9-XGBSklearn-Synthesis-Copy1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import sklearn as sk\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "game_csv = pd.read_csv('./data/Training_dataset_Original.csv',na_values=[\"NA\", \"na\", \"missing\"])\n",
    "gameDf = pd.DataFrame(game_csv)\n",
    "\n",
    "dataDict = pd.read_csv('./data/Data_Dictionary.csv',na_values=\"NA\")\n",
    "\n",
    "#Leaderboard\n",
    "leader_csv = pd.read_csv('./data/Leaderboard_dataset.csv',na_values=[\"NA\", \"na\", \"missing\"])\n",
    "leaderDf = pd.DataFrame(leader_csv)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
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       "      <td>NaN</td>\n",
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       "      <td>0.000</td>\n",
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       "      <td>4955.0</td>\n",
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       "      <td>96.272</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
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       "      <td>5494.0</td>\n",
       "      <td>7987.0</td>\n",
       "      <td>4696.0</td>\n",
       "      <td>...</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
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       "      <th>8</th>\n",
       "      <td>1836.0</td>\n",
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       "      <td>0.000</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1839.0</td>\n",
       "      <td>0.1981</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>793.0</td>\n",
       "      <td>6131.0</td>\n",
       "      <td>6045.0</td>\n",
       "      <td>48959.0</td>\n",
       "      <td>31640.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45.590</td>\n",
       "      <td>0.08824</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.33834</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1903.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>22.0</td>\n",
       "      <td>19518.0</td>\n",
       "      <td>9910.0</td>\n",
       "      <td>90618.0</td>\n",
       "      <td>110271.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.80620</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1681.0</td>\n",
       "      <td>1.5888</td>\n",
       "      <td>5.685</td>\n",
       "      <td>3.566</td>\n",
       "      <td>0.000</td>\n",
       "      <td>93.0</td>\n",
       "      <td>3554.0</td>\n",
       "      <td>439.0</td>\n",
       "      <td>2527.0</td>\n",
       "      <td>7086.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.61111</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.81172</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <th>12</th>\n",
       "      <td>1841.0</td>\n",
       "      <td>0.5388</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1487.0</td>\n",
       "      <td>19449.0</td>\n",
       "      <td>19449.0</td>\n",
       "      <td>6739.0</td>\n",
       "      <td>6612.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.98031</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1794.0</td>\n",
       "      <td>1.9684</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>856.0</td>\n",
       "      <td>8609.0</td>\n",
       "      <td>8609.0</td>\n",
       "      <td>60545.0</td>\n",
       "      <td>24893.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.35724</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1669.0</td>\n",
       "      <td>3.8558</td>\n",
       "      <td>18.465</td>\n",
       "      <td>6.292</td>\n",
       "      <td>1.200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>142.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>...</td>\n",
       "      <td>107.825</td>\n",
       "      <td>98.664</td>\n",
       "      <td>0.56000</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.29169</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1583.0</td>\n",
       "      <td>3.0284</td>\n",
       "      <td>16.325</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>51450.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.32353</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1899.0</td>\n",
       "      <td>0.0970</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1015.0</td>\n",
       "      <td>13379.0</td>\n",
       "      <td>13379.0</td>\n",
       "      <td>246906.0</td>\n",
       "      <td>56533.0</td>\n",
       "      <td>...</td>\n",
       "      <td>10.384</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0.47480</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1690.0</td>\n",
       "      <td>8.7747</td>\n",
       "      <td>10.437</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>122.0</td>\n",
       "      <td>623.0</td>\n",
       "      <td>299.0</td>\n",
       "      <td>1140.0</td>\n",
       "      <td>2043.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.63636</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.94951</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1599.0</td>\n",
       "      <td>0.8601</td>\n",
       "      <td>1.525</td>\n",
       "      <td>1.525</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>878.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>878.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>91.175</td>\n",
       "      <td>0.80000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>C</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1859.0</td>\n",
       "      <td>0.0155</td>\n",
       "      <td>0.368</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>424.0</td>\n",
       "      <td>86509.0</td>\n",
       "      <td>12451.0</td>\n",
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       "      <td>142081.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.34730</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1880.0</td>\n",
       "      <td>2.6101</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19252.0</td>\n",
       "      <td>6342.0</td>\n",
       "      <td>59601.0</td>\n",
       "      <td>86906.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>72.497</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.28708</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1852.0</td>\n",
       "      <td>3.6201</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>799.0</td>\n",
       "      <td>16515.0</td>\n",
       "      <td>16515.0</td>\n",
       "      <td>110651.0</td>\n",
       "      <td>41311.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.75349</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1655.0</td>\n",
       "      <td>3.0268</td>\n",
       "      <td>14.748</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>48.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>198.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1863.0</td>\n",
       "      <td>0.0401</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1487.0</td>\n",
       "      <td>4955.0</td>\n",
       "      <td>4955.0</td>\n",
       "      <td>22902.0</td>\n",
       "      <td>21772.0</td>\n",
       "      <td>...</td>\n",
       "      <td>96.895</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.40853</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1753.0</td>\n",
       "      <td>0.2251</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1124.0</td>\n",
       "      <td>1124.0</td>\n",
       "      <td>1124.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1124.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1894.0</td>\n",
       "      <td>0.0318</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4655.0</td>\n",
       "      <td>7433.0</td>\n",
       "      <td>7433.0</td>\n",
       "      <td>25667.0</td>\n",
       "      <td>12345.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.99419</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1803.0</td>\n",
       "      <td>0.3993</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>496.0</td>\n",
       "      <td>10505.0</td>\n",
       "      <td>496.0</td>\n",
       "      <td>991.0</td>\n",
       "      <td>18163.0</td>\n",
       "      <td>...</td>\n",
       "      <td>91.752</td>\n",
       "      <td>87.306</td>\n",
       "      <td>0.20000</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.75289</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1932.0</td>\n",
       "      <td>0.3276</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>6982.0</td>\n",
       "      <td>21569.0</td>\n",
       "      <td>18829.0</td>\n",
       "      <td>187209.0</td>\n",
       "      <td>113813.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.99710</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1714.0</td>\n",
       "      <td>5.1904</td>\n",
       "      <td>0.770</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1889.0</td>\n",
       "      <td>595.0</td>\n",
       "      <td>12574.0</td>\n",
       "      <td>4825.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.35714</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.85082</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0457</td>\n",
       "      <td>4.514</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.16667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>79970</th>\n",
       "      <td>1834.0</td>\n",
       "      <td>1.2164</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>2212.0</td>\n",
       "      <td>5244.0</td>\n",
       "      <td>4203.0</td>\n",
       "      <td>16743.0</td>\n",
       "      <td>13831.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>97.398</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.58040</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79971</th>\n",
       "      <td>1729.0</td>\n",
       "      <td>1.3696</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>356.0</td>\n",
       "      <td>4218.0</td>\n",
       "      <td>1982.0</td>\n",
       "      <td>18657.0</td>\n",
       "      <td>8921.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>83.663</td>\n",
       "      <td>0.09091</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.62632</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79972</th>\n",
       "      <td>1753.0</td>\n",
       "      <td>5.8283</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>180.0</td>\n",
       "      <td>4014.0</td>\n",
       "      <td>617.0</td>\n",
       "      <td>3667.0</td>\n",
       "      <td>9786.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>87.094</td>\n",
       "      <td>0.11111</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.59364</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79973</th>\n",
       "      <td>1748.0</td>\n",
       "      <td>1.9635</td>\n",
       "      <td>0.642</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>291.0</td>\n",
       "      <td>3469.0</td>\n",
       "      <td>3469.0</td>\n",
       "      <td>13131.0</td>\n",
       "      <td>14393.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>92.244</td>\n",
       "      <td>0.44000</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.83809</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79974</th>\n",
       "      <td>1771.0</td>\n",
       "      <td>1.7588</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>66.0</td>\n",
       "      <td>12626.0</td>\n",
       "      <td>6433.0</td>\n",
       "      <td>27946.0</td>\n",
       "      <td>24401.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.477</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.46863</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79975</th>\n",
       "      <td>1766.0</td>\n",
       "      <td>0.9540</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1140.0</td>\n",
       "      <td>10207.0</td>\n",
       "      <td>10207.0</td>\n",
       "      <td>55001.0</td>\n",
       "      <td>20636.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.05000</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.54754</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79976</th>\n",
       "      <td>1822.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.853</td>\n",
       "      <td>1.853</td>\n",
       "      <td>0.000</td>\n",
       "      <td>2581.0</td>\n",
       "      <td>13361.0</td>\n",
       "      <td>5946.0</td>\n",
       "      <td>31018.0</td>\n",
       "      <td>76774.0</td>\n",
       "      <td>...</td>\n",
       "      <td>73.611</td>\n",
       "      <td>44.656</td>\n",
       "      <td>0.03448</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.23177</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79977</th>\n",
       "      <td>1824.0</td>\n",
       "      <td>0.5634</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>3964.0</td>\n",
       "      <td>4683.0</td>\n",
       "      <td>4683.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8647.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.67222</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79978</th>\n",
       "      <td>1914.0</td>\n",
       "      <td>0.0544</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>3469.0</td>\n",
       "      <td>20424.0</td>\n",
       "      <td>20424.0</td>\n",
       "      <td>78774.0</td>\n",
       "      <td>27856.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79979</th>\n",
       "      <td>1600.0</td>\n",
       "      <td>2.6649</td>\n",
       "      <td>18.282</td>\n",
       "      <td>1.078</td>\n",
       "      <td>2.678</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7205.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>956.0</td>\n",
       "      <td>7360.0</td>\n",
       "      <td>...</td>\n",
       "      <td>132.335</td>\n",
       "      <td>56.867</td>\n",
       "      <td>0.55263</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.11763</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>L</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79980</th>\n",
       "      <td>1822.0</td>\n",
       "      <td>0.5851</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23685.0</td>\n",
       "      <td>23685.0</td>\n",
       "      <td>208174.0</td>\n",
       "      <td>55719.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.81438</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79981</th>\n",
       "      <td>1693.0</td>\n",
       "      <td>0.1828</td>\n",
       "      <td>17.767</td>\n",
       "      <td>2.024</td>\n",
       "      <td>0.000</td>\n",
       "      <td>114.0</td>\n",
       "      <td>27514.0</td>\n",
       "      <td>384.0</td>\n",
       "      <td>2329.0</td>\n",
       "      <td>48080.0</td>\n",
       "      <td>...</td>\n",
       "      <td>74.814</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.17857</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.53340</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79982</th>\n",
       "      <td>1735.0</td>\n",
       "      <td>3.1701</td>\n",
       "      <td>0.260</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>117.0</td>\n",
       "      <td>892.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>3766.0</td>\n",
       "      <td>1265.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>99.026</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.96747</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>C</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79983</th>\n",
       "      <td>1671.0</td>\n",
       "      <td>0.1380</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>491.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>491.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.80000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79984</th>\n",
       "      <td>1924.0</td>\n",
       "      <td>0.1221</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>2478.0</td>\n",
       "      <td>266683.0</td>\n",
       "      <td>266683.0</td>\n",
       "      <td>405300.0</td>\n",
       "      <td>390558.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.799</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.75322</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79985</th>\n",
       "      <td>1670.0</td>\n",
       "      <td>0.0347</td>\n",
       "      <td>9.836</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>212.0</td>\n",
       "      <td>7848.0</td>\n",
       "      <td>491.0</td>\n",
       "      <td>29785.0</td>\n",
       "      <td>16226.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>78.700</td>\n",
       "      <td>0.13636</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.85771</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79986</th>\n",
       "      <td>1901.0</td>\n",
       "      <td>0.1782</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4955.0</td>\n",
       "      <td>21753.0</td>\n",
       "      <td>12673.0</td>\n",
       "      <td>70293.0</td>\n",
       "      <td>62980.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>61.301</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.86356</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79987</th>\n",
       "      <td>1835.0</td>\n",
       "      <td>0.5372</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>29723.0</td>\n",
       "      <td>3964.0</td>\n",
       "      <td>66770.0</td>\n",
       "      <td>85900.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.41685</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79988</th>\n",
       "      <td>1927.0</td>\n",
       "      <td>0.0410</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>22000.0</td>\n",
       "      <td>30046.0</td>\n",
       "      <td>24165.0</td>\n",
       "      <td>75019.0</td>\n",
       "      <td>88343.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.444</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.53750</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79989</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.1451</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.50000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79990</th>\n",
       "      <td>1941.0</td>\n",
       "      <td>0.4834</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10846.0</td>\n",
       "      <td>52806.0</td>\n",
       "      <td>35478.0</td>\n",
       "      <td>136461.0</td>\n",
       "      <td>176240.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.05882</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.84170</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79991</th>\n",
       "      <td>1899.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>7310.0</td>\n",
       "      <td>14519.0</td>\n",
       "      <td>14519.0</td>\n",
       "      <td>5252.0</td>\n",
       "      <td>4949.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.44615</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79992</th>\n",
       "      <td>1761.0</td>\n",
       "      <td>2.0999</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>47.0</td>\n",
       "      <td>13477.0</td>\n",
       "      <td>1814.0</td>\n",
       "      <td>9320.0</td>\n",
       "      <td>2500.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.12500</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.73640</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>C</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79993</th>\n",
       "      <td>1700.0</td>\n",
       "      <td>0.3831</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>344.0</td>\n",
       "      <td>344.0</td>\n",
       "      <td>344.0</td>\n",
       "      <td>991.0</td>\n",
       "      <td>344.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.66667</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.97374</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>C</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79994</th>\n",
       "      <td>1910.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4955.0</td>\n",
       "      <td>47306.0</td>\n",
       "      <td>47306.0</td>\n",
       "      <td>88124.0</td>\n",
       "      <td>107148.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.79867</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79995</th>\n",
       "      <td>1736.0</td>\n",
       "      <td>2.1740</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>11.0</td>\n",
       "      <td>4248.0</td>\n",
       "      <td>1577.0</td>\n",
       "      <td>13379.0</td>\n",
       "      <td>6671.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>78.378</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.43829</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79996</th>\n",
       "      <td>1724.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.108</td>\n",
       "      <td>0.768</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>64041.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10926.0</td>\n",
       "      <td>84839.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38.325</td>\n",
       "      <td>0.16667</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.57931</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79997</th>\n",
       "      <td>1605.0</td>\n",
       "      <td>0.2901</td>\n",
       "      <td>11.561</td>\n",
       "      <td>0.937</td>\n",
       "      <td>2.976</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2277.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3964.0</td>\n",
       "      <td>5709.0</td>\n",
       "      <td>...</td>\n",
       "      <td>101.850</td>\n",
       "      <td>93.142</td>\n",
       "      <td>0.50000</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.42069</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>C</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79998</th>\n",
       "      <td>1780.0</td>\n",
       "      <td>1.1874</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6356.0</td>\n",
       "      <td>4802.0</td>\n",
       "      <td>3206.0</td>\n",
       "      <td>18180.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77.022</td>\n",
       "      <td>0.06061</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.53251</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>L</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79999</th>\n",
       "      <td>1727.0</td>\n",
       "      <td>1.9288</td>\n",
       "      <td>1.441</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25773.0</td>\n",
       "      <td>2869.0</td>\n",
       "      <td>132985.0</td>\n",
       "      <td>71788.0</td>\n",
       "      <td>...</td>\n",
       "      <td>32.400</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.07143</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.68482</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>C</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>80000 rows × 49 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        mvar1   mvar2   mvar3  mvar4  mvar5    mvar6     mvar7     mvar8  \\\n",
       "0      1696.0  1.6541   0.000  0.000  0.000      0.0    6015.0     322.0   \n",
       "1      1846.0  0.8095   0.000  0.000  0.000    102.0    7532.0    3171.0   \n",
       "2      1745.0  0.4001   0.000  0.000  0.000      NaN    2536.0       NaN   \n",
       "3      1739.0  0.2193   0.000  0.000  0.000   1982.0   26440.0    4955.0   \n",
       "4      1787.0  0.0118   0.225  0.000  0.000   5451.0    5494.0    5494.0   \n",
       "5      1579.0     NaN   3.502  0.000  0.000      NaN       NaN       NaN   \n",
       "6      1818.0  0.4001   0.000  0.000  0.000      NaN    1088.0       NaN   \n",
       "7         NaN     NaN     NaN    NaN    NaN      NaN       NaN       NaN   \n",
       "8      1836.0  0.1358   0.000  0.000  0.000    347.0   38964.0   17828.0   \n",
       "9      1839.0  0.1981   0.000  0.000  0.000    793.0    6131.0    6045.0   \n",
       "10     1903.0  0.0000   0.000  0.000  0.000     22.0   19518.0    9910.0   \n",
       "11     1681.0  1.5888   5.685  3.566  0.000     93.0    3554.0     439.0   \n",
       "12     1841.0  0.5388   0.000  0.000  0.000   1487.0   19449.0   19449.0   \n",
       "13     1794.0  1.9684   0.000  0.000  0.000    856.0    8609.0    8609.0   \n",
       "14     1669.0  3.8558  18.465  6.292  1.200      NaN     142.0       NaN   \n",
       "15     1583.0  3.0284  16.325  0.000  0.000      NaN       NaN       NaN   \n",
       "16     1899.0  0.0970   0.000  0.000  0.000   1015.0   13379.0   13379.0   \n",
       "17     1690.0  8.7747  10.437  0.000  0.000    122.0     623.0     299.0   \n",
       "18     1599.0  0.8601   1.525  1.525  0.000      NaN     878.0       NaN   \n",
       "19     1859.0  0.0155   0.368  0.000  0.000    424.0   86509.0   12451.0   \n",
       "20     1880.0  2.6101   0.000  0.000  0.000      0.0   19252.0    6342.0   \n",
       "21     1852.0  3.6201   0.000  0.000  0.000    799.0   16515.0   16515.0   \n",
       "22     1655.0  3.0268  14.748  0.000  0.000     48.0      48.0      48.0   \n",
       "23     1863.0  0.0401   0.000  0.000  0.000   1487.0    4955.0    4955.0   \n",
       "24     1753.0  0.2251   0.000  0.000  0.000   1124.0    1124.0    1124.0   \n",
       "25     1894.0  0.0318   0.000  0.000  0.000   4655.0    7433.0    7433.0   \n",
       "26     1803.0  0.3993   0.000  0.000  0.000    496.0   10505.0     496.0   \n",
       "27     1932.0  0.3276   0.000  0.000  0.000   6982.0   21569.0   18829.0   \n",
       "28     1714.0  5.1904   0.770  0.000  0.000      0.0    1889.0     595.0   \n",
       "29        NaN  2.0457   4.514  0.000  0.000      NaN       NaN       NaN   \n",
       "...       ...     ...     ...    ...    ...      ...       ...       ...   \n",
       "79970  1834.0  1.2164   0.000  0.000  0.000   2212.0    5244.0    4203.0   \n",
       "79971  1729.0  1.3696   0.000  0.000  0.000    356.0    4218.0    1982.0   \n",
       "79972  1753.0  5.8283   0.000  0.000  0.000    180.0    4014.0     617.0   \n",
       "79973  1748.0  1.9635   0.642  0.000  0.000    291.0    3469.0    3469.0   \n",
       "79974  1771.0  1.7588   0.000  0.000  0.000     66.0   12626.0    6433.0   \n",
       "79975  1766.0  0.9540   0.000  0.000  0.000   1140.0   10207.0   10207.0   \n",
       "79976  1822.0  0.0000   1.853  1.853  0.000   2581.0   13361.0    5946.0   \n",
       "79977  1824.0  0.5634   0.000  0.000  0.000   3964.0    4683.0    4683.0   \n",
       "79978  1914.0  0.0544   0.000  0.000  0.000   3469.0   20424.0   20424.0   \n",
       "79979  1600.0  2.6649  18.282  1.078  2.678      0.0    7205.0       0.0   \n",
       "79980  1822.0  0.5851   0.000  0.000  0.000      0.0   23685.0   23685.0   \n",
       "79981  1693.0  0.1828  17.767  2.024  0.000    114.0   27514.0     384.0   \n",
       "79982  1735.0  3.1701   0.260  0.000  0.000    117.0     892.0     117.0   \n",
       "79983  1671.0  0.1380   0.000  0.000  0.000      NaN     491.0       NaN   \n",
       "79984  1924.0  0.1221   0.000  0.000  0.000   2478.0  266683.0  266683.0   \n",
       "79985  1670.0  0.0347   9.836  0.000  0.000    212.0    7848.0     491.0   \n",
       "79986  1901.0  0.1782   0.000  0.000  0.000   4955.0   21753.0   12673.0   \n",
       "79987  1835.0  0.5372   0.000  0.000  0.000      0.0   29723.0    3964.0   \n",
       "79988  1927.0  0.0410   0.000  0.000  0.000  22000.0   30046.0   24165.0   \n",
       "79989     NaN  0.1451   0.000  0.000  0.000      NaN       NaN       NaN   \n",
       "79990  1941.0  0.4834   0.000  0.000  0.000  10846.0   52806.0   35478.0   \n",
       "79991  1899.0     NaN   0.000  0.000  0.000   7310.0   14519.0   14519.0   \n",
       "79992  1761.0  2.0999   0.000  0.000  0.000     47.0   13477.0    1814.0   \n",
       "79993  1700.0  0.3831   0.000  0.000  0.000    344.0     344.0     344.0   \n",
       "79994  1910.0  0.0000   0.000  0.000  0.000   4955.0   47306.0   47306.0   \n",
       "79995  1736.0  2.1740   0.000  0.000  0.000     11.0    4248.0    1577.0   \n",
       "79996  1724.0  0.0000   1.108  0.768  0.000      NaN   64041.0       NaN   \n",
       "79997  1605.0  0.2901  11.561  0.937  2.976      NaN    2277.0       NaN   \n",
       "79998  1780.0  1.1874   0.000  0.000  0.000      0.0    6356.0    4802.0   \n",
       "79999  1727.0  1.9288   1.441  0.000  0.000      0.0   25773.0    2869.0   \n",
       "\n",
       "          mvar9    mvar10 ...   mvar40  mvar41   mvar42  mvar43   mvar44  \\\n",
       "0       40369.0   18414.0 ...   73.780  82.547  0.08696    10.0  0.63899   \n",
       "1       18234.0   13664.0 ...   99.129     NaN  0.00000    13.0  0.63836   \n",
       "2           NaN    2536.0 ...      NaN  29.290  0.00000     1.0  1.00000   \n",
       "3       20316.0   37013.0 ...   96.272     NaN  0.15385     3.0  0.53241   \n",
       "4        7987.0    4696.0 ...  115.019     NaN  0.00000     1.0  0.92665   \n",
       "5           NaN       0.0 ...      NaN     NaN  1.50000     0.0      NaN   \n",
       "6        1536.0    1498.0 ...   88.171     NaN  0.00000     2.0  0.87224   \n",
       "7           NaN       NaN ...      NaN     NaN      NaN     NaN      NaN   \n",
       "8       70729.0   65843.0 ...      NaN     NaN  0.00000    10.0  0.89868   \n",
       "9       48959.0   31640.0 ...      NaN  45.590  0.08824    14.0  0.33834   \n",
       "10      90618.0  110271.0 ...      NaN     NaN  0.00000    17.0  0.80620   \n",
       "11       2527.0    7086.0 ...      NaN     NaN  0.61111     7.0  0.81172   \n",
       "12       6739.0    6612.0 ...      NaN     NaN  0.00000     5.0  0.98031   \n",
       "13      60545.0   24893.0 ...      NaN     NaN  0.00000    13.0  0.35724   \n",
       "14         38.0     142.0 ...  107.825  98.664  0.56000    11.0  0.29169   \n",
       "15      51450.0       0.0 ...      NaN     NaN  0.32353     2.0      NaN   \n",
       "16     246906.0   56533.0 ...   10.384     NaN  0.00000    19.0  0.47480   \n",
       "17       1140.0    2043.0 ...      NaN     NaN  0.63636     5.0  0.94951   \n",
       "18          NaN     878.0 ...      NaN  91.175  0.80000     0.0  1.00000   \n",
       "19      86635.0  142081.0 ...      NaN     NaN  0.00000    12.0  0.34730   \n",
       "20      59601.0   86906.0 ...      NaN  72.497  0.00000    14.0  0.28708   \n",
       "21     110651.0   41311.0 ...      NaN     NaN  0.00000    13.0  0.75349   \n",
       "22        198.0      48.0 ...      NaN     NaN  1.00000     1.0  1.00000   \n",
       "23      22902.0   21772.0 ...   96.895     NaN  0.00000    12.0  0.40853   \n",
       "24          0.0    1124.0 ...      NaN     NaN      NaN     0.0  1.00000   \n",
       "25      25667.0   12345.0 ...      NaN   0.000  0.00000     3.0  0.99419   \n",
       "26        991.0   18163.0 ...   91.752  87.306  0.20000     5.0  0.75289   \n",
       "27     187209.0  113813.0 ...      NaN     NaN  0.00000    11.0  0.99710   \n",
       "28      12574.0    4825.0 ...      NaN     NaN  0.35714     6.0  0.85082   \n",
       "29          NaN       0.0 ...      NaN     NaN  1.16667     0.0      NaN   \n",
       "...         ...       ... ...      ...     ...      ...     ...      ...   \n",
       "79970   16743.0   13831.0 ...      NaN  97.398  0.00000     8.0  0.58040   \n",
       "79971   18657.0    8921.0 ...      NaN  83.663  0.09091     6.0  0.62632   \n",
       "79972    3667.0    9786.0 ...      NaN  87.094  0.11111     9.0  0.59364   \n",
       "79973   13131.0   14393.0 ...      NaN  92.244  0.44000    14.0  0.83809   \n",
       "79974   27946.0   24401.0 ...      NaN  40.477  0.00000    10.0  0.46863   \n",
       "79975   55001.0   20636.0 ...      NaN     NaN  0.05000    14.0  0.54754   \n",
       "79976   31018.0   76774.0 ...   73.611  44.656  0.03448    20.0  0.23177   \n",
       "79977       NaN    8647.0 ...      NaN     NaN      NaN     NaN  0.67222   \n",
       "79978   78774.0   27856.0 ...      NaN     NaN  0.00000     8.0  1.00000   \n",
       "79979     956.0    7360.0 ...  132.335  56.867  0.55263    14.0  0.11763   \n",
       "79980  208174.0   55719.0 ...      NaN     NaN  0.00000    17.0  0.81438   \n",
       "79981    2329.0   48080.0 ...   74.814     NaN  0.17857     5.0  0.53340   \n",
       "79982    3766.0    1265.0 ...      NaN  99.026  0.00000     2.0  0.96747   \n",
       "79983       NaN     491.0 ...      NaN     NaN  0.80000     2.0  1.00000   \n",
       "79984  405300.0  390558.0 ...      NaN  70.799  0.00000    13.0  0.75322   \n",
       "79985   29785.0   16226.0 ...      NaN  78.700  0.13636    10.0  0.85771   \n",
       "79986   70293.0   62980.0 ...      NaN  61.301  0.00000    10.0  0.86356   \n",
       "79987   66770.0   85900.0 ...      NaN     NaN  0.00000     9.0  0.41685   \n",
       "79988   75019.0   88343.0 ...      NaN  19.444  0.00000     7.0  0.53750   \n",
       "79989       NaN       0.0 ...      NaN     NaN  1.50000     0.0      NaN   \n",
       "79990  136461.0  176240.0 ...      NaN     NaN  0.05882     8.0  0.84170   \n",
       "79991    5252.0    4949.0 ...      NaN     NaN  0.00000     3.0  0.44615   \n",
       "79992    9320.0    2500.0 ...      NaN     NaN  0.12500     5.0  0.73640   \n",
       "79993     991.0     344.0 ...      NaN     NaN  0.66667     2.0  0.97374   \n",
       "79994   88124.0  107148.0 ...      NaN     NaN  0.00000     4.0  0.79867   \n",
       "79995   13379.0    6671.0 ...      NaN  78.378  0.00000     4.0  0.43829   \n",
       "79996   10926.0   84839.0 ...      NaN  38.325  0.16667    14.0  0.57931   \n",
       "79997    3964.0    5709.0 ...  101.850  93.142  0.50000     4.0  0.42069   \n",
       "79998    3206.0   18180.0 ...      NaN  77.022  0.06061     9.0  0.53251   \n",
       "79999  132985.0   71788.0 ...   32.400     NaN  0.07143    12.0  0.68482   \n",
       "\n",
       "       mvar45  mvar46  mvar47  default_ind  mv  \n",
       "0         NaN     0.0       C            0   0  \n",
       "1         NaN     NaN       L            1   0  \n",
       "2         NaN     0.0       C            1   0  \n",
       "3         0.0     0.0       L            0   0  \n",
       "4         NaN     NaN       L            0   0  \n",
       "5         NaN     NaN       C            1   0  \n",
       "6         NaN     0.0       C            1   0  \n",
       "7         NaN     NaN       C            0   0  \n",
       "8         0.0     0.0       L            0   0  \n",
       "9         NaN     0.0       L            0   0  \n",
       "10        0.0     0.0       L            0   0  \n",
       "11        0.0     0.0       C            0   0  \n",
       "12        NaN     NaN       C            0   0  \n",
       "13        NaN     0.0       C            0   0  \n",
       "14        NaN     1.0       C            0   0  \n",
       "15        0.0     NaN       C            0   0  \n",
       "16        0.0     0.0       L            0   0  \n",
       "17        NaN     0.0       L            0   0  \n",
       "18        NaN     0.0       C            1   0  \n",
       "19        0.0     0.0       L            0   0  \n",
       "20        NaN     0.0       L            0   0  \n",
       "21        NaN     NaN       L            0   0  \n",
       "22        NaN     NaN       C            1   0  \n",
       "23        NaN     0.0       L            0   0  \n",
       "24        NaN     NaN       C            1   0  \n",
       "25        0.0     0.0       L            0   0  \n",
       "26        0.0     0.0       L            0   0  \n",
       "27        0.0     0.0       C            0   0  \n",
       "28        0.0     0.0       L            0   0  \n",
       "29        NaN     NaN       L            0   0  \n",
       "...       ...     ...     ...          ...  ..  \n",
       "79970     NaN     0.0       C            0   0  \n",
       "79971     0.0     0.0       C            0   0  \n",
       "79972     NaN     0.0       L            0   0  \n",
       "79973     0.0     0.0       L            0   0  \n",
       "79974     NaN     0.0       C            0   0  \n",
       "79975     NaN     NaN       C            0   0  \n",
       "79976     NaN     0.0       C            0   0  \n",
       "79977     NaN     NaN       C            0   0  \n",
       "79978     0.0     0.0       L            0   0  \n",
       "79979     NaN     0.0       L            1   0  \n",
       "79980     0.0     NaN       L            0   0  \n",
       "79981     NaN     0.0       C            0   0  \n",
       "79982     NaN     0.0       C            1   0  \n",
       "79983     NaN     NaN       C            0   0  \n",
       "79984     0.0     0.0       L            0   0  \n",
       "79985     NaN     0.0       L            0   0  \n",
       "79986     0.0     0.0       L            0   0  \n",
       "79987     0.0     0.0       L            0   0  \n",
       "79988     0.0     0.0       L            0   0  \n",
       "79989     NaN     NaN       L            0   0  \n",
       "79990     0.0     0.0       L            0   0  \n",
       "79991     NaN     NaN       L            0   0  \n",
       "79992     0.0     0.0       C            1   0  \n",
       "79993     0.0     0.0       C            1   0  \n",
       "79994     NaN     NaN       L            0   0  \n",
       "79995     NaN     0.0       C            0   0  \n",
       "79996     0.0     0.0       C            0   0  \n",
       "79997     NaN     0.0       C            1   0  \n",
       "79998     NaN     0.0       L            0   0  \n",
       "79999     0.0     0.0       C            1   0  \n",
       "\n",
       "[80000 rows x 49 columns]"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gameDf.assign(mv=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(80000, 49)\n",
      "(49, 2)\n"
     ]
    }
   ],
   "source": [
    "print(gameDf.shape)\n",
    "print(dataDict.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dic = dict(zip(dataDict.values[:, 1], dataDict.values[:, 0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'mvar25'"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dic['Average tenure of active revolving credit cards (in days)']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#remove ID column\n",
    "del gameDf[dic['Application ID (primary key)']]\n",
    "del dic['Application ID (primary key)']\n",
    "\n",
    "leaderAppID = leaderDf['application_key']\n",
    "del leaderDf['application_key']\n",
    "leaderX = leaderDf.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "gameX = gameDf.iloc[:,:-1]\n",
    "gameY = gameDf.iloc[:,-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "range(0, 80000)"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "range(gameDf[\"mvar47\"].shape[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C'"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gameX[\"mvar47\"][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#one hot encoding C=0 L=1\n",
    "gameX['mvar47'] = pd.get_dummies(gameX['mvar47'])\n",
    "leaderX['mvar47'] = pd.get_dummies(leaderX['mvar47'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('uint8')"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gameX[\"mvar47\"].dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Synthesis begins"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "gameX['mvar5'] = (1+gameX['mvar3'])*(1+gameX['mvar4'])*(1+gameX['mvar5'])\n",
    "leaderX['mvar5'] = (1+leaderX['mvar3'])*(1+leaderX['mvar4'])*(1+leaderX['mvar5'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# gameX['mvar7'] = (gameX['mvar7'] + gameX['mvar8'])#/(1+gameX['mvar6'])\n",
    "# leaderX['mvar7'] = (leaderX['mvar7'] + leaderX['mvar8'])#/(1+leaderX['mvar6'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df = gameX.copy()\n",
    "# df['mvar16'][df['mvar16'].isnull()] = -1\n",
    "# df['mvar17'][df['mvar17'].isnull()] = -1\n",
    "# df['mvar18'][df['mvar18'].isnull()] = -1\n",
    "\n",
    "# df['mvar16'] = df['mvar16']+df['mvar17']+df['mvar18']\n",
    "\n",
    "# df['mvar16'][df['mvar16']>0] = 0.5265\n",
    "# df['mvar16'][df['mvar16']==0] = 0.1763\n",
    "# df['mvar16'][df['mvar16']==-1] = 0.2594\n",
    "# df['mvar16'][df['mvar16']==-2] = 0.2594\n",
    "# df['mvar16'][df['mvar16']==-3] = 0.4423\n",
    "\n",
    "# gameX = df.copy()\n",
    "\n",
    "# df = leaderX.copy()\n",
    "# df['mvar16'][df['mvar16'].isnull()] = -1\n",
    "# df['mvar17'][df['mvar17'].isnull()] = -1\n",
    "# df['mvar18'][df['mvar18'].isnull()] = -1\n",
    "\n",
    "# df['mvar16'] = df['mvar16']+df['mvar17']+df['mvar18']\n",
    "\n",
    "# df['mvar16'][df['mvar16']>0] = 0.5265\n",
    "# df['mvar16'][df['mvar16']==0] = 0.1763\n",
    "# df['mvar16'][df['mvar16']==-1] = 0.2594\n",
    "# df['mvar16'][df['mvar16']==-2] = 0.2594\n",
    "# df['mvar16'][df['mvar16']==-3] = 0.4423\n",
    "\n",
    "# leaderX = df.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# gameX['mvar23'] = gameX['mvar23'] - gameX['mvar22']\n",
    "# leaderX['mvar23'] = leaderX['mvar23'] - leaderX['mvar22']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ekka/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \n",
      "/home/ekka/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n",
      "/home/ekka/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:14: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \n",
      "/home/ekka/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:15: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  from ipykernel import kernelapp as app\n"
     ]
    }
   ],
   "source": [
    "df = gameX.copy()\n",
    "df['mvar26'][df['mvar26'].isnull()] = -365\n",
    "df['mvar27'][df['mvar27'].isnull()] = -365\n",
    "df['mvar26'] = (df['mvar26']+df['mvar27'])/2/365\n",
    "df['mvar26'] = df['mvar26'].astype('int64')\n",
    "\n",
    "df[df['mvar26']<0] = 0.4026\n",
    "df['mvar26'][(df['mvar26']>=0) & (df['mvar26']<=5)] = 0.3243\n",
    "df['mvar26'][df['mvar26']>5] = 0.1562\n",
    "\n",
    "gameX = df.copy()\n",
    "\n",
    "df = leaderX.copy()\n",
    "df['mvar26'][df['mvar26'].isnull()] = -365\n",
    "df['mvar27'][df['mvar27'].isnull()] = -365\n",
    "df['mvar26'] = (df['mvar26']+df['mvar27'])/2/365\n",
    "df['mvar26'] = df['mvar26'].astype('int64')\n",
    "\n",
    "df[df['mvar26']<0] = 0.4026\n",
    "df['mvar26'][(df['mvar26']>=0) & (df['mvar26']<=5)] = 0.3243\n",
    "df['mvar26'][df['mvar26']>5] = 0.1562\n",
    "\n",
    "leaderX = df.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#drop\n",
    "df = gameX.copy() \n",
    "leader_df = leaderX.copy()\n",
    "drop_target = ['mvar27']\n",
    "#number of misssing values\n",
    "# for i in df.columns:\n",
    "#     if (100*(80000-gameDf[i].describe()['count'])/80000) > "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for i in drop_target:\n",
    "    del df[i]\n",
    "    del leader_df[i]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['mvar1', 'mvar2', 'mvar3', 'mvar4', 'mvar5', 'mvar6', 'mvar7', 'mvar8',\n",
       "       'mvar9', 'mvar10', 'mvar11', 'mvar12', 'mvar13', 'mvar14', 'mvar15',\n",
       "       'mvar16', 'mvar17', 'mvar18', 'mvar19', 'mvar20', 'mvar21', 'mvar22',\n",
       "       'mvar23', 'mvar24', 'mvar25', 'mvar26', 'mvar28', 'mvar29', 'mvar30',\n",
       "       'mvar31', 'mvar32', 'mvar33', 'mvar34', 'mvar35', 'mvar36', 'mvar37',\n",
       "       'mvar38', 'mvar39', 'mvar40', 'mvar41', 'mvar42', 'mvar43', 'mvar44',\n",
       "       'mvar45', 'mvar46', 'mvar47'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "leader_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "gameX = df\n",
    "leaderX = leader_df "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Synthesis Ends"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mvar1</th>\n",
       "      <th>mvar2</th>\n",
       "      <th>mvar3</th>\n",
       "      <th>mvar4</th>\n",
       "      <th>mvar5</th>\n",
       "      <th>mvar6</th>\n",
       "      <th>mvar7</th>\n",
       "      <th>mvar8</th>\n",
       "      <th>mvar9</th>\n",
       "      <th>mvar10</th>\n",
       "      <th>...</th>\n",
       "      <th>mvar38</th>\n",
       "      <th>mvar39</th>\n",
       "      <th>mvar40</th>\n",
       "      <th>mvar41</th>\n",
       "      <th>mvar42</th>\n",
       "      <th>mvar43</th>\n",
       "      <th>mvar44</th>\n",
       "      <th>mvar45</th>\n",
       "      <th>mvar46</th>\n",
       "      <th>mvar47</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1753.0000</td>\n",
       "      <td>0.500100</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>206.000000</td>\n",
       "      <td>19179.00000</td>\n",
       "      <td>206.000000</td>\n",
       "      <td>14221.000000</td>\n",
       "      <td>19438.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>20.551000</td>\n",
       "      <td>0.42105</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>0.85661</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1894.0000</td>\n",
       "      <td>1.970100</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>297.000000</td>\n",
       "      <td>19820.00000</td>\n",
       "      <td>19820.000000</td>\n",
       "      <td>176895.000000</td>\n",
       "      <td>66346.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>63.047000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>15.0000</td>\n",
       "      <td>0.94391</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1774.0000</td>\n",
       "      <td>0.171800</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>197.000000</td>\n",
       "      <td>2563.00000</td>\n",
       "      <td>877.000000</td>\n",
       "      <td>8869.000000</td>\n",
       "      <td>3637.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>83.797000</td>\n",
       "      <td>0.33333</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>0.76467</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1586.0000</td>\n",
       "      <td>0.112300</td>\n",
       "      <td>5.2990</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1326.791111</td>\n",
       "      <td>15922.63461</td>\n",
       "      <td>5751.609254</td>\n",
       "      <td>30449.229689</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0.132286</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>1.50000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.65601</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.134822</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1832.0000</td>\n",
       "      <td>1.444200</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>179.000000</td>\n",
       "      <td>7577.00000</td>\n",
       "      <td>179.000000</td>\n",
       "      <td>21059.000000</td>\n",
       "      <td>20306.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>96.052000</td>\n",
       "      <td>66.665000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>23.0000</td>\n",
       "      <td>0.79190</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1838.0000</td>\n",
       "      <td>0.054400</td>\n",
       "      <td>0.2410</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>882.000000</td>\n",
       "      <td>14039.00000</td>\n",
       "      <td>10976.000000</td>\n",
       "      <td>278941.000000</td>\n",
       "      <td>74030.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>77.780000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>21.0000</td>\n",
       "      <td>0.92462</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1743.0000</td>\n",
       "      <td>1.075300</td>\n",
       "      <td>0.2720</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>397.000000</td>\n",
       "      <td>16141.00000</td>\n",
       "      <td>3568.000000</td>\n",
       "      <td>69482.000000</td>\n",
       "      <td>56755.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>67.159000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>14.0000</td>\n",
       "      <td>0.71347</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1935.0000</td>\n",
       "      <td>0.560100</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>496.000000</td>\n",
       "      <td>44919.00000</td>\n",
       "      <td>17115.000000</td>\n",
       "      <td>124814.000000</td>\n",
       "      <td>124167.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>15.0000</td>\n",
       "      <td>0.92403</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1885.0000</td>\n",
       "      <td>0.081100</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>7369.000000</td>\n",
       "      <td>19264.00000</td>\n",
       "      <td>19264.000000</td>\n",
       "      <td>59956.000000</td>\n",
       "      <td>26633.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>0.89760</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.134822</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1730.0000</td>\n",
       "      <td>0.744400</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2103.00000</td>\n",
       "      <td>582.000000</td>\n",
       "      <td>16429.000000</td>\n",
       "      <td>9197.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.05882</td>\n",
       "      <td>14.0000</td>\n",
       "      <td>0.40529</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1731.0000</td>\n",
       "      <td>0.509700</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>2433.000000</td>\n",
       "      <td>8673.00000</td>\n",
       "      <td>8673.000000</td>\n",
       "      <td>6739.000000</td>\n",
       "      <td>7388.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.23529</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0.64242</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.134822</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1755.0000</td>\n",
       "      <td>0.301300</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>261.000000</td>\n",
       "      <td>4051.00000</td>\n",
       "      <td>261.000000</td>\n",
       "      <td>297.000000</td>\n",
       "      <td>261.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.33333</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>0.99142</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1739.0000</td>\n",
       "      <td>2.290900</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7620.00000</td>\n",
       "      <td>7620.000000</td>\n",
       "      <td>64983.000000</td>\n",
       "      <td>14067.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>11.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>95.000000</td>\n",
       "      <td>0.05882</td>\n",
       "      <td>16.0000</td>\n",
       "      <td>0.44167</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1562.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>34.6110</td>\n",
       "      <td>3.7845</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1326.791111</td>\n",
       "      <td>18.00000</td>\n",
       "      <td>5751.609254</td>\n",
       "      <td>198.000000</td>\n",
       "      <td>18.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>124.910000</td>\n",
       "      <td>99.934000</td>\n",
       "      <td>0.87500</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0.84592</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1798.0000</td>\n",
       "      <td>5.082500</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>259.000000</td>\n",
       "      <td>3359.00000</td>\n",
       "      <td>2973.000000</td>\n",
       "      <td>22099.000000</td>\n",
       "      <td>13507.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>76.881000</td>\n",
       "      <td>0.05882</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>0.43365</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.40260</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>...</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.40260</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.40260</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.4026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1789.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.4280</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>2478.000000</td>\n",
       "      <td>13874.00000</td>\n",
       "      <td>13874.000000</td>\n",
       "      <td>98011.000000</td>\n",
       "      <td>56200.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.05000</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>0.51231</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.134822</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1862.0000</td>\n",
       "      <td>0.240100</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1487.000000</td>\n",
       "      <td>12310.00000</td>\n",
       "      <td>3964.000000</td>\n",
       "      <td>7928.000000</td>\n",
       "      <td>26564.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>77.419000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>7.0000</td>\n",
       "      <td>0.56685</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1767.0000</td>\n",
       "      <td>0.300100</td>\n",
       "      <td>1.5140</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>991.000000</td>\n",
       "      <td>2478.00000</td>\n",
       "      <td>2478.000000</td>\n",
       "      <td>8790.000000</td>\n",
       "      <td>6065.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.10000</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>0.65601</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.134822</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1802.0000</td>\n",
       "      <td>0.636400</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>96.000000</td>\n",
       "      <td>18759.00000</td>\n",
       "      <td>10905.000000</td>\n",
       "      <td>51037.000000</td>\n",
       "      <td>58544.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>58.972000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>9.0000</td>\n",
       "      <td>0.59409</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1780.0000</td>\n",
       "      <td>1.955900</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>191.000000</td>\n",
       "      <td>12525.00000</td>\n",
       "      <td>12525.000000</td>\n",
       "      <td>18932.000000</td>\n",
       "      <td>14602.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>7.0000</td>\n",
       "      <td>0.92752</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1714.0000</td>\n",
       "      <td>2.266400</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>1671.00000</td>\n",
       "      <td>57.000000</td>\n",
       "      <td>396.000000</td>\n",
       "      <td>2582.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>91.666000</td>\n",
       "      <td>0.37500</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>0.34836</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1923.0000</td>\n",
       "      <td>0.088000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>5946.000000</td>\n",
       "      <td>53893.00000</td>\n",
       "      <td>24739.000000</td>\n",
       "      <td>128435.000000</td>\n",
       "      <td>125679.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>90.429000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>9.0000</td>\n",
       "      <td>0.88554</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1743.0000</td>\n",
       "      <td>1.720800</td>\n",
       "      <td>2.2950</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>159.000000</td>\n",
       "      <td>3621.00000</td>\n",
       "      <td>2323.000000</td>\n",
       "      <td>9018.000000</td>\n",
       "      <td>9649.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>82.323000</td>\n",
       "      <td>0.10000</td>\n",
       "      <td>9.0000</td>\n",
       "      <td>0.59442</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1700.0000</td>\n",
       "      <td>1.660500</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1037.00000</td>\n",
       "      <td>46.000000</td>\n",
       "      <td>892.000000</td>\n",
       "      <td>1235.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.20000</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>0.94826</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1922.0000</td>\n",
       "      <td>1.011805</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>4524.000000</td>\n",
       "      <td>15530.00000</td>\n",
       "      <td>14819.000000</td>\n",
       "      <td>116154.000000</td>\n",
       "      <td>100684.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>12.0000</td>\n",
       "      <td>0.91550</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1777.0000</td>\n",
       "      <td>0.412000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>369.000000</td>\n",
       "      <td>6201.00000</td>\n",
       "      <td>6201.000000</td>\n",
       "      <td>66477.000000</td>\n",
       "      <td>34053.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.03846</td>\n",
       "      <td>23.0000</td>\n",
       "      <td>0.15159</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.134822</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1811.0000</td>\n",
       "      <td>0.911700</td>\n",
       "      <td>0.4100</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.4100</td>\n",
       "      <td>297.000000</td>\n",
       "      <td>27717.00000</td>\n",
       "      <td>9815.000000</td>\n",
       "      <td>110001.000000</td>\n",
       "      <td>69683.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>74.996000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>15.0000</td>\n",
       "      <td>0.56671</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1658.0000</td>\n",
       "      <td>2.382900</td>\n",
       "      <td>37.1270</td>\n",
       "      <td>10.3678</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>396.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6566.000000</td>\n",
       "      <td>4068.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>14.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.57692</td>\n",
       "      <td>8.0000</td>\n",
       "      <td>0.35339</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1827.0000</td>\n",
       "      <td>0.280100</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>678.000000</td>\n",
       "      <td>1189.00000</td>\n",
       "      <td>1189.000000</td>\n",
       "      <td>892.000000</td>\n",
       "      <td>2065.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.134822</td>\n",
       "      <td>1.0000</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>24970</th>\n",
       "      <td>1734.0000</td>\n",
       "      <td>0.927900</td>\n",
       "      <td>0.5200</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>256.000000</td>\n",
       "      <td>11643.00000</td>\n",
       "      <td>1524.000000</td>\n",
       "      <td>16748.000000</td>\n",
       "      <td>25359.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>10.0000</td>\n",
       "      <td>0.38078</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24971</th>\n",
       "      <td>1849.0000</td>\n",
       "      <td>1.830500</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>2251.000000</td>\n",
       "      <td>33275.00000</td>\n",
       "      <td>7505.000000</td>\n",
       "      <td>44843.000000</td>\n",
       "      <td>47453.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>91.701000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>4.0000</td>\n",
       "      <td>0.92111</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24972</th>\n",
       "      <td>1739.0000</td>\n",
       "      <td>1.525100</td>\n",
       "      <td>2.7270</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>2.7270</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>2129.00000</td>\n",
       "      <td>720.000000</td>\n",
       "      <td>5896.000000</td>\n",
       "      <td>5206.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>109.251000</td>\n",
       "      <td>94.127000</td>\n",
       "      <td>0.36842</td>\n",
       "      <td>12.0000</td>\n",
       "      <td>0.52903</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24973</th>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.40260</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>...</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.40260</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.40260</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.4026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24974</th>\n",
       "      <td>1709.0000</td>\n",
       "      <td>3.680100</td>\n",
       "      <td>7.5830</td>\n",
       "      <td>3.1371</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>297.000000</td>\n",
       "      <td>8132.00000</td>\n",
       "      <td>297.000000</td>\n",
       "      <td>1041.000000</td>\n",
       "      <td>6960.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>32.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>81.029000</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.59459</td>\n",
       "      <td>11.0000</td>\n",
       "      <td>0.42680</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24975</th>\n",
       "      <td>1890.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1982.000000</td>\n",
       "      <td>15162.00000</td>\n",
       "      <td>15162.000000</td>\n",
       "      <td>68181.000000</td>\n",
       "      <td>43334.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>98.043000</td>\n",
       "      <td>55.197000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>15.0000</td>\n",
       "      <td>0.27143</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24976</th>\n",
       "      <td>1727.0000</td>\n",
       "      <td>1.844800</td>\n",
       "      <td>15.1810</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>2234.000000</td>\n",
       "      <td>2754.00000</td>\n",
       "      <td>2234.000000</td>\n",
       "      <td>2676.000000</td>\n",
       "      <td>6539.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.66667</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>0.87890</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24977</th>\n",
       "      <td>1789.0000</td>\n",
       "      <td>1.299400</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>364.000000</td>\n",
       "      <td>17838.00000</td>\n",
       "      <td>17838.000000</td>\n",
       "      <td>8424.000000</td>\n",
       "      <td>22307.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>109.307000</td>\n",
       "      <td>75.052000</td>\n",
       "      <td>0.15385</td>\n",
       "      <td>8.0000</td>\n",
       "      <td>0.69694</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24978</th>\n",
       "      <td>1706.0000</td>\n",
       "      <td>0.499700</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>98.000000</td>\n",
       "      <td>297.00000</td>\n",
       "      <td>98.000000</td>\n",
       "      <td>546.000000</td>\n",
       "      <td>643.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.66667</td>\n",
       "      <td>4.0000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24979</th>\n",
       "      <td>1638.0000</td>\n",
       "      <td>4.680200</td>\n",
       "      <td>16.7510</td>\n",
       "      <td>2.6642</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1326.791111</td>\n",
       "      <td>7937.00000</td>\n",
       "      <td>5751.609254</td>\n",
       "      <td>3032.000000</td>\n",
       "      <td>10489.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>102.709000</td>\n",
       "      <td>13.882000</td>\n",
       "      <td>0.50000</td>\n",
       "      <td>4.0000</td>\n",
       "      <td>0.72640</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24980</th>\n",
       "      <td>1855.0000</td>\n",
       "      <td>1.996500</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>350.000000</td>\n",
       "      <td>30203.00000</td>\n",
       "      <td>22656.000000</td>\n",
       "      <td>168999.000000</td>\n",
       "      <td>166720.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>12.0000</td>\n",
       "      <td>0.74106</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.134822</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24981</th>\n",
       "      <td>1790.0000</td>\n",
       "      <td>0.205000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>237.000000</td>\n",
       "      <td>18018.00000</td>\n",
       "      <td>13297.000000</td>\n",
       "      <td>3914.000000</td>\n",
       "      <td>1305.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.20000</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>0.41582</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24982</th>\n",
       "      <td>1546.0000</td>\n",
       "      <td>0.349100</td>\n",
       "      <td>50.8030</td>\n",
       "      <td>4.2695</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1326.791111</td>\n",
       "      <td>15922.63461</td>\n",
       "      <td>5751.609254</td>\n",
       "      <td>3330.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.70370</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24983</th>\n",
       "      <td>1777.0000</td>\n",
       "      <td>3.962900</td>\n",
       "      <td>0.9680</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>23707.00000</td>\n",
       "      <td>23707.000000</td>\n",
       "      <td>33432.000000</td>\n",
       "      <td>19640.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>80.934000</td>\n",
       "      <td>0.04000</td>\n",
       "      <td>15.0000</td>\n",
       "      <td>0.64752</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24984</th>\n",
       "      <td>1943.0000</td>\n",
       "      <td>1.011805</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>24775.00000</td>\n",
       "      <td>24775.000000</td>\n",
       "      <td>80772.000000</td>\n",
       "      <td>69483.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>6.0000</td>\n",
       "      <td>0.97068</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.134822</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24985</th>\n",
       "      <td>1691.0000</td>\n",
       "      <td>0.166300</td>\n",
       "      <td>1.9790</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9591.00000</td>\n",
       "      <td>2627.000000</td>\n",
       "      <td>46903.000000</td>\n",
       "      <td>30402.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>84.801000</td>\n",
       "      <td>63.855000</td>\n",
       "      <td>0.03448</td>\n",
       "      <td>14.0000</td>\n",
       "      <td>0.43441</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24986</th>\n",
       "      <td>1681.0000</td>\n",
       "      <td>0.173900</td>\n",
       "      <td>9.0060</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>6.5680</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3004.00000</td>\n",
       "      <td>2251.000000</td>\n",
       "      <td>6818.000000</td>\n",
       "      <td>7783.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>96.309000</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.71429</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>0.88908</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24987</th>\n",
       "      <td>1723.0000</td>\n",
       "      <td>1.057000</td>\n",
       "      <td>0.2850</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>248.000000</td>\n",
       "      <td>28479.00000</td>\n",
       "      <td>28479.000000</td>\n",
       "      <td>16352.000000</td>\n",
       "      <td>3117.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>6.0000</td>\n",
       "      <td>0.72344</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24988</th>\n",
       "      <td>1693.0000</td>\n",
       "      <td>1.214500</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>100.00000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>991.000000</td>\n",
       "      <td>118.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>0.36619</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.134822</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24989</th>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.40260</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>...</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.40260</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.40260</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.4026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24990</th>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.40260</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>...</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.40260</td>\n",
       "      <td>0.4026</td>\n",
       "      <td>0.40260</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.402600</td>\n",
       "      <td>0.4026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24991</th>\n",
       "      <td>1740.0000</td>\n",
       "      <td>0.390100</td>\n",
       "      <td>4.3220</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>490.000000</td>\n",
       "      <td>29460.00000</td>\n",
       "      <td>9449.000000</td>\n",
       "      <td>42047.000000</td>\n",
       "      <td>31583.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.20000</td>\n",
       "      <td>4.0000</td>\n",
       "      <td>0.88957</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24992</th>\n",
       "      <td>1651.0000</td>\n",
       "      <td>2.490900</td>\n",
       "      <td>1.3350</td>\n",
       "      <td>0.9108</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>3163.00000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1982.000000</td>\n",
       "      <td>3167.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>82.382000</td>\n",
       "      <td>0.61538</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>0.93745</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24993</th>\n",
       "      <td>1729.0000</td>\n",
       "      <td>1.360100</td>\n",
       "      <td>0.2180</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5675.00000</td>\n",
       "      <td>167.000000</td>\n",
       "      <td>15071.000000</td>\n",
       "      <td>10305.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.23810</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>0.71866</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24994</th>\n",
       "      <td>1730.0000</td>\n",
       "      <td>1.670100</td>\n",
       "      <td>5.5540</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>104.000000</td>\n",
       "      <td>5692.00000</td>\n",
       "      <td>496.000000</td>\n",
       "      <td>4410.000000</td>\n",
       "      <td>8125.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>79.485000</td>\n",
       "      <td>0.30769</td>\n",
       "      <td>4.0000</td>\n",
       "      <td>0.93312</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24995</th>\n",
       "      <td>1715.0000</td>\n",
       "      <td>12.000200</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1326.791111</td>\n",
       "      <td>991.00000</td>\n",
       "      <td>5751.609254</td>\n",
       "      <td>8751.000000</td>\n",
       "      <td>1814.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.07692</td>\n",
       "      <td>4.0000</td>\n",
       "      <td>0.65601</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24996</th>\n",
       "      <td>1800.0000</td>\n",
       "      <td>0.055100</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>5946.000000</td>\n",
       "      <td>14867.00000</td>\n",
       "      <td>9613.000000</td>\n",
       "      <td>46490.000000</td>\n",
       "      <td>44722.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.05882</td>\n",
       "      <td>8.0000</td>\n",
       "      <td>0.99859</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24997</th>\n",
       "      <td>1686.0000</td>\n",
       "      <td>1.330100</td>\n",
       "      <td>2.0250</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>2.0250</td>\n",
       "      <td>1326.791111</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>5751.609254</td>\n",
       "      <td>4582.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>124.171000</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.30000</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>0.77519</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.134822</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24998</th>\n",
       "      <td>1826.0000</td>\n",
       "      <td>1.011805</td>\n",
       "      <td>0.4280</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>3568.000000</td>\n",
       "      <td>26277.00000</td>\n",
       "      <td>9058.000000</td>\n",
       "      <td>72739.000000</td>\n",
       "      <td>86797.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>50.119000</td>\n",
       "      <td>0.03333</td>\n",
       "      <td>11.0000</td>\n",
       "      <td>0.40343</td>\n",
       "      <td>0.146538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24999</th>\n",
       "      <td>1916.0000</td>\n",
       "      <td>0.139400</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>18889.000000</td>\n",
       "      <td>18889.00000</td>\n",
       "      <td>18889.000000</td>\n",
       "      <td>28343.000000</td>\n",
       "      <td>51174.0000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.700697</td>\n",
       "      <td>49.621102</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>0.99663</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25000 rows × 46 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           mvar1      mvar2    mvar3    mvar4   mvar5         mvar6  \\\n",
       "0      1753.0000   0.500100   0.0000   0.0000  0.0000    206.000000   \n",
       "1      1894.0000   1.970100   0.0000   0.0000  0.0000    297.000000   \n",
       "2      1774.0000   0.171800   0.0000   0.0000  0.0000    197.000000   \n",
       "3      1586.0000   0.112300   5.2990   0.0000  0.0000   1326.791111   \n",
       "4      1832.0000   1.444200   0.0000   0.0000  0.0000    179.000000   \n",
       "5      1838.0000   0.054400   0.2410   0.0000  0.0000    882.000000   \n",
       "6      1743.0000   1.075300   0.2720   0.0000  0.0000    397.000000   \n",
       "7      1935.0000   0.560100   0.0000   0.0000  0.0000    496.000000   \n",
       "8      1885.0000   0.081100   0.0000   0.0000  0.0000   7369.000000   \n",
       "9      1730.0000   0.744400   0.0000   0.0000  0.0000      0.000000   \n",
       "10     1731.0000   0.509700   0.0000   0.0000  0.0000   2433.000000   \n",
       "11     1755.0000   0.301300   0.0000   0.0000  0.0000    261.000000   \n",
       "12     1739.0000   2.290900   0.0000   0.0000  0.0000      0.000000   \n",
       "13     1562.0000   0.000000  34.6110   3.7845  0.0000   1326.791111   \n",
       "14     1798.0000   5.082500   0.0000   0.0000  0.0000    259.000000   \n",
       "15        0.4026   0.402600   0.4026   0.4026  0.4026      0.402600   \n",
       "16     1789.0000   0.000000   1.4280   0.0000  0.0000   2478.000000   \n",
       "17     1862.0000   0.240100   0.0000   0.0000  0.0000   1487.000000   \n",
       "18     1767.0000   0.300100   1.5140   0.0000  0.0000    991.000000   \n",
       "19     1802.0000   0.636400   0.0000   0.0000  0.0000     96.000000   \n",
       "20     1780.0000   1.955900   0.0000   0.0000  0.0000    191.000000   \n",
       "21     1714.0000   2.266400   0.0000   0.0000  0.0000     31.000000   \n",
       "22     1923.0000   0.088000   0.0000   0.0000  0.0000   5946.000000   \n",
       "23     1743.0000   1.720800   2.2950   0.0000  0.0000    159.000000   \n",
       "24     1700.0000   1.660500   0.0000   0.0000  0.0000      0.000000   \n",
       "25     1922.0000   1.011805   0.0000   0.0000  0.0000   4524.000000   \n",
       "26     1777.0000   0.412000   0.0000   0.0000  0.0000    369.000000   \n",
       "27     1811.0000   0.911700   0.4100   0.0000  0.4100    297.000000   \n",
       "28     1658.0000   2.382900  37.1270  10.3678  0.0000      0.000000   \n",
       "29     1827.0000   0.280100   0.0000   0.0000  0.0000    678.000000   \n",
       "...          ...        ...      ...      ...     ...           ...   \n",
       "24970  1734.0000   0.927900   0.5200   0.0000  0.0000    256.000000   \n",
       "24971  1849.0000   1.830500   0.0000   0.0000  0.0000   2251.000000   \n",
       "24972  1739.0000   1.525100   2.7270   0.0000  2.7270      8.000000   \n",
       "24973     0.4026   0.402600   0.4026   0.4026  0.4026      0.402600   \n",
       "24974  1709.0000   3.680100   7.5830   3.1371  0.0000    297.000000   \n",
       "24975  1890.0000   0.000000   0.0000   0.0000  0.0000   1982.000000   \n",
       "24976  1727.0000   1.844800  15.1810   0.0000  0.0000   2234.000000   \n",
       "24977  1789.0000   1.299400   0.0000   0.0000  0.0000    364.000000   \n",
       "24978  1706.0000   0.499700   0.0000   0.0000  0.0000     98.000000   \n",
       "24979  1638.0000   4.680200  16.7510   2.6642  0.0000   1326.791111   \n",
       "24980  1855.0000   1.996500   0.0000   0.0000  0.0000    350.000000   \n",
       "24981  1790.0000   0.205000   0.0000   0.0000  0.0000    237.000000   \n",
       "24982  1546.0000   0.349100  50.8030   4.2695  0.0000   1326.791111   \n",
       "24983  1777.0000   3.962900   0.9680   0.0000  0.0000     14.000000   \n",
       "24984  1943.0000   1.011805   0.0000   0.0000  0.0000      0.000000   \n",
       "24985  1691.0000   0.166300   1.9790   0.0000  0.0000      0.000000   \n",
       "24986  1681.0000   0.173900   9.0060   0.0000  6.5680      0.000000   \n",
       "24987  1723.0000   1.057000   0.2850   0.0000  0.0000    248.000000   \n",
       "24988  1693.0000   1.214500   0.0000   0.0000  0.0000     18.000000   \n",
       "24989     0.4026   0.402600   0.4026   0.4026  0.4026      0.402600   \n",
       "24990     0.4026   0.402600   0.4026   0.4026  0.4026      0.402600   \n",
       "24991  1740.0000   0.390100   4.3220   0.0000  0.0000    490.000000   \n",
       "24992  1651.0000   2.490900   1.3350   0.9108  0.0000      4.000000   \n",
       "24993  1729.0000   1.360100   0.2180   0.0000  0.0000      0.000000   \n",
       "24994  1730.0000   1.670100   5.5540   0.0000  0.0000    104.000000   \n",
       "24995  1715.0000  12.000200   0.0000   0.0000  0.0000   1326.791111   \n",
       "24996  1800.0000   0.055100   0.0000   0.0000  0.0000   5946.000000   \n",
       "24997  1686.0000   1.330100   2.0250   0.0000  2.0250   1326.791111   \n",
       "24998  1826.0000   1.011805   0.4280   0.0000  0.0000   3568.000000   \n",
       "24999  1916.0000   0.139400   0.0000   0.0000  0.0000  18889.000000   \n",
       "\n",
       "             mvar7         mvar8          mvar9       mvar10   ...     mvar38  \\\n",
       "0      19179.00000    206.000000   14221.000000   19438.0000   ...     1.0000   \n",
       "1      19820.00000  19820.000000  176895.000000   66346.0000   ...     3.0000   \n",
       "2       2563.00000    877.000000    8869.000000    3637.0000   ...     1.0000   \n",
       "3      15922.63461   5751.609254   30449.229689       0.0000   ...     1.0000   \n",
       "4       7577.00000    179.000000   21059.000000   20306.0000   ...     3.0000   \n",
       "5      14039.00000  10976.000000  278941.000000   74030.0000   ...     4.0000   \n",
       "6      16141.00000   3568.000000   69482.000000   56755.0000   ...     6.0000   \n",
       "7      44919.00000  17115.000000  124814.000000  124167.0000   ...     9.0000   \n",
       "8      19264.00000  19264.000000   59956.000000   26633.0000   ...     1.0000   \n",
       "9       2103.00000    582.000000   16429.000000    9197.0000   ...     9.0000   \n",
       "10      8673.00000   8673.000000    6739.000000    7388.0000   ...     2.0000   \n",
       "11      4051.00000    261.000000     297.000000     261.0000   ...     3.0000   \n",
       "12      7620.00000   7620.000000   64983.000000   14067.0000   ...    11.0000   \n",
       "13        18.00000   5751.609254     198.000000      18.0000   ...     7.0000   \n",
       "14      3359.00000   2973.000000   22099.000000   13507.0000   ...     5.0000   \n",
       "15         0.40260      0.402600       0.402600       0.4026   ...     0.4026   \n",
       "16     13874.00000  13874.000000   98011.000000   56200.0000   ...     4.0000   \n",
       "17     12310.00000   3964.000000    7928.000000   26564.0000   ...     6.0000   \n",
       "18      2478.00000   2478.000000    8790.000000    6065.0000   ...     1.0000   \n",
       "19     18759.00000  10905.000000   51037.000000   58544.0000   ...     3.0000   \n",
       "20     12525.00000  12525.000000   18932.000000   14602.0000   ...     7.0000   \n",
       "21      1671.00000     57.000000     396.000000    2582.0000   ...     6.0000   \n",
       "22     53893.00000  24739.000000  128435.000000  125679.0000   ...     2.0000   \n",
       "23      3621.00000   2323.000000    9018.000000    9649.0000   ...     8.0000   \n",
       "24      1037.00000     46.000000     892.000000    1235.0000   ...     5.0000   \n",
       "25     15530.00000  14819.000000  116154.000000  100684.0000   ...     3.0000   \n",
       "26      6201.00000   6201.000000   66477.000000   34053.0000   ...    12.0000   \n",
       "27     27717.00000   9815.000000  110001.000000   69683.0000   ...     3.0000   \n",
       "28       396.00000      0.000000    6566.000000    4068.0000   ...    14.0000   \n",
       "29      1189.00000   1189.000000     892.000000    2065.0000   ...     3.0000   \n",
       "...            ...           ...            ...          ...   ...        ...   \n",
       "24970  11643.00000   1524.000000   16748.000000   25359.0000   ...     7.0000   \n",
       "24971  33275.00000   7505.000000   44843.000000   47453.0000   ...     2.0000   \n",
       "24972   2129.00000    720.000000    5896.000000    5206.0000   ...     6.0000   \n",
       "24973      0.40260      0.402600       0.402600       0.4026   ...     0.4026   \n",
       "24974   8132.00000    297.000000    1041.000000    6960.0000   ...    32.0000   \n",
       "24975  15162.00000  15162.000000   68181.000000   43334.0000   ...     2.0000   \n",
       "24976   2754.00000   2234.000000    2676.000000    6539.0000   ...     4.0000   \n",
       "24977  17838.00000  17838.000000    8424.000000   22307.0000   ...     5.0000   \n",
       "24978    297.00000     98.000000     546.000000     643.0000   ...     7.0000   \n",
       "24979   7937.00000   5751.609254    3032.000000   10489.0000   ...     3.0000   \n",
       "24980  30203.00000  22656.000000  168999.000000  166720.0000   ...     2.0000   \n",
       "24981  18018.00000  13297.000000    3914.000000    1305.0000   ...     5.0000   \n",
       "24982  15922.63461   5751.609254    3330.000000       0.0000   ...     8.0000   \n",
       "24983  23707.00000  23707.000000   33432.000000   19640.0000   ...    12.0000   \n",
       "24984  24775.00000  24775.000000   80772.000000   69483.0000   ...     0.0000   \n",
       "24985   9591.00000   2627.000000   46903.000000   30402.0000   ...     5.0000   \n",
       "24986   3004.00000   2251.000000    6818.000000    7783.0000   ...     1.0000   \n",
       "24987  28479.00000  28479.000000   16352.000000    3117.0000   ...     7.0000   \n",
       "24988    100.00000    100.000000     991.000000     118.0000   ...     3.0000   \n",
       "24989      0.40260      0.402600       0.402600       0.4026   ...     0.4026   \n",
       "24990      0.40260      0.402600       0.402600       0.4026   ...     0.4026   \n",
       "24991  29460.00000   9449.000000   42047.000000   31583.0000   ...     3.0000   \n",
       "24992   3163.00000      4.000000    1982.000000    3167.0000   ...    10.0000   \n",
       "24993   5675.00000    167.000000   15071.000000   10305.0000   ...     5.0000   \n",
       "24994   5692.00000    496.000000    4410.000000    8125.0000   ...     5.0000   \n",
       "24995    991.00000   5751.609254    8751.000000    1814.0000   ...     1.0000   \n",
       "24996  14867.00000   9613.000000   46490.000000   44722.0000   ...     4.0000   \n",
       "24997      0.00000   5751.609254    4582.000000       0.0000   ...     0.0000   \n",
       "24998  26277.00000   9058.000000   72739.000000   86797.0000   ...     2.0000   \n",
       "24999  18889.00000  18889.000000   28343.000000   51174.0000   ...     0.0000   \n",
       "\n",
       "         mvar39      mvar40      mvar41   mvar42   mvar43   mvar44    mvar45  \\\n",
       "0      0.000000   57.700697   20.551000  0.42105   3.0000  0.85661  0.146538   \n",
       "1      0.000000   57.700697   63.047000  0.00000  15.0000  0.94391  0.000000   \n",
       "2      0.000000   57.700697   83.797000  0.33333   3.0000  0.76467  0.000000   \n",
       "3      0.132286   57.700697   49.621102  1.50000   0.0000  0.65601  0.146538   \n",
       "4      0.000000   96.052000   66.665000  0.00000  23.0000  0.79190  0.000000   \n",
       "5      0.000000   57.700697   77.780000  0.00000  21.0000  0.92462  0.000000   \n",
       "6      0.000000   57.700697   67.159000  0.00000  14.0000  0.71347  0.000000   \n",
       "7      0.000000   57.700697   49.621102  0.00000  15.0000  0.92403  0.000000   \n",
       "8      0.000000   57.700697   49.621102  0.00000   5.0000  0.89760  0.000000   \n",
       "9      0.000000   57.700697   49.621102  0.05882  14.0000  0.40529  0.146538   \n",
       "10     0.000000   57.700697   49.621102  0.23529   1.0000  0.64242  0.000000   \n",
       "11     0.000000   57.700697   49.621102  0.33333   2.0000  0.99142  0.146538   \n",
       "12     0.000000   57.700697   95.000000  0.05882  16.0000  0.44167  0.146538   \n",
       "13     1.000000  124.910000   99.934000  0.87500   1.0000  0.84592  1.000000   \n",
       "14     0.000000   57.700697   76.881000  0.05882  13.0000  0.43365  0.000000   \n",
       "15     0.402600    0.402600    0.402600  0.40260   0.4026  0.40260  0.402600   \n",
       "16     0.000000   57.700697   49.621102  0.05000  13.0000  0.51231  0.146538   \n",
       "17     0.000000   57.700697   77.419000  0.00000   7.0000  0.56685  0.000000   \n",
       "18     0.000000   57.700697   49.621102  0.10000   3.0000  0.65601  0.146538   \n",
       "19     0.000000   57.700697   58.972000  0.00000   9.0000  0.59409  0.000000   \n",
       "20     0.000000   57.700697  100.000000  0.00000   7.0000  0.92752  0.000000   \n",
       "21     0.000000   57.700697   91.666000  0.37500   5.0000  0.34836  0.146538   \n",
       "22     0.000000   57.700697   90.429000  0.00000   9.0000  0.88554  0.000000   \n",
       "23     0.000000   57.700697   82.323000  0.10000   9.0000  0.59442  0.146538   \n",
       "24     0.000000   57.700697   49.621102  0.20000   5.0000  0.94826  0.146538   \n",
       "25     0.000000   57.700697   49.621102  0.00000  12.0000  0.91550  0.000000   \n",
       "26     0.000000   57.700697   49.621102  0.03846  23.0000  0.15159  0.146538   \n",
       "27     0.000000   57.700697   74.996000  0.00000  15.0000  0.56671  0.000000   \n",
       "28     0.000000   57.700697   49.621102  0.57692   8.0000  0.35339  0.146538   \n",
       "29     0.000000   57.700697   49.621102  0.00000   2.0000  1.00000  0.146538   \n",
       "...         ...         ...         ...      ...      ...      ...       ...   \n",
       "24970  0.000000   57.700697   49.621102  0.00000  10.0000  0.38078  0.146538   \n",
       "24971  0.000000   57.700697   91.701000  0.00000   4.0000  0.92111  0.000000   \n",
       "24972  0.000000  109.251000   94.127000  0.36842  12.0000  0.52903  0.146538   \n",
       "24973  0.402600    0.402600    0.402600  0.40260   0.4026  0.40260  0.402600   \n",
       "24974  0.000000   81.029000   49.621102  0.59459  11.0000  0.42680  0.146538   \n",
       "24975  0.000000   98.043000   55.197000  0.00000  15.0000  0.27143  0.146538   \n",
       "24976  0.000000   57.700697   49.621102  0.66667   5.0000  0.87890  0.000000   \n",
       "24977  0.000000  109.307000   75.052000  0.15385   8.0000  0.69694  0.000000   \n",
       "24978  0.000000   57.700697   49.621102  0.66667   4.0000  1.00000  0.146538   \n",
       "24979  1.000000  102.709000   13.882000  0.50000   4.0000  0.72640  0.146538   \n",
       "24980  0.000000   57.700697   49.621102  0.00000  12.0000  0.74106  0.000000   \n",
       "24981  0.000000   57.700697   49.621102  0.20000   2.0000  0.41582  0.146538   \n",
       "24982  0.000000   57.700697   49.621102  0.70370   2.0000  1.00000  1.000000   \n",
       "24983  0.000000   57.700697   80.934000  0.04000  15.0000  0.64752  0.146538   \n",
       "24984  0.000000   57.700697   49.621102  0.00000   6.0000  0.97068  0.000000   \n",
       "24985  0.000000   84.801000   63.855000  0.03448  14.0000  0.43441  0.146538   \n",
       "24986  1.000000   96.309000   49.621102  0.71429   2.0000  0.88908  0.000000   \n",
       "24987  0.000000   57.700697   49.621102  0.00000   6.0000  0.72344  0.146538   \n",
       "24988  0.000000   57.700697   49.621102  0.00000   3.0000  0.36619  0.146538   \n",
       "24989  0.402600    0.402600    0.402600  0.40260   0.4026  0.40260  0.402600   \n",
       "24990  0.402600    0.402600    0.402600  0.40260   0.4026  0.40260  0.402600   \n",
       "24991  0.000000   57.700697   49.621102  0.20000   4.0000  0.88957  1.000000   \n",
       "24992  0.000000   57.700697   82.382000  0.61538   3.0000  0.93745  0.146538   \n",
       "24993  0.000000   57.700697   49.621102  0.23810  13.0000  0.71866  0.146538   \n",
       "24994  0.000000   57.700697   79.485000  0.30769   4.0000  0.93312  0.146538   \n",
       "24995  0.000000   57.700697   49.621102  0.07692   4.0000  0.65601  0.146538   \n",
       "24996  0.000000   57.700697   49.621102  0.05882   8.0000  0.99859  0.000000   \n",
       "24997  0.000000  124.171000   49.621102  0.30000   2.0000  0.77519  0.146538   \n",
       "24998  0.000000   57.700697   50.119000  0.03333  11.0000  0.40343  0.146538   \n",
       "24999  0.000000   57.700697   49.621102  0.00000   5.0000  0.99663  0.000000   \n",
       "\n",
       "         mvar46  mvar47  \n",
       "0      0.000000  0.0000  \n",
       "1      0.000000  1.0000  \n",
       "2      0.000000  1.0000  \n",
       "3      0.134822  1.0000  \n",
       "4      0.000000  0.0000  \n",
       "5      0.000000  0.0000  \n",
       "6      0.000000  0.0000  \n",
       "7      0.000000  0.0000  \n",
       "8      0.134822  0.0000  \n",
       "9      0.000000  1.0000  \n",
       "10     0.134822  1.0000  \n",
       "11     0.000000  1.0000  \n",
       "12     0.000000  1.0000  \n",
       "13     1.000000  1.0000  \n",
       "14     0.000000  1.0000  \n",
       "15     0.402600  0.4026  \n",
       "16     0.134822  0.0000  \n",
       "17     0.000000  1.0000  \n",
       "18     0.134822  1.0000  \n",
       "19     0.000000  1.0000  \n",
       "20     0.000000  1.0000  \n",
       "21     0.000000  1.0000  \n",
       "22     0.000000  1.0000  \n",
       "23     0.000000  1.0000  \n",
       "24     0.000000  0.0000  \n",
       "25     0.000000  0.0000  \n",
       "26     0.134822  1.0000  \n",
       "27     0.000000  1.0000  \n",
       "28     2.000000  1.0000  \n",
       "29     0.134822  1.0000  \n",
       "...         ...     ...  \n",
       "24970  0.000000  0.0000  \n",
       "24971  0.000000  0.0000  \n",
       "24972  0.000000  1.0000  \n",
       "24973  0.402600  0.4026  \n",
       "24974  2.000000  1.0000  \n",
       "24975  0.000000  1.0000  \n",
       "24976  0.000000  1.0000  \n",
       "24977  0.000000  0.0000  \n",
       "24978  0.000000  1.0000  \n",
       "24979  0.000000  1.0000  \n",
       "24980  0.134822  0.0000  \n",
       "24981  0.000000  1.0000  \n",
       "24982  1.000000  1.0000  \n",
       "24983  0.000000  0.0000  \n",
       "24984  0.134822  1.0000  \n",
       "24985  0.000000  1.0000  \n",
       "24986  0.000000  1.0000  \n",
       "24987  0.000000  1.0000  \n",
       "24988  0.134822  1.0000  \n",
       "24989  0.402600  0.4026  \n",
       "24990  0.402600  0.4026  \n",
       "24991  0.000000  0.0000  \n",
       "24992  0.000000  0.0000  \n",
       "24993  0.000000  1.0000  \n",
       "24994  0.000000  1.0000  \n",
       "24995  0.000000  1.0000  \n",
       "24996  0.000000  0.0000  \n",
       "24997  0.134822  0.0000  \n",
       "24998  0.000000  1.0000  \n",
       "24999  0.000000  1.0000  \n",
       "\n",
       "[25000 rows x 46 columns]"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Missing values median\n",
    "gameX.fillna(gameX.mean(),inplace = True)\n",
    "leaderX.fillna(gameX.mean(),inplace = True)\n",
    "\n",
    "# gameX.fillna(0,inplace = True)\n",
    "# leaderX.fillna(0,inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#LR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:586: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n"
     ]
    }
   ],
   "source": [
    "from sklearn import preprocessing as prep\n",
    "\n",
    "scaler_list = []\n",
    "for i in gameX.columns:\n",
    "    scaler_list.append(prep.StandardScaler().fit(gameX[i]))\n",
    "    \n",
    "# prep.StandardScaler()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n"
     ]
    }
   ],
   "source": [
    "gameX_scaled = gameX.copy()\n",
    "\n",
    "for i in enumerate(gameX_scaled.columns):\n",
    "    gameX_scaled[i[1]] = scaler_list[i[0]].transform(gameX_scaled[i[1]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n",
      "/home/ekka/.local/lib/python3.6/site-packages/sklearn/preprocessing/data.py:649: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n"
     ]
    }
   ],
   "source": [
    "leaderX_scaled = leaderX.copy()\n",
    "\n",
    "for i in enumerate(leaderX_scaled.columns):\n",
    "    leaderX_scaled[i[1]] = scaler_list[i[0]].transform(leaderX_scaled[i[1]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Logistic Regression\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "clf = LogisticRegression(random_state=1, solver='lbfgs', multi_class='multinomial').fit(gameX_scaled, gameY)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pred1 = clf.predict_proba(leaderX_scaled)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.23254498,  0.12911522,  0.02314096, -0.01349574, -0.02214058,\n",
       "        -0.05890112,  0.09286405, -0.01314557,  0.05988206, -0.19265974,\n",
       "        -0.00931814,  0.04132023, -0.12685122,  0.00379907, -0.04532831,\n",
       "         0.02927441, -0.04275745,  0.0917262 , -0.01789015,  0.09849082,\n",
       "         0.07070302,  0.03321807,  0.03443124, -0.00086519, -0.07157274,\n",
       "         0.04013005, -0.0241332 , -0.02164531, -0.01712484, -0.01577965,\n",
       "         0.06094214, -0.0145639 ,  0.07336454,  0.04002169,  0.05847573,\n",
       "        -0.15066967,  0.04693071,  0.0037816 ,  0.08108407,  0.04245738,\n",
       "         0.12351599, -0.13275628, -0.0075014 ,  0.04811523,  0.04892993,\n",
       "         0.22590358]])"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.coef_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 46)"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.coef_.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Method 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#current"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import xgboost as xgb\n",
    "from xgboost.sklearn import XGBClassifier\n",
    "from sklearn import cross_validation, metrics   #Additional scklearn functions\n",
    "from sklearn.grid_search import GridSearchCV   #Perforing grid search\n",
    "\n",
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def modelfit(alg, dtrainX, dtrainY, predictors, useTrainCV=True, cv_folds=4, early_stopping_rounds=50):\n",
    "    \n",
    "    if useTrainCV:\n",
    "        xgb_param = alg.get_xgb_params()\n",
    "#         xgb_param['num_class']=2\n",
    "        xgtrain = xgb.DMatrix(dtrainX[predictors].values, label=dtrainY.values)\n",
    "        cvresult = xgb.cv(xgb_param, xgtrain, num_boost_round=alg.get_params()['n_estimators'], nfold=cv_folds,\n",
    "             early_stopping_rounds=early_stopping_rounds,stratified=True)\n",
    "        alg.set_params(n_estimators=cvresult.shape[0])\n",
    "    \n",
    "    #Fit the algorithm on the data\n",
    "    alg.fit(dtrainX[predictors], dtrainY ,eval_metric='error')\n",
    "        \n",
    "    #Predict training set:\n",
    "    dtrain_predictions = alg.predict(dtrainX[predictors])\n",
    "    dtrain_predprob = alg.predict_proba(dtrainX[predictors])[:,1]\n",
    "        \n",
    "    #Print model report:\n",
    "    print (\"\\nModel Report\")\n",
    "    print (\"Accuracy : %.4g\" % metrics.accuracy_score(dtrainY.values, dtrain_predictions))\n",
    "    #print (\"AUC Score (Train): %f\" % metrics.roc_auc_score(dtrain[target], dtrain_predprob))\n",
    "                    \n",
    "    #feat_imp = pd.Series(alg.booster().get_fscore()).sort_values(ascending=False)\n",
    "    #feat_imp.plot(kind='bar', title='Feature Importances')\n",
    "    #plt.ylabel('Feature Importance Score')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Model Report\n",
      "Accuracy : 0.8031\n",
      "time 59.74672055244446\n"
     ]
    }
   ],
   "source": [
    "#Choose all predictors except target & IDcols\n",
    "t=time.time()\n",
    "predictors = [x for x in gameX.columns]\n",
    "xgb1 = XGBClassifier(\n",
    " learning_rate =0.1,\n",
    " n_estimators=1000,\n",
    " max_depth=4, #4\n",
    " min_child_weight=1,\n",
    " gamma=0,\n",
    "reg_alpha = 0.05,\n",
    " subsample=0.8,\n",
    " colsample_bytree=0.8,\n",
    " objective= 'binary:logistic',\n",
    " nthread=4,\n",
    " scale_pos_weight=1,\n",
    " seed=27)\n",
    "\n",
    "modelfit(xgb1, gameX, gameY, predictors)\n",
    "\n",
    "print('time',time.time()-t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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7zlb3PLKoO9dSjrT4SmZ+JSLeTZnG82lKZ/T3gT+PiNWZ+UFzl33u\nEGvuJDciAnZ9FWhEPBS4F+UrLN8DPB34d8o30rypyj0lIu6dmZ+OiOdSvgXh9sXIHWLN5g4zd4g1\nm9tv7hBrNneYuUOs2dxh5g6xZnP7ze07Wz3KJTAXbrlcgN8FLquu7wf8EXAuu75C8h7m7j25Q6y5\ny1zgwcAVlG8t+BhwUnX/Y4F/oTSrXwh8gHLiukP3ZO4QazZ3mLlDrNlctwlzl0fuEGs2d5i5Q6zZ\n3OFuE176uezxApbTBbg/cCWwobr9VOCVVCcBNnfvyh1izV3lAk+jHKn0JMpho1uB04EDq8c3A2+o\nrp8EnL4nc4dYs7nDzB1izea6TZi7PHKHWLO5w8wdYs3mDneb8NLfZY8XsNwuwDOBa801d6g1d5EL\n/ABlrvGjqtvPqHYAx1a31wFXA6uXQu4QazZ3mLlDrNlctwlzl0fuEGs2d5i5Q6zZ3OFuE176u+zx\nApbbhfIV4r9EOXn4Pubu3blDrLmrXAYwVW7oNZs7zNwh1myu24S5yyN3iDWbO8zcIdZs7nC3CS/9\nXPw2tI5l5rcy802ZeWdWXwdo7t6b22f2AHJ/D1gbERsycyfw18DdgTuq/+frSyx3iDWbO8zcIdZs\nbr+5Q6zZ3GHmDrFmc4eZO8Saze03t+9sda3r7pMXL168jC4s4alyy6Vmc4eZO8SazXWbMHd55A6x\nZnOHmTvEms0d7jbhpfvLyrlbSJLUibcAd0bEPgDZ3RFQfeX2mW2uuYuVbe4wc/vMNtfcxco219zF\nyjZ3mLl9Z6tDkaW7J0mSJEmSJHnOIkmSJEmSJO1is0iSJEmSJEk1m0WSJEmSJEmq2SySJEmSJElS\nzWaRJEmSJEmSajaLJEmSJEmSVLNZJEmSJEmSpJrNIkmSJEmSJNX+P1vgRnAkspfGAAAAAElFTkSu\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd7f70a6128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# XGB feature imp\n",
    "plt.figure(figsize=(20, 4))\n",
    "plt.bar(range(1, len(xgb1.feature_importances_)+1), xgb1.feature_importances_)\n",
    "plt.xticks(range(1, len(xgb1.feature_importances_)), gameX.columns, rotation = 30)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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FmP1Jrq2Jy5M83Vp7ovuUtLckebi19tOjzhwAAACA0a15ZFFr7bmqujHJ3Um2JLm9tXao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\nAAAA6GkWAQAAAND7/85sLAccanVdAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd7f7231c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# XGB feature imp\n",
    "plt.figure(figsize=(20, 4))\n",
    "plt.bar(range(1, len(xgb1.feature_importances_)+1), xgb1.feature_importances_)\n",
    "plt.xticks(range(1, len(xgb1.feature_importances_)+1))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pred2 = xgb1.predict_proba(leaderX)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(25000, 3)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(25000, 3)"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred1 = pd.DataFrame(pred1)\n",
    "pred1['application_key'] = leaderAppID\n",
    "print(pred1.shape)\n",
    "\n",
    "pred2= pd.DataFrame(pred2)\n",
    "pred2['application_key'] = leaderAppID\n",
    "pred2.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>application_key</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.805953</td>\n",
       "      <td>0.194047</td>\n",
       "      <td>350053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.814798</td>\n",
       "      <td>0.185202</td>\n",
       "      <td>350054</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.690012</td>\n",
       "      <td>0.309988</td>\n",
       "      <td>350055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.484395</td>\n",
       "      <td>0.515605</td>\n",
       "      <td>350056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.786378</td>\n",
       "      <td>0.213622</td>\n",
       "      <td>350057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.895944</td>\n",
       "      <td>0.104056</td>\n",
       "      <td>350058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.824150</td>\n",
       "      <td>0.175850</td>\n",
       "      <td>350059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.913333</td>\n",
       "      <td>0.086667</td>\n",
       "      <td>350060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.888937</td>\n",
       "      <td>0.111063</td>\n",
       "      <td>350061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.660489</td>\n",
       "      <td>0.339511</td>\n",
       "      <td>350062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.748244</td>\n",
       "      <td>0.251756</td>\n",
       "      <td>350063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.658690</td>\n",
       "      <td>0.341310</td>\n",
       "      <td>350064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.598820</td>\n",
       "      <td>0.401180</td>\n",
       "      <td>350065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.351856</td>\n",
       "      <td>0.648144</td>\n",
       "      <td>350066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.630162</td>\n",
       "      <td>0.369838</td>\n",
       "      <td>350067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.547285</td>\n",
       "      <td>0.452715</td>\n",
       "      <td>350068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.890880</td>\n",
       "      <td>0.109120</td>\n",
       "      <td>350069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.750293</td>\n",
       "      <td>0.249707</td>\n",
       "      <td>350070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.690454</td>\n",
       "      <td>0.309546</td>\n",
       "      <td>350071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.749010</td>\n",
       "      <td>0.250990</td>\n",
       "      <td>350072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.655203</td>\n",
       "      <td>0.344797</td>\n",
       "      <td>350073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.576396</td>\n",
       "      <td>0.423604</td>\n",
       "      <td>350074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.868260</td>\n",
       "      <td>0.131740</td>\n",
       "      <td>350075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.632694</td>\n",
       "      <td>0.367306</td>\n",
       "      <td>350076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.638418</td>\n",
       "      <td>0.361582</td>\n",
       "      <td>350077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.911660</td>\n",
       "      <td>0.088340</td>\n",
       "      <td>350078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.713747</td>\n",
       "      <td>0.286253</td>\n",
       "      <td>350079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.795531</td>\n",
       "      <td>0.204469</td>\n",
       "      <td>350080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.166935</td>\n",
       "      <td>0.833065</td>\n",
       "      <td>350081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.710889</td>\n",
       "      <td>0.289111</td>\n",
       "      <td>350082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>24970</th>\n",
       "      <td>0.728927</td>\n",
       "      <td>0.271073</td>\n",
       "      <td>375023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24971</th>\n",
       "      <td>0.812861</td>\n",
       "      <td>0.187139</td>\n",
       "      <td>375024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24972</th>\n",
       "      <td>0.519807</td>\n",
       "      <td>0.480193</td>\n",
       "      <td>375025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24973</th>\n",
       "      <td>0.547285</td>\n",
       "      <td>0.452715</td>\n",
       "      <td>375026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24974</th>\n",
       "      <td>0.332155</td>\n",
       "      <td>0.667845</td>\n",
       "      <td>375027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24975</th>\n",
       "      <td>0.806560</td>\n",
       "      <td>0.193440</td>\n",
       "      <td>375028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24976</th>\n",
       "      <td>0.665297</td>\n",
       "      <td>0.334703</td>\n",
       "      <td>375029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24977</th>\n",
       "      <td>0.804608</td>\n",
       "      <td>0.195392</td>\n",
       "      <td>375030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24978</th>\n",
       "      <td>0.596608</td>\n",
       "      <td>0.403392</td>\n",
       "      <td>375031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24979</th>\n",
       "      <td>0.472976</td>\n",
       "      <td>0.527024</td>\n",
       "      <td>375032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24980</th>\n",
       "      <td>0.922078</td>\n",
       "      <td>0.077922</td>\n",
       "      <td>375033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24981</th>\n",
       "      <td>0.701327</td>\n",
       "      <td>0.298673</td>\n",
       "      <td>375034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24982</th>\n",
       "      <td>0.437983</td>\n",
       "      <td>0.562017</td>\n",
       "      <td>375035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24983</th>\n",
       "      <td>0.720221</td>\n",
       "      <td>0.279779</td>\n",
       "      <td>375036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24984</th>\n",
       "      <td>0.826380</td>\n",
       "      <td>0.173620</td>\n",
       "      <td>375037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24985</th>\n",
       "      <td>0.551238</td>\n",
       "      <td>0.448762</td>\n",
       "      <td>375038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24986</th>\n",
       "      <td>0.579872</td>\n",
       "      <td>0.420128</td>\n",
       "      <td>375039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24987</th>\n",
       "      <td>0.615924</td>\n",
       "      <td>0.384076</td>\n",
       "      <td>375040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24988</th>\n",
       "      <td>0.539457</td>\n",
       "      <td>0.460543</td>\n",
       "      <td>375041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24989</th>\n",
       "      <td>0.547285</td>\n",
       "      <td>0.452715</td>\n",
       "      <td>375042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24990</th>\n",
       "      <td>0.547285</td>\n",
       "      <td>0.452715</td>\n",
       "      <td>375043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24991</th>\n",
       "      <td>0.818910</td>\n",
       "      <td>0.181090</td>\n",
       "      <td>375044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24992</th>\n",
       "      <td>0.583733</td>\n",
       "      <td>0.416267</td>\n",
       "      <td>375045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24993</th>\n",
       "      <td>0.603559</td>\n",
       "      <td>0.396441</td>\n",
       "      <td>375046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24994</th>\n",
       "      <td>0.658967</td>\n",
       "      <td>0.341033</td>\n",
       "      <td>375047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24995</th>\n",
       "      <td>0.472732</td>\n",
       "      <td>0.527268</td>\n",
       "      <td>375048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24996</th>\n",
       "      <td>0.872474</td>\n",
       "      <td>0.127526</td>\n",
       "      <td>375049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24997</th>\n",
       "      <td>0.737880</td>\n",
       "      <td>0.262120</td>\n",
       "      <td>375050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24998</th>\n",
       "      <td>0.793153</td>\n",
       "      <td>0.206847</td>\n",
       "      <td>375051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24999</th>\n",
       "      <td>0.883190</td>\n",
       "      <td>0.116810</td>\n",
       "      <td>375052</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25000 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              0         1  application_key\n",
       "0      0.805953  0.194047           350053\n",
       "1      0.814798  0.185202           350054\n",
       "2      0.690012  0.309988           350055\n",
       "3      0.484395  0.515605           350056\n",
       "4      0.786378  0.213622           350057\n",
       "5      0.895944  0.104056           350058\n",
       "6      0.824150  0.175850           350059\n",
       "7      0.913333  0.086667           350060\n",
       "8      0.888937  0.111063           350061\n",
       "9      0.660489  0.339511           350062\n",
       "10     0.748244  0.251756           350063\n",
       "11     0.658690  0.341310           350064\n",
       "12     0.598820  0.401180           350065\n",
       "13     0.351856  0.648144           350066\n",
       "14     0.630162  0.369838           350067\n",
       "15     0.547285  0.452715           350068\n",
       "16     0.890880  0.109120           350069\n",
       "17     0.750293  0.249707           350070\n",
       "18     0.690454  0.309546           350071\n",
       "19     0.749010  0.250990           350072\n",
       "20     0.655203  0.344797           350073\n",
       "21     0.576396  0.423604           350074\n",
       "22     0.868260  0.131740           350075\n",
       "23     0.632694  0.367306           350076\n",
       "24     0.638418  0.361582           350077\n",
       "25     0.911660  0.088340           350078\n",
       "26     0.713747  0.286253           350079\n",
       "27     0.795531  0.204469           350080\n",
       "28     0.166935  0.833065           350081\n",
       "29     0.710889  0.289111           350082\n",
       "...         ...       ...              ...\n",
       "24970  0.728927  0.271073           375023\n",
       "24971  0.812861  0.187139           375024\n",
       "24972  0.519807  0.480193           375025\n",
       "24973  0.547285  0.452715           375026\n",
       "24974  0.332155  0.667845           375027\n",
       "24975  0.806560  0.193440           375028\n",
       "24976  0.665297  0.334703           375029\n",
       "24977  0.804608  0.195392           375030\n",
       "24978  0.596608  0.403392           375031\n",
       "24979  0.472976  0.527024           375032\n",
       "24980  0.922078  0.077922           375033\n",
       "24981  0.701327  0.298673           375034\n",
       "24982  0.437983  0.562017           375035\n",
       "24983  0.720221  0.279779           375036\n",
       "24984  0.826380  0.173620           375037\n",
       "24985  0.551238  0.448762           375038\n",
       "24986  0.579872  0.420128           375039\n",
       "24987  0.615924  0.384076           375040\n",
       "24988  0.539457  0.460543           375041\n",
       "24989  0.547285  0.452715           375042\n",
       "24990  0.547285  0.452715           375043\n",
       "24991  0.818910  0.181090           375044\n",
       "24992  0.583733  0.416267           375045\n",
       "24993  0.603559  0.396441           375046\n",
       "24994  0.658967  0.341033           375047\n",
       "24995  0.472732  0.527268           375048\n",
       "24996  0.872474  0.127526           375049\n",
       "24997  0.737880  0.262120           375050\n",
       "24998  0.793153  0.206847           375051\n",
       "24999  0.883190  0.116810           375052\n",
       "\n",
       "[25000 rows x 3 columns]"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>application_key</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.952616</td>\n",
       "      <td>0.047384</td>\n",
       "      <td>350053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.955737</td>\n",
       "      <td>0.044263</td>\n",
       "      <td>350054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.878236</td>\n",
       "      <td>0.121764</td>\n",
       "      <td>350055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.328021</td>\n",
       "      <td>0.671979</td>\n",
       "      <td>350056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.927535</td>\n",
       "      <td>0.072465</td>\n",
       "      <td>350057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.994285</td>\n",
       "      <td>0.005715</td>\n",
       "      <td>350058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.927642</td>\n",
       "      <td>0.072358</td>\n",
       "      <td>350059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.994785</td>\n",
       "      <td>0.005215</td>\n",
       "      <td>350060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.992848</td>\n",
       "      <td>0.007152</td>\n",
       "      <td>350061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.743476</td>\n",
       "      <td>0.256524</td>\n",
       "      <td>350062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.928640</td>\n",
       "      <td>0.071360</td>\n",
       "      <td>350063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.784973</td>\n",
       "      <td>0.215027</td>\n",
       "      <td>350064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.590544</td>\n",
       "      <td>0.409456</td>\n",
       "      <td>350065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.163392</td>\n",
       "      <td>0.836608</td>\n",
       "      <td>350066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.723303</td>\n",
       "      <td>0.276697</td>\n",
       "      <td>350067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.598292</td>\n",
       "      <td>0.401708</td>\n",
       "      <td>350068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.982500</td>\n",
       "      <td>0.017499</td>\n",
       "      <td>350069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.921487</td>\n",
       "      <td>0.078513</td>\n",
       "      <td>350070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.862544</td>\n",
       "      <td>0.137456</td>\n",
       "      <td>350071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.902283</td>\n",
       "      <td>0.097717</td>\n",
       "      <td>350072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.785944</td>\n",
       "      <td>0.214056</td>\n",
       "      <td>350073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.649620</td>\n",
       "      <td>0.350380</td>\n",
       "      <td>350074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.985719</td>\n",
       "      <td>0.014281</td>\n",
       "      <td>350075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.776092</td>\n",
       "      <td>0.223908</td>\n",
       "      <td>350076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.692095</td>\n",
       "      <td>0.307905</td>\n",
       "      <td>350077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.995368</td>\n",
       "      <td>0.004632</td>\n",
       "      <td>350078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.859806</td>\n",
       "      <td>0.140194</td>\n",
       "      <td>350079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.937731</td>\n",
       "      <td>0.062269</td>\n",
       "      <td>350080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.085867</td>\n",
       "      <td>0.914133</td>\n",
       "      <td>350081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.881950</td>\n",
       "      <td>0.118050</td>\n",
       "      <td>350082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24970</th>\n",
       "      <td>0.891698</td>\n",
       "      <td>0.108302</td>\n",
       "      <td>375023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24971</th>\n",
       "      <td>0.971281</td>\n",
       "      <td>0.028719</td>\n",
       "      <td>375024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24972</th>\n",
       "      <td>0.564072</td>\n",
       "      <td>0.435928</td>\n",
       "      <td>375025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24973</th>\n",
       "      <td>0.598292</td>\n",
       "      <td>0.401708</td>\n",
       "      <td>375026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24974</th>\n",
       "      <td>0.472214</td>\n",
       "      <td>0.527786</td>\n",
       "      <td>375027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24975</th>\n",
       "      <td>0.982343</td>\n",
       "      <td>0.017657</td>\n",
       "      <td>375028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24976</th>\n",
       "      <td>0.727652</td>\n",
       "      <td>0.272348</td>\n",
       "      <td>375029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24977</th>\n",
       "      <td>0.956359</td>\n",
       "      <td>0.043641</td>\n",
       "      <td>375030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24978</th>\n",
       "      <td>0.646009</td>\n",
       "      <td>0.353991</td>\n",
       "      <td>375031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24979</th>\n",
       "      <td>0.425163</td>\n",
       "      <td>0.574837</td>\n",
       "      <td>375032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24980</th>\n",
       "      <td>0.988938</td>\n",
       "      <td>0.011062</td>\n",
       "      <td>375033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24981</th>\n",
       "      <td>0.873576</td>\n",
       "      <td>0.126424</td>\n",
       "      <td>375034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24982</th>\n",
       "      <td>0.363672</td>\n",
       "      <td>0.636328</td>\n",
       "      <td>375035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24983</th>\n",
       "      <td>0.755035</td>\n",
       "      <td>0.244965</td>\n",
       "      <td>375036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24984</th>\n",
       "      <td>0.981636</td>\n",
       "      <td>0.018364</td>\n",
       "      <td>375037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24985</th>\n",
       "      <td>0.567252</td>\n",
       "      <td>0.432748</td>\n",
       "      <td>375038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24986</th>\n",
       "      <td>0.734355</td>\n",
       "      <td>0.265645</td>\n",
       "      <td>375039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24987</th>\n",
       "      <td>0.660228</td>\n",
       "      <td>0.339772</td>\n",
       "      <td>375040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24988</th>\n",
       "      <td>0.557059</td>\n",
       "      <td>0.442941</td>\n",
       "      <td>375041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24989</th>\n",
       "      <td>0.598292</td>\n",
       "      <td>0.401708</td>\n",
       "      <td>375042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24990</th>\n",
       "      <td>0.598292</td>\n",
       "      <td>0.401708</td>\n",
       "      <td>375043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24991</th>\n",
       "      <td>0.954752</td>\n",
       "      <td>0.045248</td>\n",
       "      <td>375044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24992</th>\n",
       "      <td>0.553086</td>\n",
       "      <td>0.446914</td>\n",
       "      <td>375045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24993</th>\n",
       "      <td>0.695369</td>\n",
       "      <td>0.304631</td>\n",
       "      <td>375046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24994</th>\n",
       "      <td>0.775216</td>\n",
       "      <td>0.224784</td>\n",
       "      <td>375047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24995</th>\n",
       "      <td>0.483811</td>\n",
       "      <td>0.516189</td>\n",
       "      <td>375048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24996</th>\n",
       "      <td>0.984299</td>\n",
       "      <td>0.015701</td>\n",
       "      <td>375049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24997</th>\n",
       "      <td>0.806394</td>\n",
       "      <td>0.193606</td>\n",
       "      <td>375050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24998</th>\n",
       "      <td>0.944818</td>\n",
       "      <td>0.055182</td>\n",
       "      <td>375051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24999</th>\n",
       "      <td>0.988183</td>\n",
       "      <td>0.011817</td>\n",
       "      <td>375052</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25000 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              0         1  application_key\n",
       "0      0.952616  0.047384           350053\n",
       "1      0.955737  0.044263           350054\n",
       "2      0.878236  0.121764           350055\n",
       "3      0.328021  0.671979           350056\n",
       "4      0.927535  0.072465           350057\n",
       "5      0.994285  0.005715           350058\n",
       "6      0.927642  0.072358           350059\n",
       "7      0.994785  0.005215           350060\n",
       "8      0.992848  0.007152           350061\n",
       "9      0.743476  0.256524           350062\n",
       "10     0.928640  0.071360           350063\n",
       "11     0.784973  0.215027           350064\n",
       "12     0.590544  0.409456           350065\n",
       "13     0.163392  0.836608           350066\n",
       "14     0.723303  0.276697           350067\n",
       "15     0.598292  0.401708           350068\n",
       "16     0.982500  0.017499           350069\n",
       "17     0.921487  0.078513           350070\n",
       "18     0.862544  0.137456           350071\n",
       "19     0.902283  0.097717           350072\n",
       "20     0.785944  0.214056           350073\n",
       "21     0.649620  0.350380           350074\n",
       "22     0.985719  0.014281           350075\n",
       "23     0.776092  0.223908           350076\n",
       "24     0.692095  0.307905           350077\n",
       "25     0.995368  0.004632           350078\n",
       "26     0.859806  0.140194           350079\n",
       "27     0.937731  0.062269           350080\n",
       "28     0.085867  0.914133           350081\n",
       "29     0.881950  0.118050           350082\n",
       "...         ...       ...              ...\n",
       "24970  0.891698  0.108302           375023\n",
       "24971  0.971281  0.028719           375024\n",
       "24972  0.564072  0.435928           375025\n",
       "24973  0.598292  0.401708           375026\n",
       "24974  0.472214  0.527786           375027\n",
       "24975  0.982343  0.017657           375028\n",
       "24976  0.727652  0.272348           375029\n",
       "24977  0.956359  0.043641           375030\n",
       "24978  0.646009  0.353991           375031\n",
       "24979  0.425163  0.574837           375032\n",
       "24980  0.988938  0.011062           375033\n",
       "24981  0.873576  0.126424           375034\n",
       "24982  0.363672  0.636328           375035\n",
       "24983  0.755035  0.244965           375036\n",
       "24984  0.981636  0.018364           375037\n",
       "24985  0.567252  0.432748           375038\n",
       "24986  0.734355  0.265645           375039\n",
       "24987  0.660228  0.339772           375040\n",
       "24988  0.557059  0.442941           375041\n",
       "24989  0.598292  0.401708           375042\n",
       "24990  0.598292  0.401708           375043\n",
       "24991  0.954752  0.045248           375044\n",
       "24992  0.553086  0.446914           375045\n",
       "24993  0.695369  0.304631           375046\n",
       "24994  0.775216  0.224784           375047\n",
       "24995  0.483811  0.516189           375048\n",
       "24996  0.984299  0.015701           375049\n",
       "24997  0.806394  0.193606           375050\n",
       "24998  0.944818  0.055182           375051\n",
       "24999  0.988183  0.011817           375052\n",
       "\n",
       "[25000 rows x 3 columns]"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pred1 = pred1.sort_values(by = 0,kind = 'mergesort',ascending = False)\n",
    "\n",
    "pred2 = pred2.sort_values(by = 0,kind = 'mergesort',ascending = False)\n",
    "# pred2 = pred2.sort_values(by = 0,kind = 'mergesort',ascending = True) #true for xgb method3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "cols = pred1.columns.tolist()\n",
    "cols = cols[-1:] + cols[:-1]\n",
    "pred1 = pred1[cols]\n",
    "\n",
    "cols = pred2.columns.tolist()\n",
    "cols = cols[-1:] + cols[:-1]\n",
    "pred2 = pred2[cols]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pred1 = pred1.loc[:,'application_key':]\n",
    "\n",
    "pred2 = pred2.loc[:,'application_key':]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "submit1 = pred1['application_key'][:10000]\n",
    "submit1 = pd.DataFrame(submit1)\n",
    "submit1[0] = 0\n",
    "\n",
    "submit2 = pred2['application_key'][:10000]\n",
    "submit2 = pd.DataFrame(submit2)\n",
    "submit2[0] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# submit.iloc[-400:, 1] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>application_key</th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>21128</th>\n",
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       "      <th>15911</th>\n",
       "      <td>365964</td>\n",
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       "    <tr>\n",
       "      <th>13848</th>\n",
       "      <td>363901</td>\n",
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       "    <tr>\n",
       "      <th>7820</th>\n",
       "      <td>357873</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23338</th>\n",
       "      <td>373391</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8558</th>\n",
       "      <td>358611</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3642</th>\n",
       "      <td>353695</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11401</th>\n",
       "      <td>361454</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21040</th>\n",
       "      <td>371093</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22990</th>\n",
       "      <td>373043</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21731</th>\n",
       "      <td>371784</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18127</th>\n",
       "      <td>368180</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19140</th>\n",
       "      <td>369193</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19883</th>\n",
       "      <td>369936</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23607</th>\n",
       "      <td>373660</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>922</th>\n",
       "      <td>350975</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24868</th>\n",
       "      <td>374921</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17058</th>\n",
       "      <td>367111</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22203</th>\n",
       "      <td>372256</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20952</th>\n",
       "      <td>371005</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20083</th>\n",
       "      <td>370136</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22465</th>\n",
       "      <td>372518</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11416</th>\n",
       "      <td>361469</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20760</th>\n",
       "      <td>370813</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16082</th>\n",
       "      <td>366135</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22550</th>\n",
       "      <td>372603</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14150</th>\n",
       "      <td>364203</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17829</th>\n",
       "      <td>367882</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23266</th>\n",
       "      <td>373319</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8016</th>\n",
       "      <td>358069</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19679</th>\n",
       "      <td>369732</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21568</th>\n",
       "      <td>371621</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20690</th>\n",
       "      <td>370743</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15955</th>\n",
       "      <td>366008</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6714</th>\n",
       "      <td>356767</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22591</th>\n",
       "      <td>372644</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12565</th>\n",
       "      <td>362618</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>679</th>\n",
       "      <td>350732</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23807</th>\n",
       "      <td>373860</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24983</th>\n",
       "      <td>375036</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13230</th>\n",
       "      <td>363283</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5899</th>\n",
       "      <td>355952</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11163</th>\n",
       "      <td>361216</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12065</th>\n",
       "      <td>362118</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20510</th>\n",
       "      <td>370563</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>893</th>\n",
       "      <td>350946</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19805</th>\n",
       "      <td>369858</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15807</th>\n",
       "      <td>365860</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20098</th>\n",
       "      <td>370151</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2353</th>\n",
       "      <td>352406</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7271</th>\n",
       "      <td>357324</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21619</th>\n",
       "      <td>371672</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18853</th>\n",
       "      <td>368906</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13067</th>\n",
       "      <td>363120</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6508</th>\n",
       "      <td>356561</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17146</th>\n",
       "      <td>367199</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4260</th>\n",
       "      <td>354313</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16232</th>\n",
       "      <td>366285</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8671</th>\n",
       "      <td>358724</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23394</th>\n",
       "      <td>373447</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10000 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       application_key  0\n",
       "21128           371181  0\n",
       "15911           365964  0\n",
       "13848           363901  0\n",
       "7820            357873  0\n",
       "23338           373391  0\n",
       "8558            358611  0\n",
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       "11401           361454  0\n",
       "21040           371093  0\n",
       "22990           373043  0\n",
       "21731           371784  0\n",
       "18127           368180  0\n",
       "19140           369193  0\n",
       "19883           369936  0\n",
       "23607           373660  0\n",
       "922             350975  0\n",
       "24868           374921  0\n",
       "17058           367111  0\n",
       "22203           372256  0\n",
       "20952           371005  0\n",
       "20083           370136  0\n",
       "22465           372518  0\n",
       "11416           361469  0\n",
       "20760           370813  0\n",
       "16082           366135  0\n",
       "22550           372603  0\n",
       "14150           364203  0\n",
       "17829           367882  0\n",
       "23266           373319  0\n",
       "8016            358069  0\n",
       "...                ... ..\n",
       "19679           369732  0\n",
       "21568           371621  0\n",
       "20690           370743  0\n",
       "15955           366008  0\n",
       "6714            356767  0\n",
       "22591           372644  0\n",
       "12565           362618  0\n",
       "679             350732  0\n",
       "23807           373860  0\n",
       "24983           375036  0\n",
       "13230           363283  0\n",
       "5899            355952  0\n",
       "11163           361216  0\n",
       "12065           362118  0\n",
       "20510           370563  0\n",
       "893             350946  0\n",
       "19805           369858  0\n",
       "15807           365860  0\n",
       "20098           370151  0\n",
       "2353            352406  0\n",
       "7271            357324  0\n",
       "21619           371672  0\n",
       "18853           368906  0\n",
       "13067           363120  0\n",
       "6508            356561  0\n",
       "17146           367199  0\n",
       "4260            354313  0\n",
       "16232           366285  0\n",
       "8671            358724  0\n",
       "23394           373447  0\n",
       "\n",
       "[10000 rows x 2 columns]"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "submit1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <td>372256</td>\n",
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       "      <th>23797</th>\n",
       "      <td>373850</td>\n",
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       "      <th>193</th>\n",
       "      <td>350246</td>\n",
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       "      <td>350243</td>\n",
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       "      <th>4599</th>\n",
       "      <td>354652</td>\n",
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       "      <th>15480</th>\n",
       "      <td>365533</td>\n",
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       "      <th>15268</th>\n",
       "      <td>365321</td>\n",
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       "      <th>19117</th>\n",
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       "      <th>22865</th>\n",
       "      <td>372918</td>\n",
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       "      <th>15982</th>\n",
       "      <td>366035</td>\n",
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       "      <th>22049</th>\n",
       "      <td>372102</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>23075</th>\n",
       "      <td>373128</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>10881</th>\n",
       "      <td>360934</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>8928</th>\n",
       "      <td>358981</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>350102</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>11416</th>\n",
       "      <td>361469</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>22631</th>\n",
       "      <td>372684</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>24825</th>\n",
       "      <td>374878</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>350177</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>18109</th>\n",
       "      <td>368162</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>3303</th>\n",
       "      <td>353356</td>\n",
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       "      <th>2760</th>\n",
       "      <td>352813</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>16408</th>\n",
       "      <td>366461</td>\n",
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       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>14473</th>\n",
       "      <td>364526</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>21886</th>\n",
       "      <td>371939</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16682</th>\n",
       "      <td>366735</td>\n",
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       "    <tr>\n",
       "      <th>16527</th>\n",
       "      <td>366580</td>\n",
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       "      <th>9297</th>\n",
       "      <td>359350</td>\n",
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       "    <tr>\n",
       "      <th>22004</th>\n",
       "      <td>372057</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>19047</th>\n",
       "      <td>369100</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>6836</th>\n",
       "      <td>356889</td>\n",
       "      <td>0</td>\n",
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       "      <th>8897</th>\n",
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       "      <th>18890</th>\n",
       "      <td>368943</td>\n",
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       "    <tr>\n",
       "      <th>9629</th>\n",
       "      <td>359682</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>5906</th>\n",
       "      <td>355959</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>10486</th>\n",
       "      <td>360539</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11594</th>\n",
       "      <td>361647</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5382</th>\n",
       "      <td>355435</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23825</th>\n",
       "      <td>373878</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13372</th>\n",
       "      <td>363425</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9121</th>\n",
       "      <td>359174</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13820</th>\n",
       "      <td>363873</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24275</th>\n",
       "      <td>374328</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3880</th>\n",
       "      <td>353933</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14127</th>\n",
       "      <td>364180</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19463</th>\n",
       "      <td>369516</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21808</th>\n",
       "      <td>371861</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12707</th>\n",
       "      <td>362760</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>350424</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20142</th>\n",
       "      <td>370195</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7372</th>\n",
       "      <td>357425</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20208</th>\n",
       "      <td>370261</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11304</th>\n",
       "      <td>361357</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10000 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       application_key  0\n",
       "22292           372345  0\n",
       "20330           370383  0\n",
       "14148           364201  0\n",
       "11471           361524  0\n",
       "3708            353761  0\n",
       "21956           372009  0\n",
       "2771            352824  0\n",
       "22203           372256  0\n",
       "23797           373850  0\n",
       "193             350246  0\n",
       "190             350243  0\n",
       "4599            354652  0\n",
       "15480           365533  0\n",
       "15268           365321  0\n",
       "19117           369170  0\n",
       "22865           372918  0\n",
       "15982           366035  0\n",
       "22049           372102  0\n",
       "23075           373128  0\n",
       "10881           360934  0\n",
       "8928            358981  0\n",
       "49              350102  0\n",
       "11416           361469  0\n",
       "22631           372684  0\n",
       "24825           374878  0\n",
       "124             350177  0\n",
       "18109           368162  0\n",
       "3303            353356  0\n",
       "2760            352813  0\n",
       "16408           366461  0\n",
       "...                ... ..\n",
       "14473           364526  0\n",
       "21886           371939  0\n",
       "16682           366735  0\n",
       "16527           366580  0\n",
       "9297            359350  0\n",
       "22004           372057  0\n",
       "19047           369100  0\n",
       "6836            356889  0\n",
       "8897            358950  0\n",
       "18890           368943  0\n",
       "9629            359682  0\n",
       "5906            355959  0\n",
       "10486           360539  0\n",
       "11594           361647  0\n",
       "5382            355435  0\n",
       "23825           373878  0\n",
       "13372           363425  0\n",
       "9121            359174  0\n",
       "13820           363873  0\n",
       "24275           374328  0\n",
       "3880            353933  0\n",
       "14127           364180  0\n",
       "19463           369516  0\n",
       "21808           371861  0\n",
       "12707           362760  0\n",
       "371             350424  0\n",
       "20142           370195  0\n",
       "7372            357425  0\n",
       "20208           370261  0\n",
       "11304           361357  0\n",
       "\n",
       "[10000 rows x 2 columns]"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "submit2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "# no = 262\n",
    "\n",
    "# submit1.to_csv('flabbergasted_IITGuwahati_'+str(no)+'.csv',header = False, index = False)\n",
    "submit2.to_csv('flabbergasted_IITGuwahati_'+str(no+1)+'.csv',header = False, index = False)\n",
    "\n",
    "no+=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "264"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "no"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Wh6G11p6uqhuT3JVkW5LbW2uHq+r6bvn+JAeTXJXkSJInk1zXPfxLk3xjko9U1X3dfd/f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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f4c2f9f5198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# XGB feature imp\n",
    "plt.figure(figsize=(20, 4))\n",
    "plt.bar(range(1, len(xgb1.feature_importances_)+1), xgb1.feature_importances_)\n",
    "plt.xticks(range(1, len(xgb1.feature_importances_)+1))\n",
    "plt.show()"
   ]
  }
 ],
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