8-XGB-FeatureEngineering-Copy1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "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": 2,
   "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": 3,
   "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": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dic = dict(zip(dataDict.values[:, 1], dataDict.values[:, 0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'mvar25'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dic['Average tenure of active revolving credit cards (in days)']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "gameX = gameDf.iloc[:,:-1]\n",
    "gameY = gameDf.iloc[:,-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "range(0, 80000)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "range(gameDf[\"mvar47\"].shape[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gameX[\"mvar47\"][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#one hot encoding C=0 L=1\n",
    "gameX['mvar47'] = pd.get_dummies(gameX['mvar47'])\n",
    "\n",
    "leaderX['mvar47'] = pd.get_dummies(leaderX['mvar47'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('uint8')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gameX[\"mvar47\"].dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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",
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       "      <th>mvar39</th>\n",
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       "      <th>mvar46</th>\n",
       "      <th>mvar47</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1753.0</td>\n",
       "      <td>0.5001</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>206.0</td>\n",
       "      <td>19179.0</td>\n",
       "      <td>206.0</td>\n",
       "      <td>14221.0</td>\n",
       "      <td>19438.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>20.5510</td>\n",
       "      <td>0.42105</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.85661</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1894.0</td>\n",
       "      <td>1.9701</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>297.0</td>\n",
       "      <td>19820.0</td>\n",
       "      <td>19820.0</td>\n",
       "      <td>176895.0</td>\n",
       "      <td>66346.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>63.0470</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.94391</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1774.0</td>\n",
       "      <td>0.1718</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>197.0</td>\n",
       "      <td>2563.0</td>\n",
       "      <td>877.0</td>\n",
       "      <td>8869.0</td>\n",
       "      <td>3637.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>83.7970</td>\n",
       "      <td>0.33333</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.76467</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1586.0</td>\n",
       "      <td>0.1123</td>\n",
       "      <td>5.299</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>297.0</td>\n",
       "      <td>6967.0</td>\n",
       "      <td>2478.0</td>\n",
       "      <td>14171.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>1.50000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.73703</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1832.0</td>\n",
       "      <td>1.4442</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>179.0</td>\n",
       "      <td>7577.0</td>\n",
       "      <td>179.0</td>\n",
       "      <td>21059.0</td>\n",
       "      <td>20306.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>96.052</td>\n",
       "      <td>66.6650</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.79190</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1838.0</td>\n",
       "      <td>0.0544</td>\n",
       "      <td>0.241</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>882.0</td>\n",
       "      <td>14039.0</td>\n",
       "      <td>10976.0</td>\n",
       "      <td>278941.0</td>\n",
       "      <td>74030.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>77.7800</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.92462</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1743.0</td>\n",
       "      <td>1.0753</td>\n",
       "      <td>0.272</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>397.0</td>\n",
       "      <td>16141.0</td>\n",
       "      <td>3568.0</td>\n",
       "      <td>69482.0</td>\n",
       "      <td>56755.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>67.1590</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.71347</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1935.0</td>\n",
       "      <td>0.5601</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>496.0</td>\n",
       "      <td>44919.0</td>\n",
       "      <td>17115.0</td>\n",
       "      <td>124814.0</td>\n",
       "      <td>124167.0</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.92403</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1885.0</td>\n",
       "      <td>0.0811</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>7369.0</td>\n",
       "      <td>19264.0</td>\n",
       "      <td>19264.0</td>\n",
       "      <td>59956.0</td>\n",
       "      <td>26633.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.89760</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1730.0</td>\n",
       "      <td>0.7444</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2103.0</td>\n",
       "      <td>582.0</td>\n",
       "      <td>16429.0</td>\n",
       "      <td>9197.0</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.05882</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.40529</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1731.0</td>\n",
       "      <td>0.5097</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>2433.0</td>\n",
       "      <td>8673.0</td>\n",
       "      <td>8673.0</td>\n",
       "      <td>6739.0</td>\n",
       "      <td>7388.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.23529</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.64242</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1755.0</td>\n",
       "      <td>0.3013</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>261.0</td>\n",
       "      <td>4051.0</td>\n",
       "      <td>261.0</td>\n",
       "      <td>297.0</td>\n",
       "      <td>261.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.33333</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.99142</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1739.0</td>\n",
       "      <td>2.2909</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7620.0</td>\n",
       "      <td>7620.0</td>\n",
       "      <td>64983.0</td>\n",
       "      <td>14067.0</td>\n",
       "      <td>...</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>95.0000</td>\n",
       "      <td>0.05882</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.44167</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1562.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>34.611</td>\n",
       "      <td>3.7845</td>\n",
       "      <td>0.000</td>\n",
       "      <td>297.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2478.0</td>\n",
       "      <td>198.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>124.910</td>\n",
       "      <td>99.9340</td>\n",
       "      <td>0.87500</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.84592</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1798.0</td>\n",
       "      <td>5.0825</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>259.0</td>\n",
       "      <td>3359.0</td>\n",
       "      <td>2973.0</td>\n",
       "      <td>22099.0</td>\n",
       "      <td>13507.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>76.8810</td>\n",
       "      <td>0.05882</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.43365</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1684.0</td>\n",
       "      <td>1.5479</td>\n",
       "      <td>1.338</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>297.0</td>\n",
       "      <td>6967.0</td>\n",
       "      <td>2478.0</td>\n",
       "      <td>14171.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>1.50000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.73703</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1789.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.428</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>2478.0</td>\n",
       "      <td>13874.0</td>\n",
       "      <td>13874.0</td>\n",
       "      <td>98011.0</td>\n",
       "      <td>56200.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.05000</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.51231</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1862.0</td>\n",
       "      <td>0.2401</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1487.0</td>\n",
       "      <td>12310.0</td>\n",
       "      <td>3964.0</td>\n",
       "      <td>7928.0</td>\n",
       "      <td>26564.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>77.4190</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.56685</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1767.0</td>\n",
       "      <td>0.3001</td>\n",
       "      <td>1.514</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>991.0</td>\n",
       "      <td>2478.0</td>\n",
       "      <td>2478.0</td>\n",
       "      <td>8790.0</td>\n",
       "      <td>6065.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.10000</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.73703</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1802.0</td>\n",
       "      <td>0.6364</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>96.0</td>\n",
       "      <td>18759.0</td>\n",
       "      <td>10905.0</td>\n",
       "      <td>51037.0</td>\n",
       "      <td>58544.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>58.9720</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.59409</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1780.0</td>\n",
       "      <td>1.9559</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>191.0</td>\n",
       "      <td>12525.0</td>\n",
       "      <td>12525.0</td>\n",
       "      <td>18932.0</td>\n",
       "      <td>14602.0</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>100.0000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.92752</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1714.0</td>\n",
       "      <td>2.2664</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1671.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>396.0</td>\n",
       "      <td>2582.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>91.6660</td>\n",
       "      <td>0.37500</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.34836</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1923.0</td>\n",
       "      <td>0.0880</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>5946.0</td>\n",
       "      <td>53893.0</td>\n",
       "      <td>24739.0</td>\n",
       "      <td>128435.0</td>\n",
       "      <td>125679.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>90.4290</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.88554</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1743.0</td>\n",
       "      <td>1.7208</td>\n",
       "      <td>2.295</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>159.0</td>\n",
       "      <td>3621.0</td>\n",
       "      <td>2323.0</td>\n",
       "      <td>9018.0</td>\n",
       "      <td>9649.0</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>82.3230</td>\n",
       "      <td>0.10000</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.59442</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1700.0</td>\n",
       "      <td>1.6605</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1037.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>892.0</td>\n",
       "      <td>1235.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.20000</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.94826</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1922.0</td>\n",
       "      <td>0.5389</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4524.0</td>\n",
       "      <td>15530.0</td>\n",
       "      <td>14819.0</td>\n",
       "      <td>116154.0</td>\n",
       "      <td>100684.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.91550</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1777.0</td>\n",
       "      <td>0.4120</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>369.0</td>\n",
       "      <td>6201.0</td>\n",
       "      <td>6201.0</td>\n",
       "      <td>66477.0</td>\n",
       "      <td>34053.0</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.03846</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.15159</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1811.0</td>\n",
       "      <td>0.9117</td>\n",
       "      <td>0.410</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.410</td>\n",
       "      <td>297.0</td>\n",
       "      <td>27717.0</td>\n",
       "      <td>9815.0</td>\n",
       "      <td>110001.0</td>\n",
       "      <td>69683.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>74.9960</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.56671</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1658.0</td>\n",
       "      <td>2.3829</td>\n",
       "      <td>37.127</td>\n",
       "      <td>10.3678</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>396.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6566.0</td>\n",
       "      <td>4068.0</td>\n",
       "      <td>...</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.57692</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.35339</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1827.0</td>\n",
       "      <td>0.2801</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>678.0</td>\n",
       "      <td>1189.0</td>\n",
       "      <td>1189.0</td>\n",
       "      <td>892.0</td>\n",
       "      <td>2065.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</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>1734.0</td>\n",
       "      <td>0.9279</td>\n",
       "      <td>0.520</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>256.0</td>\n",
       "      <td>11643.0</td>\n",
       "      <td>1524.0</td>\n",
       "      <td>16748.0</td>\n",
       "      <td>25359.0</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.38078</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24971</th>\n",
       "      <td>1849.0</td>\n",
       "      <td>1.8305</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>2251.0</td>\n",
       "      <td>33275.0</td>\n",
       "      <td>7505.0</td>\n",
       "      <td>44843.0</td>\n",
       "      <td>47453.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>91.7010</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.92111</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24972</th>\n",
       "      <td>1739.0</td>\n",
       "      <td>1.5251</td>\n",
       "      <td>2.727</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>2.727</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2129.0</td>\n",
       "      <td>720.0</td>\n",
       "      <td>5896.0</td>\n",
       "      <td>5206.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>109.251</td>\n",
       "      <td>94.1270</td>\n",
       "      <td>0.36842</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.52903</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24973</th>\n",
       "      <td>1642.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>3.353</td>\n",
       "      <td>1.2114</td>\n",
       "      <td>0.000</td>\n",
       "      <td>297.0</td>\n",
       "      <td>6290.0</td>\n",
       "      <td>2478.0</td>\n",
       "      <td>14171.0</td>\n",
       "      <td>6290.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>37.8900</td>\n",
       "      <td>0.83333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24974</th>\n",
       "      <td>1709.0</td>\n",
       "      <td>3.6801</td>\n",
       "      <td>7.583</td>\n",
       "      <td>3.1371</td>\n",
       "      <td>0.000</td>\n",
       "      <td>297.0</td>\n",
       "      <td>8132.0</td>\n",
       "      <td>297.0</td>\n",
       "      <td>1041.0</td>\n",
       "      <td>6960.0</td>\n",
       "      <td>...</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>81.029</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.59459</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.42680</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24975</th>\n",
       "      <td>1890.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1982.0</td>\n",
       "      <td>15162.0</td>\n",
       "      <td>15162.0</td>\n",
       "      <td>68181.0</td>\n",
       "      <td>43334.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>98.043</td>\n",
       "      <td>55.1970</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.27143</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24976</th>\n",
       "      <td>1727.0</td>\n",
       "      <td>1.8448</td>\n",
       "      <td>15.181</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>2234.0</td>\n",
       "      <td>2754.0</td>\n",
       "      <td>2234.0</td>\n",
       "      <td>2676.0</td>\n",
       "      <td>6539.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.66667</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.87890</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24977</th>\n",
       "      <td>1789.0</td>\n",
       "      <td>1.2994</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>364.0</td>\n",
       "      <td>17838.0</td>\n",
       "      <td>17838.0</td>\n",
       "      <td>8424.0</td>\n",
       "      <td>22307.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>109.307</td>\n",
       "      <td>75.0520</td>\n",
       "      <td>0.15385</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.69694</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24978</th>\n",
       "      <td>1706.0</td>\n",
       "      <td>0.4997</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>98.0</td>\n",
       "      <td>297.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>546.0</td>\n",
       "      <td>643.0</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.66667</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24979</th>\n",
       "      <td>1638.0</td>\n",
       "      <td>4.6802</td>\n",
       "      <td>16.751</td>\n",
       "      <td>2.6642</td>\n",
       "      <td>0.000</td>\n",
       "      <td>297.0</td>\n",
       "      <td>7937.0</td>\n",
       "      <td>2478.0</td>\n",
       "      <td>3032.0</td>\n",
       "      <td>10489.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>102.709</td>\n",
       "      <td>13.8820</td>\n",
       "      <td>0.50000</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.72640</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24980</th>\n",
       "      <td>1855.0</td>\n",
       "      <td>1.9965</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>350.0</td>\n",
       "      <td>30203.0</td>\n",
       "      <td>22656.0</td>\n",
       "      <td>168999.0</td>\n",
       "      <td>166720.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.74106</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24981</th>\n",
       "      <td>1790.0</td>\n",
       "      <td>0.2050</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>237.0</td>\n",
       "      <td>18018.0</td>\n",
       "      <td>13297.0</td>\n",
       "      <td>3914.0</td>\n",
       "      <td>1305.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.20000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.41582</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24982</th>\n",
       "      <td>1546.0</td>\n",
       "      <td>0.3491</td>\n",
       "      <td>50.803</td>\n",
       "      <td>4.2695</td>\n",
       "      <td>0.000</td>\n",
       "      <td>297.0</td>\n",
       "      <td>6967.0</td>\n",
       "      <td>2478.0</td>\n",
       "      <td>3330.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.70370</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24983</th>\n",
       "      <td>1777.0</td>\n",
       "      <td>3.9629</td>\n",
       "      <td>0.968</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>14.0</td>\n",
       "      <td>23707.0</td>\n",
       "      <td>23707.0</td>\n",
       "      <td>33432.0</td>\n",
       "      <td>19640.0</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>80.9340</td>\n",
       "      <td>0.04000</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.64752</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24984</th>\n",
       "      <td>1943.0</td>\n",
       "      <td>0.5389</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24775.0</td>\n",
       "      <td>24775.0</td>\n",
       "      <td>80772.0</td>\n",
       "      <td>69483.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.97068</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24985</th>\n",
       "      <td>1691.0</td>\n",
       "      <td>0.1663</td>\n",
       "      <td>1.979</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9591.0</td>\n",
       "      <td>2627.0</td>\n",
       "      <td>46903.0</td>\n",
       "      <td>30402.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>84.801</td>\n",
       "      <td>63.8550</td>\n",
       "      <td>0.03448</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.43441</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24986</th>\n",
       "      <td>1681.0</td>\n",
       "      <td>0.1739</td>\n",
       "      <td>9.006</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>6.568</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3004.0</td>\n",
       "      <td>2251.0</td>\n",
       "      <td>6818.0</td>\n",
       "      <td>7783.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>96.309</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.71429</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.88908</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24987</th>\n",
       "      <td>1723.0</td>\n",
       "      <td>1.0570</td>\n",
       "      <td>0.285</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>248.0</td>\n",
       "      <td>28479.0</td>\n",
       "      <td>28479.0</td>\n",
       "      <td>16352.0</td>\n",
       "      <td>3117.0</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.72344</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24988</th>\n",
       "      <td>1693.0</td>\n",
       "      <td>1.2145</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>18.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>991.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.36619</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24989</th>\n",
       "      <td>1592.0</td>\n",
       "      <td>6.4805</td>\n",
       "      <td>5.250</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.204</td>\n",
       "      <td>297.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2478.0</td>\n",
       "      <td>14171.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.50649</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24990</th>\n",
       "      <td>1641.0</td>\n",
       "      <td>0.6601</td>\n",
       "      <td>8.614</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>297.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2478.0</td>\n",
       "      <td>14171.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24991</th>\n",
       "      <td>1740.0</td>\n",
       "      <td>0.3901</td>\n",
       "      <td>4.322</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>490.0</td>\n",
       "      <td>29460.0</td>\n",
       "      <td>9449.0</td>\n",
       "      <td>42047.0</td>\n",
       "      <td>31583.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.20000</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.88957</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24992</th>\n",
       "      <td>1651.0</td>\n",
       "      <td>2.4909</td>\n",
       "      <td>1.335</td>\n",
       "      <td>0.9108</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3163.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1982.0</td>\n",
       "      <td>3167.0</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>82.3820</td>\n",
       "      <td>0.61538</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.93745</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24993</th>\n",
       "      <td>1729.0</td>\n",
       "      <td>1.3601</td>\n",
       "      <td>0.218</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5675.0</td>\n",
       "      <td>167.0</td>\n",
       "      <td>15071.0</td>\n",
       "      <td>10305.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.23810</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.71866</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24994</th>\n",
       "      <td>1730.0</td>\n",
       "      <td>1.6701</td>\n",
       "      <td>5.554</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>104.0</td>\n",
       "      <td>5692.0</td>\n",
       "      <td>496.0</td>\n",
       "      <td>4410.0</td>\n",
       "      <td>8125.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>79.4850</td>\n",
       "      <td>0.30769</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.93312</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24995</th>\n",
       "      <td>1715.0</td>\n",
       "      <td>12.0002</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>297.0</td>\n",
       "      <td>991.0</td>\n",
       "      <td>2478.0</td>\n",
       "      <td>8751.0</td>\n",
       "      <td>1814.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.07692</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.73703</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24996</th>\n",
       "      <td>1800.0</td>\n",
       "      <td>0.0551</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>5946.0</td>\n",
       "      <td>14867.0</td>\n",
       "      <td>9613.0</td>\n",
       "      <td>46490.0</td>\n",
       "      <td>44722.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.05882</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.99859</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24997</th>\n",
       "      <td>1686.0</td>\n",
       "      <td>1.3301</td>\n",
       "      <td>2.025</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>2.025</td>\n",
       "      <td>297.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2478.0</td>\n",
       "      <td>4582.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>124.171</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.30000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.77519</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24998</th>\n",
       "      <td>1826.0</td>\n",
       "      <td>0.5389</td>\n",
       "      <td>0.428</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>3568.0</td>\n",
       "      <td>26277.0</td>\n",
       "      <td>9058.0</td>\n",
       "      <td>72739.0</td>\n",
       "      <td>86797.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>50.1190</td>\n",
       "      <td>0.03333</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.40343</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24999</th>\n",
       "      <td>1916.0</td>\n",
       "      <td>0.1394</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>18889.0</td>\n",
       "      <td>18889.0</td>\n",
       "      <td>18889.0</td>\n",
       "      <td>28343.0</td>\n",
       "      <td>51174.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000</td>\n",
       "      <td>78.8835</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.99663</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25000 rows × 47 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        mvar1    mvar2   mvar3    mvar4  mvar5    mvar6    mvar7    mvar8  \\\n",
       "0      1753.0   0.5001   0.000   0.0000  0.000    206.0  19179.0    206.0   \n",
       "1      1894.0   1.9701   0.000   0.0000  0.000    297.0  19820.0  19820.0   \n",
       "2      1774.0   0.1718   0.000   0.0000  0.000    197.0   2563.0    877.0   \n",
       "3      1586.0   0.1123   5.299   0.0000  0.000    297.0   6967.0   2478.0   \n",
       "4      1832.0   1.4442   0.000   0.0000  0.000    179.0   7577.0    179.0   \n",
       "5      1838.0   0.0544   0.241   0.0000  0.000    882.0  14039.0  10976.0   \n",
       "6      1743.0   1.0753   0.272   0.0000  0.000    397.0  16141.0   3568.0   \n",
       "7      1935.0   0.5601   0.000   0.0000  0.000    496.0  44919.0  17115.0   \n",
       "8      1885.0   0.0811   0.000   0.0000  0.000   7369.0  19264.0  19264.0   \n",
       "9      1730.0   0.7444   0.000   0.0000  0.000      0.0   2103.0    582.0   \n",
       "10     1731.0   0.5097   0.000   0.0000  0.000   2433.0   8673.0   8673.0   \n",
       "11     1755.0   0.3013   0.000   0.0000  0.000    261.0   4051.0    261.0   \n",
       "12     1739.0   2.2909   0.000   0.0000  0.000      0.0   7620.0   7620.0   \n",
       "13     1562.0   0.0000  34.611   3.7845  0.000    297.0     18.0   2478.0   \n",
       "14     1798.0   5.0825   0.000   0.0000  0.000    259.0   3359.0   2973.0   \n",
       "15     1684.0   1.5479   1.338   0.0000  0.000    297.0   6967.0   2478.0   \n",
       "16     1789.0   0.0000   1.428   0.0000  0.000   2478.0  13874.0  13874.0   \n",
       "17     1862.0   0.2401   0.000   0.0000  0.000   1487.0  12310.0   3964.0   \n",
       "18     1767.0   0.3001   1.514   0.0000  0.000    991.0   2478.0   2478.0   \n",
       "19     1802.0   0.6364   0.000   0.0000  0.000     96.0  18759.0  10905.0   \n",
       "20     1780.0   1.9559   0.000   0.0000  0.000    191.0  12525.0  12525.0   \n",
       "21     1714.0   2.2664   0.000   0.0000  0.000     31.0   1671.0     57.0   \n",
       "22     1923.0   0.0880   0.000   0.0000  0.000   5946.0  53893.0  24739.0   \n",
       "23     1743.0   1.7208   2.295   0.0000  0.000    159.0   3621.0   2323.0   \n",
       "24     1700.0   1.6605   0.000   0.0000  0.000      0.0   1037.0     46.0   \n",
       "25     1922.0   0.5389   0.000   0.0000  0.000   4524.0  15530.0  14819.0   \n",
       "26     1777.0   0.4120   0.000   0.0000  0.000    369.0   6201.0   6201.0   \n",
       "27     1811.0   0.9117   0.410   0.0000  0.410    297.0  27717.0   9815.0   \n",
       "28     1658.0   2.3829  37.127  10.3678  0.000      0.0    396.0      0.0   \n",
       "29     1827.0   0.2801   0.000   0.0000  0.000    678.0   1189.0   1189.0   \n",
       "...       ...      ...     ...      ...    ...      ...      ...      ...   \n",
       "24970  1734.0   0.9279   0.520   0.0000  0.000    256.0  11643.0   1524.0   \n",
       "24971  1849.0   1.8305   0.000   0.0000  0.000   2251.0  33275.0   7505.0   \n",
       "24972  1739.0   1.5251   2.727   0.0000  2.727      8.0   2129.0    720.0   \n",
       "24973  1642.0   0.0000   3.353   1.2114  0.000    297.0   6290.0   2478.0   \n",
       "24974  1709.0   3.6801   7.583   3.1371  0.000    297.0   8132.0    297.0   \n",
       "24975  1890.0   0.0000   0.000   0.0000  0.000   1982.0  15162.0  15162.0   \n",
       "24976  1727.0   1.8448  15.181   0.0000  0.000   2234.0   2754.0   2234.0   \n",
       "24977  1789.0   1.2994   0.000   0.0000  0.000    364.0  17838.0  17838.0   \n",
       "24978  1706.0   0.4997   0.000   0.0000  0.000     98.0    297.0     98.0   \n",
       "24979  1638.0   4.6802  16.751   2.6642  0.000    297.0   7937.0   2478.0   \n",
       "24980  1855.0   1.9965   0.000   0.0000  0.000    350.0  30203.0  22656.0   \n",
       "24981  1790.0   0.2050   0.000   0.0000  0.000    237.0  18018.0  13297.0   \n",
       "24982  1546.0   0.3491  50.803   4.2695  0.000    297.0   6967.0   2478.0   \n",
       "24983  1777.0   3.9629   0.968   0.0000  0.000     14.0  23707.0  23707.0   \n",
       "24984  1943.0   0.5389   0.000   0.0000  0.000      0.0  24775.0  24775.0   \n",
       "24985  1691.0   0.1663   1.979   0.0000  0.000      0.0   9591.0   2627.0   \n",
       "24986  1681.0   0.1739   9.006   0.0000  6.568      0.0   3004.0   2251.0   \n",
       "24987  1723.0   1.0570   0.285   0.0000  0.000    248.0  28479.0  28479.0   \n",
       "24988  1693.0   1.2145   0.000   0.0000  0.000     18.0    100.0    100.0   \n",
       "24989  1592.0   6.4805   5.250   0.0000  1.204    297.0      0.0   2478.0   \n",
       "24990  1641.0   0.6601   8.614   0.0000  0.000    297.0      0.0   2478.0   \n",
       "24991  1740.0   0.3901   4.322   0.0000  0.000    490.0  29460.0   9449.0   \n",
       "24992  1651.0   2.4909   1.335   0.9108  0.000      4.0   3163.0      4.0   \n",
       "24993  1729.0   1.3601   0.218   0.0000  0.000      0.0   5675.0    167.0   \n",
       "24994  1730.0   1.6701   5.554   0.0000  0.000    104.0   5692.0    496.0   \n",
       "24995  1715.0  12.0002   0.000   0.0000  0.000    297.0    991.0   2478.0   \n",
       "24996  1800.0   0.0551   0.000   0.0000  0.000   5946.0  14867.0   9613.0   \n",
       "24997  1686.0   1.3301   2.025   0.0000  2.025    297.0      0.0   2478.0   \n",
       "24998  1826.0   0.5389   0.428   0.0000  0.000   3568.0  26277.0   9058.0   \n",
       "24999  1916.0   0.1394   0.000   0.0000  0.000  18889.0  18889.0  18889.0   \n",
       "\n",
       "          mvar9    mvar10   ...    mvar38  mvar39   mvar40    mvar41   mvar42  \\\n",
       "0       14221.0   19438.0   ...       1.0     0.0  100.000   20.5510  0.42105   \n",
       "1      176895.0   66346.0   ...       3.0     0.0  100.000   63.0470  0.00000   \n",
       "2        8869.0    3637.0   ...       1.0     0.0  100.000   83.7970  0.33333   \n",
       "3       14171.0       0.0   ...       1.0     0.0  100.000   78.8835  1.50000   \n",
       "4       21059.0   20306.0   ...       3.0     0.0   96.052   66.6650  0.00000   \n",
       "5      278941.0   74030.0   ...       4.0     0.0  100.000   77.7800  0.00000   \n",
       "6       69482.0   56755.0   ...       6.0     0.0  100.000   67.1590  0.00000   \n",
       "7      124814.0  124167.0   ...       9.0     0.0  100.000   78.8835  0.00000   \n",
       "8       59956.0   26633.0   ...       1.0     0.0  100.000   78.8835  0.00000   \n",
       "9       16429.0    9197.0   ...       9.0     0.0  100.000   78.8835  0.05882   \n",
       "10       6739.0    7388.0   ...       2.0     0.0  100.000   78.8835  0.23529   \n",
       "11        297.0     261.0   ...       3.0     0.0  100.000   78.8835  0.33333   \n",
       "12      64983.0   14067.0   ...      11.0     0.0  100.000   95.0000  0.05882   \n",
       "13        198.0      18.0   ...       7.0     1.0  124.910   99.9340  0.87500   \n",
       "14      22099.0   13507.0   ...       5.0     0.0  100.000   76.8810  0.05882   \n",
       "15      14171.0       0.0   ...       3.0     0.0  100.000   78.8835  1.50000   \n",
       "16      98011.0   56200.0   ...       4.0     0.0  100.000   78.8835  0.05000   \n",
       "17       7928.0   26564.0   ...       6.0     0.0  100.000   77.4190  0.00000   \n",
       "18       8790.0    6065.0   ...       1.0     0.0  100.000   78.8835  0.10000   \n",
       "19      51037.0   58544.0   ...       3.0     0.0  100.000   58.9720  0.00000   \n",
       "20      18932.0   14602.0   ...       7.0     0.0  100.000  100.0000  0.00000   \n",
       "21        396.0    2582.0   ...       6.0     0.0  100.000   91.6660  0.37500   \n",
       "22     128435.0  125679.0   ...       2.0     0.0  100.000   90.4290  0.00000   \n",
       "23       9018.0    9649.0   ...       8.0     0.0  100.000   82.3230  0.10000   \n",
       "24        892.0    1235.0   ...       5.0     0.0  100.000   78.8835  0.20000   \n",
       "25     116154.0  100684.0   ...       3.0     0.0  100.000   78.8835  0.00000   \n",
       "26      66477.0   34053.0   ...      12.0     0.0  100.000   78.8835  0.03846   \n",
       "27     110001.0   69683.0   ...       3.0     0.0  100.000   74.9960  0.00000   \n",
       "28       6566.0    4068.0   ...      14.0     0.0  100.000   78.8835  0.57692   \n",
       "29        892.0    2065.0   ...       3.0     0.0  100.000   78.8835  0.00000   \n",
       "...         ...       ...   ...       ...     ...      ...       ...      ...   \n",
       "24970   16748.0   25359.0   ...       7.0     0.0  100.000   78.8835  0.00000   \n",
       "24971   44843.0   47453.0   ...       2.0     0.0  100.000   91.7010  0.00000   \n",
       "24972    5896.0    5206.0   ...       6.0     0.0  109.251   94.1270  0.36842   \n",
       "24973   14171.0    6290.0   ...       1.0     0.0  100.000   37.8900  0.83333   \n",
       "24974    1041.0    6960.0   ...      32.0     0.0   81.029   78.8835  0.59459   \n",
       "24975   68181.0   43334.0   ...       2.0     0.0   98.043   55.1970  0.00000   \n",
       "24976    2676.0    6539.0   ...       4.0     0.0  100.000   78.8835  0.66667   \n",
       "24977    8424.0   22307.0   ...       5.0     0.0  109.307   75.0520  0.15385   \n",
       "24978     546.0     643.0   ...       7.0     0.0  100.000   78.8835  0.66667   \n",
       "24979    3032.0   10489.0   ...       3.0     1.0  102.709   13.8820  0.50000   \n",
       "24980  168999.0  166720.0   ...       2.0     0.0  100.000   78.8835  0.00000   \n",
       "24981    3914.0    1305.0   ...       5.0     0.0  100.000   78.8835  0.20000   \n",
       "24982    3330.0       0.0   ...       8.0     0.0  100.000   78.8835  0.70370   \n",
       "24983   33432.0   19640.0   ...      12.0     0.0  100.000   80.9340  0.04000   \n",
       "24984   80772.0   69483.0   ...       0.0     0.0  100.000   78.8835  0.00000   \n",
       "24985   46903.0   30402.0   ...       5.0     0.0   84.801   63.8550  0.03448   \n",
       "24986    6818.0    7783.0   ...       1.0     1.0   96.309   78.8835  0.71429   \n",
       "24987   16352.0    3117.0   ...       7.0     0.0  100.000   78.8835  0.00000   \n",
       "24988     991.0     118.0   ...       3.0     0.0  100.000   78.8835  0.00000   \n",
       "24989   14171.0       0.0   ...       3.0     0.0  100.000   78.8835  1.00000   \n",
       "24990   14171.0       0.0   ...       3.0     0.0  100.000   78.8835  1.00000   \n",
       "24991   42047.0   31583.0   ...       3.0     0.0  100.000   78.8835  0.20000   \n",
       "24992    1982.0    3167.0   ...      10.0     0.0  100.000   82.3820  0.61538   \n",
       "24993   15071.0   10305.0   ...       5.0     0.0  100.000   78.8835  0.23810   \n",
       "24994    4410.0    8125.0   ...       5.0     0.0  100.000   79.4850  0.30769   \n",
       "24995    8751.0    1814.0   ...       1.0     0.0  100.000   78.8835  0.07692   \n",
       "24996   46490.0   44722.0   ...       4.0     0.0  100.000   78.8835  0.05882   \n",
       "24997    4582.0       0.0   ...       0.0     0.0  124.171   78.8835  0.30000   \n",
       "24998   72739.0   86797.0   ...       2.0     0.0  100.000   50.1190  0.03333   \n",
       "24999   28343.0   51174.0   ...       0.0     0.0  100.000   78.8835  0.00000   \n",
       "\n",
       "       mvar43   mvar44  mvar45  mvar46  mvar47  \n",
       "0         3.0  0.85661     0.0     0.0       0  \n",
       "1        15.0  0.94391     0.0     0.0       1  \n",
       "2         3.0  0.76467     0.0     0.0       1  \n",
       "3         0.0  0.73703     0.0     0.0       1  \n",
       "4        23.0  0.79190     0.0     0.0       0  \n",
       "5        21.0  0.92462     0.0     0.0       0  \n",
       "6        14.0  0.71347     0.0     0.0       0  \n",
       "7        15.0  0.92403     0.0     0.0       0  \n",
       "8         5.0  0.89760     0.0     0.0       0  \n",
       "9        14.0  0.40529     0.0     0.0       1  \n",
       "10        1.0  0.64242     0.0     0.0       1  \n",
       "11        2.0  0.99142     0.0     0.0       1  \n",
       "12       16.0  0.44167     0.0     0.0       1  \n",
       "13        1.0  0.84592     1.0     1.0       1  \n",
       "14       13.0  0.43365     0.0     0.0       1  \n",
       "15        0.0  0.73703     0.0     0.0       1  \n",
       "16       13.0  0.51231     0.0     0.0       0  \n",
       "17        7.0  0.56685     0.0     0.0       1  \n",
       "18        3.0  0.73703     0.0     0.0       1  \n",
       "19        9.0  0.59409     0.0     0.0       1  \n",
       "20        7.0  0.92752     0.0     0.0       1  \n",
       "21        5.0  0.34836     0.0     0.0       1  \n",
       "22        9.0  0.88554     0.0     0.0       1  \n",
       "23        9.0  0.59442     0.0     0.0       1  \n",
       "24        5.0  0.94826     0.0     0.0       0  \n",
       "25       12.0  0.91550     0.0     0.0       0  \n",
       "26       23.0  0.15159     0.0     0.0       1  \n",
       "27       15.0  0.56671     0.0     0.0       1  \n",
       "28        8.0  0.35339     0.0     2.0       1  \n",
       "29        2.0  1.00000     0.0     0.0       1  \n",
       "...       ...      ...     ...     ...     ...  \n",
       "24970    10.0  0.38078     0.0     0.0       0  \n",
       "24971     4.0  0.92111     0.0     0.0       0  \n",
       "24972    12.0  0.52903     0.0     0.0       1  \n",
       "24973     0.0  1.00000     0.0     0.0       1  \n",
       "24974    11.0  0.42680     0.0     2.0       1  \n",
       "24975    15.0  0.27143     0.0     0.0       1  \n",
       "24976     5.0  0.87890     0.0     0.0       1  \n",
       "24977     8.0  0.69694     0.0     0.0       0  \n",
       "24978     4.0  1.00000     0.0     0.0       1  \n",
       "24979     4.0  0.72640     0.0     0.0       1  \n",
       "24980    12.0  0.74106     0.0     0.0       0  \n",
       "24981     2.0  0.41582     0.0     0.0       1  \n",
       "24982     2.0  1.00000     1.0     1.0       1  \n",
       "24983    15.0  0.64752     0.0     0.0       0  \n",
       "24984     6.0  0.97068     0.0     0.0       1  \n",
       "24985    14.0  0.43441     0.0     0.0       1  \n",
       "24986     2.0  0.88908     0.0     0.0       1  \n",
       "24987     6.0  0.72344     0.0     0.0       1  \n",
       "24988     3.0  0.36619     0.0     0.0       1  \n",
       "24989     1.0  0.50649     0.0     0.0       1  \n",
       "24990     1.0  1.00000     0.0     0.0       0  \n",
       "24991     4.0  0.88957     1.0     0.0       0  \n",
       "24992     3.0  0.93745     0.0     0.0       0  \n",
       "24993    13.0  0.71866     0.0     0.0       1  \n",
       "24994     4.0  0.93312     0.0     0.0       1  \n",
       "24995     4.0  0.73703     0.0     0.0       1  \n",
       "24996     8.0  0.99859     0.0     0.0       0  \n",
       "24997     2.0  0.77519     0.0     0.0       0  \n",
       "24998    11.0  0.40343     0.0     0.0       1  \n",
       "24999     5.0  0.99663     0.0     0.0       1  \n",
       "\n",
       "[25000 rows x 47 columns]"
      ]
     },
     "execution_count": 12,
     "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": 22,
   "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, gameY)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ -8.41659468e-06,   3.68192435e-08,   1.16153283e-07,\n",
       "          2.15940369e-08,   2.47769047e-08,  -1.74878662e-05,\n",
       "          9.48311789e-06,  -2.73899032e-05,  -6.00736035e-07,\n",
       "         -9.88125990e-06,   5.08953150e-06,   8.84662133e-06,\n",
       "         -4.06033771e-06,   8.39188684e-10,  -2.76934188e-07,\n",
       "          1.13800206e-08,   1.36635176e-08,   1.39591832e-08,\n",
       "          2.20864135e-08,   2.27748062e-08,   2.20831611e-07,\n",
       "          2.74454065e-05,   1.97043536e-05,   2.19128532e-07,\n",
       "         -1.64427676e-05,  -2.16871201e-05,  -1.88326253e-05,\n",
       "         -1.36243982e-05,  -4.19440364e-05,  -1.74387952e-05,\n",
       "         -1.85885286e-05,  -2.87613022e-06,  -6.60162981e-08,\n",
       "          1.19285826e-08,   8.01684020e-09,   7.44947030e-08,\n",
       "         -4.10383244e-08,   5.28877397e-08,   6.33885632e-09,\n",
       "         -2.80108680e-07,  -2.39274214e-07,   5.90291367e-09,\n",
       "         -4.46342551e-08,  -4.19636164e-09,   1.00010394e-09,\n",
       "          3.85871273e-09,   1.02853042e-08]])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.coef_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 47)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.coef_.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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HegKSJElaPtZsvb1zjAPbLpzBTCRJ0nLmGVKSJEmSJEnqlQUpSZIkSZIk9cqClCRJkiRJ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\n/wB8YML5xtCq6wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe7affba208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#XGB feature imp\n",
    "lr_coef = clf.coef_.reshape(-1, 1)\n",
    "plt.figure(figsize=(20, 4))\n",
    "plt.bar(range(1, len(lr_coef)+1), np.abs(lr_coef) )\n",
    "plt.xticks(range(1, len(lr_coef)+1))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Method 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#current"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "running cross validation\n",
      "running cross validation, with preprocessing function\n",
      "running cross validation, with cutomsized loss function\n",
      "[0]\ttrain-error:0.753787\ttest-error:0.753787\n",
      "Multiple eval metrics have been passed: 'test-error' will be used for early stopping.\n",
      "\n",
      "Will train until test-error hasn't improved in 50 rounds.\n",
      "[1]\ttrain-error:0.753787\ttest-error:0.753787\n",
      "[2]\ttrain-error:0.36955\ttest-error:0.371713\n",
      "[3]\ttrain-error:0.284816\ttest-error:0.286575\n",
      "[4]\ttrain-error:0.245163\ttest-error:0.247437\n",
      "[5]\ttrain-error:0.212703\ttest-error:0.215738\n",
      "[6]\ttrain-error:0.207472\ttest-error:0.21025\n",
      "[7]\ttrain-error:0.204878\ttest-error:0.207387\n",
      "[8]\ttrain-error:0.203591\ttest-error:0.205487\n",
      "[9]\ttrain-error:0.202441\ttest-error:0.204887\n",
      "[10]\ttrain-error:0.201412\ttest-error:0.203575\n",
      "[11]\ttrain-error:0.200553\ttest-error:0.2029\n",
      "[12]\ttrain-error:0.200172\ttest-error:0.202337\n",
      "[13]\ttrain-error:0.200022\ttest-error:0.201687\n",
      "[14]\ttrain-error:0.199413\ttest-error:0.201137\n",
      "[15]\ttrain-error:0.199253\ttest-error:0.201187\n",
      "[16]\ttrain-error:0.198778\ttest-error:0.200388\n",
      "[17]\ttrain-error:0.198515\ttest-error:0.200462\n",
      "[18]\ttrain-error:0.198319\ttest-error:0.2005\n",
      "[19]\ttrain-error:0.197688\ttest-error:0.200187\n",
      "[20]\ttrain-error:0.197438\ttest-error:0.199825\n",
      "[21]\ttrain-error:0.197147\ttest-error:0.199775\n",
      "[22]\ttrain-error:0.196863\ttest-error:0.199413\n",
      "[23]\ttrain-error:0.196853\ttest-error:0.199225\n",
      "[24]\ttrain-error:0.196344\ttest-error:0.198788\n",
      "[25]\ttrain-error:0.195819\ttest-error:0.198837\n",
      "[26]\ttrain-error:0.195425\ttest-error:0.1983\n",
      "[27]\ttrain-error:0.195206\ttest-error:0.198525\n",
      "[28]\ttrain-error:0.194906\ttest-error:0.198187\n",
      "[29]\ttrain-error:0.194647\ttest-error:0.198175\n",
      "[30]\ttrain-error:0.194316\ttest-error:0.19785\n",
      "[31]\ttrain-error:0.194041\ttest-error:0.1978\n",
      "[32]\ttrain-error:0.193688\ttest-error:0.197612\n",
      "[33]\ttrain-error:0.193378\ttest-error:0.197475\n",
      "[34]\ttrain-error:0.193112\ttest-error:0.197288\n",
      "[35]\ttrain-error:0.19285\ttest-error:0.197012\n",
      "[36]\ttrain-error:0.192606\ttest-error:0.196662\n",
      "[37]\ttrain-error:0.192322\ttest-error:0.196538\n",
      "[38]\ttrain-error:0.192019\ttest-error:0.196388\n",
      "[39]\ttrain-error:0.191709\ttest-error:0.195988\n",
      "[40]\ttrain-error:0.191391\ttest-error:0.195862\n",
      "[41]\ttrain-error:0.191275\ttest-error:0.19595\n",
      "[42]\ttrain-error:0.190988\ttest-error:0.195825\n",
      "[43]\ttrain-error:0.190691\ttest-error:0.195863\n",
      "[44]\ttrain-error:0.190369\ttest-error:0.195663\n",
      "[45]\ttrain-error:0.190266\ttest-error:0.19505\n",
      "[46]\ttrain-error:0.189866\ttest-error:0.194925\n",
      "[47]\ttrain-error:0.189625\ttest-error:0.1947\n",
      "[48]\ttrain-error:0.189463\ttest-error:0.194938\n",
      "[49]\ttrain-error:0.1892\ttest-error:0.19465\n",
      "[50]\ttrain-error:0.188944\ttest-error:0.194512\n",
      "[51]\ttrain-error:0.188787\ttest-error:0.19455\n",
      "[52]\ttrain-error:0.188581\ttest-error:0.194538\n",
      "[53]\ttrain-error:0.188428\ttest-error:0.194462\n",
      "[54]\ttrain-error:0.188128\ttest-error:0.194188\n",
      "[55]\ttrain-error:0.187922\ttest-error:0.1942\n",
      "[56]\ttrain-error:0.1878\ttest-error:0.194\n",
      "[57]\ttrain-error:0.187612\ttest-error:0.193962\n",
      "[58]\ttrain-error:0.187447\ttest-error:0.193912\n",
      "[59]\ttrain-error:0.187297\ttest-error:0.193925\n",
      "[60]\ttrain-error:0.187066\ttest-error:0.194037\n",
      "[61]\ttrain-error:0.186881\ttest-error:0.193737\n",
      "[62]\ttrain-error:0.186863\ttest-error:0.19375\n",
      "[63]\ttrain-error:0.18671\ttest-error:0.193587\n",
      "[64]\ttrain-error:0.186362\ttest-error:0.1935\n",
      "[65]\ttrain-error:0.18614\ttest-error:0.19325\n",
      "[66]\ttrain-error:0.185922\ttest-error:0.19335\n",
      "[67]\ttrain-error:0.185734\ttest-error:0.193125\n",
      "[68]\ttrain-error:0.185575\ttest-error:0.193125\n",
      "[69]\ttrain-error:0.185372\ttest-error:0.19315\n",
      "[70]\ttrain-error:0.185284\ttest-error:0.193213\n",
      "[71]\ttrain-error:0.1852\ttest-error:0.19315\n",
      "[72]\ttrain-error:0.185016\ttest-error:0.193125\n",
      "[73]\ttrain-error:0.184897\ttest-error:0.193038\n",
      "[74]\ttrain-error:0.184619\ttest-error:0.192988\n",
      "[75]\ttrain-error:0.184572\ttest-error:0.192813\n",
      "[76]\ttrain-error:0.184466\ttest-error:0.192588\n",
      "[77]\ttrain-error:0.184359\ttest-error:0.192513\n",
      "[78]\ttrain-error:0.184128\ttest-error:0.19265\n",
      "[79]\ttrain-error:0.184078\ttest-error:0.192675\n",
      "[80]\ttrain-error:0.183966\ttest-error:0.192775\n",
      "[81]\ttrain-error:0.183878\ttest-error:0.1928\n",
      "[82]\ttrain-error:0.183659\ttest-error:0.19265\n",
      "[83]\ttrain-error:0.183588\ttest-error:0.1925\n",
      "[84]\ttrain-error:0.183472\ttest-error:0.192487\n",
      "[85]\ttrain-error:0.183409\ttest-error:0.192225\n",
      "[86]\ttrain-error:0.183397\ttest-error:0.1922\n",
      "[87]\ttrain-error:0.183262\ttest-error:0.192287\n",
      "[88]\ttrain-error:0.183122\ttest-error:0.19225\n",
      "[89]\ttrain-error:0.1829\ttest-error:0.191988\n",
      "[90]\ttrain-error:0.182722\ttest-error:0.191837\n",
      "[91]\ttrain-error:0.182594\ttest-error:0.191887\n",
      "[92]\ttrain-error:0.182612\ttest-error:0.191725\n",
      "[93]\ttrain-error:0.182456\ttest-error:0.191725\n",
      "[94]\ttrain-error:0.182266\ttest-error:0.191725\n",
      "[95]\ttrain-error:0.182228\ttest-error:0.191687\n",
      "[96]\ttrain-error:0.182222\ttest-error:0.191775\n",
      "[97]\ttrain-error:0.182106\ttest-error:0.19175\n",
      "[98]\ttrain-error:0.181978\ttest-error:0.191787\n",
      "[99]\ttrain-error:0.181934\ttest-error:0.1919\n",
      "[100]\ttrain-error:0.181894\ttest-error:0.191862\n",
      "[101]\ttrain-error:0.181734\ttest-error:0.191962\n",
      "[102]\ttrain-error:0.1816\ttest-error:0.191937\n",
      "[103]\ttrain-error:0.181522\ttest-error:0.191938\n",
      "[104]\ttrain-error:0.181269\ttest-error:0.191888\n",
      "[105]\ttrain-error:0.181159\ttest-error:0.191475\n",
      "[106]\ttrain-error:0.181125\ttest-error:0.191563\n",
      "[107]\ttrain-error:0.181078\ttest-error:0.191738\n",
      "[108]\ttrain-error:0.180972\ttest-error:0.191512\n",
      "[109]\ttrain-error:0.180788\ttest-error:0.191438\n",
      "[110]\ttrain-error:0.180784\ttest-error:0.191313\n",
      "[111]\ttrain-error:0.180606\ttest-error:0.191275\n",
      "[112]\ttrain-error:0.180581\ttest-error:0.19125\n",
      "[113]\ttrain-error:0.180444\ttest-error:0.191325\n",
      "[114]\ttrain-error:0.180397\ttest-error:0.191362\n",
      "[115]\ttrain-error:0.180259\ttest-error:0.191325\n",
      "[116]\ttrain-error:0.180163\ttest-error:0.191175\n",
      "[117]\ttrain-error:0.180053\ttest-error:0.19115\n",
      "[118]\ttrain-error:0.179981\ttest-error:0.191112\n",
      "[119]\ttrain-error:0.179956\ttest-error:0.1913\n",
      "[120]\ttrain-error:0.179912\ttest-error:0.191137\n",
      "[121]\ttrain-error:0.179865\ttest-error:0.191187\n",
      "[122]\ttrain-error:0.179788\ttest-error:0.191262\n",
      "[123]\ttrain-error:0.179719\ttest-error:0.191313\n",
      "[124]\ttrain-error:0.179653\ttest-error:0.191388\n",
      "[125]\ttrain-error:0.179584\ttest-error:0.191288\n",
      "[126]\ttrain-error:0.179547\ttest-error:0.191238\n",
      "[127]\ttrain-error:0.179406\ttest-error:0.191338\n",
      "[128]\ttrain-error:0.179312\ttest-error:0.191325\n",
      "[129]\ttrain-error:0.179169\ttest-error:0.191312\n",
      "[130]\ttrain-error:0.179013\ttest-error:0.191225\n",
      "[131]\ttrain-error:0.178928\ttest-error:0.191175\n",
      "[132]\ttrain-error:0.178897\ttest-error:0.191062\n",
      "[133]\ttrain-error:0.178881\ttest-error:0.191012\n",
      "[134]\ttrain-error:0.178756\ttest-error:0.190962\n",
      "[135]\ttrain-error:0.178769\ttest-error:0.191025\n",
      "[136]\ttrain-error:0.178647\ttest-error:0.191075\n",
      "[137]\ttrain-error:0.178478\ttest-error:0.191113\n",
      "[138]\ttrain-error:0.178428\ttest-error:0.190987\n",
      "[139]\ttrain-error:0.178409\ttest-error:0.190988\n",
      "[140]\ttrain-error:0.1784\ttest-error:0.190975\n",
      "[141]\ttrain-error:0.178256\ttest-error:0.19105\n",
      "[142]\ttrain-error:0.178181\ttest-error:0.190962\n",
      "[143]\ttrain-error:0.178125\ttest-error:0.190887\n",
      "[144]\ttrain-error:0.178047\ttest-error:0.191063\n",
      "[145]\ttrain-error:0.177925\ttest-error:0.191138\n",
      "[146]\ttrain-error:0.177844\ttest-error:0.191038\n",
      "[147]\ttrain-error:0.177644\ttest-error:0.19105\n",
      "[148]\ttrain-error:0.177641\ttest-error:0.190963\n",
      "[149]\ttrain-error:0.177537\ttest-error:0.190963\n",
      "[150]\ttrain-error:0.177535\ttest-error:0.1911\n",
      "[151]\ttrain-error:0.17755\ttest-error:0.191175\n",
      "[152]\ttrain-error:0.177475\ttest-error:0.191112\n",
      "[153]\ttrain-error:0.177372\ttest-error:0.191037\n",
      "[154]\ttrain-error:0.177262\ttest-error:0.190875\n",
      "[155]\ttrain-error:0.177187\ttest-error:0.190925\n",
      "[156]\ttrain-error:0.177147\ttest-error:0.190813\n",
      "[157]\ttrain-error:0.177009\ttest-error:0.19065\n",
      "[158]\ttrain-error:0.176916\ttest-error:0.190638\n",
      "[159]\ttrain-error:0.176828\ttest-error:0.190738\n",
      "[160]\ttrain-error:0.176778\ttest-error:0.190812\n",
      "[161]\ttrain-error:0.176687\ttest-error:0.190837\n",
      "[162]\ttrain-error:0.176528\ttest-error:0.190725\n",
      "[163]\ttrain-error:0.17655\ttest-error:0.1907\n",
      "[164]\ttrain-error:0.176472\ttest-error:0.190663\n",
      "[165]\ttrain-error:0.176325\ttest-error:0.19055\n",
      "[166]\ttrain-error:0.176206\ttest-error:0.190688\n",
      "[167]\ttrain-error:0.176162\ttest-error:0.190812\n",
      "[168]\ttrain-error:0.175988\ttest-error:0.190713\n",
      "[169]\ttrain-error:0.175953\ttest-error:0.190763\n",
      "[170]\ttrain-error:0.175866\ttest-error:0.190775\n",
      "[171]\ttrain-error:0.175831\ttest-error:0.190625\n",
      "[172]\ttrain-error:0.175813\ttest-error:0.1907\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[173]\ttrain-error:0.175697\ttest-error:0.190688\n",
      "[174]\ttrain-error:0.175644\ttest-error:0.190588\n",
      "[175]\ttrain-error:0.175528\ttest-error:0.190725\n",
      "[176]\ttrain-error:0.175387\ttest-error:0.190775\n",
      "[177]\ttrain-error:0.175337\ttest-error:0.190787\n",
      "[178]\ttrain-error:0.175275\ttest-error:0.19095\n",
      "[179]\ttrain-error:0.175141\ttest-error:0.1908\n",
      "[180]\ttrain-error:0.175025\ttest-error:0.190787\n",
      "[181]\ttrain-error:0.174984\ttest-error:0.1909\n",
      "[182]\ttrain-error:0.175041\ttest-error:0.190862\n",
      "[183]\ttrain-error:0.174965\ttest-error:0.19085\n",
      "[184]\ttrain-error:0.174937\ttest-error:0.190712\n",
      "[185]\ttrain-error:0.174797\ttest-error:0.190825\n",
      "[186]\ttrain-error:0.174741\ttest-error:0.190938\n",
      "[187]\ttrain-error:0.174666\ttest-error:0.191\n",
      "[188]\ttrain-error:0.174609\ttest-error:0.190937\n",
      "[189]\ttrain-error:0.174613\ttest-error:0.190887\n",
      "[190]\ttrain-error:0.174525\ttest-error:0.190937\n",
      "[191]\ttrain-error:0.174428\ttest-error:0.191025\n",
      "[192]\ttrain-error:0.174303\ttest-error:0.1911\n",
      "[193]\ttrain-error:0.174294\ttest-error:0.19125\n",
      "[194]\ttrain-error:0.174194\ttest-error:0.191262\n",
      "[195]\ttrain-error:0.174088\ttest-error:0.191088\n",
      "[196]\ttrain-error:0.17395\ttest-error:0.191075\n",
      "[197]\ttrain-error:0.173934\ttest-error:0.191025\n",
      "[198]\ttrain-error:0.173869\ttest-error:0.1911\n",
      "[199]\ttrain-error:0.173747\ttest-error:0.191188\n",
      "[200]\ttrain-error:0.173697\ttest-error:0.190975\n",
      "[201]\ttrain-error:0.173569\ttest-error:0.191087\n",
      "[202]\ttrain-error:0.173425\ttest-error:0.19105\n",
      "[203]\ttrain-error:0.173381\ttest-error:0.191037\n",
      "[204]\ttrain-error:0.173272\ttest-error:0.190963\n",
      "[205]\ttrain-error:0.173244\ttest-error:0.190975\n",
      "[206]\ttrain-error:0.173156\ttest-error:0.190962\n",
      "[207]\ttrain-error:0.173159\ttest-error:0.191013\n",
      "[208]\ttrain-error:0.173025\ttest-error:0.19095\n",
      "[209]\ttrain-error:0.172928\ttest-error:0.190962\n",
      "[210]\ttrain-error:0.172878\ttest-error:0.191125\n",
      "[211]\ttrain-error:0.172819\ttest-error:0.191162\n",
      "[212]\ttrain-error:0.17265\ttest-error:0.191137\n",
      "[213]\ttrain-error:0.172644\ttest-error:0.191063\n",
      "[214]\ttrain-error:0.172625\ttest-error:0.191225\n",
      "[215]\ttrain-error:0.172635\ttest-error:0.19115\n",
      "Stopping. Best iteration:\n",
      "[165]\ttrain-error:0.176325+0.000166989\ttest-error:0.19055+0.00149102\n",
      "\n",
      "[0]\teval-error:0.753788\ttrain-error:0.753788\n",
      "[1]\teval-error:0.753788\ttrain-error:0.753788\n",
      "[2]\teval-error:0.371225\ttrain-error:0.371225\n",
      "[3]\teval-error:0.297088\ttrain-error:0.297088\n",
      "[4]\teval-error:0.224587\ttrain-error:0.224587\n",
      "[5]\teval-error:0.212413\ttrain-error:0.212413\n",
      "[6]\teval-error:0.210037\ttrain-error:0.210037\n",
      "[7]\teval-error:0.206838\ttrain-error:0.206838\n",
      "[8]\teval-error:0.202725\ttrain-error:0.202725\n",
      "[9]\teval-error:0.202487\ttrain-error:0.202487\n",
      "[10]\teval-error:0.201063\ttrain-error:0.201063\n",
      "[11]\teval-error:0.200412\ttrain-error:0.200412\n",
      "[12]\teval-error:0.199687\ttrain-error:0.199687\n",
      "[13]\teval-error:0.199738\ttrain-error:0.199738\n",
      "[14]\teval-error:0.1992\ttrain-error:0.1992\n",
      "[15]\teval-error:0.1979\ttrain-error:0.1979\n",
      "[16]\teval-error:0.198763\ttrain-error:0.198763\n",
      "[17]\teval-error:0.198662\ttrain-error:0.198662\n",
      "[18]\teval-error:0.198362\ttrain-error:0.198362\n",
      "[19]\teval-error:0.197963\ttrain-error:0.197963\n",
      "[20]\teval-error:0.197275\ttrain-error:0.197275\n",
      "[21]\teval-error:0.197162\ttrain-error:0.197162\n",
      "[22]\teval-error:0.196337\ttrain-error:0.196337\n",
      "[23]\teval-error:0.1969\ttrain-error:0.1969\n",
      "[24]\teval-error:0.196637\ttrain-error:0.196637\n",
      "[25]\teval-error:0.19595\ttrain-error:0.19595\n",
      "[26]\teval-error:0.195725\ttrain-error:0.195725\n",
      "[27]\teval-error:0.195775\ttrain-error:0.195775\n",
      "[28]\teval-error:0.195312\ttrain-error:0.195312\n",
      "[29]\teval-error:0.195175\ttrain-error:0.195175\n",
      "[30]\teval-error:0.194637\ttrain-error:0.194637\n",
      "[31]\teval-error:0.194125\ttrain-error:0.194125\n",
      "[32]\teval-error:0.1941\ttrain-error:0.1941\n",
      "[33]\teval-error:0.193862\ttrain-error:0.193862\n",
      "[34]\teval-error:0.193775\ttrain-error:0.193775\n",
      "[35]\teval-error:0.19335\ttrain-error:0.19335\n",
      "[36]\teval-error:0.193425\ttrain-error:0.193425\n",
      "[37]\teval-error:0.192925\ttrain-error:0.192925\n",
      "[38]\teval-error:0.192525\ttrain-error:0.192525\n",
      "[39]\teval-error:0.192225\ttrain-error:0.192225\n",
      "[40]\teval-error:0.191725\ttrain-error:0.191725\n",
      "[41]\teval-error:0.191337\ttrain-error:0.191337\n",
      "[42]\teval-error:0.191075\ttrain-error:0.191075\n",
      "[43]\teval-error:0.191\ttrain-error:0.191\n",
      "[44]\teval-error:0.19085\ttrain-error:0.19085\n",
      "[45]\teval-error:0.191025\ttrain-error:0.191025\n",
      "[46]\teval-error:0.190837\ttrain-error:0.190837\n",
      "[47]\teval-error:0.19015\ttrain-error:0.19015\n",
      "[48]\teval-error:0.1899\ttrain-error:0.1899\n",
      "[49]\teval-error:0.189525\ttrain-error:0.189525\n",
      "[50]\teval-error:0.189438\ttrain-error:0.189438\n",
      "[51]\teval-error:0.189125\ttrain-error:0.189125\n",
      "[52]\teval-error:0.188925\ttrain-error:0.188925\n",
      "[53]\teval-error:0.18885\ttrain-error:0.18885\n",
      "[54]\teval-error:0.188512\ttrain-error:0.188512\n",
      "[55]\teval-error:0.188112\ttrain-error:0.188112\n",
      "[56]\teval-error:0.187837\ttrain-error:0.187837\n",
      "[57]\teval-error:0.187663\ttrain-error:0.187663\n",
      "[58]\teval-error:0.187575\ttrain-error:0.187575\n",
      "[59]\teval-error:0.18735\ttrain-error:0.18735\n",
      "[60]\teval-error:0.1872\ttrain-error:0.1872\n",
      "[61]\teval-error:0.1869\ttrain-error:0.1869\n",
      "[62]\teval-error:0.186675\ttrain-error:0.186675\n",
      "[63]\teval-error:0.18665\ttrain-error:0.18665\n",
      "[64]\teval-error:0.186837\ttrain-error:0.186837\n",
      "[65]\teval-error:0.186738\ttrain-error:0.186738\n",
      "[66]\teval-error:0.186413\ttrain-error:0.186413\n",
      "[67]\teval-error:0.186238\ttrain-error:0.186238\n",
      "[68]\teval-error:0.1862\ttrain-error:0.1862\n",
      "[69]\teval-error:0.18615\ttrain-error:0.18615\n",
      "[70]\teval-error:0.186112\ttrain-error:0.186112\n",
      "[71]\teval-error:0.186125\ttrain-error:0.186125\n",
      "[72]\teval-error:0.186087\ttrain-error:0.186087\n",
      "[73]\teval-error:0.18585\ttrain-error:0.18585\n",
      "[74]\teval-error:0.185725\ttrain-error:0.185725\n",
      "[75]\teval-error:0.18565\ttrain-error:0.18565\n",
      "[76]\teval-error:0.185537\ttrain-error:0.185537\n",
      "[77]\teval-error:0.185425\ttrain-error:0.185425\n",
      "[78]\teval-error:0.1853\ttrain-error:0.1853\n",
      "[79]\teval-error:0.185375\ttrain-error:0.185375\n",
      "[80]\teval-error:0.185025\ttrain-error:0.185025\n",
      "[81]\teval-error:0.185087\ttrain-error:0.185087\n",
      "[82]\teval-error:0.184888\ttrain-error:0.184888\n",
      "[83]\teval-error:0.184762\ttrain-error:0.184762\n",
      "[84]\teval-error:0.184537\ttrain-error:0.184537\n",
      "[85]\teval-error:0.184337\ttrain-error:0.184337\n",
      "[86]\teval-error:0.1841\ttrain-error:0.1841\n",
      "[87]\teval-error:0.184138\ttrain-error:0.184138\n",
      "[88]\teval-error:0.183987\ttrain-error:0.183987\n",
      "[89]\teval-error:0.184062\ttrain-error:0.184062\n",
      "[90]\teval-error:0.184\ttrain-error:0.184\n",
      "[91]\teval-error:0.18385\ttrain-error:0.18385\n",
      "[92]\teval-error:0.1839\ttrain-error:0.1839\n",
      "[93]\teval-error:0.184062\ttrain-error:0.184062\n",
      "[94]\teval-error:0.1839\ttrain-error:0.1839\n",
      "[95]\teval-error:0.183562\ttrain-error:0.183562\n",
      "[96]\teval-error:0.183375\ttrain-error:0.183375\n",
      "[97]\teval-error:0.18335\ttrain-error:0.18335\n",
      "[98]\teval-error:0.183388\ttrain-error:0.183388\n",
      "[99]\teval-error:0.183025\ttrain-error:0.183025\n",
      "[100]\teval-error:0.183163\ttrain-error:0.183163\n",
      "[101]\teval-error:0.182875\ttrain-error:0.182875\n",
      "[102]\teval-error:0.182938\ttrain-error:0.182938\n",
      "[103]\teval-error:0.1829\ttrain-error:0.1829\n",
      "[104]\teval-error:0.182863\ttrain-error:0.182863\n",
      "[105]\teval-error:0.182825\ttrain-error:0.182825\n",
      "[106]\teval-error:0.182762\ttrain-error:0.182762\n",
      "[107]\teval-error:0.1828\ttrain-error:0.1828\n",
      "[108]\teval-error:0.182875\ttrain-error:0.182875\n",
      "[109]\teval-error:0.1828\ttrain-error:0.1828\n",
      "[110]\teval-error:0.182525\ttrain-error:0.182525\n",
      "[111]\teval-error:0.182588\ttrain-error:0.182588\n",
      "[112]\teval-error:0.18235\ttrain-error:0.18235\n",
      "[113]\teval-error:0.182312\ttrain-error:0.182312\n",
      "[114]\teval-error:0.1822\ttrain-error:0.1822\n",
      "[115]\teval-error:0.182188\ttrain-error:0.182188\n",
      "[116]\teval-error:0.182125\ttrain-error:0.182125\n",
      "[117]\teval-error:0.182225\ttrain-error:0.182225\n",
      "[118]\teval-error:0.182287\ttrain-error:0.182287\n",
      "[119]\teval-error:0.1822\ttrain-error:0.1822\n",
      "[120]\teval-error:0.181987\ttrain-error:0.181987\n",
      "[121]\teval-error:0.181775\ttrain-error:0.181775\n",
      "[122]\teval-error:0.181775\ttrain-error:0.181775\n",
      "[123]\teval-error:0.181838\ttrain-error:0.181838\n",
      "[124]\teval-error:0.181725\ttrain-error:0.181725\n",
      "[125]\teval-error:0.1815\ttrain-error:0.1815\n",
      "[126]\teval-error:0.181388\ttrain-error:0.181388\n",
      "[127]\teval-error:0.1813\ttrain-error:0.1813\n",
      "[128]\teval-error:0.1812\ttrain-error:0.1812\n",
      "[129]\teval-error:0.181287\ttrain-error:0.181287\n",
      "[130]\teval-error:0.181312\ttrain-error:0.181312\n",
      "[131]\teval-error:0.181262\ttrain-error:0.181262\n",
      "[132]\teval-error:0.18095\ttrain-error:0.18095\n",
      "[133]\teval-error:0.1808\ttrain-error:0.1808\n",
      "[134]\teval-error:0.180875\ttrain-error:0.180875\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[135]\teval-error:0.18075\ttrain-error:0.18075\n",
      "[136]\teval-error:0.180613\ttrain-error:0.180613\n",
      "[137]\teval-error:0.180537\ttrain-error:0.180537\n",
      "[138]\teval-error:0.180663\ttrain-error:0.180663\n",
      "[139]\teval-error:0.180537\ttrain-error:0.180537\n",
      "[140]\teval-error:0.18045\ttrain-error:0.18045\n",
      "[141]\teval-error:0.180537\ttrain-error:0.180537\n",
      "[142]\teval-error:0.180512\ttrain-error:0.180512\n",
      "[143]\teval-error:0.18045\ttrain-error:0.18045\n",
      "[144]\teval-error:0.180537\ttrain-error:0.180537\n",
      "[145]\teval-error:0.1804\ttrain-error:0.1804\n",
      "[146]\teval-error:0.18035\ttrain-error:0.18035\n",
      "[147]\teval-error:0.180388\ttrain-error:0.180388\n",
      "[148]\teval-error:0.1804\ttrain-error:0.1804\n",
      "[149]\teval-error:0.18025\ttrain-error:0.18025\n",
      "[150]\teval-error:0.18015\ttrain-error:0.18015\n",
      "[151]\teval-error:0.180025\ttrain-error:0.180025\n",
      "[152]\teval-error:0.179838\ttrain-error:0.179838\n",
      "[153]\teval-error:0.179762\ttrain-error:0.179762\n",
      "[154]\teval-error:0.179613\ttrain-error:0.179613\n",
      "[155]\teval-error:0.17965\ttrain-error:0.17965\n",
      "[156]\teval-error:0.179675\ttrain-error:0.179675\n",
      "[157]\teval-error:0.179512\ttrain-error:0.179512\n",
      "[158]\teval-error:0.1794\ttrain-error:0.1794\n",
      "[159]\teval-error:0.179338\ttrain-error:0.179338\n",
      "[160]\teval-error:0.179237\ttrain-error:0.179237\n",
      "[161]\teval-error:0.179163\ttrain-error:0.179163\n",
      "[162]\teval-error:0.178975\ttrain-error:0.178975\n",
      "[163]\teval-error:0.178925\ttrain-error:0.178925\n",
      "[164]\teval-error:0.178875\ttrain-error:0.178875\n",
      "[165]\teval-error:0.178875\ttrain-error:0.178875\n",
      "time taken: 405.32858872413635\n"
     ]
    }
   ],
   "source": [
    "import xgboost as xgb\n",
    "import time\n",
    "\n",
    "\n",
    "dtrain = xgb.DMatrix(gameX, gameY)\n",
    "num_round = 1000\n",
    "early_stopping_rounds = 50\n",
    "n_fold = 5\n",
    "watchlist = [(dtrain, 'eval'), (dtrain, 'train')]\n",
    "\n",
    "print('running cross validation')\n",
    "\n",
    "print('running cross validation, with preprocessing function')\n",
    "# define the preprocessing function\n",
    "# used to return the preprocessed training, test data, and parameter\n",
    "# we can use this to do weight rescale, etc.\n",
    "# as a example, we try to set scale_pos_weight\n",
    "def fpreproc(dtrain, dtest, param):\n",
    "    label = dtrain.get_label()\n",
    "    ratio = float(np.sum(label == 0)) / np.sum(label == 1)\n",
    "    param['scale_pos_weight'] = ratio\n",
    "    return (dtrain, dtest, param)\n",
    "\n",
    "# do cross validation, for each fold\n",
    "# the dtrain, dtest, param will be passed into fpreproc\n",
    "# then the return value of fpreproc will be used to generate\n",
    "# results of that fold\n",
    "\n",
    "###\n",
    "# you can also do cross validation with customized loss function\n",
    "# See custom_objective.py\n",
    "##\n",
    "print('running cross validation, with cutomsized loss function')\n",
    "#Custom\n",
    "# wt = 0.5\n",
    "# def logregobj(preds, dtrain):\n",
    "#     labels = dtrain.get_label()\n",
    "#     preds = 1.0 / (1.0 + np.exp(-preds))\n",
    "#     grad = wt*(1.0-labels)*preds - (1-wt)*labels*(1-preds)\n",
    "#     hess = preds * (1.0 - preds) * (wt*(1.0-labels)+(1.0-wt)*labels)\n",
    "#     return grad, hess\n",
    "\n",
    "def logregobj(preds, dtrain):\n",
    "    labels = dtrain.get_label()\n",
    "    preds = 1.0 / (1.0 + np.exp(-preds))\n",
    "    grad = preds - labels\n",
    "    hess = preds * (1.0 - preds)\n",
    "    return grad, hess\n",
    "def evalerror(preds, dtrain):\n",
    "    labels = dtrain.get_label()\n",
    "    return 'error', float(sum(labels != (preds > 0.0))) / len(labels)\n",
    "\n",
    "param = {\n",
    "#     'max_depth': 3,#3 \n",
    "    'eta': 0.1, #0.1\n",
    "    'silent': 1, \n",
    "    'gamma': 0, \n",
    "    'max_depth': 4, #4\n",
    "    'min_child_weight': 1, #1\n",
    "    'subsample': 0.8, #0.8\n",
    "    'colsample_bytree': 0.8, #0,8\n",
    "    'reg_lambda': 1, #L2 reg default:1\n",
    "    'reg_alpha': 0.05, #L1 reg default:0\n",
    "    'scale_pos_weight': 1, \n",
    "#     'missing': -999\n",
    "#     'objective': 'binary:logistic', #for custom loss define it in xgb.train(obj=custom_loss)\n",
    "#     'eval_metric': 'error'\n",
    "}\n",
    "\n",
    "t = time.time()\n",
    "# CV to find optimum number of boosted trees (num_round)\n",
    "cvresult = xgb.cv(\n",
    "            param, #param set by user\n",
    "            dtrain, #train set\n",
    "            num_round, #max number of boosted tree, >early_stopping_round\n",
    "            nfold=n_fold, #n fold CV\n",
    "            seed=0, \n",
    "            obj=logregobj, #custom loss func\n",
    "            feval=evalerror, #custom eval metric\n",
    "            callbacks=[xgb.callback.print_evaluation(show_stdv=False),\n",
    "                       xgb.callback.early_stop(early_stopping_rounds)], #decides optimum number of boosted trees, <num_round\n",
    "#             fpreproc=fpreproc, #function for preprocessing\n",
    "            )\n",
    "\n",
    "num_round = cvresult.shape[0] #optimum number of boosted trees\n",
    "# bst = xgb.train(param, dtrain, num_round, watchlist, obj=logregobj, feval=evalerror, fpreproc=fpreproc)\n",
    "bst = xgb.train(param, dtrain, num_round, watchlist, obj=logregobj, feval=evalerror)\n",
    "\n",
    "print(\"time taken:\", time.time()-t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#910k\n",
    "param = {\n",
    "#     'max_depth': 3,#3 \n",
    "    'eta': 0.1, #0.1\n",
    "    'silent': 1, \n",
    "    'gamma': 0, \n",
    "    'max_depth': 4, #4\n",
    "    'min_child_weight': 1.5, #1\n",
    "    'subsample': 0.8, #0.8\n",
    "    'colsample_bytree': 0.8, #0,8\n",
    "    'reg_lambda': 1, #L2 reg default:1\n",
    "    'reg_alpha': 0.05, #L1 reg default:0\n",
    "    'scale_pos_weight': 0.25, \n",
    "#     'missing': -999\n",
    "#     'objective': 'binary:logistic', #for custom loss define it in xgb.train(obj=custom_loss)\n",
    "#     'eval_metric': 'error'\n",
    "}\n",
    "\n",
    "num_round = 231\n",
    "\n",
    "bst = xgb.train(param, dtrain, num_round, obj=logregobj, feval=evalerror)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Jtfdc7zsxDzcxIg2ojEgbPXp0tsoTEckrGb+zl4kYNaLFlf/p7ksB3P1jd9+e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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5518f0bd30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#xgb feature imp\n",
    "from xgboost import plot_importance\n",
    "ax = plot_importance(bst, height=0.5)\n",
    "fig = ax.figure\n",
    "fig.set_size_inches(10,10)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "166"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cvresult.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.98279345, -2.33837748, -1.48666203, ...,  1.02270269,\n",
       "       -1.70188737, -0.75109828], dtype=float32)"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bst.predict(dtrain)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.27233785,  0.08799404,  0.18442327, ...,  0.73549873,\n",
       "        0.15421893,  0.32058203], dtype=float32)"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1/(1+np.exp(-bst.predict(dtrain)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dtest = xgb.DMatrix(leaderX)\n",
    "# pred = bst.predict(leaderXxgb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pred = 1/(1+np.exp(-bst.predict(dtest)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(25000, 2)"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred = pd.DataFrame(pred)\n",
    "pred['application_key'] = leaderAppID\n",
    "pred.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>application_key</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.039178</td>\n",
       "      <td>350053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.057237</td>\n",
       "      <td>350054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.116927</td>\n",
       "      <td>350055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.633439</td>\n",
       "      <td>350056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.118805</td>\n",
       "      <td>350057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.005086</td>\n",
       "      <td>350058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.072675</td>\n",
       "      <td>350059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.004523</td>\n",
       "      <td>350060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.008423</td>\n",
       "      <td>350061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.245321</td>\n",
       "      <td>350062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.056289</td>\n",
       "      <td>350063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.215603</td>\n",
       "      <td>350064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.412575</td>\n",
       "      <td>350065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.903787</td>\n",
       "      <td>350066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.205529</td>\n",
       "      <td>350067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.514564</td>\n",
       "      <td>350068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.014253</td>\n",
       "      <td>350069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.118213</td>\n",
       "      <td>350070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.122459</td>\n",
       "      <td>350071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.109929</td>\n",
       "      <td>350072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.232083</td>\n",
       "      <td>350073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.405025</td>\n",
       "      <td>350074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.011410</td>\n",
       "      <td>350075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.279600</td>\n",
       "      <td>350076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.292731</td>\n",
       "      <td>350077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.003435</td>\n",
       "      <td>350078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.102774</td>\n",
       "      <td>350079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.095699</td>\n",
       "      <td>350080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.863338</td>\n",
       "      <td>350081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.089490</td>\n",
       "      <td>350082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24970</th>\n",
       "      <td>0.144522</td>\n",
       "      <td>375023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24971</th>\n",
       "      <td>0.031652</td>\n",
       "      <td>375024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24972</th>\n",
       "      <td>0.508729</td>\n",
       "      <td>375025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24973</th>\n",
       "      <td>0.688022</td>\n",
       "      <td>375026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24974</th>\n",
       "      <td>0.662918</td>\n",
       "      <td>375027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24975</th>\n",
       "      <td>0.019196</td>\n",
       "      <td>375028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24976</th>\n",
       "      <td>0.272011</td>\n",
       "      <td>375029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24977</th>\n",
       "      <td>0.038254</td>\n",
       "      <td>375030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24978</th>\n",
       "      <td>0.350552</td>\n",
       "      <td>375031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24979</th>\n",
       "      <td>0.484068</td>\n",
       "      <td>375032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24980</th>\n",
       "      <td>0.010452</td>\n",
       "      <td>375033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24981</th>\n",
       "      <td>0.149876</td>\n",
       "      <td>375034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24982</th>\n",
       "      <td>0.676614</td>\n",
       "      <td>375035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24983</th>\n",
       "      <td>0.199820</td>\n",
       "      <td>375036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24984</th>\n",
       "      <td>0.016902</td>\n",
       "      <td>375037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24985</th>\n",
       "      <td>0.387902</td>\n",
       "      <td>375038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24986</th>\n",
       "      <td>0.252847</td>\n",
       "      <td>375039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24987</th>\n",
       "      <td>0.248919</td>\n",
       "      <td>375040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24988</th>\n",
       "      <td>0.489435</td>\n",
       "      <td>375041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24989</th>\n",
       "      <td>0.918367</td>\n",
       "      <td>375042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24990</th>\n",
       "      <td>0.353841</td>\n",
       "      <td>375043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24991</th>\n",
       "      <td>0.023880</td>\n",
       "      <td>375044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24992</th>\n",
       "      <td>0.511481</td>\n",
       "      <td>375045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24993</th>\n",
       "      <td>0.336887</td>\n",
       "      <td>375046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24994</th>\n",
       "      <td>0.269350</td>\n",
       "      <td>375047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24995</th>\n",
       "      <td>0.493467</td>\n",
       "      <td>375048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24996</th>\n",
       "      <td>0.015649</td>\n",
       "      <td>375049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24997</th>\n",
       "      <td>0.121586</td>\n",
       "      <td>375050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24998</th>\n",
       "      <td>0.040434</td>\n",
       "      <td>375051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24999</th>\n",
       "      <td>0.013433</td>\n",
       "      <td>375052</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25000 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              0  application_key\n",
       "0      0.039178           350053\n",
       "1      0.057237           350054\n",
       "2      0.116927           350055\n",
       "3      0.633439           350056\n",
       "4      0.118805           350057\n",
       "5      0.005086           350058\n",
       "6      0.072675           350059\n",
       "7      0.004523           350060\n",
       "8      0.008423           350061\n",
       "9      0.245321           350062\n",
       "10     0.056289           350063\n",
       "11     0.215603           350064\n",
       "12     0.412575           350065\n",
       "13     0.903787           350066\n",
       "14     0.205529           350067\n",
       "15     0.514564           350068\n",
       "16     0.014253           350069\n",
       "17     0.118213           350070\n",
       "18     0.122459           350071\n",
       "19     0.109929           350072\n",
       "20     0.232083           350073\n",
       "21     0.405025           350074\n",
       "22     0.011410           350075\n",
       "23     0.279600           350076\n",
       "24     0.292731           350077\n",
       "25     0.003435           350078\n",
       "26     0.102774           350079\n",
       "27     0.095699           350080\n",
       "28     0.863338           350081\n",
       "29     0.089490           350082\n",
       "...         ...              ...\n",
       "24970  0.144522           375023\n",
       "24971  0.031652           375024\n",
       "24972  0.508729           375025\n",
       "24973  0.688022           375026\n",
       "24974  0.662918           375027\n",
       "24975  0.019196           375028\n",
       "24976  0.272011           375029\n",
       "24977  0.038254           375030\n",
       "24978  0.350552           375031\n",
       "24979  0.484068           375032\n",
       "24980  0.010452           375033\n",
       "24981  0.149876           375034\n",
       "24982  0.676614           375035\n",
       "24983  0.199820           375036\n",
       "24984  0.016902           375037\n",
       "24985  0.387902           375038\n",
       "24986  0.252847           375039\n",
       "24987  0.248919           375040\n",
       "24988  0.489435           375041\n",
       "24989  0.918367           375042\n",
       "24990  0.353841           375043\n",
       "24991  0.023880           375044\n",
       "24992  0.511481           375045\n",
       "24993  0.336887           375046\n",
       "24994  0.269350           375047\n",
       "24995  0.493467           375048\n",
       "24996  0.015649           375049\n",
       "24997  0.121586           375050\n",
       "24998  0.040434           375051\n",
       "24999  0.013433           375052\n",
       "\n",
       "[25000 rows x 2 columns]"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pred = pred.sort_values(by = 0,kind = 'mergesort',ascending = True) #true for xgb method3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "cols = pred.columns.tolist()\n",
    "cols = cols[-1:] + cols[:-1]\n",
    "pred = pred[cols]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pred = pred.loc[:,'application_key':]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "submit = pred['application_key'][:10000]\n",
    "submit = pd.DataFrame(submit)\n",
    "submit[0] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# submit.iloc[-400:, 1] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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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>18109</th>\n",
       "      <td>368162</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1912</th>\n",
       "      <td>351965</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19117</th>\n",
       "      <td>369170</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22865</th>\n",
       "      <td>372918</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3366</th>\n",
       "      <td>353419</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23797</th>\n",
       "      <td>373850</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15849</th>\n",
       "      <td>365902</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>842</th>\n",
       "      <td>350895</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11471</th>\n",
       "      <td>361524</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3708</th>\n",
       "      <td>353761</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22263</th>\n",
       "      <td>372316</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15405</th>\n",
       "      <td>365458</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1600</th>\n",
       "      <td>351653</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2086</th>\n",
       "      <td>352139</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8922</th>\n",
       "      <td>358975</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>350177</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3323</th>\n",
       "      <td>353376</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2469</th>\n",
       "      <td>352522</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11521</th>\n",
       "      <td>361574</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15982</th>\n",
       "      <td>366035</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23965</th>\n",
       "      <td>374018</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2771</th>\n",
       "      <td>352824</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>350246</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11214</th>\n",
       "      <td>361267</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21592</th>\n",
       "      <td>371645</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17879</th>\n",
       "      <td>367932</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20379</th>\n",
       "      <td>370432</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4599</th>\n",
       "      <td>354652</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1701</th>\n",
       "      <td>351754</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8084</th>\n",
       "      <td>358137</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11253</th>\n",
       "      <td>361306</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6055</th>\n",
       "      <td>356108</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>350209</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5945</th>\n",
       "      <td>355998</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3484</th>\n",
       "      <td>353537</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10123</th>\n",
       "      <td>360176</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7602</th>\n",
       "      <td>357655</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21675</th>\n",
       "      <td>371728</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17204</th>\n",
       "      <td>367257</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13612</th>\n",
       "      <td>363665</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18384</th>\n",
       "      <td>368437</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14982</th>\n",
       "      <td>365035</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13548</th>\n",
       "      <td>363601</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17964</th>\n",
       "      <td>368017</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>786</th>\n",
       "      <td>350839</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6177</th>\n",
       "      <td>356230</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6172</th>\n",
       "      <td>356225</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9334</th>\n",
       "      <td>359387</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11634</th>\n",
       "      <td>361687</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4525</th>\n",
       "      <td>354578</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17276</th>\n",
       "      <td>367329</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2940</th>\n",
       "      <td>352993</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22698</th>\n",
       "      <td>372751</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>350055</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1030</th>\n",
       "      <td>351083</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>350418</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21947</th>\n",
       "      <td>372000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1362</th>\n",
       "      <td>351415</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9029</th>\n",
       "      <td>359082</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19541</th>\n",
       "      <td>369594</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",
       "18109           368162  0\n",
       "1912            351965  0\n",
       "19117           369170  0\n",
       "22865           372918  0\n",
       "3366            353419  0\n",
       "23797           373850  0\n",
       "15849           365902  0\n",
       "842             350895  0\n",
       "11471           361524  0\n",
       "3708            353761  0\n",
       "22263           372316  0\n",
       "15405           365458  0\n",
       "1600            351653  0\n",
       "2086            352139  0\n",
       "8922            358975  0\n",
       "124             350177  0\n",
       "3323            353376  0\n",
       "2469            352522  0\n",
       "11521           361574  0\n",
       "15982           366035  0\n",
       "23965           374018  0\n",
       "2771            352824  0\n",
       "193             350246  0\n",
       "11214           361267  0\n",
       "21592           371645  0\n",
       "17879           367932  0\n",
       "20379           370432  0\n",
       "4599            354652  0\n",
       "1701            351754  0\n",
       "8084            358137  0\n",
       "...                ... ..\n",
       "11253           361306  0\n",
       "6055            356108  0\n",
       "156             350209  0\n",
       "5945            355998  0\n",
       "3484            353537  0\n",
       "10123           360176  0\n",
       "7602            357655  0\n",
       "21675           371728  0\n",
       "17204           367257  0\n",
       "13612           363665  0\n",
       "18384           368437  0\n",
       "14982           365035  0\n",
       "13548           363601  0\n",
       "17964           368017  0\n",
       "786             350839  0\n",
       "6177            356230  0\n",
       "6172            356225  0\n",
       "9334            359387  0\n",
       "11634           361687  0\n",
       "4525            354578  0\n",
       "17276           367329  0\n",
       "2940            352993  0\n",
       "22698           372751  0\n",
       "2               350055  0\n",
       "1030            351083  0\n",
       "365             350418  0\n",
       "21947           372000  0\n",
       "1362            351415  0\n",
       "9029            359082  0\n",
       "19541           369594  0\n",
       "\n",
       "[10000 rows x 2 columns]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "submit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "submit.to_csv('flabbergasted_IITGuwahati_170.csv',header = False, index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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