPf06dPH+/YawuD+EdZu/A2rFp/Atk8tYtXi\nE3JO6VbrtYuK2/EppjYweytK5aZeCzfrJ1tsKtU9ZrwUt9GQafrAffGRoloWw4LzZ7xmYjIfUYrb\nRo1ZqayKFsTNbGbo7tuB5Ejp9cASP5L5GOA44KfAU8BxfuRzK8FAjfW+H9fjwBX++cuA74T2tczf\nvgL4gfp9FS+1EDWhuYnL5s8araFMzq+ca0q3Wq5dVNwWr9jawJytKHn00S7VYM8abNYHFLdRka4m\n+4hD2tgfT/Dq3iGcg1f3DgUrCufRsph6/uxorZ2YzIfiVhpN2QZrmtla4FzgcDPbAXwcONfMugia\ngLYD7wdwzj1jZt8AfgHEgeuccyN+Px8CNgAx4C7n3DP+JVYCD5jZp4DNwJ0+/U7gPj+QYw/BQSlF\nSDc46LalXXx78w6efH43wGg/xTuuOpXJE3IXxqM6aChJcVta4dpAYLQ2cM2ybia1ZT79JGNlwLei\nJJ8PB1pRsj2/2oM9K01xG13JmuxwDN98yZ+wdyjOzQ9tGY3PW6+cR0tzE+2t6eO6Fs6fhVLcioDp\nT2Cgu7vbbdq0qdrZiJT+oTjX3LNpzA/ImcdOY9XiE7joSz8aTWtuMp799CKarHZ/ELyaewNRj9uE\ncxz/kUeJh2r6ComXYgvUmWI31x+AGqW4jbB0Mbzmqm6uuTdNfF7VzaQJdRefmdRU3NZrzM656eG8\nt93+2beWMSc1o+Rx2zBHvBQu12I7SfnUUEpjSlcbWEi8FFsLqNUEJSrSxnCm+GxTfIo0Gq3VLBll\nGhw0MBSvuX7eUh2lWEykmD7aUV5NUBpPagwPDmWIzyHFp0ijURWmZDSxuYmv/uWpdLQ107ernw1b\nd7J0wRvoaI3VVT9FKZ9q9WtN/gFI7dISXrVzcP+IYliqor01xuqlXazd+AIXnTiTzhmTGBiK5xz0\nLiL1RwVxSSuRcOwZ3H/QQM2p7S3EYk1MigU/GOqOIrkkawOhcvES5VU7RZqajKntrSxZMJsVa3sU\nhyINTH+/Ja10c9+uWNvD6/FEUfsr1VRyIvnKZ9XO8c5NrriWYr0eT7BibQ/TJ7fx8PKzuf99CxgY\nirMvru4pIo1EBXFJa7yD3cYUUPbF2btv/7hXlhPJJt9CcakGcpZqxURpTO2tMY44pI0bF85lw9ad\n9O3q5+ip7cRHHCMjxVV4iEjtUUFc0hrPYLeDCij3bmLvUJzpk9uqsjqi1L9CCsWlGshZypp1aTyD\nwyNcf8HxfHvzjjGLpL3/vqfZPag/dCKNQgXxBpRPzeF4ZrtIV0D58IO9XHde5+g2mkpOSmlffISB\noTj3v28BDy8/m+mT2zIWiksxkwtoikQZn/aWGLOntXPRiTNZua53TBeVwaERdVERaRAaaddg8h2o\nNp7ZLvKZf1xzj0upJBKOgZRVCm+5fB5feGxb2kJxqWZyGe8c6dLYmpqM/n1xOmdM4ohD2rjhwrms\nXNcbOi93MaFZs/lIdGjxn/JQjXiDKbY53TmHI78BaZma/l/cM6i5x2Vc0rXmBDHdMyamV67r5foL\njs/Y3STX3OTlbjUSgaDSYmAozvUXHM/Kdb1jYnjtxhcYGA5icHA4Tv8+DQoWqUeqtmkw2ZrTx8yt\nPDTCSCLBB+7/2Zhaxm9v3sHSBW/IOsVW+jmcu+hoa+bZTy/SvM1SlEytOVM7WtLG9Oxp7VBEeSVX\nq1H4OJnYEuPOq7uZ0KL5yKVwTU1GR2uMjraJrFp8Ap0zJtG3q58nf/Uq5//xEVx779PBgM6L5vLh\nB3s1zaFIHVKNeIPJVFu9b/9IzgGWK9f1ctGJM3PWoIeb/p/99CLWLOtmWkcb7a2FrY4oEpaxNSfT\n4MuhkaLiLFurUbqByANDI+BQXEtRzIzdA8OjgzVXrX+GRSfN5Nubd/Dk87v54LmdfPjBXg0KFqlT\nKog3mEzN6YkEeQ2w7JwxKa8BacUsSy6STabWnI625vRdRIocNJmt1UgzpUipDe4fYUVK16rrH+jh\nohNnAoyec8M0KFikfqhrSgOa2BLja9cs8DWGMKE5BkZeAyz7dvVrQJpUxeDwCMvP7xxdErxvVz8b\ntu5kcHikJIMvw6+TaRCmZkqRUss1uD15zp0+uY3rzuukc8YkXtwzyL79I7S36hwsUutUI95ARpvV\n701pVie/AZa3XD6PDVt3akCaVMXE5iaWnD57TBP+ktNnM7G5qaQtMNkGYZZqDnKRpEwxNTAU58xj\np3H7E3383z/v4m8unjsa+zc/tIUBDdoUqQt5FcTN7Kx80iTasjWrpy98dDHjkDae/fQi7rjqVI6a\nMoH3nH2sBglJVbweT7DigbFN+Cse6OH1eGlXIUw/xiGIec2UIqWWKaY6WmOsWdbNF97ZRVtzLE0/\n8R51iRKpA/m2a/1f4JQ80iTCsjWrN1n2uZUnT2gBYFKbGlGkOirZLSRZww6M6YJVqjnIRZKyxdSk\nWHC+7WhrVpcokTqVtSBuZmcCfwpMN7MbQg8dAugMUGNyLUCSqfAhEgVRWUBHx4mUWq6Yikrsi0jp\n5TqCW4FJfrvJofQ/AFeUK1NSHuH5vY84pI3rLzie2dPaGRwKpmVTrZ5EWfr56avTLWTMnPuqFZcy\na2+J8ZV3ncLvBvdz9NR2XtwzyJT2FnWJEqkDWQvizrkfAj80s7udc7+pUJ6kjJIzpvTvi3P3f/ya\n1T/o0wIRUhNydQupVOE414I/IuUwPJJgfc9vR2cNGhiK45wDFHMSPXNuergs+93+2beWZb/VlLXD\nr5l9yd/8spmtT71UIH9SpNQlukdGEqMzptzw9R72DAzzobccx+M3nsv0yW2aC1kqLtMy8tmWl880\nO8pBC+3cs4ndA8NlmVVCc4nXt2zxVy2D+0dYu/EFlp4+m7bm4Gd7z8AweyOSPxEpXq6uKff668+X\nOyNSGomEC2oD22K8uneIL/3bs7z8hyFuW9rFAxtfYPrkNm64cC4r1/WOWbr+C49t08AfqZiMy9W3\nt7BncH/Btc3hwjEwWjhes6w7rz60hdSmay7x+pVIOPbu2z/aBeTVvUNMaW9h8oSWqrZ2tLfGuPzU\nWQyNJLj5oS2jx8atV86jtblJ84mL1LBcU2Dc6q8vcc79MPVS7sxJYVLnCb/5oS3ccOFcpk9uY8Xa\nHi4/dRafuPQEjpoykVWLT+CSk2aOLl1//QXHay5kqZhstcrF1DaPp3CcWpt+14+fz1ojqrnE69dw\nfATMOHpqO327+lnf81v2DsXZF6/udzs4PMKhE1sPmsLwww/2kijt7J0iUmG5/kbPNLM3A4vN7AFS\nOqM5535WtpxJwdLVCq5c18vnr5xHwsHMwybywu5BVq1/hpf/MMQtl88D4JEtO5k9rR3UwikVkm25\n+mIK1Jlmldi3f4SEI2tNd/i4WXzykVw2fxbvv+/pjDXyURo0KqWTSDj+MBRnxdqeMa2FDz29g/e8\n6diq5q29JfPqx+1tmeNOg4pFoi9XQfxjwE3ALOALKY854PxyZEqKkyzcLD75yNGlkF/6/etMamvm\nA/f/bMyPy+e/t42V63pZtfgEXtk7xODQCJMmqHlTKiNTwXlgKF7UNG3pCsdfedcpDAzFWR4qWKXr\n5hL+U3DdeZ2sXNebtYtLJeYSVwGqMsKf88BwnAc2vnBQRcaqxSdkLexWQlOT0b9vf/pjI8O5W4OK\nRWpD1q4pzrlvOucWAZ9zzp2XclEhPGIGh0dYfn4nNy48sBTy33yzl71DcaZPbhttzly5rpfrzuvk\nqe176JwxKajNU/9WqaBsK1QWs3JlutUwY01NLF/bk7ObS7irSeeMSXnVyGcaNFoKlRx42shSP+dr\n732ay+bPYvHJR45ukzxHDg5Vv9tRe2szq5d2HbT6caZztwYVi9SGvJZJdM590swWm9nn/eVt+TzP\nzO4ys11mtjWUNtXMHjOz5/z1FJ9uZrbazPrMrNfMTgk9Z5nf/jkzWxZKP9XMtvjnrDYzy/Ya9SyR\ncODgQ285jpaY8fkr57HtU4tYtfgEHnp6B9ed1zm6bfLHJahpjKuGJEQxWxmZlpGPxZoyLi+flGlW\ni9TCcXtbfv3Gw4X/vl39Oft/l3tWjWIKUIrb7MZ8Z/viDA7HwWAgQyVFUrKVJgoVFcEx05ZybLTV\n9KBixa1IngVxM/sMsAL4hb+s8Gm53A1cnJJ2E/B959xxwPf9fYBFwHH+ci1wu3/tqcDHgQXA6cDH\nQwfN7X7b5PMuzvEadSl1kOYN3/g5Dvjrb/Swav0zXDZ/Fn80vWN0+9PmTOXFPYOsXjqfjtbS1ubV\ngbtRzFZEplrlbLXNhdQW5zuoMvynoHNGB7cdVOt4oEa+ErXVRRag7kZxm9ZB39m9m9gzMMwNX+/h\n5oe2cOPCuaO14MlKiuR3f9vSLjpao9MtqJCWmBoZVHw3iltpcHkVxIG3Ahc65+5yzt1FEMw5Z1V3\nzv0I2JOSfClwj799D3BZKP1eF/gJcJiZzQQuAh5zzu1xzv0OeAy42D92iHPuSResanBvyr7SvUbN\nyWeu5YHhOJu27+bzV86j52ML+do1C4iZ8eGL5o7W8vQPxcc0Z844pE014WkoZqsnn5rmQmqLkzXd\nN1xwHBuuP4df/d0lfPUvT2Vi88GnvWQBJ9bUxOEH1ToeOE6C+Zx/w6rFJ4y2OG3avpuB4dLVkBdT\ngGrEuM23ZWJffISBoTj3v28BDy8/m+mT2/jwg7188NzOg2rBk62Eye/+8I42YrF8fyZT8rZvbA18\npbsWFdvNq5IaMW5FUhUyOu8wDhwwh47jNY9wzu0EcM7tNLMZPv0o4MXQdjt8Wrb0HWnSs73GGGZ2\nLcG/ZWbPnj2Ot1Qemea0ndTWfNBcy7ct6aKpCa65d1NoYE4Xi08+kke27OSQiS08++lFGvhVnMjE\nLEQ3bsczwDDfgWWF1BY3NRlT21tYsmD2mJkwcg1YSxbKgYMGiE5saeKy+bNG5+Fffn4nS06fzbX3\nZp5lpVAlnJWlbuM233hJJBwDQ/Exc28n103onDEJOFALniyodrQeqHEuxshIgoHhETramnnu5X42\nbN3JO06dxeS25orOR16JQcVlEpm4jeq5VupLvmeazwCbzexxgikMzwFuLnFe0p0dMq3fmy09b865\nO4A7ALq7uyM3EmpffIS9KT8it145j5ZY00HTFK54oIfPvOOklNkeeg7MiuJnnSj2x0XSqnjMQjTj\ndrwzNOS7IE+m2VYyzaryejzBCj9gM9t+8zU4PDJmVpWLTpzJigdKt3+oSAGq5uM273jZPzI6YDe5\n3cp1vXzmHSfRt6sfCOLn9eGR4PMe5+ecSDh2Dw6nnQJxcddRxGJNFT0HZ/tTWYNURshTuZaXl/LI\n2ebmBzf8O3AG8JC/nOmce6DI13zZNxnhr3f59B3A0aHtZgEv5UiflSY922vUlESC9As4uPTzyR49\ntf2gtNFZUSLUHFmDFLM5jHeGhnxrugttbi/1gLXUec7znWWlUCWalaVu4zbveMmw3exp7dz+RN+B\n+GmNlWT2m8H9I6N//MIDQC86cSZHT22P1EDJCKvbuBVJJ2dB3Pet+rZzbqdzbr1z7jvOuf8ex2uu\nB5KjmpcB3wmlX+VHRp8BvOabjjYAC81sih+AsRDY4B/ba2Zn+D8LV6XsK91r1JSMsz60xdL2IX1x\nz+BBaZoVpSQUszmMt8BbzMDKTLOqFLPffKXuL59ZVqqobuM23+8103YDQ3G+8M6unPFTqEzHQeeM\nSby4ZzAqcRF1dRu3IunkOwrlJ2Z2WqE7N7O1wJPAXDPbYWbvBT4LXGhmzwEX+vsAjwDPA33AGuCv\nAJxze4BPAk/5yyd8GsAHgX/yz/kV8KhPz/QaVZfvAKNk38Ztn1rEhuvPGR3VHyzgED+oVvC2pV1M\nmhA7aI5ZzYpSmHqK2XJPsxc23gJvITXd+dYWJ6f0/No1C3jixnO5rOvIcQ9YS83nhq07uW1J5llW\nKqWe4jYf+cZLpu3C/cBLdX5MnrOf/fQitq66iP9YeR6LTz6S0+ZMpX8ozpT2FrVMpmi0uBVJx4IK\n7xwbmf0CmAtsBwYI+l4559y8suaugrq7u92mTZvK+hqFDDBK3e6Wy+fx7c07WLpgNtM62gDGDIyb\n2NzE0EiCRCKoSR8cCh5TIbwgNfdhZYrbSq+qV4rXK+Vqkunz00VHWzMTmsffDzj12Hs9nqjmgLi6\nidtC5BsvlVilNIi3oTGruN565TwmtDTR3NTEhOYmWscZd3Wopj6MSpQRSqWe+4hv/2zOCfvKreRx\nm2+N+CLgWIIl7f8MeJu/lgLk24823XYr1/Xy7jcdM7qAQ2qtYCzWRHtrM5Mm+LQJqglvZJVeVa/Q\nLiOZ9lGq1SrTv/8eEo5xHxfpjr1yrbIpmeUbL+VcBTUpPCg0PJ6nf99IUBBXy6SIZJB1GLWZTQA+\nAHQCW4A7nXPxSmSsHo13gFGH/zERyaUaq+pFaYaGWlhVUOpHpng7emo7OmWLSDa5asTvAboJCuGL\ngL8ve47q2HgHGGmgj+Sr0WOo0d+/VFameNMATRHJJVdB/I3OuXc5574KXAGcXYE81a3xDjDSQB/J\nV6PHUKO/f6msIN7GDtq99cp5GqApIjnlaj/en7zhnIub2tjylmmAULaFOsLPmdgS486ru5nQUlMr\noklEFLMozHhXxiz3gLhC1PCqglIDwvE+MBT35+xm7lzWzYTWYLB8UxPjHhgsIvUvV0H8ZDP7g79t\nwER/PzlryiFlzV2NyjWDRLp+tJmeM6E5VvX+tlKbCumzPZ5ZTyo9Q0u+otRnXepH9lmt3sCElhiT\nJijeRCQ/WbumOOdizrlD/GWyc645dFuF8AyyzViRaW7nSs9yIRI2nvirZuxWcq50EYB98REGhuLc\n/74FPLz8bKZPbhtdPVPnbBEplP62l0GmEfQTmpvoH4rT0dbMcy/3s2HrTpYueAPTOlo1y4NU1Xji\nL/ncxScfyXXnddI5YxJ9u/qZ2JLv7KjFiWpNvNSnRMIFXZzagmPir7/Rw8t/GOKWy+fxhce20Tlj\nks7ZIlKw8v5SNqh0I+iXn9/JnsFh3n/f08z96KOsWv8Ml82fxdqNv2Fw/4hmeZCqGk/8DQ6PsPz8\nTm5cOJdV658Zje/dA8PlXc1TrUhSIck/fdfcu4njP/IoNz+0hRsunDtaG379BcfTt6tf52wRKZgK\n4mWQbsaGq886hhUpCz4kmzPbW2Oa5UGqajzx194S4+qzjmHlut4x8b1ibU9ZC8VqRZJKybTI2nXn\ndfLU9j3MntbOhq07dc4WkYKpa0oZpJ2xIUOhoXPGJAaHR5jU1qxZHqRqxjPLSFNTsJJrpQvFyVr8\nJ5/fPZqWrJHU4EwppWzn79PmTGVwKM57zj5W52wRKZhqxMskvKxye0swxdW2Ty1iw/XnsPjkI4Gg\n0DAwFB+tQanEUswimYwn/grp2lKqAZZqRZJyCsfpwFCc5ed3jnk8uWDP6qXzaW9t1jlbRIqiaqMS\nSjeXMpB2qqvO6R0sWTCbjlbVoEjtSxaKUwdOphaKSznAspB5+dXCVD8q8b2mi9PblnQBsPoHfT5u\nu+hoa9Zc4SIyLiqIl0imAkZHW2y0byEw2rfwjqtOpaNVNShSH/Lt2hLuawuMDrBcs6y7qO4khc7L\nrxlValulvtd0cbrigR7uuOpUPvSW4/THTkRKRl1TSiTTDA6JBGn7FnaoGVPqTD5dWyo1wFIzqtSn\nSn2vmeK0Q10HRaTEVCNeIplO3BNbm/i3G97M0VPb6dvVzz883scre4c0oEwaUqUGWJa7wK9uL5WX\nSDhwcP/7FoyeS9f//KXy/JHTQGARqRCdUfKQz49uuhP38vM72T0wzM0PbRltRr31ynlMbmvWgDJp\nSPn2JS9W+Fj9txvezBcee5b1P38JKF1BSt1eyquQsTZAWSo2yh2nIiJJKojnkO+PbroT99VnHcP7\n73t6TD/DDz/Yy5qruvWDLQ1pPNMk5pLuWL31ynk0Gbz8h6GSFaRK3c9dDih0rM1n3nESHWWo2Chn\nnIqIhOlXI4d8f3QLmTs8uUSySCPKNMByvNIdq8k/vhglK0hpIaHyyXi+vao77Wc+e1o7OMpSQC5X\nnIpI5cy56eG8t93+2beWMSeZabBmDoX86KYOVtOy9SKVk+2PbykH1+m4Lp9s32Gmz1y11CJSy1QQ\nz2E8P7pacESkcipVQNZxXT4Zv8OhEX3mIlKX1N6Ww3gG7aifoUjlVGqAnY7r8sn4HbbGaG+N6TMX\nkbqjgngO4/3RVT9DkcqoZAFZx3V55PoO9ZmLSL3R2SwP+tEVqQ06VmufvkMRaSTqIy4iIiIiUgVV\nK4ib2XYz22JmPWa2yadNNbPHzOw5fz3Fp5uZrTazPjPrNbNTQvtZ5rd/zsyWhdJP9fvv889VZ0IZ\nF8Ws1CLFrdQixa00imrXiJ/nnOtyznX7+zcB33fOHQd8398HWAQc5y/XArdDcFACHwcWAKcDH08e\nmH6ba0PPu7jYTCYSjv6hOAnnrxOu2F1J7auJmK1nOh6LoritYQ0c84pbqXvVLoinuhS4x9++B7gs\nlH6vC/wEOMzMZgIXAY855/Y4534HPAZc7B87xDn3pHPOAfeG9lWQ5Epv19yzieM/8ijX3LOJ3QPD\njXQilOwiF7P1TMdjyShua4RifgzFrdSdahbEHfA9M3vazK71aUc453YC+OsZPv0o4MXQc3f4tGzp\nO9KkFyy80ls84UZXehvcr8U7GlBNxGw90/FYFMVtDWvgmFfcSkOo5pD0s5xzL5nZDOAxM/uvLNum\n67vlikgfu9Pg4L4WYPbs2WlfWMtZS0jVYxbyi9t6peOxKIrbGtbAMV/1uC1nzBay9DpUb/l1Kb+q\n1Yg7517y17uAbxH033rZNxnhr3f5zXcAR4eePgt4KUf6rDTpqXm4wznX7Zzrnj59etp8ajlrSYpC\nzPrXzxm39UrHY+EUt7WtUWM+CnGrmJVKqEpB3Mw6zGxy8jawENgKrAeSo5qXAd/xt9cDV/mR0WcA\nr/lmqQ3AQjOb4gdgLAQ2+Mf2mtkZfiT0VaF9FaTWlrNu4EE9ZVVLMVvPSnU8Nspxorgtr0rEUa39\nBpWC4lYaSbW6phwBfMvPFtQM/LNz7l/N7CngG2b2XuAF4Eq//SPAJUAfMAi8G8A5t8fMPgk85bf7\nhHMu2Yb3QeBuYCLwqL8UrJaWs04O6kldHnpaR2sk81tjaiZm61kpjscGO04Ut2VSqTiqpd+gElLc\nSsOwYMCwdHd3u02bNlU7G+PSPxTnmns28eTzu0fTzjx2GmuWdWuFuvzU3C9bPcRtpdXhcaK4rYI6\njKNKq6m4LXXMlrOPeKH7riWF9pUv5LPIc98lj9uoTV8o49DAg3pE8qbjREpBcSQipaCCeB1p1EE9\nIoXQcSKloDgSkVJQQTwPtTKwqxEH9UhmtRK3labjREqhlHGkY1WkcakjWw61NLCrQQf1SBq1FLeV\npuNESqFUcaRjVaSxqUY8h1pb1aypyZjU1kyT+WudyBtSrcVtpek4kVIoRRzpWBVpbCqI56ABOVKL\nFLcitUHHqkhjU9eUHJIDcsJTVCUH5GiKKokqxa1IbdCxKvmo5ykJC1GPn4NqxHPQwC6pRYpbkdqg\nY1Wksenvdg4a2CW1SHErUht0rIo0NhXE85AckAOoqVBqhuJWpDboWBVpXOqaIiIiIiJSBSqIi4iI\niIhUgQriIiIiIiJVoIK4iIiIiEgVqCAuIiIiIlIFKoiLiIiIiFSBCuJ1JpFw9A/FSTh/nXDVzpJI\nySnORTEgIvVAE5bWkUTCsXtgmOVrN/PU9j2cNmcqq5fOZ1pHqxaHkLqhOBfFgIjUCxXE68jg/hGW\nr93Mk8/vBuDJ53ezfO1m1izr1iIRUjcU56IYkCiac9PD1c6C1CB1Takj7a0xntq+Z0zaU9v30N4a\nq1KOREpPcS6KARGpFyqI15HB4RFOmzN1TNppc6YyODxSpRyJlJ7iXBQDIlIvVBCvI+0tMVYvnc+Z\nx06juck489hprF46n/YW1RJJ/VCci2JAROqFOtPVkaYmY1pHK2uWddPeGmNweIT2lpgGL0ldUZyL\nYkBE6oUK4nWmqclGBytp0JLUK8W5KAZEpB6oa4qIiIiISBWoIC4iIiIiUgUqiIuIiIiIVIEK4iIi\nIiIiVaCCuIiIiIhIFZhzrtp5iAQzewX4TY7NDgderUB2op4HqM98vOqcu7hE+6qIPOI2Kt9TLspn\n8RS30VLLeYfK5b+m4tbM9gLbqp2PKqn1mB6P1Pde8rhVQbwAZrbJOdfd6HlQPmpHrXw+yqeE1fLn\nXMt5h9rPf7k08uei917e966uKSIiIiIiVaCCuIiIiIhIFaggXpg7qp0BopEHUD5qRa18PsqnhNXy\n51zLeYfaz3+5NPLnovdeRuojLiIiIiJSBaoRFxERERGpAhXE82BmF5vZNjPrM7ObSrTP7Wa2i1XX\nUQAAD1ZJREFUxcx6zGyTT5tqZo+Z2XP+eopPNzNb7V+/18xOCe1nmd/+OTNbFko/1e+/zz/XfPpd\nZrbLzLaGtq3E66a+xv1p8rHKzH7rP5MeM7sk9NjNfp/bzOyiXN+NmR1jZhv9633dzFp9epu/3+cf\nnzO+b7IyqhUveeQrKvE0pci8KuYiJtPnW4HXPdrMHjezX5rZM2a2wqdHMp6zvI+YmW02s+/6+wXH\nZaliv15UKybHq5bOzyV+37V1LDvndMlyAWLAr4BjgVbg58AbS7Df7cDhKWmfA27yt28CbvG3LwEe\nBQw4A9jo06cCz/vrKf72FP/YT4Ez/XMeBRb59HOAU4CtFX7d1Nf4Wpp8rAJuTPNZvdF/7m3AMf77\niGX7boBvAEv87a8AH/S3/wr4ir+9BPh6tWMsyvGSR76iEk+3FJlXxVyELtk+3wq89kzgFH97MvCs\nj4NIxnOW93ED8M/Ad4uJy1LGfj1cqhmTJch7zZyfS/y+a+pYrnqgRP3iP+gNofs3AzeXYL/bObhg\ntQ2YGQqkbf72V4GlqdsBS4GvhtK/6tNmAv8VSk/dbk7KgVn21033GmnysYr0haIxnzmwwX8vab8b\nf2C8CjSnfofJ5/rbzX47q3acRTle8shbJOKpyLwq5iJ0yfT5Vikv3wEujHI8p8nzLOD7wPnAd4uJ\ny1LGfj1cohSTReY/9ZxXM/Fcws8g0seyuqbkdhTwYuj+Dp82Xg74npk9bWbX+rQjnHM7Afz1jBx5\nyJa+o4A8V+J1M71Gqg/5pqG7Qk06heZjGvB751w8TT5Gn+Mff81vH3VRipdcohRP+VDMRUe5zrcF\n8d005gMbqa14/hLwN0DC3y8mLksZ+/UgEjFZQrUUz+NWC8eyCuK5pesr60qw37Occ6cAi4DrzOyc\nIvJQaHqhKv26twN/BHQBO4G/L0M+yvV9llstxEsuUcyXYi5aqv5ZmdkkYB1wvXPuD9k2TZNWtXg2\ns7cBu5xzT4eTs7xmqfJf9e+szOr9/SXV3fdeK8eyCuK57QCODt2fBbw03p06517y17uAbwGnAy+b\n2UwAf70rRx6ypc8qIM+VeN1MrzHKOfeyc27EOZcA1hB8JsXk41XgMDNrTpOP0ef4xw8F9hz0iURM\nxOIll0jEUz4Uc5FTlvNtvsysheCH+2vOuYd8cq3E81nAYjPbDjxA0D3lSxQel6WM/XpQ1Zgsg1qJ\n53GppWNZBfHcngKO86PCWwkGtawfzw7NrMPMJidvAwuBrX6/y/xmywj6NeHTr/Ije88AXvNNHhuA\nhWY2xTepLyToy7YT2GtmZ/iRvFeF9pVOJV4302uEP5eZobtv959J8rlLLBjlfwxwHMFAibTfjQs6\nZz0OXJHhPSXzcQXwA799ZEUwXnKJRDzlQzEXOSU/3+bLx9idwC+dc18IPVQT8eycu9k5N8s5N4fg\nc/uBc+4vKDwuSxn79aBqMVkmNRHP41Fzx3K1Os/X0oVgRO2zBCOnP1KC/R1LMPL658AzyX0S9LX7\nPvCcv57q0w34B//6W4Du0L7eA/T5y7tD6d0EhYpfAV+G0cWb1hI0we8n+Ff33gq9buprrEuTj/v8\n6/T6YJ4Z2u9H/D63EZrRI9N34z/jn/r8PQi0+fQJ/n6ff/zYasdXlOMlj7xFJZ6mFplXxVzELpk+\n3wq87psImpd7gR5/uSSq8ZzjvZzLgVlTCo7LUsV+vVyqFZMlyHfNnJ9L/L5r6ljWypoiIiIiIlWg\nrikiIiIiIlWggriIiIiISBWoIC4iIiIiUgUqiIuIiIiIVIEK4iIiIiIiVaCCeISZ2YiZ9ZjZVjP7\nFzM7LPTYcWb2UwuW5v63lOeda2avmdlmM9tmZj+yYNW1dK9xhJl918x+bma/MLNHKvC+tpvZ4eV+\nHSkfM3u7mTkz++MMj99tZlekeyzD9kea2Tfz2O6R8HGQ5vHrzaw939cNPe9qMzsydP+fzOyNhe5H\nqs/H5X2h+81m9oqZfbfA/ZxbyHPMrMvMLgndX2xmNxXymln2fYaZbfS/B780s1Wl2G+W15tjZltz\nbym1LKWM8WCh504zu9LH4+Nm1m1mq336uWb2p+XJdf1RQTzaXnfOdTnnTiRY8ey60GM3Abc75+YB\n16R57o+dc/Odc3OB5cCXzewtabb7BPCYc+5k59wb/X5FclkK/DvB4hbj5px7yTmXs+DunLvEOff7\nLJtcD6T9MTGzWJbnXQ2MFsSdc+9zzv0iV34kkgaAE81sor9/IfDbQnZgB1aJLEQXwVzFADjn1jvn\nPlvEftK5B7jWOdcFnAh8o0T7lcYWLmMMAx8IP+gXuMlWTnwv8FfOufOcc5ucc8t9+rmACuJ5UkG8\ndjwJHBW6P4xfYtU59+tsT3TO9RAUuD+U5uGZBBP9J7fthdF/tD8ys2/5mvKvJA9IM1toZk+a2c/8\nv+hJPn27mf2tT9+SrC01s2lm9j1fQ/9VgsnzpUb57/ssgpPwEp9mZvZlHysPAzNC2283s7/zMbPJ\nzE4xsw1m9isz+4DfZrQGztdOP2Rm/2pmz5nZ51L2dbgFq40+7FtytprZO81sOUFh+nEze9xv329m\nnzCzjcCZZvYxM3vKP+cOn+8rCBZn+JqvHZpoZk+YWbffx1Ifz1vN7JZQXvrN7NM+Dz8xsyPK+sFL\nIR4F3upvLyVY2AQAMzvdzP7Tn4/+08zm+vSr/fnsX4DvhXdmZqf57Y/1sXeXj6PNZnapBSsufgJ4\np4+hd/r9fdk//24zW+1f73kfc5hZk5n9o5k9Y0HL5COWviVpBsHCLDjnRpJ/Es1slZndZ2Y/8MfK\naKWMmX3Y57HXzP7Wp82xoAZzjX/N75n/w2Jmp/pYfpKxlT7SGH4MdIZi5B+BnwFHpzsHmtnHCBbO\n+YqZ3Wq+BcnM5hAU6P+3PxbOrtL7qR3VXvlJl6yrQ/X76xjBamUXhx67EXgVeFua552LX1UtlNZF\nsNxr6rYXAb8nWKL4I8CRoX3sI1gxLQY8RrCE8eHAj4AOv91K4GP+9nbgf/nbfwX8k7+9OrTNWwlW\nvDq82p+vLkXH5buAO/3t/wROAd7hYyRGUBj+PXBFKC4+6G9/kWC1s8nAdGCXT58DbPW3rwaeBw4l\nWP3vN8DRoX0dDlwOrAnl6dDw46F0B/zP0P2podv3AX/mbz/B2NXUniAonB8JvODz2gz8ALgstO/k\n8z8HfLTa340uwXkTmAd808dPD2NXmjwEaPa3LwDWheJuBwdW2zsX+C5Bzd7TwGyf/nfAu/ztwwhW\nXOzwz/9yKB+j94G7Cc7hTcAbgT6ffgXwiE//H8DvksdNynv6mH/sW8D7gQk+fRXBirsT/XHxoo/Z\nhcAdBJUeTf59nOOPszjQ5Z//jdB76QXe7G/fij8edanfCwfKGM0ES7F/0MdIAjjDP5btHDh63kw5\nxlYBN1b7/dXKRTXi0TbRzHqA3cBUgoIOZnYKQRPofOBWM/tTX7P3vJllqm1Om+6c20BQ2F4D/DGw\n2cym+4d/6px73jk3QlCj9CbgDIIfkv/weVsGvCG0y4f89dMEBzQEPwD3+9d7mOAHRWrXUuABf/sB\nf/8cYK0LauteIjhZh63311uAjc65vc65V4B9lr7P9/edc6855/YBv2BsjCX3c4GZ3WJmZzvnXsuQ\n1xFgXej+eRb0td0CnA+ckOO9ngY84Zx7xTkXB77m3ysErVLJPsTheJcqc0HL3hyC2Ewd93Io8KBv\ngfkiY2PgMefcntD9PyEo0P6Zc+4Fn7YQuMmf/54gKOzPziNb33bOJVxQm51sPXkT8KBP/2+CCpF0\n7+cTBH8Mvwf8OfCvoYe/45x73Tn3qn/+6T6PC4HNBLWafwwc57f/tQtaScHHrZkdChzmnPuhTx/t\nYy91LVnG2ERQ2L7Tp//GOfcTfzvbOVBKoJh+cFI5rzvnuvxJ8rsEzYWrCWpxfuSce9HM3k5QyPkK\n8IhzzmUoi88HfpnuAf/D88/AP1swOOkcgsK/S92UoED/mHNuaYY8D/nrEcbGV+q+pAaZ2TSCAuyJ\nZuYIasAdQU1dtu84GReJ0O3k/XTnofA2qbGEc+5ZMzuV4A/pZ8zse76wkmqf/yOJmU0A/pGgBudF\nCwa8TciSZ8jejWq/89U/6fIoVbce+DxBTd20UPongcedc2/3zehPhB4bSNnHToIYmQ+85NMMuNw5\nty28oZktyJGfcExbynVOzrlfAbeb2RrgFX8sQubz9Gecc19NyeMcDj62JvrtdY5uPK+7YNzBKF9+\nCB8H6kpaZqoRrwG+tm85cKOZtRDUclxqZoc65/6LoBnx7/G1zqnMbB7wf4B/SPPY+eZHSpvZZOCP\nCP4ZA5xuZsdY0Df8nQSD834CnGVmnf457WZ2fI638CPgL/z2i4Apeb95iZorgHudc29wzs1xzh0N\n/JpgMPESM4uZ2UzgvHJmwoIZTgadc/cTFLZO8Q/tJej2kk6y0P2qBf3cw31xMz1vI/BmC/qlxwhq\nWH+YZjuJnruATzjntqSkH8qBwZtX59jH7wm60/2dmZ3r0zYA/yvZ+mhm8316ttjL5N+By31f8SMI\n/jQcxMzeGmrtPI6gAJ0ctHypmU3wBfNzgad8Ht9jB8bvHGVmM8jABQOgXzOzN/mkvyjwfUj9KuYc\nWMyx0LBUg1MjnHObzeznwBLn3H1mdj/wEzMbJCgIvRu4OzQw4mwz20wwg8QuYLlz7vtpdn0qwYwq\ncYI/Zv/knHvK/+g8CXwWOImgMP0t51zCzK4G1ppZm9/HRwn6SWbyt377nxEcwC9k2VaibSlBTISt\nI2jCf46gy8izlL+wehJBt6wEsJ+gbyME3QgeNbOdzrkxfwacc7/3tYlbCPqSPxV6+G6CQUevA2eG\nnrPTzG4maPI3glan75TnLUkpOed2ALeleehzwD1mdgMHd6FKt5+XzezPCOLqPQQ16l8Cen3heDvw\nNoIYSXZZ+Uye2VwHvAXYSnDcbATSdbP6S+CL/nwfB/7COTfiy+Y/BR4m6B7zSd817CUz+xPgSb9N\nP8HYjpEseXk3cJd/jQ155l/qXJHnwH8BvmlmlxKMG/txufNZy+xAy6rIAb4gfqNzLu384yIiMn5m\nNsk51+9rtH8KnOX7i+fz3FUEA+4+X848ikj5qEZcRESker7rByy3EtRo51UIF5H6oBpxEREREZEq\n0GBNEREREZEqUEFcRERERKQKVBAXEREREakCFcRFRERERKpABXERERERkSpQQVxEREREpAr+P2hC\nKtjOVFxBAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a8ebc18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Displays only the numeric column. Let's how the avg Profit plays for each State."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'Profit')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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00AU4++RCnNE1JF0AvJTqXhq/bl1ENd//hY0UFsMm6QGqn92/A1fZvqvZimK4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\nonYJm4iIqF3CJiIiapewiYiI2v0vQSpPJWbCf0wAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11ed84978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.groupby(\"State\").Profit.mean().sort_values().plot.bar(title = \"Avg Profit by State\")\n",
    "plt.xlabel(\"State\")\n",
    "plt.ylabel(\"Profit\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Avg Profit is highest in state of Florida and least in California.\n",
    "\n",
    "Let's create the y vector containing the outcome column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 192261.83,  191792.06,  191050.39,  182901.99,  166187.94,\n",
       "        156991.12,  156122.51,  155752.6 ,  152211.77,  149759.96,\n",
       "        146121.95,  144259.4 ,  141585.52,  134307.35,  132602.65,\n",
       "        129917.04,  126992.93,  125370.37,  124266.9 ,  122776.86,\n",
       "        118474.03,  111313.02,  110352.25,  108733.99,  108552.04,\n",
       "        107404.34,  105733.54,  105008.31,  103282.38,  101004.64,\n",
       "         99937.59,   97483.56,   97427.84,   96778.92,   96712.8 ,\n",
       "         96479.51,   90708.19,   89949.14,   81229.06,   81005.76,\n",
       "         78239.91,   77798.83,   71498.49,   69758.98,   65200.33,\n",
       "         64926.08,   49490.75,   42559.73,   35673.41,   14681.4 ])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = df.Profit.values\n",
    "y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create dummy variables for categorical feature."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>R&amp;D Spend</th>\n",
       "      <th>Administration</th>\n",
       "      <th>Marketing Spend</th>\n",
       "      <th>State_Florida</th>\n",
       "      <th>State_New York</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>94657.16</td>\n",
       "      <td>145077.58</td>\n",
       "      <td>282574.31</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>91992.39</td>\n",
       "      <td>135495.07</td>\n",
       "      <td>252664.93</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>20229.59</td>\n",
       "      <td>65947.93</td>\n",
       "      <td>185265.10</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>46014.02</td>\n",
       "      <td>85047.44</td>\n",
       "      <td>205517.64</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>23640.93</td>\n",
       "      <td>96189.63</td>\n",
       "      <td>148001.11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>100671.96</td>\n",
       "      <td>91790.61</td>\n",
       "      <td>249744.55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>61136.38</td>\n",
       "      <td>152701.92</td>\n",
       "      <td>88218.23</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>73994.56</td>\n",
       "      <td>122782.75</td>\n",
       "      <td>303319.26</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>22177.74</td>\n",
       "      <td>154806.14</td>\n",
       "      <td>28334.72</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>27892.92</td>\n",
       "      <td>84710.77</td>\n",
       "      <td>164470.71</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    R&D Spend  Administration  Marketing Spend  State_Florida  State_New York\n",
       "17   94657.16       145077.58        282574.31              0               1\n",
       "13   91992.39       135495.07        252664.93              0               0\n",
       "38   20229.59        65947.93        185265.10              0               1\n",
       "35   46014.02        85047.44        205517.64              0               1\n",
       "42   23640.93        96189.63        148001.11              0               0\n",
       "11  100671.96        91790.61        249744.55              0               0\n",
       "31   61136.38       152701.92         88218.23              0               1\n",
       "22   73994.56       122782.75        303319.26              1               0\n",
       "44   22177.74       154806.14         28334.72              0               0\n",
       "41   27892.92        84710.77        164470.71              1               0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_features = df.iloc[:, 0:4]\n",
    "df_dummied = pd.get_dummies(df_features, columns=[\"State\"], drop_first=True)\n",
    "df_dummied.sample(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "State column has been replaced by two additional column - one for Florida and one NY. First value in the categorical values CA has been dropped to avoid collinearity issue.\n",
    "\n",
    "Now, let's create X feature matrix and y outcome vector.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 165349.2,  136897.8,  471784.1,       0. ,       1. ])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = df_dummied.values\n",
    "X[0, :]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's normalize the feature values to bring them to a similar scale."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2.073486</td>\n",
       "      <td>0.560753</td>\n",
       "      <td>2.260465</td>\n",
       "      <td>-0.685994</td>\n",
       "      <td>1.393261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.009412</td>\n",
       "      <td>1.082807</td>\n",
       "      <td>2.004818</td>\n",
       "      <td>-0.685994</td>\n",
       "      <td>-0.717741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.796193</td>\n",
       "      <td>-0.728257</td>\n",
       "      <td>1.675110</td>\n",
       "      <td>1.457738</td>\n",
       "      <td>-0.717741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.585002</td>\n",
       "      <td>-0.096365</td>\n",
       "      <td>1.448347</td>\n",
       "      <td>-0.685994</td>\n",
       "      <td>1.393261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.532256</td>\n",
       "      <td>-1.079919</td>\n",
       "      <td>1.292210</td>\n",
       "      <td>1.457738</td>\n",
       "      <td>-0.717741</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          0         1         2         3         4\n",
       "0  2.073486  0.560753  2.260465 -0.685994  1.393261\n",
       "1  2.009412  1.082807  2.004818 -0.685994 -0.717741\n",
       "2  1.796193 -0.728257  1.675110  1.457738 -0.717741\n",
       "3  1.585002 -0.096365  1.448347 -0.685994  1.393261\n",
       "4  1.532256 -1.079919  1.292210  1.457738 -0.717741"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scaler = StandardScaler() \n",
    "X_std = scaler.fit_transform(X)\n",
    "pd.DataFrame(X_std).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Split the X and y into training and test sets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X_std, y, \n",
    "                                                    test_size = 0.3, random_state = 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training set:  (35, 5) (35,)\n"
     ]
    }
   ],
   "source": [
    "print(\"Training set: \", X_train.shape, y_train.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test set:  (15, 5) (15,)\n"
     ]
    }
   ],
   "source": [
    "print(\"Test set: \", X_test.shape, y_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ratio of the size of the training data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.shape[0] / df.shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Fit linear regression model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=1, normalize=False)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr = LinearRegression()\n",
    "lr.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(111827.94141541519,\n",
       " array([ 36952.9979,  -1074.4562,   1885.608 ,    894.426 ,   -442.6833]))"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr.intercept_, lr.coef_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By looking at the cofficients, we can conclude that R&D Spend has the higest influence on the outcome variable.\n",
    "\n",
    "Predict the outcome based on the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "y_test_pred = lr.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>actual</th>\n",
       "      <th>prediction</th>\n",
       "      <th>error</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>156122.51</td>\n",
       "      <td>159019.628029</td>\n",
       "      <td>-2897.118029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>90708.19</td>\n",
       "      <td>71812.853004</td>\n",
       "      <td>18895.336996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>89949.14</td>\n",
       "      <td>86017.265670</td>\n",
       "      <td>3931.874330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>103282.38</td>\n",
       "      <td>100397.875646</td>\n",
       "      <td>2884.504354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>69758.98</td>\n",
       "      <td>54763.007516</td>\n",
       "      <td>14995.972484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>14681.40</td>\n",
       "      <td>98569.217498</td>\n",
       "      <td>-83887.817498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>156991.12</td>\n",
       "      <td>161629.007963</td>\n",
       "      <td>-4637.887963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>96778.92</td>\n",
       "      <td>96063.934484</td>\n",
       "      <td>714.985516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>118474.03</td>\n",
       "      <td>113044.675267</td>\n",
       "      <td>5429.354733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>71498.49</td>\n",
       "      <td>65850.551449</td>\n",
       "      <td>5647.938551</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>192261.83</td>\n",
       "      <td>190878.953160</td>\n",
       "      <td>1382.876840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>144259.40</td>\n",
       "      <td>134066.474864</td>\n",
       "      <td>10192.925136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>124266.90</td>\n",
       "      <td>128219.404807</td>\n",
       "      <td>-3952.504807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>64926.08</td>\n",
       "      <td>41824.481655</td>\n",
       "      <td>23101.598345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>81229.06</td>\n",
       "      <td>63796.209758</td>\n",
       "      <td>17432.850242</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       actual     prediction         error\n",
       "0   156122.51  159019.628029  -2897.118029\n",
       "1    90708.19   71812.853004  18895.336996\n",
       "2    89949.14   86017.265670   3931.874330\n",
       "3   103282.38  100397.875646   2884.504354\n",
       "4    69758.98   54763.007516  14995.972484\n",
       "5    14681.40   98569.217498 -83887.817498\n",
       "6   156991.12  161629.007963  -4637.887963\n",
       "7    96778.92   96063.934484    714.985516\n",
       "8   118474.03  113044.675267   5429.354733\n",
       "9    71498.49   65850.551449   5647.938551\n",
       "10  192261.83  190878.953160   1382.876840\n",
       "11  144259.40  134066.474864  10192.925136\n",
       "12  124266.90  128219.404807  -3952.504807\n",
       "13   64926.08   41824.481655  23101.598345\n",
       "14   81229.06   63796.209758  17432.850242"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output = pd.DataFrame({\"actual\": y_test, \"prediction\": y_test_pred})\n",
    "output[\"error\"] = output.actual - output.prediction\n",
    "output"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A simpliest prediction model could have been the average. Let's how the model did overall against one feature."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x11f0cb518>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Yf38OnBYRsyJiFjAxxzozO29baDpwV0SMBe7KnwHOAMbm1zTgekhJB7gSOBZ4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\nZlbVnKjMzKyq/f8nFiO5uM0nGAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11f0742b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "X_test_inv = scaler.inverse_transform(X_test)\n",
    "plt.scatter(X_test_inv[:, 0], y_test, alpha = 0.3, c = \"blue\", label = \"Actual\")\n",
    "plt.scatter(X_test_inv[:, 0], y_test_pred, c = \"red\", label = \"Predicted\")\n",
    "\n",
    "plt.xlabel(\"R&D Spend\")\n",
    "plt.ylabel(\"Profit\")\n",
    "plt.title(\"Profit Actual vs Estimate\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "579577930.69277871"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean((y_test_pred - y_test) ** 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "y_train_pred = lr.predict(X_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compare the root mean squared error (RMSE) of test dataset against the training."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test rmse:  24074.424825793423 \n",
      "Training rmse: 12413.672826747377\n"
     ]
    }
   ],
   "source": [
    "print(\"Test rmse: \", sqrt(mean_squared_error(y_test, y_test_pred)), \n",
    "      \"\\nTraining rmse:\", sqrt(mean_squared_error(y_train, y_train_pred)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "r2 score can have a max value 1, negative values of R2 means suboptimal model "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.69192474547582505, 0.89284947669793391)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r2_score(y_test, y_test_pred), r2_score(y_train, y_train_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On the training the both RMSE and R2 scores perform natually better than those on the test dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's calculate R2 score manually. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.89284947669793391"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SSR = np.sum((y_train - y_train_pred) ** 2)  # Sum of squared residuals\n",
    "SST = np.sum((y_train - np.mean(y_train_pred)) ** 2) # Sum of squared totals\n",
    "R2 = 1 - SSR/SST\n",
    "R2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "R2 can be viewed as (1 - mse/variance(y))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Significance Scores for feature selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.feature_selection import f_regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.    ,  0.2718,  0.0001,  0.3377,  0.9174])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_, p_vals = f_regression(X_train, y_train)\n",
    "p_vals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>feature</th>\n",
       "      <th>p_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>R&amp;D Spend</td>\n",
       "      <td>2.608341e-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Administration</td>\n",
       "      <td>2.718478e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Marketing Spend</td>\n",
       "      <td>6.395756e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>State_Florida</td>\n",
       "      <td>3.377138e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>State_New York</td>\n",
       "      <td>9.174009e-01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           feature       p_value\n",
       "0        R&D Spend  2.608341e-17\n",
       "1   Administration  2.718478e-01\n",
       "2  Marketing Spend  6.395756e-05\n",
       "3    State_Florida  3.377138e-01\n",
       "4   State_New York  9.174009e-01"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame({\"feature\": df_dummied.columns, \"p_value\": p_vals})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "p-value indicates the significant scores for each feature. p-value < 0.05 indicates, the corresponding feature is statistically significant. We can rebuild the model excluding the non-significant features one by one until all remaining features are significant.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Power Plant Dataset\n",
    "Let's look at another dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AT</th>\n",
       "      <th>V</th>\n",
       "      <th>AP</th>\n",
       "      <th>RH</th>\n",
       "      <th>PE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>14.96</td>\n",
       "      <td>41.76</td>\n",
       "      <td>1024.07</td>\n",
       "      <td>73.17</td>\n",
       "      <td>463.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>25.18</td>\n",
       "      <td>62.96</td>\n",
       "      <td>1020.04</td>\n",
       "      <td>59.08</td>\n",
       "      <td>444.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5.11</td>\n",
       "      <td>39.40</td>\n",
       "      <td>1012.16</td>\n",
       "      <td>92.14</td>\n",
       "      <td>488.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20.86</td>\n",
       "      <td>57.32</td>\n",
       "      <td>1010.24</td>\n",
       "      <td>76.64</td>\n",
       "      <td>446.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10.82</td>\n",
       "      <td>37.50</td>\n",
       "      <td>1009.23</td>\n",
       "      <td>96.62</td>\n",
       "      <td>473.90</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      AT      V       AP     RH      PE\n",
       "0  14.96  41.76  1024.07  73.17  463.26\n",
       "1  25.18  62.96  1020.04  59.08  444.37\n",
       "2   5.11  39.40  1012.16  92.14  488.56\n",
       "3  20.86  57.32  1010.24  76.64  446.48\n",
       "4  10.82  37.50  1009.23  96.62  473.90"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"/data/Combined_Cycle_Power_Plant.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "X = df.iloc[:, 0:4].values\n",
    "y = df.PE.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x11ee225c0>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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VF3t1sUTMAr4+KRM9OpuxOD8TQUHCgF/vwOzRqZh6T1+8Ny0HrYEg7CyDsxf9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\nn4lpRf305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qnsOBD1TAtJlIZcN3OU6bV172zHlBE5aGj2w2nlEAhLkGQFb04eqvN6Wz/1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hvB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zd380FMHNoT/TLdlDnx0Y37cSEUQcngLPxXaT7t3mR4dLbn8UOyaaKT1z0FqqZhUlFPPLxh\nHwKSAjGimvaae9dU49T5MP604xiCERlfXBBpPJ6+photoQj8kpyMyRZGhOAf3rAPJfnZ8IXluH3+\nwXU16JeZAl9YhhZN+j4+eg7335CHh6Kdilk3D8SjG/djwGNvY+3Hx6EBcNp4vDp9BN6ffQMyU+x4\ncF0Npo3qg78/fAPEiIIbB2Xh/rW7MWt9DVqCEUwd2RsBUcaMMXkoLczBtpnX4cj88Xh31vU40xLC\nizuOISApljqCBG5H7o3c+8Mb9uHWoT3BMgwkWcX5gARN02DnWcysqqH+80VrmB7K2tOsvKq3Ln+S\nmWLH+7NvoD5L1ieg5zT9urlxLijh56/o6/jN3SchRlRMX7OLrguyZsi1Pz56LmGO5HHwKMnPNnX7\nruqdjuaARHO4pFnbN83RiITE0SYfXphWjKduzYdTYGHjWLx6zwhUP3EzwhFrXyQMsXWNAWw7cAbT\nRvUxaUzWNfoTal8ebvBj897T9Pf9Mt2YWzoYR+aPx7aZ16G0MEc/+As8GDAIiApe+ffheHT8ILoG\nH3l9H84FJKiahu6pdhqTG6J5sFFn0i/KmFTU07Rm7r8hj8bgYETPgWeMyYtqbNsxbVQfKCri1tuD\n62q+NGf+Ni15CLQwJ89hWYUuUHo+IMaJlS6v0Gm6P5wzGnXzxqGrS0BuhssU2GJFXomV5GfTqtX9\nN+TFbR5z3tiHh0sGYvYt+gZBKiqxAT4cUbDmo+MY+Lh+eFRUYN3OetO13qg+AY/Dhlenj8D22Tdg\nojcHI/tmoKvLhvLhuZi7+SAGPPY27l+7G+XDczHrpv70M/7+Di+cAkcTq3vXVCMiq9hxuAmnW8K4\nf+1uU8KSl+mmVfNEFTZZVuELRxCWVTxYFbMQqi7tQkha0pJ2eVlI1rtgJfnZcWLED2/QxYhJPNPR\nCqewqKwAb/5iJH6Y0wUvfdh2eHx803647RwWTCowxfoFk3SWz5F9M5DX3YOx+VkYPyQb96/djQGP\nvY37XqmGrGlYMWUYZt3Un8bozBQ7nptahCPzx+ODR0Zj4tAeNLklMXPTnpOYf+sQBCXFUkw5GFGw\nvNyLj4+cxdzSwchKdWBSUU947BxCEQX3Ga5HkmPS4Xh0434IPIusVDt6pbugasBDUTig8T1K8rPh\nDyuYvcH8u4de2/uVCnrfRyNC8KQYm0gw3ePQn2fUSSOdsTljB0LVNKy9Rz/wTRvVG+eDEqav2UUT\n0jljr0RWqh0eBw8NgC+KKoo9QN67phqVo3rjP8ddSQsJj27cDxvP4q4fXYH7ov69vCI+jxE4lnbN\njffutvPw2DkomoZHN+7HmQvhuD3buMaIflvs2iGPZ6YImDcx36QFR3wW0JPlYEQxJcglURZRK5Hx\nBZMK8Oz7OsKpvQMoISIxfmZF1bByyrDvjQTANzESW79ujkZmBa/tnwl/dLb11Hk9XxwQzVX9kow/\n3Gn2lcVlhVT3tF+mG+UjcvHztdVwChz+fqgRyyu82HbgDLq6bFhUZo7Rz0wuxIrtdRjZNwNugcMf\n7xyK5oBEGy12XpeU+OCR0WgNRSBH4aAsyyAkKchMsZsOZARhQWJyF6cQl6c/vGEfujgF+rljO5Ue\nB4+dv74R5SNy8dKHx1DX6IfHwcNp4/DCtGLM/bcfml57KbvSyX64hfE8i3SnQKEUEVmlQ9tErPT6\nAd2pALCRjYoMuMaKvBIzihgbfyb26fFm9OjqpJWzZ9+vw/Jyb9ww7O/v8KKuKWBaoHNLB9PZv9LC\nHEwc2hM/N5AfLK/wwi3wuBCKmOYDyOtXVRZFBVh1OJBxzoA8J1ZuggTmVZVFmDEmD76wLg7qC0fo\nYDCFGUV05q4HxvTvkLo9SUta0i4fI1D9RHE0N8NFBeIJnL3mRAt+NzGfzg4aIUP/VToY6W4b1d1r\nahWx/tN6lBX3wsqpRQhJCo2pscLTz945FHcMz8XMqIixFVGHMdkg8DenwIGJ3m9pYQ6dCa9r9MNt\n4xASFYy5MssEQV1VWZQQTtfkE+EP6yiVGetq8PRtQxAQ5XYRJeRnq+9PVTX4whE6/52E7bcJwZOD\nhtU+T8iHmgMS0lw2Co3zh/WuncCzmL3BDOPdWH3S9DedvWEvFYyfu/kg1buzgrq1BCOmWSmjIPqr\n00dQaYUlkwuR1cWB+nNBPPXWZ5RhXNXaoNPGfTwg6klyIpF34xpLdwt4rrIIHoFHa1hn/SzJz0b1\n580o6p1uhsBFNeSWlnsx6+YByEyxw2HjTO/R3rqeWVVD73fbgTMmQXHjiMoPru4Dh8Dhn78bi5Pn\nQ5BkXQZrWYUX7ovsF53JSGyNjUkugUNYkul8K2FCBgCH0CaBwoChOWkcLHNdDRbeXkDh7yeag+jq\nsuGn1/SBJCsISG3FgLpGP64f0B2qBpR6e8DG6V1FEqP9YRmhiEKJu3731md4dNyVdC5w1s1m+P6K\nKcMQiEJBrUhpyAEOAFZMGYZNe05R+LDRCKyYGIkF5Gd/WIbAs5BkFRUjcjFjnVncflJRT9w6tAc8\nDhtONAcRlpRLBr//fkfzdkxV9WoBwzCQFA3n/BLuWr0TS/56CKMHZtEq3H0GCCfZjB8YnYdtB84g\nzaJq4TfASxNVsAj854kJg/BwyUA4BS6uEvGr9TV4YHQbhNO4oQNt0CXja2asq4Gsacjq4rB2aoHH\nrPU1AHSKWyvIhrGqaXzcbedRPjyXVsjvjUKKmv1tkALyXX1xIZQQYpu0pCUtaV/FCFQ/URwNiDKm\nPL8TJUv/QRPGhlbR8vA4999+CFFWMX1NNby/fQd3rd4JhgGmXd1bl5pggA8ONyYU9hZ4rl2Ex8Mb\n9lnG67pGPw43+jFjTB5m3zLQBAk9G5DQLUWIi+NuixlEcr1lUUIMQJ9B7OaxU51ZK8h/exCr+nNB\nNAck7DjchC8uiHhxxzE0h5KwfSIEv6hM73SlOPi4fX5ZhRdHmnxIcfDgWQbLKvTDzssfHcO0q/vQ\nQ7yxiFuSn216H3Lgefb9Onx6vJlCOq0OR4m6kS6Bp51FSdHobN4Ni7djU81p6pvzbx2CbTOvw4q7\nhpr28Uc37sdjEwYhmGAs5nCDH/1+vQXbDpxBKKJLTAQlBQFRxqzX9qJk6T/QNzMlHgJXVYPWsEzf\nIyjJON3SlheUFua0A8+W0eQT6Xc9cWhP7P68GSunFOHQvHHR5F1nJX1z90n8Yu1unDwfgjuatBOY\nbbLLndhIvIiNSb6wjFZRNkDHd6E5KCEUUfDKx8cphNQpcO0W6HLSnChZ+g/0+/UW3LTk73AIHF7c\ncQx2njfF2Gffr0NuhgtPb/kMLMPg+Q+OUojwgMfexksfHgPLAFOe34kJyz9Ak0+k+a1VDtwSjFgi\nIkhsJhBpTQNaghFMHNqDwoeNdlXvdDRcaOswLyoroN3IZeX62o/IKkKSghnraiy796Ks4qHXavDo\nxv2XFH6fPARamCyraAm3OboR/mHlWEYnIgOuZcW9YOfbqhaHnhqHhbcX4M3dJ7E0CptYsb3OtHnM\nuqk/nptahP7dPVh4ewEYVmfccibY9PtneSjmmWCPybUSLT6PnU8YXE+3hDC7ZCBdYEaYEXlOayiS\nMOGKhQ889NpeBCQl7rtSNcTBrpaVe5PwjKQl7XtoBCauanrXSVH1f8tK2+NBUYbf8Ds1ymr9/LRi\n9Mt0U/i+EfZlYxmsqizC0fnj8eljN2Lfb27Bq9NHmA6PZDZ6UlFPS/gTwzD4zeaDcAk8+mam0PkU\no13VO91ULU4Ue0mRrrQwB+/Ouh4MA6Q5bejZ1YGfXtMHPbo6TfN9M6tqEJSUuGsdTnDoDUoy/u/0\nBdz90i6dxMYQy+9dUx0H+SdwPY+Dw+Kywjgo35K/HsKDVTUY2a8bZm/Yq8PzkskzeJ6FR+CR7hLw\ns2v6Is1lQ7pLoPv8qsoipDsF5HVPodpjKXYeuRkuLH+vDp4EZHPGIi6g/01PnQ9R2vwLIQlLy72W\nh/ZEB/m6Rj/151nr95o6wmTEZO09IwDoHbWi3umo+sQ8VjKzqgZgGDwz2ewjJPElZHHGg4EG4IkJ\ng1BamJNwPfRKd5kK1ALP0rzggdF5ePmjY1he7sX22TfgyPzx2D77BqyYMgwCx5i+65w0B/pmpuDl\nj46hyS8iJToL+NRbn2Hu//s/epgWeA77TrZg9i0DkZVqTyKP2jGXwGHaqD6WhyirGVJfWMZPvD1o\n8Ysc6NuD6hr/7QvLWP5eXZRZv21mcPPe02hqFXX96Xdqo5qEDspJUVbcC26Bx9O3DaEcFeTQZjUX\nmKhYktfdo+fkU4YhJLXFN1lV4bJxcb7/+zu8SHHYUDtvHJZH2aaX3OHFiinDsGX/GbgEGx6sqmn3\n3PBgVQ2dI7yU8PvkKogxwohEEgLADO38sg3+qt7pCIoKWsMyMlPsUepYDq2hCLK7ODCyXzdkuAXK\nVtfkE7Hw9gJkd3HgXEAyaVcRCFEi/b/6c0HctOTvFF6x50SzSQvH6jUNF8J45/++wLJyb5ymjxAd\n/E4EM1oWnU8heoFGmKlLsG6ZE2Y942M5aU78an2N6V6TMKOkJe37Z1a6dgTKVT48F1Wf1OPo2QBm\nlwzExuqTcXphi8oKUNfoQ/EV6SbWRELJ7RI4+EQZGR476s/p+nt9u7kpSzPRTiNQO6ORotnDJQNx\nuiWEvO4ePPRajWX88xs01RLF6xPNQUz05pigojPG5MXptxF40pb9Z+C283h31vVY8tdDtJt5tMlH\ntbeM4wFhScFz/zimFxRvHkATMsAM5//ljf3hC8vw2DncMTwXigL8oIudjjz4wjKe2HSACiynOm24\n7/o+yElzUObpoCh/r9lDed782V32tp8JEUlK9PecwEKW1bjOdRx8VNSLuORv+szkQizc+k964Fq0\nrRYlg7Nw3YDuWF7hNbGIprlscT5BZEaIkW7ijDF5mFTUEwLPmq6xYFIBqnbq4t9GSalPjzfDaePA\nQofIpThsuBCUYONZLLnDSzU3jb5G9Itn3TwgYS5iPAh8erwZmSl2/PFvh2lutGJ7AJKimaB7yyt0\nGKkrWszW9d7S0CPNiV/e2B8NF8IISQpKlv7D9F6EdISs+5k3DUBQlOH5bmVTLhsLSool6iHRIYow\nyZPfsQywqKwAG6tPxsVLIlvGswz995u7T9KiR1e3gEVlBTRGrv+0nvr26MXbqVwDwwAugYcGDS67\nzhSblWrHvFuH4A93eulcoNG/G1vDlr4YkhS8MK0YLaEIlYUg+4vLBtg4BiunFiHFoctA1Jw4j+Ir\nMsAwgMPGwW5jqSQGAByZPx6fHm+ma/3Lzg3G7/C7tqROIOKpcN123vQHLS3MwRMTBkGDvjgI9t6I\nlw5KMoKSAjvPwmPnIckq5ChumrDBETKAn13bF2d9InIzXDjcoNMePzA6j2pbESPaKc++XxdHTb6o\nrAALt9bSxIDo35xqCWHF9jrMv3UImi00hdJcAkKSjHU76/Gza/qY6MIZhjF9bkCnUD/01DgERQUR\nVdUpzgUOflEXej3RHES6R/hKGlvGz0QC8ncgYnxZaf5car2fpE7gN7ekTmBi/zVKObRJEejzJFYa\nZ6sriyGrKoWXuQUOgejrjFTxROvsQihiqZ92PhjB7A1mUeKjTT4U98mAprXpVdU8ebNl/FoxZRhk\nVYXTxkNRNdz3SjUyU+xxeq4qNF2uYZ31TOAzkwuhaRq6OAVMX9P2ebfNvM4y7i+8vQCPvL4Pf7hz\nKGwci5QopFPTNLAMg7CswB9W0CvdhRPNQaS5bDh21o/uKQ50cQpw2Tm6txjlMA49NQ5SRKG6dF9c\nEE3fz6KyAqTYeTzxl4P0+31+WjECkhwnI+Cx8/AICeWAOo3vXiyTZRXNIQlVO+vjxc8rvHDwLFiG\npfph+kw9h9Mt+jzfD7o4caI5iOxUO0KyipZgxPT3J/pked09CEgyXtpxzHSYG9k3A3+80wtFNecx\nxt+TA9jMqhoAoH7ui874TX3hE6ycMgyi0iZ5MW/iEMp6S8haHhidh/5ZHqqDGKt1bJW/rJxahNZQ\nBDlpTgQlfe4ykSYcKX5baWySbk73VAdONAfhFjj87q3PqD+TYlFYUuCy7gZ+731XllUEo+RTxu8/\nkf7piinDwDAMnZc+Mn88HnpN73QRfekUhw2h6DyhjdX93BeWsWnPSWw90ED1W0VZAQMmTl+7b2YK\n+nf3wC+28XCQIlqGW0BdUwA90pxwCvqasdKtfH5aMXxh2eQvelePh6YB09fssozvEVXDywbuDyLF\n06ebB6lOG/yijCONPtz6/32M0sIc/O4n+fA4eHxxIQRA1x1MtN5i9QQVTYPTppN/fYPmSFIn8Oua\nVSV6VWURHeR+YHQe+nVz00NiWFKodo9VVVrgWAREWdcFsqhuTyrqCTFKH6tpgJ1n8cSEQcjw2K0h\nn909NFCSzllQVPD4pv30cfJcp8BRh3IIHBa/WWvSnlq8rRZL7vBiejTpKsnPNiUg22ZeZ1klIVW0\nxWWFsNsYTH3B3K2UZAVv7Ttjqt6QxMcWbZ8bN7sMt066k+z+JS1pnd+Mye+kol6mQ8fyCq8lO6FT\n4PDse0dpNzA21sZ2y4ziw6QTsaqyiLJeksfnvLEPz00tQktQQnaXNrKLTXtOxaEjlpV7UVN/HnlZ\nKfiPP+/C8govjXETln9A4x8AnPVJJq2/Ly6EsLzCiwyPHUFRAcMAL3xwNI4Uqz1ysD/eORQcy5jI\nvZaVe5HuFiCrGnp2FUxCx89PK0ZQkjF9zS7T9ztn7EAs2KoLzzdcCINjGVR9Uo/KUb3jvh/SwXlg\ndB5Ff6iaFqdVS57HsQzteCXty62LncfdV/eBS+D0w4hDTyCDUgRhGXhwnS7C/uF/jkFmit2yKFvz\n5C2WBQuSUALQIZrDc/Hx0WaT78gKMHN9DdbeY935zuvuQf25IB6bMAhiRMWcN/ZRQotUpw0rpxbB\nxjL4+drddM7J6G8rpwyLy30WlRWgm1vAc1P1TvPplhAcNpbO9ZH1/PKHxzBxaE889FoNFt9eiNwM\n666TkYwmougHQPJdZKbY47WZK7z4zb8NAqDHi1SnDf6wTGcEkxZvPM/CBcR1lxN1nNd8dBx3/egK\nPDO5EA+9thd1jX40tIqmjiw5wLsEDtF8GRQAACAASURBVCkuPZc+H5Aw5Ue98RNvD3x85CxG9etm\n8p93Z11vOjwZi2alhTmoHNUbKQ6diHDu5oNUTzJRXHXaOIQjChbeXoCcNCf8ogwpouCel3dh7T0j\nkJVqx8MlV8btUet21mPaqN6YNqoPUpx6YbJHVxfuX7vbtL7e/MVIZLgd+PlaAyFjuQ4dtdpfnAKH\nWTf1x21FPaFGC3yNPgm5GS5wDKOfOziGFky/DfRFh4veDMNwDMPsYRjmf6L/7sMwzE6GYQ4zDLOe\nYRjhy67xdcyKCnfH4SasmDIMj4wdiKNNPjSH2shN/v3lXRA4FndfHY+XfnjDPlwIRaABltTGJfnZ\n6OoSEIooJs0RUdHFZ62w0/7/n71zj4+quvr+b885c82ES2JIuRYwgBYIA0EoXlpFWkCfh1IRSSrC\nY71UXy1Q6qVWXpunhVoEEWh9UbFVESVIVaSPKF7AR61UIDLcRCBcytUQEiCZzPXM7PePc8k5M2fC\nLcnMJOv7+cwnmTNnZvY5s84+a++91m+FJYz3dEFVXQguu4BYjIODo7I2lLBvxUmflg/jV4p2qsm3\noxd+israEPyhhhyTZzdUGHLzzGSeFxV7UNApCy9MKcJ32tvhsopYOqUIe+eMxdIpQ5HjssFlFXHH\niJ7IccmDOzVWv4PTihy3cVuO0wbBYkG2w9rqBoAtbbsE0VQ0p+0GJHmFbPSAzgmlCKat8GLGqL6G\n/dW+TJWINysBoeZhq+H3ycSqNh+qMZTXKR3XH1l2WWhLL0RR+o+vsXbHCSyZPAR754zVcjs6d3Bp\nYZU5WXbMXydPrKn5Jx/vrkSMQ8v3Uvvbue/vQSAcw+1Lv4Tn9x/g7le2oHh4D4TiamQly5k5XO2H\nKFg0Z1+fR+ILSbh/+Vc4fiaoSe3nt7ODcyQIjkxb4UUkyvHImH7488+UAZ1yTrMd5iJf3XNc6JPv\nlvtrl007j2b7pUteVSb0vQEpilBUXk0uePw9PPHOLuw76UOWXUSW3YoyXYmnLJt4XvmnKvE5hYvX\nVyDXLQ+8VFst23QYee3shjC1+M/2BSUs/GgvsmwiHn0zsRzFfa+Woz4sIb+dPSHPKS/bDjBmWkoi\nKMU0qfwuHZwIRWJ4Tte2+R/swYKP9uHRN7djxqi+8IUlVJrUOFbzx379hhela3YlTJ4/cEOiKNP0\nFV5YBQH/9+YrZe0EZSXJH06P3NZ0tV29Sr7qv7ltItrZRbwwJfG3e/D1rejgtOKFKUUo6GSep90p\n265Ff9kEC1w2OYwz22HFL1d4E3zn+PBTdXA3blAXPPTjflqpsmVfHMIiJV923c4TSXUv9p304cHX\nt8IfjqLfrPcgMIZpZQ1KpI+OucL0HvWz738XISmG+5bL44BTdSFTsaOCTtmJgoxKbnnZpsOGe0fZ\npsOo9oVRMrwHsmwNZWAee2sHZq70Guo0qgI8zSEekx49uJHpAHYDaKc8nwvgGc55GWPsOQB3AVjS\nVF+mv8HFh3e+VX4UU6/plSAJfv/yr5LmkMTHRutfK+jkRiAcTcjVeHjVdrx61zBTmWOXVcDs8QMR\n4xyiheGOv27CX37mMZ1VyMmSk9MBjkiMa6uPowd0lkNEQhJEC7TVvvgVxtqAHPKhxv1XnPThj2t3\nY4GSBAsYcx9UKV0VfWiFvkBrtsOSsK2V0qK2m0lcaMhmc4aPEqY0m+2eTykHfbSAmsv0zCRPo+8r\n6OTG3AlyJII+gmHcoC6Y+SN5YPnZIzdAtMg3ev3KwJgB+XCIFkP0wrpdlbipsDP+8vE+VFTVayFt\nT91aCJdNjvDQz26PG9QFj4yRV0JKx/XHtJEFWl9bF4xg2ReHTKXR508cpM00r9t5IiG/SxZlkaM2\nzI67ndNqyNd+9E15VS7Z4KB7jguTX/xSm/1Wz923ZwP4aOYP0T3HZVhRPFLjR8csGwTGYBFY0pyu\nIzV+5Lpt6dKvp33fqw6Y9U5s/Op2RVU91mw7DpddwMLVew35VNNGFmDqNb0AICFP1Exswx9ODOcb\n5+mKq3rmaBPA+u9fWOzB21uPorI2pNmSWTkKtfRIvIP+wA0FSUVv2jmtWLy+whCeuv+PN6HfLONK\np2yvTgTCMeRliwk+0eISD17550Hcf32BPLF91pjjlVQQzyEiEIniv67pBXCOxesr8OCNfS7+x2xa\n0tZ2RdGirfSr17kIC2ycJ6xSbz5UA4dNgEVJbFMHkGqalVMUEJCisAgMdcEInKIAt13E0ilDEQjL\nfXi8+nx8HxWKRPHRzB+iR65LK6MmxbhmV3df1xslw3vgi/1VSXNk1f4vfkLl2Q0VeGbSIEP03LMb\nKrB2xwnkZNlw+9IvNTtLlhuZZRe11Ug1FF/dHm//ooXhgZF9MPnFL7X+W50IWjfjB6bjhOfuKEI4\nGmvSBZS0GgQyxroBuBnAHAAzGWMMwEgAP1N2eQVAKS7hgtDn/6m5EXvnjEUwHEV9WNJuxmqH67Y3\nhG3UhSRYLXL5hMZujGpdoITE76CEbGdiJ5nfzo4afxgrlZmCgk5u+IISvthfhUAkG33y3ThdH0KW\n3Ybldw+T6zVZBcNgrWzTYYzzdNVi5edPHIQDVXVa7Sp9iKZa62/zoRpU1YVgYQwzyryoqguZ5vDV\nK/HcRHJawnYJojlobts9lyBG5dmglqdzuNqv1fRTV/qSva8uGNGEL9QwJLN8vEXFHrx61zDsr6rH\nsxsqMH2FF8/fUaTl9+nrVbntIu66rjf8St400FnLsfrnviosLvagPhxFt45OLVfxuclFcDsEdBze\nI8HpUJ16oEEUq8YX0ibeDlf7AUBzqtWahlV1IU2JOf64awMR7fNUp7dHrgvHTgeSCnCo362eSzVX\n5bG3jOkMDqsFosWCSDSK+15vuBfGTzqqOYHpoOicKX2vnNMp/yb6VTTAKMK2ZttxHDsd0BQRS8f1\nx+V5Wajxhw2hwfMmFsLC5LInZmIbZmJtCz/aq006LPhwj2aHlWeDeHJtQ91A1ZYam7gxG4AlFb0J\nJvpLqqKpftu0kQWo9jWk50wbWaBcXyKO1PgRlmJo77KiSwcHDjx5E+pDEpZOKcI9y+TzYvaZ6sr6\nZW47XHZB+w3Swa/JFNuNJ5n/qz+n+gGkUxQMaVfxgljTRhZgUYnH0OfJqvTGPmpRsQdrvMcS6nKv\n2XZcG9hzAFd2bg+3rWFBQ82rfWaSB4+NvQKBsITX7hmOuoBcCkMdnFWbiMkU5GUlRJsks/PaQARD\nZ39kaFtVXQh1Jvav3sOW3z0cgXAUn+07iSlX98QDI/sgEI6apklkO0RU+0JNGhaabvF4CwE8AkBd\n78wFcIZzrhaQOwqg68V+uJr/d++ycry68RBqdWUgTtaFtFCamwZ2xvjB3fDKPw/i2OmgXDNnlhwK\nUeMPY+ZKL176/GDCcve8iYVo77Ji9dZj+PPPEqWNs5Qk1/hl6hmj+mL6Ci8WfLRPCye6b3k5rr48\nD+t2nkB9SMJr/zqMuqCEb8+GcO+yclzxf9/H/cu/wrHTAbmg/PoKg+TyQ6u2wdOjo6b2qS/bEAhH\n8dwd8hL/k7cMxIIPZadjYbEHHVxWKt1wcTSr7RJEM9KstusUBSwq8WDdzhMJpQjmTSyE0yYgGuP4\ny8f7YGFMyxVSw9PX7TyRUFJm7oRCPKGIl6zZdhxPvf8Nlk4pwuzxAxPDwcq82F9Vr5W8yW9n16Ty\n12w7rvW5Cz/ai/qQXINshZLzrdbI+sWychR26wiLhWGN9xiOnwni5X8exLEzQdy3vBwVJ+sTwoP0\npYOABmd4WpkXCz7cixNn5NplK748DAtjhlpXcycUYuP+U6bh+au3HtM+T50pBwCbaEnYf+6EQjy7\noUL77nU7T2BRiQcWxhLCnh5etR12UUBIiuGXrzccy4KP9qFs02G5DpsuDcAhpo06aEb0vU5RkGsG\nFnsaXd0WLQxvf3UUi0o8qKoL4ebFn+Ho6YCpNP/s8QOxcJIHX584izuv7WUIZT5+piGcUg2Jfvo2\nD5xWAU/dWoinb5Pv97EYh9Mm4OnbPFg6ZSjmr9uDeev2YO6EwqSlJyrPBuG0CVis84Fq6kOm1+qi\nEg+kaAxLpxQZfKLL3DbD+0f0zsXUa3oZwgEXfLQP9y0vx5EaPyyMYV9lHcYO6Kz5bfcuK4c/HMVf\nfubBntljcVm2PcEvmzuhEAs/2qsJkRyp8WuD5DQgI2w3HqcomPZNyXzF+LQrNdRf/zuXH6qBXdeH\nPXBDQUIfpYayJ6vx5wtJcFgFjFrwv/jNWzsQkWI47Q+BMeChVdvRb9Z7mPnGNpwJRDBzpRf3LW8o\nnfPADQWmffhURYlUfx08u6HCtDao2y5iw0PXY/7EQnTt6MTvf9Ifz00egliMm+6/7ItD6DdLDvcs\n+m6O4flDo/sZ6nSrg+wVXx5u0lISabMSyBj7DwAnOefljLHr1c0mu5rKmTLG7gVwLwD06NHD9Dv0\nhqiuhpkt76qzdGqojV4JtHN7uZbT6q3HYGHAgtsGIb+9Q0v+33ywGl8dPoMffe87Bmnj+RMHIRqL\ngQMJIQ7JEqCzHSImFHXHS5/LCdOBcNRU6EAt4RAvuZyssHundg4wBnDOkeuW65uoamQ20ZKwhJ8m\nN/q0pSVslyCag0u1XeUzGrVfNbfkzmtlQQy1f1GT3S0MsIqWhNfrQxKcVsF0+0ufHzQIY8k50qzR\nfCm1v3zyloGoCyTOzM4Y1RfTVsiiGfo8RADaxNqTtwzUXtPfH87l1Kuz2G6HgPx2cp7VQ6u2Y8yA\nfC3i5Pk7iuC2i6gNRpDtENHelYcDVXWG4/58XxVmv7tbzrEp9iAS44aZ8r/8bDCWTimCyy7nlKkT\nfItKPMiyCZhydU/YBAscSUr6ZNlFuEzq0i5eX4EHRvZB38ffw57ZY9Fv1nvYO2dsMpNoMTKp71Xv\no+0dIvxh85UBf1jC3jljtXuv+tsD5ikmTpuAAaXrMKJ3LhYWt0cgHNVWV2oDEW2FMF5YacGkQajx\nhQxh0nMnFEKwyNeS2q5Hx/RLCFdeVOxBrtuGk7UhuGyCtpoYDEdxS1E3vFV+tCGiSYmeuuuVLQmr\nOM9M8mDr4RpNel9VZk+28jhzpRel4/ob/DZ1YLBk8hBc/tu1GNE7F3+dOtQQJaWurPuCEgQGdMq2\nAwwIRWKG9JaWJpNsNx5RtGgaEPG+YrzavlMUEn5Xs/7ylyu82DN7DNo5RO1zz5X7qj5XB/suq6Ct\n0qn3hz+MH6BNagENoZWqkJJqP8n85WyHCH9IMoSXVtWF4LY3tNMXbFAsVVfpl//rEH7Yt5MW8fHJ\nnpOGqBPOoa1AqnZcOq4/Fny0zyC+tXbHiYb0MJuA0QM6N2kudjp599cAGMcYOwSgDPKS+EIAHRhj\n6hF3A3Dc7M2c8xc450M550Pz8vJMv0BvVPE/uD5RWjXQ+CRUdVb4/uVfYezAznj9X4cx4k/r0fux\ntRhQug53v7IFnTu4TGcwHlq1DaIg4JeveyFFY4bilv6QeRJrfVjC3Pe/0RKm89s7kl4U8yYWavLM\n6vuTJcceqfHLgz5FoMXCGLIdVrjsIkTBuI0GgOdFs9suQTQTl2S7wPnZryjK/Yq+z3E7RLjsIhw2\nUduuf90pyjLZWUqZCKcoIBblYACKh/VIWFGctXqHFk6kR58vpTqUAE9YlVQn4xpTl+ue40q4PwDJ\nBV7qghGDEIA/HMWMUX010Y0b+uXjvlfL0W/W+/jFq+U4ejqAJ97ZhckvboLAGCY+9y9k2UWs23kC\ntYEIruzcHntmy6s9TpuAX79hvM88+PpWSDGuSfwvmOTB83cUofxQDY6fDaJ0zS44bHL5CNN7Tkhq\ntPC4/m99SEIakFF9ryhaYLeJja6k6O+96rVQn8RH0IvByQN4QfMtplzdE+X/rjEt+j1z5TbUh6MJ\nqx4xDsydUKitjHynvRMuXTHu5yYXoWzTYfSb9T5mvrEN4WgM+e3sOFUXkhXJ1+3R8mIrTvrwu3d2\nwmETTFdxfrXSi6sL8vC7d3YCHJozbXactYEInr7Nk9RRb+e0av87bAIiUsywsr6oxAOrwPC3zw+i\nuj4MuyggmvryaBllu/Ho7VO1V320nbpSW+MPIxg+P0EsfzgK0WJBNMaT2kJ87msgHMWSyUPQtaMD\nISmGDi6rtsK8dseJpHmq+hp92Q5rUiGmY6cDuGdZOUTGDMJhG/efQpZdxL5KH37xajkWfLRPs+23\nyo9izIDOmqDSY2/twMgr8vHshgpc/tu1GLXgf3GZOzHcM36AqyrhygtPR+EPRzV9j6YibTx8zvlj\nnPNunPOeAIoBrOec3w5gA4Bbld2mAnjnYr9D35HGOwvPbqjQOuX4m128CtbGA9WYoXRoejYfqkGf\nfDf65DcMHvWqdG67gOV3D0fnDk6MWvC/mmrn2UAkYal43sRC1AYihnySZINFf1iC2y5qYVTqrMg/\nK6oSbjRyrUArhXg2IS1huwTRHKSr7SZzJsLRGE75wijbdFi7IT95y0A89f4erPYe10o9mIVEAg03\n9Ve+OAS3Q8Rr9wyH94kfY+mUIi3H6dkNFUkdEF9I0lRF9Y5MvNLyiN65mD9xEJ54Z5fWzy9eXwGX\nTdAGm2b3FTW8afOhGrjsgpbPdP9rWzH3/T1a2OjQ2R/BabJipzo0VXUhZNkFBMJRZNkFDOjaAfM/\n2IPKWjk/JVnYnlMU0MFlTbgfzZ1QqL1HDdNNh3tIutrvudCvpGjK2Y3UzDUdNJbIyt1LpwxFlk3E\nWX8Y9ywrx/XzP8Hlv12LJ97ZhYHdOpjqEKgTGvHbunRwYtfxMyge3kOb9FbD6ypO+nDfcqOzq6rP\nTi/zoi5grkgen8Oq/75sh4jScf0BJvtndoGZXr/LvjiEE2cD2gq+Hn2erBYyp1NifHHqULisAuxK\nVMEpXxAViiprKslU220MM7X96WVeRDk3/K7JlOhV8Zgz/ggCkWhiCKWSHqB/brEAvpCEUCSGs4EI\nZpR5Mefd3XjyloHYO2fsOQeT6v9qvmx8H25hwPK7h8MmClj2xSHMXOnFGX8Eowd0Rl1AQh+TCcPR\nAzonpGLFh64eqfEnbZP6/HC1H/1mvYfSNbtQPKwHquqC2upqU5E24aCN8CiAMsbYbABbAfz1Yj9I\n7Uinl3nxjtdYF6qqLoRct01Lwl5Y7MHKTYcxd4Ic23uuZWmgoaaeXbRg2siCxIKwxR78ce1uzBjV\n1xAKMvf9PXjiP6/UxAGO1PjhsFrw+3/sNny2hbGEWnzzJhZCYAxV9UEtgbripA+rtx7FLUXd4LIJ\nWFjsQV52Q70qezPUGiFMaTLbJYgWJqW2q3cmgIZwmaVThqJ7jksLT+QcGLXgfzWVutJ/fA3GkBCm\ns3bHCc2h/Hh3JcYP7mYQ2Zg/cRDcdkHrX1d7j5qKoUSiUbRzipg/cRDeLD+iKSyu3XECBXlZWmhb\n5dkgrKIxskudtY4pwhSNhZCqeVeLSzyY8658H1AnBNVQt7qguXBMIBzFk7cMhE2Q+/hn11doYUpP\n3zYIAgNuHdodf99yRAtPqg9JcFnlcC43RNgEC5ZOGaoVLnfZGsJy77y2VyakCaR932umvNjYvmbh\nd/5wFC6b/Pc77Y1+ypptx2FhwOzxA03txMwJDYSjuLZPnqHupjrZ0ZjypixiwU1Vy/U5rPFOri8o\nJdRac9tFPDe5CNlO+fp12QT8/NremLV6BzzdO5h+xzveY5rTXn6oBlOu7ol2Tiv8IQmBSDQhnPXY\nGX9aCMMkIe1tNxnJQjizFBGpePs1CyfNEhhcNnlo8us3vIY+6p8VVRg9oDMeGNkHvqCE1d6jWnmy\nGIcWGQEAq73HFZsoTFDCnTexEPPX7dHuCWrIsMsm4jklLP/4mQBsAsO0soaagYtKPLALFtyns9nn\n7yhKuL4a69tH9M7F07cNgssmGGtox4k7LS7xIMsmauHhVXVBuB1WrZ9uKhhP/ZJ4kzN06FC+ZcsW\n09fM1EFVIwSgdX7jBnXB73/SH24lFCleanlE71w8d0eRwZFQjQmQ45DvM3lP6bj+eHZDBR4ZY1Sw\n+8vPBiuhmCLqghKkaAwPvr5Ve10dyM1c6cX91xdo4RZLPqnAgkke+JSbeH0oKhezDMlqp1I0hoeU\n2OJcty0Tbt5NjVmMfdrSmO22BBdayoFooBnKWmSU7QJNZ78xEwly0cKwd85YHK7247G3dqB0XH/Y\nRYuhmDBgLJyt9uNqftCzGyrwwA0FWsFh/XueurUQNtGCLJsIl12APxTFKV8ooYTCk7cMRKdsO6Kc\nw2UV4DPpc6+Zu0ErjqwqNj992yAIFgYpKueGS1Fu2vYnbxmILLuAsBRDR5cNd72yxbCPKq1/08DO\nCWUGVMcBkHMtY1x+qIM5q4XBKloQisQQ5bw5c7/brO2mAkmKwR8x91NenDoUp/1hg7+hOqH6AZjq\nvyyc5EFfXekGNR0mxs3t9YUpRaj2hfHYWzswun8+xg/uKhdkD8mKur9c4TU4ueqExKISD8q+PGyQ\nzR/ROxdLJg8xlGJRt6m5gKX/+T38dHA3ZDtFTcvAbhW0siz6z/vkoetN2/z8lCKIjBnKWukg271I\n6oIRwwQC0GAj5zvgrgtGUO0LA4Dht/vnozcgEuUJ/fELU4pw77JyvHbPcNN7xp7ZY/GrlV5D+bdY\njCNbUaNe+NFeTRW3orIOQ3vl4ow/3Gj/rFfQnzmqD4rjlKHVsUH8e+USbgDA4RAF+MKSpor9yZ6T\nGHH5ZVrOYF62HZ/ulbe1c1rPt5++YNvNhJXAJkU/++awiRClGGoDEfhCcl1AtYaTOrNbPKwHypQV\nwfib7eqtcgJ0n3w3jp1ukKCtOOlDdiNxyOoM3dIpQ+G0CTh+JgAObhhQ/vlnHm2WZF+lD3Pe3Y2H\nR/czdI6AbFjVvhCcVgGVtSGt/pTaqa/eetQg593GBoAEQWQgjUmQq+GKb5UfRcmwHgnREfoZ1aq6\nEKRYDN8q+XCbD9Vo9Qf1bD5Ug64dnfCH5JUVVQBFv8oIyE6FGkb3q5VewyBs2sgC/Pza3gCAA0/e\nhGOnA+jSwYE9s8fiSI0fVgvDHKXuarUvBJeVJYhuLC7xICzF8If/2Y2quhD+OnVoQr0rNbxJXRlU\nZ8rrghFEpBhe/OwAiof3gNMq4GwggodXbUd+OztmjOqLHrku+EMSGGPyCpIyMAxKMbgEBn9IgoPu\nExmHKFrgAhJsZVGxvHLhtouGSKMsm4DV3mN46lY50kkvIlQXd+2t2XYcBXlZuOu63gn2Om+iLIN/\nmduu1UdTVXvHe7pg9vgB2DtnLPyhKAQLMHFodzwwso9cYzLLhsXrKwzHoeb3ZTus2orI3AmF8B4+\nbYh0euWLg7h1aHf86b1vtOtg5qg+mDSsBzYeqDmn6J47xaGgrRVVCTreBi8kfFENSZdiMUPf/mb5\nURQP64HJL35psD8GYHGJJ6FkCdCw4r12xwlNdXn+B3uwdscJfPOHMQDkvOnKs0GIFobnPz2I6/p2\nwqx1yeu06sOoxw3qgtEDOiM3S1mlt4k4diYAKRpNFFQq8SASjeH/vNYw8fLMJA/e8R7CjVfmY92u\nSsx+d7dm83/97ACmXtMLnHPEorzZVq3b/JWgD3/5+bW94bRZDOp1ogVy+IvVqGoHcLy/sxK/W/M1\n/vnoDZoErX4mwMwg1XCIylrZOek36wM5D+X2wfh/tw+BVbBos7aiRU4I189a6wsNqypfc97djadv\n8+C3b+/UBqVqCM/Pr+0NC0OT1hUhCIJoTvSh+2bOhL6/DkVihtBFVVH0wRv7aCsFHV0WQ4ioWd98\nuNqPkBTTnierBXWkRt5PdY7VOoF1QQlnAsYVl0UlHuS4bAhJMSz4cK+mUpiTZceRGj/y29mTKswt\nKvbgxc8O4MCpeoPa4dtbjxrCUPXOTVVdCKXj+mP6Clnx7uFVsgDNzB/1SwiHcloFbDpYjaLv5hjP\nc4kHOc7k+WlEeqKq8OpD7OQBfhSiYMFlbrucDiJawCGrZPrDUXAuD+Jmjx8Al11EMBxNcOTHD+6G\nVVuO4OaBnQ2DyQ5OK/yRaEJ9TADofVkW6sNRrYafalucc4SkGHzBqOn1VRuIQNCt+q//phIjr8jH\nfcuNn2MXLZoOwlU9c1AyvAeyVcVGmwhfSEpan039jjQNB81I1DzuMl29a32Y+fmi+uThaAwuK7S+\n3a/4xKr6saoubRMscIgCwtFYwsBrwaRByLZbsWf2WE0pds02OUw0GIkpdijbgppHGgjLua2qeFay\nMGp1hTw+5evj3ZUo/cfXGDeoi6acWxuQV6mnXN1T134JFsZwx4ieCIajeOrWQq2WqzpQffDGPohF\nebP2xW0uHDQZkhSDFItp4aHBcBQxzrUfS4rJHVckGtNmVtWixE/dWohH/r7dYCwzR/UxFMPUxyFX\n1oaUXEMHGGPwBeVY58JuHQ0DvHkTC5HjssEXkgxFNf/rml5w20Xs0y2Jq+FP6nJ1rttGHZxMRoV2\npDqsg8JBLx4KB21a+zWTGr+Um6EkxeALS4jGOCJRjl+tNPbNdsGCP7y7GwV5WZg0rAdWbjqMCUXd\nE/pkh9WC2f+zW+vH53+wB3/86QCcUkLizMKH9CGhVsXhGD+4G3YdP4Nr++Qhyy4q+YLy/Ud1GtTQ\nNjUEVB+i98ANBeiT78a+Svk+sGbbcS38SS3h0Pfx9/DutOtMw1+fvGUgOrisBsl99bULCd9KQpu2\n3VShhoW6HXKJkCylOPr0uFIQu46fQVHPHExf4TX4MvpIpEA4hi4dnPAFJbzyhTw5MW1kAaZe3Utb\nkXPZhATfR7Wtjlm2pCkxoxd+itL//B5uGtg5caLHJuClzw+ioqq+0TDUhZM8sFstaOe0ojYQQTQW\nw4OvezF/4iDYrQybD9bguj558OvKZqjf4bIJja14k+1eBE0RCnopSFIMQUnOuXY7GibVDpyqT7Dv\nRcUeuOwi/vbZAUwo6o43y4/gmnTWIwAAIABJREFUp0O6oUsHB+qCkhYZGK/roeaO37f8K5SO62/a\nry6ZPMRQML5rRwd+tXKbNvhcOmUoOLgSxmyBPxwFA3BP05w7Cge9GFTjUTuL/HZ2PDLmCvz6jYab\n/+KShpw8dZajpj6kCQHELxsvXl+B/3NDgTaLUXk2iBjnePo2jybcMvWaXrjv1XLkZdvx+58k1r9R\n64S0d1nlGlKOhtzF23VL4k/fNghPvf+Npv6phn4SBEFkKhcinHG+n6fOMDutMMwo14clzFkrh2A+\nMqYf3t95AuM8XfGd9vaEuoaAHEKkF51ZWOxB9yRqnT1yXdg7ZyyOnQ7gT+99g6q6EJZMHoLVW49h\n5BX5uHeZUaDGZROQ7bAaQuXiVyXXbDuu5Sfq0wP0K5iqAnZj5S4YM68/l2rlROLCkaQYagJhw6rc\n0ilDcc+yLQa/4tE3txty7NbN+AEeXmWsifnL12U/5/LfrtUmHB68sQ9qAxG88sVBw+REMptX/49/\nTRXUK/3H1wCg1WirD0kIS1E4rQIWr6/QJjwWFpuH5eW1s+P2pV8m+GgPrdqG5+8ownV98uCwChAt\nLGF1VLRQZFRT05goTEsgihY4AISjMQTDUdgEhjuv7aUt6jx/h2wDFSd9EC0Mf/vsAKZe3Qv3LZcH\nXws+2od1M36A0jW7NJ/cbRcNURhvlh9ByfAeml+frFzJ3jljsa9S9vN/OqSbQeXfaRMw+cUv5QnB\nkDwhaJrWUNIyCsx0FUBWopNiXFOju//6goT6S9NWeFEbiBgkkK+a8zHue7VcCznQc1XPHBw9Lef6\n/eXjfRAsDA+t2q7JvU4a1gOrtx7F4hIPqupCyHaY17/pnuNCO4cVbkVxzh+OQmAMS6cMxd45Y7G4\nxIP2TisWTPJg6ZShyHHZ4LaJ1MERBEHEIYoWuOxKfUJRDjFy2ixw2QQsmOTRpPrvGNETdtGCuqCk\n1W5zO0Q4bAIK//sD9H5sLWat3onRAzpjz+yxjdbX21fpQ+/H1uK6pzZgzbbjWhmHEZdfllAi4qFV\n2+APRxM+69kNFaZy6R1cVtNSDvMnDoJokdWkk7XrSI0/aV3FNKkBSFwAAUkOy9TbU2OOqrq9MSVD\nQJ5wKF2zC/5QFDbBguLhDTU6G7P5ZLUofSGpoVTArkqEozH85eN9GPz7D/Hg6174dTXl1mw7nvRz\nDlf7E3w0tbyK2y7i2JkgCh5/D3e+vAXHzwTR+7G1uHdZOSKx5g2va6skq2XZkn2JoX9X6nHWhyQ4\nbALe3noUvqCEgk5udFDyUd0O8yL2a7YdxxPv7MLxM0Hcv/wrzW+/pagb5ry7G6d8oaR9Z20ggn2V\nPq2sw8e7Kw2vV5z0YeOBavz6DblW5+gBnTGtzIun3t+jlTV58paBLebH03QfoM1UnKtTzHaIpiUa\nth6uMU2YVlfk7ry2F6rqgnh+iiw96w9FEYhIOOuPINsu4q9Th8IfNo9dV+OPQ1IMNy/+DHtmjwVj\nUPISAYdVgF2waE4KQRAEcW5E0QK3ttIo/1XrVAFySFF8CKpesGbNtuNaiM+LU4s0wRozkRo9qiOQ\n7D6TZRdhYQzPTPJoIatVdSE4rBYtb6Q+JCHKuSFHRs0Dn3J1T7jtIhgDQlIUDpdoen9yWgVs3H8q\nMfeyhWagiabFbCXm2OmAqV+hz4ttLPdVzbdbVOKBQ7SgPhJFjsum+TLBcKIAhpr20vuyrATbemaS\nB1YLM0RI2QQL7r6uNx68UZb9P+ULGt6n1pTTf46+dIqKvrzKPuX60m9X/6dV7ubhXHncqUCNJqkL\nRvD+zkqU//sMHrihAF07OE3zvvXP1dU7Na/v2OkA7KIFCyZ5tHQxs+MVLQwFeVkoHdcfZZsO45ai\nbvAeOWNIHwCMIjObD9VAinHtO1Ul7BY5Ry3yLWlOfUjOEzlXp3iyNoQOTqshUdXCGIZ+Nxd/+/wA\n/vyzwcjJsmn1+BiA42eDWL1VVjUKS1HcHpckHY7JCdJ/33IkQfRFzT/hMWDBh3u1jlmf70d5fwRB\nEE3DuUJQzdTv5k0sxONv78S0GwvwnXZOw/0hxjmKhxsVCxcWe5CbZUN9kok/dRZ5yeQhCSICOVny\nzHaWXS4HJColH/R14/RhfnbRggdf9yIv264pQWr1YkULrinIg01ghjaTOmhmYqao+/ZXRxPsdWGx\nB1/9u0absFjySUXC5MXCYg+kaEy3yl2PsBQz7LO42INwlOPN8iM625JXfZ6+zYOTtUG47aJhwBeN\nxRJKnsh5UkWoD0lw20WcOAus3XFCS7vxhyVwzrXagarYU2VtyHD8qn+kqqJjQGdtu74weBrXB8xo\nktWyTIe+RD9AvXnxZ5g2skArUaJX/o+fcJBrBwr4y8f7NMEudZLjsZuuhNNqSQg13rDnJO5/bav2\n3RsP1GDplKE45QtpwjSAUWTM7D7QUnZKwjA4v5zAeRMLkW0XYRUsCEVjCEsx5GXbUXk2iPz2jqT1\nSSa/+KUSUyxi8oubTJNI1Zv2uEFd8PDoftqN2sKAupCEJ9fu1uqYuO0ihXteGBmV5J3qBG8Shrl4\nSBgm9fbbEqj3C/3gzGFrmBRUk/2zlNdtFoaQrh6tyybgZG0IH3z9LW68Mt/gWKszxeoK4wtTisAA\nOJTZ9HMJ5agKfep9bMEkT9J7U79Z72mRJRbW5KZGttvC6H97/YqZ2y4iJMW0emRqXbQlk4dAsMiF\nub89G0CMA106OHGkxo/L3DY4bXL+1LqdJ3Dntb0SRD/ia/Cp+VRmQjAFnbJQ7Qsj1203CBwByqrH\n7LGo9oUQisYS8qLKvjTWFmxvFxHlQH1YMi2v8mb5Udw6tDueev8bzW9SBfkWFctqvU1day3VZLrt\ntgRmQmP+SFSbUFPzBTfuP6XV66sLRrB66zGMuPwy9Ml3K6VU9mLNtuMJYl1AooAX0NDfnjgbSKjV\nqRcJi1cZPQ87NYOEYS4GNaFUn0AcDEcTpGhFBoRiHO2VJGbOOa57agO2zBqVtByEmv8RCEfPGZuv\nhhepRsMYEOUcCyZ5DHK4NAAkCIJIDfowUrduplb/vxpeqm6zQXZCBMYQisSQ7bAapMG7dnRiX6XP\nMFOshq7pJcLPJZRjNhuf7N5kFllCZC7JVmIAQLJwcM6R67ZhwSSPtprmUGpimjmtl/92rfb8wRv7\nJPgv3XOMNfgayy2sC0awdscJ3FLUzdQe64ISctw2Q7kXtSTAz3XlXvQTHzbBuAojMIZct5x+IzCm\n+E3yxIx6zOmyMkW0PGZRHi4GMMaQZReTDt5UAaP9f7zJUDfWLGJQzZE162+XfFJhKGWkqoPeeW0v\nuGxCylZQ6WpQEEULHDYR2Q4rLIzBZRfhVv53O+REU5vu9WyHVUtgXr31GBYVexIS9J/dUKHF358N\nhJMmkSZL2leXg/VtoA6MIAgi89CLFrgdct5flHM88vftqA1EULpmlzYABBpCgi60zxdFi3bfUMOg\nzMRj5k0sRAeXlfL/WhH63z7bYYUoWrRtgsX4mks3SaBHHz6pPveZiN/Fi8KoTnH8Z9WHJGzcfwql\n//gas97eibkTChPs8ZUvDqLaF4ZNsGjXhtthhcPW4Iepx5PsWF1KLq3+f3fcdvKfCD2BSBS1gUhS\ngSP9dXA+Yl1uh5wuYDYWqKwN4ZQvhN6PrcXA0g/wvd+tw+QXNwFAwrXZknZKK4GXgD7OmDFo5SLk\nJWO5cO+iEg++2F+FdbsqE+Lun75tEBiAp28blBB6SmUeCIIgWjdqjqGpQEsTiCqYrQ65bAJ+fm1v\niiwhkop5lG06rInCzJtYiK8O1yTs19FlNeQbmgm4LCrxwGUVUNQzByN652LtjhMoyMsylLxy2eTV\nO1qlI1oapyggKEXNRb2UUGT1OsiyCQZfvaouBLddxILbBqFTOweO1PhhtVhgFy1aFGH8WMAmWDCi\nd27aCOcAlBN4yZjFGSd7HgxHEeXcEL5gt1oQisR0hekp7LOJyaj4/lTH9lNO4MVDOYGpt99MRL2H\nOK0CApHGc/4yCLLdDMHMhzHLeQ1HoojocludJnmqVguDFIMW8qbasNl3pLFtk+22ISQpBikWQ4wD\nMW60Xb3NumwCQpGYwYc38/dVuzazeeDced2XCOUEtjRmccbJnrt00sT6HAyXvcEIqMwDQRBE28Fw\nDxEaz/kjiKbGzIcxy3l12EQ4lP/19pksT1X//FyquwSRKkTRAjEuMy6ZL6/31ZPto/9cs9fS7TpI\nq6kYxpiDMbaJMbaNMbaLMfbfyvZejLEvGWP7GGMrGWO2VLeVIPSQ7RKZCtkukamQ7RKZCtkukQ6k\n1SAQQAjASM75IAAeAGMYY98HMBfAM5zzPgBOA7grhW0kCDPIdolMhWyXyFTIdolMhWyXSDlpNQjk\nMqocj1V5cAAjAfxd2f4KgPEpaB5BJIVsl8hUyHaJTIVsl8hUyHaJdCCtBoEAwBgTGGNeACcBfAhg\nP4AznHNJ2eUogK6pah9BJINsl8hUyHaJTIVsl8hUyHaJVJN2g0DOeZRz7gHQDcAwAFea7Ra/gTF2\nL2NsC2NsS1VVVXM3kyASINslMpWLtV2A7JdILWS7RKZCtkukmrQbBKpwzs8A+ATA9wF0YIypspnd\nABw32f8FzvlQzvnQvLy8lmsoQcRBtktkKhdqu8p7yH6JlEO2S2QqZLtEqkirQSBjLI8x1kH53wlg\nFIDdADYAuFXZbSqAd1LTQoIwh2yXyFTIdolMhWyXyFTIdol0IN2K0nUG8ApjTIA8QH2Dc/4/jLGv\nAZQxxmYD2Argr6lsJEGYQLZLZCpku0SmQrZLZCpku0TKSatBIOd8O4DBJtsPQI6XJoi0hGyXyFTI\ndolMhWyXyFTIdol0IK3CQQmCIAiCIAiCIIjmhQaBaYgkxVAXjCDGOeqCEcNzX1CCPyQhGotprxEE\nQRBNiyTF4AtGIEUT+2OCaM2Y+SDJtvlDEnxBKen1YfY+gmgu9Dap+smq7UVj8mtkjw2kVThoa0SS\nYghIUWTZRfhDUYgWIBLjynMJDlGAKFoM+9f4w5he5sXmQzW4qmcOFhV7ULbpMBavr8BVPXMwb2Ih\n7IIFKzYdRvGwHshx2QyfQRAEQVwckhSDFIshHOXIsgmo9ocxfYWuPy7xIMdJfS7ROjHzQZZMHoJw\nNJZwHbisAs4EInh41XbT6yOZP3OpPover6oPSXCKAgBo24LhKKKcG16P35+u39aHJMXgC0vwhSS8\nVX4U4wd3w6NvNtjm4mIPIjGOX7+xLcEeA1IUTquAQKRt2UnrProUI0kx1ATCuHdZOfo+/h7uWbYF\ntUEJL31+UHlejppA2DATEZCimF7mxcYD1ZBiHBsPVGN6mRejB3TWnj+8ajvqw1GMHtAZ08u8CEjR\nFB4lQRBE60B1ImqDEn7xajmOnw1i+oq4/ngF9blE68XMBznjj5heB1KM4+FV25NeH8n8mUu5ftSB\npepX3av4Ub6whHuXlWPmSq/h9c/3VSXu7w+3+RWg1khAiuKMX56UGD2gMx5902ib9eEofv3GtgR7\n9Eeisp3Utz07oUFgMxKQookdZ9yALt6hyLKL2HyoxvA5mw/VoKCT2/C8e44LBZ3c2HyoBll2WtAl\nCIK4VFQnQnVcu3Z0mvbH1OcSrRUzH6R7jsv0OmjntDZ6fSTzZy7l+jEdWK7w4ow/go0HqnH/9QWG\ngemIyy9r8oEokZ5k2UXNVlX/WE8yO86yi23WTmgQ2Iyc74BO3yHWhyRc1TPH8J6reuag4qTP8PxI\njR8VJ324qmcO6kNSMx0BQRBE20HvRACAPxQ17Y/9odbtGBBtFzMf5EiN3/Q6qA1ETLerPkkyf+ZS\nfJZkflX3HBcAJDj/5xqoEq2H+pCk2arqH+tJZscVJ31t1k5a99GlGLUD3HigWttmNqCrD0nIdlgB\nAE5RwKJij2lOoGhhhpzANd5jWFTs0eLhCcKMnr95N9VNaBNcyHk+9Kebm7ElxMVSH5JQ7Qtr/fbZ\nQBjzJhYacp7mTSyEhaW6pQTRPJj5IB1cViwq8STkBIoWlnB9LCpp8EmS+TOX4rMk86uO1PgBQHP+\n1dfVgWr8/nq/i2gdOEUBHVxWzJtYiLfKj2LuhEJDTmCWTcDTtw0y5gSWeFD25WHkt+vZJu2Ecc5T\n3YYmZ+jQoXzLli2pboaWE2joOONEXsxEBsySnvXiMhYG2K0W+MPRNpG4eolklLvWHLZLg8D04zwH\ngRllu0D69L0Xi15Y4OFV25Hfzo5Z/3ElfMEouue4cKTGjw4uK9w2kfrdxiHbzWDOJbyi3xaOxhDj\ngMsumIppmH3WpYrCJIjNlHhgEyy4f/lXyG9nx0Oj+2kD0z+XeFD03ZwLEach281gJCmm2aTTJvvJ\nqu25bAJCkViCaFBNIIzyQzUXaifpyAXbLg0Cm5kLVQclmpyM6tBpENg2oEFg+qJ3Ilx2AcFwFDHO\n4WpDinFNANku0Ww0szoo2W4bQ7WnVqAOesG2S+GgzYwoWpCtGJHbIZ9uh/KauxUvMRMEQWQiomgx\n3PhdupyQ1hwWRBCZgt6v0l+T6jaza9Zsf4IA4uxJaFt2klFDXIIgCIIgCIIgCOLSoEEgQRAEQRAE\nQRBEG4IGgQRBEARBEARBEG0IGgQSBEEQBEEQBEG0IUgYhiAyDFL7JAiCIAiCIC6FVlkigjFWBeDf\nuk2XATiVouakmrZ87ADg4JwPSHUjzhcT200n0t2WWlv7TnHOxzRXY5qDFNhvuv/ml0qmHl9rtN10\n/C3SsU1AZrerNdruuUjH34vadH7o23TBttsqB4HxMMa2cM6HprodqaAtHztAx9+UpPu5pPa1PVr7\nOW3tx5dJpONvkY5tAqhdmUY6nhdq0/lxqW2inECCIAiCIAiCIIg2BA0CCYIgCIIgCIIg2hBtZRD4\nQqobkELa8rEDdPxNSbqfS2pf26O1n9PWfnyZRDr+FunYJoDalWmk43mhNp0fl9SmNpETSBAEQRAE\nQRAEQci0lZVAgiAIgiAIgiAIAq18EMgYG8MY28MYq2CM/SbV7WluGGPdGWMbGGO7GWO7GGPTle05\njLEPGWP7lL8dU93W5oIxJjDGtjLG/kd53osx9qVy7CsZY7ZUtzFTSOdzyRjrwBj7O2PsG8XeR6ST\nnTPGfqVcgzsZYysYY450On/pDGPsb4yxk4yxnbptpr8tk1ms9PHbGWNDdO+Zquy/jzE2NRXHEs8F\nHtvtyjFtZ4x9wRgbpHtPm7q3tSSN3EdLGWPHGGNe5XFTCtp2iDG2Q/n+Lcq2lPV7jLF+uvPhZYzV\nMsZmpOJcNVW/0VoxuZ+/pvQhO5VzZ1W2X88YO6v77Z5owTa9zBg7qPtuj7K9xX4vkzZ9pmvPccbY\namV7S56n877uL/RctdpBIGNMAPAsgLEAvgeghDH2vdS2qtmRAPyac34lgO8DeEA55t8A+Jhz3gfA\nx8rz1sp0ALt1z+cCeEY59tMA7kpJqzKTdD6XiwC8zzm/AsAgyO1MCztnjHUFMA3AUKVGpQCgGOl1\n/tKZlwHE1zpK9tuOBdBHedwLYAkg3yAB/A7AcADDAPyuJZ3jRngZ539sBwH8kHNeCOAPUHI/2ui9\nrSVJdh8F5OvXozzWpqh9Nyjfr8rCp6zf45zvUc8HgCIAfgBvKy+39Ll6GZfYb7Ry4u/nrwG4AsBA\nAE4Ad+te+0z32/2+BdsEAA/rvturbGvJ38vQJs75dTob3wjgLd2+LXWegPO/7i/oXLXaQSDkG38F\n5/wA5zwMoAzAT1LcpmaFc36Cc/6V8n8dZEPuCvm4X1F2ewXA+NS0sHlhjHUDcDOAF5XnDMBIAH9X\ndmm1x97UpPO5ZIy1A/ADAH8FAM55mHN+Bull5yIAJ2NMBOACcAJpcv7SHc75pwBq4jYn+21/AmAZ\nl/kXgA6Msc4ARgP4kHNewzk/DeBDJDqILc6FHBvn/Aul7QDwLwDdlP/b3L2tJWnkPpqupEu/dyOA\n/ZzzSylaftE0Ub/RKom/nwMA53ytcvwcwCY09C8pa1MjtMjv1VibGGPZkO/hq5v6ey+SJrHt1jwI\n7ArgiO75UaR3R96kMMZ6AhgM4EsA+ZzzE4B8gwPQKXUta1YWAngEQEx5ngvgDOdcUp63KRu4RNL5\nXPYGUAXgJSVs40XGWBbSxM4558cAzAdwGPLg7yyAcqTP+ctEkv22yfr5TOr/z8du7wLwnvJ/Jh1b\nRhN3HwWAB5UQq7+laGWZA/iAMVbOGLtX2ZYW/R7kaIcVuuepPlfAhfcbrZX4+7mGEgZ6B4D3dZtH\nMMa2McbeY4z1b+E2zVHs5hnGmF3Z1lK/V9LzBOCnkFfeanXbWuI8ARd23V/QuWrNg0Bmsq1NSKEy\nxtwA3gQwI85gWy2Msf8AcJJzXq7fbLJrm7CBSyEDzqUIYAiAJZzzwQDqkUYhzorD8xMAvQB0AZAF\nOUQjHrLFSyeZXaaTvV4SjLEbIA8CH1U3meyWkceWzpjcR5cAuByAB/LkztMpaNY1nPMhkPuTBxhj\nP0hBGxJgcn7zOACrlE3pcK4ao81cQ0nu53r+H4BPOeefKc+/AvBdzvkgAH9GM6x8NdKmxyCHqF4F\nIAct2Oedx3kqgXGSo9nPk44Lue4v6Fy15kHgUQDddc+7ATieora0GMqszpsAXuOcq7HLlepysPL3\nZKra14xcA2AcY+wQ5PCokZBndTooIXlAG7GBJiDdz+VRAEc55+rs/N8hDwrTxc5HATjIOa/inEcg\n5xBcjfQ5f5lIst82WT+fSf1/UrtljBVCDk36Cee8WtmcSceWkZjdRznnlZzzKOc8BmAp5LDcFoVz\nflz5exJy7t0wpEe/NxbAV5zzSqV9KT9XChfab7RGEu7njLHlAMAY+x2APAAz1Z0557Wcc5/y/1oA\nVsbYZS3RJiUUm3POQwBeQoPdtMTv1dh5ylXa8q66cwudJ/W7LuS6v6Bz1ZoHgZsB9GGyIp8NcqjC\nmhS3qVlR8rb+CmA353yB7qU1AFR1vKkA3mnptjU3nPPHOOfdOOc9If/W6znntwPYAOBWZbdWeexN\nTbqfS875twCOMMb6KZtuBPA10sfODwP4PmPMpVyTavvS4vxlKMl+2zUApiiKaN8HcFYJjVkH4MeM\nsY7KyuyPlW3piOmxMcZ6QJ5AuINzvle3f5u7t7Ukye6jcXk1PwWwM/69zdyuLCUvCUr4+4+VNqRD\nv2dYJUn1udJxof1GqyPJ/XwyY+xuyLnTJcpgHQDAGPuOcg2AMTYM8jih2uSjm6NN6qCGQc5xU+2m\n2X+vZG1SXp4I4H8450F1/5Y4T8pnX+h1f2HninPeah8AbgKwF8B+AI+nuj0tcLzXQl723Q7Aqzxu\ngpzP9TGAfcrfnFS3tZnPw/WQL1hAzh/bBKACcqiKPdXty6RHup5LyGFGWxRbXw2gYzrZOYD/BvCN\n0lm/CsCeTucvnR+QnckTACKQZzXvSvbbQg59eVbp43dAVmRVP+fnyrmuAHBnqo/rIo7tRcgqsmpf\nvkX3OW3q3tbCv1Gy++irio1th+xodW7hdvUGsE157FJ/91T3e5CFr6oBtNdta/Fz1VT9Rmt+xN3P\nJeX4VRt/Qtn+oGJf2yALUl3dgm1ar/weOwEsB+BOxe+lb5Py/BMAY+L2aZHzdKHX/YWeK6a8iSAI\ngiAIgiAIgmgDtOZwUIIgCIIgCIIgCCIOGgQSBEEQBEEQBEG0IWgQSBAEQRAEQRAE0YagQSBBEARB\nEARBEEQbggaBBEEQBEEQBEEQbQgaBBIEQRAEQRAEQbQhaBBIEARBEARBEATRhqBBIEEQBEEQBEEQ\nRBuCBoEEQRAEQRAEQRBtCBoEEgRBEARBEARBtCFoEEgQBEEQBEEQBNGGoEEgQRAEQRAEQRBEG4IG\ngQRBEARBEARBEG0IGgQSBEEQBEEQBEG0IWgQSBAEQRAEQRAE0YZolYPAMWPGcAD0oAdHhkG2Sw/d\nI+Mg+6WH8sg4yHbpoTwyDrJdeiiPC6ZVDgJPnTqV6iYQxEVBtktkMmS/RKZCtktkKmS7xMXSKgeB\nBEEQBEEQBEEQhDk0CCQIgiAIgiAIgmhD0CCQIAiCIAiCIAiiDUGDQIIgCIIgCIIgiDYEDQIJgiAI\ngiAIgiDaEGKqG9CakKQYwtEYYhxw2QXUhyS4bAL84SicogBRpDE3kdlIUgwBKYosu4j6kER2TbR6\nev7m3Qva/9Cfbm6mlhBEamis31dfc9kEhCLk/xCtk/hrwGphkGKyrftDEiyMwWETMs4vyoxWZgCS\nFIM/EoXDJuCUL4SZK724d1k5vj0bwkufH8TpQBiSFEt1MwnigpGkGOqCEUhSDL6whGpfGJwD1b4w\nfGGJ7JogCKKVIkkx1ATCuHdZOfo+/h7uXVaO04Ew/CFJ83uybCJCUgyRGIfTJmBfpQ8vfX4QVXVh\nvPT5QdT4yf8hMg/N94kar4GKk3UIRxts/W+fH0R9WMKJM4GMs3caBF4kkhSDPyTBF5S0TvIXr8oG\n8thbOzDzR/2Ql23HQ6u24adDumHaCi+CUjTVzSaIC0KSYqjxy51fOBqDLyThsbd2oN8s2c59IQnh\naGZ0dgRBEMT5ow7ypq/wYuOBakgxjo0HqjFthRdnAxHU+GW/Z+YbXviCEu57tRz9Zr2H0jW7MH5w\nN7yx+TAmXdUD08u8CJD/Q2QQqu/z0ucHUR9uuAZm3XwlunZ04Rdxtr7iy8OIRDkmFHVH+b9rEJCi\niHGuTaCnKzQIvAjUFZEafxh/+/wA6k06yUff3I4HbijA5kM16NrRic2HauCyNx59q846ZILhEG2D\ngBTF9DLZtmMceHjVdoOdP7xqO2IcZKsEQRCtjIAUhdshYvOhGsP2zYdqkN/eod0b7r++QPtf7wON\nHtAZee3s2HyoBlnn8H8IoiWJ97ejsZjB71Z9n9EDOsNtb7gGxg/uaurvjx7QGd1zXHho1TZcU5Bn\nWDlP55VBGgReAKrRWAQEY/8/AAAgAElEQVQGAHir/GiCgahsPlSDgk5uXNUzB/5QVPvb2GerKy6a\n4VAIKZFisuwi8tvZsW7GD+CyC6Z27rILZKsEQRCtjCy7qPkvelR/Rr0fFHRyJ/WB1PcHw1HN6fYF\nJQTDUqNOOEE0F6b+dn0Y/nBUS3HJUvz6gk5uVJz0addAO6c1qa0fPxNA6bj+cDtElI7rj5sGdsbG\nA9WYXuZFUEpP+6ZB4HkSbzTLvjiEqdf0Qp98N+qCEdNO8kiNH/MmFqI+LGFRsQcWlvzz9SsuNw3s\njNJx/ZGbZUdAiqad0RBth2A4iln/cSXsoiWpM1AfklD25WEK9yEIgmhFhCNRMAYsLvFgRO9cjPd0\nwScPXY/X7hmOKOeYNrIAAAxOsspVPXPgC0kAOJZOKYIvLGn+0z3LtqA2KOGlzw9qTvix08GMy6ci\nMg9VwNEfjmL53cPx7rTrkJdtx7QVXgTCUS3FpT4k4aqeOag46cO6nScwd0IhRvTORW3A3N/3hyV0\n7eiEXbRg5kovStfswuM3X4mKOWNROq4/HFZLWq4K0iDwPIkfpI0f3A33vdowIFxULHeSooVhRO9c\nLC7xwGkTkG0XkWUX4bIJsAkNpzt+KVqddRg3qAse+nE/lK7ZhX6zaEWQSD3BSAyPvbUDs1bvwLyJ\nhQY7X1Tiwef7qjChqDtcNiHVTSUIgiAuEr1f4g9JqA1JuPuVLZjz7m4sLPbg8ZuvxGNv7UDfx9/D\nfa+Wo3hYD8wc1QdLPqnA07cNMt4bij0QGGCzMHAgIYRuepkX/3VNL+ydMxZLJg9BdX0QP7+2F1w2\nERaBpeWqCZGZ6O06FI2hPtygbVC6Zhce+nE/5Lezo3uOS0txcYoCFhV7sG7nCUwo6o7VW4/Kq3w2\nMcHfX1Ts0SY09JogM8q82F9Vj9I1u1BdH0Zetj3t8mMpSPs8ydKFfD5wQwEefVPOjQKABR/tAwAs\nmTwE2Q4r6oIRZDtE+MNRWC0MMQ7Y4iSVa/xhTC/zYvOhGlzVMwfP31GEq3rm4PGbrsSMlV7tszce\nqMb0FV68MKUI2RkiOUu0HvR5gOrzJ28ZiB65LtQGIli99RhK//E1RvTOlW3UQTZKEASRacT7JZ89\ncgNmvrFN6/vvv74ApWt2GX2TMq/m9wQjUbwwpUgLIWUMYAw4E5SQ67abhtBl2UX0ffw9XNUzB0sm\nD4EvFMWvVjb4RYtKPMhx2jJGbp9IP/R2nd/Ojv/+yQBMW2H0sR99czuevGUgfEEJ+e3scNkFWBhD\njsuGO6/thSy7iDuv7QWnVUBNfRjl/67BkslD0M5pRX1IXtFWxwHq55WO64+bF3+Ggk5ubDxQjRll\nXm1bOuXH0pV1nqhLw4B5/Pvi9RXIdlhx+W/XwvP7DzH5xU2IxjjqQhIsDIZOTL+qqM6K7a+qw1+n\nDkWWXcRr9wzHZ4/cgHGDugAAJVUTKSM+D3DNtuMYteB/tedTru4J7xM/wpgB+WSjBEEQGYhaAy3X\nbUfpuP6YdfOVyG/vMPT9yfL+2jmtqDjpg120IBrjOFzth9MmoKouhBgHppd5k4aLVpz0aT7QGX8E\nv1oZt1q4In1zqYjMQBN46Z+P3950ZVINj24dnQADFkzyoD7UoPqvzxusD8ufdf9rW+H5/Yfo/dha\nuGwiFq+vSPg8VROk4qQvYVt9SGqx4z8XzTYIZIz9jTF2kjG2U7cthzH2IWNsn/K3o7L9J4yx7Ywx\nL2NsC2PsWt17pir772OMTW2u9p4LpyhocfGNdWgqauc4bYUXkRg37JsVZ4Sl//k99LrMjRp/GPcs\n24K+j7+HR/6+HY+OuQLjBnVRkrDTx2haO63Ndi8Fv27yQ+WqnjnwBSXcv/wr9H38Pdy//CuMHdAZ\n4UhmSCK3dsh+iUyFbLdpOZfiuF7srtoXxq/fkHOZfjq4Gw5X+w19fzK/pzYQQemaXQhGEksIBcLy\nysrG/adMQ+g27j+lfVb3HFdS4bFMqElLtpt+SFIMDAzL7x6OW4Z0Szoh8ecSD2rqw1qKl5q7V36o\nxjApYTaATHZdHKnxY+6EQjy7ocKwbVGxB04xfVJnmnMl8GUAY+K2/QbAx5zzPgA+Vp5D+X8Q59wD\n4OcAXgTkCwjA7wAMBzAMwO/Ui6ilEUULsmwinrxlIAo6ZSV0aPMmFmLj/lNYN+MH2P/Hm/DRzB8i\nGI6idFx/uGyCoROuj3Osxw/uipAUgxTlhkTVh1Ztw8wf9cXiEg/ExlRliKbmZbQi270ULIwl5Hos\nmTwE9SHJYKtlmw5rkx3RGEeQBI1Sycsg+yUyk5dBttskmCog6kQp4l/X5zJlO0Qs/GivJoYhWhgO\nVNXh+TuKsP+PN2HdjB9g5qg+mDuhENl2EfMmFgJILCE0bYUXM0b1xYjLL0PZpsMoHdcfe2bLQhll\nmw5jxOWXae09UuNPOuHYPccFxhhisbQuo/UyyHbTBnUl755lW9Bv1nva4suzGyo0u1aFjkYP6Ax/\nOIq8bLshZ/W6PnmaT79uxg/w7dlAgo2u23nCVBMkL9uO1VuPYu2OE9q2Ttl25LjSK7y52eK3OOef\nMsZ6xm3+CYDrlf9fAfAJgEc55z7dPlkA1KWz0QA+5JzXAABj7EPIF9mKZml0I6idTZZdwLPrK1Ay\nrAeevGUguue4UFMfQpZNxE0DOxvy/OZPHIR1O0+g4/Ae+OO7u1FZG8KiEg9cVgHzJhbi4VXbsflQ\nDbIdIiL1YTz21g7tvXMnFGLBh3vQI9cFf0hCevV1rZvWZrvnQg0FyrKLqA9JcOryVy0McNkEzdZP\n+UKIRGOY+cY2zVYXF3sQjnLcu6y8IZejWJ64ECnivMVpa/ZLtB7IdpsOfdoJ0JDDp+oLmL3+6Jvb\n8dSthagLSqisDWH+B3tQOq4/Ls/L0grDq338wmIPvvp3DTq48tDOISYtIdQj1wXOgZvXV2h5UwAg\nWhgeGNkHooVh2sgC5GTZ8No9w3G42o+FH+2V/aViD17+50EsXl+BaSMLUDysh8HHWlziQZZNhE2w\npNyxJttNLwJSQ/1uoGHFbs224wCA+RMLYRMtmLbCa/C7ATntJb+dHYFIFKVrdmmvPzPJgyWTh+D+\n5V9p24qH9YDbLuK5O4qQ7ZB9KKuFQRQsuPPaXnjwxj6aX6W2K0tgCb5WqmjpJJ58zvkJAOCcn2CM\ndVJfYIz9FMCTADoBuFnZ3BXAEd37jyrbWhS1OPwZfwTdc1yYcnVPuO0inDY5+TnGgUiMY3qZF3nZ\ndrw77ToUdHLjSI0fE4q6YfoKOSF09MJPMX2FF0/eMhALPtyL0nH95To6YanRRNW3tx7FHSN6tvRh\nE0Yy0nbPhTpbNn2FeTK+aLFAtHB0cFnBGGAXLVj2xSHNdtWcjodWbTN1NhwpPj5Co1XaL9EmINu9\nCOLTTgCjvkCy17t2dOIvH+/D3AmFePTN7bh58Wf4aOYP8dhbOwx9/IwyL5ZOKUJdUEI7pxW+oBzh\npO4DNKzkMQbT1+qCEXzzhzGoqTcOMBeXeOC0ivjb5we0gePoAZ211UT13rPiy8MY5+kKl01IuxUW\nBbLdFBFv389uqMD8iYPwZvkRjB7QGe2dNtyzbEuC3106rj/WbDuOGaP6Jvjlv1rpxYLbBmk2+O3Z\nABgDHDYBJ6v9+N07O7XJC8HC8ODrWw1+lU2w4P7lXyG/nR0zRvVFj1wX6oKRlA4G0+aK4Zy/zTm/\nAsB4AH9QNpvFQHKTbWCM3avEVm+pqqpq0raFo8ZY9/uXf4Vva4PgAG5f+iXO+CNwK0W1H/pxP6zb\neQIVJ33onuNCtsOKMQPyUdDJDUDuZLvnuLBm23GMXvgpLv/t2qSdcY9cF47U1OP9nZVplUhKGEln\n2z0XQd1smTEZX5YwFkULHKIAQQlHFi0MJcN6aCVMStfsShAQAEjMKJPIZPsl2jZku8mJTzsBGuq6\nNva6PxTF4vUV2irgntlj0SM3Wb6eiFVbjsAflmAVmKabIFoYZo7qg+fukNVCfUEJSyYPSSgvZBMs\nCEZiCUJ501Z4AcAguHF5XhbGD+5muPeMH9wN3To60052/3wg221e4u17zbbj2H70NIqHy/6L02a+\ncl3QyY0RvXPRPceJ0nH9tVDQcYO6YPOhGnRq58DohZ/iVyu9iMaAaSu8CeHU08u8qAtKCX7VGX8E\nedl2zPxRP63USqprB7b0ILCSMdYZAJS/J+N34Jx/CuByxthlkGdBuute7gbguNkHc85f4JwP5ZwP\nzcvLO6/GnCtpWkUvk6/+oA+v2q4N3tRZqRmj+mL11qOGjuoXr5Zj7IDO+PZsAEBDcqieZJ1xXVBC\np3YOLCpJr0TSNkpa2W5T4UoyAeFSBnDxCln3LCtHKBozxM7HCwgARmeDSAtapf0SbQKy3YtArXMW\nL8ai+hJmry8u8cCirNrpJ6qT9fGHq/0YPaAzpq3wQopxOK0CXphShD2zx6D4/7P37vFR1Pf+/3P2\nvptNgIQQE0LKJZAikKyEQgWqgmhA2xRBJGkhaitejj3IQcRjpeekVmsRTIEeDyDWC9JDlGpp+vVC\nxUtbhJ+WQLiVAuFiuDUJCSHZ+87s/P6YnclOdpeKFeSyr8ejj8bd2d3Z5T2feX/e79f79RqVx/2v\n1lKw4B3mvr6DoBTm13eOYP9Tk3i+oph0uwWHNTGN1GE16j7THRA1ay713vPoGztxB8SLueiYjN2v\nCHaTkaXl+vgek5+pFb0TCbr4ghKrKopp8QR1BYd5Nxcwe3y+lr9HW8VFx+OD4/K1Zk801MceHJev\neQ5Gz8d+VUWMC70JrAFUtaM7gd8DCIKQLwiCEPl7OGABWoANwM2CIPSIDMfeHHnsX0Y8+ddEu/Ho\nRaq0KIcNc65jzT2j8AREZo/Pp77JzYbdJ8nLcFAyNDsmMB6qriMso1W/ujvMusB0WIy6Aexr+2ew\ncGohKRYjGU4r3S7Oxe1Kw0UTu18mvAEpYTVYFMN4Q7GdwkfWKQudiiUb9+sqwGr8Js3jLypclvGb\nxBWBZOx+AZhMBtIdFp6vKO7ceEVRJuM938NuwWI0xGwOezotcdf4JRv3a9YRDouJNl8IoyDgDcZn\nmEiyjEEQSLWZtfNIVARv7gjoPjPNZo67WUy1mS/momMydr8imEwG0u2d8b2kzIXT1ln0jhaIiS6C\nvLjpEMfb/DHx++gbO7lzTD9SLEau7Z+R0DJFtYE42urV9guqWOQpdyBhR9thMX4lYkfnbXchCMJa\nlIHYnoIgHENRPPoF8LogCD8EGoBpkcOnAhWCIIQAHzBdlmUZaBUE4WfAXyPHPaEOzP4r6JrcQuzQ\ndDTUzd73v5mH2WgkxWrSNn5lI/Oo/ayVydfk0njGnzAwevew8+s7R2AxKu+tmqp6AiLeoKRVBvJ7\nOTnR5sNiMmAwCLT7QpgMAmcCwaRp6gXCxRy7XxZUMRizQWBpmUs3bK+IuqCJxSRa6FQ0tgcwCgIr\nZxbjtJlo94XYcvAUPVIyk+bxXwGuhPhN4vJEMna/XJhMBi2fSbWZP/fz6ubQYTHiDUoaM6TqjiJ6\npdmob3Kz+I/7aO4IaB2V+iY3lTV7WFUx4p/OI0ZD7dhEz6X/6nsuLEYjTptJO4+OQPyZw6Z2/0Uh\nu5+M3YsLXU3in5w8lHZfiH1PTqK+ya3MCP5xH09PGUZehoOGFi8pFpNmDh+/4GBi9bZjPHN7Ib5g\n/Hj0BSVWzCzGaID5Ews0AUh1LtATlLRGEXTOIqqCM0vLXBd0vlVQ4u7ywogRI+StW7cmfL7DH8Jh\nMVGw4B3EKA8/k0Fg/1OTMAh6WrYYmQkMimFdsrxwaiHrtx/j7rH9cFiM+IISYRnue7VWFxiqrH5Q\nCuO0mLBZjDplIFEMc9oXZPZaJVjnlegDZ1m5i7WfNHD32H5xF/IkzopLylvjn8XulwFRDOMJipz2\nhujptPLipkOUDM3WaM0bdp/UFsIDjcqNvWs8Pz1lGBOq/sQ3+qbz7B1FOCxGnWLW0jIX6SkWTMbk\nJvBfwCUVu3Bh4vdCo+9/vnXe3vvIL2795wddmkjG7iWO6CQ6el2v/rSBZR/U63KTspF5pKdYONjs\nYUBmCr6QxL2rY/OgVRUjkJFjhDC8AZGmjgB90h2R0RmBees6FagXTSskPcVCqyeoy40WTSsk3WH5\nstVBk7F7GaDDH9JisLQoh598e3CMEqg6vrV++zHKR+XxVETFf+XM4rh5fNUdRRgNAtZIrHUExJh4\nXLxhn+YEUP1Jg04R99r+Gfxm1igGPR6799j35CQG/Phtru2foTSjvliuf86xe0VmaGon7/POMflD\nEm3eUMzw8qNv7KRkaDYOi4k/7vkHBkHAYhRieMgLpxbitJp4aG0dTR0BBj3+DpsONOMTFXNtnyjR\nzapUvKqmuxAlWTdzNXttHSVDsy9WznsSlxiCUpiOiNCR3WLk0CmP7vlDpzxal3rD7pMxlInF04pI\nsRrZ/9QkVlWMoLvdrCmG6jjuoUtrUD+JJJJIIgkF0RYS0aMtFaP78vefTWT5jOFkOK3cPbYfNrMB\nQRDolWbFG5Swm40siTOP+Ma2o8rojU8/emOzGJlQ9ScG/Pht3AFJU5uOHkEIh2UWb9inu88s3rAP\nm+Wrl9lP4qvB2XQ91G5eaVEOT3x3iKb0GZ2/3zWmHzndbVSM7kuG08oDN+STmWrl5Y8Px+Txi6YV\nYjII1H7WCoJAqt3M4g37eOb2Qi0XElA0RFT6c8nQbN35/vVIa8IRnPomt3bMhcz1r8hdRXRy++gb\n+lZtNKUg2j+tjyUxLc4XFCnM7U5ICnM6YiOxfMZwUm0mTrT5+d22Y1SM7qsNhi64dTDFX0vXfNXi\n+d9E+5Won+MJiMlOYBL/MqKFjv5xxsdPvn01HX6l+GE1GfjJt6/GF7mRTynO5c3aY6yqGIHdYqS+\nyc3Cd/9OzY4TSuf8yUnIyEy+Jld3LSVnApNIIokkLk2IYjghJc5pNfGPdr/WAZk9Pp87x/RDEMAo\nCDpfvxUzFO+0dn+I1ZuPcNvwXL7ZvycZKVZFUTQcxmRQPAtVal2ikRqH1UT/nimULPmz9vi1/TPw\nBiSctisylb2ikahTrVIp1TGuydfkkppgnjTFaqSxPcDDUb7HS8pcZKRYCIphzR+5vsnNM+/uY9LQ\nLEbnZ+KMKN6WDMnCaTPR0OKN+CjL/OTWwQC8veukbmwGlM2eQSCG/qxYohipf2oSx0778EdRsM83\nrrgrR60U/OjGgZzxhZRFyh5rkh3tDZhiNdHhD8X3wAmIuP0hUu1m2n0hneH7ommFZKRY+MHY/thM\nBm23P/ma3jywZpv2XiVDs+Oatqp+JarXjtOWTKqT+NfhsBrJSrOyYc519HBYaPUGY+LWbDLgC0mk\nOywK3dlqpKHFy5aDp3hwXD6/nO7iaKsXf0hCkuW4HHeF0pCs0CaRRBJJXErwiRKI8b39fCFJKyKW\nFuUw+Zpc7o/y+Fs4tZD6Zg9VGw+w5VCrpnVw6JSHHg4z2d1seIOixjYRwxIvbTqsFeVVllZmqpUH\nx+VrnsvNHQHuGtOPLYdadfeqiHuRrmh/sRhxJ3H+EN2pBr2uhz1yzA/G9mfW6q1Ulg6JG8veoMTD\nr+s9judU12kxO6HqTxpts7Qoh+FfS+eVjw8ztTiXHg4L1w3qxek4+dPTU4ZRdUcRnqDI3AkDNfq0\naoviMBtZdecIkJV8zO0XMQgCBoNAitVIUApjEcMXJH6vqCtErRzcu7qWua/V4QmI3L8mvjpotDfg\noMffYfXmIzGKWUvKXKzffoysVBsG4ttIhGVo8wVxB0V+9T0Xz31YT5pdX5U4m8qQqigKMoIg4PaL\neAPi57a3SCKJrvAHJeaVFFBZsyeh/YkBsJuNuAOipqBbU3ecW4Zla6pWj725C0/kZv55RQASxW0y\nnpNIIokkzg/Otr7Ge05AwBIRDevq7Re93p9NJh+U+8DAiKn2/Ilf5y8HmnEHRFrcQWQZWtxBxLBM\nmt3M4j/uY1XFCAZkprBixnDmTyzQ3WtESSbFatTR73o4LBgFkMKK2vtLmw5zoNGNw2LCG5KS95HL\nDNGxKiAwcWiWpr65Yc51ZKVZsZuNeEMSDkun/Ug8JdClZa6zCt91HRl7pKSA1z5toHxkHjLQ1BFA\nTpA/yTJ4AhIfH2hm+sg8/v6ziaycqdiiiOEwCALeoMis1VsZ9LhiJdfqDTL3tTpmr63DG5QIShcm\ndq+oTmB05WDDnOu0fzyIrSJEJ8eANtyp0DzNnGjzIUphZnyzL4GQdBa/NSOzVu9kxcxi0lOszL1p\nEN5Im7pkaDYDMlPwBET2PzmJdr9iOn+w2cOG3SfxBSWeuV2pdN0fJbrxy+kubGZDrBDHBVQUSuLS\nRViWtdhO7NFkwh/svF5Ki3L4wdh+nHIHWXPPKP5xxkdYhvQUq0a7iB6AVm0momk6Z6NvqF13h8VE\niztId4cZJ6ZkPCeRRBJJnCOiu2L+oIQ7KOroZ+q6C8Rdk2s/a2VMfia1n7WyfMZw0uxmvAERVcti\n49zrqXpvv66AXVqUo3XufEGJ0qIcmjsCuAMiaXYzL206zA+/1V/XOVGppBWj+3LtADdnfEEtX+qa\nn81bt0PJzywGvr/qE935mk0Gao+0Mn1kHnOiv0u5C6fFhNVswBcMYxD4skVkkrhAOJtQ0a2RTtuv\nvudSjonE+sa512u5dm4POytnFpNiNSobtPpmRudn6jqEpUU5zL1pEIIAV6XZePGuEQTEMKk2E4Ig\nUDI0G09Q4rE3d7HmnlEIAnHzJ7vFyIwXPmFJmYvXPm2gZKhSPF85s1jRAQlKzI3qQGamWhElmarp\nLg40uvnt1qP8YGz/C/K7XlFXQvSuP1H3LcVqwidKcZPjZR8oXbznPjiALMO8dTspWPAOYZmEZqrH\nT/s0Hv2gxyMVrbBM2ag8Nuw+yYk2P/e9WsugBe/wwJptnGjza9YTNpOBbnYzPRxWKkuHcMuwbLYc\nauE/XqujzRvSqg+ZqcowtsEoJLsoSfxTRBcsjp/2JTQBDsuyNlj939+5Gl9IWfwefr0OGZj/WyX+\n711dS9nIPOZOGKgbojZ00alKJDQQlMJ4IwurWvW9kJWwJJJIIolLEfG6eKoFlsOiqDt3BMRYz77q\nOnyilHBNHjswE6fNRP/MVP7r93s42eaj3S8quUokj5k/sYATbcr9o7Qoh3k3d3buZq3eyvyJBSwr\nc/Hyx4dxWIxMviZX1zm5ZVi2RiUd9LjilwYCv/qei9RE7BKLCX8orAnnZaZakQGzwUDJ0GzCYb2o\n3kNr6zjjC3H8tJ8XNx2i1auwspI50qWHrrGq5r0/unEgb83+FpmpVtx+iepPGjTxoBSrkbJReVTW\n7GHQAqXjdvy0n5c/PsyQnO5srm/WBGAmu3KYP7FAY//dv6aWjoBIqtWEOyDhDYjk93LSJ93BX4+0\ncqLNR+MZf0KRF5Vaqiqv//VIK06bCQHI6mbTFU/m3dz5uapvoN1iuCD5/BW1CYw2JT2bOmiK1ZQw\nOXb7Re4e20/z9dv35CQcViNLNu6Pazy5aMM+zTtEDdSAGMYbUII3LOsXLVVx9KHqOjxBifterdUM\nJefdXEBpUY4mMAOxAXTv6lpO+4IaZTSJJLoi+jpYtGFfQhNgh9XEN/qm8/gtgxFQ6A1r7hlFZekQ\n3qw9FpM43D22n46mY+liD5GIehGWZY2Xr77fw6/vIHwZ2tckkUQSSXwZiB5vUe/97qDIaV9QlzcY\nBMhKs+peq5i7GxOuyQ6Libmv1WE1Gfjl9CJS7Way0my6YvQj63aSkWJhaZmLuTcNiqGFquMwyz6o\nxxvxRosursejks5btwOLURlDiJd/HWhy88g6hW5aWpTDT24dTEgKa7S6dVuP8rPJQ3X0wKxuNqxm\nAz+6cSCiJBOIdEmTuLQQHavxNk7zbi4gt4edqcV9tGKEKMlxTd9Lhmbz6Bs7Gdq7O1ajg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ekFw4LyN4AqJGBVYXuAfH5TM7irpRWpTD/IkF+EMSk4Zmx9Cf/SGJ2/53i/ae1/bPYGVF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Fo5sHE9JtvtpF49ghMMw4zgCbASjJy9aF7qgr/uqfnekd8a6KptwnSOhs0k8y7CHtqHBGu/HO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\nqrqERdtPhKBYCly4k8MMvxjE7x7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whcRZTSweX7UfTV4BbkG8ERkRr7rvEmz/92GXJB2X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lhMLM66RXS2mXBVJwtWTB0Mu8DTnNGSkVkd1CAyttc0ap4BWakO/GRQGhZ9UI1T59qb2B0N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qjvHD+mSNC7NX1hGJJ7n4nIos4TA4MVHt16OExkgi5xjQFE3w8S+uYe2cy+jdzefIyzpZ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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11ee22a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "scaler = StandardScaler()\n",
    "X_std = scaler.fit_transform(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X_std, y, test_size = 0.3, random_state = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def rmse(y_true, y_pred):\n",
    "    return sqrt(mean_squared_error(y_true, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.56908403075697"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr = LinearRegression(normalize=False)\n",
    "lr.fit(X_train, y_train)\n",
    "y_train_pred = lr.predict(X_train)\n",
    "y_test_pred = lr.predict(X_test)\n",
    "rmse(y_test, y_test_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from scipy import stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((array([-3.899 , -3.6787, -3.5579, ...,  3.5579,  3.6787,  3.899 ]),\n",
       "  array([-43.4127, -43.029 , -43.029 , ...,  16.7918,  17.4058,  17.4058])),\n",
       " (4.5192590374114339, -0.023764787618388999, 0.98885330775966918))"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ED47/nm/z38aN8JvfwObNvl5+TSj8gWYAJYxoZgrcioaAr+n0wFnLQu5FKhh+XsRL14b0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\n9HLVxm30ZQLQl8lVG7expqe34mSSpMG6u+HMM0ce+jltGqx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      "text/plain": [
       "<matplotlib.figure.Figure at 0x120462a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "residuals = y_test - y_test_pred\n",
    "\n",
    "plt.figure(figsize=(15, 6))\n",
    "plt.subplot(1, 2, 1)\n",
    "plt.scatter(y_test, residuals)\n",
    "plt.xlabel(\"y_test\")\n",
    "plt.ylabel(\"Residuals\")\n",
    "plt.hlines([0], xmin = 420, xmax = 500, linestyles = \"dashed\")\n",
    "\n",
    "plt.subplot(1, 2, 2)\n",
    "stats.probplot(residuals, plot=plt)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Residual plots show there are outliers in the lower end of the y_test values. qqPlot shows that residuals do not exhibit normaality, indicating non linearity in the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.922813</td>\n",
       "      <td>-1.038771</td>\n",
       "      <td>1.548754</td>\n",
       "      <td>0.887904</td>\n",
       "      <td>-0.961410</td>\n",
       "      <td>-0.981797</td>\n",
       "      <td>-0.911073</td>\n",
       "      <td>-0.588861</td>\n",
       "      <td>-1.003315</td>\n",
       "      <td>-1.017924</td>\n",
       "      <td>-0.360645</td>\n",
       "      <td>1.551684</td>\n",
       "      <td>0.938456</td>\n",
       "      <td>0.898371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.806093</td>\n",
       "      <td>-0.641344</td>\n",
       "      <td>-0.375735</td>\n",
       "      <td>-1.079505</td>\n",
       "      <td>0.747957</td>\n",
       "      <td>0.058652</td>\n",
       "      <td>0.807495</td>\n",
       "      <td>0.199676</td>\n",
       "      <td>-0.692063</td>\n",
       "      <td>-0.653966</td>\n",
       "      <td>-1.211656</td>\n",
       "      <td>-0.377966</td>\n",
       "      <td>-1.085846</td>\n",
       "      <td>-1.101707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.838247</td>\n",
       "      <td>-0.839664</td>\n",
       "      <td>0.500565</td>\n",
       "      <td>-0.016857</td>\n",
       "      <td>-0.904417</td>\n",
       "      <td>-0.887329</td>\n",
       "      <td>-0.836248</td>\n",
       "      <td>-0.847481</td>\n",
       "      <td>-0.851878</td>\n",
       "      <td>-0.836163</td>\n",
       "      <td>-0.703084</td>\n",
       "      <td>0.497996</td>\n",
       "      <td>-0.002738</td>\n",
       "      <td>-0.120483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.512091</td>\n",
       "      <td>-1.077333</td>\n",
       "      <td>1.134197</td>\n",
       "      <td>-0.278400</td>\n",
       "      <td>-1.282547</td>\n",
       "      <td>-1.273221</td>\n",
       "      <td>-1.512930</td>\n",
       "      <td>-1.687473</td>\n",
       "      <td>-1.031601</td>\n",
       "      <td>-1.065114</td>\n",
       "      <td>-1.062435</td>\n",
       "      <td>1.134184</td>\n",
       "      <td>-0.246762</td>\n",
       "      <td>-0.383576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.232950</td>\n",
       "      <td>1.498469</td>\n",
       "      <td>-0.315068</td>\n",
       "      <td>-0.995069</td>\n",
       "      <td>1.346129</td>\n",
       "      <td>1.527732</td>\n",
       "      <td>1.238003</td>\n",
       "      <td>0.660068</td>\n",
       "      <td>1.602163</td>\n",
       "      <td>1.506417</td>\n",
       "      <td>0.371953</td>\n",
       "      <td>-0.317467</td>\n",
       "      <td>-1.000394</td>\n",
       "      <td>-1.032252</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    0         1         2         3         4         5         6         7   \\\n",
       "0  0.0 -0.922813 -1.038771  1.548754  0.887904 -0.961410 -0.981797 -0.911073   \n",
       "1  0.0  0.806093 -0.641344 -0.375735 -1.079505  0.747957  0.058652  0.807495   \n",
       "2  0.0 -0.838247 -0.839664  0.500565 -0.016857 -0.904417 -0.887329 -0.836248   \n",
       "3  0.0 -1.512091 -1.077333  1.134197 -0.278400 -1.282547 -1.273221 -1.512930   \n",
       "4  0.0  1.232950  1.498469 -0.315068 -0.995069  1.346129  1.527732  1.238003   \n",
       "\n",
       "         8         9         10        11        12        13        14  \n",
       "0 -0.588861 -1.003315 -1.017924 -0.360645  1.551684  0.938456  0.898371  \n",
       "1  0.199676 -0.692063 -0.653966 -1.211656 -0.377966 -1.085846 -1.101707  \n",
       "2 -0.847481 -0.851878 -0.836163 -0.703084  0.497996 -0.002738 -0.120483  \n",
       "3 -1.687473 -1.031601 -1.065114 -1.062435  1.134184 -0.246762 -0.383576  \n",
       "4  0.660068  1.602163  1.506417  0.371953 -0.317467 -1.000394 -1.032252  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "poly = PolynomialFeatures(degree=2)\n",
    "\n",
    "X = df.iloc[:, 0:4].values\n",
    "X_poly = poly.fit_transform(X)\n",
    "X_poly_train, X_poly_test, y_train, y_test = train_test_split(X_poly, y, test_size = 0.3, random_state = 100)\n",
    "X_poly_train_std = scaler.fit_transform(X_poly_train)\n",
    "X_poly_test_std = scaler.transform(X_poly_test)\n",
    "\n",
    "pd.DataFrame(X_poly_train_std).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train rmse:  4.246283890430433\n",
      "Test rmse:  4.276988298022075\n"
     ]
    }
   ],
   "source": [
    "lr.fit(X_poly_train_std, y_train)\n",
    "print(\"Train rmse: \", rmse(y_train, lr.predict(X_poly_train_std)))\n",
    "print(\"Test rmse: \", rmse(y_test, lr.predict(X_poly_test_std)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "454.309651218 [  0.     -39.9701 -42.9304  92.6406  61.3886   4.9224   7.0201  20.0357\n",
      "  -2.6156  -1.2008  36.9954   0.0829 -91.48   -57.9414  -3.7064]\n"
     ]
    }
   ],
   "source": [
    "print(lr.intercept_, lr.coef_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Polynomial regression generally sufferes from overfitting. Let's regularize the model using Lasso."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train rmse:  4.330404075518093\n",
      "Test rmse:  4.35914090833783\n",
      "454.309651218 [  0.     -17.3624  -1.4063   0.4679   0.       4.471    0.      -0.\n",
      "  -1.0568  -0.      -0.435   -1.6751   0.       0.      -0.    ]\n"
     ]
    }
   ],
   "source": [
    "lasso = Lasso(alpha=0.03, max_iter=10000, normalize=False, random_state=100)\n",
    "lasso.fit(X_poly_train_std, y_train)\n",
    "print(\"Train rmse: \", rmse(y_train, lasso.predict(X_poly_train_std)))\n",
    "print(\"Test rmse: \", rmse(y_test, lasso.predict(X_poly_test_std)))\n",
    "print(lasso.intercept_, lasso.coef_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's find cross validation score that accuracy score is more reliable in a sense that it incorporates every piece of is incorporated in both training and testing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE scores [ 4.307   4.371   4.3509  4.3279  4.3506  4.3315  4.4165  4.2604  4.3743\n",
      "  4.3033]\n",
      "Mean rmse:  4.33935182329\n"
     ]
    }
   ],
   "source": [
    "X_poly_std = scaler.fit_transform(X_poly)\n",
    "lasso = Lasso(alpha=0.03, max_iter=10000, random_state=100)\n",
    "scores = cross_val_score(lasso, X_poly_std, y, cv = 10, scoring=\"neg_mean_squared_error\")\n",
    "scores = np.sqrt(-scores)\n",
    "print(\"RMSE scores\", scores)\n",
    "print(\"Mean rmse: \", np.mean(scores))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Encapsulate the steps in a pipeline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.pipeline import Pipeline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.353479757142914"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipeline = Pipeline(steps = [\n",
    "    (\"poly\", PolynomialFeatures(degree=2, include_bias=False)),\n",
    "    (\"scaler\", StandardScaler()),\n",
    "    (\"lasso\", Lasso(alpha=0.03, max_iter=10000, normalize=False, random_state=1))\n",
    "])\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.3, random_state = 1)\n",
    "pipeline.fit(X_train, y_train)\n",
    "rmse(y_test, pipeline.predict(X_test))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "LassoCV helps find the best alpha. We could also use model tuning techqniues to find best alpha as well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lassocv alpha:  0.0161806999848\n",
      "Mean rmse:  4.32254217026\n"
     ]
    }
   ],
   "source": [
    "# Find best alpha\n",
    "lassocv = LassoCV(cv = 10, max_iter=10000, tol=1e-5)\n",
    "lassocv.fit(X_poly_std, y)\n",
    "print(\"Lassocv alpha: \", lassocv.alpha_)\n",
    "\n",
    "# Apply the best alpha to find cross validation score\n",
    "lasso = Lasso(alpha = lassocv.alpha_, max_iter=10000, random_state=100)\n",
    "scores = cross_val_score(lasso, X_poly_std, y, cv = 10, scoring=\"neg_mean_squared_error\")\n",
    "print(\"Mean rmse: \", np.mean(np.sqrt(-scores)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Look at the cofficients values. Many of the features are not zero making the model parsimonious hence more robust - that is less prone to overfitting."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's plot how coefficient reached 0 values by varying the alpha valuess."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/abulbasar/anaconda/lib/python3.6/site-packages/sklearn/linear_model/coordinate_descent.py:491: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Fitting data with very small alpha may cause precision problems.\n",
      "  ConvergenceWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'Coefficients of the features')"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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FL2l76inE56P46qspvfVT+MrK9jrOiceJ9vYSi/QSi0SIhLtp27mD3dsb2L1jO7t3NLJ7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\nEolEIlHKnwQP5beaNKj+AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11fbadba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "coefs = []\n",
    "alphas = 10 ** np.linspace(-5, 5, 20)\n",
    "for alpha in alphas:\n",
    "    lasso = Lasso(alpha=alpha, max_iter=10000, tol=1e-5,random_state=100)\n",
    "    lasso.fit(X_poly_std, y)\n",
    "    coefs.append(lasso.coef_)\n",
    "\n",
    "plt.plot(alphas, coefs)\n",
    "plt.xscale(\"log\")\n",
    "plt.xlabel(\"Alpha (penalty term on the coefficients)\")\n",
    "plt.ylabel(\"Coefficients of the features\")\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From this graph, which alpha values should we select. That question can be answered by looking which alpha values gives the best performance (rmse for example). lassocv function does that for us, or we can use model tuning techniques using grid search - that will be explained later."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Xgboost\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "poly = PolynomialFeatures(degree=2)\n",
    "\n",
    "X = df.iloc[:, 0:4].values\n",
    "X_poly = poly.fit_transform(X)\n",
    "X_poly_train, X_poly_test, y_train, y_test = train_test_split(X_poly, y, test_size = 0.3, random_state = 100)\n",
    "X_poly_train_std = scaler.fit_transform(X_poly_train)\n",
    "X_poly_test_std = scaler.transform(X_poly_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "rmse: 1.8581129118988502\n"
     ]
    }
   ],
   "source": [
    "gbm = xgb.XGBRegressor(max_depth=10, learning_rate=0.1, n_estimators=100, \n",
    "                     objective='reg:linear', booster='gbtree', \n",
    "                     reg_alpha=0.01, reg_lambda=1, random_state=0)\n",
    "gbm.fit(X_poly_train_std, y_train)\n",
    "print(\"rmse:\", rmse(y_test, gbm.predict(X_poly_test_std)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "rmse: 2.019509243562749\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1208e6278>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x120c1d048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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DBswMdycjI6NoaGnp0qX079+fl19+mRNOOKHc8saxP68ypS6OueKWycxSLgxR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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1212735c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "param = {'silent':1, \n",
    "         'objective':'reg:linear', \n",
    "         'booster':'gbtree',\n",
    "         'alpha': 0.01, \n",
    "         'lambda': 1\n",
    "        }\n",
    "\n",
    "dtrain = xgb.DMatrix(X_poly_train_std, label=y_train)\n",
    "dtest = xgb.DMatrix(X_poly_test_std, label=y_test)\n",
    "watchlist  = [(dtrain,'eval'), (dtest, 'train')]\n",
    "num_round = 100\n",
    "bst = xgb.train(param, dtrain, num_round, watchlist, verbose_eval=False)\n",
    "print(\"rmse:\", rmse(y_test, bst.predict(dtest)))\n",
    "\n",
    "plt.figure(figsize=(8, 10))\n",
    "xgb.plot_importance(bst)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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