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terapyon/breast_cancer.ipynb

Created January 28, 2018 13:20
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breast_cancer.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.datasets import load_breast_cancer"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"data = load_breast_cancer(return_X_y=False)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['DESCR', 'data', 'feature_names', 'target', 'target_names']"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dir(data)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(569, 30)"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.data.shape"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(['mean radius', 'mean texture', 'mean perimeter', 'mean area',\n",
" 'mean smoothness', 'mean compactness', 'mean concavity',\n",
" 'mean concave points', 'mean symmetry', 'mean fractal dimension',\n",
" 'radius error', 'texture error', 'perimeter error', 'area error',\n",
" 'smoothness error', 'compactness error', 'concavity error',\n",
" 'concave points error', 'symmetry error',\n",
" 'fractal dimension error', 'worst radius', 'worst texture',\n",
" 'worst perimeter', 'worst area', 'worst smoothness',\n",
" 'worst compactness', 'worst concavity', 'worst concave points',\n",
" 'worst symmetry', 'worst fractal dimension'], dtype='<U23')"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.feature_names"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(30,)"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.feature_names.shape"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(['malignant', 'benign'], dtype='<U9')"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.target_names"
]
},
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"scrolled": true
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"source": [
"data.target"
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{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"X, y = load_breast_cancer(return_X_y=True)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
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" 1.189e-01],\n",
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" 8.902e-02],\n",
" [1.969e+01, 2.125e+01, 1.300e+02, ..., 2.430e-01, 3.613e-01,\n",
" 8.758e-02],\n",
" ...,\n",
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" 7.820e-02],\n",
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" 1.240e-01],\n",
" [7.760e+00, 2.454e+01, 4.792e+01, ..., 0.000e+00, 2.871e-01,\n",
" 7.039e-02]])"
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"metadata": {},
"output_type": "execute_result"
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"source": [
"X"
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{
"cell_type": "code",
"execution_count": 7,
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},
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"y"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"df = pd.DataFrame(X)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
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" <th>0</th>\n",
" <td>17.990</td>\n",
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" <td>0.4601</td>\n",
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" <tr>\n",
" <th>1</th>\n",
" <td>20.570</td>\n",
" <td>17.77</td>\n",
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" <td>0.1812</td>\n",
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" <td>23.41</td>\n",
" <td>158.80</td>\n",
" <td>1956.0</td>\n",
" <td>0.12380</td>\n",
" <td>0.18660</td>\n",
" <td>0.24160</td>\n",
" <td>0.18600</td>\n",
" <td>0.2750</td>\n",
" <td>0.08902</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>19.690</td>\n",
" <td>21.25</td>\n",
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" <td>0.05999</td>\n",
" <td>...</td>\n",
" <td>23.570</td>\n",
" <td>25.53</td>\n",
" <td>152.50</td>\n",
" <td>1709.0</td>\n",
" <td>0.14440</td>\n",
" <td>0.42450</td>\n",
" <td>0.45040</td>\n",
" <td>0.24300</td>\n",
" <td>0.3613</td>\n",
" <td>0.08758</td>\n",
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" <tr>\n",
" <th>3</th>\n",
" <td>11.420</td>\n",
" <td>20.38</td>\n",
" <td>77.58</td>\n",
" <td>386.1</td>\n",
" <td>0.14250</td>\n",
" <td>0.28390</td>\n",
" <td>0.241400</td>\n",
" <td>0.105200</td>\n",
" <td>0.2597</td>\n",
" <td>0.09744</td>\n",
" <td>...</td>\n",
" <td>14.910</td>\n",
" <td>26.50</td>\n",
" <td>98.87</td>\n",
" <td>567.7</td>\n",
" <td>0.20980</td>\n",
" <td>0.86630</td>\n",
" <td>0.68690</td>\n",
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" <td>0.6638</td>\n",
" <td>0.17300</td>\n",
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" <th>4</th>\n",
" <td>20.290</td>\n",
" <td>14.34</td>\n",
" <td>135.10</td>\n",
" <td>1297.0</td>\n",
" <td>0.10030</td>\n",
" <td>0.13280</td>\n",
" <td>0.198000</td>\n",
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" <td>0.1809</td>\n",
" <td>0.05883</td>\n",
" <td>...</td>\n",
" <td>22.540</td>\n",
" <td>16.67</td>\n",
" <td>152.20</td>\n",
" <td>1575.0</td>\n",
" <td>0.13740</td>\n",
" <td>0.20500</td>\n",
" <td>0.40000</td>\n",
" <td>0.16250</td>\n",
" <td>0.2364</td>\n",
" <td>0.07678</td>\n",
" </tr>\n",
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" <th>5</th>\n",
" <td>12.450</td>\n",
" <td>15.70</td>\n",
" <td>82.57</td>\n",
" <td>477.1</td>\n",
" <td>0.12780</td>\n",
" <td>0.17000</td>\n",
" <td>0.157800</td>\n",
" <td>0.080890</td>\n",
" <td>0.2087</td>\n",
" <td>0.07613</td>\n",
" <td>...</td>\n",
" <td>15.470</td>\n",
" <td>23.75</td>\n",
" <td>103.40</td>\n",
" <td>741.6</td>\n",
" <td>0.17910</td>\n",
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" <td>0.53550</td>\n",
" <td>0.17410</td>\n",
" <td>0.3985</td>\n",
" <td>0.12440</td>\n",
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" <th>6</th>\n",
" <td>18.250</td>\n",
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" <td>0.10900</td>\n",
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" <td>0.1794</td>\n",
" <td>0.05742</td>\n",
" <td>...</td>\n",
" <td>22.880</td>\n",
" <td>27.66</td>\n",
" <td>153.20</td>\n",
" <td>1606.0</td>\n",
" <td>0.14420</td>\n",
" <td>0.25760</td>\n",
" <td>0.37840</td>\n",
" <td>0.19320</td>\n",
" <td>0.3063</td>\n",
" <td>0.08368</td>\n",
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" <tr>\n",
" <th>7</th>\n",
" <td>13.710</td>\n",
" <td>20.83</td>\n",
" <td>90.20</td>\n",
" <td>577.9</td>\n",
" <td>0.11890</td>\n",
" <td>0.16450</td>\n",
" <td>0.093660</td>\n",
" <td>0.059850</td>\n",
" <td>0.2196</td>\n",
" <td>0.07451</td>\n",
" <td>...</td>\n",
" <td>17.060</td>\n",
" <td>28.14</td>\n",
" <td>110.60</td>\n",
" <td>897.0</td>\n",
" <td>0.16540</td>\n",
" <td>0.36820</td>\n",
" <td>0.26780</td>\n",
" <td>0.15560</td>\n",
" <td>0.3196</td>\n",
" <td>0.11510</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>13.000</td>\n",
" <td>21.82</td>\n",
" <td>87.50</td>\n",
" <td>519.8</td>\n",
" <td>0.12730</td>\n",
" <td>0.19320</td>\n",
" <td>0.185900</td>\n",
" <td>0.093530</td>\n",
" <td>0.2350</td>\n",
" <td>0.07389</td>\n",
" <td>...</td>\n",
" <td>15.490</td>\n",
" <td>30.73</td>\n",
" <td>106.20</td>\n",
" <td>739.3</td>\n",
" <td>0.17030</td>\n",
" <td>0.54010</td>\n",
" <td>0.53900</td>\n",
" <td>0.20600</td>\n",
" <td>0.4378</td>\n",
" <td>0.10720</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>12.460</td>\n",
" <td>24.04</td>\n",
" <td>83.97</td>\n",
" <td>475.9</td>\n",
" <td>0.11860</td>\n",
" <td>0.23960</td>\n",
" <td>0.227300</td>\n",
" <td>0.085430</td>\n",
" <td>0.2030</td>\n",
" <td>0.08243</td>\n",
" <td>...</td>\n",
" <td>15.090</td>\n",
" <td>40.68</td>\n",
" <td>97.65</td>\n",
" <td>711.4</td>\n",
" <td>0.18530</td>\n",
" <td>1.05800</td>\n",
" <td>1.10500</td>\n",
" <td>0.22100</td>\n",
" <td>0.4366</td>\n",
" <td>0.20750</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>16.020</td>\n",
" <td>23.24</td>\n",
" <td>102.70</td>\n",
" <td>797.8</td>\n",
" <td>0.08206</td>\n",
" <td>0.06669</td>\n",
" <td>0.032990</td>\n",
" <td>0.033230</td>\n",
" <td>0.1528</td>\n",
" <td>0.05697</td>\n",
" <td>...</td>\n",
" <td>19.190</td>\n",
" <td>33.88</td>\n",
" <td>123.80</td>\n",
" <td>1150.0</td>\n",
" <td>0.11810</td>\n",
" <td>0.15510</td>\n",
" <td>0.14590</td>\n",
" <td>0.09975</td>\n",
" <td>0.2948</td>\n",
" <td>0.08452</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>15.780</td>\n",
" <td>17.89</td>\n",
" <td>103.60</td>\n",
" <td>781.0</td>\n",
" <td>0.09710</td>\n",
" <td>0.12920</td>\n",
" <td>0.099540</td>\n",
" <td>0.066060</td>\n",
" <td>0.1842</td>\n",
" <td>0.06082</td>\n",
" <td>...</td>\n",
" <td>20.420</td>\n",
" <td>27.28</td>\n",
" <td>136.50</td>\n",
" <td>1299.0</td>\n",
" <td>0.13960</td>\n",
" <td>0.56090</td>\n",
" <td>0.39650</td>\n",
" <td>0.18100</td>\n",
" <td>0.3792</td>\n",
" <td>0.10480</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>19.170</td>\n",
" <td>24.80</td>\n",
" <td>132.40</td>\n",
" <td>1123.0</td>\n",
" <td>0.09740</td>\n",
" <td>0.24580</td>\n",
" <td>0.206500</td>\n",
" <td>0.111800</td>\n",
" <td>0.2397</td>\n",
" <td>0.07800</td>\n",
" <td>...</td>\n",
" <td>20.960</td>\n",
" <td>29.94</td>\n",
" <td>151.70</td>\n",
" <td>1332.0</td>\n",
" <td>0.10370</td>\n",
" <td>0.39030</td>\n",
" <td>0.36390</td>\n",
" <td>0.17670</td>\n",
" <td>0.3176</td>\n",
" <td>0.10230</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>15.850</td>\n",
" <td>23.95</td>\n",
" <td>103.70</td>\n",
" <td>782.7</td>\n",
" <td>0.08401</td>\n",
" <td>0.10020</td>\n",
" <td>0.099380</td>\n",
" <td>0.053640</td>\n",
" <td>0.1847</td>\n",
" <td>0.05338</td>\n",
" <td>...</td>\n",
" <td>16.840</td>\n",
" <td>27.66</td>\n",
" <td>112.00</td>\n",
" <td>876.5</td>\n",
" <td>0.11310</td>\n",
" <td>0.19240</td>\n",
" <td>0.23220</td>\n",
" <td>0.11190</td>\n",
" <td>0.2809</td>\n",
" <td>0.06287</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>13.730</td>\n",
" <td>22.61</td>\n",
" <td>93.60</td>\n",
" <td>578.3</td>\n",
" <td>0.11310</td>\n",
" <td>0.22930</td>\n",
" <td>0.212800</td>\n",
" <td>0.080250</td>\n",
" <td>0.2069</td>\n",
" <td>0.07682</td>\n",
" <td>...</td>\n",
" <td>15.030</td>\n",
" <td>32.01</td>\n",
" <td>108.80</td>\n",
" <td>697.7</td>\n",
" <td>0.16510</td>\n",
" <td>0.77250</td>\n",
" <td>0.69430</td>\n",
" <td>0.22080</td>\n",
" <td>0.3596</td>\n",
" <td>0.14310</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>14.540</td>\n",
" <td>27.54</td>\n",
" <td>96.73</td>\n",
" <td>658.8</td>\n",
" <td>0.11390</td>\n",
" <td>0.15950</td>\n",
" <td>0.163900</td>\n",
" <td>0.073640</td>\n",
" <td>0.2303</td>\n",
" <td>0.07077</td>\n",
" <td>...</td>\n",
" <td>17.460</td>\n",
" <td>37.13</td>\n",
" <td>124.10</td>\n",
" <td>943.2</td>\n",
" <td>0.16780</td>\n",
" <td>0.65770</td>\n",
" <td>0.70260</td>\n",
" <td>0.17120</td>\n",
" <td>0.4218</td>\n",
" <td>0.13410</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>14.680</td>\n",
" <td>20.13</td>\n",
" <td>94.74</td>\n",
" <td>684.5</td>\n",
" <td>0.09867</td>\n",
" <td>0.07200</td>\n",
" <td>0.073950</td>\n",
" <td>0.052590</td>\n",
" <td>0.1586</td>\n",
" <td>0.05922</td>\n",
" <td>...</td>\n",
" <td>19.070</td>\n",
" <td>30.88</td>\n",
" <td>123.40</td>\n",
" <td>1138.0</td>\n",
" <td>0.14640</td>\n",
" <td>0.18710</td>\n",
" <td>0.29140</td>\n",
" <td>0.16090</td>\n",
" <td>0.3029</td>\n",
" <td>0.08216</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>16.130</td>\n",
" <td>20.68</td>\n",
" <td>108.10</td>\n",
" <td>798.8</td>\n",
" <td>0.11700</td>\n",
" <td>0.20220</td>\n",
" <td>0.172200</td>\n",
" <td>0.102800</td>\n",
" <td>0.2164</td>\n",
" <td>0.07356</td>\n",
" <td>...</td>\n",
" <td>20.960</td>\n",
" <td>31.48</td>\n",
" <td>136.80</td>\n",
" <td>1315.0</td>\n",
" <td>0.17890</td>\n",
" <td>0.42330</td>\n",
" <td>0.47840</td>\n",
" <td>0.20730</td>\n",
" <td>0.3706</td>\n",
" <td>0.11420</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>19.810</td>\n",
" <td>22.15</td>\n",
" <td>130.00</td>\n",
" <td>1260.0</td>\n",
" <td>0.09831</td>\n",
" <td>0.10270</td>\n",
" <td>0.147900</td>\n",
" <td>0.094980</td>\n",
" <td>0.1582</td>\n",
" <td>0.05395</td>\n",
" <td>...</td>\n",
" <td>27.320</td>\n",
" <td>30.88</td>\n",
" <td>186.80</td>\n",
" <td>2398.0</td>\n",
" <td>0.15120</td>\n",
" <td>0.31500</td>\n",
" <td>0.53720</td>\n",
" <td>0.23880</td>\n",
" <td>0.2768</td>\n",
" <td>0.07615</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>13.540</td>\n",
" <td>14.36</td>\n",
" <td>87.46</td>\n",
" <td>566.3</td>\n",
" <td>0.09779</td>\n",
" <td>0.08129</td>\n",
" <td>0.066640</td>\n",
" <td>0.047810</td>\n",
" <td>0.1885</td>\n",
" <td>0.05766</td>\n",
" <td>...</td>\n",
" <td>15.110</td>\n",
" <td>19.26</td>\n",
" <td>99.70</td>\n",
" <td>711.2</td>\n",
" <td>0.14400</td>\n",
" <td>0.17730</td>\n",
" <td>0.23900</td>\n",
" <td>0.12880</td>\n",
" <td>0.2977</td>\n",
" <td>0.07259</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>13.080</td>\n",
" <td>15.71</td>\n",
" <td>85.63</td>\n",
" <td>520.0</td>\n",
" <td>0.10750</td>\n",
" <td>0.12700</td>\n",
" <td>0.045680</td>\n",
" <td>0.031100</td>\n",
" <td>0.1967</td>\n",
" <td>0.06811</td>\n",
" <td>...</td>\n",
" <td>14.500</td>\n",
" <td>20.49</td>\n",
" <td>96.09</td>\n",
" <td>630.5</td>\n",
" <td>0.13120</td>\n",
" <td>0.27760</td>\n",
" <td>0.18900</td>\n",
" <td>0.07283</td>\n",
" <td>0.3184</td>\n",
" <td>0.08183</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>9.504</td>\n",
" <td>12.44</td>\n",
" <td>60.34</td>\n",
" <td>273.9</td>\n",
" <td>0.10240</td>\n",
" <td>0.06492</td>\n",
" <td>0.029560</td>\n",
" <td>0.020760</td>\n",
" <td>0.1815</td>\n",
" <td>0.06905</td>\n",
" <td>...</td>\n",
" <td>10.230</td>\n",
" <td>15.66</td>\n",
" <td>65.13</td>\n",
" <td>314.9</td>\n",
" <td>0.13240</td>\n",
" <td>0.11480</td>\n",
" <td>0.08867</td>\n",
" <td>0.06227</td>\n",
" <td>0.2450</td>\n",
" <td>0.07773</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>15.340</td>\n",
" <td>14.26</td>\n",
" <td>102.50</td>\n",
" <td>704.4</td>\n",
" <td>0.10730</td>\n",
" <td>0.21350</td>\n",
" <td>0.207700</td>\n",
" <td>0.097560</td>\n",
" <td>0.2521</td>\n",
" <td>0.07032</td>\n",
" <td>...</td>\n",
" <td>18.070</td>\n",
" <td>19.08</td>\n",
" <td>125.10</td>\n",
" <td>980.9</td>\n",
" <td>0.13900</td>\n",
" <td>0.59540</td>\n",
" <td>0.63050</td>\n",
" <td>0.23930</td>\n",
" <td>0.4667</td>\n",
" <td>0.09946</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>21.160</td>\n",
" <td>23.04</td>\n",
" <td>137.20</td>\n",
" <td>1404.0</td>\n",
" <td>0.09428</td>\n",
" <td>0.10220</td>\n",
" <td>0.109700</td>\n",
" <td>0.086320</td>\n",
" <td>0.1769</td>\n",
" <td>0.05278</td>\n",
" <td>...</td>\n",
" <td>29.170</td>\n",
" <td>35.59</td>\n",
" <td>188.00</td>\n",
" <td>2615.0</td>\n",
" <td>0.14010</td>\n",
" <td>0.26000</td>\n",
" <td>0.31550</td>\n",
" <td>0.20090</td>\n",
" <td>0.2822</td>\n",
" <td>0.07526</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>16.650</td>\n",
" <td>21.38</td>\n",
" <td>110.00</td>\n",
" <td>904.6</td>\n",
" <td>0.11210</td>\n",
" <td>0.14570</td>\n",
" <td>0.152500</td>\n",
" <td>0.091700</td>\n",
" <td>0.1995</td>\n",
" <td>0.06330</td>\n",
" <td>...</td>\n",
" <td>26.460</td>\n",
" <td>31.56</td>\n",
" <td>177.00</td>\n",
" <td>2215.0</td>\n",
" <td>0.18050</td>\n",
" <td>0.35780</td>\n",
" <td>0.46950</td>\n",
" <td>0.20950</td>\n",
" <td>0.3613</td>\n",
" <td>0.09564</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>17.140</td>\n",
" <td>16.40</td>\n",
" <td>116.00</td>\n",
" <td>912.7</td>\n",
" <td>0.11860</td>\n",
" <td>0.22760</td>\n",
" <td>0.222900</td>\n",
" <td>0.140100</td>\n",
" <td>0.3040</td>\n",
" <td>0.07413</td>\n",
" <td>...</td>\n",
" <td>22.250</td>\n",
" <td>21.40</td>\n",
" <td>152.40</td>\n",
" <td>1461.0</td>\n",
" <td>0.15450</td>\n",
" <td>0.39490</td>\n",
" <td>0.38530</td>\n",
" <td>0.25500</td>\n",
" <td>0.4066</td>\n",
" <td>0.10590</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>14.580</td>\n",
" <td>21.53</td>\n",
" <td>97.41</td>\n",
" <td>644.8</td>\n",
" <td>0.10540</td>\n",
" <td>0.18680</td>\n",
" <td>0.142500</td>\n",
" <td>0.087830</td>\n",
" <td>0.2252</td>\n",
" <td>0.06924</td>\n",
" <td>...</td>\n",
" <td>17.620</td>\n",
" <td>33.21</td>\n",
" <td>122.40</td>\n",
" <td>896.9</td>\n",
" <td>0.15250</td>\n",
" <td>0.66430</td>\n",
" <td>0.55390</td>\n",
" <td>0.27010</td>\n",
" <td>0.4264</td>\n",
" <td>0.12750</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>18.610</td>\n",
" <td>20.25</td>\n",
" <td>122.10</td>\n",
" <td>1094.0</td>\n",
" <td>0.09440</td>\n",
" <td>0.10660</td>\n",
" <td>0.149000</td>\n",
" <td>0.077310</td>\n",
" <td>0.1697</td>\n",
" <td>0.05699</td>\n",
" <td>...</td>\n",
" <td>21.310</td>\n",
" <td>27.26</td>\n",
" <td>139.90</td>\n",
" <td>1403.0</td>\n",
" <td>0.13380</td>\n",
" <td>0.21170</td>\n",
" <td>0.34460</td>\n",
" <td>0.14900</td>\n",
" <td>0.2341</td>\n",
" <td>0.07421</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>15.300</td>\n",
" <td>25.27</td>\n",
" <td>102.40</td>\n",
" <td>732.4</td>\n",
" <td>0.10820</td>\n",
" <td>0.16970</td>\n",
" <td>0.168300</td>\n",
" <td>0.087510</td>\n",
" <td>0.1926</td>\n",
" <td>0.06540</td>\n",
" <td>...</td>\n",
" <td>20.270</td>\n",
" <td>36.71</td>\n",
" <td>149.30</td>\n",
" <td>1269.0</td>\n",
" <td>0.16410</td>\n",
" <td>0.61100</td>\n",
" <td>0.63350</td>\n",
" <td>0.20240</td>\n",
" <td>0.4027</td>\n",
" <td>0.09876</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>17.570</td>\n",
" <td>15.05</td>\n",
" <td>115.00</td>\n",
" <td>955.1</td>\n",
" <td>0.09847</td>\n",
" <td>0.11570</td>\n",
" <td>0.098750</td>\n",
" <td>0.079530</td>\n",
" <td>0.1739</td>\n",
" <td>0.06149</td>\n",
" <td>...</td>\n",
" <td>20.010</td>\n",
" <td>19.52</td>\n",
" <td>134.90</td>\n",
" <td>1227.0</td>\n",
" <td>0.12550</td>\n",
" <td>0.28120</td>\n",
" <td>0.24890</td>\n",
" <td>0.14560</td>\n",
" <td>0.2756</td>\n",
" <td>0.07919</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>539</th>\n",
" <td>7.691</td>\n",
" <td>25.44</td>\n",
" <td>48.34</td>\n",
" <td>170.4</td>\n",
" <td>0.08668</td>\n",
" <td>0.11990</td>\n",
" <td>0.092520</td>\n",
" <td>0.013640</td>\n",
" <td>0.2037</td>\n",
" <td>0.07751</td>\n",
" <td>...</td>\n",
" <td>8.678</td>\n",
" <td>31.89</td>\n",
" <td>54.49</td>\n",
" <td>223.6</td>\n",
" <td>0.15960</td>\n",
" <td>0.30640</td>\n",
" <td>0.33930</td>\n",
" <td>0.05000</td>\n",
" <td>0.2790</td>\n",
" <td>0.10660</td>\n",
" </tr>\n",
" <tr>\n",
" <th>540</th>\n",
" <td>11.540</td>\n",
" <td>14.44</td>\n",
" <td>74.65</td>\n",
" <td>402.9</td>\n",
" <td>0.09984</td>\n",
" <td>0.11200</td>\n",
" <td>0.067370</td>\n",
" <td>0.025940</td>\n",
" <td>0.1818</td>\n",
" <td>0.06782</td>\n",
" <td>...</td>\n",
" <td>12.260</td>\n",
" <td>19.68</td>\n",
" <td>78.78</td>\n",
" <td>457.8</td>\n",
" <td>0.13450</td>\n",
" <td>0.21180</td>\n",
" <td>0.17970</td>\n",
" <td>0.06918</td>\n",
" <td>0.2329</td>\n",
" <td>0.08134</td>\n",
" </tr>\n",
" <tr>\n",
" <th>541</th>\n",
" <td>14.470</td>\n",
" <td>24.99</td>\n",
" <td>95.81</td>\n",
" <td>656.4</td>\n",
" <td>0.08837</td>\n",
" <td>0.12300</td>\n",
" <td>0.100900</td>\n",
" <td>0.038900</td>\n",
" <td>0.1872</td>\n",
" <td>0.06341</td>\n",
" <td>...</td>\n",
" <td>16.220</td>\n",
" <td>31.73</td>\n",
" <td>113.50</td>\n",
" <td>808.9</td>\n",
" <td>0.13400</td>\n",
" <td>0.42020</td>\n",
" <td>0.40400</td>\n",
" <td>0.12050</td>\n",
" <td>0.3187</td>\n",
" <td>0.10230</td>\n",
" </tr>\n",
" <tr>\n",
" <th>542</th>\n",
" <td>14.740</td>\n",
" <td>25.42</td>\n",
" <td>94.70</td>\n",
" <td>668.6</td>\n",
" <td>0.08275</td>\n",
" <td>0.07214</td>\n",
" <td>0.041050</td>\n",
" <td>0.030270</td>\n",
" <td>0.1840</td>\n",
" <td>0.05680</td>\n",
" <td>...</td>\n",
" <td>16.510</td>\n",
" <td>32.29</td>\n",
" <td>107.40</td>\n",
" <td>826.4</td>\n",
" <td>0.10600</td>\n",
" <td>0.13760</td>\n",
" <td>0.16110</td>\n",
" <td>0.10950</td>\n",
" <td>0.2722</td>\n",
" <td>0.06956</td>\n",
" </tr>\n",
" <tr>\n",
" <th>543</th>\n",
" <td>13.210</td>\n",
" <td>28.06</td>\n",
" <td>84.88</td>\n",
" <td>538.4</td>\n",
" <td>0.08671</td>\n",
" <td>0.06877</td>\n",
" <td>0.029870</td>\n",
" <td>0.032750</td>\n",
" <td>0.1628</td>\n",
" <td>0.05781</td>\n",
" <td>...</td>\n",
" <td>14.370</td>\n",
" <td>37.17</td>\n",
" <td>92.48</td>\n",
" <td>629.6</td>\n",
" <td>0.10720</td>\n",
" <td>0.13810</td>\n",
" <td>0.10620</td>\n",
" <td>0.07958</td>\n",
" <td>0.2473</td>\n",
" <td>0.06443</td>\n",
" </tr>\n",
" <tr>\n",
" <th>544</th>\n",
" <td>13.870</td>\n",
" <td>20.70</td>\n",
" <td>89.77</td>\n",
" <td>584.8</td>\n",
" <td>0.09578</td>\n",
" <td>0.10180</td>\n",
" <td>0.036880</td>\n",
" <td>0.023690</td>\n",
" <td>0.1620</td>\n",
" <td>0.06688</td>\n",
" <td>...</td>\n",
" <td>15.050</td>\n",
" <td>24.75</td>\n",
" <td>99.17</td>\n",
" <td>688.6</td>\n",
" <td>0.12640</td>\n",
" <td>0.20370</td>\n",
" <td>0.13770</td>\n",
" <td>0.06845</td>\n",
" <td>0.2249</td>\n",
" <td>0.08492</td>\n",
" </tr>\n",
" <tr>\n",
" <th>545</th>\n",
" <td>13.620</td>\n",
" <td>23.23</td>\n",
" <td>87.19</td>\n",
" <td>573.2</td>\n",
" <td>0.09246</td>\n",
" <td>0.06747</td>\n",
" <td>0.029740</td>\n",
" <td>0.024430</td>\n",
" <td>0.1664</td>\n",
" <td>0.05801</td>\n",
" <td>...</td>\n",
" <td>15.350</td>\n",
" <td>29.09</td>\n",
" <td>97.58</td>\n",
" <td>729.8</td>\n",
" <td>0.12160</td>\n",
" <td>0.15170</td>\n",
" <td>0.10490</td>\n",
" <td>0.07174</td>\n",
" <td>0.2642</td>\n",
" <td>0.06953</td>\n",
" </tr>\n",
" <tr>\n",
" <th>546</th>\n",
" <td>10.320</td>\n",
" <td>16.35</td>\n",
" <td>65.31</td>\n",
" <td>324.9</td>\n",
" <td>0.09434</td>\n",
" <td>0.04994</td>\n",
" <td>0.010120</td>\n",
" <td>0.005495</td>\n",
" <td>0.1885</td>\n",
" <td>0.06201</td>\n",
" <td>...</td>\n",
" <td>11.250</td>\n",
" <td>21.77</td>\n",
" <td>71.12</td>\n",
" <td>384.9</td>\n",
" <td>0.12850</td>\n",
" <td>0.08842</td>\n",
" <td>0.04384</td>\n",
" <td>0.02381</td>\n",
" <td>0.2681</td>\n",
" <td>0.07399</td>\n",
" </tr>\n",
" <tr>\n",
" <th>547</th>\n",
" <td>10.260</td>\n",
" <td>16.58</td>\n",
" <td>65.85</td>\n",
" <td>320.8</td>\n",
" <td>0.08877</td>\n",
" <td>0.08066</td>\n",
" <td>0.043580</td>\n",
" <td>0.024380</td>\n",
" <td>0.1669</td>\n",
" <td>0.06714</td>\n",
" <td>...</td>\n",
" <td>10.830</td>\n",
" <td>22.04</td>\n",
" <td>71.08</td>\n",
" <td>357.4</td>\n",
" <td>0.14610</td>\n",
" <td>0.22460</td>\n",
" <td>0.17830</td>\n",
" <td>0.08333</td>\n",
" <td>0.2691</td>\n",
" <td>0.09479</td>\n",
" </tr>\n",
" <tr>\n",
" <th>548</th>\n",
" <td>9.683</td>\n",
" <td>19.34</td>\n",
" <td>61.05</td>\n",
" <td>285.7</td>\n",
" <td>0.08491</td>\n",
" <td>0.05030</td>\n",
" <td>0.023370</td>\n",
" <td>0.009615</td>\n",
" <td>0.1580</td>\n",
" <td>0.06235</td>\n",
" <td>...</td>\n",
" <td>10.930</td>\n",
" <td>25.59</td>\n",
" <td>69.10</td>\n",
" <td>364.2</td>\n",
" <td>0.11990</td>\n",
" <td>0.09546</td>\n",
" <td>0.09350</td>\n",
" <td>0.03846</td>\n",
" <td>0.2552</td>\n",
" <td>0.07920</td>\n",
" </tr>\n",
" <tr>\n",
" <th>549</th>\n",
" <td>10.820</td>\n",
" <td>24.21</td>\n",
" <td>68.89</td>\n",
" <td>361.6</td>\n",
" <td>0.08192</td>\n",
" <td>0.06602</td>\n",
" <td>0.015480</td>\n",
" <td>0.008160</td>\n",
" <td>0.1976</td>\n",
" <td>0.06328</td>\n",
" <td>...</td>\n",
" <td>13.030</td>\n",
" <td>31.45</td>\n",
" <td>83.90</td>\n",
" <td>505.6</td>\n",
" <td>0.12040</td>\n",
" <td>0.16330</td>\n",
" <td>0.06194</td>\n",
" <td>0.03264</td>\n",
" <td>0.3059</td>\n",
" <td>0.07626</td>\n",
" </tr>\n",
" <tr>\n",
" <th>550</th>\n",
" <td>10.860</td>\n",
" <td>21.48</td>\n",
" <td>68.51</td>\n",
" <td>360.5</td>\n",
" <td>0.07431</td>\n",
" <td>0.04227</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.1661</td>\n",
" <td>0.05948</td>\n",
" <td>...</td>\n",
" <td>11.660</td>\n",
" <td>24.77</td>\n",
" <td>74.08</td>\n",
" <td>412.3</td>\n",
" <td>0.10010</td>\n",
" <td>0.07348</td>\n",
" <td>0.00000</td>\n",
" <td>0.00000</td>\n",
" <td>0.2458</td>\n",
" <td>0.06592</td>\n",
" </tr>\n",
" <tr>\n",
" <th>551</th>\n",
" <td>11.130</td>\n",
" <td>22.44</td>\n",
" <td>71.49</td>\n",
" <td>378.4</td>\n",
" <td>0.09566</td>\n",
" <td>0.08194</td>\n",
" <td>0.048240</td>\n",
" <td>0.022570</td>\n",
" <td>0.2030</td>\n",
" <td>0.06552</td>\n",
" <td>...</td>\n",
" <td>12.020</td>\n",
" <td>28.26</td>\n",
" <td>77.80</td>\n",
" <td>436.6</td>\n",
" <td>0.10870</td>\n",
" <td>0.17820</td>\n",
" <td>0.15640</td>\n",
" <td>0.06413</td>\n",
" <td>0.3169</td>\n",
" <td>0.08032</td>\n",
" </tr>\n",
" <tr>\n",
" <th>552</th>\n",
" <td>12.770</td>\n",
" <td>29.43</td>\n",
" <td>81.35</td>\n",
" <td>507.9</td>\n",
" <td>0.08276</td>\n",
" <td>0.04234</td>\n",
" <td>0.019970</td>\n",
" <td>0.014990</td>\n",
" <td>0.1539</td>\n",
" <td>0.05637</td>\n",
" <td>...</td>\n",
" <td>13.870</td>\n",
" <td>36.00</td>\n",
" <td>88.10</td>\n",
" <td>594.7</td>\n",
" <td>0.12340</td>\n",
" <td>0.10640</td>\n",
" <td>0.08653</td>\n",
" <td>0.06498</td>\n",
" <td>0.2407</td>\n",
" <td>0.06484</td>\n",
" </tr>\n",
" <tr>\n",
" <th>553</th>\n",
" <td>9.333</td>\n",
" <td>21.94</td>\n",
" <td>59.01</td>\n",
" <td>264.0</td>\n",
" <td>0.09240</td>\n",
" <td>0.05605</td>\n",
" <td>0.039960</td>\n",
" <td>0.012820</td>\n",
" <td>0.1692</td>\n",
" <td>0.06576</td>\n",
" <td>...</td>\n",
" <td>9.845</td>\n",
" <td>25.05</td>\n",
" <td>62.86</td>\n",
" <td>295.8</td>\n",
" <td>0.11030</td>\n",
" <td>0.08298</td>\n",
" <td>0.07993</td>\n",
" <td>0.02564</td>\n",
" <td>0.2435</td>\n",
" <td>0.07393</td>\n",
" </tr>\n",
" <tr>\n",
" <th>554</th>\n",
" <td>12.880</td>\n",
" <td>28.92</td>\n",
" <td>82.50</td>\n",
" <td>514.3</td>\n",
" <td>0.08123</td>\n",
" <td>0.05824</td>\n",
" <td>0.061950</td>\n",
" <td>0.023430</td>\n",
" <td>0.1566</td>\n",
" <td>0.05708</td>\n",
" <td>...</td>\n",
" <td>13.890</td>\n",
" <td>35.74</td>\n",
" <td>88.84</td>\n",
" <td>595.7</td>\n",
" <td>0.12270</td>\n",
" <td>0.16200</td>\n",
" <td>0.24390</td>\n",
" <td>0.06493</td>\n",
" <td>0.2372</td>\n",
" <td>0.07242</td>\n",
" </tr>\n",
" <tr>\n",
" <th>555</th>\n",
" <td>10.290</td>\n",
" <td>27.61</td>\n",
" <td>65.67</td>\n",
" <td>321.4</td>\n",
" <td>0.09030</td>\n",
" <td>0.07658</td>\n",
" <td>0.059990</td>\n",
" <td>0.027380</td>\n",
" <td>0.1593</td>\n",
" <td>0.06127</td>\n",
" <td>...</td>\n",
" <td>10.840</td>\n",
" <td>34.91</td>\n",
" <td>69.57</td>\n",
" <td>357.6</td>\n",
" <td>0.13840</td>\n",
" <td>0.17100</td>\n",
" <td>0.20000</td>\n",
" <td>0.09127</td>\n",
" <td>0.2226</td>\n",
" <td>0.08283</td>\n",
" </tr>\n",
" <tr>\n",
" <th>556</th>\n",
" <td>10.160</td>\n",
" <td>19.59</td>\n",
" <td>64.73</td>\n",
" <td>311.7</td>\n",
" <td>0.10030</td>\n",
" <td>0.07504</td>\n",
" <td>0.005025</td>\n",
" <td>0.011160</td>\n",
" <td>0.1791</td>\n",
" <td>0.06331</td>\n",
" <td>...</td>\n",
" <td>10.650</td>\n",
" <td>22.88</td>\n",
" <td>67.88</td>\n",
" <td>347.3</td>\n",
" <td>0.12650</td>\n",
" <td>0.12000</td>\n",
" <td>0.01005</td>\n",
" <td>0.02232</td>\n",
" <td>0.2262</td>\n",
" <td>0.06742</td>\n",
" </tr>\n",
" <tr>\n",
" <th>557</th>\n",
" <td>9.423</td>\n",
" <td>27.88</td>\n",
" <td>59.26</td>\n",
" <td>271.3</td>\n",
" <td>0.08123</td>\n",
" <td>0.04971</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.1742</td>\n",
" <td>0.06059</td>\n",
" <td>...</td>\n",
" <td>10.490</td>\n",
" <td>34.24</td>\n",
" <td>66.50</td>\n",
" <td>330.6</td>\n",
" <td>0.10730</td>\n",
" <td>0.07158</td>\n",
" <td>0.00000</td>\n",
" <td>0.00000</td>\n",
" <td>0.2475</td>\n",
" <td>0.06969</td>\n",
" </tr>\n",
" <tr>\n",
" <th>558</th>\n",
" <td>14.590</td>\n",
" <td>22.68</td>\n",
" <td>96.39</td>\n",
" <td>657.1</td>\n",
" <td>0.08473</td>\n",
" <td>0.13300</td>\n",
" <td>0.102900</td>\n",
" <td>0.037360</td>\n",
" <td>0.1454</td>\n",
" <td>0.06147</td>\n",
" <td>...</td>\n",
" <td>15.480</td>\n",
" <td>27.27</td>\n",
" <td>105.90</td>\n",
" <td>733.5</td>\n",
" <td>0.10260</td>\n",
" <td>0.31710</td>\n",
" <td>0.36620</td>\n",
" <td>0.11050</td>\n",
" <td>0.2258</td>\n",
" <td>0.08004</td>\n",
" </tr>\n",
" <tr>\n",
" <th>559</th>\n",
" <td>11.510</td>\n",
" <td>23.93</td>\n",
" <td>74.52</td>\n",
" <td>403.5</td>\n",
" <td>0.09261</td>\n",
" <td>0.10210</td>\n",
" <td>0.111200</td>\n",
" <td>0.041050</td>\n",
" <td>0.1388</td>\n",
" <td>0.06570</td>\n",
" <td>...</td>\n",
" <td>12.480</td>\n",
" <td>37.16</td>\n",
" <td>82.28</td>\n",
" <td>474.2</td>\n",
" <td>0.12980</td>\n",
" <td>0.25170</td>\n",
" <td>0.36300</td>\n",
" <td>0.09653</td>\n",
" <td>0.2112</td>\n",
" <td>0.08732</td>\n",
" </tr>\n",
" <tr>\n",
" <th>560</th>\n",
" <td>14.050</td>\n",
" <td>27.15</td>\n",
" <td>91.38</td>\n",
" <td>600.4</td>\n",
" <td>0.09929</td>\n",
" <td>0.11260</td>\n",
" <td>0.044620</td>\n",
" <td>0.043040</td>\n",
" <td>0.1537</td>\n",
" <td>0.06171</td>\n",
" <td>...</td>\n",
" <td>15.300</td>\n",
" <td>33.17</td>\n",
" <td>100.20</td>\n",
" <td>706.7</td>\n",
" <td>0.12410</td>\n",
" <td>0.22640</td>\n",
" <td>0.13260</td>\n",
" <td>0.10480</td>\n",
" <td>0.2250</td>\n",
" <td>0.08321</td>\n",
" </tr>\n",
" <tr>\n",
" <th>561</th>\n",
" <td>11.200</td>\n",
" <td>29.37</td>\n",
" <td>70.67</td>\n",
" <td>386.0</td>\n",
" <td>0.07449</td>\n",
" <td>0.03558</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.1060</td>\n",
" <td>0.05502</td>\n",
" <td>...</td>\n",
" <td>11.920</td>\n",
" <td>38.30</td>\n",
" <td>75.19</td>\n",
" <td>439.6</td>\n",
" <td>0.09267</td>\n",
" <td>0.05494</td>\n",
" <td>0.00000</td>\n",
" <td>0.00000</td>\n",
" <td>0.1566</td>\n",
" <td>0.05905</td>\n",
" </tr>\n",
" <tr>\n",
" <th>562</th>\n",
" <td>15.220</td>\n",
" <td>30.62</td>\n",
" <td>103.40</td>\n",
" <td>716.9</td>\n",
" <td>0.10480</td>\n",
" <td>0.20870</td>\n",
" <td>0.255000</td>\n",
" <td>0.094290</td>\n",
" <td>0.2128</td>\n",
" <td>0.07152</td>\n",
" <td>...</td>\n",
" <td>17.520</td>\n",
" <td>42.79</td>\n",
" <td>128.70</td>\n",
" <td>915.0</td>\n",
" <td>0.14170</td>\n",
" <td>0.79170</td>\n",
" <td>1.17000</td>\n",
" <td>0.23560</td>\n",
" <td>0.4089</td>\n",
" <td>0.14090</td>\n",
" </tr>\n",
" <tr>\n",
" <th>563</th>\n",
" <td>20.920</td>\n",
" <td>25.09</td>\n",
" <td>143.00</td>\n",
" <td>1347.0</td>\n",
" <td>0.10990</td>\n",
" <td>0.22360</td>\n",
" <td>0.317400</td>\n",
" <td>0.147400</td>\n",
" <td>0.2149</td>\n",
" <td>0.06879</td>\n",
" <td>...</td>\n",
" <td>24.290</td>\n",
" <td>29.41</td>\n",
" <td>179.10</td>\n",
" <td>1819.0</td>\n",
" <td>0.14070</td>\n",
" <td>0.41860</td>\n",
" <td>0.65990</td>\n",
" <td>0.25420</td>\n",
" <td>0.2929</td>\n",
" <td>0.09873</td>\n",
" </tr>\n",
" <tr>\n",
" <th>564</th>\n",
" <td>21.560</td>\n",
" <td>22.39</td>\n",
" <td>142.00</td>\n",
" <td>1479.0</td>\n",
" <td>0.11100</td>\n",
" <td>0.11590</td>\n",
" <td>0.243900</td>\n",
" <td>0.138900</td>\n",
" <td>0.1726</td>\n",
" <td>0.05623</td>\n",
" <td>...</td>\n",
" <td>25.450</td>\n",
" <td>26.40</td>\n",
" <td>166.10</td>\n",
" <td>2027.0</td>\n",
" <td>0.14100</td>\n",
" <td>0.21130</td>\n",
" <td>0.41070</td>\n",
" <td>0.22160</td>\n",
" <td>0.2060</td>\n",
" <td>0.07115</td>\n",
" </tr>\n",
" <tr>\n",
" <th>565</th>\n",
" <td>20.130</td>\n",
" <td>28.25</td>\n",
" <td>131.20</td>\n",
" <td>1261.0</td>\n",
" <td>0.09780</td>\n",
" <td>0.10340</td>\n",
" <td>0.144000</td>\n",
" <td>0.097910</td>\n",
" <td>0.1752</td>\n",
" <td>0.05533</td>\n",
" <td>...</td>\n",
" <td>23.690</td>\n",
" <td>38.25</td>\n",
" <td>155.00</td>\n",
" <td>1731.0</td>\n",
" <td>0.11660</td>\n",
" <td>0.19220</td>\n",
" <td>0.32150</td>\n",
" <td>0.16280</td>\n",
" <td>0.2572</td>\n",
" <td>0.06637</td>\n",
" </tr>\n",
" <tr>\n",
" <th>566</th>\n",
" <td>16.600</td>\n",
" <td>28.08</td>\n",
" <td>108.30</td>\n",
" <td>858.1</td>\n",
" <td>0.08455</td>\n",
" <td>0.10230</td>\n",
" <td>0.092510</td>\n",
" <td>0.053020</td>\n",
" <td>0.1590</td>\n",
" <td>0.05648</td>\n",
" <td>...</td>\n",
" <td>18.980</td>\n",
" <td>34.12</td>\n",
" <td>126.70</td>\n",
" <td>1124.0</td>\n",
" <td>0.11390</td>\n",
" <td>0.30940</td>\n",
" <td>0.34030</td>\n",
" <td>0.14180</td>\n",
" <td>0.2218</td>\n",
" <td>0.07820</td>\n",
" </tr>\n",
" <tr>\n",
" <th>567</th>\n",
" <td>20.600</td>\n",
" <td>29.33</td>\n",
" <td>140.10</td>\n",
" <td>1265.0</td>\n",
" <td>0.11780</td>\n",
" <td>0.27700</td>\n",
" <td>0.351400</td>\n",
" <td>0.152000</td>\n",
" <td>0.2397</td>\n",
" <td>0.07016</td>\n",
" <td>...</td>\n",
" <td>25.740</td>\n",
" <td>39.42</td>\n",
" <td>184.60</td>\n",
" <td>1821.0</td>\n",
" <td>0.16500</td>\n",
" <td>0.86810</td>\n",
" <td>0.93870</td>\n",
" <td>0.26500</td>\n",
" <td>0.4087</td>\n",
" <td>0.12400</td>\n",
" </tr>\n",
" <tr>\n",
" <th>568</th>\n",
" <td>7.760</td>\n",
" <td>24.54</td>\n",
" <td>47.92</td>\n",
" <td>181.0</td>\n",
" <td>0.05263</td>\n",
" <td>0.04362</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.1587</td>\n",
" <td>0.05884</td>\n",
" <td>...</td>\n",
" <td>9.456</td>\n",
" <td>30.37</td>\n",
" <td>59.16</td>\n",
" <td>268.6</td>\n",
" <td>0.08996</td>\n",
" <td>0.06444</td>\n",
" <td>0.00000</td>\n",
" <td>0.00000</td>\n",
" <td>0.2871</td>\n",
" <td>0.07039</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>569 rows × 30 columns</p>\n",
"</div>"
],
"text/plain": [
" 0 1 2 3 4 5 6 7 \\\n",
"0 17.990 10.38 122.80 1001.0 0.11840 0.27760 0.300100 0.147100 \n",
"1 20.570 17.77 132.90 1326.0 0.08474 0.07864 0.086900 0.070170 \n",
"2 19.690 21.25 130.00 1203.0 0.10960 0.15990 0.197400 0.127900 \n",
"3 11.420 20.38 77.58 386.1 0.14250 0.28390 0.241400 0.105200 \n",
"4 20.290 14.34 135.10 1297.0 0.10030 0.13280 0.198000 0.104300 \n",
"5 12.450 15.70 82.57 477.1 0.12780 0.17000 0.157800 0.080890 \n",
"6 18.250 19.98 119.60 1040.0 0.09463 0.10900 0.112700 0.074000 \n",
"7 13.710 20.83 90.20 577.9 0.11890 0.16450 0.093660 0.059850 \n",
"8 13.000 21.82 87.50 519.8 0.12730 0.19320 0.185900 0.093530 \n",
"9 12.460 24.04 83.97 475.9 0.11860 0.23960 0.227300 0.085430 \n",
"10 16.020 23.24 102.70 797.8 0.08206 0.06669 0.032990 0.033230 \n",
"11 15.780 17.89 103.60 781.0 0.09710 0.12920 0.099540 0.066060 \n",
"12 19.170 24.80 132.40 1123.0 0.09740 0.24580 0.206500 0.111800 \n",
"13 15.850 23.95 103.70 782.7 0.08401 0.10020 0.099380 0.053640 \n",
"14 13.730 22.61 93.60 578.3 0.11310 0.22930 0.212800 0.080250 \n",
"15 14.540 27.54 96.73 658.8 0.11390 0.15950 0.163900 0.073640 \n",
"16 14.680 20.13 94.74 684.5 0.09867 0.07200 0.073950 0.052590 \n",
"17 16.130 20.68 108.10 798.8 0.11700 0.20220 0.172200 0.102800 \n",
"18 19.810 22.15 130.00 1260.0 0.09831 0.10270 0.147900 0.094980 \n",
"19 13.540 14.36 87.46 566.3 0.09779 0.08129 0.066640 0.047810 \n",
"20 13.080 15.71 85.63 520.0 0.10750 0.12700 0.045680 0.031100 \n",
"21 9.504 12.44 60.34 273.9 0.10240 0.06492 0.029560 0.020760 \n",
"22 15.340 14.26 102.50 704.4 0.10730 0.21350 0.207700 0.097560 \n",
"23 21.160 23.04 137.20 1404.0 0.09428 0.10220 0.109700 0.086320 \n",
"24 16.650 21.38 110.00 904.6 0.11210 0.14570 0.152500 0.091700 \n",
"25 17.140 16.40 116.00 912.7 0.11860 0.22760 0.222900 0.140100 \n",
"26 14.580 21.53 97.41 644.8 0.10540 0.18680 0.142500 0.087830 \n",
"27 18.610 20.25 122.10 1094.0 0.09440 0.10660 0.149000 0.077310 \n",
"28 15.300 25.27 102.40 732.4 0.10820 0.16970 0.168300 0.087510 \n",
"29 17.570 15.05 115.00 955.1 0.09847 0.11570 0.098750 0.079530 \n",
".. ... ... ... ... ... ... ... ... \n",
"539 7.691 25.44 48.34 170.4 0.08668 0.11990 0.092520 0.013640 \n",
"540 11.540 14.44 74.65 402.9 0.09984 0.11200 0.067370 0.025940 \n",
"541 14.470 24.99 95.81 656.4 0.08837 0.12300 0.100900 0.038900 \n",
"542 14.740 25.42 94.70 668.6 0.08275 0.07214 0.041050 0.030270 \n",
"543 13.210 28.06 84.88 538.4 0.08671 0.06877 0.029870 0.032750 \n",
"544 13.870 20.70 89.77 584.8 0.09578 0.10180 0.036880 0.023690 \n",
"545 13.620 23.23 87.19 573.2 0.09246 0.06747 0.029740 0.024430 \n",
"546 10.320 16.35 65.31 324.9 0.09434 0.04994 0.010120 0.005495 \n",
"547 10.260 16.58 65.85 320.8 0.08877 0.08066 0.043580 0.024380 \n",
"548 9.683 19.34 61.05 285.7 0.08491 0.05030 0.023370 0.009615 \n",
"549 10.820 24.21 68.89 361.6 0.08192 0.06602 0.015480 0.008160 \n",
"550 10.860 21.48 68.51 360.5 0.07431 0.04227 0.000000 0.000000 \n",
"551 11.130 22.44 71.49 378.4 0.09566 0.08194 0.048240 0.022570 \n",
"552 12.770 29.43 81.35 507.9 0.08276 0.04234 0.019970 0.014990 \n",
"553 9.333 21.94 59.01 264.0 0.09240 0.05605 0.039960 0.012820 \n",
"554 12.880 28.92 82.50 514.3 0.08123 0.05824 0.061950 0.023430 \n",
"555 10.290 27.61 65.67 321.4 0.09030 0.07658 0.059990 0.027380 \n",
"556 10.160 19.59 64.73 311.7 0.10030 0.07504 0.005025 0.011160 \n",
"557 9.423 27.88 59.26 271.3 0.08123 0.04971 0.000000 0.000000 \n",
"558 14.590 22.68 96.39 657.1 0.08473 0.13300 0.102900 0.037360 \n",
"559 11.510 23.93 74.52 403.5 0.09261 0.10210 0.111200 0.041050 \n",
"560 14.050 27.15 91.38 600.4 0.09929 0.11260 0.044620 0.043040 \n",
"561 11.200 29.37 70.67 386.0 0.07449 0.03558 0.000000 0.000000 \n",
"562 15.220 30.62 103.40 716.9 0.10480 0.20870 0.255000 0.094290 \n",
"563 20.920 25.09 143.00 1347.0 0.10990 0.22360 0.317400 0.147400 \n",
"564 21.560 22.39 142.00 1479.0 0.11100 0.11590 0.243900 0.138900 \n",
"565 20.130 28.25 131.20 1261.0 0.09780 0.10340 0.144000 0.097910 \n",
"566 16.600 28.08 108.30 858.1 0.08455 0.10230 0.092510 0.053020 \n",
"567 20.600 29.33 140.10 1265.0 0.11780 0.27700 0.351400 0.152000 \n",
"568 7.760 24.54 47.92 181.0 0.05263 0.04362 0.000000 0.000000 \n",
"\n",
" 8 9 ... 20 21 22 23 24 \\\n",
"0 0.2419 0.07871 ... 25.380 17.33 184.60 2019.0 0.16220 \n",
"1 0.1812 0.05667 ... 24.990 23.41 158.80 1956.0 0.12380 \n",
"2 0.2069 0.05999 ... 23.570 25.53 152.50 1709.0 0.14440 \n",
"3 0.2597 0.09744 ... 14.910 26.50 98.87 567.7 0.20980 \n",
"4 0.1809 0.05883 ... 22.540 16.67 152.20 1575.0 0.13740 \n",
"5 0.2087 0.07613 ... 15.470 23.75 103.40 741.6 0.17910 \n",
"6 0.1794 0.05742 ... 22.880 27.66 153.20 1606.0 0.14420 \n",
"7 0.2196 0.07451 ... 17.060 28.14 110.60 897.0 0.16540 \n",
"8 0.2350 0.07389 ... 15.490 30.73 106.20 739.3 0.17030 \n",
"9 0.2030 0.08243 ... 15.090 40.68 97.65 711.4 0.18530 \n",
"10 0.1528 0.05697 ... 19.190 33.88 123.80 1150.0 0.11810 \n",
"11 0.1842 0.06082 ... 20.420 27.28 136.50 1299.0 0.13960 \n",
"12 0.2397 0.07800 ... 20.960 29.94 151.70 1332.0 0.10370 \n",
"13 0.1847 0.05338 ... 16.840 27.66 112.00 876.5 0.11310 \n",
"14 0.2069 0.07682 ... 15.030 32.01 108.80 697.7 0.16510 \n",
"15 0.2303 0.07077 ... 17.460 37.13 124.10 943.2 0.16780 \n",
"16 0.1586 0.05922 ... 19.070 30.88 123.40 1138.0 0.14640 \n",
"17 0.2164 0.07356 ... 20.960 31.48 136.80 1315.0 0.17890 \n",
"18 0.1582 0.05395 ... 27.320 30.88 186.80 2398.0 0.15120 \n",
"19 0.1885 0.05766 ... 15.110 19.26 99.70 711.2 0.14400 \n",
"20 0.1967 0.06811 ... 14.500 20.49 96.09 630.5 0.13120 \n",
"21 0.1815 0.06905 ... 10.230 15.66 65.13 314.9 0.13240 \n",
"22 0.2521 0.07032 ... 18.070 19.08 125.10 980.9 0.13900 \n",
"23 0.1769 0.05278 ... 29.170 35.59 188.00 2615.0 0.14010 \n",
"24 0.1995 0.06330 ... 26.460 31.56 177.00 2215.0 0.18050 \n",
"25 0.3040 0.07413 ... 22.250 21.40 152.40 1461.0 0.15450 \n",
"26 0.2252 0.06924 ... 17.620 33.21 122.40 896.9 0.15250 \n",
"27 0.1697 0.05699 ... 21.310 27.26 139.90 1403.0 0.13380 \n",
"28 0.1926 0.06540 ... 20.270 36.71 149.30 1269.0 0.16410 \n",
"29 0.1739 0.06149 ... 20.010 19.52 134.90 1227.0 0.12550 \n",
".. ... ... ... ... ... ... ... ... \n",
"539 0.2037 0.07751 ... 8.678 31.89 54.49 223.6 0.15960 \n",
"540 0.1818 0.06782 ... 12.260 19.68 78.78 457.8 0.13450 \n",
"541 0.1872 0.06341 ... 16.220 31.73 113.50 808.9 0.13400 \n",
"542 0.1840 0.05680 ... 16.510 32.29 107.40 826.4 0.10600 \n",
"543 0.1628 0.05781 ... 14.370 37.17 92.48 629.6 0.10720 \n",
"544 0.1620 0.06688 ... 15.050 24.75 99.17 688.6 0.12640 \n",
"545 0.1664 0.05801 ... 15.350 29.09 97.58 729.8 0.12160 \n",
"546 0.1885 0.06201 ... 11.250 21.77 71.12 384.9 0.12850 \n",
"547 0.1669 0.06714 ... 10.830 22.04 71.08 357.4 0.14610 \n",
"548 0.1580 0.06235 ... 10.930 25.59 69.10 364.2 0.11990 \n",
"549 0.1976 0.06328 ... 13.030 31.45 83.90 505.6 0.12040 \n",
"550 0.1661 0.05948 ... 11.660 24.77 74.08 412.3 0.10010 \n",
"551 0.2030 0.06552 ... 12.020 28.26 77.80 436.6 0.10870 \n",
"552 0.1539 0.05637 ... 13.870 36.00 88.10 594.7 0.12340 \n",
"553 0.1692 0.06576 ... 9.845 25.05 62.86 295.8 0.11030 \n",
"554 0.1566 0.05708 ... 13.890 35.74 88.84 595.7 0.12270 \n",
"555 0.1593 0.06127 ... 10.840 34.91 69.57 357.6 0.13840 \n",
"556 0.1791 0.06331 ... 10.650 22.88 67.88 347.3 0.12650 \n",
"557 0.1742 0.06059 ... 10.490 34.24 66.50 330.6 0.10730 \n",
"558 0.1454 0.06147 ... 15.480 27.27 105.90 733.5 0.10260 \n",
"559 0.1388 0.06570 ... 12.480 37.16 82.28 474.2 0.12980 \n",
"560 0.1537 0.06171 ... 15.300 33.17 100.20 706.7 0.12410 \n",
"561 0.1060 0.05502 ... 11.920 38.30 75.19 439.6 0.09267 \n",
"562 0.2128 0.07152 ... 17.520 42.79 128.70 915.0 0.14170 \n",
"563 0.2149 0.06879 ... 24.290 29.41 179.10 1819.0 0.14070 \n",
"564 0.1726 0.05623 ... 25.450 26.40 166.10 2027.0 0.14100 \n",
"565 0.1752 0.05533 ... 23.690 38.25 155.00 1731.0 0.11660 \n",
"566 0.1590 0.05648 ... 18.980 34.12 126.70 1124.0 0.11390 \n",
"567 0.2397 0.07016 ... 25.740 39.42 184.60 1821.0 0.16500 \n",
"568 0.1587 0.05884 ... 9.456 30.37 59.16 268.6 0.08996 \n",
"\n",
" 25 26 27 28 29 \n",
"0 0.66560 0.71190 0.26540 0.4601 0.11890 \n",
"1 0.18660 0.24160 0.18600 0.2750 0.08902 \n",
"2 0.42450 0.45040 0.24300 0.3613 0.08758 \n",
"3 0.86630 0.68690 0.25750 0.6638 0.17300 \n",
"4 0.20500 0.40000 0.16250 0.2364 0.07678 \n",
"5 0.52490 0.53550 0.17410 0.3985 0.12440 \n",
"6 0.25760 0.37840 0.19320 0.3063 0.08368 \n",
"7 0.36820 0.26780 0.15560 0.3196 0.11510 \n",
"8 0.54010 0.53900 0.20600 0.4378 0.10720 \n",
"9 1.05800 1.10500 0.22100 0.4366 0.20750 \n",
"10 0.15510 0.14590 0.09975 0.2948 0.08452 \n",
"11 0.56090 0.39650 0.18100 0.3792 0.10480 \n",
"12 0.39030 0.36390 0.17670 0.3176 0.10230 \n",
"13 0.19240 0.23220 0.11190 0.2809 0.06287 \n",
"14 0.77250 0.69430 0.22080 0.3596 0.14310 \n",
"15 0.65770 0.70260 0.17120 0.4218 0.13410 \n",
"16 0.18710 0.29140 0.16090 0.3029 0.08216 \n",
"17 0.42330 0.47840 0.20730 0.3706 0.11420 \n",
"18 0.31500 0.53720 0.23880 0.2768 0.07615 \n",
"19 0.17730 0.23900 0.12880 0.2977 0.07259 \n",
"20 0.27760 0.18900 0.07283 0.3184 0.08183 \n",
"21 0.11480 0.08867 0.06227 0.2450 0.07773 \n",
"22 0.59540 0.63050 0.23930 0.4667 0.09946 \n",
"23 0.26000 0.31550 0.20090 0.2822 0.07526 \n",
"24 0.35780 0.46950 0.20950 0.3613 0.09564 \n",
"25 0.39490 0.38530 0.25500 0.4066 0.10590 \n",
"26 0.66430 0.55390 0.27010 0.4264 0.12750 \n",
"27 0.21170 0.34460 0.14900 0.2341 0.07421 \n",
"28 0.61100 0.63350 0.20240 0.4027 0.09876 \n",
"29 0.28120 0.24890 0.14560 0.2756 0.07919 \n",
".. ... ... ... ... ... \n",
"539 0.30640 0.33930 0.05000 0.2790 0.10660 \n",
"540 0.21180 0.17970 0.06918 0.2329 0.08134 \n",
"541 0.42020 0.40400 0.12050 0.3187 0.10230 \n",
"542 0.13760 0.16110 0.10950 0.2722 0.06956 \n",
"543 0.13810 0.10620 0.07958 0.2473 0.06443 \n",
"544 0.20370 0.13770 0.06845 0.2249 0.08492 \n",
"545 0.15170 0.10490 0.07174 0.2642 0.06953 \n",
"546 0.08842 0.04384 0.02381 0.2681 0.07399 \n",
"547 0.22460 0.17830 0.08333 0.2691 0.09479 \n",
"548 0.09546 0.09350 0.03846 0.2552 0.07920 \n",
"549 0.16330 0.06194 0.03264 0.3059 0.07626 \n",
"550 0.07348 0.00000 0.00000 0.2458 0.06592 \n",
"551 0.17820 0.15640 0.06413 0.3169 0.08032 \n",
"552 0.10640 0.08653 0.06498 0.2407 0.06484 \n",
"553 0.08298 0.07993 0.02564 0.2435 0.07393 \n",
"554 0.16200 0.24390 0.06493 0.2372 0.07242 \n",
"555 0.17100 0.20000 0.09127 0.2226 0.08283 \n",
"556 0.12000 0.01005 0.02232 0.2262 0.06742 \n",
"557 0.07158 0.00000 0.00000 0.2475 0.06969 \n",
"558 0.31710 0.36620 0.11050 0.2258 0.08004 \n",
"559 0.25170 0.36300 0.09653 0.2112 0.08732 \n",
"560 0.22640 0.13260 0.10480 0.2250 0.08321 \n",
"561 0.05494 0.00000 0.00000 0.1566 0.05905 \n",
"562 0.79170 1.17000 0.23560 0.4089 0.14090 \n",
"563 0.41860 0.65990 0.25420 0.2929 0.09873 \n",
"564 0.21130 0.41070 0.22160 0.2060 0.07115 \n",
"565 0.19220 0.32150 0.16280 0.2572 0.06637 \n",
"566 0.30940 0.34030 0.14180 0.2218 0.07820 \n",
"567 0.86810 0.93870 0.26500 0.4087 0.12400 \n",
"568 0.06444 0.00000 0.00000 0.2871 0.07039 \n",
"\n",
"[569 rows x 30 columns]"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>0</th>\n",
" <th>1</th>\n",
" <th>2</th>\n",
" <th>3</th>\n",
" <th>4</th>\n",
" <th>5</th>\n",
" <th>6</th>\n",
" <th>7</th>\n",
" <th>8</th>\n",
" <th>9</th>\n",
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" <th>20</th>\n",
" <th>21</th>\n",
" <th>22</th>\n",
" <th>23</th>\n",
" <th>24</th>\n",
" <th>25</th>\n",
" <th>26</th>\n",
" <th>27</th>\n",
" <th>28</th>\n",
" <th>29</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>569.000000</td>\n",
" <td>569.000000</td>\n",
" <td>569.000000</td>\n",
" <td>569.000000</td>\n",
" <td>569.000000</td>\n",
" <td>569.000000</td>\n",
" <td>569.000000</td>\n",
" <td>569.000000</td>\n",
" <td>569.000000</td>\n",
" <td>569.000000</td>\n",
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" <td>569.000000</td>\n",
" <td>569.000000</td>\n",
" <td>569.000000</td>\n",
" <td>569.000000</td>\n",
" <td>569.000000</td>\n",
" <td>569.000000</td>\n",
" <td>569.000000</td>\n",
" <td>569.000000</td>\n",
" <td>569.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>14.127292</td>\n",
" <td>19.289649</td>\n",
" <td>91.969033</td>\n",
" <td>654.889104</td>\n",
" <td>0.096360</td>\n",
" <td>0.104341</td>\n",
" <td>0.088799</td>\n",
" <td>0.048919</td>\n",
" <td>0.181162</td>\n",
" <td>0.062798</td>\n",
" <td>...</td>\n",
" <td>16.269190</td>\n",
" <td>25.677223</td>\n",
" <td>107.261213</td>\n",
" <td>880.583128</td>\n",
" <td>0.132369</td>\n",
" <td>0.254265</td>\n",
" <td>0.272188</td>\n",
" <td>0.114606</td>\n",
" <td>0.290076</td>\n",
" <td>0.083946</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>3.524049</td>\n",
" <td>4.301036</td>\n",
" <td>24.298981</td>\n",
" <td>351.914129</td>\n",
" <td>0.014064</td>\n",
" <td>0.052813</td>\n",
" <td>0.079720</td>\n",
" <td>0.038803</td>\n",
" <td>0.027414</td>\n",
" <td>0.007060</td>\n",
" <td>...</td>\n",
" <td>4.833242</td>\n",
" <td>6.146258</td>\n",
" <td>33.602542</td>\n",
" <td>569.356993</td>\n",
" <td>0.022832</td>\n",
" <td>0.157336</td>\n",
" <td>0.208624</td>\n",
" <td>0.065732</td>\n",
" <td>0.061867</td>\n",
" <td>0.018061</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>6.981000</td>\n",
" <td>9.710000</td>\n",
" <td>43.790000</td>\n",
" <td>143.500000</td>\n",
" <td>0.052630</td>\n",
" <td>0.019380</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.106000</td>\n",
" <td>0.049960</td>\n",
" <td>...</td>\n",
" <td>7.930000</td>\n",
" <td>12.020000</td>\n",
" <td>50.410000</td>\n",
" <td>185.200000</td>\n",
" <td>0.071170</td>\n",
" <td>0.027290</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.156500</td>\n",
" <td>0.055040</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>11.700000</td>\n",
" <td>16.170000</td>\n",
" <td>75.170000</td>\n",
" <td>420.300000</td>\n",
" <td>0.086370</td>\n",
" <td>0.064920</td>\n",
" <td>0.029560</td>\n",
" <td>0.020310</td>\n",
" <td>0.161900</td>\n",
" <td>0.057700</td>\n",
" <td>...</td>\n",
" <td>13.010000</td>\n",
" <td>21.080000</td>\n",
" <td>84.110000</td>\n",
" <td>515.300000</td>\n",
" <td>0.116600</td>\n",
" <td>0.147200</td>\n",
" <td>0.114500</td>\n",
" <td>0.064930</td>\n",
" <td>0.250400</td>\n",
" <td>0.071460</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>13.370000</td>\n",
" <td>18.840000</td>\n",
" <td>86.240000</td>\n",
" <td>551.100000</td>\n",
" <td>0.095870</td>\n",
" <td>0.092630</td>\n",
" <td>0.061540</td>\n",
" <td>0.033500</td>\n",
" <td>0.179200</td>\n",
" <td>0.061540</td>\n",
" <td>...</td>\n",
" <td>14.970000</td>\n",
" <td>25.410000</td>\n",
" <td>97.660000</td>\n",
" <td>686.500000</td>\n",
" <td>0.131300</td>\n",
" <td>0.211900</td>\n",
" <td>0.226700</td>\n",
" <td>0.099930</td>\n",
" <td>0.282200</td>\n",
" <td>0.080040</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>15.780000</td>\n",
" <td>21.800000</td>\n",
" <td>104.100000</td>\n",
" <td>782.700000</td>\n",
" <td>0.105300</td>\n",
" <td>0.130400</td>\n",
" <td>0.130700</td>\n",
" <td>0.074000</td>\n",
" <td>0.195700</td>\n",
" <td>0.066120</td>\n",
" <td>...</td>\n",
" <td>18.790000</td>\n",
" <td>29.720000</td>\n",
" <td>125.400000</td>\n",
" <td>1084.000000</td>\n",
" <td>0.146000</td>\n",
" <td>0.339100</td>\n",
" <td>0.382900</td>\n",
" <td>0.161400</td>\n",
" <td>0.317900</td>\n",
" <td>0.092080</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>28.110000</td>\n",
" <td>39.280000</td>\n",
" <td>188.500000</td>\n",
" <td>2501.000000</td>\n",
" <td>0.163400</td>\n",
" <td>0.345400</td>\n",
" <td>0.426800</td>\n",
" <td>0.201200</td>\n",
" <td>0.304000</td>\n",
" <td>0.097440</td>\n",
" <td>...</td>\n",
" <td>36.040000</td>\n",
" <td>49.540000</td>\n",
" <td>251.200000</td>\n",
" <td>4254.000000</td>\n",
" <td>0.222600</td>\n",
" <td>1.058000</td>\n",
" <td>1.252000</td>\n",
" <td>0.291000</td>\n",
" <td>0.663800</td>\n",
" <td>0.207500</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>8 rows × 30 columns</p>\n",
"</div>"
],
"text/plain": [
" 0 1 2 3 4 \\\n",
"count 569.000000 569.000000 569.000000 569.000000 569.000000 \n",
"mean 14.127292 19.289649 91.969033 654.889104 0.096360 \n",
"std 3.524049 4.301036 24.298981 351.914129 0.014064 \n",
"min 6.981000 9.710000 43.790000 143.500000 0.052630 \n",
"25% 11.700000 16.170000 75.170000 420.300000 0.086370 \n",
"50% 13.370000 18.840000 86.240000 551.100000 0.095870 \n",
"75% 15.780000 21.800000 104.100000 782.700000 0.105300 \n",
"max 28.110000 39.280000 188.500000 2501.000000 0.163400 \n",
"\n",
" 5 6 7 8 9 ... \\\n",
"count 569.000000 569.000000 569.000000 569.000000 569.000000 ... \n",
"mean 0.104341 0.088799 0.048919 0.181162 0.062798 ... \n",
"std 0.052813 0.079720 0.038803 0.027414 0.007060 ... \n",
"min 0.019380 0.000000 0.000000 0.106000 0.049960 ... \n",
"25% 0.064920 0.029560 0.020310 0.161900 0.057700 ... \n",
"50% 0.092630 0.061540 0.033500 0.179200 0.061540 ... \n",
"75% 0.130400 0.130700 0.074000 0.195700 0.066120 ... \n",
"max 0.345400 0.426800 0.201200 0.304000 0.097440 ... \n",
"\n",
" 20 21 22 23 24 \\\n",
"count 569.000000 569.000000 569.000000 569.000000 569.000000 \n",
"mean 16.269190 25.677223 107.261213 880.583128 0.132369 \n",
"std 4.833242 6.146258 33.602542 569.356993 0.022832 \n",
"min 7.930000 12.020000 50.410000 185.200000 0.071170 \n",
"25% 13.010000 21.080000 84.110000 515.300000 0.116600 \n",
"50% 14.970000 25.410000 97.660000 686.500000 0.131300 \n",
"75% 18.790000 29.720000 125.400000 1084.000000 0.146000 \n",
"max 36.040000 49.540000 251.200000 4254.000000 0.222600 \n",
"\n",
" 25 26 27 28 29 \n",
"count 569.000000 569.000000 569.000000 569.000000 569.000000 \n",
"mean 0.254265 0.272188 0.114606 0.290076 0.083946 \n",
"std 0.157336 0.208624 0.065732 0.061867 0.018061 \n",
"min 0.027290 0.000000 0.000000 0.156500 0.055040 \n",
"25% 0.147200 0.114500 0.064930 0.250400 0.071460 \n",
"50% 0.211900 0.226700 0.099930 0.282200 0.080040 \n",
"75% 0.339100 0.382900 0.161400 0.317900 0.092080 \n",
"max 1.058000 1.252000 0.291000 0.663800 0.207500 \n",
"\n",
"[8 rows x 30 columns]"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.describe()"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"df = pd.DataFrame(data.data, columns=data.feature_names)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
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" vertical-align: middle;\n",
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" 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>mean radius</th>\n",
" <th>mean texture</th>\n",
" <th>mean perimeter</th>\n",
" <th>mean area</th>\n",
" <th>mean smoothness</th>\n",
" <th>mean compactness</th>\n",
" <th>mean concavity</th>\n",
" <th>mean concave points</th>\n",
" <th>mean symmetry</th>\n",
" <th>mean fractal dimension</th>\n",
" <th>...</th>\n",
" <th>worst radius</th>\n",
" <th>worst texture</th>\n",
" <th>worst perimeter</th>\n",
" <th>worst area</th>\n",
" <th>worst smoothness</th>\n",
" <th>worst compactness</th>\n",
" <th>worst concavity</th>\n",
" <th>worst concave points</th>\n",
" <th>worst symmetry</th>\n",
" <th>worst fractal dimension</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>17.990</td>\n",
" <td>10.38</td>\n",
" <td>122.80</td>\n",
" <td>1001.0</td>\n",
" <td>0.11840</td>\n",
" <td>0.27760</td>\n",
" <td>0.300100</td>\n",
" <td>0.147100</td>\n",
" <td>0.2419</td>\n",
" <td>0.07871</td>\n",
" <td>...</td>\n",
" <td>25.380</td>\n",
" <td>17.33</td>\n",
" <td>184.60</td>\n",
" <td>2019.0</td>\n",
" <td>0.16220</td>\n",
" <td>0.66560</td>\n",
" <td>0.71190</td>\n",
" <td>0.26540</td>\n",
" <td>0.4601</td>\n",
" <td>0.11890</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>20.570</td>\n",
" <td>17.77</td>\n",
" <td>132.90</td>\n",
" <td>1326.0</td>\n",
" <td>0.08474</td>\n",
" <td>0.07864</td>\n",
" <td>0.086900</td>\n",
" <td>0.070170</td>\n",
" <td>0.1812</td>\n",
" <td>0.05667</td>\n",
" <td>...</td>\n",
" <td>24.990</td>\n",
" <td>23.41</td>\n",
" <td>158.80</td>\n",
" <td>1956.0</td>\n",
" <td>0.12380</td>\n",
" <td>0.18660</td>\n",
" <td>0.24160</td>\n",
" <td>0.18600</td>\n",
" <td>0.2750</td>\n",
" <td>0.08902</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>19.690</td>\n",
" <td>21.25</td>\n",
" <td>130.00</td>\n",
" <td>1203.0</td>\n",
" <td>0.10960</td>\n",
" <td>0.15990</td>\n",
" <td>0.197400</td>\n",
" <td>0.127900</td>\n",
" <td>0.2069</td>\n",
" <td>0.05999</td>\n",
" <td>...</td>\n",
" <td>23.570</td>\n",
" <td>25.53</td>\n",
" <td>152.50</td>\n",
" <td>1709.0</td>\n",
" <td>0.14440</td>\n",
" <td>0.42450</td>\n",
" <td>0.45040</td>\n",
" <td>0.24300</td>\n",
" <td>0.3613</td>\n",
" <td>0.08758</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>11.420</td>\n",
" <td>20.38</td>\n",
" <td>77.58</td>\n",
" <td>386.1</td>\n",
" <td>0.14250</td>\n",
" <td>0.28390</td>\n",
" <td>0.241400</td>\n",
" <td>0.105200</td>\n",
" <td>0.2597</td>\n",
" <td>0.09744</td>\n",
" <td>...</td>\n",
" <td>14.910</td>\n",
" <td>26.50</td>\n",
" <td>98.87</td>\n",
" <td>567.7</td>\n",
" <td>0.20980</td>\n",
" <td>0.86630</td>\n",
" <td>0.68690</td>\n",
" <td>0.25750</td>\n",
" <td>0.6638</td>\n",
" <td>0.17300</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>20.290</td>\n",
" <td>14.34</td>\n",
" <td>135.10</td>\n",
" <td>1297.0</td>\n",
" <td>0.10030</td>\n",
" <td>0.13280</td>\n",
" <td>0.198000</td>\n",
" <td>0.104300</td>\n",
" <td>0.1809</td>\n",
" <td>0.05883</td>\n",
" <td>...</td>\n",
" <td>22.540</td>\n",
" <td>16.67</td>\n",
" <td>152.20</td>\n",
" <td>1575.0</td>\n",
" <td>0.13740</td>\n",
" <td>0.20500</td>\n",
" <td>0.40000</td>\n",
" <td>0.16250</td>\n",
" <td>0.2364</td>\n",
" <td>0.07678</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>12.450</td>\n",
" <td>15.70</td>\n",
" <td>82.57</td>\n",
" <td>477.1</td>\n",
" <td>0.12780</td>\n",
" <td>0.17000</td>\n",
" <td>0.157800</td>\n",
" <td>0.080890</td>\n",
" <td>0.2087</td>\n",
" <td>0.07613</td>\n",
" <td>...</td>\n",
" <td>15.470</td>\n",
" <td>23.75</td>\n",
" <td>103.40</td>\n",
" <td>741.6</td>\n",
" <td>0.17910</td>\n",
" <td>0.52490</td>\n",
" <td>0.53550</td>\n",
" <td>0.17410</td>\n",
" <td>0.3985</td>\n",
" <td>0.12440</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>18.250</td>\n",
" <td>19.98</td>\n",
" <td>119.60</td>\n",
" <td>1040.0</td>\n",
" <td>0.09463</td>\n",
" <td>0.10900</td>\n",
" <td>0.112700</td>\n",
" <td>0.074000</td>\n",
" <td>0.1794</td>\n",
" <td>0.05742</td>\n",
" <td>...</td>\n",
" <td>22.880</td>\n",
" <td>27.66</td>\n",
" <td>153.20</td>\n",
" <td>1606.0</td>\n",
" <td>0.14420</td>\n",
" <td>0.25760</td>\n",
" <td>0.37840</td>\n",
" <td>0.19320</td>\n",
" <td>0.3063</td>\n",
" <td>0.08368</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>13.710</td>\n",
" <td>20.83</td>\n",
" <td>90.20</td>\n",
" <td>577.9</td>\n",
" <td>0.11890</td>\n",
" <td>0.16450</td>\n",
" <td>0.093660</td>\n",
" <td>0.059850</td>\n",
" <td>0.2196</td>\n",
" <td>0.07451</td>\n",
" <td>...</td>\n",
" <td>17.060</td>\n",
" <td>28.14</td>\n",
" <td>110.60</td>\n",
" <td>897.0</td>\n",
" <td>0.16540</td>\n",
" <td>0.36820</td>\n",
" <td>0.26780</td>\n",
" <td>0.15560</td>\n",
" <td>0.3196</td>\n",
" <td>0.11510</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>13.000</td>\n",
" <td>21.82</td>\n",
" <td>87.50</td>\n",
" <td>519.8</td>\n",
" <td>0.12730</td>\n",
" <td>0.19320</td>\n",
" <td>0.185900</td>\n",
" <td>0.093530</td>\n",
" <td>0.2350</td>\n",
" <td>0.07389</td>\n",
" <td>...</td>\n",
" <td>15.490</td>\n",
" <td>30.73</td>\n",
" <td>106.20</td>\n",
" <td>739.3</td>\n",
" <td>0.17030</td>\n",
" <td>0.54010</td>\n",
" <td>0.53900</td>\n",
" <td>0.20600</td>\n",
" <td>0.4378</td>\n",
" <td>0.10720</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>12.460</td>\n",
" <td>24.04</td>\n",
" <td>83.97</td>\n",
" <td>475.9</td>\n",
" <td>0.11860</td>\n",
" <td>0.23960</td>\n",
" <td>0.227300</td>\n",
" <td>0.085430</td>\n",
" <td>0.2030</td>\n",
" <td>0.08243</td>\n",
" <td>...</td>\n",
" <td>15.090</td>\n",
" <td>40.68</td>\n",
" <td>97.65</td>\n",
" <td>711.4</td>\n",
" <td>0.18530</td>\n",
" <td>1.05800</td>\n",
" <td>1.10500</td>\n",
" <td>0.22100</td>\n",
" <td>0.4366</td>\n",
" <td>0.20750</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>16.020</td>\n",
" <td>23.24</td>\n",
" <td>102.70</td>\n",
" <td>797.8</td>\n",
" <td>0.08206</td>\n",
" <td>0.06669</td>\n",
" <td>0.032990</td>\n",
" <td>0.033230</td>\n",
" <td>0.1528</td>\n",
" <td>0.05697</td>\n",
" <td>...</td>\n",
" <td>19.190</td>\n",
" <td>33.88</td>\n",
" <td>123.80</td>\n",
" <td>1150.0</td>\n",
" <td>0.11810</td>\n",
" <td>0.15510</td>\n",
" <td>0.14590</td>\n",
" <td>0.09975</td>\n",
" <td>0.2948</td>\n",
" <td>0.08452</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>15.780</td>\n",
" <td>17.89</td>\n",
" <td>103.60</td>\n",
" <td>781.0</td>\n",
" <td>0.09710</td>\n",
" <td>0.12920</td>\n",
" <td>0.099540</td>\n",
" <td>0.066060</td>\n",
" <td>0.1842</td>\n",
" <td>0.06082</td>\n",
" <td>...</td>\n",
" <td>20.420</td>\n",
" <td>27.28</td>\n",
" <td>136.50</td>\n",
" <td>1299.0</td>\n",
" <td>0.13960</td>\n",
" <td>0.56090</td>\n",
" <td>0.39650</td>\n",
" <td>0.18100</td>\n",
" <td>0.3792</td>\n",
" <td>0.10480</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>19.170</td>\n",
" <td>24.80</td>\n",
" <td>132.40</td>\n",
" <td>1123.0</td>\n",
" <td>0.09740</td>\n",
" <td>0.24580</td>\n",
" <td>0.206500</td>\n",
" <td>0.111800</td>\n",
" <td>0.2397</td>\n",
" <td>0.07800</td>\n",
" <td>...</td>\n",
" <td>20.960</td>\n",
" <td>29.94</td>\n",
" <td>151.70</td>\n",
" <td>1332.0</td>\n",
" <td>0.10370</td>\n",
" <td>0.39030</td>\n",
" <td>0.36390</td>\n",
" <td>0.17670</td>\n",
" <td>0.3176</td>\n",
" <td>0.10230</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>15.850</td>\n",
" <td>23.95</td>\n",
" <td>103.70</td>\n",
" <td>782.7</td>\n",
" <td>0.08401</td>\n",
" <td>0.10020</td>\n",
" <td>0.099380</td>\n",
" <td>0.053640</td>\n",
" <td>0.1847</td>\n",
" <td>0.05338</td>\n",
" <td>...</td>\n",
" <td>16.840</td>\n",
" <td>27.66</td>\n",
" <td>112.00</td>\n",
" <td>876.5</td>\n",
" <td>0.11310</td>\n",
" <td>0.19240</td>\n",
" <td>0.23220</td>\n",
" <td>0.11190</td>\n",
" <td>0.2809</td>\n",
" <td>0.06287</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>13.730</td>\n",
" <td>22.61</td>\n",
" <td>93.60</td>\n",
" <td>578.3</td>\n",
" <td>0.11310</td>\n",
" <td>0.22930</td>\n",
" <td>0.212800</td>\n",
" <td>0.080250</td>\n",
" <td>0.2069</td>\n",
" <td>0.07682</td>\n",
" <td>...</td>\n",
" <td>15.030</td>\n",
" <td>32.01</td>\n",
" <td>108.80</td>\n",
" <td>697.7</td>\n",
" <td>0.16510</td>\n",
" <td>0.77250</td>\n",
" <td>0.69430</td>\n",
" <td>0.22080</td>\n",
" <td>0.3596</td>\n",
" <td>0.14310</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>14.540</td>\n",
" <td>27.54</td>\n",
" <td>96.73</td>\n",
" <td>658.8</td>\n",
" <td>0.11390</td>\n",
" <td>0.15950</td>\n",
" <td>0.163900</td>\n",
" <td>0.073640</td>\n",
" <td>0.2303</td>\n",
" <td>0.07077</td>\n",
" <td>...</td>\n",
" <td>17.460</td>\n",
" <td>37.13</td>\n",
" <td>124.10</td>\n",
" <td>943.2</td>\n",
" <td>0.16780</td>\n",
" <td>0.65770</td>\n",
" <td>0.70260</td>\n",
" <td>0.17120</td>\n",
" <td>0.4218</td>\n",
" <td>0.13410</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>14.680</td>\n",
" <td>20.13</td>\n",
" <td>94.74</td>\n",
" <td>684.5</td>\n",
" <td>0.09867</td>\n",
" <td>0.07200</td>\n",
" <td>0.073950</td>\n",
" <td>0.052590</td>\n",
" <td>0.1586</td>\n",
" <td>0.05922</td>\n",
" <td>...</td>\n",
" <td>19.070</td>\n",
" <td>30.88</td>\n",
" <td>123.40</td>\n",
" <td>1138.0</td>\n",
" <td>0.14640</td>\n",
" <td>0.18710</td>\n",
" <td>0.29140</td>\n",
" <td>0.16090</td>\n",
" <td>0.3029</td>\n",
" <td>0.08216</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>16.130</td>\n",
" <td>20.68</td>\n",
" <td>108.10</td>\n",
" <td>798.8</td>\n",
" <td>0.11700</td>\n",
" <td>0.20220</td>\n",
" <td>0.172200</td>\n",
" <td>0.102800</td>\n",
" <td>0.2164</td>\n",
" <td>0.07356</td>\n",
" <td>...</td>\n",
" <td>20.960</td>\n",
" <td>31.48</td>\n",
" <td>136.80</td>\n",
" <td>1315.0</td>\n",
" <td>0.17890</td>\n",
" <td>0.42330</td>\n",
" <td>0.47840</td>\n",
" <td>0.20730</td>\n",
" <td>0.3706</td>\n",
" <td>0.11420</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>19.810</td>\n",
" <td>22.15</td>\n",
" <td>130.00</td>\n",
" <td>1260.0</td>\n",
" <td>0.09831</td>\n",
" <td>0.10270</td>\n",
" <td>0.147900</td>\n",
" <td>0.094980</td>\n",
" <td>0.1582</td>\n",
" <td>0.05395</td>\n",
" <td>...</td>\n",
" <td>27.320</td>\n",
" <td>30.88</td>\n",
" <td>186.80</td>\n",
" <td>2398.0</td>\n",
" <td>0.15120</td>\n",
" <td>0.31500</td>\n",
" <td>0.53720</td>\n",
" <td>0.23880</td>\n",
" <td>0.2768</td>\n",
" <td>0.07615</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>13.540</td>\n",
" <td>14.36</td>\n",
" <td>87.46</td>\n",
" <td>566.3</td>\n",
" <td>0.09779</td>\n",
" <td>0.08129</td>\n",
" <td>0.066640</td>\n",
" <td>0.047810</td>\n",
" <td>0.1885</td>\n",
" <td>0.05766</td>\n",
" <td>...</td>\n",
" <td>15.110</td>\n",
" <td>19.26</td>\n",
" <td>99.70</td>\n",
" <td>711.2</td>\n",
" <td>0.14400</td>\n",
" <td>0.17730</td>\n",
" <td>0.23900</td>\n",
" <td>0.12880</td>\n",
" <td>0.2977</td>\n",
" <td>0.07259</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>13.080</td>\n",
" <td>15.71</td>\n",
" <td>85.63</td>\n",
" <td>520.0</td>\n",
" <td>0.10750</td>\n",
" <td>0.12700</td>\n",
" <td>0.045680</td>\n",
" <td>0.031100</td>\n",
" <td>0.1967</td>\n",
" <td>0.06811</td>\n",
" <td>...</td>\n",
" <td>14.500</td>\n",
" <td>20.49</td>\n",
" <td>96.09</td>\n",
" <td>630.5</td>\n",
" <td>0.13120</td>\n",
" <td>0.27760</td>\n",
" <td>0.18900</td>\n",
" <td>0.07283</td>\n",
" <td>0.3184</td>\n",
" <td>0.08183</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>9.504</td>\n",
" <td>12.44</td>\n",
" <td>60.34</td>\n",
" <td>273.9</td>\n",
" <td>0.10240</td>\n",
" <td>0.06492</td>\n",
" <td>0.029560</td>\n",
" <td>0.020760</td>\n",
" <td>0.1815</td>\n",
" <td>0.06905</td>\n",
" <td>...</td>\n",
" <td>10.230</td>\n",
" <td>15.66</td>\n",
" <td>65.13</td>\n",
" <td>314.9</td>\n",
" <td>0.13240</td>\n",
" <td>0.11480</td>\n",
" <td>0.08867</td>\n",
" <td>0.06227</td>\n",
" <td>0.2450</td>\n",
" <td>0.07773</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>15.340</td>\n",
" <td>14.26</td>\n",
" <td>102.50</td>\n",
" <td>704.4</td>\n",
" <td>0.10730</td>\n",
" <td>0.21350</td>\n",
" <td>0.207700</td>\n",
" <td>0.097560</td>\n",
" <td>0.2521</td>\n",
" <td>0.07032</td>\n",
" <td>...</td>\n",
" <td>18.070</td>\n",
" <td>19.08</td>\n",
" <td>125.10</td>\n",
" <td>980.9</td>\n",
" <td>0.13900</td>\n",
" <td>0.59540</td>\n",
" <td>0.63050</td>\n",
" <td>0.23930</td>\n",
" <td>0.4667</td>\n",
" <td>0.09946</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>21.160</td>\n",
" <td>23.04</td>\n",
" <td>137.20</td>\n",
" <td>1404.0</td>\n",
" <td>0.09428</td>\n",
" <td>0.10220</td>\n",
" <td>0.109700</td>\n",
" <td>0.086320</td>\n",
" <td>0.1769</td>\n",
" <td>0.05278</td>\n",
" <td>...</td>\n",
" <td>29.170</td>\n",
" <td>35.59</td>\n",
" <td>188.00</td>\n",
" <td>2615.0</td>\n",
" <td>0.14010</td>\n",
" <td>0.26000</td>\n",
" <td>0.31550</td>\n",
" <td>0.20090</td>\n",
" <td>0.2822</td>\n",
" <td>0.07526</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>16.650</td>\n",
" <td>21.38</td>\n",
" <td>110.00</td>\n",
" <td>904.6</td>\n",
" <td>0.11210</td>\n",
" <td>0.14570</td>\n",
" <td>0.152500</td>\n",
" <td>0.091700</td>\n",
" <td>0.1995</td>\n",
" <td>0.06330</td>\n",
" <td>...</td>\n",
" <td>26.460</td>\n",
" <td>31.56</td>\n",
" <td>177.00</td>\n",
" <td>2215.0</td>\n",
" <td>0.18050</td>\n",
" <td>0.35780</td>\n",
" <td>0.46950</td>\n",
" <td>0.20950</td>\n",
" <td>0.3613</td>\n",
" <td>0.09564</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>17.140</td>\n",
" <td>16.40</td>\n",
" <td>116.00</td>\n",
" <td>912.7</td>\n",
" <td>0.11860</td>\n",
" <td>0.22760</td>\n",
" <td>0.222900</td>\n",
" <td>0.140100</td>\n",
" <td>0.3040</td>\n",
" <td>0.07413</td>\n",
" <td>...</td>\n",
" <td>22.250</td>\n",
" <td>21.40</td>\n",
" <td>152.40</td>\n",
" <td>1461.0</td>\n",
" <td>0.15450</td>\n",
" <td>0.39490</td>\n",
" <td>0.38530</td>\n",
" <td>0.25500</td>\n",
" <td>0.4066</td>\n",
" <td>0.10590</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>14.580</td>\n",
" <td>21.53</td>\n",
" <td>97.41</td>\n",
" <td>644.8</td>\n",
" <td>0.10540</td>\n",
" <td>0.18680</td>\n",
" <td>0.142500</td>\n",
" <td>0.087830</td>\n",
" <td>0.2252</td>\n",
" <td>0.06924</td>\n",
" <td>...</td>\n",
" <td>17.620</td>\n",
" <td>33.21</td>\n",
" <td>122.40</td>\n",
" <td>896.9</td>\n",
" <td>0.15250</td>\n",
" <td>0.66430</td>\n",
" <td>0.55390</td>\n",
" <td>0.27010</td>\n",
" <td>0.4264</td>\n",
" <td>0.12750</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>18.610</td>\n",
" <td>20.25</td>\n",
" <td>122.10</td>\n",
" <td>1094.0</td>\n",
" <td>0.09440</td>\n",
" <td>0.10660</td>\n",
" <td>0.149000</td>\n",
" <td>0.077310</td>\n",
" <td>0.1697</td>\n",
" <td>0.05699</td>\n",
" <td>...</td>\n",
" <td>21.310</td>\n",
" <td>27.26</td>\n",
" <td>139.90</td>\n",
" <td>1403.0</td>\n",
" <td>0.13380</td>\n",
" <td>0.21170</td>\n",
" <td>0.34460</td>\n",
" <td>0.14900</td>\n",
" <td>0.2341</td>\n",
" <td>0.07421</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>15.300</td>\n",
" <td>25.27</td>\n",
" <td>102.40</td>\n",
" <td>732.4</td>\n",
" <td>0.10820</td>\n",
" <td>0.16970</td>\n",
" <td>0.168300</td>\n",
" <td>0.087510</td>\n",
" <td>0.1926</td>\n",
" <td>0.06540</td>\n",
" <td>...</td>\n",
" <td>20.270</td>\n",
" <td>36.71</td>\n",
" <td>149.30</td>\n",
" <td>1269.0</td>\n",
" <td>0.16410</td>\n",
" <td>0.61100</td>\n",
" <td>0.63350</td>\n",
" <td>0.20240</td>\n",
" <td>0.4027</td>\n",
" <td>0.09876</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>17.570</td>\n",
" <td>15.05</td>\n",
" <td>115.00</td>\n",
" <td>955.1</td>\n",
" <td>0.09847</td>\n",
" <td>0.11570</td>\n",
" <td>0.098750</td>\n",
" <td>0.079530</td>\n",
" <td>0.1739</td>\n",
" <td>0.06149</td>\n",
" <td>...</td>\n",
" <td>20.010</td>\n",
" <td>19.52</td>\n",
" <td>134.90</td>\n",
" <td>1227.0</td>\n",
" <td>0.12550</td>\n",
" <td>0.28120</td>\n",
" <td>0.24890</td>\n",
" <td>0.14560</td>\n",
" <td>0.2756</td>\n",
" <td>0.07919</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>539</th>\n",
" <td>7.691</td>\n",
" <td>25.44</td>\n",
" <td>48.34</td>\n",
" <td>170.4</td>\n",
" <td>0.08668</td>\n",
" <td>0.11990</td>\n",
" <td>0.092520</td>\n",
" <td>0.013640</td>\n",
" <td>0.2037</td>\n",
" <td>0.07751</td>\n",
" <td>...</td>\n",
" <td>8.678</td>\n",
" <td>31.89</td>\n",
" <td>54.49</td>\n",
" <td>223.6</td>\n",
" <td>0.15960</td>\n",
" <td>0.30640</td>\n",
" <td>0.33930</td>\n",
" <td>0.05000</td>\n",
" <td>0.2790</td>\n",
" <td>0.10660</td>\n",
" </tr>\n",
" <tr>\n",
" <th>540</th>\n",
" <td>11.540</td>\n",
" <td>14.44</td>\n",
" <td>74.65</td>\n",
" <td>402.9</td>\n",
" <td>0.09984</td>\n",
" <td>0.11200</td>\n",
" <td>0.067370</td>\n",
" <td>0.025940</td>\n",
" <td>0.1818</td>\n",
" <td>0.06782</td>\n",
" <td>...</td>\n",
" <td>12.260</td>\n",
" <td>19.68</td>\n",
" <td>78.78</td>\n",
" <td>457.8</td>\n",
" <td>0.13450</td>\n",
" <td>0.21180</td>\n",
" <td>0.17970</td>\n",
" <td>0.06918</td>\n",
" <td>0.2329</td>\n",
" <td>0.08134</td>\n",
" </tr>\n",
" <tr>\n",
" <th>541</th>\n",
" <td>14.470</td>\n",
" <td>24.99</td>\n",
" <td>95.81</td>\n",
" <td>656.4</td>\n",
" <td>0.08837</td>\n",
" <td>0.12300</td>\n",
" <td>0.100900</td>\n",
" <td>0.038900</td>\n",
" <td>0.1872</td>\n",
" <td>0.06341</td>\n",
" <td>...</td>\n",
" <td>16.220</td>\n",
" <td>31.73</td>\n",
" <td>113.50</td>\n",
" <td>808.9</td>\n",
" <td>0.13400</td>\n",
" <td>0.42020</td>\n",
" <td>0.40400</td>\n",
" <td>0.12050</td>\n",
" <td>0.3187</td>\n",
" <td>0.10230</td>\n",
" </tr>\n",
" <tr>\n",
" <th>542</th>\n",
" <td>14.740</td>\n",
" <td>25.42</td>\n",
" <td>94.70</td>\n",
" <td>668.6</td>\n",
" <td>0.08275</td>\n",
" <td>0.07214</td>\n",
" <td>0.041050</td>\n",
" <td>0.030270</td>\n",
" <td>0.1840</td>\n",
" <td>0.05680</td>\n",
" <td>...</td>\n",
" <td>16.510</td>\n",
" <td>32.29</td>\n",
" <td>107.40</td>\n",
" <td>826.4</td>\n",
" <td>0.10600</td>\n",
" <td>0.13760</td>\n",
" <td>0.16110</td>\n",
" <td>0.10950</td>\n",
" <td>0.2722</td>\n",
" <td>0.06956</td>\n",
" </tr>\n",
" <tr>\n",
" <th>543</th>\n",
" <td>13.210</td>\n",
" <td>28.06</td>\n",
" <td>84.88</td>\n",
" <td>538.4</td>\n",
" <td>0.08671</td>\n",
" <td>0.06877</td>\n",
" <td>0.029870</td>\n",
" <td>0.032750</td>\n",
" <td>0.1628</td>\n",
" <td>0.05781</td>\n",
" <td>...</td>\n",
" <td>14.370</td>\n",
" <td>37.17</td>\n",
" <td>92.48</td>\n",
" <td>629.6</td>\n",
" <td>0.10720</td>\n",
" <td>0.13810</td>\n",
" <td>0.10620</td>\n",
" <td>0.07958</td>\n",
" <td>0.2473</td>\n",
" <td>0.06443</td>\n",
" </tr>\n",
" <tr>\n",
" <th>544</th>\n",
" <td>13.870</td>\n",
" <td>20.70</td>\n",
" <td>89.77</td>\n",
" <td>584.8</td>\n",
" <td>0.09578</td>\n",
" <td>0.10180</td>\n",
" <td>0.036880</td>\n",
" <td>0.023690</td>\n",
" <td>0.1620</td>\n",
" <td>0.06688</td>\n",
" <td>...</td>\n",
" <td>15.050</td>\n",
" <td>24.75</td>\n",
" <td>99.17</td>\n",
" <td>688.6</td>\n",
" <td>0.12640</td>\n",
" <td>0.20370</td>\n",
" <td>0.13770</td>\n",
" <td>0.06845</td>\n",
" <td>0.2249</td>\n",
" <td>0.08492</td>\n",
" </tr>\n",
" <tr>\n",
" <th>545</th>\n",
" <td>13.620</td>\n",
" <td>23.23</td>\n",
" <td>87.19</td>\n",
" <td>573.2</td>\n",
" <td>0.09246</td>\n",
" <td>0.06747</td>\n",
" <td>0.029740</td>\n",
" <td>0.024430</td>\n",
" <td>0.1664</td>\n",
" <td>0.05801</td>\n",
" <td>...</td>\n",
" <td>15.350</td>\n",
" <td>29.09</td>\n",
" <td>97.58</td>\n",
" <td>729.8</td>\n",
" <td>0.12160</td>\n",
" <td>0.15170</td>\n",
" <td>0.10490</td>\n",
" <td>0.07174</td>\n",
" <td>0.2642</td>\n",
" <td>0.06953</td>\n",
" </tr>\n",
" <tr>\n",
" <th>546</th>\n",
" <td>10.320</td>\n",
" <td>16.35</td>\n",
" <td>65.31</td>\n",
" <td>324.9</td>\n",
" <td>0.09434</td>\n",
" <td>0.04994</td>\n",
" <td>0.010120</td>\n",
" <td>0.005495</td>\n",
" <td>0.1885</td>\n",
" <td>0.06201</td>\n",
" <td>...</td>\n",
" <td>11.250</td>\n",
" <td>21.77</td>\n",
" <td>71.12</td>\n",
" <td>384.9</td>\n",
" <td>0.12850</td>\n",
" <td>0.08842</td>\n",
" <td>0.04384</td>\n",
" <td>0.02381</td>\n",
" <td>0.2681</td>\n",
" <td>0.07399</td>\n",
" </tr>\n",
" <tr>\n",
" <th>547</th>\n",
" <td>10.260</td>\n",
" <td>16.58</td>\n",
" <td>65.85</td>\n",
" <td>320.8</td>\n",
" <td>0.08877</td>\n",
" <td>0.08066</td>\n",
" <td>0.043580</td>\n",
" <td>0.024380</td>\n",
" <td>0.1669</td>\n",
" <td>0.06714</td>\n",
" <td>...</td>\n",
" <td>10.830</td>\n",
" <td>22.04</td>\n",
" <td>71.08</td>\n",
" <td>357.4</td>\n",
" <td>0.14610</td>\n",
" <td>0.22460</td>\n",
" <td>0.17830</td>\n",
" <td>0.08333</td>\n",
" <td>0.2691</td>\n",
" <td>0.09479</td>\n",
" </tr>\n",
" <tr>\n",
" <th>548</th>\n",
" <td>9.683</td>\n",
" <td>19.34</td>\n",
" <td>61.05</td>\n",
" <td>285.7</td>\n",
" <td>0.08491</td>\n",
" <td>0.05030</td>\n",
" <td>0.023370</td>\n",
" <td>0.009615</td>\n",
" <td>0.1580</td>\n",
" <td>0.06235</td>\n",
" <td>...</td>\n",
" <td>10.930</td>\n",
" <td>25.59</td>\n",
" <td>69.10</td>\n",
" <td>364.2</td>\n",
" <td>0.11990</td>\n",
" <td>0.09546</td>\n",
" <td>0.09350</td>\n",
" <td>0.03846</td>\n",
" <td>0.2552</td>\n",
" <td>0.07920</td>\n",
" </tr>\n",
" <tr>\n",
" <th>549</th>\n",
" <td>10.820</td>\n",
" <td>24.21</td>\n",
" <td>68.89</td>\n",
" <td>361.6</td>\n",
" <td>0.08192</td>\n",
" <td>0.06602</td>\n",
" <td>0.015480</td>\n",
" <td>0.008160</td>\n",
" <td>0.1976</td>\n",
" <td>0.06328</td>\n",
" <td>...</td>\n",
" <td>13.030</td>\n",
" <td>31.45</td>\n",
" <td>83.90</td>\n",
" <td>505.6</td>\n",
" <td>0.12040</td>\n",
" <td>0.16330</td>\n",
" <td>0.06194</td>\n",
" <td>0.03264</td>\n",
" <td>0.3059</td>\n",
" <td>0.07626</td>\n",
" </tr>\n",
" <tr>\n",
" <th>550</th>\n",
" <td>10.860</td>\n",
" <td>21.48</td>\n",
" <td>68.51</td>\n",
" <td>360.5</td>\n",
" <td>0.07431</td>\n",
" <td>0.04227</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.1661</td>\n",
" <td>0.05948</td>\n",
" <td>...</td>\n",
" <td>11.660</td>\n",
" <td>24.77</td>\n",
" <td>74.08</td>\n",
" <td>412.3</td>\n",
" <td>0.10010</td>\n",
" <td>0.07348</td>\n",
" <td>0.00000</td>\n",
" <td>0.00000</td>\n",
" <td>0.2458</td>\n",
" <td>0.06592</td>\n",
" </tr>\n",
" <tr>\n",
" <th>551</th>\n",
" <td>11.130</td>\n",
" <td>22.44</td>\n",
" <td>71.49</td>\n",
" <td>378.4</td>\n",
" <td>0.09566</td>\n",
" <td>0.08194</td>\n",
" <td>0.048240</td>\n",
" <td>0.022570</td>\n",
" <td>0.2030</td>\n",
" <td>0.06552</td>\n",
" <td>...</td>\n",
" <td>12.020</td>\n",
" <td>28.26</td>\n",
" <td>77.80</td>\n",
" <td>436.6</td>\n",
" <td>0.10870</td>\n",
" <td>0.17820</td>\n",
" <td>0.15640</td>\n",
" <td>0.06413</td>\n",
" <td>0.3169</td>\n",
" <td>0.08032</td>\n",
" </tr>\n",
" <tr>\n",
" <th>552</th>\n",
" <td>12.770</td>\n",
" <td>29.43</td>\n",
" <td>81.35</td>\n",
" <td>507.9</td>\n",
" <td>0.08276</td>\n",
" <td>0.04234</td>\n",
" <td>0.019970</td>\n",
" <td>0.014990</td>\n",
" <td>0.1539</td>\n",
" <td>0.05637</td>\n",
" <td>...</td>\n",
" <td>13.870</td>\n",
" <td>36.00</td>\n",
" <td>88.10</td>\n",
" <td>594.7</td>\n",
" <td>0.12340</td>\n",
" <td>0.10640</td>\n",
" <td>0.08653</td>\n",
" <td>0.06498</td>\n",
" <td>0.2407</td>\n",
" <td>0.06484</td>\n",
" </tr>\n",
" <tr>\n",
" <th>553</th>\n",
" <td>9.333</td>\n",
" <td>21.94</td>\n",
" <td>59.01</td>\n",
" <td>264.0</td>\n",
" <td>0.09240</td>\n",
" <td>0.05605</td>\n",
" <td>0.039960</td>\n",
" <td>0.012820</td>\n",
" <td>0.1692</td>\n",
" <td>0.06576</td>\n",
" <td>...</td>\n",
" <td>9.845</td>\n",
" <td>25.05</td>\n",
" <td>62.86</td>\n",
" <td>295.8</td>\n",
" <td>0.11030</td>\n",
" <td>0.08298</td>\n",
" <td>0.07993</td>\n",
" <td>0.02564</td>\n",
" <td>0.2435</td>\n",
" <td>0.07393</td>\n",
" </tr>\n",
" <tr>\n",
" <th>554</th>\n",
" <td>12.880</td>\n",
" <td>28.92</td>\n",
" <td>82.50</td>\n",
" <td>514.3</td>\n",
" <td>0.08123</td>\n",
" <td>0.05824</td>\n",
" <td>0.061950</td>\n",
" <td>0.023430</td>\n",
" <td>0.1566</td>\n",
" <td>0.05708</td>\n",
" <td>...</td>\n",
" <td>13.890</td>\n",
" <td>35.74</td>\n",
" <td>88.84</td>\n",
" <td>595.7</td>\n",
" <td>0.12270</td>\n",
" <td>0.16200</td>\n",
" <td>0.24390</td>\n",
" <td>0.06493</td>\n",
" <td>0.2372</td>\n",
" <td>0.07242</td>\n",
" </tr>\n",
" <tr>\n",
" <th>555</th>\n",
" <td>10.290</td>\n",
" <td>27.61</td>\n",
" <td>65.67</td>\n",
" <td>321.4</td>\n",
" <td>0.09030</td>\n",
" <td>0.07658</td>\n",
" <td>0.059990</td>\n",
" <td>0.027380</td>\n",
" <td>0.1593</td>\n",
" <td>0.06127</td>\n",
" <td>...</td>\n",
" <td>10.840</td>\n",
" <td>34.91</td>\n",
" <td>69.57</td>\n",
" <td>357.6</td>\n",
" <td>0.13840</td>\n",
" <td>0.17100</td>\n",
" <td>0.20000</td>\n",
" <td>0.09127</td>\n",
" <td>0.2226</td>\n",
" <td>0.08283</td>\n",
" </tr>\n",
" <tr>\n",
" <th>556</th>\n",
" <td>10.160</td>\n",
" <td>19.59</td>\n",
" <td>64.73</td>\n",
" <td>311.7</td>\n",
" <td>0.10030</td>\n",
" <td>0.07504</td>\n",
" <td>0.005025</td>\n",
" <td>0.011160</td>\n",
" <td>0.1791</td>\n",
" <td>0.06331</td>\n",
" <td>...</td>\n",
" <td>10.650</td>\n",
" <td>22.88</td>\n",
" <td>67.88</td>\n",
" <td>347.3</td>\n",
" <td>0.12650</td>\n",
" <td>0.12000</td>\n",
" <td>0.01005</td>\n",
" <td>0.02232</td>\n",
" <td>0.2262</td>\n",
" <td>0.06742</td>\n",
" </tr>\n",
" <tr>\n",
" <th>557</th>\n",
" <td>9.423</td>\n",
" <td>27.88</td>\n",
" <td>59.26</td>\n",
" <td>271.3</td>\n",
" <td>0.08123</td>\n",
" <td>0.04971</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.1742</td>\n",
" <td>0.06059</td>\n",
" <td>...</td>\n",
" <td>10.490</td>\n",
" <td>34.24</td>\n",
" <td>66.50</td>\n",
" <td>330.6</td>\n",
" <td>0.10730</td>\n",
" <td>0.07158</td>\n",
" <td>0.00000</td>\n",
" <td>0.00000</td>\n",
" <td>0.2475</td>\n",
" <td>0.06969</td>\n",
" </tr>\n",
" <tr>\n",
" <th>558</th>\n",
" <td>14.590</td>\n",
" <td>22.68</td>\n",
" <td>96.39</td>\n",
" <td>657.1</td>\n",
" <td>0.08473</td>\n",
" <td>0.13300</td>\n",
" <td>0.102900</td>\n",
" <td>0.037360</td>\n",
" <td>0.1454</td>\n",
" <td>0.06147</td>\n",
" <td>...</td>\n",
" <td>15.480</td>\n",
" <td>27.27</td>\n",
" <td>105.90</td>\n",
" <td>733.5</td>\n",
" <td>0.10260</td>\n",
" <td>0.31710</td>\n",
" <td>0.36620</td>\n",
" <td>0.11050</td>\n",
" <td>0.2258</td>\n",
" <td>0.08004</td>\n",
" </tr>\n",
" <tr>\n",
" <th>559</th>\n",
" <td>11.510</td>\n",
" <td>23.93</td>\n",
" <td>74.52</td>\n",
" <td>403.5</td>\n",
" <td>0.09261</td>\n",
" <td>0.10210</td>\n",
" <td>0.111200</td>\n",
" <td>0.041050</td>\n",
" <td>0.1388</td>\n",
" <td>0.06570</td>\n",
" <td>...</td>\n",
" <td>12.480</td>\n",
" <td>37.16</td>\n",
" <td>82.28</td>\n",
" <td>474.2</td>\n",
" <td>0.12980</td>\n",
" <td>0.25170</td>\n",
" <td>0.36300</td>\n",
" <td>0.09653</td>\n",
" <td>0.2112</td>\n",
" <td>0.08732</td>\n",
" </tr>\n",
" <tr>\n",
" <th>560</th>\n",
" <td>14.050</td>\n",
" <td>27.15</td>\n",
" <td>91.38</td>\n",
" <td>600.4</td>\n",
" <td>0.09929</td>\n",
" <td>0.11260</td>\n",
" <td>0.044620</td>\n",
" <td>0.043040</td>\n",
" <td>0.1537</td>\n",
" <td>0.06171</td>\n",
" <td>...</td>\n",
" <td>15.300</td>\n",
" <td>33.17</td>\n",
" <td>100.20</td>\n",
" <td>706.7</td>\n",
" <td>0.12410</td>\n",
" <td>0.22640</td>\n",
" <td>0.13260</td>\n",
" <td>0.10480</td>\n",
" <td>0.2250</td>\n",
" <td>0.08321</td>\n",
" </tr>\n",
" <tr>\n",
" <th>561</th>\n",
" <td>11.200</td>\n",
" <td>29.37</td>\n",
" <td>70.67</td>\n",
" <td>386.0</td>\n",
" <td>0.07449</td>\n",
" <td>0.03558</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.1060</td>\n",
" <td>0.05502</td>\n",
" <td>...</td>\n",
" <td>11.920</td>\n",
" <td>38.30</td>\n",
" <td>75.19</td>\n",
" <td>439.6</td>\n",
" <td>0.09267</td>\n",
" <td>0.05494</td>\n",
" <td>0.00000</td>\n",
" <td>0.00000</td>\n",
" <td>0.1566</td>\n",
" <td>0.05905</td>\n",
" </tr>\n",
" <tr>\n",
" <th>562</th>\n",
" <td>15.220</td>\n",
" <td>30.62</td>\n",
" <td>103.40</td>\n",
" <td>716.9</td>\n",
" <td>0.10480</td>\n",
" <td>0.20870</td>\n",
" <td>0.255000</td>\n",
" <td>0.094290</td>\n",
" <td>0.2128</td>\n",
" <td>0.07152</td>\n",
" <td>...</td>\n",
" <td>17.520</td>\n",
" <td>42.79</td>\n",
" <td>128.70</td>\n",
" <td>915.0</td>\n",
" <td>0.14170</td>\n",
" <td>0.79170</td>\n",
" <td>1.17000</td>\n",
" <td>0.23560</td>\n",
" <td>0.4089</td>\n",
" <td>0.14090</td>\n",
" </tr>\n",
" <tr>\n",
" <th>563</th>\n",
" <td>20.920</td>\n",
" <td>25.09</td>\n",
" <td>143.00</td>\n",
" <td>1347.0</td>\n",
" <td>0.10990</td>\n",
" <td>0.22360</td>\n",
" <td>0.317400</td>\n",
" <td>0.147400</td>\n",
" <td>0.2149</td>\n",
" <td>0.06879</td>\n",
" <td>...</td>\n",
" <td>24.290</td>\n",
" <td>29.41</td>\n",
" <td>179.10</td>\n",
" <td>1819.0</td>\n",
" <td>0.14070</td>\n",
" <td>0.41860</td>\n",
" <td>0.65990</td>\n",
" <td>0.25420</td>\n",
" <td>0.2929</td>\n",
" <td>0.09873</td>\n",
" </tr>\n",
" <tr>\n",
" <th>564</th>\n",
" <td>21.560</td>\n",
" <td>22.39</td>\n",
" <td>142.00</td>\n",
" <td>1479.0</td>\n",
" <td>0.11100</td>\n",
" <td>0.11590</td>\n",
" <td>0.243900</td>\n",
" <td>0.138900</td>\n",
" <td>0.1726</td>\n",
" <td>0.05623</td>\n",
" <td>...</td>\n",
" <td>25.450</td>\n",
" <td>26.40</td>\n",
" <td>166.10</td>\n",
" <td>2027.0</td>\n",
" <td>0.14100</td>\n",
" <td>0.21130</td>\n",
" <td>0.41070</td>\n",
" <td>0.22160</td>\n",
" <td>0.2060</td>\n",
" <td>0.07115</td>\n",
" </tr>\n",
" <tr>\n",
" <th>565</th>\n",
" <td>20.130</td>\n",
" <td>28.25</td>\n",
" <td>131.20</td>\n",
" <td>1261.0</td>\n",
" <td>0.09780</td>\n",
" <td>0.10340</td>\n",
" <td>0.144000</td>\n",
" <td>0.097910</td>\n",
" <td>0.1752</td>\n",
" <td>0.05533</td>\n",
" <td>...</td>\n",
" <td>23.690</td>\n",
" <td>38.25</td>\n",
" <td>155.00</td>\n",
" <td>1731.0</td>\n",
" <td>0.11660</td>\n",
" <td>0.19220</td>\n",
" <td>0.32150</td>\n",
" <td>0.16280</td>\n",
" <td>0.2572</td>\n",
" <td>0.06637</td>\n",
" </tr>\n",
" <tr>\n",
" <th>566</th>\n",
" <td>16.600</td>\n",
" <td>28.08</td>\n",
" <td>108.30</td>\n",
" <td>858.1</td>\n",
" <td>0.08455</td>\n",
" <td>0.10230</td>\n",
" <td>0.092510</td>\n",
" <td>0.053020</td>\n",
" <td>0.1590</td>\n",
" <td>0.05648</td>\n",
" <td>...</td>\n",
" <td>18.980</td>\n",
" <td>34.12</td>\n",
" <td>126.70</td>\n",
" <td>1124.0</td>\n",
" <td>0.11390</td>\n",
" <td>0.30940</td>\n",
" <td>0.34030</td>\n",
" <td>0.14180</td>\n",
" <td>0.2218</td>\n",
" <td>0.07820</td>\n",
" </tr>\n",
" <tr>\n",
" <th>567</th>\n",
" <td>20.600</td>\n",
" <td>29.33</td>\n",
" <td>140.10</td>\n",
" <td>1265.0</td>\n",
" <td>0.11780</td>\n",
" <td>0.27700</td>\n",
" <td>0.351400</td>\n",
" <td>0.152000</td>\n",
" <td>0.2397</td>\n",
" <td>0.07016</td>\n",
" <td>...</td>\n",
" <td>25.740</td>\n",
" <td>39.42</td>\n",
" <td>184.60</td>\n",
" <td>1821.0</td>\n",
" <td>0.16500</td>\n",
" <td>0.86810</td>\n",
" <td>0.93870</td>\n",
" <td>0.26500</td>\n",
" <td>0.4087</td>\n",
" <td>0.12400</td>\n",
" </tr>\n",
" <tr>\n",
" <th>568</th>\n",
" <td>7.760</td>\n",
" <td>24.54</td>\n",
" <td>47.92</td>\n",
" <td>181.0</td>\n",
" <td>0.05263</td>\n",
" <td>0.04362</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.1587</td>\n",
" <td>0.05884</td>\n",
" <td>...</td>\n",
" <td>9.456</td>\n",
" <td>30.37</td>\n",
" <td>59.16</td>\n",
" <td>268.6</td>\n",
" <td>0.08996</td>\n",
" <td>0.06444</td>\n",
" <td>0.00000</td>\n",
" <td>0.00000</td>\n",
" <td>0.2871</td>\n",
" <td>0.07039</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>569 rows × 30 columns</p>\n",
"</div>"
],
"text/plain": [
" mean radius mean texture mean perimeter mean area mean smoothness \\\n",
"0 17.990 10.38 122.80 1001.0 0.11840 \n",
"1 20.570 17.77 132.90 1326.0 0.08474 \n",
"2 19.690 21.25 130.00 1203.0 0.10960 \n",
"3 11.420 20.38 77.58 386.1 0.14250 \n",
"4 20.290 14.34 135.10 1297.0 0.10030 \n",
"5 12.450 15.70 82.57 477.1 0.12780 \n",
"6 18.250 19.98 119.60 1040.0 0.09463 \n",
"7 13.710 20.83 90.20 577.9 0.11890 \n",
"8 13.000 21.82 87.50 519.8 0.12730 \n",
"9 12.460 24.04 83.97 475.9 0.11860 \n",
"10 16.020 23.24 102.70 797.8 0.08206 \n",
"11 15.780 17.89 103.60 781.0 0.09710 \n",
"12 19.170 24.80 132.40 1123.0 0.09740 \n",
"13 15.850 23.95 103.70 782.7 0.08401 \n",
"14 13.730 22.61 93.60 578.3 0.11310 \n",
"15 14.540 27.54 96.73 658.8 0.11390 \n",
"16 14.680 20.13 94.74 684.5 0.09867 \n",
"17 16.130 20.68 108.10 798.8 0.11700 \n",
"18 19.810 22.15 130.00 1260.0 0.09831 \n",
"19 13.540 14.36 87.46 566.3 0.09779 \n",
"20 13.080 15.71 85.63 520.0 0.10750 \n",
"21 9.504 12.44 60.34 273.9 0.10240 \n",
"22 15.340 14.26 102.50 704.4 0.10730 \n",
"23 21.160 23.04 137.20 1404.0 0.09428 \n",
"24 16.650 21.38 110.00 904.6 0.11210 \n",
"25 17.140 16.40 116.00 912.7 0.11860 \n",
"26 14.580 21.53 97.41 644.8 0.10540 \n",
"27 18.610 20.25 122.10 1094.0 0.09440 \n",
"28 15.300 25.27 102.40 732.4 0.10820 \n",
"29 17.570 15.05 115.00 955.1 0.09847 \n",
".. ... ... ... ... ... \n",
"539 7.691 25.44 48.34 170.4 0.08668 \n",
"540 11.540 14.44 74.65 402.9 0.09984 \n",
"541 14.470 24.99 95.81 656.4 0.08837 \n",
"542 14.740 25.42 94.70 668.6 0.08275 \n",
"543 13.210 28.06 84.88 538.4 0.08671 \n",
"544 13.870 20.70 89.77 584.8 0.09578 \n",
"545 13.620 23.23 87.19 573.2 0.09246 \n",
"546 10.320 16.35 65.31 324.9 0.09434 \n",
"547 10.260 16.58 65.85 320.8 0.08877 \n",
"548 9.683 19.34 61.05 285.7 0.08491 \n",
"549 10.820 24.21 68.89 361.6 0.08192 \n",
"550 10.860 21.48 68.51 360.5 0.07431 \n",
"551 11.130 22.44 71.49 378.4 0.09566 \n",
"552 12.770 29.43 81.35 507.9 0.08276 \n",
"553 9.333 21.94 59.01 264.0 0.09240 \n",
"554 12.880 28.92 82.50 514.3 0.08123 \n",
"555 10.290 27.61 65.67 321.4 0.09030 \n",
"556 10.160 19.59 64.73 311.7 0.10030 \n",
"557 9.423 27.88 59.26 271.3 0.08123 \n",
"558 14.590 22.68 96.39 657.1 0.08473 \n",
"559 11.510 23.93 74.52 403.5 0.09261 \n",
"560 14.050 27.15 91.38 600.4 0.09929 \n",
"561 11.200 29.37 70.67 386.0 0.07449 \n",
"562 15.220 30.62 103.40 716.9 0.10480 \n",
"563 20.920 25.09 143.00 1347.0 0.10990 \n",
"564 21.560 22.39 142.00 1479.0 0.11100 \n",
"565 20.130 28.25 131.20 1261.0 0.09780 \n",
"566 16.600 28.08 108.30 858.1 0.08455 \n",
"567 20.600 29.33 140.10 1265.0 0.11780 \n",
"568 7.760 24.54 47.92 181.0 0.05263 \n",
"\n",
" mean compactness mean concavity mean concave points mean symmetry \\\n",
"0 0.27760 0.300100 0.147100 0.2419 \n",
"1 0.07864 0.086900 0.070170 0.1812 \n",
"2 0.15990 0.197400 0.127900 0.2069 \n",
"3 0.28390 0.241400 0.105200 0.2597 \n",
"4 0.13280 0.198000 0.104300 0.1809 \n",
"5 0.17000 0.157800 0.080890 0.2087 \n",
"6 0.10900 0.112700 0.074000 0.1794 \n",
"7 0.16450 0.093660 0.059850 0.2196 \n",
"8 0.19320 0.185900 0.093530 0.2350 \n",
"9 0.23960 0.227300 0.085430 0.2030 \n",
"10 0.06669 0.032990 0.033230 0.1528 \n",
"11 0.12920 0.099540 0.066060 0.1842 \n",
"12 0.24580 0.206500 0.111800 0.2397 \n",
"13 0.10020 0.099380 0.053640 0.1847 \n",
"14 0.22930 0.212800 0.080250 0.2069 \n",
"15 0.15950 0.163900 0.073640 0.2303 \n",
"16 0.07200 0.073950 0.052590 0.1586 \n",
"17 0.20220 0.172200 0.102800 0.2164 \n",
"18 0.10270 0.147900 0.094980 0.1582 \n",
"19 0.08129 0.066640 0.047810 0.1885 \n",
"20 0.12700 0.045680 0.031100 0.1967 \n",
"21 0.06492 0.029560 0.020760 0.1815 \n",
"22 0.21350 0.207700 0.097560 0.2521 \n",
"23 0.10220 0.109700 0.086320 0.1769 \n",
"24 0.14570 0.152500 0.091700 0.1995 \n",
"25 0.22760 0.222900 0.140100 0.3040 \n",
"26 0.18680 0.142500 0.087830 0.2252 \n",
"27 0.10660 0.149000 0.077310 0.1697 \n",
"28 0.16970 0.168300 0.087510 0.1926 \n",
"29 0.11570 0.098750 0.079530 0.1739 \n",
".. ... ... ... ... \n",
"539 0.11990 0.092520 0.013640 0.2037 \n",
"540 0.11200 0.067370 0.025940 0.1818 \n",
"541 0.12300 0.100900 0.038900 0.1872 \n",
"542 0.07214 0.041050 0.030270 0.1840 \n",
"543 0.06877 0.029870 0.032750 0.1628 \n",
"544 0.10180 0.036880 0.023690 0.1620 \n",
"545 0.06747 0.029740 0.024430 0.1664 \n",
"546 0.04994 0.010120 0.005495 0.1885 \n",
"547 0.08066 0.043580 0.024380 0.1669 \n",
"548 0.05030 0.023370 0.009615 0.1580 \n",
"549 0.06602 0.015480 0.008160 0.1976 \n",
"550 0.04227 0.000000 0.000000 0.1661 \n",
"551 0.08194 0.048240 0.022570 0.2030 \n",
"552 0.04234 0.019970 0.014990 0.1539 \n",
"553 0.05605 0.039960 0.012820 0.1692 \n",
"554 0.05824 0.061950 0.023430 0.1566 \n",
"555 0.07658 0.059990 0.027380 0.1593 \n",
"556 0.07504 0.005025 0.011160 0.1791 \n",
"557 0.04971 0.000000 0.000000 0.1742 \n",
"558 0.13300 0.102900 0.037360 0.1454 \n",
"559 0.10210 0.111200 0.041050 0.1388 \n",
"560 0.11260 0.044620 0.043040 0.1537 \n",
"561 0.03558 0.000000 0.000000 0.1060 \n",
"562 0.20870 0.255000 0.094290 0.2128 \n",
"563 0.22360 0.317400 0.147400 0.2149 \n",
"564 0.11590 0.243900 0.138900 0.1726 \n",
"565 0.10340 0.144000 0.097910 0.1752 \n",
"566 0.10230 0.092510 0.053020 0.1590 \n",
"567 0.27700 0.351400 0.152000 0.2397 \n",
"568 0.04362 0.000000 0.000000 0.1587 \n",
"\n",
" mean fractal dimension ... worst radius \\\n",
"0 0.07871 ... 25.380 \n",
"1 0.05667 ... 24.990 \n",
"2 0.05999 ... 23.570 \n",
"3 0.09744 ... 14.910 \n",
"4 0.05883 ... 22.540 \n",
"5 0.07613 ... 15.470 \n",
"6 0.05742 ... 22.880 \n",
"7 0.07451 ... 17.060 \n",
"8 0.07389 ... 15.490 \n",
"9 0.08243 ... 15.090 \n",
"10 0.05697 ... 19.190 \n",
"11 0.06082 ... 20.420 \n",
"12 0.07800 ... 20.960 \n",
"13 0.05338 ... 16.840 \n",
"14 0.07682 ... 15.030 \n",
"15 0.07077 ... 17.460 \n",
"16 0.05922 ... 19.070 \n",
"17 0.07356 ... 20.960 \n",
"18 0.05395 ... 27.320 \n",
"19 0.05766 ... 15.110 \n",
"20 0.06811 ... 14.500 \n",
"21 0.06905 ... 10.230 \n",
"22 0.07032 ... 18.070 \n",
"23 0.05278 ... 29.170 \n",
"24 0.06330 ... 26.460 \n",
"25 0.07413 ... 22.250 \n",
"26 0.06924 ... 17.620 \n",
"27 0.05699 ... 21.310 \n",
"28 0.06540 ... 20.270 \n",
"29 0.06149 ... 20.010 \n",
".. ... ... ... \n",
"539 0.07751 ... 8.678 \n",
"540 0.06782 ... 12.260 \n",
"541 0.06341 ... 16.220 \n",
"542 0.05680 ... 16.510 \n",
"543 0.05781 ... 14.370 \n",
"544 0.06688 ... 15.050 \n",
"545 0.05801 ... 15.350 \n",
"546 0.06201 ... 11.250 \n",
"547 0.06714 ... 10.830 \n",
"548 0.06235 ... 10.930 \n",
"549 0.06328 ... 13.030 \n",
"550 0.05948 ... 11.660 \n",
"551 0.06552 ... 12.020 \n",
"552 0.05637 ... 13.870 \n",
"553 0.06576 ... 9.845 \n",
"554 0.05708 ... 13.890 \n",
"555 0.06127 ... 10.840 \n",
"556 0.06331 ... 10.650 \n",
"557 0.06059 ... 10.490 \n",
"558 0.06147 ... 15.480 \n",
"559 0.06570 ... 12.480 \n",
"560 0.06171 ... 15.300 \n",
"561 0.05502 ... 11.920 \n",
"562 0.07152 ... 17.520 \n",
"563 0.06879 ... 24.290 \n",
"564 0.05623 ... 25.450 \n",
"565 0.05533 ... 23.690 \n",
"566 0.05648 ... 18.980 \n",
"567 0.07016 ... 25.740 \n",
"568 0.05884 ... 9.456 \n",
"\n",
" worst texture worst perimeter worst area worst smoothness \\\n",
"0 17.33 184.60 2019.0 0.16220 \n",
"1 23.41 158.80 1956.0 0.12380 \n",
"2 25.53 152.50 1709.0 0.14440 \n",
"3 26.50 98.87 567.7 0.20980 \n",
"4 16.67 152.20 1575.0 0.13740 \n",
"5 23.75 103.40 741.6 0.17910 \n",
"6 27.66 153.20 1606.0 0.14420 \n",
"7 28.14 110.60 897.0 0.16540 \n",
"8 30.73 106.20 739.3 0.17030 \n",
"9 40.68 97.65 711.4 0.18530 \n",
"10 33.88 123.80 1150.0 0.11810 \n",
"11 27.28 136.50 1299.0 0.13960 \n",
"12 29.94 151.70 1332.0 0.10370 \n",
"13 27.66 112.00 876.5 0.11310 \n",
"14 32.01 108.80 697.7 0.16510 \n",
"15 37.13 124.10 943.2 0.16780 \n",
"16 30.88 123.40 1138.0 0.14640 \n",
"17 31.48 136.80 1315.0 0.17890 \n",
"18 30.88 186.80 2398.0 0.15120 \n",
"19 19.26 99.70 711.2 0.14400 \n",
"20 20.49 96.09 630.5 0.13120 \n",
"21 15.66 65.13 314.9 0.13240 \n",
"22 19.08 125.10 980.9 0.13900 \n",
"23 35.59 188.00 2615.0 0.14010 \n",
"24 31.56 177.00 2215.0 0.18050 \n",
"25 21.40 152.40 1461.0 0.15450 \n",
"26 33.21 122.40 896.9 0.15250 \n",
"27 27.26 139.90 1403.0 0.13380 \n",
"28 36.71 149.30 1269.0 0.16410 \n",
"29 19.52 134.90 1227.0 0.12550 \n",
".. ... ... ... ... \n",
"539 31.89 54.49 223.6 0.15960 \n",
"540 19.68 78.78 457.8 0.13450 \n",
"541 31.73 113.50 808.9 0.13400 \n",
"542 32.29 107.40 826.4 0.10600 \n",
"543 37.17 92.48 629.6 0.10720 \n",
"544 24.75 99.17 688.6 0.12640 \n",
"545 29.09 97.58 729.8 0.12160 \n",
"546 21.77 71.12 384.9 0.12850 \n",
"547 22.04 71.08 357.4 0.14610 \n",
"548 25.59 69.10 364.2 0.11990 \n",
"549 31.45 83.90 505.6 0.12040 \n",
"550 24.77 74.08 412.3 0.10010 \n",
"551 28.26 77.80 436.6 0.10870 \n",
"552 36.00 88.10 594.7 0.12340 \n",
"553 25.05 62.86 295.8 0.11030 \n",
"554 35.74 88.84 595.7 0.12270 \n",
"555 34.91 69.57 357.6 0.13840 \n",
"556 22.88 67.88 347.3 0.12650 \n",
"557 34.24 66.50 330.6 0.10730 \n",
"558 27.27 105.90 733.5 0.10260 \n",
"559 37.16 82.28 474.2 0.12980 \n",
"560 33.17 100.20 706.7 0.12410 \n",
"561 38.30 75.19 439.6 0.09267 \n",
"562 42.79 128.70 915.0 0.14170 \n",
"563 29.41 179.10 1819.0 0.14070 \n",
"564 26.40 166.10 2027.0 0.14100 \n",
"565 38.25 155.00 1731.0 0.11660 \n",
"566 34.12 126.70 1124.0 0.11390 \n",
"567 39.42 184.60 1821.0 0.16500 \n",
"568 30.37 59.16 268.6 0.08996 \n",
"\n",
" worst compactness worst concavity worst concave points worst symmetry \\\n",
"0 0.66560 0.71190 0.26540 0.4601 \n",
"1 0.18660 0.24160 0.18600 0.2750 \n",
"2 0.42450 0.45040 0.24300 0.3613 \n",
"3 0.86630 0.68690 0.25750 0.6638 \n",
"4 0.20500 0.40000 0.16250 0.2364 \n",
"5 0.52490 0.53550 0.17410 0.3985 \n",
"6 0.25760 0.37840 0.19320 0.3063 \n",
"7 0.36820 0.26780 0.15560 0.3196 \n",
"8 0.54010 0.53900 0.20600 0.4378 \n",
"9 1.05800 1.10500 0.22100 0.4366 \n",
"10 0.15510 0.14590 0.09975 0.2948 \n",
"11 0.56090 0.39650 0.18100 0.3792 \n",
"12 0.39030 0.36390 0.17670 0.3176 \n",
"13 0.19240 0.23220 0.11190 0.2809 \n",
"14 0.77250 0.69430 0.22080 0.3596 \n",
"15 0.65770 0.70260 0.17120 0.4218 \n",
"16 0.18710 0.29140 0.16090 0.3029 \n",
"17 0.42330 0.47840 0.20730 0.3706 \n",
"18 0.31500 0.53720 0.23880 0.2768 \n",
"19 0.17730 0.23900 0.12880 0.2977 \n",
"20 0.27760 0.18900 0.07283 0.3184 \n",
"21 0.11480 0.08867 0.06227 0.2450 \n",
"22 0.59540 0.63050 0.23930 0.4667 \n",
"23 0.26000 0.31550 0.20090 0.2822 \n",
"24 0.35780 0.46950 0.20950 0.3613 \n",
"25 0.39490 0.38530 0.25500 0.4066 \n",
"26 0.66430 0.55390 0.27010 0.4264 \n",
"27 0.21170 0.34460 0.14900 0.2341 \n",
"28 0.61100 0.63350 0.20240 0.4027 \n",
"29 0.28120 0.24890 0.14560 0.2756 \n",
".. ... ... ... ... \n",
"539 0.30640 0.33930 0.05000 0.2790 \n",
"540 0.21180 0.17970 0.06918 0.2329 \n",
"541 0.42020 0.40400 0.12050 0.3187 \n",
"542 0.13760 0.16110 0.10950 0.2722 \n",
"543 0.13810 0.10620 0.07958 0.2473 \n",
"544 0.20370 0.13770 0.06845 0.2249 \n",
"545 0.15170 0.10490 0.07174 0.2642 \n",
"546 0.08842 0.04384 0.02381 0.2681 \n",
"547 0.22460 0.17830 0.08333 0.2691 \n",
"548 0.09546 0.09350 0.03846 0.2552 \n",
"549 0.16330 0.06194 0.03264 0.3059 \n",
"550 0.07348 0.00000 0.00000 0.2458 \n",
"551 0.17820 0.15640 0.06413 0.3169 \n",
"552 0.10640 0.08653 0.06498 0.2407 \n",
"553 0.08298 0.07993 0.02564 0.2435 \n",
"554 0.16200 0.24390 0.06493 0.2372 \n",
"555 0.17100 0.20000 0.09127 0.2226 \n",
"556 0.12000 0.01005 0.02232 0.2262 \n",
"557 0.07158 0.00000 0.00000 0.2475 \n",
"558 0.31710 0.36620 0.11050 0.2258 \n",
"559 0.25170 0.36300 0.09653 0.2112 \n",
"560 0.22640 0.13260 0.10480 0.2250 \n",
"561 0.05494 0.00000 0.00000 0.1566 \n",
"562 0.79170 1.17000 0.23560 0.4089 \n",
"563 0.41860 0.65990 0.25420 0.2929 \n",
"564 0.21130 0.41070 0.22160 0.2060 \n",
"565 0.19220 0.32150 0.16280 0.2572 \n",
"566 0.30940 0.34030 0.14180 0.2218 \n",
"567 0.86810 0.93870 0.26500 0.4087 \n",
"568 0.06444 0.00000 0.00000 0.2871 \n",
"\n",
" worst fractal dimension \n",
"0 0.11890 \n",
"1 0.08902 \n",
"2 0.08758 \n",
"3 0.17300 \n",
"4 0.07678 \n",
"5 0.12440 \n",
"6 0.08368 \n",
"7 0.11510 \n",
"8 0.10720 \n",
"9 0.20750 \n",
"10 0.08452 \n",
"11 0.10480 \n",
"12 0.10230 \n",
"13 0.06287 \n",
"14 0.14310 \n",
"15 0.13410 \n",
"16 0.08216 \n",
"17 0.11420 \n",
"18 0.07615 \n",
"19 0.07259 \n",
"20 0.08183 \n",
"21 0.07773 \n",
"22 0.09946 \n",
"23 0.07526 \n",
"24 0.09564 \n",
"25 0.10590 \n",
"26 0.12750 \n",
"27 0.07421 \n",
"28 0.09876 \n",
"29 0.07919 \n",
".. ... \n",
"539 0.10660 \n",
"540 0.08134 \n",
"541 0.10230 \n",
"542 0.06956 \n",
"543 0.06443 \n",
"544 0.08492 \n",
"545 0.06953 \n",
"546 0.07399 \n",
"547 0.09479 \n",
"548 0.07920 \n",
"549 0.07626 \n",
"550 0.06592 \n",
"551 0.08032 \n",
"552 0.06484 \n",
"553 0.07393 \n",
"554 0.07242 \n",
"555 0.08283 \n",
"556 0.06742 \n",
"557 0.06969 \n",
"558 0.08004 \n",
"559 0.08732 \n",
"560 0.08321 \n",
"561 0.05905 \n",
"562 0.14090 \n",
"563 0.09873 \n",
"564 0.07115 \n",
"565 0.06637 \n",
"566 0.07820 \n",
"567 0.12400 \n",
"568 0.07039 \n",
"\n",
"[569 rows x 30 columns]"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"mean radius 14.127292\n",
"mean texture 19.289649\n",
"mean perimeter 91.969033\n",
"mean area 654.889104\n",
"mean smoothness 0.096360\n",
"mean compactness 0.104341\n",
"mean concavity 0.088799\n",
"mean concave points 0.048919\n",
"mean symmetry 0.181162\n",
"mean fractal dimension 0.062798\n",
"radius error 0.405172\n",
"texture error 1.216853\n",
"perimeter error 2.866059\n",
"area error 40.337079\n",
"smoothness error 0.007041\n",
"compactness error 0.025478\n",
"concavity error 0.031894\n",
"concave points error 0.011796\n",
"symmetry error 0.020542\n",
"fractal dimension error 0.003795\n",
"worst radius 16.269190\n",
"worst texture 25.677223\n",
"worst perimeter 107.261213\n",
"worst area 880.583128\n",
"worst smoothness 0.132369\n",
"worst compactness 0.254265\n",
"worst concavity 0.272188\n",
"worst concave points 0.114606\n",
"worst symmetry 0.290076\n",
"worst fractal dimension 0.083946\n",
"dtype: float64"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.mean()"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"df10 = df.iloc[:, :10]"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(569, 10)"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df10.shape"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>mean radius</th>\n",
" <th>mean texture</th>\n",
" <th>mean perimeter</th>\n",
" <th>mean area</th>\n",
" <th>mean smoothness</th>\n",
" <th>mean compactness</th>\n",
" <th>mean concavity</th>\n",
" <th>mean concave points</th>\n",
" <th>mean symmetry</th>\n",
" <th>mean fractal dimension</th>\n",
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" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>17.99</td>\n",
" <td>10.38</td>\n",
" <td>122.80</td>\n",
" <td>1001.0</td>\n",
" <td>0.11840</td>\n",
" <td>0.27760</td>\n",
" <td>0.3001</td>\n",
" <td>0.14710</td>\n",
" <td>0.2419</td>\n",
" <td>0.07871</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>20.57</td>\n",
" <td>17.77</td>\n",
" <td>132.90</td>\n",
" <td>1326.0</td>\n",
" <td>0.08474</td>\n",
" <td>0.07864</td>\n",
" <td>0.0869</td>\n",
" <td>0.07017</td>\n",
" <td>0.1812</td>\n",
" <td>0.05667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>19.69</td>\n",
" <td>21.25</td>\n",
" <td>130.00</td>\n",
" <td>1203.0</td>\n",
" <td>0.10960</td>\n",
" <td>0.15990</td>\n",
" <td>0.1974</td>\n",
" <td>0.12790</td>\n",
" <td>0.2069</td>\n",
" <td>0.05999</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>11.42</td>\n",
" <td>20.38</td>\n",
" <td>77.58</td>\n",
" <td>386.1</td>\n",
" <td>0.14250</td>\n",
" <td>0.28390</td>\n",
" <td>0.2414</td>\n",
" <td>0.10520</td>\n",
" <td>0.2597</td>\n",
" <td>0.09744</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>20.29</td>\n",
" <td>14.34</td>\n",
" <td>135.10</td>\n",
" <td>1297.0</td>\n",
" <td>0.10030</td>\n",
" <td>0.13280</td>\n",
" <td>0.1980</td>\n",
" <td>0.10430</td>\n",
" <td>0.1809</td>\n",
" <td>0.05883</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" mean radius mean texture mean perimeter mean area mean smoothness \\\n",
"0 17.99 10.38 122.80 1001.0 0.11840 \n",
"1 20.57 17.77 132.90 1326.0 0.08474 \n",
"2 19.69 21.25 130.00 1203.0 0.10960 \n",
"3 11.42 20.38 77.58 386.1 0.14250 \n",
"4 20.29 14.34 135.10 1297.0 0.10030 \n",
"\n",
" mean compactness mean concavity mean concave points mean symmetry \\\n",
"0 0.27760 0.3001 0.14710 0.2419 \n",
"1 0.07864 0.0869 0.07017 0.1812 \n",
"2 0.15990 0.1974 0.12790 0.2069 \n",
"3 0.28390 0.2414 0.10520 0.2597 \n",
"4 0.13280 0.1980 0.10430 0.1809 \n",
"\n",
" mean fractal dimension \n",
"0 0.07871 \n",
"1 0.05667 \n",
"2 0.05999 \n",
"3 0.09744 \n",
"4 0.05883 "
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df10.head()"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.model_selection import train_test_split"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [],
"source": [
"X_train, X_val, y_train, y_val = train_test_split(df10, y, test_size=0.2)"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"((455, 10), (114, 10))"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X_train.shape, X_val.shape"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"569"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"455 + 114"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.7996485061511424"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"455 / (455 + 114)"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.linear_model import LogisticRegression"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [],
"source": [
"clf = LogisticRegression()"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
" intercept_scaling=1, max_iter=100, multi_class='ovr', n_jobs=1,\n",
" penalty='l2', random_state=None, solver='liblinear', tol=0.0001,\n",
" verbose=0, warm_start=False)"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"clf.fit(X_train, y_train)"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [],
"source": [
"y_train_pred = clf.predict(X_train)"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.metrics import accuracy_score"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.9142857142857143"
]
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"accuracy_score(y_train, y_train_pred)"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [],
"source": [
"y_val_pred = clf.predict(X_val)"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.8947368421052632"
]
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"accuracy_score(y_val, y_val_pred)"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.6274165202108963"
]
},
"execution_count": 50,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"y.mean()"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.metrics import confusion_matrix"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [],
"source": [
"cm = confusion_matrix(y_val, y_val_pred)"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[38, 9],\n",
" [ 3, 64]])"
]
},
"execution_count": 54,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cm"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.metrics import classification_report"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" precision recall f1-score support\n",
"\n",
" 0 0.93 0.81 0.86 47\n",
" 1 0.88 0.96 0.91 67\n",
"\n",
"avg / total 0.90 0.89 0.89 114\n",
"\n"
]
}
],
"source": [
"print(classification_report(y_val, y_val_pred))"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {},
"outputs": [],
"source": [
"X_train, X_val, y_train, y_val = train_test_split(df, y, test_size=0.2)"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {},
"outputs": [],
"source": [
"clf = LogisticRegression()"
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
" intercept_scaling=1, max_iter=100, multi_class='ovr', n_jobs=1,\n",
" penalty='l2', random_state=None, solver='liblinear', tol=0.0001,\n",
" verbose=0, warm_start=False)"
]
},
"execution_count": 59,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"clf.fit(X_train, y_train)"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {},
"outputs": [],
"source": [
"y_train_pred = clf.predict(X_train)"
]
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.9560439560439561"
]
},
"execution_count": 61,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"accuracy_score(y_train, y_train_pred)"
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {},
"outputs": [],
"source": [
"y_val_pred = clf.predict(X_val)"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.9473684210526315"
]
},
"execution_count": 63,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"accuracy_score(y_val, y_val_pred)"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {},
"outputs": [],
"source": [
"cm2 = confusion_matrix(y_val, y_val_pred)"
]
},
{
"cell_type": "code",
"execution_count": 65,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[35, 2],\n",
" [ 4, 73]])"
]
},
"execution_count": 65,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cm2"
]
},
{
"cell_type": "code",
"execution_count": 66,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" precision recall f1-score support\n",
"\n",
" 0 0.90 0.95 0.92 37\n",
" 1 0.97 0.95 0.96 77\n",
"\n",
"avg / total 0.95 0.95 0.95 114\n",
"\n"
]
}
],
"source": [
"print(classification_report(y_val, y_val_pred))"
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.svm import SVC"
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {},
"outputs": [],
"source": [
"svc = SVC(kernel=\"rbf\")"
]
},
{
"cell_type": "code",
"execution_count": 75,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
" decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
" max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
" tol=0.001, verbose=False)"
]
},
"execution_count": 75,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"svc.fit(X_train, y_train)"
]
},
{
"cell_type": "code",
"execution_count": 76,
"metadata": {},
"outputs": [],
"source": [
"y_train_pred = svc.predict(X_train)"
]
},
{
"cell_type": "code",
"execution_count": 77,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1.0"
]
},
"execution_count": 77,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"accuracy_score(y_train, y_train_pred)"
]
},
{
"cell_type": "code",
"execution_count": 78,
"metadata": {},
"outputs": [],
"source": [
"y_val_pred = svc.predict(X_val)"
]
},
{
"cell_type": "code",
"execution_count": 79,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.6754385964912281"
]
},
"execution_count": 79,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"accuracy_score(y_val, y_val_pred)"
]
},
{
"cell_type": "code",
"execution_count": 83,
"metadata": {},
"outputs": [],
"source": [
"def report(y, pred):\n",
" print(accuracy_score(y, pred))\n",
" cm = confusion_matrix(y, pred)\n",
" print(cm)\n",
" cr = classification_report(y, pred)\n",
" print(cr)\n",
"\n",
"def fit_to_pred(clf, X_train, X_val, y_train, y_val):\n",
" # 学習\n",
" clf.fit(X_train, y_train)\n",
" \n",
" # 学習データで評価\n",
" y_train_pred = clf.predict(X_train)\n",
" print(\"y_train_pred: \")\n",
" report(y_train, y_train_pred)\n",
" \n",
" # テストデータで評価\n",
" y_val_pred = clf.predict(X_val)\n",
" print(\"y_val_pred: \")\n",
" report(y_val, y_val_pred)\n",
" \n",
" # 学習済みデータを返す\n",
" return clf"
]
},
{
"cell_type": "code",
"execution_count": 81,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.tree import DecisionTreeClassifier"
]
},
{
"cell_type": "code",
"execution_count": 86,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"y_train_pred: \n",
"0.9934065934065934\n",
"[[172 3]\n",
" [ 0 280]]\n",
" precision recall f1-score support\n",
"\n",
" 0 1.00 0.98 0.99 175\n",
" 1 0.99 1.00 0.99 280\n",
"\n",
"avg / total 0.99 0.99 0.99 455\n",
"\n",
"y_val_pred: \n",
"0.9210526315789473\n",
"[[33 4]\n",
" [ 5 72]]\n",
" precision recall f1-score support\n",
"\n",
" 0 0.87 0.89 0.88 37\n",
" 1 0.95 0.94 0.94 77\n",
"\n",
"avg / total 0.92 0.92 0.92 114\n",
"\n"
]
},
{
"data": {
"text/plain": [
"DecisionTreeClassifier(class_weight=None, criterion='gini', max_depth=5,\n",
" max_features=None, max_leaf_nodes=None,\n",
" min_impurity_decrease=0.0, min_impurity_split=None,\n",
" min_samples_leaf=1, min_samples_split=2,\n",
" min_weight_fraction_leaf=0.0, presort=False, random_state=None,\n",
" splitter='best')"
]
},
"execution_count": 86,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tree = DecisionTreeClassifier(max_depth=5)\n",
"fit_to_pred(tree, X_train, X_val, y_train, y_val)"
]
},
{
"cell_type": "code",
"execution_count": 87,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.ensemble import RandomForestClassifier"
]
},
{
"cell_type": "code",
"execution_count": 88,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"y_train_pred: \n",
"0.9978021978021978\n",
"[[175 0]\n",
" [ 1 279]]\n",
" precision recall f1-score support\n",
"\n",
" 0 0.99 1.00 1.00 175\n",
" 1 1.00 1.00 1.00 280\n",
"\n",
"avg / total 1.00 1.00 1.00 455\n",
"\n",
"y_val_pred: \n",
"0.9736842105263158\n",
"[[37 0]\n",
" [ 3 74]]\n",
" precision recall f1-score support\n",
"\n",
" 0 0.93 1.00 0.96 37\n",
" 1 1.00 0.96 0.98 77\n",
"\n",
"avg / total 0.98 0.97 0.97 114\n",
"\n"
]
},
{
"data": {
"text/plain": [
"RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',\n",
" max_depth=None, max_features='auto', max_leaf_nodes=None,\n",
" min_impurity_decrease=0.0, min_impurity_split=None,\n",
" min_samples_leaf=1, min_samples_split=2,\n",
" min_weight_fraction_leaf=0.0, n_estimators=10, n_jobs=1,\n",
" oob_score=False, random_state=None, verbose=0,\n",
" warm_start=False)"
]
},
"execution_count": 88,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"rf = RandomForestClassifier()\n",
"fit_to_pred(rf, X_train, X_val, y_train, y_val)"
]
},
{
"cell_type": "code",
"execution_count": 89,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.model_selection import cross_val_score"
]
},
{
"cell_type": "code",
"execution_count": 90,
"metadata": {},
"outputs": [],
"source": [
"\n",
"from sklearn.model_selection import KFold"
]
},
{
"cell_type": "code",
"execution_count": 91,
"metadata": {},
"outputs": [],
"source": [
"cv = KFold(5, shuffle=True)"
]
},
{
"cell_type": "code",
"execution_count": 99,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[0.90350877 0.98245614 0.99122807 0.92105263 0.94690265] 0.9490296537804689\n",
"[0.95238095 0.94594595 0.98484848 0.97468354 0.94814815] 0.9612014151254658\n"
]
}
],
"source": [
"clf = LogisticRegression()\n",
"s = cross_val_score(clf, df, y, cv=cv)\n",
"print(s, s.mean())\n",
"sf = cross_val_score(clf, df, y, cv=cv, scoring=\"f1\")\n",
"print(sf, sf.mean())"
]
},
{
"cell_type": "code",
"execution_count": 100,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[0.5877193 0.60526316 0.64035088 0.64035088 0.66371681] 0.6274802049371215\n",
"[0.74033149 0.74033149 0.82474227 0.78723404 0.75824176] 0.7701762104523202\n"
]
}
],
"source": [
"k_svc = SVC(kernel=\"rbf\")\n",
"s = cross_val_score(k_svc, df, y, cv=cv)\n",
"print(s, s.mean())\n",
"sf = s = cross_val_score(k_svc, df, y, cv=cv, scoring=\"f1\")\n",
"print(sf, sf.mean())"
]
},
{
"cell_type": "code",
"execution_count": 101,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[0.95614035 0.94736842 0.99122807 0.95614035 0.92920354] 0.956016146561093\n",
"[0.95454545 0.95522388 0.95172414 0.97368421 0.95364238] 0.957764013541156\n"
]
}
],
"source": [
"rf = RandomForestClassifier()\n",
"s = cross_val_score(rf, df, y, cv=cv)\n",
"print(s, s.mean())\n",
"sf = cross_val_score(rf, df, y, cv=cv, scoring=\"f1\")\n",
"print(sf, sf.mean())"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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