AirPressureSystem.ipynb

{
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     "status": "completed"
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    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "pd.set_option('display.max_columns',None)\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import sklearn\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "621b7741",
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   "outputs": [
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       "      <td>0.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2291079.36</td>\n",
       "      <td>0.0</td>\n",
       "      <td>643536.96</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>98644.0</td>\n",
       "      <td>1179502.0</td>\n",
       "      <td>1286736.0</td>\n",
       "      <td>336388.0</td>\n",
       "      <td>36294.0</td>\n",
       "      <td>5192.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3646660.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6160.0</td>\n",
       "      <td>796.0</td>\n",
       "      <td>164860.0</td>\n",
       "      <td>350066.0</td>\n",
       "      <td>272956.0</td>\n",
       "      <td>1837600.0</td>\n",
       "      <td>301242.0</td>\n",
       "      <td>9148.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3312.0</td>\n",
       "      <td>522.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33736.0</td>\n",
       "      <td>36946.0</td>\n",
       "      <td>5936.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>103330.0</td>\n",
       "      <td>16254.0</td>\n",
       "      <td>4510080.0</td>\n",
       "      <td>868538.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3477820.0</td>\n",
       "      <td>2211.76</td>\n",
       "      <td>2334.0</td>\n",
       "      <td>664504.0</td>\n",
       "      <td>824154.0</td>\n",
       "      <td>421400.0</td>\n",
       "      <td>178064.0</td>\n",
       "      <td>293306.0</td>\n",
       "      <td>245416.0</td>\n",
       "      <td>133654.0</td>\n",
       "      <td>81140.0</td>\n",
       "      <td>97576.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>neg</td>\n",
       "      <td>41040</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.280000e+02</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1648.0</td>\n",
       "      <td>370592.0</td>\n",
       "      <td>1883374.0</td>\n",
       "      <td>292936.0</td>\n",
       "      <td>12016.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1234132.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2371990.0</td>\n",
       "      <td>2173634.0</td>\n",
       "      <td>300796.0</td>\n",
       "      <td>153698.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>358.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>870456.0</td>\n",
       "      <td>239798.0</td>\n",
       "      <td>1450312.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1620.0</td>\n",
       "      <td>1156.0</td>\n",
       "      <td>1228.0</td>\n",
       "      <td>34250.0</td>\n",
       "      <td>1811606.0</td>\n",
       "      <td>710672.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>790690.0</td>\n",
       "      <td>672026.0</td>\n",
       "      <td>332340.0</td>\n",
       "      <td>254892.0</td>\n",
       "      <td>189596.0</td>\n",
       "      <td>135758.0</td>\n",
       "      <td>103552.0</td>\n",
       "      <td>81666.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2673338.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>202.0</td>\n",
       "      <td>576.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1234132.0</td>\n",
       "      <td>28804.0</td>\n",
       "      <td>160176.0</td>\n",
       "      <td>139730.0</td>\n",
       "      <td>137160.0</td>\n",
       "      <td>130640.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28000.0</td>\n",
       "      <td>41040.08</td>\n",
       "      <td>2673338.0</td>\n",
       "      <td>2673338.0</td>\n",
       "      <td>2678534.0</td>\n",
       "      <td>15439.0</td>\n",
       "      <td>7466.0</td>\n",
       "      <td>22436.0</td>\n",
       "      <td>248240.0</td>\n",
       "      <td>2560566.0</td>\n",
       "      <td>1209600.0</td>\n",
       "      <td>63328.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2322692.16</td>\n",
       "      <td>0.0</td>\n",
       "      <td>236099.52</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33276.0</td>\n",
       "      <td>1215280.0</td>\n",
       "      <td>1102798.0</td>\n",
       "      <td>196502.0</td>\n",
       "      <td>10260.0</td>\n",
       "      <td>2422.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2673338.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3584.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>56362.0</td>\n",
       "      <td>149726.0</td>\n",
       "      <td>100326.0</td>\n",
       "      <td>1744838.0</td>\n",
       "      <td>488302.0</td>\n",
       "      <td>16682.0</td>\n",
       "      <td>246.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>292.0</td>\n",
       "      <td>2180528.0</td>\n",
       "      <td>29188.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>20346.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2341048.0</td>\n",
       "      <td>1494.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13876.0</td>\n",
       "      <td>38182.0</td>\n",
       "      <td>8138.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>65772.0</td>\n",
       "      <td>10534.0</td>\n",
       "      <td>300240.0</td>\n",
       "      <td>48028.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1040120.0</td>\n",
       "      <td>1018.64</td>\n",
       "      <td>1020.0</td>\n",
       "      <td>262032.0</td>\n",
       "      <td>453378.0</td>\n",
       "      <td>277378.0</td>\n",
       "      <td>159812.0</td>\n",
       "      <td>423992.0</td>\n",
       "      <td>409564.0</td>\n",
       "      <td>320746.0</td>\n",
       "      <td>158022.0</td>\n",
       "      <td>95128.0</td>\n",
       "      <td>514.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>neg</td>\n",
       "      <td>12</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.000000e+01</td>\n",
       "      <td>66.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>318.0</td>\n",
       "      <td>2212.0</td>\n",
       "      <td>3232.0</td>\n",
       "      <td>1872.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2668.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>642.0</td>\n",
       "      <td>3894.0</td>\n",
       "      <td>10184.0</td>\n",
       "      <td>7554.0</td>\n",
       "      <td>10764.0</td>\n",
       "      <td>1014.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2038.0</td>\n",
       "      <td>5596.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>914.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>2478.0</td>\n",
       "      <td>2398.0</td>\n",
       "      <td>1692.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6176.0</td>\n",
       "      <td>340.0</td>\n",
       "      <td>304.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>406.0</td>\n",
       "      <td>216.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21614.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2668.0</td>\n",
       "      <td>184.0</td>\n",
       "      <td>7632.0</td>\n",
       "      <td>3090.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10580.0</td>\n",
       "      <td>12.69</td>\n",
       "      <td>21614.0</td>\n",
       "      <td>21614.0</td>\n",
       "      <td>21772.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>21400.0</td>\n",
       "      <td>7710.0</td>\n",
       "      <td>1209600.0</td>\n",
       "      <td>302.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2135.04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4525.44</td>\n",
       "      <td>2.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>2544.0</td>\n",
       "      <td>1894.0</td>\n",
       "      <td>2170.0</td>\n",
       "      <td>822.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>21614.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1032.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>656.0</td>\n",
       "      <td>692.0</td>\n",
       "      <td>4836.0</td>\n",
       "      <td>388.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1666.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2578.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>232.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>15740.0</td>\n",
       "      <td>1822.0</td>\n",
       "      <td>20174.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.08</td>\n",
       "      <td>54.0</td>\n",
       "      <td>5670.0</td>\n",
       "      <td>1566.0</td>\n",
       "      <td>240.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>neg</td>\n",
       "      <td>60874</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.368000e+03</td>\n",
       "      <td>458.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>43752.0</td>\n",
       "      <td>1966618.0</td>\n",
       "      <td>1800340.0</td>\n",
       "      <td>131646.0</td>\n",
       "      <td>4588.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1974038.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>226.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3230626.0</td>\n",
       "      <td>2618878.0</td>\n",
       "      <td>1058136.0</td>\n",
       "      <td>551022.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1788.0</td>\n",
       "      <td>642.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42124.0</td>\n",
       "      <td>372236.0</td>\n",
       "      <td>2128914.0</td>\n",
       "      <td>819596.0</td>\n",
       "      <td>584074.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1644.0</td>\n",
       "      <td>362.0</td>\n",
       "      <td>562.0</td>\n",
       "      <td>842.0</td>\n",
       "      <td>30194.0</td>\n",
       "      <td>3911734.0</td>\n",
       "      <td>1606.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1348578.0</td>\n",
       "      <td>1035668.0</td>\n",
       "      <td>338762.0</td>\n",
       "      <td>236540.0</td>\n",
       "      <td>182278.0</td>\n",
       "      <td>151778.0</td>\n",
       "      <td>163248.0</td>\n",
       "      <td>470800.0</td>\n",
       "      <td>19292.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4289260.0</td>\n",
       "      <td>448.0</td>\n",
       "      <td>556.0</td>\n",
       "      <td>642.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1974038.0</td>\n",
       "      <td>86454.0</td>\n",
       "      <td>653692.0</td>\n",
       "      <td>399410.0</td>\n",
       "      <td>306780.0</td>\n",
       "      <td>282560.0</td>\n",
       "      <td>274180.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>189000.0</td>\n",
       "      <td>60874.03</td>\n",
       "      <td>4289260.0</td>\n",
       "      <td>4289260.0</td>\n",
       "      <td>4283332.0</td>\n",
       "      <td>24793.0</td>\n",
       "      <td>17052.0</td>\n",
       "      <td>61844.0</td>\n",
       "      <td>654700.0</td>\n",
       "      <td>3946944.0</td>\n",
       "      <td>1209600.0</td>\n",
       "      <td>135720.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3565684.80</td>\n",
       "      <td>0.0</td>\n",
       "      <td>379111.68</td>\n",
       "      <td>0.0</td>\n",
       "      <td>746.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>378910.0</td>\n",
       "      <td>2497104.0</td>\n",
       "      <td>993000.0</td>\n",
       "      <td>64230.0</td>\n",
       "      <td>10482.0</td>\n",
       "      <td>2776.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>202.0</td>\n",
       "      <td>212.0</td>\n",
       "      <td>4289260.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3942.0</td>\n",
       "      <td>520.0</td>\n",
       "      <td>80950.0</td>\n",
       "      <td>227322.0</td>\n",
       "      <td>186242.0</td>\n",
       "      <td>2288268.0</td>\n",
       "      <td>1137268.0</td>\n",
       "      <td>22228.0</td>\n",
       "      <td>204.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1716.0</td>\n",
       "      <td>1664.0</td>\n",
       "      <td>3440288.0</td>\n",
       "      <td>215826.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4262.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3590004.0</td>\n",
       "      <td>2026.0</td>\n",
       "      <td>444.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>44946.0</td>\n",
       "      <td>62648.0</td>\n",
       "      <td>11506.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>149474.0</td>\n",
       "      <td>35154.0</td>\n",
       "      <td>457040.0</td>\n",
       "      <td>80482.0</td>\n",
       "      <td>98334.0</td>\n",
       "      <td>27588.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21173050.0</td>\n",
       "      <td>1116.06</td>\n",
       "      <td>1176.0</td>\n",
       "      <td>404740.0</td>\n",
       "      <td>904230.0</td>\n",
       "      <td>622012.0</td>\n",
       "      <td>229790.0</td>\n",
       "      <td>405298.0</td>\n",
       "      <td>347188.0</td>\n",
       "      <td>286954.0</td>\n",
       "      <td>311560.0</td>\n",
       "      <td>433954.0</td>\n",
       "      <td>1218.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  class  aa_000  ab_000        ac_000  ad_000  ae_000  af_000  ag_000  ag_001  \\\n",
       "0   neg   76698     NaN  2.130706e+09   280.0     0.0     0.0     0.0     0.0   \n",
       "1   neg   33058     NaN  0.000000e+00     NaN     0.0     0.0     0.0     0.0   \n",
       "2   neg   41040     NaN  2.280000e+02   100.0     0.0     0.0     0.0     0.0   \n",
       "3   neg      12     0.0  7.000000e+01    66.0     0.0    10.0     0.0     0.0   \n",
       "4   neg   60874     NaN  1.368000e+03   458.0     0.0     0.0     0.0     0.0   \n",
       "\n",
       "   ag_002  ag_003   ag_004     ag_005     ag_006     ag_007   ag_008  ag_009  \\\n",
       "0     0.0     0.0  37250.0  1432864.0  3664156.0  1007684.0  25896.0     0.0   \n",
       "1     0.0     0.0  18254.0   653294.0  1720800.0   516724.0  31642.0     0.0   \n",
       "2     0.0     0.0   1648.0   370592.0  1883374.0   292936.0  12016.0     0.0   \n",
       "3     0.0   318.0   2212.0     3232.0     1872.0        0.0      0.0     0.0   \n",
       "4     0.0     0.0  43752.0  1966618.0  1800340.0   131646.0   4588.0     0.0   \n",
       "\n",
       "      ah_000  ai_000  aj_000  ak_000  al_000    am_0     an_000     ao_000  \\\n",
       "0  2551696.0     0.0     0.0     0.0     0.0     0.0  4933296.0  3655166.0   \n",
       "1  1393352.0     0.0    68.0     0.0     0.0     0.0  2560898.0  2127150.0   \n",
       "2  1234132.0     0.0     0.0     0.0     0.0     0.0  2371990.0  2173634.0   \n",
       "3     2668.0     0.0     0.0     0.0   642.0  3894.0    10184.0     7554.0   \n",
       "4  1974038.0     0.0   226.0     0.0     0.0     0.0  3230626.0  2618878.0   \n",
       "\n",
       "      ap_000     aq_000  ar_000  as_000  at_000  au_000  av_000  ax_000  \\\n",
       "0  1766008.0  1132040.0     0.0     0.0     0.0     0.0  1012.0   268.0   \n",
       "1  1084598.0   338544.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2   300796.0   153698.0     0.0     0.0     0.0     0.0   358.0   110.0   \n",
       "3    10764.0     1014.0     0.0     0.0     0.0     0.0    60.0     6.0   \n",
       "4  1058136.0   551022.0     0.0     0.0     0.0     0.0  1788.0   642.0   \n",
       "\n",
       "   ay_000  ay_001  ay_002  ay_003   ay_004    ay_005     ay_006     ay_007  \\\n",
       "0     0.0     0.0     0.0     0.0      0.0  469014.0  4239660.0   703300.0   \n",
       "1     0.0     0.0     0.0     0.0      0.0   71510.0   772720.0  1996924.0   \n",
       "2     0.0     0.0     0.0     0.0      0.0       0.0   870456.0   239798.0   \n",
       "3     0.0     0.0     0.0     0.0      0.0       0.0        0.0     2038.0   \n",
       "4     0.0     0.0     0.0     0.0  42124.0  372236.0  2128914.0   819596.0   \n",
       "\n",
       "      ay_008  ay_009  az_000  az_001   az_002   az_003     az_004     az_005  \\\n",
       "0   755876.0     0.0  5374.0  2108.0   4114.0  12348.0   615248.0  5526276.0   \n",
       "1    99560.0     0.0  7336.0  7808.0  13776.0  13086.0  1010074.0  1873902.0   \n",
       "2  1450312.0     0.0  1620.0  1156.0   1228.0  34250.0  1811606.0   710672.0   \n",
       "3     5596.0     0.0    64.0     6.0      6.0    914.0       76.0     2478.0   \n",
       "4   584074.0     0.0  1644.0   362.0    562.0    842.0    30194.0  3911734.0   \n",
       "\n",
       "    az_006  az_007  az_008  az_009     ba_000     ba_001    ba_002    ba_003  \\\n",
       "0   2378.0     4.0     0.0     0.0  2328746.0  1022304.0  415432.0  287230.0   \n",
       "1  14726.0     6.0     0.0     0.0  1378576.0   447166.0  199512.0  154298.0   \n",
       "2     34.0     0.0     0.0     0.0   790690.0   672026.0  332340.0  254892.0   \n",
       "3   2398.0  1692.0     0.0     0.0     6176.0      340.0     304.0     102.0   \n",
       "4   1606.0     0.0     0.0     0.0  1348578.0  1035668.0  338762.0  236540.0   \n",
       "\n",
       "     ba_004    ba_005     ba_006    ba_007   ba_008  ba_009     bb_000  \\\n",
       "0  310246.0  681504.0  1118814.0    3574.0      0.0     0.0  6700214.0   \n",
       "1  137280.0  138668.0   165908.0  229652.0  87082.0  4708.0  3646660.0   \n",
       "2  189596.0  135758.0   103552.0   81666.0     46.0     0.0  2673338.0   \n",
       "3      74.0     406.0      216.0      16.0      0.0     0.0    21614.0   \n",
       "4  182278.0  151778.0   163248.0  470800.0  19292.0     0.0  4289260.0   \n",
       "\n",
       "   bc_000  bd_000  be_000  bf_000     bg_000   bh_000    bi_000    bj_000  \\\n",
       "0     0.0    10.0   108.0    50.0  2551696.0  97518.0  947550.0  799478.0   \n",
       "1    86.0   454.0   364.0   350.0  1393352.0  49028.0  688314.0  392208.0   \n",
       "2   128.0   202.0   576.0     4.0  1234132.0  28804.0  160176.0  139730.0   \n",
       "3     2.0    12.0     0.0     0.0     2668.0    184.0    7632.0    3090.0   \n",
       "4   448.0   556.0   642.0     2.0  1974038.0  86454.0  653692.0  399410.0   \n",
       "\n",
       "     bk_000    bl_000    bm_000    bn_000    bo_000  bp_000  bq_000  br_000  \\\n",
       "0  330760.0  353400.0  299160.0  305200.0  283680.0     NaN     NaN     NaN   \n",
       "1  341420.0  359780.0  366560.0       NaN       NaN     NaN     NaN     NaN   \n",
       "2  137160.0  130640.0       NaN       NaN       NaN     NaN     NaN     NaN   \n",
       "3       NaN       NaN       NaN       NaN       NaN     NaN     NaN     NaN   \n",
       "4  306780.0  282560.0  274180.0       NaN       NaN     NaN     NaN     NaN   \n",
       "\n",
       "     bs_000    bt_000     bu_000     bv_000     bx_000   by_000    bz_000  \\\n",
       "0  178540.0  76698.08  6700214.0  6700214.0  6599892.0  43566.0   68656.0   \n",
       "1    6700.0  33057.51  3646660.0  3646660.0  3582034.0  17733.0  260120.0   \n",
       "2   28000.0  41040.08  2673338.0  2673338.0  2678534.0  15439.0    7466.0   \n",
       "3   10580.0     12.69    21614.0    21614.0    21772.0     32.0      50.0   \n",
       "4  189000.0  60874.03  4289260.0  4289260.0  4283332.0  24793.0   17052.0   \n",
       "\n",
       "     ca_000    cb_000     cc_000     cd_000    ce_000  cf_000  cg_000  ch_000  \\\n",
       "0   54064.0  638360.0  6167850.0  1209600.0  246244.0     2.0    96.0     0.0   \n",
       "1  115626.0    6900.0  2942850.0  1209600.0       0.0     NaN     NaN     NaN   \n",
       "2   22436.0  248240.0  2560566.0  1209600.0   63328.0     0.0   124.0     0.0   \n",
       "3    1994.0   21400.0     7710.0  1209600.0     302.0     2.0     6.0     0.0   \n",
       "4   61844.0  654700.0  3946944.0  1209600.0  135720.0     0.0   152.0     0.0   \n",
       "\n",
       "       ci_000  cj_000     ck_000  cl_000  cm_000  cn_000  cn_001  cn_002  \\\n",
       "0  5245752.00     0.0  916567.68     6.0  1924.0     0.0     0.0     0.0   \n",
       "1  2291079.36     0.0  643536.96     0.0     0.0     0.0     0.0    38.0   \n",
       "2  2322692.16     0.0  236099.52     0.0     0.0     0.0     0.0     0.0   \n",
       "3     2135.04     0.0    4525.44     2.0    16.0     0.0    52.0  2544.0   \n",
       "4  3565684.80     0.0  379111.68     0.0   746.0     0.0     0.0   356.0   \n",
       "\n",
       "     cn_003     cn_004     cn_005     cn_006   cn_007   cn_008  cn_009  \\\n",
       "0  118196.0  1309472.0  3247182.0  1381362.0  98822.0  11208.0  1608.0   \n",
       "1   98644.0  1179502.0  1286736.0   336388.0  36294.0   5192.0    56.0   \n",
       "2   33276.0  1215280.0  1102798.0   196502.0  10260.0   2422.0    28.0   \n",
       "3    1894.0     2170.0      822.0      152.0      0.0      0.0     0.0   \n",
       "4  378910.0  2497104.0   993000.0    64230.0  10482.0   2776.0    86.0   \n",
       "\n",
       "   co_000  cp_000     cq_000  cr_000   cs_000  cs_001    cs_002    cs_003  \\\n",
       "0   220.0   240.0  6700214.0     NaN  10476.0  1226.0  267998.0  521832.0   \n",
       "1     NaN     0.0  3646660.0     NaN   6160.0   796.0  164860.0  350066.0   \n",
       "2     0.0     6.0  2673338.0     NaN   3584.0   500.0   56362.0  149726.0   \n",
       "3     2.0     2.0    21614.0     0.0   1032.0     6.0      24.0     656.0   \n",
       "4   202.0   212.0  4289260.0     NaN   3942.0   520.0   80950.0  227322.0   \n",
       "\n",
       "     cs_004     cs_005     cs_006   cs_007  cs_008  cs_009  ct_000  cu_000  \\\n",
       "0  428776.0  4015854.0   895240.0  26330.0   118.0     0.0   532.0   734.0   \n",
       "1  272956.0  1837600.0   301242.0   9148.0    22.0     0.0     NaN     NaN   \n",
       "2  100326.0  1744838.0   488302.0  16682.0   246.0     0.0   230.0   292.0   \n",
       "3     692.0     4836.0      388.0      0.0     0.0     0.0   138.0     8.0   \n",
       "4  186242.0  2288268.0  1137268.0  22228.0   204.0     0.0  1716.0  1664.0   \n",
       "\n",
       "      cv_000    cx_000  cy_000    cz_000  da_000  db_000     dc_000  dd_000  \\\n",
       "0  4122704.0   51288.0     0.0  532572.0     0.0    18.0  5330690.0  4732.0   \n",
       "1        NaN       NaN     NaN       NaN     NaN     NaN        NaN  3312.0   \n",
       "2  2180528.0   29188.0    22.0   20346.0     0.0     0.0  2341048.0  1494.0   \n",
       "3     1666.0      72.0     0.0      12.0     0.0     0.0     2578.0    76.0   \n",
       "4  3440288.0  215826.0     0.0    4262.0     0.0     0.0  3590004.0  2026.0   \n",
       "\n",
       "   de_000  df_000  dg_000  dh_000  di_000  dj_000  dk_000  dl_000  dm_000  \\\n",
       "0  1126.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "1   522.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2   152.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "3    62.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "4   444.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "\n",
       "    dn_000   do_000   dp_000  dq_000  dr_000    ds_000   dt_000      du_000  \\\n",
       "0  62282.0  85908.0  32790.0     0.0     0.0  202710.0  37928.0  14745580.0   \n",
       "1  33736.0  36946.0   5936.0     0.0     0.0  103330.0  16254.0   4510080.0   \n",
       "2  13876.0  38182.0   8138.0     0.0     0.0   65772.0  10534.0    300240.0   \n",
       "3    232.0      0.0      0.0  2014.0   370.0      48.0     18.0     15740.0   \n",
       "4  44946.0  62648.0  11506.0     0.0     0.0  149474.0  35154.0    457040.0   \n",
       "\n",
       "      dv_000   dx_000   dy_000  dz_000  ea_000      eb_000    ec_00  ed_000  \\\n",
       "0  1876644.0      0.0      0.0     0.0     0.0   2801180.0  2445.80  2712.0   \n",
       "1   868538.0      0.0      0.0     0.0     0.0   3477820.0  2211.76  2334.0   \n",
       "2    48028.0      0.0      0.0     0.0     0.0   1040120.0  1018.64  1020.0   \n",
       "3     1822.0  20174.0     44.0     0.0     0.0         0.0     1.08    54.0   \n",
       "4    80482.0  98334.0  27588.0     0.0     0.0  21173050.0  1116.06  1176.0   \n",
       "\n",
       "     ee_000     ee_001     ee_002    ee_003    ee_004    ee_005    ee_006  \\\n",
       "0  965866.0  1706908.0  1240520.0  493384.0  721044.0  469792.0  339156.0   \n",
       "1  664504.0   824154.0   421400.0  178064.0  293306.0  245416.0  133654.0   \n",
       "2  262032.0   453378.0   277378.0  159812.0  423992.0  409564.0  320746.0   \n",
       "3    5670.0     1566.0      240.0      46.0      58.0      44.0      10.0   \n",
       "4  404740.0   904230.0   622012.0  229790.0  405298.0  347188.0  286954.0   \n",
       "\n",
       "     ee_007    ee_008  ee_009  ef_000  eg_000  \n",
       "0  157956.0   73224.0     0.0     0.0     0.0  \n",
       "1   81140.0   97576.0  1500.0     0.0     0.0  \n",
       "2  158022.0   95128.0   514.0     0.0     0.0  \n",
       "3       0.0       0.0     0.0     4.0    32.0  \n",
       "4  311560.0  433954.0  1218.0     0.0     0.0  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df = pd.read_csv('/kaggle/input/aps-failure-at-scania-trucks-data-set/aps_failure_training_set.csv',na_values=[\"na\"])\n",
    "train_df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6536443c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:18.545576Z",
     "iopub.status.busy": "2023-06-07T14:18:18.545141Z",
     "iopub.status.idle": "2023-06-07T14:18:18.552246Z",
     "shell.execute_reply": "2023-06-07T14:18:18.551134Z"
    },
    "papermill": {
     "duration": 0.028694,
     "end_time": "2023-06-07T14:18:18.554812",
     "exception": false,
     "start_time": "2023-06-07T14:18:18.526118",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(60000, 171)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "eda364d5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:18.593960Z",
     "iopub.status.busy": "2023-06-07T14:18:18.592893Z",
     "iopub.status.idle": "2023-06-07T14:18:19.343872Z",
     "shell.execute_reply": "2023-06-07T14:18:19.342747Z"
    },
    "papermill": {
     "duration": 0.773914,
     "end_time": "2023-06-07T14:18:19.347583",
     "exception": false,
     "start_time": "2023-06-07T14:18:18.573669",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "      <th>ee_002</th>\n",
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       "      <th>ee_004</th>\n",
       "      <th>ee_005</th>\n",
       "      <th>ee_006</th>\n",
       "      <th>ee_007</th>\n",
       "      <th>ee_008</th>\n",
       "      <th>ee_009</th>\n",
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       "      <th>0</th>\n",
       "      <td>neg</td>\n",
       "      <td>60</td>\n",
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       "      <td>20.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2682.0</td>\n",
       "      <td>4736.0</td>\n",
       "      <td>3862.0</td>\n",
       "      <td>1846.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3976.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1520.0</td>\n",
       "      <td>2374.0</td>\n",
       "      <td>11516.0</td>\n",
       "      <td>9480.0</td>\n",
       "      <td>111258.0</td>\n",
       "      <td>470.0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>58.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13124.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1956.0</td>\n",
       "      <td>434.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>174.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>6198.0</td>\n",
       "      <td>1148.0</td>\n",
       "      <td>2948.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8762.0</td>\n",
       "      <td>2566.0</td>\n",
       "      <td>480.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>196.0</td>\n",
       "      <td>516.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>124340.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3976.0</td>\n",
       "      <td>318.0</td>\n",
       "      <td>107662.0</td>\n",
       "      <td>3458.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>110980.0</td>\n",
       "      <td>59.53</td>\n",
       "      <td>124340.0</td>\n",
       "      <td>124340.0</td>\n",
       "      <td>184970.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>686.0</td>\n",
       "      <td>12246.0</td>\n",
       "      <td>123880.0</td>\n",
       "      <td>13196.0</td>\n",
       "      <td>1209600.0</td>\n",
       "      <td>598.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5913.60</td>\n",
       "      <td>0.00</td>\n",
       "      <td>5851.20</td>\n",
       "      <td>6.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5512.0</td>\n",
       "      <td>4674.0</td>\n",
       "      <td>1388.0</td>\n",
       "      <td>1508.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>124340.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1550.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>920.0</td>\n",
       "      <td>430.0</td>\n",
       "      <td>7650.0</td>\n",
       "      <td>2294.0</td>\n",
       "      <td>206.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>5336.0</td>\n",
       "      <td>1276.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6598.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>340.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>574.0</td>\n",
       "      <td>232.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>780.0</td>\n",
       "      <td>882.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>465.50</td>\n",
       "      <td>90.0</td>\n",
       "      <td>7502.0</td>\n",
       "      <td>3156.0</td>\n",
       "      <td>1098.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>412.0</td>\n",
       "      <td>654.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>neg</td>\n",
       "      <td>82</td>\n",
       "      <td>0.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>748.0</td>\n",
       "      <td>12594.0</td>\n",
       "      <td>3636.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5244.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23174.0</td>\n",
       "      <td>18166.0</td>\n",
       "      <td>23686.0</td>\n",
       "      <td>1270.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>692.0</td>\n",
       "      <td>16286.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>1274.0</td>\n",
       "      <td>866.0</td>\n",
       "      <td>3362.0</td>\n",
       "      <td>11102.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12564.0</td>\n",
       "      <td>1756.0</td>\n",
       "      <td>638.0</td>\n",
       "      <td>276.0</td>\n",
       "      <td>172.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>812.0</td>\n",
       "      <td>308.0</td>\n",
       "      <td>192.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>46894.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5244.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>20520.0</td>\n",
       "      <td>3134.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23320.0</td>\n",
       "      <td>81.89</td>\n",
       "      <td>46894.0</td>\n",
       "      <td>46894.0</td>\n",
       "      <td>48324.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4486.0</td>\n",
       "      <td>46480.0</td>\n",
       "      <td>17050.0</td>\n",
       "      <td>1209600.0</td>\n",
       "      <td>726.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7224.96</td>\n",
       "      <td>0.00</td>\n",
       "      <td>7768.32</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7064.0</td>\n",
       "      <td>6200.0</td>\n",
       "      <td>2452.0</td>\n",
       "      <td>1246.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>46894.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2202.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>114.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>700.0</td>\n",
       "      <td>1708.0</td>\n",
       "      <td>9622.0</td>\n",
       "      <td>2174.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>206.0</td>\n",
       "      <td>7802.0</td>\n",
       "      <td>1466.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7918.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>352.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3996.0</td>\n",
       "      <td>584.0</td>\n",
       "      <td>200.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>37580.0</td>\n",
       "      <td>3756.0</td>\n",
       "      <td>6368.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.86</td>\n",
       "      <td>102.0</td>\n",
       "      <td>10040.0</td>\n",
       "      <td>3310.0</td>\n",
       "      <td>1068.0</td>\n",
       "      <td>276.0</td>\n",
       "      <td>1620.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>462.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>neg</td>\n",
       "      <td>66002</td>\n",
       "      <td>2.0</td>\n",
       "      <td>212.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>199486.0</td>\n",
       "      <td>1358536.0</td>\n",
       "      <td>1952422.0</td>\n",
       "      <td>452706.0</td>\n",
       "      <td>25130.0</td>\n",
       "      <td>520.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1891670.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>77898.0</td>\n",
       "      <td>110548.0</td>\n",
       "      <td>3605894.0</td>\n",
       "      <td>3291610.0</td>\n",
       "      <td>959756.0</td>\n",
       "      <td>286536.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>340.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24286.0</td>\n",
       "      <td>681260.0</td>\n",
       "      <td>2808472.0</td>\n",
       "      <td>474782.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22984.0</td>\n",
       "      <td>894.0</td>\n",
       "      <td>1162.0</td>\n",
       "      <td>1304.0</td>\n",
       "      <td>1856.0</td>\n",
       "      <td>388700.0</td>\n",
       "      <td>3424812.0</td>\n",
       "      <td>123828.0</td>\n",
       "      <td>23260.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1662580.0</td>\n",
       "      <td>667960.0</td>\n",
       "      <td>387998.0</td>\n",
       "      <td>226078.0</td>\n",
       "      <td>161558.0</td>\n",
       "      <td>148288.0</td>\n",
       "      <td>154908.0</td>\n",
       "      <td>220820.0</td>\n",
       "      <td>147744.0</td>\n",
       "      <td>210866.0</td>\n",
       "      <td>4644422.0</td>\n",
       "      <td>958.0</td>\n",
       "      <td>7848.0</td>\n",
       "      <td>3624.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1891670.0</td>\n",
       "      <td>47066.0</td>\n",
       "      <td>692800.0</td>\n",
       "      <td>265492.0</td>\n",
       "      <td>336240.0</td>\n",
       "      <td>194360.0</td>\n",
       "      <td>245240.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>175480.0</td>\n",
       "      <td>66002.89</td>\n",
       "      <td>4644422.0</td>\n",
       "      <td>4644422.0</td>\n",
       "      <td>4608738.0</td>\n",
       "      <td>22706.0</td>\n",
       "      <td>2272.0</td>\n",
       "      <td>95510.0</td>\n",
       "      <td>1006260.0</td>\n",
       "      <td>3991552.0</td>\n",
       "      <td>1209600.0</td>\n",
       "      <td>126310.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3594885.12</td>\n",
       "      <td>0.00</td>\n",
       "      <td>374649.60</td>\n",
       "      <td>148.0</td>\n",
       "      <td>720.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5154.0</td>\n",
       "      <td>174956.0</td>\n",
       "      <td>622312.0</td>\n",
       "      <td>1002504.0</td>\n",
       "      <td>793938.0</td>\n",
       "      <td>541734.0</td>\n",
       "      <td>345896.0</td>\n",
       "      <td>300806.0</td>\n",
       "      <td>201500.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>4644422.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24818.0</td>\n",
       "      <td>964.0</td>\n",
       "      <td>162660.0</td>\n",
       "      <td>215004.0</td>\n",
       "      <td>217930.0</td>\n",
       "      <td>3038612.0</td>\n",
       "      <td>322718.0</td>\n",
       "      <td>6080.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>226.0</td>\n",
       "      <td>572.0</td>\n",
       "      <td>3593728.0</td>\n",
       "      <td>1911060.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>284.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3613906.0</td>\n",
       "      <td>4218.0</td>\n",
       "      <td>692.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25278.0</td>\n",
       "      <td>9438.0</td>\n",
       "      <td>2504.0</td>\n",
       "      <td>10262714.0</td>\n",
       "      <td>1278664.0</td>\n",
       "      <td>109700.0</td>\n",
       "      <td>19072.0</td>\n",
       "      <td>9520.0</td>\n",
       "      <td>4902.0</td>\n",
       "      <td>4434614.0</td>\n",
       "      <td>70900.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>26002880.0</td>\n",
       "      <td>2057.84</td>\n",
       "      <td>2158.0</td>\n",
       "      <td>396312.0</td>\n",
       "      <td>538136.0</td>\n",
       "      <td>495076.0</td>\n",
       "      <td>380368.0</td>\n",
       "      <td>440134.0</td>\n",
       "      <td>269556.0</td>\n",
       "      <td>1315022.0</td>\n",
       "      <td>153680.0</td>\n",
       "      <td>516.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>neg</td>\n",
       "      <td>59816</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1010.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>123922.0</td>\n",
       "      <td>984314.0</td>\n",
       "      <td>1680050.0</td>\n",
       "      <td>1135268.0</td>\n",
       "      <td>92606.0</td>\n",
       "      <td>14038.0</td>\n",
       "      <td>1772828.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1116.0</td>\n",
       "      <td>2372.0</td>\n",
       "      <td>3546760.0</td>\n",
       "      <td>3053176.0</td>\n",
       "      <td>652616.0</td>\n",
       "      <td>423374.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7274.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1622.0</td>\n",
       "      <td>432.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6388.0</td>\n",
       "      <td>1091104.0</td>\n",
       "      <td>2930694.0</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3526.0</td>\n",
       "      <td>904.0</td>\n",
       "      <td>1426.0</td>\n",
       "      <td>223226.0</td>\n",
       "      <td>2663348.0</td>\n",
       "      <td>1137664.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1283806.0</td>\n",
       "      <td>928212.0</td>\n",
       "      <td>345132.0</td>\n",
       "      <td>265930.0</td>\n",
       "      <td>194770.0</td>\n",
       "      <td>158262.0</td>\n",
       "      <td>219942.0</td>\n",
       "      <td>620264.0</td>\n",
       "      <td>13880.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4201350.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>238.0</td>\n",
       "      <td>880.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1772828.0</td>\n",
       "      <td>51468.0</td>\n",
       "      <td>331744.0</td>\n",
       "      <td>316130.0</td>\n",
       "      <td>176000.0</td>\n",
       "      <td>208420.0</td>\n",
       "      <td>159380.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100120.0</td>\n",
       "      <td>59816.46</td>\n",
       "      <td>4201350.0</td>\n",
       "      <td>4201350.0</td>\n",
       "      <td>4203050.0</td>\n",
       "      <td>29967.0</td>\n",
       "      <td>26214.0</td>\n",
       "      <td>51894.0</td>\n",
       "      <td>562680.0</td>\n",
       "      <td>4030198.0</td>\n",
       "      <td>1209600.0</td>\n",
       "      <td>114684.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>144.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3387773.76</td>\n",
       "      <td>38633.28</td>\n",
       "      <td>599624.64</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14308.0</td>\n",
       "      <td>475410.0</td>\n",
       "      <td>1109740.0</td>\n",
       "      <td>1528024.0</td>\n",
       "      <td>837114.0</td>\n",
       "      <td>58942.0</td>\n",
       "      <td>6220.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>1278.0</td>\n",
       "      <td>1292.0</td>\n",
       "      <td>4201350.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6846.0</td>\n",
       "      <td>810.0</td>\n",
       "      <td>70090.0</td>\n",
       "      <td>345884.0</td>\n",
       "      <td>191284.0</td>\n",
       "      <td>2454600.0</td>\n",
       "      <td>926846.0</td>\n",
       "      <td>33558.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1516.0</td>\n",
       "      <td>1398.0</td>\n",
       "      <td>2050280.0</td>\n",
       "      <td>64066.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>674.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>3413978.0</td>\n",
       "      <td>2924.0</td>\n",
       "      <td>414.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>38710.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27740.0</td>\n",
       "      <td>33354.0</td>\n",
       "      <td>6330.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>133542.0</td>\n",
       "      <td>21290.0</td>\n",
       "      <td>2718360.0</td>\n",
       "      <td>435370.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1179900.0</td>\n",
       "      <td>1541.32</td>\n",
       "      <td>1678.0</td>\n",
       "      <td>659550.0</td>\n",
       "      <td>691580.0</td>\n",
       "      <td>540820.0</td>\n",
       "      <td>243270.0</td>\n",
       "      <td>483302.0</td>\n",
       "      <td>485332.0</td>\n",
       "      <td>431376.0</td>\n",
       "      <td>210074.0</td>\n",
       "      <td>281662.0</td>\n",
       "      <td>3232.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>neg</td>\n",
       "      <td>1814</td>\n",
       "      <td>NaN</td>\n",
       "      <td>156.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>17926.0</td>\n",
       "      <td>82834.0</td>\n",
       "      <td>3114.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>48978.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>97146.0</td>\n",
       "      <td>89920.0</td>\n",
       "      <td>12932.0</td>\n",
       "      <td>5092.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11544.0</td>\n",
       "      <td>73570.0</td>\n",
       "      <td>3662.0</td>\n",
       "      <td>15170.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>10768.0</td>\n",
       "      <td>92898.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>53558.0</td>\n",
       "      <td>34620.0</td>\n",
       "      <td>9824.0</td>\n",
       "      <td>4552.0</td>\n",
       "      <td>764.0</td>\n",
       "      <td>294.0</td>\n",
       "      <td>192.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>110094.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>986.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>48978.0</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>7932.0</td>\n",
       "      <td>4966.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12700.0</td>\n",
       "      <td>1813.74</td>\n",
       "      <td>110094.0</td>\n",
       "      <td>110094.0</td>\n",
       "      <td>113274.0</td>\n",
       "      <td>364.0</td>\n",
       "      <td>330.0</td>\n",
       "      <td>10874.0</td>\n",
       "      <td>109880.0</td>\n",
       "      <td>103946.0</td>\n",
       "      <td>1209600.0</td>\n",
       "      <td>1832.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>94319.04</td>\n",
       "      <td>0.00</td>\n",
       "      <td>9556.80</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6560.0</td>\n",
       "      <td>77394.0</td>\n",
       "      <td>17810.0</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>110094.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>144.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>5532.0</td>\n",
       "      <td>1792.0</td>\n",
       "      <td>30864.0</td>\n",
       "      <td>63436.0</td>\n",
       "      <td>1986.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>93820.0</td>\n",
       "      <td>57312.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>95372.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>538.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1822.0</td>\n",
       "      <td>344.0</td>\n",
       "      <td>2140.0</td>\n",
       "      <td>394.0</td>\n",
       "      <td>13664.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>813740.0</td>\n",
       "      <td>113.86</td>\n",
       "      <td>52.0</td>\n",
       "      <td>10216.0</td>\n",
       "      <td>9958.0</td>\n",
       "      <td>7646.0</td>\n",
       "      <td>4144.0</td>\n",
       "      <td>18466.0</td>\n",
       "      <td>49782.0</td>\n",
       "      <td>3176.0</td>\n",
       "      <td>482.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  class  aa_000  ab_000  ac_000  ad_000  ae_000  af_000  ag_000  ag_001  \\\n",
       "0   neg      60     0.0    20.0    12.0     0.0     0.0     0.0     0.0   \n",
       "1   neg      82     0.0    68.0    40.0     0.0     0.0     0.0     0.0   \n",
       "2   neg   66002     2.0   212.0   112.0     0.0     0.0     0.0     0.0   \n",
       "3   neg   59816     NaN  1010.0   936.0     0.0     0.0     0.0     0.0   \n",
       "4   neg    1814     NaN   156.0   140.0     0.0     0.0     0.0     0.0   \n",
       "\n",
       "   ag_002    ag_003     ag_004     ag_005     ag_006     ag_007   ag_008  \\\n",
       "0     0.0    2682.0     4736.0     3862.0     1846.0        0.0      0.0   \n",
       "1     0.0       0.0      748.0    12594.0     3636.0        0.0      0.0   \n",
       "2     0.0  199486.0  1358536.0  1952422.0   452706.0    25130.0    520.0   \n",
       "3     0.0       0.0   123922.0   984314.0  1680050.0  1135268.0  92606.0   \n",
       "4     0.0       0.0       72.0    17926.0    82834.0     3114.0      0.0   \n",
       "\n",
       "    ag_009     ah_000  ai_000  aj_000  ak_000   al_000      am_0     an_000  \\\n",
       "0      0.0     3976.0     0.0     0.0     0.0   1520.0    2374.0    11516.0   \n",
       "1      0.0     5244.0     0.0    60.0     0.0      0.0       0.0    23174.0   \n",
       "2      0.0  1891670.0     0.0     0.0     0.0  77898.0  110548.0  3605894.0   \n",
       "3  14038.0  1772828.0     0.0     0.0     0.0   1116.0    2372.0  3546760.0   \n",
       "4      0.0    48978.0     0.0     0.0     0.0      0.0       0.0    97146.0   \n",
       "\n",
       "      ao_000    ap_000    aq_000  ar_000  as_000  at_000  au_000  av_000  \\\n",
       "0     9480.0  111258.0     470.0     0.0     0.0     0.0     0.0    58.0   \n",
       "1    18166.0   23686.0    1270.0     0.0     0.0     0.0     0.0    12.0   \n",
       "2  3291610.0  959756.0  286536.0     0.0     0.0     0.0     0.0   106.0   \n",
       "3  3053176.0  652616.0  423374.0     0.0     0.0  7274.0     0.0  1622.0   \n",
       "4    89920.0   12932.0    5092.0     0.0     0.0     0.0     0.0   102.0   \n",
       "\n",
       "   ax_000  ay_000  ay_001  ay_002  ay_003  ay_004   ay_005     ay_006  \\\n",
       "0    26.0     0.0     0.0     0.0     0.0     0.0      0.0        0.0   \n",
       "1    82.0     0.0     0.0     0.0     0.0     0.0      0.0        0.0   \n",
       "2   340.0     0.0     0.0     0.0     0.0     0.0  24286.0   681260.0   \n",
       "3   432.0     0.0     0.0     0.0     0.0     0.0   6388.0  1091104.0   \n",
       "4    50.0     0.0     0.0     0.0     0.0     0.0  11544.0    73570.0   \n",
       "\n",
       "      ay_007    ay_008  ay_009   az_000  az_001  az_002    az_003     az_004  \\\n",
       "0        0.0   13124.0     2.0   1956.0   434.0    76.0     174.0      190.0   \n",
       "1      692.0   16286.0     0.0    280.0    44.0    50.0    1274.0      866.0   \n",
       "2  2808472.0  474782.0     0.0  22984.0   894.0  1162.0    1304.0     1856.0   \n",
       "3  2930694.0    2012.0     0.0   3526.0   904.0  1426.0  223226.0  2663348.0   \n",
       "4     3662.0   15170.0     0.0    126.0    34.0    60.0      58.0    10768.0   \n",
       "\n",
       "      az_005     az_006    az_007   az_008  az_009     ba_000    ba_001  \\\n",
       "0     6198.0     1148.0    2948.0      2.0     0.0     8762.0    2566.0   \n",
       "1     3362.0    11102.0       0.0      0.0     0.0    12564.0    1756.0   \n",
       "2   388700.0  3424812.0  123828.0  23260.0     0.0  1662580.0  667960.0   \n",
       "3  1137664.0      104.0       0.0      0.0     0.0  1283806.0  928212.0   \n",
       "4    92898.0        2.0       0.0      0.0     0.0    53558.0   34620.0   \n",
       "\n",
       "     ba_002    ba_003    ba_004    ba_005    ba_006    ba_007    ba_008  \\\n",
       "0     480.0     380.0     196.0     516.0      86.0      66.0      74.0   \n",
       "1     638.0     276.0     172.0     132.0     812.0     308.0     192.0   \n",
       "2  387998.0  226078.0  161558.0  148288.0  154908.0  220820.0  147744.0   \n",
       "3  345132.0  265930.0  194770.0  158262.0  219942.0  620264.0   13880.0   \n",
       "4    9824.0    4552.0     764.0     294.0     192.0     142.0       0.0   \n",
       "\n",
       "     ba_009     bb_000  bc_000  bd_000  be_000  bf_000     bg_000   bh_000  \\\n",
       "0       0.0   124340.0     4.0     6.0     4.0     0.0     3976.0    318.0   \n",
       "1     128.0    46894.0     4.0     2.0    38.0     0.0     5244.0    360.0   \n",
       "2  210866.0  4644422.0   958.0  7848.0  3624.0     0.0  1891670.0  47066.0   \n",
       "3       0.0  4201350.0    98.0   238.0   880.0    16.0  1772828.0  51468.0   \n",
       "4       0.0   110094.0     4.0     4.0   986.0     0.0    48978.0   1100.0   \n",
       "\n",
       "     bi_000    bj_000    bk_000    bl_000    bm_000  bn_000  bo_000  bp_000  \\\n",
       "0  107662.0    3458.0       NaN       NaN       NaN     NaN     NaN     NaN   \n",
       "1   20520.0    3134.0       NaN       NaN       NaN     NaN     NaN     NaN   \n",
       "2  692800.0  265492.0  336240.0  194360.0  245240.0     NaN     NaN     NaN   \n",
       "3  331744.0  316130.0  176000.0  208420.0  159380.0     NaN     NaN     NaN   \n",
       "4    7932.0    4966.0       NaN       NaN       NaN     NaN     NaN     NaN   \n",
       "\n",
       "   bq_000  br_000    bs_000    bt_000     bu_000     bv_000     bx_000  \\\n",
       "0     NaN     NaN  110980.0     59.53   124340.0   124340.0   184970.0   \n",
       "1     NaN     NaN   23320.0     81.89    46894.0    46894.0    48324.0   \n",
       "2     NaN     NaN  175480.0  66002.89  4644422.0  4644422.0  4608738.0   \n",
       "3     NaN     NaN  100120.0  59816.46  4201350.0  4201350.0  4203050.0   \n",
       "4     NaN     NaN   12700.0   1813.74   110094.0   110094.0   113274.0   \n",
       "\n",
       "    by_000   bz_000   ca_000     cb_000     cc_000     cd_000    ce_000  \\\n",
       "0     54.0    686.0  12246.0   123880.0    13196.0  1209600.0     598.0   \n",
       "1     68.0      0.0   4486.0    46480.0    17050.0  1209600.0     726.0   \n",
       "2  22706.0   2272.0  95510.0  1006260.0  3991552.0  1209600.0  126310.0   \n",
       "3  29967.0  26214.0  51894.0   562680.0  4030198.0  1209600.0  114684.0   \n",
       "4    364.0    330.0  10874.0   109880.0   103946.0  1209600.0    1832.0   \n",
       "\n",
       "   cf_000  cg_000  ch_000      ci_000    cj_000     ck_000  cl_000  cm_000  \\\n",
       "0     0.0     6.0     0.0     5913.60      0.00    5851.20     6.0    30.0   \n",
       "1     2.0     4.0     0.0     7224.96      0.00    7768.32     0.0    42.0   \n",
       "2     0.0   104.0     0.0  3594885.12      0.00  374649.60   148.0   720.0   \n",
       "3     0.0   144.0     0.0  3387773.76  38633.28  599624.64     0.0     0.0   \n",
       "4     0.0     8.0     0.0    94319.04      0.00    9556.80     0.0     0.0   \n",
       "\n",
       "   cn_000  cn_001    cn_002    cn_003     cn_004     cn_005    cn_006  \\\n",
       "0     0.0     2.0    5512.0    4674.0     1388.0     1508.0      38.0   \n",
       "1     0.0     0.0       4.0    7064.0     6200.0     2452.0    1246.0   \n",
       "2     0.0  5154.0  174956.0  622312.0  1002504.0   793938.0  541734.0   \n",
       "3     0.0     0.0   14308.0  475410.0  1109740.0  1528024.0  837114.0   \n",
       "4     0.0     0.0       0.0    6560.0    77394.0    17810.0    1924.0   \n",
       "\n",
       "     cn_007    cn_008    cn_009  co_000  cp_000     cq_000  cr_000   cs_000  \\\n",
       "0       4.0       0.0       0.0     8.0    12.0   124340.0     0.0   1550.0   \n",
       "1      12.0       0.0       0.0    14.0    54.0    46894.0     0.0   2202.0   \n",
       "2  345896.0  300806.0  201500.0    52.0    92.0  4644422.0     0.0  24818.0   \n",
       "3   58942.0    6220.0     440.0  1278.0  1292.0  4201350.0     NaN   6846.0   \n",
       "4     230.0      28.0       0.0     2.0    10.0   110094.0     NaN    144.0   \n",
       "\n",
       "   cs_001    cs_002    cs_003    cs_004     cs_005    cs_006   cs_007  cs_008  \\\n",
       "0    14.0      36.0      26.0     920.0      430.0    7650.0   2294.0   206.0   \n",
       "1    28.0     114.0     350.0     700.0     1708.0    9622.0   2174.0    80.0   \n",
       "2   964.0  162660.0  215004.0  217930.0  3038612.0  322718.0   6080.0    14.0   \n",
       "3   810.0   70090.0  345884.0  191284.0  2454600.0  926846.0  33558.0   280.0   \n",
       "4    14.0      86.0    5532.0    1792.0    30864.0   63436.0   1986.0    92.0   \n",
       "\n",
       "   cs_009  ct_000  cu_000     cv_000     cx_000  cy_000  cz_000  da_000  \\\n",
       "0     0.0    22.0    42.0     5336.0     1276.0     0.0     0.0     0.0   \n",
       "1     0.0    80.0   206.0     7802.0     1466.0     0.0     0.0     0.0   \n",
       "2     0.0   226.0   572.0  3593728.0  1911060.0     0.0   284.0     0.0   \n",
       "3     0.0  1516.0  1398.0  2050280.0    64066.0     0.0   674.0     0.0   \n",
       "4     0.0   230.0   178.0    93820.0    57312.0    44.0     4.0     0.0   \n",
       "\n",
       "   db_000     dc_000  dd_000  de_000  df_000  dg_000  dh_000   di_000  dj_000  \\\n",
       "0     0.0     6598.0    70.0   112.0     0.0     0.0     0.0      0.0     0.0   \n",
       "1     0.0     7918.0    78.0    40.0     0.0     0.0     0.0      0.0     0.0   \n",
       "2     0.0  3613906.0  4218.0   692.0     0.0     0.0     0.0      0.0     0.0   \n",
       "3    46.0  3413978.0  2924.0   414.0     0.0     0.0    60.0  38710.0     0.0   \n",
       "4     0.0    95372.0    78.0    36.0     0.0     0.0     0.0      0.0     0.0   \n",
       "\n",
       "   dk_000  dl_000  dm_000   dn_000   do_000  dp_000      dq_000     dr_000  \\\n",
       "0     0.0     0.0     0.0    340.0      0.0     0.0      1100.0      574.0   \n",
       "1     0.0     0.0     0.0    352.0      0.0     0.0      3996.0      584.0   \n",
       "2     0.0     0.0     0.0  25278.0   9438.0  2504.0  10262714.0  1278664.0   \n",
       "3     0.0     0.0     0.0  27740.0  33354.0  6330.0         0.0        0.0   \n",
       "4     0.0     0.0     0.0    538.0    360.0   142.0         0.0        0.0   \n",
       "\n",
       "     ds_000   dt_000     du_000    dv_000     dx_000   dy_000  dz_000  ea_000  \\\n",
       "0     232.0     66.0      780.0     882.0        0.0      4.0     0.0     0.0   \n",
       "1     200.0     62.0    37580.0    3756.0     6368.0     36.0     0.0     0.0   \n",
       "2  109700.0  19072.0     9520.0    4902.0  4434614.0  70900.0     0.0     0.0   \n",
       "3  133542.0  21290.0  2718360.0  435370.0        0.0      0.0     0.0     0.0   \n",
       "4    1822.0    344.0     2140.0     394.0    13664.0    110.0     0.0     0.0   \n",
       "\n",
       "       eb_000    ec_00  ed_000    ee_000    ee_001    ee_002    ee_003  \\\n",
       "0         0.0   465.50    90.0    7502.0    3156.0    1098.0     138.0   \n",
       "1         0.0     2.86   102.0   10040.0    3310.0    1068.0     276.0   \n",
       "2  26002880.0  2057.84  2158.0  396312.0  538136.0  495076.0  380368.0   \n",
       "3   1179900.0  1541.32  1678.0  659550.0  691580.0  540820.0  243270.0   \n",
       "4    813740.0   113.86    52.0   10216.0    9958.0    7646.0    4144.0   \n",
       "\n",
       "     ee_004    ee_005     ee_006    ee_007    ee_008  ee_009  ef_000  eg_000  \n",
       "0     412.0     654.0       78.0      88.0       0.0     0.0     0.0     0.0  \n",
       "1    1620.0     116.0       86.0     462.0       0.0     0.0     0.0     0.0  \n",
       "2  440134.0  269556.0  1315022.0  153680.0     516.0     0.0     0.0     0.0  \n",
       "3  483302.0  485332.0   431376.0  210074.0  281662.0  3232.0     0.0     0.0  \n",
       "4   18466.0   49782.0     3176.0     482.0      76.0     0.0     0.0     0.0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_df = pd.read_csv('/kaggle/input/aps-failure-at-scania-trucks-data-set/aps_failure_test_set.csv',na_values=[\"na\"])\n",
    "test_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6fdd27ff",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:19.389268Z",
     "iopub.status.busy": "2023-06-07T14:18:19.388878Z",
     "iopub.status.idle": "2023-06-07T14:18:19.395562Z",
     "shell.execute_reply": "2023-06-07T14:18:19.394417Z"
    },
    "papermill": {
     "duration": 0.030379,
     "end_time": "2023-06-07T14:18:19.397987",
     "exception": false,
     "start_time": "2023-06-07T14:18:19.367608",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(16000, 171)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6060ddbe",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:19.439895Z",
     "iopub.status.busy": "2023-06-07T14:18:19.439513Z",
     "iopub.status.idle": "2023-06-07T14:18:19.482343Z",
     "shell.execute_reply": "2023-06-07T14:18:19.480842Z"
    },
    "papermill": {
     "duration": 0.067007,
     "end_time": "2023-06-07T14:18:19.485391",
     "exception": false,
     "start_time": "2023-06-07T14:18:19.418384",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_20/715710.py:1: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df=train_df.append(test_df)\n"
     ]
    }
   ],
   "source": [
    "df=train_df.append(test_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "7aee0fd2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:19.526192Z",
     "iopub.status.busy": "2023-06-07T14:18:19.525782Z",
     "iopub.status.idle": "2023-06-07T14:18:19.738723Z",
     "shell.execute_reply": "2023-06-07T14:18:19.737563Z"
    },
    "papermill": {
     "duration": 0.23655,
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3312.0</td>\n",
       "      <td>522.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33736.0</td>\n",
       "      <td>36946.0</td>\n",
       "      <td>5936.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>103330.0</td>\n",
       "      <td>16254.0</td>\n",
       "      <td>4510080.0</td>\n",
       "      <td>868538.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3477820.0</td>\n",
       "      <td>2211.76</td>\n",
       "      <td>2334.0</td>\n",
       "      <td>664504.0</td>\n",
       "      <td>824154.0</td>\n",
       "      <td>421400.0</td>\n",
       "      <td>178064.0</td>\n",
       "      <td>293306.0</td>\n",
       "      <td>245416.0</td>\n",
       "      <td>133654.0</td>\n",
       "      <td>81140.0</td>\n",
       "      <td>97576.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>neg</td>\n",
       "      <td>41040</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.280000e+02</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1648.0</td>\n",
       "      <td>370592.0</td>\n",
       "      <td>1883374.0</td>\n",
       "      <td>292936.0</td>\n",
       "      <td>12016.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1234132.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2371990.0</td>\n",
       "      <td>2173634.0</td>\n",
       "      <td>300796.0</td>\n",
       "      <td>153698.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>358.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>870456.0</td>\n",
       "      <td>239798.0</td>\n",
       "      <td>1450312.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1620.0</td>\n",
       "      <td>1156.0</td>\n",
       "      <td>1228.0</td>\n",
       "      <td>34250.0</td>\n",
       "      <td>1811606.0</td>\n",
       "      <td>710672.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>790690.0</td>\n",
       "      <td>672026.0</td>\n",
       "      <td>332340.0</td>\n",
       "      <td>254892.0</td>\n",
       "      <td>189596.0</td>\n",
       "      <td>135758.0</td>\n",
       "      <td>103552.0</td>\n",
       "      <td>81666.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2673338.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>202.0</td>\n",
       "      <td>576.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1234132.0</td>\n",
       "      <td>28804.0</td>\n",
       "      <td>160176.0</td>\n",
       "      <td>139730.0</td>\n",
       "      <td>137160.0</td>\n",
       "      <td>130640.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28000.0</td>\n",
       "      <td>41040.08</td>\n",
       "      <td>2673338.0</td>\n",
       "      <td>2673338.0</td>\n",
       "      <td>2678534.0</td>\n",
       "      <td>15439.0</td>\n",
       "      <td>7466.0</td>\n",
       "      <td>22436.0</td>\n",
       "      <td>248240.0</td>\n",
       "      <td>2560566.0</td>\n",
       "      <td>1209600.0</td>\n",
       "      <td>63328.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2322692.16</td>\n",
       "      <td>0.0</td>\n",
       "      <td>236099.52</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33276.0</td>\n",
       "      <td>1215280.0</td>\n",
       "      <td>1102798.0</td>\n",
       "      <td>196502.0</td>\n",
       "      <td>10260.0</td>\n",
       "      <td>2422.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2673338.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3584.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>56362.0</td>\n",
       "      <td>149726.0</td>\n",
       "      <td>100326.0</td>\n",
       "      <td>1744838.0</td>\n",
       "      <td>488302.0</td>\n",
       "      <td>16682.0</td>\n",
       "      <td>246.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>292.0</td>\n",
       "      <td>2180528.0</td>\n",
       "      <td>29188.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>20346.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2341048.0</td>\n",
       "      <td>1494.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13876.0</td>\n",
       "      <td>38182.0</td>\n",
       "      <td>8138.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>65772.0</td>\n",
       "      <td>10534.0</td>\n",
       "      <td>300240.0</td>\n",
       "      <td>48028.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1040120.0</td>\n",
       "      <td>1018.64</td>\n",
       "      <td>1020.0</td>\n",
       "      <td>262032.0</td>\n",
       "      <td>453378.0</td>\n",
       "      <td>277378.0</td>\n",
       "      <td>159812.0</td>\n",
       "      <td>423992.0</td>\n",
       "      <td>409564.0</td>\n",
       "      <td>320746.0</td>\n",
       "      <td>158022.0</td>\n",
       "      <td>95128.0</td>\n",
       "      <td>514.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>neg</td>\n",
       "      <td>12</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.000000e+01</td>\n",
       "      <td>66.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>318.0</td>\n",
       "      <td>2212.0</td>\n",
       "      <td>3232.0</td>\n",
       "      <td>1872.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2668.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>642.0</td>\n",
       "      <td>3894.0</td>\n",
       "      <td>10184.0</td>\n",
       "      <td>7554.0</td>\n",
       "      <td>10764.0</td>\n",
       "      <td>1014.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2038.0</td>\n",
       "      <td>5596.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>914.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>2478.0</td>\n",
       "      <td>2398.0</td>\n",
       "      <td>1692.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6176.0</td>\n",
       "      <td>340.0</td>\n",
       "      <td>304.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>406.0</td>\n",
       "      <td>216.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21614.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2668.0</td>\n",
       "      <td>184.0</td>\n",
       "      <td>7632.0</td>\n",
       "      <td>3090.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10580.0</td>\n",
       "      <td>12.69</td>\n",
       "      <td>21614.0</td>\n",
       "      <td>21614.0</td>\n",
       "      <td>21772.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>21400.0</td>\n",
       "      <td>7710.0</td>\n",
       "      <td>1209600.0</td>\n",
       "      <td>302.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2135.04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4525.44</td>\n",
       "      <td>2.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>2544.0</td>\n",
       "      <td>1894.0</td>\n",
       "      <td>2170.0</td>\n",
       "      <td>822.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>21614.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1032.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>656.0</td>\n",
       "      <td>692.0</td>\n",
       "      <td>4836.0</td>\n",
       "      <td>388.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1666.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2578.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>232.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>15740.0</td>\n",
       "      <td>1822.0</td>\n",
       "      <td>20174.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.08</td>\n",
       "      <td>54.0</td>\n",
       "      <td>5670.0</td>\n",
       "      <td>1566.0</td>\n",
       "      <td>240.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>neg</td>\n",
       "      <td>60874</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.368000e+03</td>\n",
       "      <td>458.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>43752.0</td>\n",
       "      <td>1966618.0</td>\n",
       "      <td>1800340.0</td>\n",
       "      <td>131646.0</td>\n",
       "      <td>4588.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1974038.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>226.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3230626.0</td>\n",
       "      <td>2618878.0</td>\n",
       "      <td>1058136.0</td>\n",
       "      <td>551022.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1788.0</td>\n",
       "      <td>642.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42124.0</td>\n",
       "      <td>372236.0</td>\n",
       "      <td>2128914.0</td>\n",
       "      <td>819596.0</td>\n",
       "      <td>584074.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1644.0</td>\n",
       "      <td>362.0</td>\n",
       "      <td>562.0</td>\n",
       "      <td>842.0</td>\n",
       "      <td>30194.0</td>\n",
       "      <td>3911734.0</td>\n",
       "      <td>1606.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1348578.0</td>\n",
       "      <td>1035668.0</td>\n",
       "      <td>338762.0</td>\n",
       "      <td>236540.0</td>\n",
       "      <td>182278.0</td>\n",
       "      <td>151778.0</td>\n",
       "      <td>163248.0</td>\n",
       "      <td>470800.0</td>\n",
       "      <td>19292.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4289260.0</td>\n",
       "      <td>448.0</td>\n",
       "      <td>556.0</td>\n",
       "      <td>642.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1974038.0</td>\n",
       "      <td>86454.0</td>\n",
       "      <td>653692.0</td>\n",
       "      <td>399410.0</td>\n",
       "      <td>306780.0</td>\n",
       "      <td>282560.0</td>\n",
       "      <td>274180.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>189000.0</td>\n",
       "      <td>60874.03</td>\n",
       "      <td>4289260.0</td>\n",
       "      <td>4289260.0</td>\n",
       "      <td>4283332.0</td>\n",
       "      <td>24793.0</td>\n",
       "      <td>17052.0</td>\n",
       "      <td>61844.0</td>\n",
       "      <td>654700.0</td>\n",
       "      <td>3946944.0</td>\n",
       "      <td>1209600.0</td>\n",
       "      <td>135720.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3565684.80</td>\n",
       "      <td>0.0</td>\n",
       "      <td>379111.68</td>\n",
       "      <td>0.0</td>\n",
       "      <td>746.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>378910.0</td>\n",
       "      <td>2497104.0</td>\n",
       "      <td>993000.0</td>\n",
       "      <td>64230.0</td>\n",
       "      <td>10482.0</td>\n",
       "      <td>2776.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>202.0</td>\n",
       "      <td>212.0</td>\n",
       "      <td>4289260.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3942.0</td>\n",
       "      <td>520.0</td>\n",
       "      <td>80950.0</td>\n",
       "      <td>227322.0</td>\n",
       "      <td>186242.0</td>\n",
       "      <td>2288268.0</td>\n",
       "      <td>1137268.0</td>\n",
       "      <td>22228.0</td>\n",
       "      <td>204.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1716.0</td>\n",
       "      <td>1664.0</td>\n",
       "      <td>3440288.0</td>\n",
       "      <td>215826.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4262.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3590004.0</td>\n",
       "      <td>2026.0</td>\n",
       "      <td>444.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>44946.0</td>\n",
       "      <td>62648.0</td>\n",
       "      <td>11506.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>149474.0</td>\n",
       "      <td>35154.0</td>\n",
       "      <td>457040.0</td>\n",
       "      <td>80482.0</td>\n",
       "      <td>98334.0</td>\n",
       "      <td>27588.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21173050.0</td>\n",
       "      <td>1116.06</td>\n",
       "      <td>1176.0</td>\n",
       "      <td>404740.0</td>\n",
       "      <td>904230.0</td>\n",
       "      <td>622012.0</td>\n",
       "      <td>229790.0</td>\n",
       "      <td>405298.0</td>\n",
       "      <td>347188.0</td>\n",
       "      <td>286954.0</td>\n",
       "      <td>311560.0</td>\n",
       "      <td>433954.0</td>\n",
       "      <td>1218.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  class  aa_000  ab_000        ac_000  ad_000  ae_000  af_000  ag_000  ag_001  \\\n",
       "0   neg   76698     NaN  2.130706e+09   280.0     0.0     0.0     0.0     0.0   \n",
       "1   neg   33058     NaN  0.000000e+00     NaN     0.0     0.0     0.0     0.0   \n",
       "2   neg   41040     NaN  2.280000e+02   100.0     0.0     0.0     0.0     0.0   \n",
       "3   neg      12     0.0  7.000000e+01    66.0     0.0    10.0     0.0     0.0   \n",
       "4   neg   60874     NaN  1.368000e+03   458.0     0.0     0.0     0.0     0.0   \n",
       "\n",
       "   ag_002  ag_003   ag_004     ag_005     ag_006     ag_007   ag_008  ag_009  \\\n",
       "0     0.0     0.0  37250.0  1432864.0  3664156.0  1007684.0  25896.0     0.0   \n",
       "1     0.0     0.0  18254.0   653294.0  1720800.0   516724.0  31642.0     0.0   \n",
       "2     0.0     0.0   1648.0   370592.0  1883374.0   292936.0  12016.0     0.0   \n",
       "3     0.0   318.0   2212.0     3232.0     1872.0        0.0      0.0     0.0   \n",
       "4     0.0     0.0  43752.0  1966618.0  1800340.0   131646.0   4588.0     0.0   \n",
       "\n",
       "      ah_000  ai_000  aj_000  ak_000  al_000    am_0     an_000     ao_000  \\\n",
       "0  2551696.0     0.0     0.0     0.0     0.0     0.0  4933296.0  3655166.0   \n",
       "1  1393352.0     0.0    68.0     0.0     0.0     0.0  2560898.0  2127150.0   \n",
       "2  1234132.0     0.0     0.0     0.0     0.0     0.0  2371990.0  2173634.0   \n",
       "3     2668.0     0.0     0.0     0.0   642.0  3894.0    10184.0     7554.0   \n",
       "4  1974038.0     0.0   226.0     0.0     0.0     0.0  3230626.0  2618878.0   \n",
       "\n",
       "      ap_000     aq_000  ar_000  as_000  at_000  au_000  av_000  ax_000  \\\n",
       "0  1766008.0  1132040.0     0.0     0.0     0.0     0.0  1012.0   268.0   \n",
       "1  1084598.0   338544.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2   300796.0   153698.0     0.0     0.0     0.0     0.0   358.0   110.0   \n",
       "3    10764.0     1014.0     0.0     0.0     0.0     0.0    60.0     6.0   \n",
       "4  1058136.0   551022.0     0.0     0.0     0.0     0.0  1788.0   642.0   \n",
       "\n",
       "   ay_000  ay_001  ay_002  ay_003   ay_004    ay_005     ay_006     ay_007  \\\n",
       "0     0.0     0.0     0.0     0.0      0.0  469014.0  4239660.0   703300.0   \n",
       "1     0.0     0.0     0.0     0.0      0.0   71510.0   772720.0  1996924.0   \n",
       "2     0.0     0.0     0.0     0.0      0.0       0.0   870456.0   239798.0   \n",
       "3     0.0     0.0     0.0     0.0      0.0       0.0        0.0     2038.0   \n",
       "4     0.0     0.0     0.0     0.0  42124.0  372236.0  2128914.0   819596.0   \n",
       "\n",
       "      ay_008  ay_009  az_000  az_001   az_002   az_003     az_004     az_005  \\\n",
       "0   755876.0     0.0  5374.0  2108.0   4114.0  12348.0   615248.0  5526276.0   \n",
       "1    99560.0     0.0  7336.0  7808.0  13776.0  13086.0  1010074.0  1873902.0   \n",
       "2  1450312.0     0.0  1620.0  1156.0   1228.0  34250.0  1811606.0   710672.0   \n",
       "3     5596.0     0.0    64.0     6.0      6.0    914.0       76.0     2478.0   \n",
       "4   584074.0     0.0  1644.0   362.0    562.0    842.0    30194.0  3911734.0   \n",
       "\n",
       "    az_006  az_007  az_008  az_009     ba_000     ba_001    ba_002    ba_003  \\\n",
       "0   2378.0     4.0     0.0     0.0  2328746.0  1022304.0  415432.0  287230.0   \n",
       "1  14726.0     6.0     0.0     0.0  1378576.0   447166.0  199512.0  154298.0   \n",
       "2     34.0     0.0     0.0     0.0   790690.0   672026.0  332340.0  254892.0   \n",
       "3   2398.0  1692.0     0.0     0.0     6176.0      340.0     304.0     102.0   \n",
       "4   1606.0     0.0     0.0     0.0  1348578.0  1035668.0  338762.0  236540.0   \n",
       "\n",
       "     ba_004    ba_005     ba_006    ba_007   ba_008  ba_009     bb_000  \\\n",
       "0  310246.0  681504.0  1118814.0    3574.0      0.0     0.0  6700214.0   \n",
       "1  137280.0  138668.0   165908.0  229652.0  87082.0  4708.0  3646660.0   \n",
       "2  189596.0  135758.0   103552.0   81666.0     46.0     0.0  2673338.0   \n",
       "3      74.0     406.0      216.0      16.0      0.0     0.0    21614.0   \n",
       "4  182278.0  151778.0   163248.0  470800.0  19292.0     0.0  4289260.0   \n",
       "\n",
       "   bc_000  bd_000  be_000  bf_000     bg_000   bh_000    bi_000    bj_000  \\\n",
       "0     0.0    10.0   108.0    50.0  2551696.0  97518.0  947550.0  799478.0   \n",
       "1    86.0   454.0   364.0   350.0  1393352.0  49028.0  688314.0  392208.0   \n",
       "2   128.0   202.0   576.0     4.0  1234132.0  28804.0  160176.0  139730.0   \n",
       "3     2.0    12.0     0.0     0.0     2668.0    184.0    7632.0    3090.0   \n",
       "4   448.0   556.0   642.0     2.0  1974038.0  86454.0  653692.0  399410.0   \n",
       "\n",
       "     bk_000    bl_000    bm_000    bn_000    bo_000  bp_000  bq_000  br_000  \\\n",
       "0  330760.0  353400.0  299160.0  305200.0  283680.0     NaN     NaN     NaN   \n",
       "1  341420.0  359780.0  366560.0       NaN       NaN     NaN     NaN     NaN   \n",
       "2  137160.0  130640.0       NaN       NaN       NaN     NaN     NaN     NaN   \n",
       "3       NaN       NaN       NaN       NaN       NaN     NaN     NaN     NaN   \n",
       "4  306780.0  282560.0  274180.0       NaN       NaN     NaN     NaN     NaN   \n",
       "\n",
       "     bs_000    bt_000     bu_000     bv_000     bx_000   by_000    bz_000  \\\n",
       "0  178540.0  76698.08  6700214.0  6700214.0  6599892.0  43566.0   68656.0   \n",
       "1    6700.0  33057.51  3646660.0  3646660.0  3582034.0  17733.0  260120.0   \n",
       "2   28000.0  41040.08  2673338.0  2673338.0  2678534.0  15439.0    7466.0   \n",
       "3   10580.0     12.69    21614.0    21614.0    21772.0     32.0      50.0   \n",
       "4  189000.0  60874.03  4289260.0  4289260.0  4283332.0  24793.0   17052.0   \n",
       "\n",
       "     ca_000    cb_000     cc_000     cd_000    ce_000  cf_000  cg_000  ch_000  \\\n",
       "0   54064.0  638360.0  6167850.0  1209600.0  246244.0     2.0    96.0     0.0   \n",
       "1  115626.0    6900.0  2942850.0  1209600.0       0.0     NaN     NaN     NaN   \n",
       "2   22436.0  248240.0  2560566.0  1209600.0   63328.0     0.0   124.0     0.0   \n",
       "3    1994.0   21400.0     7710.0  1209600.0     302.0     2.0     6.0     0.0   \n",
       "4   61844.0  654700.0  3946944.0  1209600.0  135720.0     0.0   152.0     0.0   \n",
       "\n",
       "       ci_000  cj_000     ck_000  cl_000  cm_000  cn_000  cn_001  cn_002  \\\n",
       "0  5245752.00     0.0  916567.68     6.0  1924.0     0.0     0.0     0.0   \n",
       "1  2291079.36     0.0  643536.96     0.0     0.0     0.0     0.0    38.0   \n",
       "2  2322692.16     0.0  236099.52     0.0     0.0     0.0     0.0     0.0   \n",
       "3     2135.04     0.0    4525.44     2.0    16.0     0.0    52.0  2544.0   \n",
       "4  3565684.80     0.0  379111.68     0.0   746.0     0.0     0.0   356.0   \n",
       "\n",
       "     cn_003     cn_004     cn_005     cn_006   cn_007   cn_008  cn_009  \\\n",
       "0  118196.0  1309472.0  3247182.0  1381362.0  98822.0  11208.0  1608.0   \n",
       "1   98644.0  1179502.0  1286736.0   336388.0  36294.0   5192.0    56.0   \n",
       "2   33276.0  1215280.0  1102798.0   196502.0  10260.0   2422.0    28.0   \n",
       "3    1894.0     2170.0      822.0      152.0      0.0      0.0     0.0   \n",
       "4  378910.0  2497104.0   993000.0    64230.0  10482.0   2776.0    86.0   \n",
       "\n",
       "   co_000  cp_000     cq_000  cr_000   cs_000  cs_001    cs_002    cs_003  \\\n",
       "0   220.0   240.0  6700214.0     NaN  10476.0  1226.0  267998.0  521832.0   \n",
       "1     NaN     0.0  3646660.0     NaN   6160.0   796.0  164860.0  350066.0   \n",
       "2     0.0     6.0  2673338.0     NaN   3584.0   500.0   56362.0  149726.0   \n",
       "3     2.0     2.0    21614.0     0.0   1032.0     6.0      24.0     656.0   \n",
       "4   202.0   212.0  4289260.0     NaN   3942.0   520.0   80950.0  227322.0   \n",
       "\n",
       "     cs_004     cs_005     cs_006   cs_007  cs_008  cs_009  ct_000  cu_000  \\\n",
       "0  428776.0  4015854.0   895240.0  26330.0   118.0     0.0   532.0   734.0   \n",
       "1  272956.0  1837600.0   301242.0   9148.0    22.0     0.0     NaN     NaN   \n",
       "2  100326.0  1744838.0   488302.0  16682.0   246.0     0.0   230.0   292.0   \n",
       "3     692.0     4836.0      388.0      0.0     0.0     0.0   138.0     8.0   \n",
       "4  186242.0  2288268.0  1137268.0  22228.0   204.0     0.0  1716.0  1664.0   \n",
       "\n",
       "      cv_000    cx_000  cy_000    cz_000  da_000  db_000     dc_000  dd_000  \\\n",
       "0  4122704.0   51288.0     0.0  532572.0     0.0    18.0  5330690.0  4732.0   \n",
       "1        NaN       NaN     NaN       NaN     NaN     NaN        NaN  3312.0   \n",
       "2  2180528.0   29188.0    22.0   20346.0     0.0     0.0  2341048.0  1494.0   \n",
       "3     1666.0      72.0     0.0      12.0     0.0     0.0     2578.0    76.0   \n",
       "4  3440288.0  215826.0     0.0    4262.0     0.0     0.0  3590004.0  2026.0   \n",
       "\n",
       "   de_000  df_000  dg_000  dh_000  di_000  dj_000  dk_000  dl_000  dm_000  \\\n",
       "0  1126.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "1   522.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2   152.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "3    62.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "4   444.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "\n",
       "    dn_000   do_000   dp_000  dq_000  dr_000    ds_000   dt_000      du_000  \\\n",
       "0  62282.0  85908.0  32790.0     0.0     0.0  202710.0  37928.0  14745580.0   \n",
       "1  33736.0  36946.0   5936.0     0.0     0.0  103330.0  16254.0   4510080.0   \n",
       "2  13876.0  38182.0   8138.0     0.0     0.0   65772.0  10534.0    300240.0   \n",
       "3    232.0      0.0      0.0  2014.0   370.0      48.0     18.0     15740.0   \n",
       "4  44946.0  62648.0  11506.0     0.0     0.0  149474.0  35154.0    457040.0   \n",
       "\n",
       "      dv_000   dx_000   dy_000  dz_000  ea_000      eb_000    ec_00  ed_000  \\\n",
       "0  1876644.0      0.0      0.0     0.0     0.0   2801180.0  2445.80  2712.0   \n",
       "1   868538.0      0.0      0.0     0.0     0.0   3477820.0  2211.76  2334.0   \n",
       "2    48028.0      0.0      0.0     0.0     0.0   1040120.0  1018.64  1020.0   \n",
       "3     1822.0  20174.0     44.0     0.0     0.0         0.0     1.08    54.0   \n",
       "4    80482.0  98334.0  27588.0     0.0     0.0  21173050.0  1116.06  1176.0   \n",
       "\n",
       "     ee_000     ee_001     ee_002    ee_003    ee_004    ee_005    ee_006  \\\n",
       "0  965866.0  1706908.0  1240520.0  493384.0  721044.0  469792.0  339156.0   \n",
       "1  664504.0   824154.0   421400.0  178064.0  293306.0  245416.0  133654.0   \n",
       "2  262032.0   453378.0   277378.0  159812.0  423992.0  409564.0  320746.0   \n",
       "3    5670.0     1566.0      240.0      46.0      58.0      44.0      10.0   \n",
       "4  404740.0   904230.0   622012.0  229790.0  405298.0  347188.0  286954.0   \n",
       "\n",
       "     ee_007    ee_008  ee_009  ef_000  eg_000  \n",
       "0  157956.0   73224.0     0.0     0.0     0.0  \n",
       "1   81140.0   97576.0  1500.0     0.0     0.0  \n",
       "2  158022.0   95128.0   514.0     0.0     0.0  \n",
       "3       0.0       0.0     0.0     4.0    32.0  \n",
       "4  311560.0  433954.0  1218.0     0.0     0.0  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "155cdbea",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:19.786818Z",
     "iopub.status.busy": "2023-06-07T14:18:19.785618Z",
     "iopub.status.idle": "2023-06-07T14:18:19.793423Z",
     "shell.execute_reply": "2023-06-07T14:18:19.792122Z"
    },
    "papermill": {
     "duration": 0.033013,
     "end_time": "2023-06-07T14:18:19.795947",
     "exception": false,
     "start_time": "2023-06-07T14:18:19.762934",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(76000, 171)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a1982ef6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:19.840267Z",
     "iopub.status.busy": "2023-06-07T14:18:19.839813Z",
     "iopub.status.idle": "2023-06-07T14:18:19.879301Z",
     "shell.execute_reply": "2023-06-07T14:18:19.877918Z"
    },
    "papermill": {
     "duration": 0.06442,
     "end_time": "2023-06-07T14:18:19.881662",
     "exception": false,
     "start_time": "2023-06-07T14:18:19.817242",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 76000 entries, 0 to 15999\n",
      "Columns: 171 entries, class to eg_000\n",
      "dtypes: float64(169), int64(1), object(1)\n",
      "memory usage: 99.7+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "2c2ff36e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:19.926573Z",
     "iopub.status.busy": "2023-06-07T14:18:19.926134Z",
     "iopub.status.idle": "2023-06-07T14:18:21.053642Z",
     "shell.execute_reply": "2023-06-07T14:18:21.052526Z"
    },
    "papermill": {
     "duration": 1.153119,
     "end_time": "2023-06-07T14:18:21.056200",
     "exception": false,
     "start_time": "2023-06-07T14:18:19.903081",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>aa_000</th>\n",
       "      <td>76000.0</td>\n",
       "      <td>6.115976e+04</td>\n",
       "      <td>2.647366e+05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>860.0</td>\n",
       "      <td>30813.0</td>\n",
       "      <td>48840.0</td>\n",
       "      <td>4.294967e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ab_000</th>\n",
       "      <td>17308.0</td>\n",
       "      <td>7.255604e-01</td>\n",
       "      <td>3.311913e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.040000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ac_000</th>\n",
       "      <td>71739.0</td>\n",
       "      <td>3.564398e+08</td>\n",
       "      <td>7.952530e+08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>154.0</td>\n",
       "      <td>970.0</td>\n",
       "      <td>2.130707e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ad_000</th>\n",
       "      <td>57158.0</td>\n",
       "      <td>1.506300e+05</td>\n",
       "      <td>3.590593e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>430.0</td>\n",
       "      <td>8.584298e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ae_000</th>\n",
       "      <td>72810.0</td>\n",
       "      <td>6.736959e+00</td>\n",
       "      <td>1.534465e+02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.105000e+04</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ee_007</th>\n",
       "      <td>75137.0</td>\n",
       "      <td>3.475611e+05</td>\n",
       "      <td>1.707593e+06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>41260.0</td>\n",
       "      <td>168046.0</td>\n",
       "      <td>1.195801e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ee_008</th>\n",
       "      <td>75137.0</td>\n",
       "      <td>1.398968e+05</td>\n",
       "      <td>4.692327e+05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3862.0</td>\n",
       "      <td>139500.0</td>\n",
       "      <td>1.926740e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ee_009</th>\n",
       "      <td>75137.0</td>\n",
       "      <td>8.424984e+03</td>\n",
       "      <td>4.875440e+04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>4.570398e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ef_000</th>\n",
       "      <td>72514.0</td>\n",
       "      <td>8.519734e-02</td>\n",
       "      <td>4.179600e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.820000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>eg_000</th>\n",
       "      <td>72515.0</td>\n",
       "      <td>2.190443e-01</td>\n",
       "      <td>1.023705e+01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.720000e+03</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>170 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          count          mean           std  min    25%      50%       75%  \\\n",
       "aa_000  76000.0  6.115976e+04  2.647366e+05  0.0  860.0  30813.0   48840.0   \n",
       "ab_000  17308.0  7.255604e-01  3.311913e+00  0.0    0.0      0.0       0.0   \n",
       "ac_000  71739.0  3.564398e+08  7.952530e+08  0.0   16.0    154.0     970.0   \n",
       "ad_000  57158.0  1.506300e+05  3.590593e+07  0.0   24.0    128.0     430.0   \n",
       "ae_000  72810.0  6.736959e+00  1.534465e+02  0.0    0.0      0.0       0.0   \n",
       "...         ...           ...           ...  ...    ...      ...       ...   \n",
       "ee_007  75137.0  3.475611e+05  1.707593e+06  0.0  112.0  41260.0  168046.0   \n",
       "ee_008  75137.0  1.398968e+05  4.692327e+05  0.0    0.0   3862.0  139500.0   \n",
       "ee_009  75137.0  8.424984e+03  4.875440e+04  0.0    0.0      0.0    2000.0   \n",
       "ef_000  72514.0  8.519734e-02  4.179600e+00  0.0    0.0      0.0       0.0   \n",
       "eg_000  72515.0  2.190443e-01  1.023705e+01  0.0    0.0      0.0       0.0   \n",
       "\n",
       "                 max  \n",
       "aa_000  4.294967e+07  \n",
       "ab_000  2.040000e+02  \n",
       "ac_000  2.130707e+09  \n",
       "ad_000  8.584298e+09  \n",
       "ae_000  2.105000e+04  \n",
       "...              ...  \n",
       "ee_007  1.195801e+08  \n",
       "ee_008  1.926740e+07  \n",
       "ee_009  4.570398e+06  \n",
       "ef_000  4.820000e+02  \n",
       "eg_000  1.720000e+03  \n",
       "\n",
       "[170 rows x 8 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b82464d0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:21.101794Z",
     "iopub.status.busy": "2023-06-07T14:18:21.101376Z",
     "iopub.status.idle": "2023-06-07T14:18:21.108835Z",
     "shell.execute_reply": "2023-06-07T14:18:21.107661Z"
    },
    "papermill": {
     "duration": 0.033366,
     "end_time": "2023-06-07T14:18:21.111366",
     "exception": false,
     "start_time": "2023-06-07T14:18:21.078000",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['class', 'aa_000', 'ab_000', 'ac_000', 'ad_000', 'ae_000', 'af_000',\n",
       "       'ag_000', 'ag_001', 'ag_002',\n",
       "       ...\n",
       "       'ee_002', 'ee_003', 'ee_004', 'ee_005', 'ee_006', 'ee_007', 'ee_008',\n",
       "       'ee_009', 'ef_000', 'eg_000'],\n",
       "      dtype='object', length=171)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "babe0272",
   "metadata": {
    "papermill": {
     "duration": 0.023203,
     "end_time": "2023-06-07T14:18:21.156379",
     "exception": false,
     "start_time": "2023-06-07T14:18:21.133176",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Dropping the columns with more than 50% missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "be4567c3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:21.206917Z",
     "iopub.status.busy": "2023-06-07T14:18:21.205634Z",
     "iopub.status.idle": "2023-06-07T14:18:21.275764Z",
     "shell.execute_reply": "2023-06-07T14:18:21.274551Z"
    },
    "papermill": {
     "duration": 0.098142,
     "end_time": "2023-06-07T14:18:21.278372",
     "exception": false,
     "start_time": "2023-06-07T14:18:21.180230",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ab_000\n",
      "bm_000\n",
      "bn_000\n",
      "bo_000\n",
      "bp_000\n",
      "bq_000\n",
      "br_000\n",
      "cr_000\n"
     ]
    }
   ],
   "source": [
    "drop_cols=[]\n",
    "for i in df.columns:\n",
    "    null_percentage = df[i].isnull().sum()/len(df)*100\n",
    "    if null_percentage>50:\n",
    "        print(i)\n",
    "        drop_cols.append(str(i))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "52bc29b4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:21.324288Z",
     "iopub.status.busy": "2023-06-07T14:18:21.323879Z",
     "iopub.status.idle": "2023-06-07T14:18:21.329244Z",
     "shell.execute_reply": "2023-06-07T14:18:21.328046Z"
    },
    "papermill": {
     "duration": 0.031705,
     "end_time": "2023-06-07T14:18:21.332267",
     "exception": false,
     "start_time": "2023-06-07T14:18:21.300562",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'list'>\n"
     ]
    }
   ],
   "source": [
    "print(type(drop_cols))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af4ffc3c",
   "metadata": {
    "papermill": {
     "duration": 0.021882,
     "end_time": "2023-06-07T14:18:21.376382",
     "exception": false,
     "start_time": "2023-06-07T14:18:21.354500",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### All these columns have more than 50% null values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "67f66fd6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:21.422826Z",
     "iopub.status.busy": "2023-06-07T14:18:21.422373Z",
     "iopub.status.idle": "2023-06-07T14:18:21.463540Z",
     "shell.execute_reply": "2023-06-07T14:18:21.462466Z"
    },
    "papermill": {
     "duration": 0.067076,
     "end_time": "2023-06-07T14:18:21.466123",
     "exception": false,
     "start_time": "2023-06-07T14:18:21.399047",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "df.drop(drop_cols,axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "28c598e9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:21.513674Z",
     "iopub.status.busy": "2023-06-07T14:18:21.513264Z",
     "iopub.status.idle": "2023-06-07T14:18:21.520259Z",
     "shell.execute_reply": "2023-06-07T14:18:21.519217Z"
    },
    "papermill": {
     "duration": 0.033528,
     "end_time": "2023-06-07T14:18:21.522512",
     "exception": false,
     "start_time": "2023-06-07T14:18:21.488984",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(76000, 163)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c1a6207",
   "metadata": {
    "papermill": {
     "duration": 0.021989,
     "end_time": "2023-06-07T14:18:21.566804",
     "exception": false,
     "start_time": "2023-06-07T14:18:21.544815",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Labeling the target attribute with 1,0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "3b5b9cf3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:21.613487Z",
     "iopub.status.busy": "2023-06-07T14:18:21.613023Z",
     "iopub.status.idle": "2023-06-07T14:18:21.675686Z",
     "shell.execute_reply": "2023-06-07T14:18:21.674325Z"
    },
    "papermill": {
     "duration": 0.089454,
     "end_time": "2023-06-07T14:18:21.678650",
     "exception": false,
     "start_time": "2023-06-07T14:18:21.589196",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "df['class']=df['class'].replace(['neg','pos'],[0,1])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41ab0b0f",
   "metadata": {
    "papermill": {
     "duration": 0.022022,
     "end_time": "2023-06-07T14:18:21.723189",
     "exception": false,
     "start_time": "2023-06-07T14:18:21.701167",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Visualizing the data balance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2878f8fe",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:21.770095Z",
     "iopub.status.busy": "2023-06-07T14:18:21.769310Z",
     "iopub.status.idle": "2023-06-07T14:18:22.049556Z",
     "shell.execute_reply": "2023-06-07T14:18:22.048298Z"
    },
    "papermill": {
     "duration": 0.30633,
     "end_time": "2023-06-07T14:18:22.051907",
     "exception": false,
     "start_time": "2023-06-07T14:18:21.745577",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: ylabel='class'>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(data=df,x=df['class'].unique(),y=df['class'].value_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71862a3c",
   "metadata": {
    "papermill": {
     "duration": 0.022329,
     "end_time": "2023-06-07T14:18:22.096918",
     "exception": false,
     "start_time": "2023-06-07T14:18:22.074589",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### The data is very unbalanced"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0f422b8",
   "metadata": {
    "papermill": {
     "duration": 0.022393,
     "end_time": "2023-06-07T14:18:22.142079",
     "exception": false,
     "start_time": "2023-06-07T14:18:22.119686",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Handeling Missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d37e7ec1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:22.189625Z",
     "iopub.status.busy": "2023-06-07T14:18:22.189179Z",
     "iopub.status.idle": "2023-06-07T14:18:22.252909Z",
     "shell.execute_reply": "2023-06-07T14:18:22.251426Z"
    },
    "papermill": {
     "duration": 0.091298,
     "end_time": "2023-06-07T14:18:22.256133",
     "exception": false,
     "start_time": "2023-06-07T14:18:22.164835",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "missing_vals={}\n",
    "for i in df.columns:\n",
    "    null_percentage = df[i].isnull().sum()/len(df)*100\n",
    "    if null_percentage>0:\n",
    "        missing_vals[i]=null_percentage\n",
    "\n",
    "missing_vals = sorted(missing_vals.items(), key=lambda x: x[1],reverse=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "64e93ccf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:22.304088Z",
     "iopub.status.busy": "2023-06-07T14:18:22.303630Z",
     "iopub.status.idle": "2023-06-07T14:18:23.087036Z",
     "shell.execute_reply": "2023-06-07T14:18:23.085902Z"
    },
    "papermill": {
     "duration": 0.810587,
     "end_time": "2023-06-07T14:18:23.089751",
     "exception": false,
     "start_time": "2023-06-07T14:18:22.279164",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_20/2071793674.py:12: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  plot.set_yticklabels(map('{:.1f}%'.format, plot.yaxis.get_majorticklocs()))\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style(style=\"whitegrid\")\n",
    "plt.figure(figsize=(20,10))\n",
    "\n",
    "# Bar Plot\n",
    "plot = sns.barplot(x=[items[0] for items in missing_vals][:25],y = [items[1] for items in missing_vals][:25],palette=\"hls\")\n",
    "\n",
    "# Add annotations above each bar signifying their value\n",
    "for p in plot.patches:\n",
    "        plot.annotate('{:.1f}%'.format(p.get_height()), (p.get_x()+0.2, p.get_height()+1))\n",
    "\n",
    "# Make y-axis more interpretable\n",
    "plot.set_yticklabels(map('{:.1f}%'.format, plot.yaxis.get_majorticklocs())) \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6795f64d",
   "metadata": {
    "papermill": {
     "duration": 0.023774,
     "end_time": "2023-06-07T14:18:23.137124",
     "exception": false,
     "start_time": "2023-06-07T14:18:23.113350",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### So many attributes have more than 15% missing values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d4e1642",
   "metadata": {
    "papermill": {
     "duration": 0.023291,
     "end_time": "2023-06-07T14:18:23.184359",
     "exception": false,
     "start_time": "2023-06-07T14:18:23.161068",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "For features having 15% to 50% missing values, we will perform an Iterative model based imputation technique called MICE. At each step, a feature with missing values is designated as output y and the other feature columns are treated as inputs X. A regressor ( we have used Ridge Regressor ) is fit on (X, y) for known y. Then, the regressor is used to predict the missing values of y. This is done for each feature in an iterative fashion, and then is repeated for max_iter (10 as default) imputation rounds. The results of the final imputation round are returned."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12ca593f",
   "metadata": {
    "papermill": {
     "duration": 0.023175,
     "end_time": "2023-06-07T14:18:23.231381",
     "exception": false,
     "start_time": "2023-06-07T14:18:23.208206",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### columns with less than 5% missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "f9004880",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:23.280388Z",
     "iopub.status.busy": "2023-06-07T14:18:23.279994Z",
     "iopub.status.idle": "2023-06-07T14:18:23.286585Z",
     "shell.execute_reply": "2023-06-07T14:18:23.285322Z"
    },
    "papermill": {
     "duration": 0.034631,
     "end_time": "2023-06-07T14:18:23.289540",
     "exception": false,
     "start_time": "2023-06-07T14:18:23.254909",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'list'>\n"
     ]
    }
   ],
   "source": [
    "na_5 = [items[0] for items in missing_vals if items[1]<5]\n",
    "print(type(na_5))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "f396e607",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:23.339552Z",
     "iopub.status.busy": "2023-06-07T14:18:23.339147Z",
     "iopub.status.idle": "2023-06-07T14:18:23.421633Z",
     "shell.execute_reply": "2023-06-07T14:18:23.420573Z"
    },
    "papermill": {
     "duration": 0.110546,
     "end_time": "2023-06-07T14:18:23.424257",
     "exception": false,
     "start_time": "2023-06-07T14:18:23.313711",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "na_5 = [items[0] for items in missing_vals if items[1] < 5]\n",
    "\n",
    "df.dropna(subset=na_5,inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "2671786f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:23.474118Z",
     "iopub.status.busy": "2023-06-07T14:18:23.473364Z",
     "iopub.status.idle": "2023-06-07T14:18:23.480606Z",
     "shell.execute_reply": "2023-06-07T14:18:23.479466Z"
    },
    "papermill": {
     "duration": 0.034831,
     "end_time": "2023-06-07T14:18:23.482931",
     "exception": false,
     "start_time": "2023-06-07T14:18:23.448100",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(70827, 163)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d3bd2b8",
   "metadata": {
    "papermill": {
     "duration": 0.023295,
     "end_time": "2023-06-07T14:18:23.530062",
     "exception": false,
     "start_time": "2023-06-07T14:18:23.506767",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### columns with 5% to 15% missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "2a38942f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:23.579156Z",
     "iopub.status.busy": "2023-06-07T14:18:23.578736Z",
     "iopub.status.idle": "2023-06-07T14:18:23.584664Z",
     "shell.execute_reply": "2023-06-07T14:18:23.583381Z"
    },
    "papermill": {
     "duration": 0.033178,
     "end_time": "2023-06-07T14:18:23.586908",
     "exception": false,
     "start_time": "2023-06-07T14:18:23.553730",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "na_5to15=[items[0] for items in missing_vals if items[1]>=5 and items[1]<15]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "0244f572",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:23.637092Z",
     "iopub.status.busy": "2023-06-07T14:18:23.636386Z",
     "iopub.status.idle": "2023-06-07T14:18:24.164280Z",
     "shell.execute_reply": "2023-06-07T14:18:24.162986Z"
    },
    "papermill": {
     "duration": 0.556469,
     "end_time": "2023-06-07T14:18:24.167196",
     "exception": false,
     "start_time": "2023-06-07T14:18:23.610727",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "df[na_5to15]=df[na_5to15].fillna(df[na_5to15].median())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f89c39fc",
   "metadata": {
    "papermill": {
     "duration": 0.023785,
     "end_time": "2023-06-07T14:18:24.214750",
     "exception": false,
     "start_time": "2023-06-07T14:18:24.190965",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### columns with 15% to 50% missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a2c3ab74",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:24.264319Z",
     "iopub.status.busy": "2023-06-07T14:18:24.263890Z",
     "iopub.status.idle": "2023-06-07T14:18:24.269677Z",
     "shell.execute_reply": "2023-06-07T14:18:24.268340Z"
    },
    "papermill": {
     "duration": 0.033287,
     "end_time": "2023-06-07T14:18:24.272128",
     "exception": false,
     "start_time": "2023-06-07T14:18:24.238841",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "na_50=[items[0] for items in missing_vals if items[1]>=15 and items[1]<50]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "f9eff893",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:24.323683Z",
     "iopub.status.busy": "2023-06-07T14:18:24.323239Z",
     "iopub.status.idle": "2023-06-07T14:18:24.786387Z",
     "shell.execute_reply": "2023-06-07T14:18:24.785518Z"
    },
    "papermill": {
     "duration": 0.491114,
     "end_time": "2023-06-07T14:18:24.788935",
     "exception": false,
     "start_time": "2023-06-07T14:18:24.297821",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from sklearn.experimental import enable_iterative_imputer\n",
    "from sklearn.impute import IterativeImputer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "0fc2f05f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:24.840466Z",
     "iopub.status.busy": "2023-06-07T14:18:24.839225Z",
     "iopub.status.idle": "2023-06-07T14:18:24.847269Z",
     "shell.execute_reply": "2023-06-07T14:18:24.846003Z"
    },
    "papermill": {
     "duration": 0.036231,
     "end_time": "2023-06-07T14:18:24.849654",
     "exception": false,
     "start_time": "2023-06-07T14:18:24.813423",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(70827, 163)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "d116c41e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:24.898868Z",
     "iopub.status.busy": "2023-06-07T14:18:24.898409Z",
     "iopub.status.idle": "2023-06-07T14:18:42.736265Z",
     "shell.execute_reply": "2023-06-07T14:18:42.734928Z"
    },
    "papermill": {
     "duration": 17.865829,
     "end_time": "2023-06-07T14:18:42.739169",
     "exception": false,
     "start_time": "2023-06-07T14:18:24.873340",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.10/site-packages/sklearn/impute/_iterative.py:785: ConvergenceWarning: [IterativeImputer] Early stopping criterion not reached.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "\n",
    "imputer = IterativeImputer(n_nearest_features=10,max_iter=10)\n",
    "df_filled = pd.DataFrame(imputer.fit_transform(df[na_50]), columns=na_50)\n",
    "df[na_50]=df_filled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e18cfe73",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:42.789620Z",
     "iopub.status.busy": "2023-06-07T14:18:42.789159Z",
     "iopub.status.idle": "2023-06-07T14:18:42.853833Z",
     "shell.execute_reply": "2023-06-07T14:18:42.852539Z"
    },
    "papermill": {
     "duration": 0.09316,
     "end_time": "2023-06-07T14:18:42.856399",
     "exception": false,
     "start_time": "2023-06-07T14:18:42.763239",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[i for i in df.columns if df[i].isnull().sum()>0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "bfe429e1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:42.907709Z",
     "iopub.status.busy": "2023-06-07T14:18:42.907278Z",
     "iopub.status.idle": "2023-06-07T14:18:43.849552Z",
     "shell.execute_reply": "2023-06-07T14:18:43.848406Z"
    },
    "papermill": {
     "duration": 0.97112,
     "end_time": "2023-06-07T14:18:43.852224",
     "exception": false,
     "start_time": "2023-06-07T14:18:42.881104",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>class</th>\n",
       "      <td>70827.0</td>\n",
       "      <td>1.154927e-02</td>\n",
       "      <td>1.068459e-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000e+00</td>\n",
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       "    <tr>\n",
       "      <th>aa_000</th>\n",
       "      <td>70827.0</td>\n",
       "      <td>4.779677e+04</td>\n",
       "      <td>1.076463e+05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>804.0</td>\n",
       "      <td>30422.0</td>\n",
       "      <td>44296.0</td>\n",
       "      <td>2.060422e+06</td>\n",
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       "    <tr>\n",
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       "      <td>70827.0</td>\n",
       "      <td>3.582317e+08</td>\n",
       "      <td>7.968468e+08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>979.0</td>\n",
       "      <td>2.130707e+09</td>\n",
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       "    <tr>\n",
       "      <th>ad_000</th>\n",
       "      <td>70827.0</td>\n",
       "      <td>1.538946e+05</td>\n",
       "      <td>3.225555e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>252.0</td>\n",
       "      <td>1541.0</td>\n",
       "      <td>8.584298e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ae_000</th>\n",
       "      <td>70827.0</td>\n",
       "      <td>6.806500e+00</td>\n",
       "      <td>1.552894e+02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
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       "      <th>ee_007</th>\n",
       "      <td>70827.0</td>\n",
       "      <td>2.387794e+05</td>\n",
       "      <td>1.181551e+06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>36850.0</td>\n",
       "      <td>159288.0</td>\n",
       "      <td>1.195801e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ee_008</th>\n",
       "      <td>70827.0</td>\n",
       "      <td>1.275513e+05</td>\n",
       "      <td>3.886205e+05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3032.0</td>\n",
       "      <td>136067.0</td>\n",
       "      <td>1.718575e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ee_009</th>\n",
       "      <td>70827.0</td>\n",
       "      <td>8.037239e+03</td>\n",
       "      <td>4.337519e+04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2108.0</td>\n",
       "      <td>4.570398e+06</td>\n",
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       "    <tr>\n",
       "      <th>ef_000</th>\n",
       "      <td>70827.0</td>\n",
       "      <td>8.008245e-02</td>\n",
       "      <td>3.987488e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.820000e+02</td>\n",
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       "    <tr>\n",
       "      <th>eg_000</th>\n",
       "      <td>70827.0</td>\n",
       "      <td>2.083104e-01</td>\n",
       "      <td>9.791711e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.720000e+03</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>163 rows × 8 columns</p>\n",
       "</div>"
      ],
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       "          count          mean           std  min    25%      50%       75%  \\\n",
       "class   70827.0  1.154927e-02  1.068459e-01  0.0    0.0      0.0       0.0   \n",
       "aa_000  70827.0  4.779677e+04  1.076463e+05  0.0  804.0  30422.0   44296.0   \n",
       "ac_000  70827.0  3.582317e+08  7.968468e+08  0.0   18.0    160.0     979.0   \n",
       "ad_000  70827.0  1.538946e+05  3.225555e+07  0.0   38.0    252.0    1541.0   \n",
       "ae_000  70827.0  6.806500e+00  1.552894e+02  0.0    0.0      0.0       0.0   \n",
       "...         ...           ...           ...  ...    ...      ...       ...   \n",
       "ee_007  70827.0  2.387794e+05  1.181551e+06  0.0   92.0  36850.0  159288.0   \n",
       "ee_008  70827.0  1.275513e+05  3.886205e+05  0.0    0.0   3032.0  136067.0   \n",
       "ee_009  70827.0  8.037239e+03  4.337519e+04  0.0    0.0      0.0    2108.0   \n",
       "ef_000  70827.0  8.008245e-02  3.987488e+00  0.0    0.0      0.0       0.0   \n",
       "eg_000  70827.0  2.083104e-01  9.791711e+00  0.0    0.0      0.0       0.0   \n",
       "\n",
       "                 max  \n",
       "class   1.000000e+00  \n",
       "aa_000  2.060422e+06  \n",
       "ac_000  2.130707e+09  \n",
       "ad_000  8.584298e+09  \n",
       "ae_000  2.105000e+04  \n",
       "...              ...  \n",
       "ee_007  1.195801e+08  \n",
       "ee_008  1.718575e+07  \n",
       "ee_009  4.570398e+06  \n",
       "ef_000  4.820000e+02  \n",
       "eg_000  1.720000e+03  \n",
       "\n",
       "[163 rows x 8 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "85a439a8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:43.904006Z",
     "iopub.status.busy": "2023-06-07T14:18:43.903563Z",
     "iopub.status.idle": "2023-06-07T14:18:44.097238Z",
     "shell.execute_reply": "2023-06-07T14:18:44.095864Z"
    },
    "papermill": {
     "duration": 0.22338,
     "end_time": "2023-06-07T14:18:44.100165",
     "exception": false,
     "start_time": "2023-06-07T14:18:43.876785",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
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       "      <th>ar_000</th>\n",
       "      <th>as_000</th>\n",
       "      <th>at_000</th>\n",
       "      <th>au_000</th>\n",
       "      <th>av_000</th>\n",
       "      <th>ax_000</th>\n",
       "      <th>ay_000</th>\n",
       "      <th>ay_001</th>\n",
       "      <th>ay_002</th>\n",
       "      <th>ay_003</th>\n",
       "      <th>ay_004</th>\n",
       "      <th>ay_005</th>\n",
       "      <th>ay_006</th>\n",
       "      <th>ay_007</th>\n",
       "      <th>ay_008</th>\n",
       "      <th>ay_009</th>\n",
       "      <th>az_000</th>\n",
       "      <th>az_001</th>\n",
       "      <th>az_002</th>\n",
       "      <th>az_003</th>\n",
       "      <th>az_004</th>\n",
       "      <th>az_005</th>\n",
       "      <th>az_006</th>\n",
       "      <th>az_007</th>\n",
       "      <th>az_008</th>\n",
       "      <th>az_009</th>\n",
       "      <th>ba_000</th>\n",
       "      <th>ba_001</th>\n",
       "      <th>ba_002</th>\n",
       "      <th>ba_003</th>\n",
       "      <th>ba_004</th>\n",
       "      <th>ba_005</th>\n",
       "      <th>ba_006</th>\n",
       "      <th>ba_007</th>\n",
       "      <th>ba_008</th>\n",
       "      <th>ba_009</th>\n",
       "      <th>bb_000</th>\n",
       "      <th>bc_000</th>\n",
       "      <th>bd_000</th>\n",
       "      <th>be_000</th>\n",
       "      <th>bf_000</th>\n",
       "      <th>bg_000</th>\n",
       "      <th>bh_000</th>\n",
       "      <th>bi_000</th>\n",
       "      <th>bj_000</th>\n",
       "      <th>bk_000</th>\n",
       "      <th>bl_000</th>\n",
       "      <th>bs_000</th>\n",
       "      <th>bt_000</th>\n",
       "      <th>bu_000</th>\n",
       "      <th>bv_000</th>\n",
       "      <th>bx_000</th>\n",
       "      <th>by_000</th>\n",
       "      <th>bz_000</th>\n",
       "      <th>ca_000</th>\n",
       "      <th>cb_000</th>\n",
       "      <th>cc_000</th>\n",
       "      <th>cd_000</th>\n",
       "      <th>ce_000</th>\n",
       "      <th>cf_000</th>\n",
       "      <th>cg_000</th>\n",
       "      <th>ch_000</th>\n",
       "      <th>ci_000</th>\n",
       "      <th>cj_000</th>\n",
       "      <th>ck_000</th>\n",
       "      <th>cl_000</th>\n",
       "      <th>cm_000</th>\n",
       "      <th>cn_000</th>\n",
       "      <th>cn_001</th>\n",
       "      <th>cn_002</th>\n",
       "      <th>cn_003</th>\n",
       "      <th>cn_004</th>\n",
       "      <th>cn_005</th>\n",
       "      <th>cn_006</th>\n",
       "      <th>cn_007</th>\n",
       "      <th>cn_008</th>\n",
       "      <th>cn_009</th>\n",
       "      <th>co_000</th>\n",
       "      <th>cp_000</th>\n",
       "      <th>cq_000</th>\n",
       "      <th>cs_000</th>\n",
       "      <th>cs_001</th>\n",
       "      <th>cs_002</th>\n",
       "      <th>cs_003</th>\n",
       "      <th>cs_004</th>\n",
       "      <th>cs_005</th>\n",
       "      <th>cs_006</th>\n",
       "      <th>cs_007</th>\n",
       "      <th>cs_008</th>\n",
       "      <th>cs_009</th>\n",
       "      <th>ct_000</th>\n",
       "      <th>cu_000</th>\n",
       "      <th>cv_000</th>\n",
       "      <th>cx_000</th>\n",
       "      <th>cy_000</th>\n",
       "      <th>cz_000</th>\n",
       "      <th>da_000</th>\n",
       "      <th>db_000</th>\n",
       "      <th>dc_000</th>\n",
       "      <th>dd_000</th>\n",
       "      <th>de_000</th>\n",
       "      <th>df_000</th>\n",
       "      <th>dg_000</th>\n",
       "      <th>dh_000</th>\n",
       "      <th>di_000</th>\n",
       "      <th>dj_000</th>\n",
       "      <th>dk_000</th>\n",
       "      <th>dl_000</th>\n",
       "      <th>dm_000</th>\n",
       "      <th>dn_000</th>\n",
       "      <th>do_000</th>\n",
       "      <th>dp_000</th>\n",
       "      <th>dq_000</th>\n",
       "      <th>dr_000</th>\n",
       "      <th>ds_000</th>\n",
       "      <th>dt_000</th>\n",
       "      <th>du_000</th>\n",
       "      <th>dv_000</th>\n",
       "      <th>dx_000</th>\n",
       "      <th>dy_000</th>\n",
       "      <th>dz_000</th>\n",
       "      <th>ea_000</th>\n",
       "      <th>eb_000</th>\n",
       "      <th>ec_00</th>\n",
       "      <th>ed_000</th>\n",
       "      <th>ee_000</th>\n",
       "      <th>ee_001</th>\n",
       "      <th>ee_002</th>\n",
       "      <th>ee_003</th>\n",
       "      <th>ee_004</th>\n",
       "      <th>ee_005</th>\n",
       "      <th>ee_006</th>\n",
       "      <th>ee_007</th>\n",
       "      <th>ee_008</th>\n",
       "      <th>ee_009</th>\n",
       "      <th>ef_000</th>\n",
       "      <th>eg_000</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>76698</td>\n",
       "      <td>2.130706e+09</td>\n",
       "      <td>280.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>37250.0</td>\n",
       "      <td>1432864.0</td>\n",
       "      <td>3664156.0</td>\n",
       "      <td>1007684.0</td>\n",
       "      <td>25896.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2551696.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4933296.0</td>\n",
       "      <td>3655166.0</td>\n",
       "      <td>1766008.0</td>\n",
       "      <td>1132040.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1012.0</td>\n",
       "      <td>268.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>469014.0</td>\n",
       "      <td>4239660.0</td>\n",
       "      <td>703300.0</td>\n",
       "      <td>755876.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5374.0</td>\n",
       "      <td>2108.0</td>\n",
       "      <td>4114.0</td>\n",
       "      <td>12348.0</td>\n",
       "      <td>615248.0</td>\n",
       "      <td>5526276.0</td>\n",
       "      <td>2378.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2328746.0</td>\n",
       "      <td>1022304.0</td>\n",
       "      <td>415432.0</td>\n",
       "      <td>287230.0</td>\n",
       "      <td>310246.0</td>\n",
       "      <td>681504.0</td>\n",
       "      <td>1118814.0</td>\n",
       "      <td>3574.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6700214.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>2551696.0</td>\n",
       "      <td>97518.0</td>\n",
       "      <td>947550.0</td>\n",
       "      <td>799478.0</td>\n",
       "      <td>330760.000000</td>\n",
       "      <td>353400.000000</td>\n",
       "      <td>178540.0</td>\n",
       "      <td>76698.08</td>\n",
       "      <td>6700214.0</td>\n",
       "      <td>6700214.0</td>\n",
       "      <td>6599892.0</td>\n",
       "      <td>43566.0</td>\n",
       "      <td>68656.0</td>\n",
       "      <td>54064.0</td>\n",
       "      <td>638360.0</td>\n",
       "      <td>6167850.0</td>\n",
       "      <td>1209600.0</td>\n",
       "      <td>246244.0</td>\n",
       "      <td>2.00000</td>\n",
       "      <td>96.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5245752.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>916567.68</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>118196.0</td>\n",
       "      <td>1309472.0</td>\n",
       "      <td>3247182.0</td>\n",
       "      <td>1381362.0</td>\n",
       "      <td>98822.0</td>\n",
       "      <td>11208.0</td>\n",
       "      <td>1608.0</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>240.0</td>\n",
       "      <td>6700214.0</td>\n",
       "      <td>10476.0</td>\n",
       "      <td>1226.0</td>\n",
       "      <td>267998.0</td>\n",
       "      <td>521832.0</td>\n",
       "      <td>428776.0</td>\n",
       "      <td>4015854.0</td>\n",
       "      <td>895240.0</td>\n",
       "      <td>26330.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>532.000000</td>\n",
       "      <td>734.0000</td>\n",
       "      <td>4.122704e+06</td>\n",
       "      <td>51288.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>532572.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>5.330690e+06</td>\n",
       "      <td>4732.0</td>\n",
       "      <td>1126.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>62282.0</td>\n",
       "      <td>85908.0</td>\n",
       "      <td>32790.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>202710.0</td>\n",
       "      <td>37928.0</td>\n",
       "      <td>14745580.0</td>\n",
       "      <td>1876644.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2801180.0</td>\n",
       "      <td>2445.80</td>\n",
       "      <td>2712.0</td>\n",
       "      <td>965866.0</td>\n",
       "      <td>1706908.0</td>\n",
       "      <td>1240520.0</td>\n",
       "      <td>493384.0</td>\n",
       "      <td>721044.0</td>\n",
       "      <td>469792.0</td>\n",
       "      <td>339156.0</td>\n",
       "      <td>157956.0</td>\n",
       "      <td>73224.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>33058</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>154115.925709</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18254.0</td>\n",
       "      <td>653294.0</td>\n",
       "      <td>1720800.0</td>\n",
       "      <td>516724.0</td>\n",
       "      <td>31642.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1393352.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2560898.0</td>\n",
       "      <td>2127150.0</td>\n",
       "      <td>1084598.0</td>\n",
       "      <td>338544.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>71510.0</td>\n",
       "      <td>772720.0</td>\n",
       "      <td>1996924.0</td>\n",
       "      <td>99560.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7336.0</td>\n",
       "      <td>7808.0</td>\n",
       "      <td>13776.0</td>\n",
       "      <td>13086.0</td>\n",
       "      <td>1010074.0</td>\n",
       "      <td>1873902.0</td>\n",
       "      <td>14726.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1378576.0</td>\n",
       "      <td>447166.0</td>\n",
       "      <td>199512.0</td>\n",
       "      <td>154298.0</td>\n",
       "      <td>137280.0</td>\n",
       "      <td>138668.0</td>\n",
       "      <td>165908.0</td>\n",
       "      <td>229652.0</td>\n",
       "      <td>87082.0</td>\n",
       "      <td>4708.0</td>\n",
       "      <td>3646660.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>454.0</td>\n",
       "      <td>364.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>1393352.0</td>\n",
       "      <td>49028.0</td>\n",
       "      <td>688314.0</td>\n",
       "      <td>392208.0</td>\n",
       "      <td>341420.000000</td>\n",
       "      <td>359780.000000</td>\n",
       "      <td>6700.0</td>\n",
       "      <td>33057.51</td>\n",
       "      <td>3646660.0</td>\n",
       "      <td>3646660.0</td>\n",
       "      <td>3582034.0</td>\n",
       "      <td>17733.0</td>\n",
       "      <td>260120.0</td>\n",
       "      <td>115626.0</td>\n",
       "      <td>6900.0</td>\n",
       "      <td>2942850.0</td>\n",
       "      <td>1209600.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>153535.07638</td>\n",
       "      <td>145.779859</td>\n",
       "      <td>0.000064</td>\n",
       "      <td>2291079.36</td>\n",
       "      <td>0.0</td>\n",
       "      <td>643536.96</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>98644.0</td>\n",
       "      <td>1179502.0</td>\n",
       "      <td>1286736.0</td>\n",
       "      <td>336388.0</td>\n",
       "      <td>36294.0</td>\n",
       "      <td>5192.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>153905.080898</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3646660.0</td>\n",
       "      <td>6160.0</td>\n",
       "      <td>796.0</td>\n",
       "      <td>164860.0</td>\n",
       "      <td>350066.0</td>\n",
       "      <td>272956.0</td>\n",
       "      <td>1837600.0</td>\n",
       "      <td>301242.0</td>\n",
       "      <td>9148.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1434.235234</td>\n",
       "      <td>1384.3233</td>\n",
       "      <td>2.183843e+06</td>\n",
       "      <td>84843.7321</td>\n",
       "      <td>-385.530528</td>\n",
       "      <td>36635.529207</td>\n",
       "      <td>9.35737</td>\n",
       "      <td>16.808097</td>\n",
       "      <td>2.768263e+06</td>\n",
       "      <td>3312.0</td>\n",
       "      <td>522.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33736.0</td>\n",
       "      <td>36946.0</td>\n",
       "      <td>5936.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>103330.0</td>\n",
       "      <td>16254.0</td>\n",
       "      <td>4510080.0</td>\n",
       "      <td>868538.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3477820.0</td>\n",
       "      <td>2211.76</td>\n",
       "      <td>2334.0</td>\n",
       "      <td>664504.0</td>\n",
       "      <td>824154.0</td>\n",
       "      <td>421400.0</td>\n",
       "      <td>178064.0</td>\n",
       "      <td>293306.0</td>\n",
       "      <td>245416.0</td>\n",
       "      <td>133654.0</td>\n",
       "      <td>81140.0</td>\n",
       "      <td>97576.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>41040</td>\n",
       "      <td>2.280000e+02</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1648.0</td>\n",
       "      <td>370592.0</td>\n",
       "      <td>1883374.0</td>\n",
       "      <td>292936.0</td>\n",
       "      <td>12016.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1234132.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2371990.0</td>\n",
       "      <td>2173634.0</td>\n",
       "      <td>300796.0</td>\n",
       "      <td>153698.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>358.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>870456.0</td>\n",
       "      <td>239798.0</td>\n",
       "      <td>1450312.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1620.0</td>\n",
       "      <td>1156.0</td>\n",
       "      <td>1228.0</td>\n",
       "      <td>34250.0</td>\n",
       "      <td>1811606.0</td>\n",
       "      <td>710672.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>790690.0</td>\n",
       "      <td>672026.0</td>\n",
       "      <td>332340.0</td>\n",
       "      <td>254892.0</td>\n",
       "      <td>189596.0</td>\n",
       "      <td>135758.0</td>\n",
       "      <td>103552.0</td>\n",
       "      <td>81666.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2673338.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>202.0</td>\n",
       "      <td>576.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1234132.0</td>\n",
       "      <td>28804.0</td>\n",
       "      <td>160176.0</td>\n",
       "      <td>139730.0</td>\n",
       "      <td>137160.000000</td>\n",
       "      <td>130640.000000</td>\n",
       "      <td>28000.0</td>\n",
       "      <td>41040.08</td>\n",
       "      <td>2673338.0</td>\n",
       "      <td>2673338.0</td>\n",
       "      <td>2678534.0</td>\n",
       "      <td>15439.0</td>\n",
       "      <td>7466.0</td>\n",
       "      <td>22436.0</td>\n",
       "      <td>248240.0</td>\n",
       "      <td>2560566.0</td>\n",
       "      <td>1209600.0</td>\n",
       "      <td>63328.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>124.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2322692.16</td>\n",
       "      <td>0.0</td>\n",
       "      <td>236099.52</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33276.0</td>\n",
       "      <td>1215280.0</td>\n",
       "      <td>1102798.0</td>\n",
       "      <td>196502.0</td>\n",
       "      <td>10260.0</td>\n",
       "      <td>2422.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2673338.0</td>\n",
       "      <td>3584.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>56362.0</td>\n",
       "      <td>149726.0</td>\n",
       "      <td>100326.0</td>\n",
       "      <td>1744838.0</td>\n",
       "      <td>488302.0</td>\n",
       "      <td>16682.0</td>\n",
       "      <td>246.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.000000</td>\n",
       "      <td>292.0000</td>\n",
       "      <td>2.180528e+06</td>\n",
       "      <td>29188.0000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>20346.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.341048e+06</td>\n",
       "      <td>1494.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13876.0</td>\n",
       "      <td>38182.0</td>\n",
       "      <td>8138.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>65772.0</td>\n",
       "      <td>10534.0</td>\n",
       "      <td>300240.0</td>\n",
       "      <td>48028.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1040120.0</td>\n",
       "      <td>1018.64</td>\n",
       "      <td>1020.0</td>\n",
       "      <td>262032.0</td>\n",
       "      <td>453378.0</td>\n",
       "      <td>277378.0</td>\n",
       "      <td>159812.0</td>\n",
       "      <td>423992.0</td>\n",
       "      <td>409564.0</td>\n",
       "      <td>320746.0</td>\n",
       "      <td>158022.0</td>\n",
       "      <td>95128.0</td>\n",
       "      <td>514.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>7.000000e+01</td>\n",
       "      <td>66.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>318.0</td>\n",
       "      <td>2212.0</td>\n",
       "      <td>3232.0</td>\n",
       "      <td>1872.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2668.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>642.0</td>\n",
       "      <td>3894.0</td>\n",
       "      <td>10184.0</td>\n",
       "      <td>7554.0</td>\n",
       "      <td>10764.0</td>\n",
       "      <td>1014.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2038.0</td>\n",
       "      <td>5596.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>914.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>2478.0</td>\n",
       "      <td>2398.0</td>\n",
       "      <td>1692.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6176.0</td>\n",
       "      <td>340.0</td>\n",
       "      <td>304.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>406.0</td>\n",
       "      <td>216.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21614.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2668.0</td>\n",
       "      <td>184.0</td>\n",
       "      <td>7632.0</td>\n",
       "      <td>3090.0</td>\n",
       "      <td>316836.460341</td>\n",
       "      <td>399868.982587</td>\n",
       "      <td>10580.0</td>\n",
       "      <td>12.69</td>\n",
       "      <td>21614.0</td>\n",
       "      <td>21614.0</td>\n",
       "      <td>21772.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>21400.0</td>\n",
       "      <td>7710.0</td>\n",
       "      <td>1209600.0</td>\n",
       "      <td>302.0</td>\n",
       "      <td>2.00000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2135.04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4525.44</td>\n",
       "      <td>2.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>2544.0</td>\n",
       "      <td>1894.0</td>\n",
       "      <td>2170.0</td>\n",
       "      <td>822.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>21614.0</td>\n",
       "      <td>1032.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>656.0</td>\n",
       "      <td>692.0</td>\n",
       "      <td>4836.0</td>\n",
       "      <td>388.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>138.000000</td>\n",
       "      <td>8.0000</td>\n",
       "      <td>1.666000e+03</td>\n",
       "      <td>72.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.578000e+03</td>\n",
       "      <td>76.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>232.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>15740.0</td>\n",
       "      <td>1822.0</td>\n",
       "      <td>20174.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.08</td>\n",
       "      <td>54.0</td>\n",
       "      <td>5670.0</td>\n",
       "      <td>1566.0</td>\n",
       "      <td>240.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>60874</td>\n",
       "      <td>1.368000e+03</td>\n",
       "      <td>458.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>43752.0</td>\n",
       "      <td>1966618.0</td>\n",
       "      <td>1800340.0</td>\n",
       "      <td>131646.0</td>\n",
       "      <td>4588.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1974038.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>226.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3230626.0</td>\n",
       "      <td>2618878.0</td>\n",
       "      <td>1058136.0</td>\n",
       "      <td>551022.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1788.0</td>\n",
       "      <td>642.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42124.0</td>\n",
       "      <td>372236.0</td>\n",
       "      <td>2128914.0</td>\n",
       "      <td>819596.0</td>\n",
       "      <td>584074.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1644.0</td>\n",
       "      <td>362.0</td>\n",
       "      <td>562.0</td>\n",
       "      <td>842.0</td>\n",
       "      <td>30194.0</td>\n",
       "      <td>3911734.0</td>\n",
       "      <td>1606.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1348578.0</td>\n",
       "      <td>1035668.0</td>\n",
       "      <td>338762.0</td>\n",
       "      <td>236540.0</td>\n",
       "      <td>182278.0</td>\n",
       "      <td>151778.0</td>\n",
       "      <td>163248.0</td>\n",
       "      <td>470800.0</td>\n",
       "      <td>19292.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4289260.0</td>\n",
       "      <td>448.0</td>\n",
       "      <td>556.0</td>\n",
       "      <td>642.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1974038.0</td>\n",
       "      <td>86454.0</td>\n",
       "      <td>653692.0</td>\n",
       "      <td>399410.0</td>\n",
       "      <td>306780.000000</td>\n",
       "      <td>282560.000000</td>\n",
       "      <td>189000.0</td>\n",
       "      <td>60874.03</td>\n",
       "      <td>4289260.0</td>\n",
       "      <td>4289260.0</td>\n",
       "      <td>4283332.0</td>\n",
       "      <td>24793.0</td>\n",
       "      <td>17052.0</td>\n",
       "      <td>61844.0</td>\n",
       "      <td>654700.0</td>\n",
       "      <td>3946944.0</td>\n",
       "      <td>1209600.0</td>\n",
       "      <td>135720.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>152.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3565684.80</td>\n",
       "      <td>0.0</td>\n",
       "      <td>379111.68</td>\n",
       "      <td>0.0</td>\n",
       "      <td>746.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>378910.0</td>\n",
       "      <td>2497104.0</td>\n",
       "      <td>993000.0</td>\n",
       "      <td>64230.0</td>\n",
       "      <td>10482.0</td>\n",
       "      <td>2776.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>202.000000</td>\n",
       "      <td>212.0</td>\n",
       "      <td>4289260.0</td>\n",
       "      <td>3942.0</td>\n",
       "      <td>520.0</td>\n",
       "      <td>80950.0</td>\n",
       "      <td>227322.0</td>\n",
       "      <td>186242.0</td>\n",
       "      <td>2288268.0</td>\n",
       "      <td>1137268.0</td>\n",
       "      <td>22228.0</td>\n",
       "      <td>204.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1716.000000</td>\n",
       "      <td>1664.0000</td>\n",
       "      <td>3.440288e+06</td>\n",
       "      <td>215826.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4262.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.590004e+06</td>\n",
       "      <td>2026.0</td>\n",
       "      <td>444.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>44946.0</td>\n",
       "      <td>62648.0</td>\n",
       "      <td>11506.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>149474.0</td>\n",
       "      <td>35154.0</td>\n",
       "      <td>457040.0</td>\n",
       "      <td>80482.0</td>\n",
       "      <td>98334.0</td>\n",
       "      <td>27588.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21173050.0</td>\n",
       "      <td>1116.06</td>\n",
       "      <td>1176.0</td>\n",
       "      <td>404740.0</td>\n",
       "      <td>904230.0</td>\n",
       "      <td>622012.0</td>\n",
       "      <td>229790.0</td>\n",
       "      <td>405298.0</td>\n",
       "      <td>347188.0</td>\n",
       "      <td>286954.0</td>\n",
       "      <td>311560.0</td>\n",
       "      <td>433954.0</td>\n",
       "      <td>1218.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   class  aa_000        ac_000         ad_000  ae_000  af_000  ag_000  ag_001  \\\n",
       "0      0   76698  2.130706e+09     280.000000     0.0     0.0     0.0     0.0   \n",
       "1      0   33058  0.000000e+00  154115.925709     0.0     0.0     0.0     0.0   \n",
       "2      0   41040  2.280000e+02     100.000000     0.0     0.0     0.0     0.0   \n",
       "3      0      12  7.000000e+01      66.000000     0.0    10.0     0.0     0.0   \n",
       "4      0   60874  1.368000e+03     458.000000     0.0     0.0     0.0     0.0   \n",
       "\n",
       "   ag_002  ag_003   ag_004     ag_005     ag_006     ag_007   ag_008  ag_009  \\\n",
       "0     0.0     0.0  37250.0  1432864.0  3664156.0  1007684.0  25896.0     0.0   \n",
       "1     0.0     0.0  18254.0   653294.0  1720800.0   516724.0  31642.0     0.0   \n",
       "2     0.0     0.0   1648.0   370592.0  1883374.0   292936.0  12016.0     0.0   \n",
       "3     0.0   318.0   2212.0     3232.0     1872.0        0.0      0.0     0.0   \n",
       "4     0.0     0.0  43752.0  1966618.0  1800340.0   131646.0   4588.0     0.0   \n",
       "\n",
       "      ah_000  ai_000  aj_000  ak_000  al_000    am_0     an_000     ao_000  \\\n",
       "0  2551696.0     0.0     0.0     0.0     0.0     0.0  4933296.0  3655166.0   \n",
       "1  1393352.0     0.0    68.0     0.0     0.0     0.0  2560898.0  2127150.0   \n",
       "2  1234132.0     0.0     0.0     0.0     0.0     0.0  2371990.0  2173634.0   \n",
       "3     2668.0     0.0     0.0     0.0   642.0  3894.0    10184.0     7554.0   \n",
       "4  1974038.0     0.0   226.0     0.0     0.0     0.0  3230626.0  2618878.0   \n",
       "\n",
       "      ap_000     aq_000  ar_000  as_000  at_000  au_000  av_000  ax_000  \\\n",
       "0  1766008.0  1132040.0     0.0     0.0     0.0     0.0  1012.0   268.0   \n",
       "1  1084598.0   338544.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2   300796.0   153698.0     0.0     0.0     0.0     0.0   358.0   110.0   \n",
       "3    10764.0     1014.0     0.0     0.0     0.0     0.0    60.0     6.0   \n",
       "4  1058136.0   551022.0     0.0     0.0     0.0     0.0  1788.0   642.0   \n",
       "\n",
       "   ay_000  ay_001  ay_002  ay_003   ay_004    ay_005     ay_006     ay_007  \\\n",
       "0     0.0     0.0     0.0     0.0      0.0  469014.0  4239660.0   703300.0   \n",
       "1     0.0     0.0     0.0     0.0      0.0   71510.0   772720.0  1996924.0   \n",
       "2     0.0     0.0     0.0     0.0      0.0       0.0   870456.0   239798.0   \n",
       "3     0.0     0.0     0.0     0.0      0.0       0.0        0.0     2038.0   \n",
       "4     0.0     0.0     0.0     0.0  42124.0  372236.0  2128914.0   819596.0   \n",
       "\n",
       "      ay_008  ay_009  az_000  az_001   az_002   az_003     az_004     az_005  \\\n",
       "0   755876.0     0.0  5374.0  2108.0   4114.0  12348.0   615248.0  5526276.0   \n",
       "1    99560.0     0.0  7336.0  7808.0  13776.0  13086.0  1010074.0  1873902.0   \n",
       "2  1450312.0     0.0  1620.0  1156.0   1228.0  34250.0  1811606.0   710672.0   \n",
       "3     5596.0     0.0    64.0     6.0      6.0    914.0       76.0     2478.0   \n",
       "4   584074.0     0.0  1644.0   362.0    562.0    842.0    30194.0  3911734.0   \n",
       "\n",
       "    az_006  az_007  az_008  az_009     ba_000     ba_001    ba_002    ba_003  \\\n",
       "0   2378.0     4.0     0.0     0.0  2328746.0  1022304.0  415432.0  287230.0   \n",
       "1  14726.0     6.0     0.0     0.0  1378576.0   447166.0  199512.0  154298.0   \n",
       "2     34.0     0.0     0.0     0.0   790690.0   672026.0  332340.0  254892.0   \n",
       "3   2398.0  1692.0     0.0     0.0     6176.0      340.0     304.0     102.0   \n",
       "4   1606.0     0.0     0.0     0.0  1348578.0  1035668.0  338762.0  236540.0   \n",
       "\n",
       "     ba_004    ba_005     ba_006    ba_007   ba_008  ba_009     bb_000  \\\n",
       "0  310246.0  681504.0  1118814.0    3574.0      0.0     0.0  6700214.0   \n",
       "1  137280.0  138668.0   165908.0  229652.0  87082.0  4708.0  3646660.0   \n",
       "2  189596.0  135758.0   103552.0   81666.0     46.0     0.0  2673338.0   \n",
       "3      74.0     406.0      216.0      16.0      0.0     0.0    21614.0   \n",
       "4  182278.0  151778.0   163248.0  470800.0  19292.0     0.0  4289260.0   \n",
       "\n",
       "   bc_000  bd_000  be_000  bf_000     bg_000   bh_000    bi_000    bj_000  \\\n",
       "0     0.0    10.0   108.0    50.0  2551696.0  97518.0  947550.0  799478.0   \n",
       "1    86.0   454.0   364.0   350.0  1393352.0  49028.0  688314.0  392208.0   \n",
       "2   128.0   202.0   576.0     4.0  1234132.0  28804.0  160176.0  139730.0   \n",
       "3     2.0    12.0     0.0     0.0     2668.0    184.0    7632.0    3090.0   \n",
       "4   448.0   556.0   642.0     2.0  1974038.0  86454.0  653692.0  399410.0   \n",
       "\n",
       "          bk_000         bl_000    bs_000    bt_000     bu_000     bv_000  \\\n",
       "0  330760.000000  353400.000000  178540.0  76698.08  6700214.0  6700214.0   \n",
       "1  341420.000000  359780.000000    6700.0  33057.51  3646660.0  3646660.0   \n",
       "2  137160.000000  130640.000000   28000.0  41040.08  2673338.0  2673338.0   \n",
       "3  316836.460341  399868.982587   10580.0     12.69    21614.0    21614.0   \n",
       "4  306780.000000  282560.000000  189000.0  60874.03  4289260.0  4289260.0   \n",
       "\n",
       "      bx_000   by_000    bz_000    ca_000    cb_000     cc_000     cd_000  \\\n",
       "0  6599892.0  43566.0   68656.0   54064.0  638360.0  6167850.0  1209600.0   \n",
       "1  3582034.0  17733.0  260120.0  115626.0    6900.0  2942850.0  1209600.0   \n",
       "2  2678534.0  15439.0    7466.0   22436.0  248240.0  2560566.0  1209600.0   \n",
       "3    21772.0     32.0      50.0    1994.0   21400.0     7710.0  1209600.0   \n",
       "4  4283332.0  24793.0   17052.0   61844.0  654700.0  3946944.0  1209600.0   \n",
       "\n",
       "     ce_000        cf_000      cg_000    ch_000      ci_000  cj_000  \\\n",
       "0  246244.0       2.00000   96.000000  0.000000  5245752.00     0.0   \n",
       "1       0.0  153535.07638  145.779859  0.000064  2291079.36     0.0   \n",
       "2   63328.0       0.00000  124.000000  0.000000  2322692.16     0.0   \n",
       "3     302.0       2.00000    6.000000  0.000000     2135.04     0.0   \n",
       "4  135720.0       0.00000  152.000000  0.000000  3565684.80     0.0   \n",
       "\n",
       "      ck_000  cl_000  cm_000  cn_000  cn_001  cn_002    cn_003     cn_004  \\\n",
       "0  916567.68     6.0  1924.0     0.0     0.0     0.0  118196.0  1309472.0   \n",
       "1  643536.96     0.0     0.0     0.0     0.0    38.0   98644.0  1179502.0   \n",
       "2  236099.52     0.0     0.0     0.0     0.0     0.0   33276.0  1215280.0   \n",
       "3    4525.44     2.0    16.0     0.0    52.0  2544.0    1894.0     2170.0   \n",
       "4  379111.68     0.0   746.0     0.0     0.0   356.0  378910.0  2497104.0   \n",
       "\n",
       "      cn_005     cn_006   cn_007   cn_008  cn_009         co_000  cp_000  \\\n",
       "0  3247182.0  1381362.0  98822.0  11208.0  1608.0     220.000000   240.0   \n",
       "1  1286736.0   336388.0  36294.0   5192.0    56.0  153905.080898     0.0   \n",
       "2  1102798.0   196502.0  10260.0   2422.0    28.0       0.000000     6.0   \n",
       "3      822.0      152.0      0.0      0.0     0.0       2.000000     2.0   \n",
       "4   993000.0    64230.0  10482.0   2776.0    86.0     202.000000   212.0   \n",
       "\n",
       "      cq_000   cs_000  cs_001    cs_002    cs_003    cs_004     cs_005  \\\n",
       "0  6700214.0  10476.0  1226.0  267998.0  521832.0  428776.0  4015854.0   \n",
       "1  3646660.0   6160.0   796.0  164860.0  350066.0  272956.0  1837600.0   \n",
       "2  2673338.0   3584.0   500.0   56362.0  149726.0  100326.0  1744838.0   \n",
       "3    21614.0   1032.0     6.0      24.0     656.0     692.0     4836.0   \n",
       "4  4289260.0   3942.0   520.0   80950.0  227322.0  186242.0  2288268.0   \n",
       "\n",
       "      cs_006   cs_007  cs_008  cs_009       ct_000     cu_000        cv_000  \\\n",
       "0   895240.0  26330.0   118.0     0.0   532.000000   734.0000  4.122704e+06   \n",
       "1   301242.0   9148.0    22.0     0.0  1434.235234  1384.3233  2.183843e+06   \n",
       "2   488302.0  16682.0   246.0     0.0   230.000000   292.0000  2.180528e+06   \n",
       "3      388.0      0.0     0.0     0.0   138.000000     8.0000  1.666000e+03   \n",
       "4  1137268.0  22228.0   204.0     0.0  1716.000000  1664.0000  3.440288e+06   \n",
       "\n",
       "        cx_000      cy_000         cz_000   da_000     db_000        dc_000  \\\n",
       "0   51288.0000    0.000000  532572.000000  0.00000  18.000000  5.330690e+06   \n",
       "1   84843.7321 -385.530528   36635.529207  9.35737  16.808097  2.768263e+06   \n",
       "2   29188.0000   22.000000   20346.000000  0.00000   0.000000  2.341048e+06   \n",
       "3      72.0000    0.000000      12.000000  0.00000   0.000000  2.578000e+03   \n",
       "4  215826.0000    0.000000    4262.000000  0.00000   0.000000  3.590004e+06   \n",
       "\n",
       "   dd_000  de_000  df_000  dg_000  dh_000  di_000  dj_000  dk_000  dl_000  \\\n",
       "0  4732.0  1126.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "1  3312.0   522.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2  1494.0   152.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "3    76.0    62.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "4  2026.0   444.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "\n",
       "   dm_000   dn_000   do_000   dp_000  dq_000  dr_000    ds_000   dt_000  \\\n",
       "0     0.0  62282.0  85908.0  32790.0     0.0     0.0  202710.0  37928.0   \n",
       "1     0.0  33736.0  36946.0   5936.0     0.0     0.0  103330.0  16254.0   \n",
       "2     0.0  13876.0  38182.0   8138.0     0.0     0.0   65772.0  10534.0   \n",
       "3     0.0    232.0      0.0      0.0  2014.0   370.0      48.0     18.0   \n",
       "4     0.0  44946.0  62648.0  11506.0     0.0     0.0  149474.0  35154.0   \n",
       "\n",
       "       du_000     dv_000   dx_000   dy_000  dz_000  ea_000      eb_000  \\\n",
       "0  14745580.0  1876644.0      0.0      0.0     0.0     0.0   2801180.0   \n",
       "1   4510080.0   868538.0      0.0      0.0     0.0     0.0   3477820.0   \n",
       "2    300240.0    48028.0      0.0      0.0     0.0     0.0   1040120.0   \n",
       "3     15740.0     1822.0  20174.0     44.0     0.0     0.0         0.0   \n",
       "4    457040.0    80482.0  98334.0  27588.0     0.0     0.0  21173050.0   \n",
       "\n",
       "     ec_00  ed_000    ee_000     ee_001     ee_002    ee_003    ee_004  \\\n",
       "0  2445.80  2712.0  965866.0  1706908.0  1240520.0  493384.0  721044.0   \n",
       "1  2211.76  2334.0  664504.0   824154.0   421400.0  178064.0  293306.0   \n",
       "2  1018.64  1020.0  262032.0   453378.0   277378.0  159812.0  423992.0   \n",
       "3     1.08    54.0    5670.0     1566.0      240.0      46.0      58.0   \n",
       "4  1116.06  1176.0  404740.0   904230.0   622012.0  229790.0  405298.0   \n",
       "\n",
       "     ee_005    ee_006    ee_007    ee_008  ee_009  ef_000  eg_000  \n",
       "0  469792.0  339156.0  157956.0   73224.0     0.0     0.0     0.0  \n",
       "1  245416.0  133654.0   81140.0   97576.0  1500.0     0.0     0.0  \n",
       "2  409564.0  320746.0  158022.0   95128.0   514.0     0.0     0.0  \n",
       "3      44.0      10.0       0.0       0.0     0.0     4.0    32.0  \n",
       "4  347188.0  286954.0  311560.0  433954.0  1218.0     0.0     0.0  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "02d7e734",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:44.154552Z",
     "iopub.status.busy": "2023-06-07T14:18:44.154057Z",
     "iopub.status.idle": "2023-06-07T14:18:44.161401Z",
     "shell.execute_reply": "2023-06-07T14:18:44.160348Z"
    },
    "papermill": {
     "duration": 0.037013,
     "end_time": "2023-06-07T14:18:44.163614",
     "exception": false,
     "start_time": "2023-06-07T14:18:44.126601",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(70827, 163)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2716ffbe",
   "metadata": {
    "papermill": {
     "duration": 0.026058,
     "end_time": "2023-06-07T14:18:44.215997",
     "exception": false,
     "start_time": "2023-06-07T14:18:44.189939",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### seperating trian and test set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "7d8f5e06",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:44.270743Z",
     "iopub.status.busy": "2023-06-07T14:18:44.269946Z",
     "iopub.status.idle": "2023-06-07T14:18:44.277146Z",
     "shell.execute_reply": "2023-06-07T14:18:44.275671Z"
    },
    "papermill": {
     "duration": 0.037393,
     "end_time": "2023-06-07T14:18:44.279661",
     "exception": false,
     "start_time": "2023-06-07T14:18:44.242268",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "Train = df[:60000]\n",
    "Test = df[60000:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "a2c596b6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:44.334939Z",
     "iopub.status.busy": "2023-06-07T14:18:44.334238Z",
     "iopub.status.idle": "2023-06-07T14:18:44.339924Z",
     "shell.execute_reply": "2023-06-07T14:18:44.339079Z"
    },
    "papermill": {
     "duration": 0.036053,
     "end_time": "2023-06-07T14:18:44.342208",
     "exception": false,
     "start_time": "2023-06-07T14:18:44.306155",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(60000, 163)\n",
      "(10827, 163)\n"
     ]
    }
   ],
   "source": [
    "print(Train.shape)\n",
    "print(Test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "43e5c6d9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:44.397819Z",
     "iopub.status.busy": "2023-06-07T14:18:44.396636Z",
     "iopub.status.idle": "2023-06-07T14:18:44.514379Z",
     "shell.execute_reply": "2023-06-07T14:18:44.512970Z"
    },
    "papermill": {
     "duration": 0.14865,
     "end_time": "2023-06-07T14:18:44.517362",
     "exception": false,
     "start_time": "2023-06-07T14:18:44.368712",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "y_train = Train['class'].copy()\n",
    "X_train = Train.drop(['class'],axis=1).copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "085c2027",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:44.574748Z",
     "iopub.status.busy": "2023-06-07T14:18:44.573601Z",
     "iopub.status.idle": "2023-06-07T14:18:44.604717Z",
     "shell.execute_reply": "2023-06-07T14:18:44.603174Z"
    },
    "papermill": {
     "duration": 0.063424,
     "end_time": "2023-06-07T14:18:44.608170",
     "exception": false,
     "start_time": "2023-06-07T14:18:44.544746",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "y_test = Test['class'].copy()\n",
    "X_test = Test.drop(['class'],axis=1).copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "2c9a109b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:44.663505Z",
     "iopub.status.busy": "2023-06-07T14:18:44.663042Z",
     "iopub.status.idle": "2023-06-07T14:18:44.897038Z",
     "shell.execute_reply": "2023-06-07T14:18:44.895517Z"
    },
    "papermill": {
     "duration": 0.265028,
     "end_time": "2023-06-07T14:18:44.900031",
     "exception": false,
     "start_time": "2023-06-07T14:18:44.635003",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from collections import Counter\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.feature_selection import RFE\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "8ac9d772",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:44.956235Z",
     "iopub.status.busy": "2023-06-07T14:18:44.955824Z",
     "iopub.status.idle": "2023-06-07T14:18:44.963891Z",
     "shell.execute_reply": "2023-06-07T14:18:44.962533Z"
    },
    "papermill": {
     "duration": 0.039818,
     "end_time": "2023-06-07T14:18:44.966574",
     "exception": false,
     "start_time": "2023-06-07T14:18:44.926756",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def Identifier_Bin_count(x):\n",
    "    \"\"\"\n",
    "    This function finds the identifiers\n",
    "    and the number of bins in each identifier\n",
    "    \"\"\"\n",
    "    prefix = []\n",
    "    # For each feature name, find it's Identifier and count  \n",
    "    for name in x.columns:\n",
    "        prefix.append(name.split('_')[0])\n",
    "    counter = Counter(prefix)\n",
    "    return list(counter.keys()),list(counter.values())\n",
    "feature_prefix , bin_count = Identifier_Bin_count(X_train)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "eef1b473",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:45.021889Z",
     "iopub.status.busy": "2023-06-07T14:18:45.021487Z",
     "iopub.status.idle": "2023-06-07T14:18:46.921118Z",
     "shell.execute_reply": "2023-06-07T14:18:46.919752Z"
    },
    "papermill": {
     "duration": 1.930281,
     "end_time": "2023-06-07T14:18:46.923472",
     "exception": false,
     "start_time": "2023-06-07T14:18:44.993191",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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p7TC3tYw//vGPyTbbbJPU19cXrGV51ZQk2Ye5bWXtv//+yQ033NB03VVXXZUceuihRdWVJEly0kknJUceeWRy7LHHJscdd1yrr2WFsk488cTkggsuaLru0ksvbfX5mPZcOnPmzGSPPfZILrzwwhZz6uvrkwEDBiyz7mlLW71JW1lZ1zJtZWXtcwplZVkXtZVVTJ9T6Pin6XPaysja56S5D7OukdNkpl2vFTpehfqcNLVk7XOK3b+sxzptn1Oq+7CtnKx9zvI8N2Ttc9rKy9qflOKx3lZG1t6kraysvUmh516W3qStrKy9SdrXsLZ6kyRJko8++ijp37//MtfPmjUrGThwYKvrvJZ6lDQ5WfqTQnlpe5S0OWn6k0JZWXuUNMesUH9SKCNLf5L2PszSn6TNTNOfpMkq1J9kqSdtj1LsPhZzvKdNm5bU1NQkP/3pT5sue+mll5KampqmX34r1X1YKOudd95JampqkhdeeKHp+pkzZyYDBw5MHnvsscz7mebcUMrnc5bavvnNbzbbNmtWlj6zFM+bNBlpe8w0WWl7zLSvOWl6zDRZaXvMLK+FhXrMefPmJbW1tc1+2fbcc89NTj/99Ba3ufDCC5NTTz01U87StVFLNbf0ml8o76qrrkqGDx/e6iA4S05LvXpLw85CWT/96U+T448/fpnrpk6d2uovCqQ59q29j5I244orrkj222+/Za67+uqrixrm5v5v5k6aNCmuvfbaePnll2PWrFlNXx03derUqKmpiccffzzuuuuumDRpUsyfPz8aGhqia9eumbPeeOON2GqrrVL/rYS2siZMmBD9+vWLLl26NP384MGDi8oaN25cTJo0KbbZZptltlm4cGGrX7tb6Ji1d//eeeed6NevX6y22mpNP19bW1tU1mabbRYRsczXOyz9200zZ85sur6YzLTae7zS1HLGGWfEeuutF3feeecyj4v2ZBa73aeP9VprrdXiZZ/96oFS3Ydpnjef/kPi22yzTSxZsiTeeeed6NWrV+aaPv28q6ysjAEDBsTEiRMzHbesz+e0tQ0YMKDNjEI5Bx98cBx//PGx9957xy677BK777577Lzzzu2uqz01rb766qky0mTV1NTE0KFD46GHHortttsu6urq4qWXXooLL7ywqKzu3bvHpZdeGieccEIMHjw4TjrppKLr2n///eOBBx6IL33pS/HGG2/Em2++GTfeeGNRWRERU6ZMiW9961tx/PHHx5e+9KUWcwYNGhRlZWVN/996663jjjvuiMbGxhg/fnxcf/318eabb8bs2bOXuY3NN988U9bS/3/a1ltv3erXt7SW9cYbb0RFRUUMGTKkxe2yZE2YMKHp+bvUZpttFt26dcuU89prr0WSJLH33nsv8/OLFi0q+Npf6Ji1Z//eeeedqKysjP79+zddt/HGG0f37t2LrufT5+OysrLo1atXm1+9Xap9LFVWoe3vuOOOWLBgQTzwwAPRp0+f5VJTWxk77bRT9O7dO/bYY4/YZZddYpdddok999yz4Ot9R9ZU6vtt6XnvW9/6ViRJEo888kgce+yxRWVVVFTE//7v/8bIkSOjvLw8Hn744WV+NkvWl7/85Tj33HPjBz/4QVPW2WefXXRdixcvju985zux/vrrx3nnnddixsSJE2PRokWx4447tnh9lt6kUFZE+rVMW1lZ+5y2srKui9rKKqbPSXPMCmkrI2ufk6aerH1OKfaxVFlpts/a5xRbU9ZjnbbPKdV9mOZ5k7bPWV7nhmL6nLbysvYnHf18LmVWz549M/UmherK0pu0ldW5c+dMvUma45WmN6mrq4vFixcv0zf06NEjNtlkk6b/v/766wV7lDQ5Een7k0J5aXuUQjlZ+pNCWePGjcvUo6Q9Zu3Zvyz9Sdp6svQnpdjHUmalzcjSoxRbVzHHe+lrzKff31z6GjljxoyYMWNGye7DtM+dQYMGNV1fXV0dm2yySUyYMCHzfqY5N5Ty+ZyltjTv+RXKGjp0aOo+c3k+1kuVlbbHTFtXmh4zTVbaHjNtXWl6zLfffjsWLlwYxx9/fLNtt9xyy4iIuPfee+O3v/1tTJkyJRYuXBiLFy+OLbbYInNORLRYc0vryEJ5c+fOje222y46derU4n6lzfn4449b7NWLyaqvr4/nnnuuxTXtpEmTmt0/aY9Ze/fvs+eEgQMHpsr+rNwPc08++eRYf/3145JLLol11lknlixZEvvtt18sXrw4Xn755Tj99NPj1FNPjZ133jmqqqri0UcfjTvuuCNzVtYhRFtZSxeppchasmRJ9O/fv9nfZ4n4pKHImleq/WvrTbdi6vn0k35p9pIlS9qVWcr62rv9brvtFg899FC8/PLLsdNOO3VYTcUe68rKymUu++yxL9V9WOzjqqXLl9djIOvzOW1tn34zp5ic/v37x5/+9Kd4+umn49lnn43TTjsthg4d2urfL0xbV3tqWrpPnz5mbWUXqmf//fePSy+9NH74wx/GI488El/4wheaLVSy7NuYMWOioqIipk2bFgsWLGj1zfVCWYcddlgcdNBB8cEHH8QDDzwQO+20U2ywwQZFZc2fPz9OOeWU2HrrreO73/1uq8eqNUsXC1/84hfjiiuuiOrq6pg6dWqccMIJRT0XWpPlnB/xyRtLpbJ0KJW1hpZUVFTEAw88EBUVFctcnub52FFaG7oVc+5Z6tPn9IhPjl178vJmu+22i7/85S/x//7f/2vzzc/lZY011ojf//738fzzz8czzzwT1113Xdxwww1x//33t/omwPLQ0v3e0NBQVNb+++8fV111VYwbNy4+/vjj+OCDD2LfffcturY333wzFixYEGVlZfHhhx/GuuuuW1TOsGHDonPnzvHkk09G586dY9GiRTFy5Mii67rwwgtjypQpcf/99zd7Hi316SHfZ2XtTdrKyqqtrKx9TltZWc8lbWUV0+eU4pgV2r8srzdp6sna5yyvx0Wpts/a5xRbU7HHulCfU6r7sNjHVUuXL6/HQDFrg7bysvYnHf18Li8vj4j0vUmherL0Jmn2LW1vUigrS29SKCttb1LosTN//vxUPUp71qctPXcK5aV9PUxbV5rXi0JZSZJk6lFKsaYvNqOl7dJmZelPStm3LM/jlaVHKeV90JLPvvZFtPxalqWONPdhmsd7a5d/+vlUynNDKZ/PWfLS/IJboayuXbum7jOX12M9bY+ZJittj5l239L0mGmy0vaYaetK02MuzRo9enSzujt37hyPPfZYjBo1Ks4+++wYPHhwrLnmmnHbbbfFK6+8kimntV+YbU2hvP/93/8tSc7FF19cspp++MMfxrBhw+LMM89stu3SX8rMkleKmi6++OKiz02fVV7UVsvJrFmzYsKECXHKKafETjvtFJtttlnMmTOn6foXX3wxevfuHaecckrU1tZG3759Y8qUKUVl9evXL954442YPXt2u+vafPPNY/z48fHxxx83Xfbyyy8XldW/f/947733Yq211oqNN954mX9VVVWZ89IolLHpppvG+PHjY9GiRU2XjR07tqisYpQys71Zabf/yle+EmeccUZ885vfjOeff75DauqIY13K3DTPmzfffDPmz5/fdNmLL74Y5eXl0bdv36Jq+vTzrqGhIcaNGxebbrpp5rrSPp+z1FZImpyuXbvGl770pbjkkkvimmuuiT/+8Y+tnsMK5S1d2Lf1aa5CGUvfeJ0+fXrTZW+++WbR+7fHHnvEokWL4m9/+1s88sgjccABBxSd9eKLL8Ztt90WN998c3Tt2rXVhUKarH79+sWAAQPiN7/5TTz88MNx6KGHFpWVJEl8//vfjyVLlsRPfvKTNpuHzy7QXnnlldh4441j4sSJMWvWrDjzzDNju+22i80226zgJzBby1r65kFL13/2eVMoa4sttoglS5bEmDFj2qwlTdYXvvCFaGhoiNdee63puokTJ8bcuXMz5Wy55ZbR2NgYM2fObPZ62tKCLk3mZ99wKSZj8803j4aGhnj99debrnvvvfda3b9S1dORme3NKrR9bW1t3HrrrfGzn/0sbr311uVSU6GMysrKGDp0aJx11lnx0EMPxfvvvx///Oc/i87r1KlTm8OeNBk9e/aMadOmNV337rvvxoIFC4rKWm+99WLIkCHx8MMPx8MPPxw77bRTs0+Spc2aPXt2nHPOOXHyySfHIYccEmeeeeYyr7FZsiorK+Oggw6K3/3ud/G73/0u9t133zbfOGkr64477ojHHnssbr755qiurm41o2/fvrH66qu3eP9m6U0KZS2VZi1TKCtLn1MoK+u6qK2srH1Ooby02srI0ueUqp6OzGxvVprts/Q57ampI451KXMLPW/S9jlpayrFuSHr8zlNbVn6k7ay0vQmhTKy9CaFsiLS9yZpstL2Jmmy0vYmhbKy9CYbbbRRdOrUaZnHy5w5c+Ldd9+NiEjdoxTKWSptf1Ior6amJlWPUihn0003Td2fFMrK2qOkPWbt2b9NNtkkdX9Sino6MnN5HK+lsvQoxdb1eT/eS3vfTz+nZ82aFe++++4y33ZRynNDKZ/PWWpLI01W2j4zTVahHjNNRtoeM01W2h4zTVbaHjPtMU/TY6bJSttjbrbZZtG5c+eYMmVKs9eC9ddfP1544YUYPHhwfPWrX42tttoqNt544xYHs4Vylmqp5pZeVwvl9evXL/71r38V/DBJoZzNN9+8xedzMVn9+/ePt956KzbYYINm17f0S1Jpj1l79m/TTTdt1lN++pyTRa4/mdu9e/fo0aNH3HfffbH22mvHlClT4qqrrmq6fqONNoqpU6fGo48+GrW1tfGXv/wlnnrqqaKy9t133/jZz34W3/rWt+L000+PddZZJ15//fVYZ511mn0su1DWfvvtF9dcc02cd955ccopp8T7778ft99+e1F17b///nHbbbfFKaecEt/97ndj3XXXjalTp8YTTzwRJ554Yqy33nqZ8tJIU9NPf/rT+OEPfxgnnXRSTJkypWn/PrvgL0U9WetbnllZtj/66KOjsbExvvGNb8Qtt9wS2223XUlr6ohjXcrcNI+r6667Ls4555z49re/HTNnzoyLL744DjzwwGYv5mlr+tWvfhV9+/aNTTfdNO66666YM2dOs+a2lM/n5Xm87rzzzlh77bVjiy22iPLy8nj88cdj7bXXbvVTYIXy1lprrVh99dXjb3/7W6y33nqx2mqrNXsjNc05ef3114/rr78+TjvttHjvvfeKPvdFfPKbyMOHD49rr702JkyYEPvtt19RWR999FGcddZZcdRRR8Vuu+0WvXv3jkMPPTR233332GeffTLXFfHJb8BfdNFF0aVLl9hzzz2Lquv666+PZ599Nm6//faYP39+0xt8VVVVzX5rfOrUqTFq1Kg4/PDD4/XXX4977rknzj777Ojdu3d06tQp7r777vjKV74S//73v+Omm25qsZ5CWUu9+OKLccstt8Qee+wRzz77bDz++OMxevToTFkbbrhhHHzwwXHuuefG+eefH/369YspU6bEjBkzWv26ttayNt1009hll13i/PPPj4svvrjpK1pb+8361nI22WST2H///eOss86Kc845J7bccsuYNWtW/POf/4x+/frFbrvtVvQxS6O1jM022yyGDh0aP/rRj+LCCy+MysrKuOyyy2L11Vdv9U20UtTTkZntzUqz/eDBg+OWW26JE088MSorK+NrX/tah9bUVsb//d//RV1dXQwZMiS6desWf/3rX2PJkiUFv46qrZo22GCDGDNmTOy7777RqVOnVj+l2FbGjjvuGL/85S9j6623jiVLlsSVV17Z5tcfFTpG+++/f1x//fWxePHi+MEPflD0vl1wwQWx/vrrxymnnBKLFy+Ogw8+OC6//PK44IILiqrrsMMOazqv3HvvvUXV9eyzz8YVV1wRP/rRj6K6urrpjf/VV1+92WvhaqutFl//+tfjiiuuiE6dOsU222wTM2fOjLfeeitTb1Ioa+knHNOsZQplHXjggan7nEJZWddFbWVl7XMK5R122GGt1pGlprR9Ttr7MKtSZrb3eKWtJW2f057964hjXcrcQo+rtH1O2ppKcW7I+nwulDdv3rxM/UlbWQcffHDB3qRQxkEHHZS6NymUddhhh6XuTQpl7bPPPql7kzR1RaTrTQplTZ06NXVvsuaaa8ahhx7a9KnbtdZaK6655pqm82TaHqVQzlJp+5NCeWl7lEI5WfqTQllZe5S0x6wthTKy9CelqCdrfcs7K0tG2h6l2Lo+78e7b9++MWLEiPjhD38YP/7xj6Nr165x5ZVXxrrrrhsjRozIXFOac0Mpn8/L+3hl6TPT1FWox0yTkbbHTHuc0vSYabLS9php60rTYxbKytJjdu3aNY4//vgYNWpUJEkS2267bXz00Ufx0ksvxRprrBEbbbRRPPjgg/G3v/0tNtxww/jDH/4QY8eOjQ033DBTTu/evSMi4qabblqm5urq6thjjz2a7WOhvK9+9atx9913x+mnnx4nnXRSVFVVxcsvvxwDBw5cZjhcKOeII46I22+/valXHzduXPz+979v8bgXyjryyCPjN7/5TZx++ulx4oknRnV1dbz33nvx6KOPxiWXXNLsF/oL5R188MEt1pEl4/DDD48777wzrrjiivif//mfeOONN5r2L+u5I9fD3PLy8rjmmmvikksuif322y822WSTOP/88+Poo4+OiE9+M/LYY4+Niy66KBYtWhS77757nHLKKXHDDTdkzurcuXPcfvvtcfnll8dJJ50UjY2Nsdlmm7X4xlKhrDXXXDN+9rOfxQUXXBAHHXRQbL755nHmmWfGqaeemjmrS5cucc8998SVV14Z3/72t2PevHmx7rrrxk477dTi1/AUyivFce/atWvcfPPNceGFF8aBBx4YNTU18a1vfSvOOOOMZh8/L0U9HbGPpcrKuv3Xvva1SJIkTjrppLj11lub/Y2w9tTUEce6lLlpHuu33XZbXHrppfE///M/0aVLl9hrr73inHPOKbqmM844I2655ZZ4/fXXY6ONNoqbbrqp2WKllM/n5Xm81lhjjbjlllvivffei/Ly8qitrY2f//znTV8nljWvsrIyzj///Ljxxhvjuuuui+222y7uvvvuTBmdOnWKq666quncUFtbG6eddlqLX9GV9jgdcMABcdJJJ8WQIUOaFh1Zsy699NLo0qVLnH766RER8YUvfCHOPPPMuPDCC2ObbbZZ5isw0ta17777xv/+7//Gfvvt1+rXlRXKGjNmTMyfPz+OOOKIZbYbNWpUHHLIIctcdtBBB8XHH38chx12WFRUVMRRRx0Vhx9+eJSVlcVll10WV199ddx9993Rv3//OPvss+OUU05psaa2spY67rjjYty4cXHjjTfGmmuuGWeffXbssssumbMuvPDCuPrqq+PCCy+M2bNnR+/eveMb3/hGUXWNGjUqzj///DjqqKOiV69e8d3vfrfVr+wrlHPzzTfHZZddFtOmTYsePXrE1ltv3eYgN80xS6OtjMsvvzzOO++8+OpXvxprr712nH766fH222+3+tgqRT0dmdnerLTbb7vttvHzn/88TjrppCgvL49jjjmmQ/evtYwXXnghnnzyybjhhhti4cKFsfHGG8dVV10VX/jCF4rez+985zvxox/9qOlTQOPHj8+ccfbZZ8e5554bRx11VKyzzjpx7rnnxrhx44o+RnvvvXfTGxwtNXppsh588MF4+umn4/e//31UVlZGZWVlXHnllXHEEUfE7rvv3uJzsVBdffv2jcGDB8fs2bOX+ftbWeq64YYborGxMS644IJl1v4HH3xwXHbZZc1yvvnNb0ZFRUVcd911MW3atFh77bXjiCOOiMMOOyx1b1Ioa6k0a5lCWVn6nEJZWddFbWVl7XPSHrM0WsvI0ueUsp6OzGxvVtrt0/Q57a2pI451KXPbeqyn7XPS1lSKc0Mxz+e28qqrqzP1J21lpelNCmVk6U3SHvc0vUmhrCy9Sdq60vQmhbKy9CYREWeddVbT1zKvueaacdxxx8VHH30UEZ98cittj9JWzlJZ+pNCeWl7lEI5WfqTNFlZepQ0x6yQQhlZ+pNS1NORmcvjeH1a2h6l2Lo+78d71KhRcemll8bJJ58cixcvju222y5+/vOfNxsIlvLcUMrn8/I8XlVVVZn6zEJ1pekxC2Vk6THTHKe0PWZbWVl7zDR1pe0x28p64YUXMvWYp512Wqy11loxevTomDx5clRVVcVWW20VJ598cgwaNCjefPPN+N73vhdlZWWx7777xpFHHhlPP/10ppyln8w+44wz4tJLL4133303tthii7j55ptb7XXayquuro677rorrrjiijj66KOjvLw8ttxyy9h2220z5fTu3Tuuv/76GDVqVPzqV7+KgQMHxve+970499xzM9e07rrrxr333htXXnllnHDCCbFo0aLo3bt37LLLLq2uSdvKS6utjD59+sS1114bl19+efziF7+IrbfeOk4++eS48MILM/+ZurJkZfojaqwwDz30UJx77rnxr3/9K/Pf5cqzRYsWRW1tbdxxxx0xdOjQFV0OKU2ePDlGjBgRDz74YOo/Vp6nfPJv6tSpMXz48Lj//vujf//+K7ocVjIffPBB7LbbbnHnnXe269NGeXT44YfHjjvuGN/73vdWdCmsJJIkib333juOOOKIOO6441Z0OayE9DnkiT6HluhN6Gj6E/Jm+PDhccwxxxT8hqa85pNvekw62s033xy//vWv469//Wum7XL9yVzy68EHH4wNN9ww1l133Rg/fnxceeWVsffee69Ub3B89NFH8cQTT0R5eXmrfy8SWLUsXrw4pk+fHldddVUMGjTImyWUxD/+8Y+YP39+1NTUxPTp0+OKK66IDTbYoM2vqfy8Wfqbv2+99Va7vzEClpoxY0b84Q9/iGnTprX4qSEohj4H+LzQm9BR9CfAqkqPSUf45S9/GbW1tVFdXR0vvPBC3HbbbfHVr341c45hLkWZPn16XHfddTF9+vRYe+21Y++9917pfovtuuuui0ceeSTOPPPMFv9mF7DqefHFF+OYY46Jvn37tvm1O5BFQ0NDXHPNNVFXVxdrrrlmDB48uODfN/28efrpp+Oss86KYcOGxciRI1d0Oawkhg4dGtXV1XHRRRdF9+7dV3Q5rCT0OcDnhd6EjqI/AVZVekw6wnvvvRc333xzzJkzJ3r37h3HHXdcm3+KrjW+ZhkAAAAAAAAgh1r+q78AAAAAAAAArFCGuQAAAAAAAAA5ZJgLAAAAAAAAkEOGuQAAAAAAAAA5ZJgLAAAAAAAAkEOGuQAAAAAAAAA5ZJgLAAAAAAAAkEOGuQAAAAAAAAA59P8B5mK4Eqy4YugAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 2400x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the same\n",
    "plt.figure(figsize=(24,5))\n",
    "sns.barplot(x = feature_prefix,y = bin_count)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "9eccda80",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:46.981498Z",
     "iopub.status.busy": "2023-06-07T14:18:46.980772Z",
     "iopub.status.idle": "2023-06-07T14:18:46.988208Z",
     "shell.execute_reply": "2023-06-07T14:18:46.986812Z"
    },
    "papermill": {
     "duration": 0.039639,
     "end_time": "2023-06-07T14:18:46.991063",
     "exception": false,
     "start_time": "2023-06-07T14:18:46.951424",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Histogram Identifiers are:  ['ag', 'ay', 'az', 'ba', 'cn', 'cs', 'ee']\n"
     ]
    }
   ],
   "source": [
    "hist_identifier = [feature_prefix[i] for i,j in enumerate(bin_count) if j==10]\n",
    "print(\"The Histogram Identifiers are: \",hist_identifier)\n",
    "\n",
    "# Getting the names of the features having histograms bin information\n",
    "hist_features = [i for i in X_train.columns if i.split('_')[0] in hist_identifier]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "7abefb4a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:18:47.048158Z",
     "iopub.status.busy": "2023-06-07T14:18:47.047089Z",
     "iopub.status.idle": "2023-06-07T14:38:40.509410Z",
     "shell.execute_reply": "2023-06-07T14:38:40.508193Z"
    },
    "papermill": {
     "duration": 1193.494327,
     "end_time": "2023-06-07T14:38:40.512408",
     "exception": false,
     "start_time": "2023-06-07T14:18:47.018081",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting estimator with 70 features.\n",
      "Fitting estimator with 69 features.\n",
      "Fitting estimator with 68 features.\n",
      "Fitting estimator with 67 features.\n",
      "Fitting estimator with 66 features.\n",
      "Fitting estimator with 65 features.\n",
      "Fitting estimator with 64 features.\n",
      "Fitting estimator with 63 features.\n",
      "Fitting estimator with 62 features.\n",
      "Fitting estimator with 61 features.\n",
      "Fitting estimator with 60 features.\n",
      "Fitting estimator with 59 features.\n",
      "Fitting estimator with 58 features.\n",
      "Fitting estimator with 57 features.\n",
      "Fitting estimator with 56 features.\n",
      "Fitting estimator with 55 features.\n",
      "Fitting estimator with 54 features.\n",
      "Fitting estimator with 53 features.\n",
      "Fitting estimator with 52 features.\n",
      "Fitting estimator with 51 features.\n",
      "Fitting estimator with 50 features.\n",
      "Fitting estimator with 49 features.\n",
      "Fitting estimator with 48 features.\n",
      "Fitting estimator with 47 features.\n",
      "Fitting estimator with 46 features.\n",
      "Fitting estimator with 45 features.\n",
      "Fitting estimator with 44 features.\n",
      "Fitting estimator with 43 features.\n",
      "Fitting estimator with 42 features.\n",
      "Fitting estimator with 41 features.\n",
      "Fitting estimator with 40 features.\n",
      "Fitting estimator with 39 features.\n",
      "Fitting estimator with 38 features.\n",
      "Fitting estimator with 37 features.\n",
      "Fitting estimator with 36 features.\n",
      "Fitting estimator with 35 features.\n",
      "Fitting estimator with 34 features.\n",
      "Fitting estimator with 33 features.\n",
      "Fitting estimator with 32 features.\n",
      "Fitting estimator with 31 features.\n",
      "Fitting estimator with 30 features.\n",
      "Fitting estimator with 29 features.\n",
      "Fitting estimator with 28 features.\n",
      "Fitting estimator with 27 features.\n",
      "Fitting estimator with 26 features.\n",
      "Fitting estimator with 25 features.\n",
      "Fitting estimator with 24 features.\n",
      "Fitting estimator with 23 features.\n",
      "Fitting estimator with 22 features.\n",
      "Fitting estimator with 21 features.\n",
      "Fitting estimator with 20 features.\n",
      "Fitting estimator with 19 features.\n",
      "Fitting estimator with 18 features.\n",
      "Fitting estimator with 17 features.\n",
      "Fitting estimator with 16 features.\n",
      "The top features selected after Recursive Feature Elimination are: \n",
      " ['ag_001', 'ag_002', 'ag_003', 'ag_005', 'ay_005', 'ay_006', 'ay_008', 'ba_003', 'cn_000', 'cn_004', 'cs_002', 'cs_004', 'ee_000', 'ee_003', 'ee_005']\n"
     ]
    }
   ],
   "source": [
    "def get_top(df,y,n):\n",
    "    \"\"\"\n",
    "    This function returns the top n features,\n",
    "    by performing Recursive Feature Elimination\n",
    "    using Random Forest Classifier\n",
    "    \"\"\"\n",
    "    # Use RFE algorithm from sklearn to perform feature selection\n",
    "    feature_select = RFE(estimator=RandomForestClassifier(n_estimators=150,max_depth=5,random_state=1),\n",
    "                         n_features_to_select=n,\n",
    "                         verbose=5)\n",
    "    feature_select.fit(df,y)\n",
    "\n",
    "    # support_ gives an array of True/False for each feature where True signifies that the feature is selected\n",
    "    top_f = [ c for i,c in enumerate(df.columns.tolist()) if feature_select.support_[i] ]   \n",
    "    return top_f\n",
    "\n",
    "top_feature_hist = get_top(X_train[hist_features],y_train,15)\n",
    "print(\"The top features selected after Recursive Feature Elimination are: \\n\",top_feature_hist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "4bd4def4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:38:40.583486Z",
     "iopub.status.busy": "2023-06-07T14:38:40.583046Z",
     "iopub.status.idle": "2023-06-07T14:38:40.590110Z",
     "shell.execute_reply": "2023-06-07T14:38:40.588787Z"
    },
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     "exception": false,
     "start_time": "2023-06-07T14:38:40.548016",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import accuracy_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "2899cb7a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:38:40.660556Z",
     "iopub.status.busy": "2023-06-07T14:38:40.660090Z",
     "iopub.status.idle": "2023-06-07T14:39:02.826146Z",
     "shell.execute_reply": "2023-06-07T14:39:02.824590Z"
    },
    "papermill": {
     "duration": 22.203109,
     "end_time": "2023-06-07T14:39:02.829061",
     "exception": false,
     "start_time": "2023-06-07T14:38:40.625952",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[10664     7]\n",
      " [   57    99]]\n"
     ]
    }
   ],
   "source": [
    "model = RandomForestClassifier()\n",
    "model.fit(X_train[top_feature_hist],y_train)\n",
    "y_pred=model.predict(X_test[top_feature_hist])\n",
    "confusion_mat = confusion_matrix(y_test, y_pred)\n",
    "\n",
    "print(confusion_mat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "71014167",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-07T14:39:02.896918Z",
     "iopub.status.busy": "2023-06-07T14:39:02.896167Z",
     "iopub.status.idle": "2023-06-07T14:39:02.904894Z",
     "shell.execute_reply": "2023-06-07T14:39:02.903530Z"
    },
    "papermill": {
     "duration": 0.045343,
     "end_time": "2023-06-07T14:39:02.907430",
     "exception": false,
     "start_time": "2023-06-07T14:39:02.862087",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "99.41%\n"
     ]
    }
   ],
   "source": [
    "accuracy = accuracy_score(y_test, y_pred)\n",
    "print(\"{:.2f}%\".format(accuracy*100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "769306f5",
   "metadata": {
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     "end_time": "2023-06-07T14:39:02.971200",
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  }
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