DS2_Days_3_4.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from scipy import stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CrimeRate</th>\n",
       "      <th>Youth</th>\n",
       "      <th>Southern</th>\n",
       "      <th>Education</th>\n",
       "      <th>ExpenditureYear0</th>\n",
       "      <th>LabourForce</th>\n",
       "      <th>Males</th>\n",
       "      <th>MoreMales</th>\n",
       "      <th>StateSize</th>\n",
       "      <th>YouthUnemployment</th>\n",
       "      <th>...</th>\n",
       "      <th>ExpenditureYear10</th>\n",
       "      <th>LabourForce10</th>\n",
       "      <th>Males10</th>\n",
       "      <th>MoreMales10</th>\n",
       "      <th>StateSize10</th>\n",
       "      <th>YouthUnemploy10</th>\n",
       "      <th>MatureUnemploy10</th>\n",
       "      <th>HighYouthUnemploy10</th>\n",
       "      <th>Wage10</th>\n",
       "      <th>BelowWage10</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>45.5</td>\n",
       "      <td>135</td>\n",
       "      <td>0</td>\n",
       "      <td>12.4</td>\n",
       "      <td>69</td>\n",
       "      <td>540</td>\n",
       "      <td>965</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>80</td>\n",
       "      <td>...</td>\n",
       "      <td>71</td>\n",
       "      <td>564</td>\n",
       "      <td>974</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>82</td>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "      <td>632</td>\n",
       "      <td>142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>52.3</td>\n",
       "      <td>140</td>\n",
       "      <td>0</td>\n",
       "      <td>10.9</td>\n",
       "      <td>55</td>\n",
       "      <td>535</td>\n",
       "      <td>1045</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>135</td>\n",
       "      <td>...</td>\n",
       "      <td>54</td>\n",
       "      <td>540</td>\n",
       "      <td>1039</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>138</td>\n",
       "      <td>39</td>\n",
       "      <td>1</td>\n",
       "      <td>521</td>\n",
       "      <td>210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>56.6</td>\n",
       "      <td>157</td>\n",
       "      <td>1</td>\n",
       "      <td>11.2</td>\n",
       "      <td>47</td>\n",
       "      <td>512</td>\n",
       "      <td>962</td>\n",
       "      <td>0</td>\n",
       "      <td>22</td>\n",
       "      <td>97</td>\n",
       "      <td>...</td>\n",
       "      <td>44</td>\n",
       "      <td>529</td>\n",
       "      <td>959</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>98</td>\n",
       "      <td>33</td>\n",
       "      <td>0</td>\n",
       "      <td>359</td>\n",
       "      <td>256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>60.3</td>\n",
       "      <td>139</td>\n",
       "      <td>1</td>\n",
       "      <td>11.9</td>\n",
       "      <td>46</td>\n",
       "      <td>480</td>\n",
       "      <td>968</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>135</td>\n",
       "      <td>...</td>\n",
       "      <td>41</td>\n",
       "      <td>497</td>\n",
       "      <td>983</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>131</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "      <td>510</td>\n",
       "      <td>235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>64.2</td>\n",
       "      <td>126</td>\n",
       "      <td>0</td>\n",
       "      <td>12.2</td>\n",
       "      <td>106</td>\n",
       "      <td>599</td>\n",
       "      <td>989</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>78</td>\n",
       "      <td>...</td>\n",
       "      <td>97</td>\n",
       "      <td>602</td>\n",
       "      <td>989</td>\n",
       "      <td>0</td>\n",
       "      <td>42</td>\n",
       "      <td>79</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>660</td>\n",
       "      <td>162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>67.6</td>\n",
       "      <td>128</td>\n",
       "      <td>0</td>\n",
       "      <td>13.5</td>\n",
       "      <td>67</td>\n",
       "      <td>624</td>\n",
       "      <td>972</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>77</td>\n",
       "      <td>...</td>\n",
       "      <td>60</td>\n",
       "      <td>621</td>\n",
       "      <td>983</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>81</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>571</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>70.5</td>\n",
       "      <td>130</td>\n",
       "      <td>0</td>\n",
       "      <td>14.1</td>\n",
       "      <td>63</td>\n",
       "      <td>641</td>\n",
       "      <td>984</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>70</td>\n",
       "      <td>...</td>\n",
       "      <td>57</td>\n",
       "      <td>641</td>\n",
       "      <td>993</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>71</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>556</td>\n",
       "      <td>176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>73.2</td>\n",
       "      <td>143</td>\n",
       "      <td>0</td>\n",
       "      <td>12.9</td>\n",
       "      <td>66</td>\n",
       "      <td>537</td>\n",
       "      <td>977</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>114</td>\n",
       "      <td>...</td>\n",
       "      <td>63</td>\n",
       "      <td>549</td>\n",
       "      <td>973</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>119</td>\n",
       "      <td>36</td>\n",
       "      <td>1</td>\n",
       "      <td>561</td>\n",
       "      <td>168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>75.0</td>\n",
       "      <td>141</td>\n",
       "      <td>0</td>\n",
       "      <td>12.9</td>\n",
       "      <td>56</td>\n",
       "      <td>523</td>\n",
       "      <td>968</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>107</td>\n",
       "      <td>...</td>\n",
       "      <td>54</td>\n",
       "      <td>538</td>\n",
       "      <td>968</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>110</td>\n",
       "      <td>36</td>\n",
       "      <td>1</td>\n",
       "      <td>550</td>\n",
       "      <td>126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>78.1</td>\n",
       "      <td>133</td>\n",
       "      <td>0</td>\n",
       "      <td>11.4</td>\n",
       "      <td>51</td>\n",
       "      <td>599</td>\n",
       "      <td>1024</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>99</td>\n",
       "      <td>...</td>\n",
       "      <td>47</td>\n",
       "      <td>600</td>\n",
       "      <td>1024</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>97</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>499</td>\n",
       "      <td>215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>79.8</td>\n",
       "      <td>142</td>\n",
       "      <td>1</td>\n",
       "      <td>12.9</td>\n",
       "      <td>45</td>\n",
       "      <td>533</td>\n",
       "      <td>969</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>94</td>\n",
       "      <td>...</td>\n",
       "      <td>44</td>\n",
       "      <td>552</td>\n",
       "      <td>969</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>93</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>378</td>\n",
       "      <td>247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>82.3</td>\n",
       "      <td>123</td>\n",
       "      <td>0</td>\n",
       "      <td>12.5</td>\n",
       "      <td>97</td>\n",
       "      <td>526</td>\n",
       "      <td>948</td>\n",
       "      <td>0</td>\n",
       "      <td>113</td>\n",
       "      <td>124</td>\n",
       "      <td>...</td>\n",
       "      <td>87</td>\n",
       "      <td>529</td>\n",
       "      <td>949</td>\n",
       "      <td>0</td>\n",
       "      <td>117</td>\n",
       "      <td>125</td>\n",
       "      <td>49</td>\n",
       "      <td>0</td>\n",
       "      <td>639</td>\n",
       "      <td>146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>83.1</td>\n",
       "      <td>135</td>\n",
       "      <td>0</td>\n",
       "      <td>13.6</td>\n",
       "      <td>62</td>\n",
       "      <td>595</td>\n",
       "      <td>986</td>\n",
       "      <td>0</td>\n",
       "      <td>22</td>\n",
       "      <td>77</td>\n",
       "      <td>...</td>\n",
       "      <td>61</td>\n",
       "      <td>599</td>\n",
       "      <td>993</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>80</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "      <td>591</td>\n",
       "      <td>189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>84.9</td>\n",
       "      <td>121</td>\n",
       "      <td>0</td>\n",
       "      <td>13.2</td>\n",
       "      <td>118</td>\n",
       "      <td>547</td>\n",
       "      <td>964</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>84</td>\n",
       "      <td>...</td>\n",
       "      <td>115</td>\n",
       "      <td>538</td>\n",
       "      <td>968</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>82</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>742</td>\n",
       "      <td>127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>85.6</td>\n",
       "      <td>166</td>\n",
       "      <td>1</td>\n",
       "      <td>11.4</td>\n",
       "      <td>58</td>\n",
       "      <td>521</td>\n",
       "      <td>973</td>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>72</td>\n",
       "      <td>...</td>\n",
       "      <td>54</td>\n",
       "      <td>543</td>\n",
       "      <td>983</td>\n",
       "      <td>0</td>\n",
       "      <td>47</td>\n",
       "      <td>76</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>568</td>\n",
       "      <td>246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>88.0</td>\n",
       "      <td>140</td>\n",
       "      <td>0</td>\n",
       "      <td>12.9</td>\n",
       "      <td>71</td>\n",
       "      <td>632</td>\n",
       "      <td>1029</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>100</td>\n",
       "      <td>...</td>\n",
       "      <td>68</td>\n",
       "      <td>620</td>\n",
       "      <td>1024</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>104</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>570</td>\n",
       "      <td>182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>92.3</td>\n",
       "      <td>126</td>\n",
       "      <td>0</td>\n",
       "      <td>12.7</td>\n",
       "      <td>74</td>\n",
       "      <td>602</td>\n",
       "      <td>984</td>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "      <td>102</td>\n",
       "      <td>...</td>\n",
       "      <td>67</td>\n",
       "      <td>599</td>\n",
       "      <td>982</td>\n",
       "      <td>0</td>\n",
       "      <td>33</td>\n",
       "      <td>107</td>\n",
       "      <td>34</td>\n",
       "      <td>1</td>\n",
       "      <td>621</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>94.3</td>\n",
       "      <td>130</td>\n",
       "      <td>0</td>\n",
       "      <td>13.3</td>\n",
       "      <td>128</td>\n",
       "      <td>536</td>\n",
       "      <td>934</td>\n",
       "      <td>0</td>\n",
       "      <td>51</td>\n",
       "      <td>78</td>\n",
       "      <td>...</td>\n",
       "      <td>128</td>\n",
       "      <td>530</td>\n",
       "      <td>949</td>\n",
       "      <td>0</td>\n",
       "      <td>52</td>\n",
       "      <td>79</td>\n",
       "      <td>33</td>\n",
       "      <td>0</td>\n",
       "      <td>692</td>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>95.3</td>\n",
       "      <td>125</td>\n",
       "      <td>0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>90</td>\n",
       "      <td>586</td>\n",
       "      <td>964</td>\n",
       "      <td>0</td>\n",
       "      <td>97</td>\n",
       "      <td>105</td>\n",
       "      <td>...</td>\n",
       "      <td>81</td>\n",
       "      <td>571</td>\n",
       "      <td>971</td>\n",
       "      <td>0</td>\n",
       "      <td>99</td>\n",
       "      <td>106</td>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>679</td>\n",
       "      <td>162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>96.8</td>\n",
       "      <td>151</td>\n",
       "      <td>1</td>\n",
       "      <td>10.0</td>\n",
       "      <td>58</td>\n",
       "      <td>510</td>\n",
       "      <td>950</td>\n",
       "      <td>0</td>\n",
       "      <td>33</td>\n",
       "      <td>108</td>\n",
       "      <td>...</td>\n",
       "      <td>56</td>\n",
       "      <td>515</td>\n",
       "      <td>1001</td>\n",
       "      <td>1</td>\n",
       "      <td>32</td>\n",
       "      <td>110</td>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "      <td>465</td>\n",
       "      <td>254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>97.4</td>\n",
       "      <td>152</td>\n",
       "      <td>1</td>\n",
       "      <td>10.8</td>\n",
       "      <td>57</td>\n",
       "      <td>530</td>\n",
       "      <td>986</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>92</td>\n",
       "      <td>...</td>\n",
       "      <td>53</td>\n",
       "      <td>541</td>\n",
       "      <td>989</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>92</td>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>470</td>\n",
       "      <td>243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>98.7</td>\n",
       "      <td>162</td>\n",
       "      <td>1</td>\n",
       "      <td>12.1</td>\n",
       "      <td>75</td>\n",
       "      <td>522</td>\n",
       "      <td>996</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>73</td>\n",
       "      <td>...</td>\n",
       "      <td>70</td>\n",
       "      <td>533</td>\n",
       "      <td>992</td>\n",
       "      <td>0</td>\n",
       "      <td>41</td>\n",
       "      <td>80</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "      <td>562</td>\n",
       "      <td>229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>99.9</td>\n",
       "      <td>149</td>\n",
       "      <td>1</td>\n",
       "      <td>10.7</td>\n",
       "      <td>61</td>\n",
       "      <td>515</td>\n",
       "      <td>953</td>\n",
       "      <td>0</td>\n",
       "      <td>36</td>\n",
       "      <td>86</td>\n",
       "      <td>...</td>\n",
       "      <td>54</td>\n",
       "      <td>520</td>\n",
       "      <td>952</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>84</td>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>476</td>\n",
       "      <td>249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>103.0</td>\n",
       "      <td>177</td>\n",
       "      <td>1</td>\n",
       "      <td>11.0</td>\n",
       "      <td>58</td>\n",
       "      <td>638</td>\n",
       "      <td>974</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>76</td>\n",
       "      <td>...</td>\n",
       "      <td>56</td>\n",
       "      <td>638</td>\n",
       "      <td>978</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>79</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "      <td>456</td>\n",
       "      <td>257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>104.3</td>\n",
       "      <td>134</td>\n",
       "      <td>0</td>\n",
       "      <td>12.5</td>\n",
       "      <td>75</td>\n",
       "      <td>595</td>\n",
       "      <td>972</td>\n",
       "      <td>0</td>\n",
       "      <td>47</td>\n",
       "      <td>83</td>\n",
       "      <td>...</td>\n",
       "      <td>71</td>\n",
       "      <td>599</td>\n",
       "      <td>982</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>87</td>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>649</td>\n",
       "      <td>182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>105.9</td>\n",
       "      <td>130</td>\n",
       "      <td>0</td>\n",
       "      <td>13.4</td>\n",
       "      <td>90</td>\n",
       "      <td>623</td>\n",
       "      <td>1049</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>113</td>\n",
       "      <td>...</td>\n",
       "      <td>91</td>\n",
       "      <td>622</td>\n",
       "      <td>1050</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>119</td>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>649</td>\n",
       "      <td>159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>106.6</td>\n",
       "      <td>157</td>\n",
       "      <td>1</td>\n",
       "      <td>11.1</td>\n",
       "      <td>65</td>\n",
       "      <td>553</td>\n",
       "      <td>955</td>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "      <td>81</td>\n",
       "      <td>...</td>\n",
       "      <td>62</td>\n",
       "      <td>562</td>\n",
       "      <td>956</td>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "      <td>85</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>499</td>\n",
       "      <td>243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>107.2</td>\n",
       "      <td>148</td>\n",
       "      <td>0</td>\n",
       "      <td>13.7</td>\n",
       "      <td>72</td>\n",
       "      <td>601</td>\n",
       "      <td>998</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>84</td>\n",
       "      <td>...</td>\n",
       "      <td>66</td>\n",
       "      <td>602</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>87</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>656</td>\n",
       "      <td>151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>108.3</td>\n",
       "      <td>126</td>\n",
       "      <td>0</td>\n",
       "      <td>13.8</td>\n",
       "      <td>97</td>\n",
       "      <td>542</td>\n",
       "      <td>990</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>102</td>\n",
       "      <td>...</td>\n",
       "      <td>97</td>\n",
       "      <td>549</td>\n",
       "      <td>993</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>103</td>\n",
       "      <td>34</td>\n",
       "      <td>1</td>\n",
       "      <td>659</td>\n",
       "      <td>160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>109.4</td>\n",
       "      <td>135</td>\n",
       "      <td>1</td>\n",
       "      <td>11.4</td>\n",
       "      <td>123</td>\n",
       "      <td>537</td>\n",
       "      <td>978</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>89</td>\n",
       "      <td>...</td>\n",
       "      <td>115</td>\n",
       "      <td>529</td>\n",
       "      <td>978</td>\n",
       "      <td>0</td>\n",
       "      <td>32</td>\n",
       "      <td>93</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>703</td>\n",
       "      <td>175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>112.1</td>\n",
       "      <td>142</td>\n",
       "      <td>1</td>\n",
       "      <td>10.9</td>\n",
       "      <td>81</td>\n",
       "      <td>497</td>\n",
       "      <td>956</td>\n",
       "      <td>0</td>\n",
       "      <td>33</td>\n",
       "      <td>116</td>\n",
       "      <td>...</td>\n",
       "      <td>77</td>\n",
       "      <td>501</td>\n",
       "      <td>962</td>\n",
       "      <td>0</td>\n",
       "      <td>33</td>\n",
       "      <td>117</td>\n",
       "      <td>44</td>\n",
       "      <td>0</td>\n",
       "      <td>500</td>\n",
       "      <td>256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>114.3</td>\n",
       "      <td>127</td>\n",
       "      <td>1</td>\n",
       "      <td>12.8</td>\n",
       "      <td>82</td>\n",
       "      <td>519</td>\n",
       "      <td>982</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>97</td>\n",
       "      <td>...</td>\n",
       "      <td>79</td>\n",
       "      <td>510</td>\n",
       "      <td>945</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>99</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "      <td>696</td>\n",
       "      <td>170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>115.1</td>\n",
       "      <td>131</td>\n",
       "      <td>0</td>\n",
       "      <td>13.7</td>\n",
       "      <td>78</td>\n",
       "      <td>574</td>\n",
       "      <td>1038</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>142</td>\n",
       "      <td>...</td>\n",
       "      <td>73</td>\n",
       "      <td>581</td>\n",
       "      <td>1029</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>143</td>\n",
       "      <td>41</td>\n",
       "      <td>1</td>\n",
       "      <td>615</td>\n",
       "      <td>177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>117.2</td>\n",
       "      <td>136</td>\n",
       "      <td>0</td>\n",
       "      <td>12.9</td>\n",
       "      <td>95</td>\n",
       "      <td>574</td>\n",
       "      <td>1012</td>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>111</td>\n",
       "      <td>...</td>\n",
       "      <td>96</td>\n",
       "      <td>581</td>\n",
       "      <td>1011</td>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>115</td>\n",
       "      <td>36</td>\n",
       "      <td>1</td>\n",
       "      <td>691</td>\n",
       "      <td>169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>119.7</td>\n",
       "      <td>119</td>\n",
       "      <td>0</td>\n",
       "      <td>11.9</td>\n",
       "      <td>166</td>\n",
       "      <td>521</td>\n",
       "      <td>938</td>\n",
       "      <td>0</td>\n",
       "      <td>168</td>\n",
       "      <td>92</td>\n",
       "      <td>...</td>\n",
       "      <td>157</td>\n",
       "      <td>524</td>\n",
       "      <td>935</td>\n",
       "      <td>0</td>\n",
       "      <td>180</td>\n",
       "      <td>93</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>698</td>\n",
       "      <td>169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>121.6</td>\n",
       "      <td>147</td>\n",
       "      <td>1</td>\n",
       "      <td>13.9</td>\n",
       "      <td>63</td>\n",
       "      <td>560</td>\n",
       "      <td>972</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>76</td>\n",
       "      <td>...</td>\n",
       "      <td>64</td>\n",
       "      <td>571</td>\n",
       "      <td>970</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>78</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>511</td>\n",
       "      <td>220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>123.4</td>\n",
       "      <td>145</td>\n",
       "      <td>1</td>\n",
       "      <td>11.7</td>\n",
       "      <td>82</td>\n",
       "      <td>560</td>\n",
       "      <td>981</td>\n",
       "      <td>0</td>\n",
       "      <td>96</td>\n",
       "      <td>88</td>\n",
       "      <td>...</td>\n",
       "      <td>74</td>\n",
       "      <td>563</td>\n",
       "      <td>980</td>\n",
       "      <td>0</td>\n",
       "      <td>99</td>\n",
       "      <td>89</td>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>550</td>\n",
       "      <td>230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>127.2</td>\n",
       "      <td>132</td>\n",
       "      <td>0</td>\n",
       "      <td>10.4</td>\n",
       "      <td>87</td>\n",
       "      <td>564</td>\n",
       "      <td>953</td>\n",
       "      <td>0</td>\n",
       "      <td>43</td>\n",
       "      <td>83</td>\n",
       "      <td>...</td>\n",
       "      <td>83</td>\n",
       "      <td>560</td>\n",
       "      <td>948</td>\n",
       "      <td>0</td>\n",
       "      <td>44</td>\n",
       "      <td>83</td>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>589</td>\n",
       "      <td>234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>132.4</td>\n",
       "      <td>152</td>\n",
       "      <td>0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>82</td>\n",
       "      <td>571</td>\n",
       "      <td>1018</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>103</td>\n",
       "      <td>...</td>\n",
       "      <td>76</td>\n",
       "      <td>567</td>\n",
       "      <td>1079</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>105</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>617</td>\n",
       "      <td>204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>135.5</td>\n",
       "      <td>125</td>\n",
       "      <td>0</td>\n",
       "      <td>12.5</td>\n",
       "      <td>113</td>\n",
       "      <td>567</td>\n",
       "      <td>985</td>\n",
       "      <td>0</td>\n",
       "      <td>78</td>\n",
       "      <td>130</td>\n",
       "      <td>...</td>\n",
       "      <td>105</td>\n",
       "      <td>571</td>\n",
       "      <td>993</td>\n",
       "      <td>0</td>\n",
       "      <td>77</td>\n",
       "      <td>131</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>684</td>\n",
       "      <td>174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>137.8</td>\n",
       "      <td>141</td>\n",
       "      <td>0</td>\n",
       "      <td>14.2</td>\n",
       "      <td>109</td>\n",
       "      <td>591</td>\n",
       "      <td>985</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>91</td>\n",
       "      <td>...</td>\n",
       "      <td>101</td>\n",
       "      <td>590</td>\n",
       "      <td>987</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>94</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>649</td>\n",
       "      <td>180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>140.8</td>\n",
       "      <td>150</td>\n",
       "      <td>0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>109</td>\n",
       "      <td>531</td>\n",
       "      <td>964</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>87</td>\n",
       "      <td>...</td>\n",
       "      <td>98</td>\n",
       "      <td>539</td>\n",
       "      <td>982</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>88</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>635</td>\n",
       "      <td>151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>145.4</td>\n",
       "      <td>131</td>\n",
       "      <td>1</td>\n",
       "      <td>12.2</td>\n",
       "      <td>115</td>\n",
       "      <td>542</td>\n",
       "      <td>969</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>79</td>\n",
       "      <td>...</td>\n",
       "      <td>109</td>\n",
       "      <td>548</td>\n",
       "      <td>976</td>\n",
       "      <td>0</td>\n",
       "      <td>52</td>\n",
       "      <td>82</td>\n",
       "      <td>34</td>\n",
       "      <td>0</td>\n",
       "      <td>539</td>\n",
       "      <td>219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>149.3</td>\n",
       "      <td>143</td>\n",
       "      <td>0</td>\n",
       "      <td>12.3</td>\n",
       "      <td>103</td>\n",
       "      <td>583</td>\n",
       "      <td>1012</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>96</td>\n",
       "      <td>...</td>\n",
       "      <td>95</td>\n",
       "      <td>612</td>\n",
       "      <td>1003</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>97</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>625</td>\n",
       "      <td>196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>154.3</td>\n",
       "      <td>124</td>\n",
       "      <td>0</td>\n",
       "      <td>12.3</td>\n",
       "      <td>121</td>\n",
       "      <td>580</td>\n",
       "      <td>966</td>\n",
       "      <td>0</td>\n",
       "      <td>101</td>\n",
       "      <td>77</td>\n",
       "      <td>...</td>\n",
       "      <td>116</td>\n",
       "      <td>580</td>\n",
       "      <td>987</td>\n",
       "      <td>0</td>\n",
       "      <td>104</td>\n",
       "      <td>79</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>719</td>\n",
       "      <td>172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>157.7</td>\n",
       "      <td>136</td>\n",
       "      <td>0</td>\n",
       "      <td>15.1</td>\n",
       "      <td>149</td>\n",
       "      <td>577</td>\n",
       "      <td>994</td>\n",
       "      <td>0</td>\n",
       "      <td>157</td>\n",
       "      <td>102</td>\n",
       "      <td>...</td>\n",
       "      <td>141</td>\n",
       "      <td>578</td>\n",
       "      <td>995</td>\n",
       "      <td>0</td>\n",
       "      <td>160</td>\n",
       "      <td>110</td>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "      <td>739</td>\n",
       "      <td>169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>161.8</td>\n",
       "      <td>131</td>\n",
       "      <td>0</td>\n",
       "      <td>13.2</td>\n",
       "      <td>160</td>\n",
       "      <td>631</td>\n",
       "      <td>1071</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>102</td>\n",
       "      <td>...</td>\n",
       "      <td>143</td>\n",
       "      <td>632</td>\n",
       "      <td>1058</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>100</td>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "      <td>748</td>\n",
       "      <td>150</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>47 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    CrimeRate  Youth  Southern  Education  ExpenditureYear0  LabourForce  \\\n",
       "0        45.5    135         0       12.4                69          540   \n",
       "1        52.3    140         0       10.9                55          535   \n",
       "2        56.6    157         1       11.2                47          512   \n",
       "3        60.3    139         1       11.9                46          480   \n",
       "4        64.2    126         0       12.2               106          599   \n",
       "5        67.6    128         0       13.5                67          624   \n",
       "6        70.5    130         0       14.1                63          641   \n",
       "7        73.2    143         0       12.9                66          537   \n",
       "8        75.0    141         0       12.9                56          523   \n",
       "9        78.1    133         0       11.4                51          599   \n",
       "10       79.8    142         1       12.9                45          533   \n",
       "11       82.3    123         0       12.5                97          526   \n",
       "12       83.1    135         0       13.6                62          595   \n",
       "13       84.9    121         0       13.2               118          547   \n",
       "14       85.6    166         1       11.4                58          521   \n",
       "15       88.0    140         0       12.9                71          632   \n",
       "16       92.3    126         0       12.7                74          602   \n",
       "17       94.3    130         0       13.3               128          536   \n",
       "18       95.3    125         0       12.0                90          586   \n",
       "19       96.8    151         1       10.0                58          510   \n",
       "20       97.4    152         1       10.8                57          530   \n",
       "21       98.7    162         1       12.1                75          522   \n",
       "22       99.9    149         1       10.7                61          515   \n",
       "23      103.0    177         1       11.0                58          638   \n",
       "24      104.3    134         0       12.5                75          595   \n",
       "25      105.9    130         0       13.4                90          623   \n",
       "26      106.6    157         1       11.1                65          553   \n",
       "27      107.2    148         0       13.7                72          601   \n",
       "28      108.3    126         0       13.8                97          542   \n",
       "29      109.4    135         1       11.4               123          537   \n",
       "30      112.1    142         1       10.9                81          497   \n",
       "31      114.3    127         1       12.8                82          519   \n",
       "32      115.1    131         0       13.7                78          574   \n",
       "33      117.2    136         0       12.9                95          574   \n",
       "34      119.7    119         0       11.9               166          521   \n",
       "35      121.6    147         1       13.9                63          560   \n",
       "36      123.4    145         1       11.7                82          560   \n",
       "37      127.2    132         0       10.4                87          564   \n",
       "38      132.4    152         0       12.0                82          571   \n",
       "39      135.5    125         0       12.5               113          567   \n",
       "40      137.8    141         0       14.2               109          591   \n",
       "41      140.8    150         0       12.0               109          531   \n",
       "42      145.4    131         1       12.2               115          542   \n",
       "43      149.3    143         0       12.3               103          583   \n",
       "44      154.3    124         0       12.3               121          580   \n",
       "45      157.7    136         0       15.1               149          577   \n",
       "46      161.8    131         0       13.2               160          631   \n",
       "\n",
       "    Males  MoreMales  StateSize  YouthUnemployment  ...  ExpenditureYear10  \\\n",
       "0     965          0          6                 80  ...                 71   \n",
       "1    1045          1          6                135  ...                 54   \n",
       "2     962          0         22                 97  ...                 44   \n",
       "3     968          0         19                135  ...                 41   \n",
       "4     989          0         40                 78  ...                 97   \n",
       "5     972          0         28                 77  ...                 60   \n",
       "6     984          0         14                 70  ...                 57   \n",
       "7     977          0         10                114  ...                 63   \n",
       "8     968          0          4                107  ...                 54   \n",
       "9    1024          1          7                 99  ...                 47   \n",
       "10    969          0         18                 94  ...                 44   \n",
       "11    948          0        113                124  ...                 87   \n",
       "12    986          0         22                 77  ...                 61   \n",
       "13    964          0         25                 84  ...                115   \n",
       "14    973          0         46                 72  ...                 54   \n",
       "15   1029          1          7                100  ...                 68   \n",
       "16    984          0         34                102  ...                 67   \n",
       "17    934          0         51                 78  ...                128   \n",
       "18    964          0         97                105  ...                 81   \n",
       "19    950          0         33                108  ...                 56   \n",
       "20    986          0         30                 92  ...                 53   \n",
       "21    996          0         40                 73  ...                 70   \n",
       "22    953          0         36                 86  ...                 54   \n",
       "23    974          0         24                 76  ...                 56   \n",
       "24    972          0         47                 83  ...                 71   \n",
       "25   1049          1          3                113  ...                 91   \n",
       "26    955          0         39                 81  ...                 62   \n",
       "27    998          0          9                 84  ...                 66   \n",
       "28    990          0         18                102  ...                 97   \n",
       "29    978          0         31                 89  ...                115   \n",
       "30    956          0         33                116  ...                 77   \n",
       "31    982          0          4                 97  ...                 79   \n",
       "32   1038          1          7                142  ...                 73   \n",
       "33   1012          1         29                111  ...                 96   \n",
       "34    938          0        168                 92  ...                157   \n",
       "35    972          0         23                 76  ...                 64   \n",
       "36    981          0         96                 88  ...                 74   \n",
       "37    953          0         43                 83  ...                 83   \n",
       "38   1018          1         10                103  ...                 76   \n",
       "39    985          0         78                130  ...                105   \n",
       "40    985          0         18                 91  ...                101   \n",
       "41    964          0          9                 87  ...                 98   \n",
       "42    969          0         50                 79  ...                109   \n",
       "43   1012          1         13                 96  ...                 95   \n",
       "44    966          0        101                 77  ...                116   \n",
       "45    994          0        157                102  ...                141   \n",
       "46   1071          1          3                102  ...                143   \n",
       "\n",
       "    LabourForce10  Males10  MoreMales10  StateSize10  YouthUnemploy10  \\\n",
       "0             564      974            0            6               82   \n",
       "1             540     1039            1            7              138   \n",
       "2             529      959            0           24               98   \n",
       "3             497      983            0           20              131   \n",
       "4             602      989            0           42               79   \n",
       "5             621      983            0           28               81   \n",
       "6             641      993            0           14               71   \n",
       "7             549      973            0           11              119   \n",
       "8             538      968            0            5              110   \n",
       "9             600     1024            1            7               97   \n",
       "10            552      969            0           19               93   \n",
       "11            529      949            0          117              125   \n",
       "12            599      993            0           23               80   \n",
       "13            538      968            0           25               82   \n",
       "14            543      983            0           47               76   \n",
       "15            620     1024            1            8              104   \n",
       "16            599      982            0           33              107   \n",
       "17            530      949            0           52               79   \n",
       "18            571      971            0           99              106   \n",
       "19            515     1001            1           32              110   \n",
       "20            541      989            0           30               92   \n",
       "21            533      992            0           41               80   \n",
       "22            520      952            0           35               84   \n",
       "23            638      978            0           25               79   \n",
       "24            599      982            0           50               87   \n",
       "25            622     1050            1            3              119   \n",
       "26            562      956            0           39               85   \n",
       "27            602      999            0            9               87   \n",
       "28            549      993            0           19              103   \n",
       "29            529      978            0           32               93   \n",
       "30            501      962            0           33              117   \n",
       "31            510      945            0            4               99   \n",
       "32            581     1029            1            7              143   \n",
       "33            581     1011            1           29              115   \n",
       "34            524      935            0          180               93   \n",
       "35            571      970            0           24               78   \n",
       "36            563      980            0           99               89   \n",
       "37            560      948            0           44               83   \n",
       "38            567     1079            1           11              105   \n",
       "39            571      993            0           77              131   \n",
       "40            590      987            0           19               94   \n",
       "41            539      982            0           10               88   \n",
       "42            548      976            0           52               82   \n",
       "43            612     1003            1           13               97   \n",
       "44            580      987            0          104               79   \n",
       "45            578      995            0          160              110   \n",
       "46            632     1058            1            4              100   \n",
       "\n",
       "    MatureUnemploy10  HighYouthUnemploy10  Wage10  BelowWage10  \n",
       "0                 20                    1     632          142  \n",
       "1                 39                    1     521          210  \n",
       "2                 33                    0     359          256  \n",
       "3                 50                    0     510          235  \n",
       "4                 24                    1     660          162  \n",
       "5                 24                    1     571          199  \n",
       "6                 23                    1     556          176  \n",
       "7                 36                    1     561          168  \n",
       "8                 36                    1     550          126  \n",
       "9                 28                    1     499          215  \n",
       "10                36                    0     378          247  \n",
       "11                49                    0     639          146  \n",
       "12                28                    0     591          189  \n",
       "13                30                    0     742          127  \n",
       "14                25                    1     568          246  \n",
       "15                25                    1     570          182  \n",
       "16                34                    1     621          199  \n",
       "17                33                    0     692          140  \n",
       "18                41                    0     679          162  \n",
       "19                40                    0     465          254  \n",
       "20                41                    0     470          243  \n",
       "21                28                    0     562          229  \n",
       "22                32                    0     476          249  \n",
       "23                28                    0     456          257  \n",
       "24                32                    0     649          182  \n",
       "25                41                    0     649          159  \n",
       "26                29                    0     499          243  \n",
       "27                15                    0     656          151  \n",
       "28                34                    1     659          160  \n",
       "29                35                    0     703          175  \n",
       "30                44                    0     500          256  \n",
       "31                39                    0     696          170  \n",
       "32                41                    1     615          177  \n",
       "33                36                    1     691          169  \n",
       "34                27                    1     698          169  \n",
       "35                24                    1     511          220  \n",
       "36                29                    1     550          230  \n",
       "37                32                    0     589          234  \n",
       "38                27                    1     617          204  \n",
       "39                59                    0     684          174  \n",
       "40                19                    1     649          180  \n",
       "41                36                    0     635          151  \n",
       "42                34                    0     539          219  \n",
       "43                36                    0     625          196  \n",
       "44                36                    0     719          172  \n",
       "45                40                    0     739          169  \n",
       "46                40                    0     748          150  \n",
       "\n",
       "[47 rows x 27 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Read csv file\n",
    "\n",
    "crime = pd.read_csv('Crime_R.csv')\n",
    "\n",
    "crime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 47 entries, 0 to 46\n",
      "Data columns (total 27 columns):\n",
      " #   Column               Non-Null Count  Dtype  \n",
      "---  ------               --------------  -----  \n",
      " 0   CrimeRate            47 non-null     float64\n",
      " 1   Youth                47 non-null     int64  \n",
      " 2   Southern             47 non-null     int64  \n",
      " 3   Education            47 non-null     float64\n",
      " 4   ExpenditureYear0     47 non-null     int64  \n",
      " 5   LabourForce          47 non-null     int64  \n",
      " 6   Males                47 non-null     int64  \n",
      " 7   MoreMales            47 non-null     int64  \n",
      " 8   StateSize            47 non-null     int64  \n",
      " 9   YouthUnemployment    47 non-null     int64  \n",
      " 10  MatureUnemployment   47 non-null     int64  \n",
      " 11  HighYouthUnemploy    47 non-null     int64  \n",
      " 12  Wage                 47 non-null     int64  \n",
      " 13  BelowWage            47 non-null     int64  \n",
      " 14  CrimeRate10          47 non-null     float64\n",
      " 15  Youth10              47 non-null     int64  \n",
      " 16  Education10          47 non-null     float64\n",
      " 17  ExpenditureYear10    47 non-null     int64  \n",
      " 18  LabourForce10        47 non-null     int64  \n",
      " 19  Males10              47 non-null     int64  \n",
      " 20  MoreMales10          47 non-null     int64  \n",
      " 21  StateSize10          47 non-null     int64  \n",
      " 22  YouthUnemploy10      47 non-null     int64  \n",
      " 23  MatureUnemploy10     47 non-null     int64  \n",
      " 24  HighYouthUnemploy10  47 non-null     int64  \n",
      " 25  Wage10               47 non-null     int64  \n",
      " 26  BelowWage10          47 non-null     int64  \n",
      "dtypes: float64(4), int64(23)\n",
      "memory usage: 10.0 KB\n"
     ]
    }
   ],
   "source": [
    "#Explore dataset\n",
    "\n",
    "crime.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CrimeRate</th>\n",
       "      <th>Youth</th>\n",
       "      <th>Southern</th>\n",
       "      <th>Education</th>\n",
       "      <th>ExpenditureYear0</th>\n",
       "      <th>LabourForce</th>\n",
       "      <th>Males</th>\n",
       "      <th>MoreMales</th>\n",
       "      <th>StateSize</th>\n",
       "      <th>YouthUnemployment</th>\n",
       "      <th>...</th>\n",
       "      <th>ExpenditureYear10</th>\n",
       "      <th>LabourForce10</th>\n",
       "      <th>Males10</th>\n",
       "      <th>MoreMales10</th>\n",
       "      <th>StateSize10</th>\n",
       "      <th>YouthUnemploy10</th>\n",
       "      <th>MatureUnemploy10</th>\n",
       "      <th>HighYouthUnemploy10</th>\n",
       "      <th>Wage10</th>\n",
       "      <th>BelowWage10</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>47.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>47.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>102.808511</td>\n",
       "      <td>138.574468</td>\n",
       "      <td>0.340426</td>\n",
       "      <td>12.391489</td>\n",
       "      <td>85.000000</td>\n",
       "      <td>561.191489</td>\n",
       "      <td>983.021277</td>\n",
       "      <td>0.191489</td>\n",
       "      <td>36.617021</td>\n",
       "      <td>95.468085</td>\n",
       "      <td>...</td>\n",
       "      <td>80.234043</td>\n",
       "      <td>565.531915</td>\n",
       "      <td>986.872340</td>\n",
       "      <td>0.212766</td>\n",
       "      <td>37.702128</td>\n",
       "      <td>97.446809</td>\n",
       "      <td>33.361702</td>\n",
       "      <td>0.404255</td>\n",
       "      <td>594.638298</td>\n",
       "      <td>192.957447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>28.893266</td>\n",
       "      <td>12.567634</td>\n",
       "      <td>0.478975</td>\n",
       "      <td>1.120332</td>\n",
       "      <td>29.718974</td>\n",
       "      <td>40.411814</td>\n",
       "      <td>29.467365</td>\n",
       "      <td>0.397727</td>\n",
       "      <td>38.071188</td>\n",
       "      <td>18.028783</td>\n",
       "      <td>...</td>\n",
       "      <td>27.961319</td>\n",
       "      <td>37.645284</td>\n",
       "      <td>29.845702</td>\n",
       "      <td>0.413688</td>\n",
       "      <td>39.490734</td>\n",
       "      <td>17.843289</td>\n",
       "      <td>8.414340</td>\n",
       "      <td>0.496053</td>\n",
       "      <td>93.749765</td>\n",
       "      <td>38.756182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>45.500000</td>\n",
       "      <td>119.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>45.000000</td>\n",
       "      <td>480.000000</td>\n",
       "      <td>934.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>497.000000</td>\n",
       "      <td>935.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>359.000000</td>\n",
       "      <td>126.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>82.700000</td>\n",
       "      <td>130.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>11.550000</td>\n",
       "      <td>62.500000</td>\n",
       "      <td>530.500000</td>\n",
       "      <td>964.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>80.500000</td>\n",
       "      <td>...</td>\n",
       "      <td>58.500000</td>\n",
       "      <td>538.000000</td>\n",
       "      <td>969.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>530.000000</td>\n",
       "      <td>165.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>103.000000</td>\n",
       "      <td>136.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>12.400000</td>\n",
       "      <td>78.000000</td>\n",
       "      <td>560.000000</td>\n",
       "      <td>977.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>92.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>563.000000</td>\n",
       "      <td>983.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>93.000000</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>615.000000</td>\n",
       "      <td>182.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>120.650000</td>\n",
       "      <td>146.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>13.200000</td>\n",
       "      <td>104.500000</td>\n",
       "      <td>593.000000</td>\n",
       "      <td>992.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>41.500000</td>\n",
       "      <td>104.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>599.000000</td>\n",
       "      <td>994.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>108.500000</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>659.500000</td>\n",
       "      <td>229.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>161.800000</td>\n",
       "      <td>177.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>15.100000</td>\n",
       "      <td>166.000000</td>\n",
       "      <td>641.000000</td>\n",
       "      <td>1071.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>168.000000</td>\n",
       "      <td>142.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>157.000000</td>\n",
       "      <td>641.000000</td>\n",
       "      <td>1079.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>180.000000</td>\n",
       "      <td>143.000000</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>748.000000</td>\n",
       "      <td>257.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        CrimeRate       Youth   Southern  Education  ExpenditureYear0  \\\n",
       "count   47.000000   47.000000  47.000000  47.000000         47.000000   \n",
       "mean   102.808511  138.574468   0.340426  12.391489         85.000000   \n",
       "std     28.893266   12.567634   0.478975   1.120332         29.718974   \n",
       "min     45.500000  119.000000   0.000000  10.000000         45.000000   \n",
       "25%     82.700000  130.000000   0.000000  11.550000         62.500000   \n",
       "50%    103.000000  136.000000   0.000000  12.400000         78.000000   \n",
       "75%    120.650000  146.000000   1.000000  13.200000        104.500000   \n",
       "max    161.800000  177.000000   1.000000  15.100000        166.000000   \n",
       "\n",
       "       LabourForce        Males  MoreMales   StateSize  YouthUnemployment  \\\n",
       "count    47.000000    47.000000  47.000000   47.000000          47.000000   \n",
       "mean    561.191489   983.021277   0.191489   36.617021          95.468085   \n",
       "std      40.411814    29.467365   0.397727   38.071188          18.028783   \n",
       "min     480.000000   934.000000   0.000000    3.000000          70.000000   \n",
       "25%     530.500000   964.500000   0.000000   10.000000          80.500000   \n",
       "50%     560.000000   977.000000   0.000000   25.000000          92.000000   \n",
       "75%     593.000000   992.000000   0.000000   41.500000         104.000000   \n",
       "max     641.000000  1071.000000   1.000000  168.000000         142.000000   \n",
       "\n",
       "       ...  ExpenditureYear10  LabourForce10      Males10  MoreMales10  \\\n",
       "count  ...          47.000000      47.000000    47.000000    47.000000   \n",
       "mean   ...          80.234043     565.531915   986.872340     0.212766   \n",
       "std    ...          27.961319      37.645284    29.845702     0.413688   \n",
       "min    ...          41.000000     497.000000   935.000000     0.000000   \n",
       "25%    ...          58.500000     538.000000   969.500000     0.000000   \n",
       "50%    ...          73.000000     563.000000   983.000000     0.000000   \n",
       "75%    ...          97.000000     599.000000   994.000000     0.000000   \n",
       "max    ...         157.000000     641.000000  1079.000000     1.000000   \n",
       "\n",
       "       StateSize10  YouthUnemploy10  MatureUnemploy10  HighYouthUnemploy10  \\\n",
       "count    47.000000        47.000000         47.000000            47.000000   \n",
       "mean     37.702128        97.446809         33.361702             0.404255   \n",
       "std      39.490734        17.843289          8.414340             0.496053   \n",
       "min       3.000000        71.000000         15.000000             0.000000   \n",
       "25%      11.000000        82.000000         28.000000             0.000000   \n",
       "50%      25.000000        93.000000         34.000000             0.000000   \n",
       "75%      43.000000       108.500000         39.000000             1.000000   \n",
       "max     180.000000       143.000000         59.000000             1.000000   \n",
       "\n",
       "           Wage10  BelowWage10  \n",
       "count   47.000000    47.000000  \n",
       "mean   594.638298   192.957447  \n",
       "std     93.749765    38.756182  \n",
       "min    359.000000   126.000000  \n",
       "25%    530.000000   165.000000  \n",
       "50%    615.000000   182.000000  \n",
       "75%    659.500000   229.500000  \n",
       "max    748.000000   257.000000  \n",
       "\n",
       "[8 rows x 27 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "crime.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Check for normality\n",
    "#Plot your variable\n",
    "\n",
    "#Matplotlib\n",
    "plt.hist(crime.CrimeRate, bins=10);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='CrimeRate', ylabel='Count'>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Seaborn\n",
    "\n",
    "sns.histplot(x=crime.CrimeRate, bins=10, kde=True, palette='gnuplot2_r')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "102.80851063829788"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Descriptive statistics\n",
    "\n",
    "np.mean(crime.CrimeRate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "103.0"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.median(crime.CrimeRate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "28.58423780640812"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.std(crime.CrimeRate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='YouthUnemployment', ylabel='Count'>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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n3CRgBrDeoxwfsHx7oD2DTseXw2Vm3PnJ6eSnJfCVh5bT0dPvdSSRAwp74TezNOBM4PcAzrle51xLuHPsq6t3gPV17Uwel6r2DHJE0pNi+emVM6ne3cl3n1jjdRyRA/Jij/8YoBH4o5ktN7PfmVmyBzk+YPWOVgYGnQ7hlKNy0oQsbj7nOB5btoMnVuzwOo7IfnlR+GOAE4FfO+dmAXuAW/e9k5ndaGaVZlbZ2BjaVrgDg46VNS2UZieRlRwX0m3J2PflcyYyuzSTf398DdW7O72OI/IhXhT+GqDGOfdW8PojBN4IPsA5d49zrsI5V5GbmxvSQJsbOujsHWBmcUZItyPRIcbv42dXzgTgyw8tp39g0NtAIvsIe+F3ztUB1WZWHlw1D1gX7hxDraxpIT0xltKsJC9jyBhSnJXEDy89geXbW/j5S5u8jiPyAcMq/GY2dzjrDsO/Aveb2SpgJvCjo3iuo9LQ3k1tazczitJ1wpaMqPkzCrhsdhH/b+Fm3tra5HUckfcNd4//F8NcNyzOuRXBYZzpzrmLnXPNR/pcR2tVTSsxPmPK+DSvIsgYdvv8qZRkJfHVv66gtVMtHSQyHLTwm9mpZvZ1INfMbhmy3A6M+glou/sG2FjXzqRxqcTHjvpfRyJQSnwM/33VLBrae7j9qbVexxEBDr3HHwekEDgSJ3XI0gZcFtpoobduZxv9g47pRRleR5ExbEZxBjefPZHHl+/g2dW1XscROfhk6865V4FXzexPzrmqMGUKi0HnWLWjlcKMRHJT1XNfQuvmcyaycGMDtz2+morSTPLSEryOJFFsuGP88WZ2j5ktMLOX9y4hTRZiVU2dtHb1MaNI7Rkk9GL9Pu6+YiadvQPc+thqdfEUTw23N8HDwP8AvwMGQhcnfFbWtJAc7+eYXHXhlPCYmJfCrRdM4vtPreOhd6q5+qQSryNJlBpu4e93zv06pEnCqKUz0IXzlAlZ+H06hFPC57pTy3hhXT0/eHodc4/NoSRb545I+A13qOcpM/uSmY03s6y9S0iThdCqmlZ8BtPUhVPCzOcz7rp8Bn4zvv7wCgYGNeQj4Tfcwn8d8E3gTWBpcKkMVahQ6hsYZG1tGxPzUkiOVxdOCb/CjES+f9FU3tnWzG9f2+p1HIlCw6p8zrkJoQ4SLhvq2untH2SGDuEUD10yq5AFa+u5e8G7fOT4XCbrBEIJo+G2bPjM/pZQhxtpzjlW1bSQmxLP+HQdTifeMTN+eMk00hJj+dpfV9DTPyaOmZBRYrhDPXOGLGcAtwPzQ5QpZHa2dLOro5fpxerLI97LTonnzk+ewIa6dn72ohq5SfgMd6jnX4deN7N04N6QJAqhlTUtxMf4KM9P9TqKCADzJudz1ZxifvPqFuZNyqOibNQeMyGjyJG2Ze4EjhvJIKHW0d3PlsYOphakEevXROoSOf79wikUZCTy9YdXskdz9UoYDHeM/ykzezK4PANsBJ4IbbSRtXpnK4MO9eWRiJMSH8N/XT6D7bs7+dGz672OI1FguMcz/mTI5X6gyjlXE4I8ITEw6Fizo5Wy7CTSE2O9jiPyIScfk83nzziGexZt5dwp+Zxdnud1JBnDhrXHH2zWtoFAZ85MoDeUoUba3qkVZ2hqRRlp5sPMRmS5bf4MehuruPbnz+FPTD2q5youKfX6lZEINqw9fjO7ArgLeAUw4Bdm9k3n3CMhzDZiNLWihIwb5O4FG0fs6Rrau/nrO9XM+9HTXDBt/BE/zy3nlx/6ThK1hjvUcxswxznXAGBmucCLBCZKj2ixecdQ29rNmcfl6BBOiXh5qQmcPCGbxVubOCannfJxOgJNRt5wD2/x7S36QU2H8VhPpZ74CU2tKKNKRWkm49ISWLixgQ4d5SMhMNzi/ZyZPW9m15vZ9cAzwLOhizUyWjp7SZ7yEU2tKKOKz2ecPzWfgUHHi+vq1btfRtyh5tydaGZznXPfBH4DTAdmAIuBe8KQ76g8XFmDLzZBh3DKqJOZFMfpE3Oo2t3J6h2tXseRMeZQe/w/A9oBnHOPOeducc59jcDe/s9CG+3oJcT52bN+kaZWlFFpelE6JVlJvLZpFy2do+pAOolwhyr8Zc65VfuudM5VAmUhSTSCrj2llF1P/tjrGCJHxMw4d3IePp+xYF09gxrykRFyqMJ/sBaWiSMZREQ+LDUhlrPLc6lt7WZpVbPXcWSMOFThf8fMPr/vSjO7gcBkLCISYuX5qRyXl8KSrU00tvd4HUfGgEMdx/9V4HEz+zT/KPQVQBxwSQhziUiQmXF2eR47Wrp4fl0dV80pJsY3Ko6mlgh10H89zrl659xpwPeBbcHl+865U51zdaGPJyIAiXF+zp2cT1NHL0u27vY6joxyw+3HvxBYGOIsInIQE3KSmVaQxtKqZibkJFOYoa/Z5Mjo86LIKHLGcbmkJcSwYG2dpmuUI6bCLzKKxMX4+OjUcbR397NwQ6PO6pUjosIvMsoUZCRy8oQsNta3s6Gu3es4Mgqp8IuMQnMmZFGYkcjCjQ0066xeOUwq/CKjkM+Mj07Nx2fGc2vqGBjUkI8Mn2eF38z8ZrbczJ72KoPIaJaaEMu5k/NpaO9h8ZYmr+PIKOLlHv9XAM0sLXIUJualcEJhOku3N1PVtMfrODJKeFL4zawI+ATwOy+2LzKWnHFcDlnJcSxYV09nryZukUPzao//Z8C3gMED3cHMbjSzSjOrbGxsDFswkdEm1u/jgmnj6OkfZIEmbpFhCHvhN7MLgQbn3EGbvDnn7nHOVTjnKnJzc8OUTmR0ykmJ54zjcqhq6qRSXTzlEIY72fpImgvMN7OPE2j7nGZm9znnrvEgi8iYMb0wnZ0tXSze0kR8yQlex5EIFvY9fufcd5xzRc65MuAq4GUVfZGjZ2bMm5RPRlIsufO/RV1rt9eRJELpOH6RMSQuxscnThiPxSZw8wPL6Bs44NdoEsU8LfzOuVeccxd6mUFkrMlOiafpuV9QWdXMnX/f4HUciUDa4xcZgzrXL+Izp5byu9ff49nVtV7HkQijwi8yRt32icnMKsng6/+7knU727yOIxFEhV9kjIqP8fOba2aTlhjD5/9Sya4OzdcrASr8ImNYXloCv/1MBbs6evjSfcvo7deXvaLCLzLmTS/K4MeXTeftbbv57hNrdGaveHICl4iE2UUzC3m3vp1fLtzCpHGpXD93gteRxEPa4xeJEl8/r5zzpuTzg2fWs3BDg9dxxEMq/CJRwuczfnrlTCaPT+VL9y9jRXWL15HEIyr8IlEkJT6GP1w/h5zUOD73p3fY2tjhdSTxgAq/SJTJS03gL587GYDr/vg2De3q6RNtVPhFotCEnGT+cP0cdrX38tk/vkNHjyZwiSYq/CJRamZxBr+65kQ21LXzL/dW0t034HUkCRMVfpEodnZ5HnddNp03tzTxhfuW0tOv4h8NVPhFotylJxbxo0tO4JWNjdx0/3Kd3RsFVPhFhKtPKuE/LprKi+vr+fKDKv5jnQq/iADwmVPL+O6FU3hubR1fuG9pVI35F5eUYmYRuRSXlI7476uWDSLyvs+dPoGEWD+3/W01n/3jO/zuugqS48d+maip3s7dCzZ6HWO/bjm/fMSfU3v8IvIBnzq5hJ9eMZO3t+3mmt+/xe49vV5HkhGmwi8iH3LxrEJ+/ekTWbezjUt/9Qbbdu3xOpKMIBV+Edmv86eO44HPn0Jbdz+X/vpNllY1ex1JRogKv4gc0OzSTB774mmkJcRw9W+X8HBltdeRZASo8IvIQZXlJPPYl+YypyyTbz6yiu8+sUaHe45yKvwickhZyXH8+bMnceOZx/CXxVV86rdL2NHS5XUsOUIq/CIyLDF+H//28cn8/OpZrK9t44KfLeKZVbVex5IjoMIvIodl/owCnv3KGUzITeGmB5bxzYdX0tbd53UsOQwq/CJy2Eqzk3nkC6dy89kTeXRZDef+16s8t6bO61gyTCr8InJEYv0+vvHRcv5201yyU+L5wn1L+Zd7K6ne3el1NDkEFX4ROSrTizJ48ua5fPtjk3j13Ubm3f0qdz63gXYN/0QsFX4ROWqxfh9fPOtYXv76WVx4wnh+/coWzrrrFX67aCudvZrdK9Ko8IvIiCnISOTuK2fy5M1zmTQ+lR8+u57T71zILxduprVTnwAihQq/iIy46UUZ3P/Pp/DoF0/lhMJ07np+Iyf/54t857FVrK9t8zpe1Bv7/VZFxDOzS7P48+dOYu3OVu5dXMXjy3fw4NvVTC9K5+KZhfzTjAJyU+O9jhl1wr7Hb2bFZrbQzNab2Voz+0q4M4hIeE0tSOeOT05nyXfm8X8unIJz8B9Pr+PkH73IFb9ZzD2LtrClsQPnnNdRo4IXe/z9wNedc8vMLBVYamYvOOfWeZBFRMIoIymOG06fwA2nT2BzQztPrtjJC+sb+NGzG/jRsxsYn57AnLIsTpoQWCbmpuDzmdexx5ywF37nXC1QG7zcbmbrgUJAhV8kikzMS+WW88u55fxyapo7Wbixkbe2NrFkaxNPrtwJQFpCDJPHpwWXVCaNS+PYvBRSomBWsFDy9NUzszJgFvDWfm67EbgRoKSkJLzBRCQkiktKqanefsj7xWSMI754Gu0F5TTmTmBxbim+uMT3bx/Y00J/Sx39LXX0tdTS31JLf0s9/W0NDLQ3gVP30IPxrPCbWQrwKPBV59yHvuZ3zt0D3ANQUVGhgT+RMeBI57Z1ztHa1UdjRw8tnX20dqXR2jWe1q4+Orr7GVogzCAlPobUhBjSEmJJS4glNSF4PTGW1PgYYvwf/HozFPPaRjJPCr+ZxRIo+vc75x7zIoOIjB5mRkZSHBlJcR+6bWDQ0dbdR1tXH+3d/bR1/+PnjpYuNna3s++eY1Kc//03hLSEWFJmXsCO5i6yU+JIiPWH55fyUNgLv5kZ8HtgvXPu7nBvX0TGFr/PyEyKI3M/bwoQeGPY0/PBN4S9Pxvbe9jauIfsj97EI8tqAEiO95OdHE9uajzj0hLIT4snJT6GQOkaG7zY458LXAusNrMVwXX/5px71oMsIjLG+X1GWmIsaYmx+73dOce3Ljudm+5ZQFNHL017emjq6GX59mYGgx8VkuP8jEtPoDAjkeKsJLKT40b1G4EXR/W8DozeV0xExhQzY6B9F2XZyZRlJ7+/vn9wkF3tvdS1dVPf1k1tazdbGvcAgaGiosxESrOSmZCTTGLc6Boe0jFRIiL7EePzMS49gXHpCe+va+vqo7q5k+rmLqp3d/JufQdGoEfRMbnJHJubQvoBPllEEhV+EZFhSkuMZWpiOlML0nHO0djew5bGPWzZ1cFrm3bx2qZd5KfFM2lcGsfnp5AUF5klNjJTiYhEODMjLy2BvLQETj02m9auPjY3dLCxvp1X321k0aZGSrOSgiedJRPji5yemCr8IiIjID0xltmlmcwuzaSpo4cNde1srG/nubV1JL7rZ0pBGtMK0vZ7SGq4qfCLiIyw7JR45k6M57Rjs9m+u5PVO1pZtr2ZpVXNlGQlMaMonQk5yZ4dGaTCLyISImZGaXYypdnJdPT0s3ZnK2t2tPHUqloykmKZVZzB5PFpxPrDOwykwi8iEgYp8TGcPCGbOaVZbGroYNn2ZhZubGTx1iamF2YwvSid5DA1n1PhFxEJI5/PKB+XyvH5Kexs6WbZ9mbe3rabpVXNTB6fSkVZVsgPCVXhFxHxgJlRmJlIYWYizXt6Wba9mfW17aytbaM8P5U5ZVlkJYfmi2AVfhERj2UmxzFvcj4nH5PNsqpmVu9oZUNdOxNzU4jJKhrx7anwi4hEiJT4GM48PpeKskxWVLewsroVX3zSiG8ncs4oEBERAJLiYjjt2BxuOH0CvbXvjvjzq/CLiESouJjQlGgVfhGRKKPCLyISZfTlrshYZL5RPVGIhJYKv8hY5AaPaFLzUIu2Sc0jlYZ6RESijAq/iEiUUeEXEYkyKvwiIlFGhV9EJMqo8IuIRBkVfhGRKKPCLyISZVT4RUSijAq/iEiUUeEXEYkyKvwiIlFGhV9EJMqo8IuIRBkVfhGRKKPCLyISZTwp/Gb2MTPbaGabzexWLzKIiESrsBd+M/MDvwQuAKYAV5vZlHDnEBGJVl7s8Z8EbHbObXXO9QIPARd5kENEJCqZcy68GzS7DPiYc+6fg9evBU52zt28z/1uBG4MXi0HjnQC0Rxg1xE+NpxGS04YPVmVc+SNlqzKGVDqnMvdd6UXk63bftZ96N3HOXcPcM9Rb8ys0jlXcbTPE2qjJSeMnqzKOfJGS1blPDgvhnpqgOIh14uAnR7kEBGJSl4U/neA48xsgpnFAVcBT3qQQ0QkKoV9qMc5129mNwPPA37gD865tSHc5FEPF4XJaMkJoyerco680ZJVOQ8i7F/uioiIt3TmrohIlFHhFxGJMmOq8JtZuZmtGLK0mdlXzSzLzF4ws03Bn5kRkPVrZrbWzNaY2YNmlhChOb8SzLjWzL4aXBcROc3sD2bWYGZrhqw7YDYz+06wTchGM/uoxzkvD76mg2ZWsc/9IynnXWa2wcxWmdnjZpYRoTl/EMy4wswWmFmB1zkPlHXIbd8wM2dmOWHP6pwbkwuBL47rgFLgx8CtwfW3And6nK0QeA9IDF7/X+D6CMw5DVgDJBE4EOBF4LhIyQmcCZwIrBmybr/ZCLQHWQnEAxOALYDfw5yTCZyY+ApQMWR9pOU8H4gJXr4zgl/PtCGXvwz8j9c5D5Q1uL6YwAEuVUBOuLOOqT3+fcwDtjjnqgi0hPhzcP2fgYu9CjVEDJBoZjEECutOIi/nZGCJc67TOdcPvApcQoTkdM4tAnbvs/pA2S4CHnLO9Tjn3gM2E2gf4klO59x659z+zkaPtJwLgn97gCUEzruJxJxtQ64m84+TQj3LGcy1v3+jAD8FvsUHT14NW9axXPivAh4MXs53ztUCBH/meZYqkGEH8BNgO1ALtDrnFhBhOQns7Z9pZtlmlgR8nMCeSqTlHOpA2QqB6iH3qwmuizSRnPNzwN+DlyMup5n90MyqgU8D3w2ujsSc84EdzrmV+9wUtqxjsvAHTwybDzzsdZb9CY47X0Tg41wBkGxm13ib6sOcc+sJfLx/AXiOwMfQ/oM+KHINq1VIBIjInGZ2G4G//f17V+3nbp7mdM7d5pwrJpBxb++viMoZ3IG6jX+8MX3g5v2sC0nWMVn4CbR8Xuacqw9erzez8QDBnw2eJQs4F3jPOdfonOsDHgNOI/Jy4pz7vXPuROfcmQQ+sm4iAnMOcaBso6VVSMTlNLPrgAuBT7vgYDQRmHOIB4BPBi9HWs5jCezwrTSzbcE8y8xsHGHMOlYL/9X8Y5gHAi0hrgtevg54IuyJPmg7cIqZJZmZEfg+Yj2RlxMzywv+LAEuJfC6RlzOIQ6U7UngKjOLN7MJBL6kftuDfIcSUTnN7GPAt4H5zrnOITdFWs7jhlydD2wIXo6onM651c65POdcmXOujECxP9E5VxfWrOH6djtcC4EvSpuA9CHrsoGXCOytvgRkRUDO7xP4x7kGuJfAN/mRmPM1YB2BYZ55kfR6EngTqgX6gv+BbjhYNgIfsbcQaPF9gcc5Lwle7gHqgecjNOdmAuPOK4LL/0RozkeD/5dWAU8BhV7nPFDWfW7fRvConnBmVcsGEZEoM1aHekRE5ABU+EVEoowKv4hIlFHhFxGJMir8IiJRRoVfwsoCXjezC4asu8LMnjuM58gwsy8NuX6WmT19gPtu26f74QHvGw5m1uHVtvfHzMrM7FNe55DwUuGXsHKB44e/ANxtgVbUycAPgZsO42kygC8d6k4yLGWACn+UUeGXsHPOrSFwks23ge8B9wH/FeynvsTMpgOY2e1m9o29j7PAvABlwB3AscHe63cFb04xs0eCvePvD54RfVDB5/+Dmb1iZlvN7MtDbrvGzN4ObuM3ZuYPru8wszvNbKmZvWhmJw15/Pzgfa43syfM7LlgX/Xv7WfbZoFe92vMbLWZXRlcf6+ZXTTkfveb2fzgc/7NzJ4ys/fM7GYzu8XMlgdfs6zg/Y8Nbnepmb1mZpOC6/9kZj83szeDWS8LbuIO4Izg7/m1Yf0BZfQL51lsWrTsXQi0zt0IrAZ+DXwvuP4cYEXw8u3AN4Y8Zg2BPdQyPtiL/SyglUBvEx+wGDg9eNs2Pnhm5FnA00Oe/00CZ03nEDjjO5ZAO+qngNjg/X4FfCZ42RE8oxJ4HFgQfMyMIbmvJ3C2ZjaQGMxdEbytI/jzkwSa3/mBfAJtPMYDHwH+FrxPOoF5G2KCz7kZSAVyg7/vF4L3+ynw1eDll4DjgpdPBl4OXv4TgaaFPgJ93zfv+3poiZ4lZr/vBiIh5pzbY2Z/BToI9Fb6ZHD9yxZoA51+mE/5tnOuBsDMVhB4c3id/Xc3HLruGedcD9BjZg0EivA8YDbwTvCDQyL/aPbWS6BTKQTetHqcc31mtjq4zb1ecM41BfM8BpwOVA65/XTgQefcAIHGcq8Cc5xzT5rZL4M9ki4FHnXO9QdzLHTOtQPtZtZK4M1pb47pZpZCoNnfw0M+8MQP2ebfnHODwDozy9/fiyjRQYVfvDQYXA7UjrafDw5HJhzkuXqGXB7gH/+2m4BMYFfwetaQywd6nAF/ds59Zz/b6XPO7X3jGNz7eOfcoAUm1Rmaf9/fZ6iDDUXdS6Cn/FUEeuDvL+vgkOuDwdw+oMU5N/MAzzv08YccCpOxS2P8EgkWESh0mNlZwC4XmFFpG4Fp6zCzEwm0swVoJzDkMRyvANcGn8MPXAMsPMRjXgIuG9KZNMvMSoe5vb3OCz4ukcAsYG/sc/si4Eoz85tZLoEp+vZ2YvwT8FUA59za4W4w+Jq9Z2aXB3Obmc04xMMO57WUMUKFXyLB7UCFma0i8GXj3rbKjwJZwaGbLwLvAgSHUN4IfjF614ef7gN+AEw0s5XAcgLj5Pcd7AHOuXXAvwMLgpleIDD+fjheJ7DnvoLAcE3lPrc/TqCT5ErgZeBbLtCaFxeYR2I98MfD3CYE3kBvCP6+awlM+HMwq4B+M1upL3ejh7pziowwM7uewJe5Nx/qvgd4fBKBcfsTnXOtI5lNBLTHLxJRzOxcAvM0/EJFX0JFe/wiIlFGe/wiIlFGhV9EJMqo8IuIRBkVfhGRKKPCLyISZf4/JHR/2PohT98AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(x=crime.YouthUnemployment, bins=8, kde=True, palette='gnuplot2_r')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "95.46808510638297"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(crime.YouthUnemployment)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "92.0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.median(crime.YouthUnemployment)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "17.835955871920554"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.std(crime.YouthUnemployment)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "23.5"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.iqr(crime.YouthUnemployment)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ModeResult(mode=array([0], dtype=int64), count=array([31]))"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mode = stats.mode(crime.Southern)\n",
    "mode"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Ana Maria Lobos\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='CrimeRate', ylabel='Density'>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from scipy.stats import norm\n",
    "\n",
    "sns.distplot(crime.CrimeRate, bins=8, fit=norm, kde=True, color='orange')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.6961002872022128e-34"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Hypothesis Testing\n",
    "\n",
    "#Normally distributed samples\n",
    "\n",
    "#H0:there is no relationship between wages and crime rates\n",
    "#Ha:there is a (negative) between wages and crime rates\n",
    "\n",
    "\n",
    "#Welch's T Test - two normally distributed samples - unequal variances\n",
    "\n",
    "#H0: the means are equal\n",
    "#Ha:the two groups do not have equal means\n",
    "\n",
    "#Test\n",
    "\n",
    "stats.ttest_ind(crime.Wage, crime.CrimeRate, equal_var=False).pvalue\n",
    "\n",
    "#P-value = probability of getting your results by chance. We want this to be < 0.05\n",
    "\n",
    "#If p-value is > 0.05 fail to reject H0\n",
    "#If p-value is < 0.05 reject H0\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Statistics=128.000, p=0.004\n",
      "Different distribution (reject H0)\n"
     ]
    }
   ],
   "source": [
    "#Hypothesis Testing\n",
    "\n",
    "#Non-normally distributed samples\n",
    "\n",
    "#H0: there is no relationship between police expenditure and being in a Southern region\n",
    "#Ha: there is a relationship between police expenditure and being in a Southern region\n",
    "\n",
    "#Mann-Whitney U Test\n",
    "\n",
    "#H0:both groups have the same median - the probability that a randomly drawn observation \n",
    "#from Expenditure is larger than a randomly drawn observation from Southern is equal to 50% (0.5)\n",
    "\n",
    "#Ha: both groups do not have the same median\n",
    "\n",
    "crime_south = crime[crime.Southern == 1]\n",
    "crime_north = crime[crime.Southern == 0]\n",
    "\n",
    "stat, p = stats.mannwhitneyu(crime_south.ExpenditureYear0, crime_north.ExpenditureYear0)\n",
    "\n",
    "#Interpret\n",
    "\n",
    "print('Statistics=%.3f, p=%.3f' % (stat,p))\n",
    "\n",
    "alpha = 0.05\n",
    "\n",
    "if p > alpha:\n",
    "    print('Same distribution (fail to reject H0)')\n",
    "else:\n",
    "    print('Different distribution (reject H0)')\n",
    "\n",
    "\n",
    "#P-value = probability of getting your results by chance. We want this to be < 0.05\n",
    "\n",
    "#If p-value is > 0.05 fail to reject H0\n",
    "#If p-value is < 0.05 reject H0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0036388459860889574"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#One sided\n",
    "stats.mannwhitneyu(crime_south.ExpenditureYear0, crime_north.ExpenditureYear0, alternative='less').pvalue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.007277691972177915"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Two-sided\n",
    "stats.mannwhitneyu(crime_south.ExpenditureYear0, crime_north.ExpenditureYear0, alternative='two-sided').pvalue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CrimeRate</th>\n",
       "      <th>Youth</th>\n",
       "      <th>Southern</th>\n",
       "      <th>Education</th>\n",
       "      <th>ExpenditureYear0</th>\n",
       "      <th>LabourForce</th>\n",
       "      <th>Males</th>\n",
       "      <th>MoreMales</th>\n",
       "      <th>StateSize</th>\n",
       "      <th>YouthUnemployment</th>\n",
       "      <th>...</th>\n",
       "      <th>ExpenditureYear10</th>\n",
       "      <th>LabourForce10</th>\n",
       "      <th>Males10</th>\n",
       "      <th>MoreMales10</th>\n",
       "      <th>StateSize10</th>\n",
       "      <th>YouthUnemploy10</th>\n",
       "      <th>MatureUnemploy10</th>\n",
       "      <th>HighYouthUnemploy10</th>\n",
       "      <th>Wage10</th>\n",
       "      <th>BelowWage10</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>45.5</td>\n",
       "      <td>135</td>\n",
       "      <td>0</td>\n",
       "      <td>12.4</td>\n",
       "      <td>69</td>\n",
       "      <td>540</td>\n",
       "      <td>965</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>80</td>\n",
       "      <td>...</td>\n",
       "      <td>71</td>\n",
       "      <td>564</td>\n",
       "      <td>974</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>82</td>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "      <td>632</td>\n",
       "      <td>142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>52.3</td>\n",
       "      <td>140</td>\n",
       "      <td>0</td>\n",
       "      <td>10.9</td>\n",
       "      <td>55</td>\n",
       "      <td>535</td>\n",
       "      <td>1045</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>135</td>\n",
       "      <td>...</td>\n",
       "      <td>54</td>\n",
       "      <td>540</td>\n",
       "      <td>1039</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>138</td>\n",
       "      <td>39</td>\n",
       "      <td>1</td>\n",
       "      <td>521</td>\n",
       "      <td>210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>56.6</td>\n",
       "      <td>157</td>\n",
       "      <td>1</td>\n",
       "      <td>11.2</td>\n",
       "      <td>47</td>\n",
       "      <td>512</td>\n",
       "      <td>962</td>\n",
       "      <td>0</td>\n",
       "      <td>22</td>\n",
       "      <td>97</td>\n",
       "      <td>...</td>\n",
       "      <td>44</td>\n",
       "      <td>529</td>\n",
       "      <td>959</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>98</td>\n",
       "      <td>33</td>\n",
       "      <td>0</td>\n",
       "      <td>359</td>\n",
       "      <td>256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>60.3</td>\n",
       "      <td>139</td>\n",
       "      <td>1</td>\n",
       "      <td>11.9</td>\n",
       "      <td>46</td>\n",
       "      <td>480</td>\n",
       "      <td>968</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>135</td>\n",
       "      <td>...</td>\n",
       "      <td>41</td>\n",
       "      <td>497</td>\n",
       "      <td>983</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>131</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "      <td>510</td>\n",
       "      <td>235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>64.2</td>\n",
       "      <td>126</td>\n",
       "      <td>0</td>\n",
       "      <td>12.2</td>\n",
       "      <td>106</td>\n",
       "      <td>599</td>\n",
       "      <td>989</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>78</td>\n",
       "      <td>...</td>\n",
       "      <td>97</td>\n",
       "      <td>602</td>\n",
       "      <td>989</td>\n",
       "      <td>0</td>\n",
       "      <td>42</td>\n",
       "      <td>79</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>660</td>\n",
       "      <td>162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>67.6</td>\n",
       "      <td>128</td>\n",
       "      <td>0</td>\n",
       "      <td>13.5</td>\n",
       "      <td>67</td>\n",
       "      <td>624</td>\n",
       "      <td>972</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>77</td>\n",
       "      <td>...</td>\n",
       "      <td>60</td>\n",
       "      <td>621</td>\n",
       "      <td>983</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>81</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>571</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>70.5</td>\n",
       "      <td>130</td>\n",
       "      <td>0</td>\n",
       "      <td>14.1</td>\n",
       "      <td>63</td>\n",
       "      <td>641</td>\n",
       "      <td>984</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>70</td>\n",
       "      <td>...</td>\n",
       "      <td>57</td>\n",
       "      <td>641</td>\n",
       "      <td>993</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>71</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>556</td>\n",
       "      <td>176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>73.2</td>\n",
       "      <td>143</td>\n",
       "      <td>0</td>\n",
       "      <td>12.9</td>\n",
       "      <td>66</td>\n",
       "      <td>537</td>\n",
       "      <td>977</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>114</td>\n",
       "      <td>...</td>\n",
       "      <td>63</td>\n",
       "      <td>549</td>\n",
       "      <td>973</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>119</td>\n",
       "      <td>36</td>\n",
       "      <td>1</td>\n",
       "      <td>561</td>\n",
       "      <td>168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>75.0</td>\n",
       "      <td>141</td>\n",
       "      <td>0</td>\n",
       "      <td>12.9</td>\n",
       "      <td>56</td>\n",
       "      <td>523</td>\n",
       "      <td>968</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>107</td>\n",
       "      <td>...</td>\n",
       "      <td>54</td>\n",
       "      <td>538</td>\n",
       "      <td>968</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>110</td>\n",
       "      <td>36</td>\n",
       "      <td>1</td>\n",
       "      <td>550</td>\n",
       "      <td>126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>78.1</td>\n",
       "      <td>133</td>\n",
       "      <td>0</td>\n",
       "      <td>11.4</td>\n",
       "      <td>51</td>\n",
       "      <td>599</td>\n",
       "      <td>1024</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>99</td>\n",
       "      <td>...</td>\n",
       "      <td>47</td>\n",
       "      <td>600</td>\n",
       "      <td>1024</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>97</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>499</td>\n",
       "      <td>215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>79.8</td>\n",
       "      <td>142</td>\n",
       "      <td>1</td>\n",
       "      <td>12.9</td>\n",
       "      <td>45</td>\n",
       "      <td>533</td>\n",
       "      <td>969</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>94</td>\n",
       "      <td>...</td>\n",
       "      <td>44</td>\n",
       "      <td>552</td>\n",
       "      <td>969</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>93</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>378</td>\n",
       "      <td>247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>82.3</td>\n",
       "      <td>123</td>\n",
       "      <td>0</td>\n",
       "      <td>12.5</td>\n",
       "      <td>97</td>\n",
       "      <td>526</td>\n",
       "      <td>948</td>\n",
       "      <td>0</td>\n",
       "      <td>113</td>\n",
       "      <td>124</td>\n",
       "      <td>...</td>\n",
       "      <td>87</td>\n",
       "      <td>529</td>\n",
       "      <td>949</td>\n",
       "      <td>0</td>\n",
       "      <td>117</td>\n",
       "      <td>125</td>\n",
       "      <td>49</td>\n",
       "      <td>0</td>\n",
       "      <td>639</td>\n",
       "      <td>146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>83.1</td>\n",
       "      <td>135</td>\n",
       "      <td>0</td>\n",
       "      <td>13.6</td>\n",
       "      <td>62</td>\n",
       "      <td>595</td>\n",
       "      <td>986</td>\n",
       "      <td>0</td>\n",
       "      <td>22</td>\n",
       "      <td>77</td>\n",
       "      <td>...</td>\n",
       "      <td>61</td>\n",
       "      <td>599</td>\n",
       "      <td>993</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>80</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "      <td>591</td>\n",
       "      <td>189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>84.9</td>\n",
       "      <td>121</td>\n",
       "      <td>0</td>\n",
       "      <td>13.2</td>\n",
       "      <td>118</td>\n",
       "      <td>547</td>\n",
       "      <td>964</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>84</td>\n",
       "      <td>...</td>\n",
       "      <td>115</td>\n",
       "      <td>538</td>\n",
       "      <td>968</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>82</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>742</td>\n",
       "      <td>127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>85.6</td>\n",
       "      <td>166</td>\n",
       "      <td>1</td>\n",
       "      <td>11.4</td>\n",
       "      <td>58</td>\n",
       "      <td>521</td>\n",
       "      <td>973</td>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>72</td>\n",
       "      <td>...</td>\n",
       "      <td>54</td>\n",
       "      <td>543</td>\n",
       "      <td>983</td>\n",
       "      <td>0</td>\n",
       "      <td>47</td>\n",
       "      <td>76</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>568</td>\n",
       "      <td>246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>88.0</td>\n",
       "      <td>140</td>\n",
       "      <td>0</td>\n",
       "      <td>12.9</td>\n",
       "      <td>71</td>\n",
       "      <td>632</td>\n",
       "      <td>1029</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>100</td>\n",
       "      <td>...</td>\n",
       "      <td>68</td>\n",
       "      <td>620</td>\n",
       "      <td>1024</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>104</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>570</td>\n",
       "      <td>182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>92.3</td>\n",
       "      <td>126</td>\n",
       "      <td>0</td>\n",
       "      <td>12.7</td>\n",
       "      <td>74</td>\n",
       "      <td>602</td>\n",
       "      <td>984</td>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "      <td>102</td>\n",
       "      <td>...</td>\n",
       "      <td>67</td>\n",
       "      <td>599</td>\n",
       "      <td>982</td>\n",
       "      <td>0</td>\n",
       "      <td>33</td>\n",
       "      <td>107</td>\n",
       "      <td>34</td>\n",
       "      <td>1</td>\n",
       "      <td>621</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>94.3</td>\n",
       "      <td>130</td>\n",
       "      <td>0</td>\n",
       "      <td>13.3</td>\n",
       "      <td>128</td>\n",
       "      <td>536</td>\n",
       "      <td>934</td>\n",
       "      <td>0</td>\n",
       "      <td>51</td>\n",
       "      <td>78</td>\n",
       "      <td>...</td>\n",
       "      <td>128</td>\n",
       "      <td>530</td>\n",
       "      <td>949</td>\n",
       "      <td>0</td>\n",
       "      <td>52</td>\n",
       "      <td>79</td>\n",
       "      <td>33</td>\n",
       "      <td>0</td>\n",
       "      <td>692</td>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>95.3</td>\n",
       "      <td>125</td>\n",
       "      <td>0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>90</td>\n",
       "      <td>586</td>\n",
       "      <td>964</td>\n",
       "      <td>0</td>\n",
       "      <td>97</td>\n",
       "      <td>105</td>\n",
       "      <td>...</td>\n",
       "      <td>81</td>\n",
       "      <td>571</td>\n",
       "      <td>971</td>\n",
       "      <td>0</td>\n",
       "      <td>99</td>\n",
       "      <td>106</td>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>679</td>\n",
       "      <td>162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>96.8</td>\n",
       "      <td>151</td>\n",
       "      <td>1</td>\n",
       "      <td>10.0</td>\n",
       "      <td>58</td>\n",
       "      <td>510</td>\n",
       "      <td>950</td>\n",
       "      <td>0</td>\n",
       "      <td>33</td>\n",
       "      <td>108</td>\n",
       "      <td>...</td>\n",
       "      <td>56</td>\n",
       "      <td>515</td>\n",
       "      <td>1001</td>\n",
       "      <td>1</td>\n",
       "      <td>32</td>\n",
       "      <td>110</td>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "      <td>465</td>\n",
       "      <td>254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>97.4</td>\n",
       "      <td>152</td>\n",
       "      <td>1</td>\n",
       "      <td>10.8</td>\n",
       "      <td>57</td>\n",
       "      <td>530</td>\n",
       "      <td>986</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>92</td>\n",
       "      <td>...</td>\n",
       "      <td>53</td>\n",
       "      <td>541</td>\n",
       "      <td>989</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>92</td>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>470</td>\n",
       "      <td>243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>98.7</td>\n",
       "      <td>162</td>\n",
       "      <td>1</td>\n",
       "      <td>12.1</td>\n",
       "      <td>75</td>\n",
       "      <td>522</td>\n",
       "      <td>996</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>73</td>\n",
       "      <td>...</td>\n",
       "      <td>70</td>\n",
       "      <td>533</td>\n",
       "      <td>992</td>\n",
       "      <td>0</td>\n",
       "      <td>41</td>\n",
       "      <td>80</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "      <td>562</td>\n",
       "      <td>229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>99.9</td>\n",
       "      <td>149</td>\n",
       "      <td>1</td>\n",
       "      <td>10.7</td>\n",
       "      <td>61</td>\n",
       "      <td>515</td>\n",
       "      <td>953</td>\n",
       "      <td>0</td>\n",
       "      <td>36</td>\n",
       "      <td>86</td>\n",
       "      <td>...</td>\n",
       "      <td>54</td>\n",
       "      <td>520</td>\n",
       "      <td>952</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>84</td>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>476</td>\n",
       "      <td>249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>103.0</td>\n",
       "      <td>177</td>\n",
       "      <td>1</td>\n",
       "      <td>11.0</td>\n",
       "      <td>58</td>\n",
       "      <td>638</td>\n",
       "      <td>974</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>76</td>\n",
       "      <td>...</td>\n",
       "      <td>56</td>\n",
       "      <td>638</td>\n",
       "      <td>978</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>79</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "      <td>456</td>\n",
       "      <td>257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>104.3</td>\n",
       "      <td>134</td>\n",
       "      <td>0</td>\n",
       "      <td>12.5</td>\n",
       "      <td>75</td>\n",
       "      <td>595</td>\n",
       "      <td>972</td>\n",
       "      <td>0</td>\n",
       "      <td>47</td>\n",
       "      <td>83</td>\n",
       "      <td>...</td>\n",
       "      <td>71</td>\n",
       "      <td>599</td>\n",
       "      <td>982</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>87</td>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>649</td>\n",
       "      <td>182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>105.9</td>\n",
       "      <td>130</td>\n",
       "      <td>0</td>\n",
       "      <td>13.4</td>\n",
       "      <td>90</td>\n",
       "      <td>623</td>\n",
       "      <td>1049</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>113</td>\n",
       "      <td>...</td>\n",
       "      <td>91</td>\n",
       "      <td>622</td>\n",
       "      <td>1050</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>119</td>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>649</td>\n",
       "      <td>159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>106.6</td>\n",
       "      <td>157</td>\n",
       "      <td>1</td>\n",
       "      <td>11.1</td>\n",
       "      <td>65</td>\n",
       "      <td>553</td>\n",
       "      <td>955</td>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "      <td>81</td>\n",
       "      <td>...</td>\n",
       "      <td>62</td>\n",
       "      <td>562</td>\n",
       "      <td>956</td>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "      <td>85</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>499</td>\n",
       "      <td>243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>107.2</td>\n",
       "      <td>148</td>\n",
       "      <td>0</td>\n",
       "      <td>13.7</td>\n",
       "      <td>72</td>\n",
       "      <td>601</td>\n",
       "      <td>998</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>84</td>\n",
       "      <td>...</td>\n",
       "      <td>66</td>\n",
       "      <td>602</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>87</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>656</td>\n",
       "      <td>151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>108.3</td>\n",
       "      <td>126</td>\n",
       "      <td>0</td>\n",
       "      <td>13.8</td>\n",
       "      <td>97</td>\n",
       "      <td>542</td>\n",
       "      <td>990</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>102</td>\n",
       "      <td>...</td>\n",
       "      <td>97</td>\n",
       "      <td>549</td>\n",
       "      <td>993</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>103</td>\n",
       "      <td>34</td>\n",
       "      <td>1</td>\n",
       "      <td>659</td>\n",
       "      <td>160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>109.4</td>\n",
       "      <td>135</td>\n",
       "      <td>1</td>\n",
       "      <td>11.4</td>\n",
       "      <td>123</td>\n",
       "      <td>537</td>\n",
       "      <td>978</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>89</td>\n",
       "      <td>...</td>\n",
       "      <td>115</td>\n",
       "      <td>529</td>\n",
       "      <td>978</td>\n",
       "      <td>0</td>\n",
       "      <td>32</td>\n",
       "      <td>93</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>703</td>\n",
       "      <td>175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>112.1</td>\n",
       "      <td>142</td>\n",
       "      <td>1</td>\n",
       "      <td>10.9</td>\n",
       "      <td>81</td>\n",
       "      <td>497</td>\n",
       "      <td>956</td>\n",
       "      <td>0</td>\n",
       "      <td>33</td>\n",
       "      <td>116</td>\n",
       "      <td>...</td>\n",
       "      <td>77</td>\n",
       "      <td>501</td>\n",
       "      <td>962</td>\n",
       "      <td>0</td>\n",
       "      <td>33</td>\n",
       "      <td>117</td>\n",
       "      <td>44</td>\n",
       "      <td>0</td>\n",
       "      <td>500</td>\n",
       "      <td>256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>114.3</td>\n",
       "      <td>127</td>\n",
       "      <td>1</td>\n",
       "      <td>12.8</td>\n",
       "      <td>82</td>\n",
       "      <td>519</td>\n",
       "      <td>982</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>97</td>\n",
       "      <td>...</td>\n",
       "      <td>79</td>\n",
       "      <td>510</td>\n",
       "      <td>945</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>99</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "      <td>696</td>\n",
       "      <td>170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>115.1</td>\n",
       "      <td>131</td>\n",
       "      <td>0</td>\n",
       "      <td>13.7</td>\n",
       "      <td>78</td>\n",
       "      <td>574</td>\n",
       "      <td>1038</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>142</td>\n",
       "      <td>...</td>\n",
       "      <td>73</td>\n",
       "      <td>581</td>\n",
       "      <td>1029</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>143</td>\n",
       "      <td>41</td>\n",
       "      <td>1</td>\n",
       "      <td>615</td>\n",
       "      <td>177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>117.2</td>\n",
       "      <td>136</td>\n",
       "      <td>0</td>\n",
       "      <td>12.9</td>\n",
       "      <td>95</td>\n",
       "      <td>574</td>\n",
       "      <td>1012</td>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>111</td>\n",
       "      <td>...</td>\n",
       "      <td>96</td>\n",
       "      <td>581</td>\n",
       "      <td>1011</td>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>115</td>\n",
       "      <td>36</td>\n",
       "      <td>1</td>\n",
       "      <td>691</td>\n",
       "      <td>169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>119.7</td>\n",
       "      <td>119</td>\n",
       "      <td>0</td>\n",
       "      <td>11.9</td>\n",
       "      <td>166</td>\n",
       "      <td>521</td>\n",
       "      <td>938</td>\n",
       "      <td>0</td>\n",
       "      <td>168</td>\n",
       "      <td>92</td>\n",
       "      <td>...</td>\n",
       "      <td>157</td>\n",
       "      <td>524</td>\n",
       "      <td>935</td>\n",
       "      <td>0</td>\n",
       "      <td>180</td>\n",
       "      <td>93</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>698</td>\n",
       "      <td>169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>121.6</td>\n",
       "      <td>147</td>\n",
       "      <td>1</td>\n",
       "      <td>13.9</td>\n",
       "      <td>63</td>\n",
       "      <td>560</td>\n",
       "      <td>972</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>76</td>\n",
       "      <td>...</td>\n",
       "      <td>64</td>\n",
       "      <td>571</td>\n",
       "      <td>970</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>78</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>511</td>\n",
       "      <td>220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>123.4</td>\n",
       "      <td>145</td>\n",
       "      <td>1</td>\n",
       "      <td>11.7</td>\n",
       "      <td>82</td>\n",
       "      <td>560</td>\n",
       "      <td>981</td>\n",
       "      <td>0</td>\n",
       "      <td>96</td>\n",
       "      <td>88</td>\n",
       "      <td>...</td>\n",
       "      <td>74</td>\n",
       "      <td>563</td>\n",
       "      <td>980</td>\n",
       "      <td>0</td>\n",
       "      <td>99</td>\n",
       "      <td>89</td>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>550</td>\n",
       "      <td>230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>127.2</td>\n",
       "      <td>132</td>\n",
       "      <td>0</td>\n",
       "      <td>10.4</td>\n",
       "      <td>87</td>\n",
       "      <td>564</td>\n",
       "      <td>953</td>\n",
       "      <td>0</td>\n",
       "      <td>43</td>\n",
       "      <td>83</td>\n",
       "      <td>...</td>\n",
       "      <td>83</td>\n",
       "      <td>560</td>\n",
       "      <td>948</td>\n",
       "      <td>0</td>\n",
       "      <td>44</td>\n",
       "      <td>83</td>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>589</td>\n",
       "      <td>234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>132.4</td>\n",
       "      <td>152</td>\n",
       "      <td>0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>82</td>\n",
       "      <td>571</td>\n",
       "      <td>1018</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>103</td>\n",
       "      <td>...</td>\n",
       "      <td>76</td>\n",
       "      <td>567</td>\n",
       "      <td>1079</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>105</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>617</td>\n",
       "      <td>204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>135.5</td>\n",
       "      <td>125</td>\n",
       "      <td>0</td>\n",
       "      <td>12.5</td>\n",
       "      <td>113</td>\n",
       "      <td>567</td>\n",
       "      <td>985</td>\n",
       "      <td>0</td>\n",
       "      <td>78</td>\n",
       "      <td>130</td>\n",
       "      <td>...</td>\n",
       "      <td>105</td>\n",
       "      <td>571</td>\n",
       "      <td>993</td>\n",
       "      <td>0</td>\n",
       "      <td>77</td>\n",
       "      <td>131</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>684</td>\n",
       "      <td>174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>137.8</td>\n",
       "      <td>141</td>\n",
       "      <td>0</td>\n",
       "      <td>14.2</td>\n",
       "      <td>109</td>\n",
       "      <td>591</td>\n",
       "      <td>985</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>91</td>\n",
       "      <td>...</td>\n",
       "      <td>101</td>\n",
       "      <td>590</td>\n",
       "      <td>987</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>94</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>649</td>\n",
       "      <td>180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>140.8</td>\n",
       "      <td>150</td>\n",
       "      <td>0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>109</td>\n",
       "      <td>531</td>\n",
       "      <td>964</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>87</td>\n",
       "      <td>...</td>\n",
       "      <td>98</td>\n",
       "      <td>539</td>\n",
       "      <td>982</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>88</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>635</td>\n",
       "      <td>151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>145.4</td>\n",
       "      <td>131</td>\n",
       "      <td>1</td>\n",
       "      <td>12.2</td>\n",
       "      <td>115</td>\n",
       "      <td>542</td>\n",
       "      <td>969</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>79</td>\n",
       "      <td>...</td>\n",
       "      <td>109</td>\n",
       "      <td>548</td>\n",
       "      <td>976</td>\n",
       "      <td>0</td>\n",
       "      <td>52</td>\n",
       "      <td>82</td>\n",
       "      <td>34</td>\n",
       "      <td>0</td>\n",
       "      <td>539</td>\n",
       "      <td>219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>149.3</td>\n",
       "      <td>143</td>\n",
       "      <td>0</td>\n",
       "      <td>12.3</td>\n",
       "      <td>103</td>\n",
       "      <td>583</td>\n",
       "      <td>1012</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>96</td>\n",
       "      <td>...</td>\n",
       "      <td>95</td>\n",
       "      <td>612</td>\n",
       "      <td>1003</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>97</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>625</td>\n",
       "      <td>196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>154.3</td>\n",
       "      <td>124</td>\n",
       "      <td>0</td>\n",
       "      <td>12.3</td>\n",
       "      <td>121</td>\n",
       "      <td>580</td>\n",
       "      <td>966</td>\n",
       "      <td>0</td>\n",
       "      <td>101</td>\n",
       "      <td>77</td>\n",
       "      <td>...</td>\n",
       "      <td>116</td>\n",
       "      <td>580</td>\n",
       "      <td>987</td>\n",
       "      <td>0</td>\n",
       "      <td>104</td>\n",
       "      <td>79</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>719</td>\n",
       "      <td>172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>157.7</td>\n",
       "      <td>136</td>\n",
       "      <td>0</td>\n",
       "      <td>15.1</td>\n",
       "      <td>149</td>\n",
       "      <td>577</td>\n",
       "      <td>994</td>\n",
       "      <td>0</td>\n",
       "      <td>157</td>\n",
       "      <td>102</td>\n",
       "      <td>...</td>\n",
       "      <td>141</td>\n",
       "      <td>578</td>\n",
       "      <td>995</td>\n",
       "      <td>0</td>\n",
       "      <td>160</td>\n",
       "      <td>110</td>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "      <td>739</td>\n",
       "      <td>169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>161.8</td>\n",
       "      <td>131</td>\n",
       "      <td>0</td>\n",
       "      <td>13.2</td>\n",
       "      <td>160</td>\n",
       "      <td>631</td>\n",
       "      <td>1071</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>102</td>\n",
       "      <td>...</td>\n",
       "      <td>143</td>\n",
       "      <td>632</td>\n",
       "      <td>1058</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>100</td>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "      <td>748</td>\n",
       "      <td>150</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>47 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    CrimeRate  Youth  Southern  Education  ExpenditureYear0  LabourForce  \\\n",
       "0        45.5    135         0       12.4                69          540   \n",
       "1        52.3    140         0       10.9                55          535   \n",
       "2        56.6    157         1       11.2                47          512   \n",
       "3        60.3    139         1       11.9                46          480   \n",
       "4        64.2    126         0       12.2               106          599   \n",
       "5        67.6    128         0       13.5                67          624   \n",
       "6        70.5    130         0       14.1                63          641   \n",
       "7        73.2    143         0       12.9                66          537   \n",
       "8        75.0    141         0       12.9                56          523   \n",
       "9        78.1    133         0       11.4                51          599   \n",
       "10       79.8    142         1       12.9                45          533   \n",
       "11       82.3    123         0       12.5                97          526   \n",
       "12       83.1    135         0       13.6                62          595   \n",
       "13       84.9    121         0       13.2               118          547   \n",
       "14       85.6    166         1       11.4                58          521   \n",
       "15       88.0    140         0       12.9                71          632   \n",
       "16       92.3    126         0       12.7                74          602   \n",
       "17       94.3    130         0       13.3               128          536   \n",
       "18       95.3    125         0       12.0                90          586   \n",
       "19       96.8    151         1       10.0                58          510   \n",
       "20       97.4    152         1       10.8                57          530   \n",
       "21       98.7    162         1       12.1                75          522   \n",
       "22       99.9    149         1       10.7                61          515   \n",
       "23      103.0    177         1       11.0                58          638   \n",
       "24      104.3    134         0       12.5                75          595   \n",
       "25      105.9    130         0       13.4                90          623   \n",
       "26      106.6    157         1       11.1                65          553   \n",
       "27      107.2    148         0       13.7                72          601   \n",
       "28      108.3    126         0       13.8                97          542   \n",
       "29      109.4    135         1       11.4               123          537   \n",
       "30      112.1    142         1       10.9                81          497   \n",
       "31      114.3    127         1       12.8                82          519   \n",
       "32      115.1    131         0       13.7                78          574   \n",
       "33      117.2    136         0       12.9                95          574   \n",
       "34      119.7    119         0       11.9               166          521   \n",
       "35      121.6    147         1       13.9                63          560   \n",
       "36      123.4    145         1       11.7                82          560   \n",
       "37      127.2    132         0       10.4                87          564   \n",
       "38      132.4    152         0       12.0                82          571   \n",
       "39      135.5    125         0       12.5               113          567   \n",
       "40      137.8    141         0       14.2               109          591   \n",
       "41      140.8    150         0       12.0               109          531   \n",
       "42      145.4    131         1       12.2               115          542   \n",
       "43      149.3    143         0       12.3               103          583   \n",
       "44      154.3    124         0       12.3               121          580   \n",
       "45      157.7    136         0       15.1               149          577   \n",
       "46      161.8    131         0       13.2               160          631   \n",
       "\n",
       "    Males  MoreMales  StateSize  YouthUnemployment  ...  ExpenditureYear10  \\\n",
       "0     965          0          6                 80  ...                 71   \n",
       "1    1045          1          6                135  ...                 54   \n",
       "2     962          0         22                 97  ...                 44   \n",
       "3     968          0         19                135  ...                 41   \n",
       "4     989          0         40                 78  ...                 97   \n",
       "5     972          0         28                 77  ...                 60   \n",
       "6     984          0         14                 70  ...                 57   \n",
       "7     977          0         10                114  ...                 63   \n",
       "8     968          0          4                107  ...                 54   \n",
       "9    1024          1          7                 99  ...                 47   \n",
       "10    969          0         18                 94  ...                 44   \n",
       "11    948          0        113                124  ...                 87   \n",
       "12    986          0         22                 77  ...                 61   \n",
       "13    964          0         25                 84  ...                115   \n",
       "14    973          0         46                 72  ...                 54   \n",
       "15   1029          1          7                100  ...                 68   \n",
       "16    984          0         34                102  ...                 67   \n",
       "17    934          0         51                 78  ...                128   \n",
       "18    964          0         97                105  ...                 81   \n",
       "19    950          0         33                108  ...                 56   \n",
       "20    986          0         30                 92  ...                 53   \n",
       "21    996          0         40                 73  ...                 70   \n",
       "22    953          0         36                 86  ...                 54   \n",
       "23    974          0         24                 76  ...                 56   \n",
       "24    972          0         47                 83  ...                 71   \n",
       "25   1049          1          3                113  ...                 91   \n",
       "26    955          0         39                 81  ...                 62   \n",
       "27    998          0          9                 84  ...                 66   \n",
       "28    990          0         18                102  ...                 97   \n",
       "29    978          0         31                 89  ...                115   \n",
       "30    956          0         33                116  ...                 77   \n",
       "31    982          0          4                 97  ...                 79   \n",
       "32   1038          1          7                142  ...                 73   \n",
       "33   1012          1         29                111  ...                 96   \n",
       "34    938          0        168                 92  ...                157   \n",
       "35    972          0         23                 76  ...                 64   \n",
       "36    981          0         96                 88  ...                 74   \n",
       "37    953          0         43                 83  ...                 83   \n",
       "38   1018          1         10                103  ...                 76   \n",
       "39    985          0         78                130  ...                105   \n",
       "40    985          0         18                 91  ...                101   \n",
       "41    964          0          9                 87  ...                 98   \n",
       "42    969          0         50                 79  ...                109   \n",
       "43   1012          1         13                 96  ...                 95   \n",
       "44    966          0        101                 77  ...                116   \n",
       "45    994          0        157                102  ...                141   \n",
       "46   1071          1          3                102  ...                143   \n",
       "\n",
       "    LabourForce10  Males10  MoreMales10  StateSize10  YouthUnemploy10  \\\n",
       "0             564      974            0            6               82   \n",
       "1             540     1039            1            7              138   \n",
       "2             529      959            0           24               98   \n",
       "3             497      983            0           20              131   \n",
       "4             602      989            0           42               79   \n",
       "5             621      983            0           28               81   \n",
       "6             641      993            0           14               71   \n",
       "7             549      973            0           11              119   \n",
       "8             538      968            0            5              110   \n",
       "9             600     1024            1            7               97   \n",
       "10            552      969            0           19               93   \n",
       "11            529      949            0          117              125   \n",
       "12            599      993            0           23               80   \n",
       "13            538      968            0           25               82   \n",
       "14            543      983            0           47               76   \n",
       "15            620     1024            1            8              104   \n",
       "16            599      982            0           33              107   \n",
       "17            530      949            0           52               79   \n",
       "18            571      971            0           99              106   \n",
       "19            515     1001            1           32              110   \n",
       "20            541      989            0           30               92   \n",
       "21            533      992            0           41               80   \n",
       "22            520      952            0           35               84   \n",
       "23            638      978            0           25               79   \n",
       "24            599      982            0           50               87   \n",
       "25            622     1050            1            3              119   \n",
       "26            562      956            0           39               85   \n",
       "27            602      999            0            9               87   \n",
       "28            549      993            0           19              103   \n",
       "29            529      978            0           32               93   \n",
       "30            501      962            0           33              117   \n",
       "31            510      945            0            4               99   \n",
       "32            581     1029            1            7              143   \n",
       "33            581     1011            1           29              115   \n",
       "34            524      935            0          180               93   \n",
       "35            571      970            0           24               78   \n",
       "36            563      980            0           99               89   \n",
       "37            560      948            0           44               83   \n",
       "38            567     1079            1           11              105   \n",
       "39            571      993            0           77              131   \n",
       "40            590      987            0           19               94   \n",
       "41            539      982            0           10               88   \n",
       "42            548      976            0           52               82   \n",
       "43            612     1003            1           13               97   \n",
       "44            580      987            0          104               79   \n",
       "45            578      995            0          160              110   \n",
       "46            632     1058            1            4              100   \n",
       "\n",
       "    MatureUnemploy10  HighYouthUnemploy10  Wage10  BelowWage10  \n",
       "0                 20                    1     632          142  \n",
       "1                 39                    1     521          210  \n",
       "2                 33                    0     359          256  \n",
       "3                 50                    0     510          235  \n",
       "4                 24                    1     660          162  \n",
       "5                 24                    1     571          199  \n",
       "6                 23                    1     556          176  \n",
       "7                 36                    1     561          168  \n",
       "8                 36                    1     550          126  \n",
       "9                 28                    1     499          215  \n",
       "10                36                    0     378          247  \n",
       "11                49                    0     639          146  \n",
       "12                28                    0     591          189  \n",
       "13                30                    0     742          127  \n",
       "14                25                    1     568          246  \n",
       "15                25                    1     570          182  \n",
       "16                34                    1     621          199  \n",
       "17                33                    0     692          140  \n",
       "18                41                    0     679          162  \n",
       "19                40                    0     465          254  \n",
       "20                41                    0     470          243  \n",
       "21                28                    0     562          229  \n",
       "22                32                    0     476          249  \n",
       "23                28                    0     456          257  \n",
       "24                32                    0     649          182  \n",
       "25                41                    0     649          159  \n",
       "26                29                    0     499          243  \n",
       "27                15                    0     656          151  \n",
       "28                34                    1     659          160  \n",
       "29                35                    0     703          175  \n",
       "30                44                    0     500          256  \n",
       "31                39                    0     696          170  \n",
       "32                41                    1     615          177  \n",
       "33                36                    1     691          169  \n",
       "34                27                    1     698          169  \n",
       "35                24                    1     511          220  \n",
       "36                29                    1     550          230  \n",
       "37                32                    0     589          234  \n",
       "38                27                    1     617          204  \n",
       "39                59                    0     684          174  \n",
       "40                19                    1     649          180  \n",
       "41                36                    0     635          151  \n",
       "42                34                    0     539          219  \n",
       "43                36                    0     625          196  \n",
       "44                36                    0     719          172  \n",
       "45                40                    0     739          169  \n",
       "46                40                    0     748          150  \n",
       "\n",
       "[47 rows x 27 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "crime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "85.0"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(crime.ExpenditureYear0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "78.0"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.median(crime.ExpenditureYear0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.1.3\n",
      "1.19.2\n",
      "0.11.0\n"
     ]
    }
   ],
   "source": [
    "print(pd.__version__)\n",
    "print(np.__version__)\n",
    "print(sns.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='ExpenditureYear0', ylabel='Count'>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(x=crime.ExpenditureYear0, hue=crime.Southern)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='ExpenditureYear0', ylabel='Count'>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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KlscCF0XEaqlU9/RJEeOB8QCSirdhlh9rGogbj6x0FS2ikfdWugRrRJZBUA/0KFjuDiwp6tMPuCUNgY7AEZIaIuKODOsyM7MCWQbBDKCXpJ7AYuAE4MTCDhHRc+1jSROBexwCZmatK7MgiIgGSWNI7gaqAyZExFxJZ6Xrx2W1bzMza74sjwiIiCkUfZJZYwEQEadlWYuVSRVfrDSz0jINAqtBVXyxEnzB0qwUTzFhZpZzDgIzs5xzEJiZ5ZyDwMws5xwEZmY55yAwM8s5B4GZWc45CMzMcs5BYGaWcw4CM7OccxCYmeWcg8DMLOccBGZmOecgMDPLOQeBmVnOOQjMzHLOQWBmlnMOAjOznHMQmJnlnIPAzCznHARmZjnnIDAzyzkHgZlZzjkIzMxyzkFgZpZzbStdQN6oTVsmjx5U6TJaro3/y5jVGv9Wt7JY00DceGSly2gxjby30iWYWZn51JCZWc45CMzMcs5BYGaWcw4CM7OccxCYmeWcg8DMLOcyDQJJQyW9KmmepItLrD9J0pz0a5qkvbOsx8zMNpRZEEiqA64BhgG9gRGSehd1exM4KCL6AL8ExmdVj5mZlZblEcEAYF5EzI+IVcAtwPDCDhExLSI+SBenA90zrMfMzErIMgi6AYsKluvTtsacDtxXaoWkUZJmSppZxvrMzIxsp5hQibYo2VE6hCQI9i+1PiLGk542klRyG2Zm1jJZBkE90KNguTuwpLiTpD7ADcCwiHgvw3rMzKyELE8NzQB6SeopqR1wAnBXYQdJuwC3A9+PiNcyrMXMzBqR2RFBRDRIGgM8ANQBEyJirqSz0vXjgEuBHYFrJQE0RES/rGoyM7MNZToNdURMAaYUtY0reHwGcEaWNZiZWdP8zmIzs5xzEJiZ5ZyDwMws5xwEZmY55yAwM8s5B4GZWc45CMzMcs5BYGaWcw4CM7OccxCYmeWcg8DMLOccBGZmOecgMDPLOQeBmVnOOQjMzHLOQWBmlnMOAjOznHMQmJnlnIPAzCznHARmZjnnIDAzyzkHgZlZzjkIzMxyzkFgZpZzDgIzs5xzEJiZ5ZyDwMws5xwEZmY55yAwM8s5B4GZWc45CMzMcs5BYGaWcw4CM7OccxCYmeWcg8DMLOcyDQJJQyW9KmmepItLrJekq9L1cyTtm2U9Zma2ocyCQFIdcA0wDOgNjJDUu6jbMKBX+jUKuC6reszMrLQsjwgGAPMiYn5ErAJuAYYX9RkO/D4S04HtJHXJsCYzMyuiiMhmw9IxwNCIOCNd/j7wrYgYU9DnHuCyiHgyXX4YuCgiZhZtaxTJEQPAnsCrmRRdXh2BdytdREY8tupVy+Pz2Jq2a0R0KrWi7SZuuCkq0VacOs3pQ0SMB8aXo6jWImlmRPSrdB1Z8NiqVy2Pz2NruSxPDdUDPQqWuwNLWtDHzMwylGUQzAB6SeopqR1wAnBXUZ+7gFPSu4cGAh9GxNsZ1mRmZkUyOzUUEQ2SxgAPAHXAhIiYK+msdP04YApwBDAPWAGMzKqeCqiqU1lfkMdWvWp5fB5bC2V2sdjMzKqD31lsZpZzDgIzs5xzEJSBpO0k3SbpFUkvS9pP0g6SHpT0evp9+0rX2RKSzpM0V9KLkiZJ+lI1j03SBEnLJL1Y0NboeCT9LJ0C5VVJh1em6uZpZGyXp/8v50j6s6TtCtZVzdig9PgK1p0vKSR1LGirmvE1NjZJ56T1z5X0HwXt5R1bRPhrE7+Am4Az0sftgO2A/wAuTtsuBn5T6TpbMK5uwJvAlunyn4DTqnlswIHAvsCLBW0lx0MyNcpfgfZAT+ANoK7SY/iCY/s20DZ9/JtqHVtj40vbe5DclLIA6FiN42vkZ3cI8BDQPl3unNXYfESwiSRtQ/JD/C+AiFgVEf9DMn3GTWm3m4DvVqK+MmgLbCmpLdCB5H0eVTu2iHgceL+oubHxDAduiYiVEfEmyd1tA1qjzpYoNbaI+EtENKSL00neqwNVNjZo9GcH8J/Ahaz/ZtSqGl8jY/shycwLK9M+y9L2so/NQbDpdgeWAzdKel7SDZK2AnaK9D0R6ffOlSyyJSJiMXAFsBB4m+R9Hn+hBsZWpLHxdAMWFfSrT9uq1Q+A+9LHNTE2SUcBiyPir0WramF8XwEOkPSMpKmS+qftZR+bg2DTtSU5pLsuIr4JfEJyeqHqpefKh5McfnYFtpJ0cmWralXNmgKlGki6BGgAbl7bVKJbVY1NUgfgEuDSUqtLtFXV+EheW7YHBgIXAH+SJDIYm4Ng09UD9RHxTLp8G0kwvLN2JtX0+7JGnr85Owx4MyKWR8TnwO3AIGpjbIUaG09NTIEi6VTgn4CTIj3JTG2MbQ+SP1L+KuktkjHMkrQztTG+euD2SDwLrCGZfK7sY3MQbKKIWAoskrRn2jQEeIlk+oxT07ZTgTsrUN6mWggMlNQh/UtkCPAytTG2Qo2N5y7gBEntJfUk+dyMZytQX4tJGgpcBBwVESsKVlX92CLihYjoHBG7RcRuJC+Q+6a/k1U/PuAO4FAASV8huRHlXbIYW6WvltfCF7APMBOYk/7wtgd2BB4GXk+/71DpOls4tl8ArwAvAn8guVOhascGTCK53vE5yQvH6U2Nh+TUwxskU58Pq3T9LRjbPJLzybPTr3HVOLbGxle0/i3Su4aqbXyN/OzaAX9Mf/dmAYdmNTZPMWFmlnM+NWRmlnMOAjOznHMQmJnlnIPAzCznHARmZjnnILDNnqTVkmYXfFXknduSJko6Jn18g6Te6eN/KeM+RkmaXLC8jaQ30vvFN2W7VTtjrGXPt4/aZk/SxxGx9WZQx0Tgnoi4raj9C9cnqW38fTK4wnYBTwI/j4iHJI0FlkfErzeh7jrg34H3I+KyNEi3j4iLWrpNqy0+IrCqJGnbdC72PdPlSZLOTB9/LOlKSbMkPSypU9q+h6T7JT0n6QlJX03bJ0q6StI0SfML/uqXpKslvSTpXgom15P0mKR+ki4jmZ11tqSbJe2m9T8P4HxJ/1bwnP8jaSpwrqS+6WRiz0l6QFKXSP4y+yEwVlI/kndzXy7pZEnPpvu5Pn1xR9J1kmam89X/omC/b0m6VNKTwLFU8Yyxlj0HgVWDtS+0a7+Oj4gPgTHAREknkPyF+7u0/1bArIjYF5gK/DxtHw+cExF9gfOBawv20QXYn2ROnsvStqOBPYFvAGeSzLO0noi4GPg0IvaJiJOaMZbtIuIg4Crgt8AxaT0TgF+n25xDMr/+w8CPSebUOR4YHBH7AKuBtfu6JCL6AX2AgyT1KdjXZxGxf0TcQu3NGGtl1LbSBZg1w6fpC+B6IuJBSccC1wB7F6xaA6w9z/5H4HZJW5O8kN+anH0Bkuky1rojItYAL0naKW07EJgUEauBJZIeKcNY1ta1J/B14MG0njqSKQbWuoZk6oBHJY0B+gIz0r5b8veJ8Y6TNIrkd7kLyYeWzCnal1mTHARWtSS1AfYCPgV2IJmjpZQgOfr9n1KBklpZuOmi534RDax/pP2lovWfFOxjbkTs18h21qRfa/veFBE/K+yQXkA+H+gfER+k1zAK9/dJweN30lNPb9fIjLFWRj41ZNXsPJLZUEcAEyRtkba3AY5JH58IPBkRfwPeTI8g1p7/37t4g0UeJ5nlsS598TykkX6fF+z7HaCzpB0ltSc51VTKq0AnSful9Wwh6WuN9H0YOEZS57TvDpJ2BbYhebH/MD2KGdbEWGptxlgrIx8RWDXYUtLsguX7Sc6pnwEMiIiPJD0O/CvJ9YBPgK9Jeg74kOT8OiTn1a+T9K/AFsAtJJ/92pg/k0wD/ALwGsn1hlLGA3MkzYqIkyT9b+AZks97fqXUEyJiVXpR+ipJ25L8Lo4F5pbo+1Ja81/So6DPgbMjYrqk59PnzAeeamIsl5F8sMnpJNOLH9tEX8sZ3z5qNWdzud3UrFr41JCZWc75iMDMLOd8RGBmlnMOAjOznHMQmJnlnIPAzCznHARmZjn3/wEJSOJoDsb21wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(x=crime.ExpenditureYear0, hue=crime.Southern, multiple='fill')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='ExpenditureYear0', ylabel='Count'>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(x=crime.ExpenditureYear0, hue=crime.Southern, multiple='stack')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='ExpenditureYear0', ylabel='Count'>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(x=crime.ExpenditureYear0, hue=crime.Southern, multiple='dodge')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CrimeRate</th>\n",
       "      <th>Youth</th>\n",
       "      <th>Southern</th>\n",
       "      <th>Education</th>\n",
       "      <th>ExpenditureYear0</th>\n",
       "      <th>LabourForce</th>\n",
       "      <th>Males</th>\n",
       "      <th>MoreMales</th>\n",
       "      <th>StateSize</th>\n",
       "      <th>YouthUnemployment</th>\n",
       "      <th>...</th>\n",
       "      <th>ExpenditureYear10</th>\n",
       "      <th>LabourForce10</th>\n",
       "      <th>Males10</th>\n",
       "      <th>MoreMales10</th>\n",
       "      <th>StateSize10</th>\n",
       "      <th>YouthUnemploy10</th>\n",
       "      <th>MatureUnemploy10</th>\n",
       "      <th>HighYouthUnemploy10</th>\n",
       "      <th>Wage10</th>\n",
       "      <th>BelowWage10</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CrimeRate</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.055002</td>\n",
       "      <td>-0.053465</td>\n",
       "      <td>0.157005</td>\n",
       "      <td>0.646211</td>\n",
       "      <td>0.169309</td>\n",
       "      <td>0.157113</td>\n",
       "      <td>0.141546</td>\n",
       "      <td>0.307945</td>\n",
       "      <td>-0.050613</td>\n",
       "      <td>...</td>\n",
       "      <td>0.629700</td>\n",
       "      <td>0.138849</td>\n",
       "      <td>0.163331</td>\n",
       "      <td>0.125157</td>\n",
       "      <td>0.303974</td>\n",
       "      <td>-0.038185</td>\n",
       "      <td>0.165357</td>\n",
       "      <td>-0.281453</td>\n",
       "      <td>0.436740</td>\n",
       "      <td>-0.076246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Youth</th>\n",
       "      <td>-0.055002</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.584355</td>\n",
       "      <td>-0.404477</td>\n",
       "      <td>-0.505737</td>\n",
       "      <td>-0.160949</td>\n",
       "      <td>-0.028680</td>\n",
       "      <td>-0.048581</td>\n",
       "      <td>-0.280638</td>\n",
       "      <td>-0.224381</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.513173</td>\n",
       "      <td>-0.073214</td>\n",
       "      <td>0.059896</td>\n",
       "      <td>0.005249</td>\n",
       "      <td>-0.282565</td>\n",
       "      <td>-0.201452</td>\n",
       "      <td>-0.244174</td>\n",
       "      <td>-0.097341</td>\n",
       "      <td>-0.615583</td>\n",
       "      <td>0.633203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Southern</th>\n",
       "      <td>-0.053465</td>\n",
       "      <td>0.584355</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.496831</td>\n",
       "      <td>-0.372636</td>\n",
       "      <td>-0.505469</td>\n",
       "      <td>-0.314733</td>\n",
       "      <td>-0.349630</td>\n",
       "      <td>-0.049918</td>\n",
       "      <td>-0.172419</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.376168</td>\n",
       "      <td>-0.478050</td>\n",
       "      <td>-0.329930</td>\n",
       "      <td>-0.263777</td>\n",
       "      <td>-0.054286</td>\n",
       "      <td>-0.186064</td>\n",
       "      <td>0.071269</td>\n",
       "      <td>-0.317315</td>\n",
       "      <td>-0.615912</td>\n",
       "      <td>0.751462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Education</th>\n",
       "      <td>0.157005</td>\n",
       "      <td>-0.404477</td>\n",
       "      <td>-0.496831</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.300018</td>\n",
       "      <td>0.427860</td>\n",
       "      <td>0.272360</td>\n",
       "      <td>0.057403</td>\n",
       "      <td>-0.001403</td>\n",
       "      <td>-0.026598</td>\n",
       "      <td>...</td>\n",
       "      <td>0.318456</td>\n",
       "      <td>0.427725</td>\n",
       "      <td>0.173557</td>\n",
       "      <td>-0.056985</td>\n",
       "      <td>-0.000550</td>\n",
       "      <td>0.009220</td>\n",
       "      <td>-0.171931</td>\n",
       "      <td>0.233205</td>\n",
       "      <td>0.485811</td>\n",
       "      <td>-0.623747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ExpenditureYear0</th>\n",
       "      <td>0.646211</td>\n",
       "      <td>-0.505737</td>\n",
       "      <td>-0.372636</td>\n",
       "      <td>0.300018</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.121493</td>\n",
       "      <td>0.033760</td>\n",
       "      <td>0.036784</td>\n",
       "      <td>0.526284</td>\n",
       "      <td>-0.043698</td>\n",
       "      <td>...</td>\n",
       "      <td>0.993586</td>\n",
       "      <td>0.047956</td>\n",
       "      <td>-0.003897</td>\n",
       "      <td>-0.012378</td>\n",
       "      <td>0.531186</td>\n",
       "      <td>-0.038003</td>\n",
       "      <td>0.135443</td>\n",
       "      <td>-0.157784</td>\n",
       "      <td>0.787296</td>\n",
       "      <td>-0.538800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LabourForce</th>\n",
       "      <td>0.169309</td>\n",
       "      <td>-0.160949</td>\n",
       "      <td>-0.505469</td>\n",
       "      <td>0.427860</td>\n",
       "      <td>0.121493</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.513559</td>\n",
       "      <td>0.366911</td>\n",
       "      <td>-0.123672</td>\n",
       "      <td>-0.229400</td>\n",
       "      <td>...</td>\n",
       "      <td>0.106350</td>\n",
       "      <td>0.974818</td>\n",
       "      <td>0.474179</td>\n",
       "      <td>0.286188</td>\n",
       "      <td>-0.125571</td>\n",
       "      <td>-0.200756</td>\n",
       "      <td>-0.347803</td>\n",
       "      <td>0.198845</td>\n",
       "      <td>0.272300</td>\n",
       "      <td>-0.254833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Males</th>\n",
       "      <td>0.157113</td>\n",
       "      <td>-0.028680</td>\n",
       "      <td>-0.314733</td>\n",
       "      <td>0.272360</td>\n",
       "      <td>0.033760</td>\n",
       "      <td>0.513559</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.836195</td>\n",
       "      <td>-0.410628</td>\n",
       "      <td>0.351892</td>\n",
       "      <td>...</td>\n",
       "      <td>0.022843</td>\n",
       "      <td>0.535478</td>\n",
       "      <td>0.882966</td>\n",
       "      <td>0.745046</td>\n",
       "      <td>-0.408964</td>\n",
       "      <td>0.373205</td>\n",
       "      <td>0.035302</td>\n",
       "      <td>0.247763</td>\n",
       "      <td>0.177925</td>\n",
       "      <td>-0.161323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MoreMales</th>\n",
       "      <td>0.141546</td>\n",
       "      <td>-0.048581</td>\n",
       "      <td>-0.349630</td>\n",
       "      <td>0.057403</td>\n",
       "      <td>0.036784</td>\n",
       "      <td>0.366911</td>\n",
       "      <td>0.836195</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.351102</td>\n",
       "      <td>0.429861</td>\n",
       "      <td>...</td>\n",
       "      <td>0.040843</td>\n",
       "      <td>0.385071</td>\n",
       "      <td>0.796917</td>\n",
       "      <td>0.936117</td>\n",
       "      <td>-0.346462</td>\n",
       "      <td>0.431853</td>\n",
       "      <td>0.082788</td>\n",
       "      <td>0.260228</td>\n",
       "      <td>0.106842</td>\n",
       "      <td>-0.105233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StateSize</th>\n",
       "      <td>0.307945</td>\n",
       "      <td>-0.280638</td>\n",
       "      <td>-0.049918</td>\n",
       "      <td>-0.001403</td>\n",
       "      <td>0.526284</td>\n",
       "      <td>-0.123672</td>\n",
       "      <td>-0.410628</td>\n",
       "      <td>-0.351102</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.038120</td>\n",
       "      <td>...</td>\n",
       "      <td>0.513789</td>\n",
       "      <td>-0.175913</td>\n",
       "      <td>-0.378248</td>\n",
       "      <td>-0.342549</td>\n",
       "      <td>0.999371</td>\n",
       "      <td>-0.020832</td>\n",
       "      <td>0.201788</td>\n",
       "      <td>-0.143571</td>\n",
       "      <td>0.308716</td>\n",
       "      <td>-0.060654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YouthUnemployment</th>\n",
       "      <td>-0.050613</td>\n",
       "      <td>-0.224381</td>\n",
       "      <td>-0.172419</td>\n",
       "      <td>-0.026598</td>\n",
       "      <td>-0.043698</td>\n",
       "      <td>-0.229400</td>\n",
       "      <td>0.351892</td>\n",
       "      <td>0.429861</td>\n",
       "      <td>-0.038120</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.051712</td>\n",
       "      <td>-0.237177</td>\n",
       "      <td>0.321949</td>\n",
       "      <td>0.449803</td>\n",
       "      <td>-0.040807</td>\n",
       "      <td>0.991235</td>\n",
       "      <td>0.726123</td>\n",
       "      <td>0.061028</td>\n",
       "      <td>0.012540</td>\n",
       "      <td>-0.087397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MatureUnemployment</th>\n",
       "      <td>0.171835</td>\n",
       "      <td>-0.244843</td>\n",
       "      <td>0.071693</td>\n",
       "      <td>-0.222656</td>\n",
       "      <td>0.185093</td>\n",
       "      <td>-0.420762</td>\n",
       "      <td>-0.018692</td>\n",
       "      <td>0.059487</td>\n",
       "      <td>0.270422</td>\n",
       "      <td>0.745925</td>\n",
       "      <td>...</td>\n",
       "      <td>0.169224</td>\n",
       "      <td>-0.438669</td>\n",
       "      <td>-0.024591</td>\n",
       "      <td>0.100880</td>\n",
       "      <td>0.262662</td>\n",
       "      <td>0.718910</td>\n",
       "      <td>0.972611</td>\n",
       "      <td>-0.402651</td>\n",
       "      <td>0.069840</td>\n",
       "      <td>0.000661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HighYouthUnemploy</th>\n",
       "      <td>-0.286033</td>\n",
       "      <td>-0.083029</td>\n",
       "      <td>-0.395545</td>\n",
       "      <td>0.310001</td>\n",
       "      <td>-0.239076</td>\n",
       "      <td>0.413431</td>\n",
       "      <td>0.386228</td>\n",
       "      <td>0.362814</td>\n",
       "      <td>-0.365080</td>\n",
       "      <td>0.076718</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.236797</td>\n",
       "      <td>0.422848</td>\n",
       "      <td>0.390969</td>\n",
       "      <td>0.313222</td>\n",
       "      <td>-0.362794</td>\n",
       "      <td>0.099026</td>\n",
       "      <td>-0.468400</td>\n",
       "      <td>0.738129</td>\n",
       "      <td>0.005131</td>\n",
       "      <td>-0.167093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wage</th>\n",
       "      <td>0.424853</td>\n",
       "      <td>-0.670055</td>\n",
       "      <td>-0.636945</td>\n",
       "      <td>0.519187</td>\n",
       "      <td>0.787225</td>\n",
       "      <td>0.294632</td>\n",
       "      <td>0.179609</td>\n",
       "      <td>0.109640</td>\n",
       "      <td>0.308263</td>\n",
       "      <td>0.044857</td>\n",
       "      <td>...</td>\n",
       "      <td>0.794262</td>\n",
       "      <td>0.201533</td>\n",
       "      <td>0.125145</td>\n",
       "      <td>0.033858</td>\n",
       "      <td>0.308606</td>\n",
       "      <td>0.064470</td>\n",
       "      <td>0.080366</td>\n",
       "      <td>-0.021018</td>\n",
       "      <td>0.984164</td>\n",
       "      <td>-0.824248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BelowWage</th>\n",
       "      <td>-0.167318</td>\n",
       "      <td>0.639211</td>\n",
       "      <td>0.737181</td>\n",
       "      <td>-0.588214</td>\n",
       "      <td>-0.630500</td>\n",
       "      <td>-0.269886</td>\n",
       "      <td>-0.167089</td>\n",
       "      <td>-0.120562</td>\n",
       "      <td>-0.126294</td>\n",
       "      <td>-0.063832</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.648152</td>\n",
       "      <td>-0.206434</td>\n",
       "      <td>-0.083873</td>\n",
       "      <td>-0.027660</td>\n",
       "      <td>-0.131550</td>\n",
       "      <td>-0.087033</td>\n",
       "      <td>0.026680</td>\n",
       "      <td>-0.108748</td>\n",
       "      <td>-0.870723</td>\n",
       "      <td>0.962544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CrimeRate10</th>\n",
       "      <td>0.996596</td>\n",
       "      <td>-0.044827</td>\n",
       "      <td>-0.028568</td>\n",
       "      <td>0.142139</td>\n",
       "      <td>0.643465</td>\n",
       "      <td>0.141884</td>\n",
       "      <td>0.148907</td>\n",
       "      <td>0.141896</td>\n",
       "      <td>0.323885</td>\n",
       "      <td>-0.046139</td>\n",
       "      <td>...</td>\n",
       "      <td>0.630609</td>\n",
       "      <td>0.109649</td>\n",
       "      <td>0.146830</td>\n",
       "      <td>0.128568</td>\n",
       "      <td>0.320024</td>\n",
       "      <td>-0.032754</td>\n",
       "      <td>0.165383</td>\n",
       "      <td>-0.289350</td>\n",
       "      <td>0.436787</td>\n",
       "      <td>-0.065965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Youth10</th>\n",
       "      <td>-0.015760</td>\n",
       "      <td>0.790785</td>\n",
       "      <td>0.471938</td>\n",
       "      <td>-0.360348</td>\n",
       "      <td>-0.452323</td>\n",
       "      <td>-0.130551</td>\n",
       "      <td>-0.047824</td>\n",
       "      <td>-0.069045</td>\n",
       "      <td>-0.180831</td>\n",
       "      <td>-0.080064</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.463578</td>\n",
       "      <td>-0.056523</td>\n",
       "      <td>0.102920</td>\n",
       "      <td>0.032166</td>\n",
       "      <td>-0.189973</td>\n",
       "      <td>-0.057507</td>\n",
       "      <td>0.020821</td>\n",
       "      <td>-0.165053</td>\n",
       "      <td>-0.552219</td>\n",
       "      <td>0.517785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Education10</th>\n",
       "      <td>0.142153</td>\n",
       "      <td>-0.397194</td>\n",
       "      <td>-0.489556</td>\n",
       "      <td>0.995153</td>\n",
       "      <td>0.278156</td>\n",
       "      <td>0.431150</td>\n",
       "      <td>0.262139</td>\n",
       "      <td>0.041105</td>\n",
       "      <td>-0.009439</td>\n",
       "      <td>-0.040403</td>\n",
       "      <td>...</td>\n",
       "      <td>0.297020</td>\n",
       "      <td>0.430526</td>\n",
       "      <td>0.172449</td>\n",
       "      <td>-0.063764</td>\n",
       "      <td>-0.008963</td>\n",
       "      <td>-0.003167</td>\n",
       "      <td>-0.187126</td>\n",
       "      <td>0.237943</td>\n",
       "      <td>0.474663</td>\n",
       "      <td>-0.616755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ExpenditureYear10</th>\n",
       "      <td>0.629700</td>\n",
       "      <td>-0.513173</td>\n",
       "      <td>-0.376168</td>\n",
       "      <td>0.318456</td>\n",
       "      <td>0.993586</td>\n",
       "      <td>0.106350</td>\n",
       "      <td>0.022843</td>\n",
       "      <td>0.040843</td>\n",
       "      <td>0.513789</td>\n",
       "      <td>-0.051712</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.033316</td>\n",
       "      <td>-0.013535</td>\n",
       "      <td>-0.006278</td>\n",
       "      <td>0.518868</td>\n",
       "      <td>-0.042348</td>\n",
       "      <td>0.123816</td>\n",
       "      <td>-0.148028</td>\n",
       "      <td>0.791696</td>\n",
       "      <td>-0.552640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LabourForce10</th>\n",
       "      <td>0.138849</td>\n",
       "      <td>-0.073214</td>\n",
       "      <td>-0.478050</td>\n",
       "      <td>0.427725</td>\n",
       "      <td>0.047956</td>\n",
       "      <td>0.974818</td>\n",
       "      <td>0.535478</td>\n",
       "      <td>0.385071</td>\n",
       "      <td>-0.175913</td>\n",
       "      <td>-0.237177</td>\n",
       "      <td>...</td>\n",
       "      <td>0.033316</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.491284</td>\n",
       "      <td>0.299676</td>\n",
       "      <td>-0.177005</td>\n",
       "      <td>-0.208783</td>\n",
       "      <td>-0.365044</td>\n",
       "      <td>0.230375</td>\n",
       "      <td>0.186369</td>\n",
       "      <td>-0.203341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Males10</th>\n",
       "      <td>0.163331</td>\n",
       "      <td>0.059896</td>\n",
       "      <td>-0.329930</td>\n",
       "      <td>0.173557</td>\n",
       "      <td>-0.003897</td>\n",
       "      <td>0.474179</td>\n",
       "      <td>0.882966</td>\n",
       "      <td>0.796917</td>\n",
       "      <td>-0.378248</td>\n",
       "      <td>0.321949</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.013535</td>\n",
       "      <td>0.491284</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.791045</td>\n",
       "      <td>-0.378937</td>\n",
       "      <td>0.340885</td>\n",
       "      <td>0.019319</td>\n",
       "      <td>0.242904</td>\n",
       "      <td>0.129189</td>\n",
       "      <td>-0.096061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MoreMales10</th>\n",
       "      <td>0.125157</td>\n",
       "      <td>0.005249</td>\n",
       "      <td>-0.263777</td>\n",
       "      <td>-0.056985</td>\n",
       "      <td>-0.012378</td>\n",
       "      <td>0.286188</td>\n",
       "      <td>0.745046</td>\n",
       "      <td>0.936117</td>\n",
       "      <td>-0.342549</td>\n",
       "      <td>0.449803</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.006278</td>\n",
       "      <td>0.299676</td>\n",
       "      <td>0.791045</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.340683</td>\n",
       "      <td>0.452161</td>\n",
       "      <td>0.121051</td>\n",
       "      <td>0.207363</td>\n",
       "      <td>0.030054</td>\n",
       "      <td>-0.018406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StateSize10</th>\n",
       "      <td>0.303974</td>\n",
       "      <td>-0.282565</td>\n",
       "      <td>-0.054286</td>\n",
       "      <td>-0.000550</td>\n",
       "      <td>0.531186</td>\n",
       "      <td>-0.125571</td>\n",
       "      <td>-0.408964</td>\n",
       "      <td>-0.346462</td>\n",
       "      <td>0.999371</td>\n",
       "      <td>-0.040807</td>\n",
       "      <td>...</td>\n",
       "      <td>0.518868</td>\n",
       "      <td>-0.177005</td>\n",
       "      <td>-0.378937</td>\n",
       "      <td>-0.340683</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.024025</td>\n",
       "      <td>0.190580</td>\n",
       "      <td>-0.133546</td>\n",
       "      <td>0.308625</td>\n",
       "      <td>-0.066213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YouthUnemploy10</th>\n",
       "      <td>-0.038185</td>\n",
       "      <td>-0.201452</td>\n",
       "      <td>-0.186064</td>\n",
       "      <td>0.009220</td>\n",
       "      <td>-0.038003</td>\n",
       "      <td>-0.200756</td>\n",
       "      <td>0.373205</td>\n",
       "      <td>0.431853</td>\n",
       "      <td>-0.020832</td>\n",
       "      <td>0.991235</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.042348</td>\n",
       "      <td>-0.208783</td>\n",
       "      <td>0.340885</td>\n",
       "      <td>0.452161</td>\n",
       "      <td>-0.024025</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.706937</td>\n",
       "      <td>0.079848</td>\n",
       "      <td>0.035044</td>\n",
       "      <td>-0.101227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MatureUnemploy10</th>\n",
       "      <td>0.165357</td>\n",
       "      <td>-0.244174</td>\n",
       "      <td>0.071269</td>\n",
       "      <td>-0.171931</td>\n",
       "      <td>0.135443</td>\n",
       "      <td>-0.347803</td>\n",
       "      <td>0.035302</td>\n",
       "      <td>0.082788</td>\n",
       "      <td>0.201788</td>\n",
       "      <td>0.726123</td>\n",
       "      <td>...</td>\n",
       "      <td>0.123816</td>\n",
       "      <td>-0.365044</td>\n",
       "      <td>0.019319</td>\n",
       "      <td>0.121051</td>\n",
       "      <td>0.190580</td>\n",
       "      <td>0.706937</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.431622</td>\n",
       "      <td>0.055754</td>\n",
       "      <td>0.006781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HighYouthUnemploy10</th>\n",
       "      <td>-0.281453</td>\n",
       "      <td>-0.097341</td>\n",
       "      <td>-0.317315</td>\n",
       "      <td>0.233205</td>\n",
       "      <td>-0.157784</td>\n",
       "      <td>0.198845</td>\n",
       "      <td>0.247763</td>\n",
       "      <td>0.260228</td>\n",
       "      <td>-0.143571</td>\n",
       "      <td>0.061028</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.148028</td>\n",
       "      <td>0.230375</td>\n",
       "      <td>0.242904</td>\n",
       "      <td>0.207363</td>\n",
       "      <td>-0.133546</td>\n",
       "      <td>0.079848</td>\n",
       "      <td>-0.431622</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000408</td>\n",
       "      <td>-0.149478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wage10</th>\n",
       "      <td>0.436740</td>\n",
       "      <td>-0.615583</td>\n",
       "      <td>-0.615912</td>\n",
       "      <td>0.485811</td>\n",
       "      <td>0.787296</td>\n",
       "      <td>0.272300</td>\n",
       "      <td>0.177925</td>\n",
       "      <td>0.106842</td>\n",
       "      <td>0.308716</td>\n",
       "      <td>0.012540</td>\n",
       "      <td>...</td>\n",
       "      <td>0.791696</td>\n",
       "      <td>0.186369</td>\n",
       "      <td>0.129189</td>\n",
       "      <td>0.030054</td>\n",
       "      <td>0.308625</td>\n",
       "      <td>0.035044</td>\n",
       "      <td>0.055754</td>\n",
       "      <td>0.000408</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.800181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BelowWage10</th>\n",
       "      <td>-0.076246</td>\n",
       "      <td>0.633203</td>\n",
       "      <td>0.751462</td>\n",
       "      <td>-0.623747</td>\n",
       "      <td>-0.538800</td>\n",
       "      <td>-0.254833</td>\n",
       "      <td>-0.161323</td>\n",
       "      <td>-0.105233</td>\n",
       "      <td>-0.060654</td>\n",
       "      <td>-0.087397</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.552640</td>\n",
       "      <td>-0.203341</td>\n",
       "      <td>-0.096061</td>\n",
       "      <td>-0.018406</td>\n",
       "      <td>-0.066213</td>\n",
       "      <td>-0.101227</td>\n",
       "      <td>0.006781</td>\n",
       "      <td>-0.149478</td>\n",
       "      <td>-0.800181</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>27 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     CrimeRate     Youth  Southern  Education  \\\n",
       "CrimeRate             1.000000 -0.055002 -0.053465   0.157005   \n",
       "Youth                -0.055002  1.000000  0.584355  -0.404477   \n",
       "Southern             -0.053465  0.584355  1.000000  -0.496831   \n",
       "Education             0.157005 -0.404477 -0.496831   1.000000   \n",
       "ExpenditureYear0      0.646211 -0.505737 -0.372636   0.300018   \n",
       "LabourForce           0.169309 -0.160949 -0.505469   0.427860   \n",
       "Males                 0.157113 -0.028680 -0.314733   0.272360   \n",
       "MoreMales             0.141546 -0.048581 -0.349630   0.057403   \n",
       "StateSize             0.307945 -0.280638 -0.049918  -0.001403   \n",
       "YouthUnemployment    -0.050613 -0.224381 -0.172419  -0.026598   \n",
       "MatureUnemployment    0.171835 -0.244843  0.071693  -0.222656   \n",
       "HighYouthUnemploy    -0.286033 -0.083029 -0.395545   0.310001   \n",
       "Wage                  0.424853 -0.670055 -0.636945   0.519187   \n",
       "BelowWage            -0.167318  0.639211  0.737181  -0.588214   \n",
       "CrimeRate10           0.996596 -0.044827 -0.028568   0.142139   \n",
       "Youth10              -0.015760  0.790785  0.471938  -0.360348   \n",
       "Education10           0.142153 -0.397194 -0.489556   0.995153   \n",
       "ExpenditureYear10     0.629700 -0.513173 -0.376168   0.318456   \n",
       "LabourForce10         0.138849 -0.073214 -0.478050   0.427725   \n",
       "Males10               0.163331  0.059896 -0.329930   0.173557   \n",
       "MoreMales10           0.125157  0.005249 -0.263777  -0.056985   \n",
       "StateSize10           0.303974 -0.282565 -0.054286  -0.000550   \n",
       "YouthUnemploy10      -0.038185 -0.201452 -0.186064   0.009220   \n",
       "MatureUnemploy10      0.165357 -0.244174  0.071269  -0.171931   \n",
       "HighYouthUnemploy10  -0.281453 -0.097341 -0.317315   0.233205   \n",
       "Wage10                0.436740 -0.615583 -0.615912   0.485811   \n",
       "BelowWage10          -0.076246  0.633203  0.751462  -0.623747   \n",
       "\n",
       "                     ExpenditureYear0  LabourForce     Males  MoreMales  \\\n",
       "CrimeRate                    0.646211     0.169309  0.157113   0.141546   \n",
       "Youth                       -0.505737    -0.160949 -0.028680  -0.048581   \n",
       "Southern                    -0.372636    -0.505469 -0.314733  -0.349630   \n",
       "Education                    0.300018     0.427860  0.272360   0.057403   \n",
       "ExpenditureYear0             1.000000     0.121493  0.033760   0.036784   \n",
       "LabourForce                  0.121493     1.000000  0.513559   0.366911   \n",
       "Males                        0.033760     0.513559  1.000000   0.836195   \n",
       "MoreMales                    0.036784     0.366911  0.836195   1.000000   \n",
       "StateSize                    0.526284    -0.123672 -0.410628  -0.351102   \n",
       "YouthUnemployment           -0.043698    -0.229400  0.351892   0.429861   \n",
       "MatureUnemployment           0.185093    -0.420762 -0.018692   0.059487   \n",
       "HighYouthUnemploy           -0.239076     0.413431  0.386228   0.362814   \n",
       "Wage                         0.787225     0.294632  0.179609   0.109640   \n",
       "BelowWage                   -0.630500    -0.269886 -0.167089  -0.120562   \n",
       "CrimeRate10                  0.643465     0.141884  0.148907   0.141896   \n",
       "Youth10                     -0.452323    -0.130551 -0.047824  -0.069045   \n",
       "Education10                  0.278156     0.431150  0.262139   0.041105   \n",
       "ExpenditureYear10            0.993586     0.106350  0.022843   0.040843   \n",
       "LabourForce10                0.047956     0.974818  0.535478   0.385071   \n",
       "Males10                     -0.003897     0.474179  0.882966   0.796917   \n",
       "MoreMales10                 -0.012378     0.286188  0.745046   0.936117   \n",
       "StateSize10                  0.531186    -0.125571 -0.408964  -0.346462   \n",
       "YouthUnemploy10             -0.038003    -0.200756  0.373205   0.431853   \n",
       "MatureUnemploy10             0.135443    -0.347803  0.035302   0.082788   \n",
       "HighYouthUnemploy10         -0.157784     0.198845  0.247763   0.260228   \n",
       "Wage10                       0.787296     0.272300  0.177925   0.106842   \n",
       "BelowWage10                 -0.538800    -0.254833 -0.161323  -0.105233   \n",
       "\n",
       "                     StateSize  YouthUnemployment  ...  ExpenditureYear10  \\\n",
       "CrimeRate             0.307945          -0.050613  ...           0.629700   \n",
       "Youth                -0.280638          -0.224381  ...          -0.513173   \n",
       "Southern             -0.049918          -0.172419  ...          -0.376168   \n",
       "Education            -0.001403          -0.026598  ...           0.318456   \n",
       "ExpenditureYear0      0.526284          -0.043698  ...           0.993586   \n",
       "LabourForce          -0.123672          -0.229400  ...           0.106350   \n",
       "Males                -0.410628           0.351892  ...           0.022843   \n",
       "MoreMales            -0.351102           0.429861  ...           0.040843   \n",
       "StateSize             1.000000          -0.038120  ...           0.513789   \n",
       "YouthUnemployment    -0.038120           1.000000  ...          -0.051712   \n",
       "MatureUnemployment    0.270422           0.745925  ...           0.169224   \n",
       "HighYouthUnemploy    -0.365080           0.076718  ...          -0.236797   \n",
       "Wage                  0.308263           0.044857  ...           0.794262   \n",
       "BelowWage            -0.126294          -0.063832  ...          -0.648152   \n",
       "CrimeRate10           0.323885          -0.046139  ...           0.630609   \n",
       "Youth10              -0.180831          -0.080064  ...          -0.463578   \n",
       "Education10          -0.009439          -0.040403  ...           0.297020   \n",
       "ExpenditureYear10     0.513789          -0.051712  ...           1.000000   \n",
       "LabourForce10        -0.175913          -0.237177  ...           0.033316   \n",
       "Males10              -0.378248           0.321949  ...          -0.013535   \n",
       "MoreMales10          -0.342549           0.449803  ...          -0.006278   \n",
       "StateSize10           0.999371          -0.040807  ...           0.518868   \n",
       "YouthUnemploy10      -0.020832           0.991235  ...          -0.042348   \n",
       "MatureUnemploy10      0.201788           0.726123  ...           0.123816   \n",
       "HighYouthUnemploy10  -0.143571           0.061028  ...          -0.148028   \n",
       "Wage10                0.308716           0.012540  ...           0.791696   \n",
       "BelowWage10          -0.060654          -0.087397  ...          -0.552640   \n",
       "\n",
       "                     LabourForce10   Males10  MoreMales10  StateSize10  \\\n",
       "CrimeRate                 0.138849  0.163331     0.125157     0.303974   \n",
       "Youth                    -0.073214  0.059896     0.005249    -0.282565   \n",
       "Southern                 -0.478050 -0.329930    -0.263777    -0.054286   \n",
       "Education                 0.427725  0.173557    -0.056985    -0.000550   \n",
       "ExpenditureYear0          0.047956 -0.003897    -0.012378     0.531186   \n",
       "LabourForce               0.974818  0.474179     0.286188    -0.125571   \n",
       "Males                     0.535478  0.882966     0.745046    -0.408964   \n",
       "MoreMales                 0.385071  0.796917     0.936117    -0.346462   \n",
       "StateSize                -0.175913 -0.378248    -0.342549     0.999371   \n",
       "YouthUnemployment        -0.237177  0.321949     0.449803    -0.040807   \n",
       "MatureUnemployment       -0.438669 -0.024591     0.100880     0.262662   \n",
       "HighYouthUnemploy         0.422848  0.390969     0.313222    -0.362794   \n",
       "Wage                      0.201533  0.125145     0.033858     0.308606   \n",
       "BelowWage                -0.206434 -0.083873    -0.027660    -0.131550   \n",
       "CrimeRate10               0.109649  0.146830     0.128568     0.320024   \n",
       "Youth10                  -0.056523  0.102920     0.032166    -0.189973   \n",
       "Education10               0.430526  0.172449    -0.063764    -0.008963   \n",
       "ExpenditureYear10         0.033316 -0.013535    -0.006278     0.518868   \n",
       "LabourForce10             1.000000  0.491284     0.299676    -0.177005   \n",
       "Males10                   0.491284  1.000000     0.791045    -0.378937   \n",
       "MoreMales10               0.299676  0.791045     1.000000    -0.340683   \n",
       "StateSize10              -0.177005 -0.378937    -0.340683     1.000000   \n",
       "YouthUnemploy10          -0.208783  0.340885     0.452161    -0.024025   \n",
       "MatureUnemploy10         -0.365044  0.019319     0.121051     0.190580   \n",
       "HighYouthUnemploy10       0.230375  0.242904     0.207363    -0.133546   \n",
       "Wage10                    0.186369  0.129189     0.030054     0.308625   \n",
       "BelowWage10              -0.203341 -0.096061    -0.018406    -0.066213   \n",
       "\n",
       "                     YouthUnemploy10  MatureUnemploy10  HighYouthUnemploy10  \\\n",
       "CrimeRate                  -0.038185          0.165357            -0.281453   \n",
       "Youth                      -0.201452         -0.244174            -0.097341   \n",
       "Southern                   -0.186064          0.071269            -0.317315   \n",
       "Education                   0.009220         -0.171931             0.233205   \n",
       "ExpenditureYear0           -0.038003          0.135443            -0.157784   \n",
       "LabourForce                -0.200756         -0.347803             0.198845   \n",
       "Males                       0.373205          0.035302             0.247763   \n",
       "MoreMales                   0.431853          0.082788             0.260228   \n",
       "StateSize                  -0.020832          0.201788            -0.143571   \n",
       "YouthUnemployment           0.991235          0.726123             0.061028   \n",
       "MatureUnemployment          0.718910          0.972611            -0.402651   \n",
       "HighYouthUnemploy           0.099026         -0.468400             0.738129   \n",
       "Wage                        0.064470          0.080366            -0.021018   \n",
       "BelowWage                  -0.087033          0.026680            -0.108748   \n",
       "CrimeRate10                -0.032754          0.165383            -0.289350   \n",
       "Youth10                    -0.057507          0.020821            -0.165053   \n",
       "Education10                -0.003167         -0.187126             0.237943   \n",
       "ExpenditureYear10          -0.042348          0.123816            -0.148028   \n",
       "LabourForce10              -0.208783         -0.365044             0.230375   \n",
       "Males10                     0.340885          0.019319             0.242904   \n",
       "MoreMales10                 0.452161          0.121051             0.207363   \n",
       "StateSize10                -0.024025          0.190580            -0.133546   \n",
       "YouthUnemploy10             1.000000          0.706937             0.079848   \n",
       "MatureUnemploy10            0.706937          1.000000            -0.431622   \n",
       "HighYouthUnemploy10         0.079848         -0.431622             1.000000   \n",
       "Wage10                      0.035044          0.055754             0.000408   \n",
       "BelowWage10                -0.101227          0.006781            -0.149478   \n",
       "\n",
       "                       Wage10  BelowWage10  \n",
       "CrimeRate            0.436740    -0.076246  \n",
       "Youth               -0.615583     0.633203  \n",
       "Southern            -0.615912     0.751462  \n",
       "Education            0.485811    -0.623747  \n",
       "ExpenditureYear0     0.787296    -0.538800  \n",
       "LabourForce          0.272300    -0.254833  \n",
       "Males                0.177925    -0.161323  \n",
       "MoreMales            0.106842    -0.105233  \n",
       "StateSize            0.308716    -0.060654  \n",
       "YouthUnemployment    0.012540    -0.087397  \n",
       "MatureUnemployment   0.069840     0.000661  \n",
       "HighYouthUnemploy    0.005131    -0.167093  \n",
       "Wage                 0.984164    -0.824248  \n",
       "BelowWage           -0.870723     0.962544  \n",
       "CrimeRate10          0.436787    -0.065965  \n",
       "Youth10             -0.552219     0.517785  \n",
       "Education10          0.474663    -0.616755  \n",
       "ExpenditureYear10    0.791696    -0.552640  \n",
       "LabourForce10        0.186369    -0.203341  \n",
       "Males10              0.129189    -0.096061  \n",
       "MoreMales10          0.030054    -0.018406  \n",
       "StateSize10          0.308625    -0.066213  \n",
       "YouthUnemploy10      0.035044    -0.101227  \n",
       "MatureUnemploy10     0.055754     0.006781  \n",
       "HighYouthUnemploy10  0.000408    -0.149478  \n",
       "Wage10               1.000000    -0.800181  \n",
       "BelowWage10         -0.800181     1.000000  \n",
       "\n",
       "[27 rows x 27 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "crime.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(crime.corr(), annot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.4248530127607083, 0.0029142013171254526)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Pearson's R Correlation Coefficient\n",
    "\n",
    "#Strength-Magnitude - given by coefficient\n",
    "#Direction - given by coefficient\n",
    "#Significance -  ( p < 0.05 )\n",
    "\n",
    "# Pearson R can be interpreted as percentage\n",
    "\n",
    "# 0-40 = weak\n",
    "# 40-70 = moderate\n",
    "# 70-100 = strong\n",
    "\n",
    "\n",
    "stats.pearsonr(crime['Wage'], crime['CrimeRate'])\n",
    "\n",
    "# Moderately weak, positive, statistically significant correlation between wages and crime rates\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x20e38066490>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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WwZqVXR7mTPxdrOXTcqKXdBvwG8BYRNwL9AD7gceAFyJiN/BCcr9QPBFl3ZKHOZM8vNlYttKWbnqBTZKuAZuBN4DHgfuTx58CXgQ+m/J1OmZ5ImpooJeRLf3Mzi9w5OSUJyitY7o9Z9Lp+rG1X8uJPiJ+LOk/Aa8DV4BvRsQ3Je2IiMnknElJt9Z7vqSDwEGAD37wg62GkTlPRJl1/83GstVyok9q7/uAO4AZ4E8kfabR50fEIeAQwNjYWLQaR9Y8EZUdL/wxy4c0k7G/AJyJiOmIuAb8KfD3gClJOwGS3+fTh9k5nojKhnuxzfIjTaJ/HdgrabMkAQ8APwCeBw4k5xwAvp4uxM7yRFQ28rDwx8yWpKnRH5X0NeA7wALwXZZKMVuA5yQ9wtKbwa9kEWineCIqGy6BmeVHqq6biPg88PkVh+dZGt0Xliei0svDwh8zW+KVsdYWe0aHOXJyClgayc/OL3BpboG9d27rcmSN82SylYU3NbO2yMPCnzQ8mWxl4hG9tU2RS2BeT2Fl4kRvVseZ6VnenrvK5flFhgZ62bVtC8Ob+zyZbIXk0o3ZCpMzVzh78R3enlvgpoE+5heu88q5GX781hVPJlshOdGbrXBsYoa7dmwhQsxdu85Abw9ScGrqba+nsEJy6cZshYuzVxm9ZTNb+nt57cI7vD13jaH+Pm7a1Ov6vBWSE73ZCgK+/aMLLFwPhgZ6+enbhunrEZs29nQ7NLOWuHRjVmNy5goXLs3z9twCfRs2MHdtkb/+mzeZmLniso0VlhO9WY1jEzOMbt3M37ljKwN9PVxbDG7e1MvIYJ/LNlZYLt2Y1Vjeo2eDxNbBpb16rke4rdIKzSN6sxreptrKyCN6sxpZ7NHjPXIsbzyiN6uRdo8e75FjeeQRvdkKafbo8R45lkce0Ztl6OLsVQb7bxw/Dfb3cnH2apciMnOiN8uUJ3Mtj5zozTLk7xy2PHKN3ixD/s7hJe48yhcnerOMFfkLV7Kw3Hk0NNDLyJZ+ZucXOHJyqlDfMFY2Lt2YWaZqO482SAwN9DE00MuxiZluh1ZZTvRmlil3HuWPE72ZZcqdR/njRG9mmXLnUf440ZtZptJuI2HZS9V1I2kY+DJwLxDArwGngD8GdgGvAb8aEW+leR2zetzCl19V7zzKm7Qj+v8GHI6Ivw3sAX4APAa8EBG7gReS+2aZ8uZhZo1rOdFLugn4OPAVgIi4GhEzwD7gqeS0p4BfThei2fu5hc+scWlG9HcC08DvS/qupC9LGgR2RMQkQPL71npPlnRQ0rik8enp6RRhWBW5hc+scWkSfS/wMeBLEfEzwCxNlGki4lBEjEXE2Pbt21OEYVXkFj6zxqVJ9BPAREQcTe5/jaXEPyVpJ0Dy+3y6EM3ezy18Zo1ruesmIn4i6ZykuyPiFPAAcDL5OQB8Ifn99UwircNdF9XlzcPMGpd2U7NfB/5I0kbgb4B/ytKnhOckPQK8DvxKyteoyxsnmVv4zBqTKtFHxCvAWJ2HHkjzdxvhr2wzM2tMYVfGuuvCzKwxhU307rowM2tMYRO9uy7MzBpT2ETvjZPMzBpT6K8SdNdF9bil1qx5hR3RW/V4IzOz1jjRW2F4IzOz1jjRW2G4pdasNU70VhhuqTVrjRO9FYZbas1a40RvheGWWrPWFLq90qrHLbVmzfOI3sys5JzozcxKzonezKzknOjNzErOk7FmFea9g6rBI3qzivLeQdXhRG9WUd47qDqc6M0qynsHVYcTvVlFee+g6nCiN6so7x1UHU70ZhXlvYOqw+2VZhXmvYOqwSN6M7OSS53oJfVI+q6kv0jub5V0RNKrye9b0odpZmatymJE/y+BH9Tcfwx4ISJ2Ay8k983MrEtSJXpJo8A/Ar5cc3gf8FRy+yngl9O8hpmZpZN2RP+7wG8B12uO7YiISYDk9631nijpoKRxSePT09MpwzAzs9W03HUj6VPA+Yh4WdL9zT4/Ig4Bh5K/NS3pbKuxNGgEuNDm12iF42pOHuPKY0zguJpVxLj+ViN/IE175c8Bn5b0S8AAcJOkPwSmJO2MiElJO4Hz6/2hiNieIo6GSBqPiLF2v06zHFdz8hhXHmMCx9WsMsfVcukmIh6PiNGI2AXsB/5PRHwGeB44kJx2APh6mgDNzCyddvTRfwF4UNKrwIPJfTMz65JMVsZGxIvAi8ntN4EHsvi7GTvU7QBW4biak8e48hgTOK5mlTYuRUQWgZiZWU55CwQzs5JzojczK7lSJHpJA5JeknRM0glJ/z45vuq+O5Iel3Ra0ilJn+hwXL8t6ceSXkl+fqmTcSWv0/AeRZ2KaZW4un6tktd6TdL3kxjGk2Ndv2arxNX1ayZpWNLXJP1Q0g8k/d1uX69VYsrDtbq75vVfkfS2pH+V6fWKiML/AAK2JLf7gKPAXuB3gMeS448B/yG5fQ9wDOgH7gB+BPR0MK7fBn6zzvkdiSt5rX8DPA38RXK/q9dqjbi6fq2S13sNGFlxrOvXbJW4un7NWNr+5J8ltzcCw92+XqvE1PVrteJ1e4CfsLQQKrPrVYoRfSy5nNztS36C1ffd2Qc8GxHzEXEGOA3c18G4VtORuNTcHkUdiWmNuFbTsbjWiaGr16xJnfr3dRPwceArABFxNSJm6OL1WiOm1XTrv+EDwI8i4iwZXq9SJHp49yP/KyytxD0SEUdZfd+d24BzNU+fSI51Ki6AfyHpe5KerPlI1qm4fpfG9yjq2LVaJS7o7rVaFsA3Jb0s6WByLA/XrF5c0N1rdicwDfx+Uob7sqRBunu9VosJ8vHva9l+4JnkdmbXqzSJPiIWI+KjwChwn6R71zhd9f5EB+P6EvAh4KPAJPCfOxWXavYoavQpdY5lfq3WiKtr12qFn4uIjwGfBB6V9PE1zu1kbPXi6vY16wU+BnwpIn4GmGXt7co7EddqMXX7Wr1L0kbg08CfrHdqnWNrxlaaRL8s+Tj2IvAQyb47ALpx350J4Paap40Cb3QqroiYSt4ArgP/g/c+dnUiruU9il4DngV+XjV7FEHXrlXduLp8rd4VEW8kv88Df5bE0e1rVjeuHFyzCWCi5tPr11hKst28XnVjysG1qvVJ4DsRMZXcz+x6lSLRS9ouaTi5vQn4BeCHrL7vzvPAfkn9ku4AdgMvdSqu5f94iX8MHO9UXNH8HkUduVarxdXNa7VM0qCkoeXbwC8mcXT731fduLp9zSLiJ8A5SXcnhx4ATtLF67VaTN2+Vis8zHtlm+UYsrle7Z5F7sQP8BHgu8D3WPoP9e+S49tY+parV5PfW2ue8zmWZqtPAZ/scFx/AHw/Of48sLOTcdW81v28193S1Wu1Rlxdv1Ys1XePJT8ngM/l4ZqtEVcertlHgfEkhj8HbsnB9aoXU9evVfJam4E3gZtrjmV2vbwFgplZyZWidGNmZqtzojczKzknejOzknOiNzMrOSd6M7OSc6I3Mys5J3ozs5L7/5ethg0pv/hqAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plot the correlation\n",
    "\n",
    "plt.scatter(crime.Wage, crime.CrimeRate, alpha = 0.3, cmap = 'viridis')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Wage', ylabel='CrimeRate'>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x=crime['Wage'], y=crime['CrimeRate'], line_kws={'color': \"r\", \"alpha\":0.7, \"lw\":5})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "BelowWage10         BelowWage10            1.000000\n",
       "StateSize           StateSize10            0.999371\n",
       "CrimeRate           CrimeRate10            0.996596\n",
       "Education10         Education              0.995153\n",
       "ExpenditureYear10   ExpenditureYear0       0.993586\n",
       "YouthUnemployment   YouthUnemploy10        0.991235\n",
       "Wage                Wage10                 0.984164\n",
       "LabourForce         LabourForce10          0.974818\n",
       "MatureUnemploy10    MatureUnemployment     0.972611\n",
       "BelowWage10         BelowWage              0.962544\n",
       "MoreMales           MoreMales10            0.936117\n",
       "Wage                BelowWage              0.883997\n",
       "Males10             Males                  0.882966\n",
       "BelowWage           Wage10                 0.870723\n",
       "MoreMales           Males                  0.836195\n",
       "BelowWage10         Wage                   0.824248\n",
       "Wage10              BelowWage10            0.800181\n",
       "MoreMales           Males10                0.796917\n",
       "Wage                ExpenditureYear10      0.794262\n",
       "Wage10              ExpenditureYear10      0.791696\n",
       "MoreMales10         Males10                0.791045\n",
       "Youth               Youth10                0.790785\n",
       "ExpenditureYear0    Wage10                 0.787296\n",
       "                    Wage                   0.787225\n",
       "BelowWage10         Southern               0.751462\n",
       "MatureUnemployment  YouthUnemployment      0.745925\n",
       "MoreMales10         Males                  0.745046\n",
       "HighYouthUnemploy   HighYouthUnemploy10    0.738129\n",
       "Southern            BelowWage              0.737181\n",
       "YouthUnemployment   MatureUnemploy10       0.726123\n",
       "MatureUnemployment  YouthUnemploy10        0.718910\n",
       "YouthUnemploy10     MatureUnemploy10       0.706937\n",
       "dtype: float64"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr = crime.corr().abs().unstack().sort_values(ascending=False).drop_duplicates()\n",
    "                                  \n",
    "corr[corr>=0.7]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "BelowWage10          BelowWage10           1.000000\n",
       "StateSize            StateSize10           0.999371\n",
       "CrimeRate            CrimeRate10           0.996596\n",
       "Education10          Education             0.995153\n",
       "ExpenditureYear10    ExpenditureYear0      0.993586\n",
       "                                             ...   \n",
       "LabourForce          HighYouthUnemploy     0.413431\n",
       "StateSize            Males                 0.410628\n",
       "Males                StateSize10           0.408964\n",
       "Youth                Education             0.404477\n",
       "HighYouthUnemploy10  MatureUnemployment    0.402651\n",
       "Length: 99, dtype: float64"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr = crime.corr().abs().unstack().sort_values(ascending=False).drop_duplicates()\n",
    "                                  \n",
    "corr[corr>=0.4]"
   ]
  }
 ],
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