{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from collections import Counter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Found cached dataset liver (/Users/natalia.szymczyk/.cache/huggingface/datasets/mstz___liver/liver/1.0.0/3115a4001e742dc2c89457a3906d35982a649915f71f35fc5e6d025c786eeacf)\n",
      "100%|██████████| 1/1 [00:00<00:00, 684.45it/s]\n"
     ]
    }
   ],
   "source": [
    "from datasets import load_dataset\n",
    "\n",
    "dataset = load_dataset(\"mstz/liver\")['train']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dataset({\n",
       "    features: ['age', 'is_male', 'total_bilirubin', 'direct_ribilubin', 'alkaline_phosphotase', 'alamine_aminotransferasi', 'aspartate_aminotransferase', 'total_proteins', 'albumin', 'albumin_to_globulin_ratio', 'class'],\n",
       "    num_rows: 583\n",
       "})"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset = dataset.to_pandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "train, test = train_test_split(dataset, test_size=0.2, random_state=42)\n",
    "train, val = train_test_split(train, test_size=0.2, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
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       "     age  is_male  total_bilirubin  direct_ribilubin  alkaline_phosphotase  \\\n",
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       "33    38    False              2.6               1.2                   410   \n",
       "534   39     True              1.6               0.8                   230   \n",
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       "48    32    False              0.6               0.1                   176   \n",
       "..   ...      ...              ...               ...                   ...   \n",
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       "\n",
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       "107                        29                          39             6.0   \n",
       "33                         59                          57             5.6   \n",
       "534                        88                          74             8.0   \n",
       "204                        27                          26             6.4   \n",
       "48                         39                          28             6.0   \n",
       "..                        ...                         ...             ...   \n",
       "42                         25                          47             6.1   \n",
       "179                        30                          25             5.5   \n",
       "430                        20                          33             4.8   \n",
       "475                       119                          42             7.9   \n",
       "425                        59                         126             4.3   \n",
       "\n",
       "     albumin  albumin_to_globulin_ratio  class  \n",
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       "33       3.0                       0.80      1  \n",
       "534      4.0                       1.00      1  \n",
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       "48       3.0                       1.00      0  \n",
       "..       ...                        ...    ...  \n",
       "42       2.3                       0.60      1  \n",
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       "430      1.9                       0.60      0  \n",
       "475      4.1                       1.00      1  \n",
       "425      2.5                       1.40      0  \n",
       "\n",
       "[372 rows x 11 columns]"
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     "execution_count": 48,
     "metadata": {},
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  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
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       "     age  is_male  total_bilirubin  direct_ribilubin  alkaline_phosphotase  \\\n",
       "582   38     True              1.0               0.3                   216   \n",
       "453   46     True              0.7               0.2                   224   \n",
       "89    60     True              4.0               1.9                   238   \n",
       "71    75    False              0.8               0.2                   188   \n",
       "124   28     True              0.6               0.1                   177   \n",
       "..   ...      ...              ...               ...                   ...   \n",
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       "487   32     True              0.7               0.2                   276   \n",
       "27    34     True              6.2               3.0                   240   \n",
       "307   30     True              0.8               0.2                   174   \n",
       "512   56     True              1.0               0.3                   195   \n",
       "\n",
       "     alamine_aminotransferasi  aspartate_aminotransferase  total_proteins  \\\n",
       "582                        21                          24             7.3   \n",
       "453                        40                          23             7.1   \n",
       "89                        119                         350             7.1   \n",
       "71                         20                          29             4.4   \n",
       "124                        36                          29             6.9   \n",
       "..                        ...                         ...             ...   \n",
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       "27                       1680                         850             7.2   \n",
       "307                        21                          47             4.6   \n",
       "512                        22                          28             5.8   \n",
       "\n",
       "     albumin  albumin_to_globulin_ratio  class  \n",
       "582      4.4                       1.50      1  \n",
       "453      3.0                       0.70      0  \n",
       "89       3.3                       0.80      0  \n",
       "71       1.8                       0.60      0  \n",
       "124      4.1                       1.40      1  \n",
       "..       ...                        ...    ...  \n",
       "236      3.8                       0.90      1  \n",
       "487      2.9                       0.93      0  \n",
       "27       4.0                       1.20      0  \n",
       "307      2.3                       1.00      0  \n",
       "512      2.6                       0.80      1  \n",
       "\n",
       "[94 rows x 11 columns]"
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     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "val"
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  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
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       "      <th>is_male</th>\n",
       "      <th>total_bilirubin</th>\n",
       "      <th>direct_ribilubin</th>\n",
       "      <th>alkaline_phosphotase</th>\n",
       "      <th>alamine_aminotransferasi</th>\n",
       "      <th>aspartate_aminotransferase</th>\n",
       "      <th>total_proteins</th>\n",
       "      <th>albumin</th>\n",
       "      <th>albumin_to_globulin_ratio</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>355</th>\n",
       "      <td>19</td>\n",
       "      <td>True</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.8</td>\n",
       "      <td>178</td>\n",
       "      <td>13</td>\n",
       "      <td>26</td>\n",
       "      <td>8.0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>1.30</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>407</th>\n",
       "      <td>12</td>\n",
       "      <td>True</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>719</td>\n",
       "      <td>157</td>\n",
       "      <td>108</td>\n",
       "      <td>7.2</td>\n",
       "      <td>3.7</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>60</td>\n",
       "      <td>True</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2.8</td>\n",
       "      <td>214</td>\n",
       "      <td>412</td>\n",
       "      <td>850</td>\n",
       "      <td>7.3</td>\n",
       "      <td>3.2</td>\n",
       "      <td>0.78</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>402</th>\n",
       "      <td>42</td>\n",
       "      <td>False</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>162</td>\n",
       "      <td>155</td>\n",
       "      <td>108</td>\n",
       "      <td>8.1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>268</th>\n",
       "      <td>40</td>\n",
       "      <td>True</td>\n",
       "      <td>14.5</td>\n",
       "      <td>6.4</td>\n",
       "      <td>358</td>\n",
       "      <td>50</td>\n",
       "      <td>75</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2.1</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>516</th>\n",
       "      <td>60</td>\n",
       "      <td>True</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.3</td>\n",
       "      <td>168</td>\n",
       "      <td>16</td>\n",
       "      <td>24</td>\n",
       "      <td>6.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>305</th>\n",
       "      <td>54</td>\n",
       "      <td>False</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.7</td>\n",
       "      <td>195</td>\n",
       "      <td>36</td>\n",
       "      <td>16</td>\n",
       "      <td>7.9</td>\n",
       "      <td>3.7</td>\n",
       "      <td>0.90</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>47</td>\n",
       "      <td>False</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>292</td>\n",
       "      <td>64</td>\n",
       "      <td>67</td>\n",
       "      <td>5.6</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.47</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>312</th>\n",
       "      <td>27</td>\n",
       "      <td>True</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.6</td>\n",
       "      <td>106</td>\n",
       "      <td>25</td>\n",
       "      <td>54</td>\n",
       "      <td>8.5</td>\n",
       "      <td>4.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>329</th>\n",
       "      <td>21</td>\n",
       "      <td>True</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.2</td>\n",
       "      <td>211</td>\n",
       "      <td>14</td>\n",
       "      <td>23</td>\n",
       "      <td>7.3</td>\n",
       "      <td>4.1</td>\n",
       "      <td>1.20</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>117 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     age  is_male  total_bilirubin  direct_ribilubin  alkaline_phosphotase  \\\n",
       "355   19     True              1.4               0.8                   178   \n",
       "407   12     True              1.0               0.2                   719   \n",
       "90    60     True              5.7               2.8                   214   \n",
       "402   42    False              0.5               0.1                   162   \n",
       "268   40     True             14.5               6.4                   358   \n",
       "..   ...      ...              ...               ...                   ...   \n",
       "516   60     True              0.9               0.3                   168   \n",
       "305   54    False              1.4               0.7                   195   \n",
       "167   47    False              3.0               1.5                   292   \n",
       "312   27     True              1.3               0.6                   106   \n",
       "329   21     True              0.7               0.2                   211   \n",
       "\n",
       "     alamine_aminotransferasi  aspartate_aminotransferase  total_proteins  \\\n",
       "355                        13                          26             8.0   \n",
       "407                       157                         108             7.2   \n",
       "90                        412                         850             7.3   \n",
       "402                       155                         108             8.1   \n",
       "268                        50                          75             5.7   \n",
       "..                        ...                         ...             ...   \n",
       "516                        16                          24             6.7   \n",
       "305                        36                          16             7.9   \n",
       "167                        64                          67             5.6   \n",
       "312                        25                          54             8.5   \n",
       "329                        14                          23             7.3   \n",
       "\n",
       "     albumin  albumin_to_globulin_ratio  class  \n",
       "355      4.6                       1.30      1  \n",
       "407      3.7                       1.00      0  \n",
       "90       3.2                       0.78      0  \n",
       "402      4.0                       0.90      0  \n",
       "268      2.1                       0.50      0  \n",
       "..       ...                        ...    ...  \n",
       "516      3.0                       0.80      0  \n",
       "305      3.7                       0.90      1  \n",
       "167      1.8                       0.47      0  \n",
       "312      4.8                        NaN      1  \n",
       "329      4.1                       1.20      1  \n",
       "\n",
       "[117 rows x 11 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>total_bilirubin</th>\n",
       "      <th>direct_ribilubin</th>\n",
       "      <th>alkaline_phosphotase</th>\n",
       "      <th>alamine_aminotransferasi</th>\n",
       "      <th>aspartate_aminotransferase</th>\n",
       "      <th>total_proteins</th>\n",
       "      <th>albumin</th>\n",
       "      <th>albumin_to_globulin_ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>372.000000</td>\n",
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       "      <td>372.000000</td>\n",
       "      <td>372.000000</td>\n",
       "      <td>372.000000</td>\n",
       "      <td>372.000000</td>\n",
       "      <td>372.000000</td>\n",
       "      <td>372.000000</td>\n",
       "      <td>371.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>44.680108</td>\n",
       "      <td>3.415860</td>\n",
       "      <td>1.494355</td>\n",
       "      <td>286.473118</td>\n",
       "      <td>72.986559</td>\n",
       "      <td>110.147849</td>\n",
       "      <td>6.500269</td>\n",
       "      <td>3.150806</td>\n",
       "      <td>0.959515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>16.054568</td>\n",
       "      <td>6.736683</td>\n",
       "      <td>2.877245</td>\n",
       "      <td>242.459927</td>\n",
       "      <td>147.472734</td>\n",
       "      <td>306.425153</td>\n",
       "      <td>1.100049</td>\n",
       "      <td>0.806994</td>\n",
       "      <td>0.336514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>63.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>2.700000</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>0.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>32.000000</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>170.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>5.775000</td>\n",
       "      <td>2.575000</td>\n",
       "      <td>0.700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>45.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>205.500000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>42.000000</td>\n",
       "      <td>6.600000</td>\n",
       "      <td>3.100000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>58.000000</td>\n",
       "      <td>2.625000</td>\n",
       "      <td>1.300000</td>\n",
       "      <td>298.000000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>86.250000</td>\n",
       "      <td>7.200000</td>\n",
       "      <td>3.800000</td>\n",
       "      <td>1.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>85.000000</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>19.700000</td>\n",
       "      <td>2110.000000</td>\n",
       "      <td>1350.000000</td>\n",
       "      <td>4929.000000</td>\n",
       "      <td>9.600000</td>\n",
       "      <td>5.500000</td>\n",
       "      <td>2.800000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              age  total_bilirubin  direct_ribilubin  alkaline_phosphotase  \\\n",
       "count  372.000000       372.000000        372.000000            372.000000   \n",
       "mean    44.680108         3.415860          1.494355            286.473118   \n",
       "std     16.054568         6.736683          2.877245            242.459927   \n",
       "min      4.000000         0.400000          0.100000             63.000000   \n",
       "25%     32.000000         0.800000          0.200000            170.000000   \n",
       "50%     45.000000         1.000000          0.300000            205.500000   \n",
       "75%     58.000000         2.625000          1.300000            298.000000   \n",
       "max     85.000000        75.000000         19.700000           2110.000000   \n",
       "\n",
       "       alamine_aminotransferasi  aspartate_aminotransferase  total_proteins  \\\n",
       "count                372.000000                  372.000000      372.000000   \n",
       "mean                  72.986559                  110.147849        6.500269   \n",
       "std                  147.472734                  306.425153        1.100049   \n",
       "min                   10.000000                   11.000000        2.700000   \n",
       "25%                   24.000000                   25.000000        5.775000   \n",
       "50%                   35.000000                   42.000000        6.600000   \n",
       "75%                   60.000000                   86.250000        7.200000   \n",
       "max                 1350.000000                 4929.000000        9.600000   \n",
       "\n",
       "          albumin  albumin_to_globulin_ratio  \n",
       "count  372.000000                 371.000000  \n",
       "mean     3.150806                   0.959515  \n",
       "std      0.806994                   0.336514  \n",
       "min      0.900000                   0.300000  \n",
       "25%      2.575000                   0.700000  \n",
       "50%      3.100000                   1.000000  \n",
       "75%      3.800000                   1.100000  \n",
       "max      5.500000                   2.800000  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numerical_features = ['age', 'total_bilirubin', 'direct_ribilubin', 'alkaline_phosphotase',\n",
    "                      'alamine_aminotransferasi', 'aspartate_aminotransferase', 'total_proteins', 'albumin',\n",
    "                      'albumin_to_globulin_ratio']\n",
    "train[numerical_features].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Rozkład częstości dla klas:\n",
      "1: 30.38%\n",
      "0: 69.62%\n"
     ]
    }
   ],
   "source": [
    "label_counter = Counter(train['class'])\n",
    "print(\"\\nRozkład częstości dla klas:\")\n",
    "for label in label_counter.keys():\n",
    "    print(f\"{label}: {label_counter[label] / len(train) * 100:.2f}%\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "scaler = MinMaxScaler()\n",
    "train[numerical_features] = scaler.fit_transform(train[numerical_features])\n",
    "test[numerical_features] = scaler.fit_transform(test[numerical_features])\n",
    "val[numerical_features] = scaler.fit_transform(val[numerical_features])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
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       "          age  is_male  total_bilirubin  direct_ribilubin  \\\n",
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       "48   0.345679    False         0.002681          0.000000   \n",
       "..        ...      ...              ...               ...   \n",
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       "475  0.419753     True         0.024129          0.045918   \n",
       "425  0.666667     True         0.000000          0.000000   \n",
       "\n",
       "     alkaline_phosphotase  alamine_aminotransferasi  \\\n",
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       "33               0.169516                  0.036567   \n",
       "534              0.081583                  0.058209   \n",
       "204              0.035173                  0.012687   \n",
       "48               0.055203                  0.021642   \n",
       "..                    ...                       ...   \n",
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       "179              0.157792                  0.014925   \n",
       "430              0.058134                  0.007463   \n",
       "475              0.120664                  0.081343   \n",
       "425              0.018075                  0.036567   \n",
       "\n",
       "     aspartate_aminotransferase  total_proteins   albumin  \\\n",
       "107                    0.005693        0.478261  0.282609   \n",
       "33                     0.009353        0.420290  0.456522   \n",
       "534                    0.012810        0.768116  0.673913   \n",
       "204                    0.003050        0.536232  0.521739   \n",
       "48                     0.003457        0.478261  0.456522   \n",
       "..                          ...             ...       ...   \n",
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       "179                    0.002847        0.405797  0.195652   \n",
       "430                    0.004473        0.304348  0.217391   \n",
       "475                    0.006303        0.753623  0.695652   \n",
       "425                    0.023383        0.231884  0.347826   \n",
       "\n",
       "     albumin_to_globulin_ratio  class  \n",
       "107                      0.080      1  \n",
       "33                       0.200      1  \n",
       "534                      0.280      1  \n",
       "204                      0.280      1  \n",
       "48                       0.280      0  \n",
       "..                         ...    ...  \n",
       "42                       0.120      1  \n",
       "179                      0.072      0  \n",
       "430                      0.120      0  \n",
       "475                      0.280      1  \n",
       "425                      0.440      0  \n",
       "\n",
       "[371 rows x 11 columns]"
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     },
     "execution_count": 56,
     "metadata": {},
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    }
   ],
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  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "train.dropna(inplace=True)\n",
    "test.dropna(inplace=True)\n",
    "val.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
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       "\n",
       "[371 rows x 11 columns]"
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     "execution_count": 59,
     "metadata": {},
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  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
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       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>0.372093</td>\n",
       "      <td>True</td>\n",
       "      <td>0.013333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.278644</td>\n",
       "      <td>0.017972</td>\n",
       "      <td>0.023077</td>\n",
       "      <td>0.527273</td>\n",
       "      <td>0.473684</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>516</th>\n",
       "      <td>0.651163</td>\n",
       "      <td>True</td>\n",
       "      <td>0.013333</td>\n",
       "      <td>0.014184</td>\n",
       "      <td>0.063051</td>\n",
       "      <td>0.006418</td>\n",
       "      <td>0.013462</td>\n",
       "      <td>0.672727</td>\n",
       "      <td>0.526316</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>305</th>\n",
       "      <td>0.581395</td>\n",
       "      <td>False</td>\n",
       "      <td>0.030000</td>\n",
       "      <td>0.042553</td>\n",
       "      <td>0.081356</td>\n",
       "      <td>0.032092</td>\n",
       "      <td>0.005769</td>\n",
       "      <td>0.890909</td>\n",
       "      <td>0.710526</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>False</td>\n",
       "      <td>0.083333</td>\n",
       "      <td>0.099291</td>\n",
       "      <td>0.147119</td>\n",
       "      <td>0.068036</td>\n",
       "      <td>0.054808</td>\n",
       "      <td>0.472727</td>\n",
       "      <td>0.210526</td>\n",
       "      <td>0.113333</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>329</th>\n",
       "      <td>0.197674</td>\n",
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       "      <td>0.006667</td>\n",
       "      <td>0.007092</td>\n",
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       "      <td>0.815789</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>115 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          age  is_male  total_bilirubin  direct_ribilubin  \\\n",
       "355  0.174419     True         0.030000          0.049645   \n",
       "407  0.093023     True         0.016667          0.007092   \n",
       "90   0.651163     True         0.173333          0.191489   \n",
       "402  0.441860    False         0.000000          0.000000   \n",
       "268  0.418605     True         0.466667          0.446809   \n",
       "..        ...      ...              ...               ...   \n",
       "109  0.372093     True         0.013333          0.000000   \n",
       "516  0.651163     True         0.013333          0.014184   \n",
       "305  0.581395    False         0.030000          0.042553   \n",
       "167  0.500000    False         0.083333          0.099291   \n",
       "329  0.197674     True         0.006667          0.007092   \n",
       "\n",
       "     alkaline_phosphotase  alamine_aminotransferasi  \\\n",
       "355              0.069831                  0.002567   \n",
       "407              0.436610                  0.187420   \n",
       "90               0.094237                  0.514763   \n",
       "402              0.058983                  0.184852   \n",
       "268              0.191864                  0.050064   \n",
       "..                    ...                       ...   \n",
       "109              0.278644                  0.017972   \n",
       "516              0.063051                  0.006418   \n",
       "305              0.081356                  0.032092   \n",
       "167              0.147119                  0.068036   \n",
       "329              0.092203                  0.003851   \n",
       "\n",
       "     aspartate_aminotransferase  total_proteins   albumin  \\\n",
       "355                    0.015385        0.909091  0.947368   \n",
       "407                    0.094231        0.763636  0.710526   \n",
       "90                     0.807692        0.781818  0.578947   \n",
       "402                    0.094231        0.927273  0.789474   \n",
       "268                    0.062500        0.490909  0.289474   \n",
       "..                          ...             ...       ...   \n",
       "109                    0.023077        0.527273  0.473684   \n",
       "516                    0.013462        0.672727  0.526316   \n",
       "305                    0.005769        0.890909  0.710526   \n",
       "167                    0.054808        0.472727  0.210526   \n",
       "329                    0.012500        0.781818  0.815789   \n",
       "\n",
       "     albumin_to_globulin_ratio  class  \n",
       "355                   0.666667      1  \n",
       "407                   0.466667      0  \n",
       "90                    0.320000      0  \n",
       "402                   0.400000      0  \n",
       "268                   0.133333      0  \n",
       "..                         ...    ...  \n",
       "109                   0.400000      1  \n",
       "516                   0.333333      0  \n",
       "305                   0.400000      1  \n",
       "167                   0.113333      0  \n",
       "329                   0.600000      1  \n",
       "\n",
       "[115 rows x 11 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test"
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  {
   "cell_type": "code",
   "execution_count": 61,
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   "outputs": [
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      "text/plain": [
       "          age  is_male  total_bilirubin  direct_ribilubin  \\\n",
       "582  0.403226     True         0.018100          0.017094   \n",
       "453  0.532258     True         0.004525          0.008547   \n",
       "89   0.758065     True         0.153846          0.153846   \n",
       "71   1.000000    False         0.009050          0.008547   \n",
       "124  0.241935     True         0.000000          0.000000   \n",
       "..        ...      ...              ...               ...   \n",
       "236  0.145161     True         0.009050          0.008547   \n",
       "487  0.306452     True         0.004525          0.008547   \n",
       "27   0.338710     True         0.253394          0.247863   \n",
       "307  0.274194     True         0.009050          0.008547   \n",
       "512  0.693548     True         0.018100          0.017094   \n",
       "\n",
       "     alkaline_phosphotase  alamine_aminotransferasi  \\\n",
       "582              0.069175                  0.005528   \n",
       "453              0.074029                  0.015075   \n",
       "89               0.082524                  0.054774   \n",
       "71               0.052184                  0.005025   \n",
       "124              0.045510                  0.013065   \n",
       "..                    ...                       ...   \n",
       "236              0.120146                  0.023618   \n",
       "487              0.105583                  0.046231   \n",
       "27               0.083738                  0.839196   \n",
       "307              0.043689                  0.005528   \n",
       "512              0.056432                  0.006030   \n",
       "\n",
       "     aspartate_aminotransferase  total_proteins   albumin  \\\n",
       "582                    0.004090        0.725490  0.731707   \n",
       "453                    0.003749        0.686275  0.390244   \n",
       "89                     0.115201        0.686275  0.463415   \n",
       "71                     0.005794        0.156863  0.097561   \n",
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       "..                          ...             ...       ...   \n",
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       "307                    0.011929        0.196078  0.219512   \n",
       "512                    0.005453        0.431373  0.292683   \n",
       "\n",
       "     albumin_to_globulin_ratio  class  \n",
       "582                   0.846154      1  \n",
       "453                   0.230769      0  \n",
       "89                    0.307692      0  \n",
       "71                    0.153846      0  \n",
       "124                   0.769231      1  \n",
       "..                         ...    ...  \n",
       "236                   0.384615      1  \n",
       "487                   0.407692      0  \n",
       "27                    0.615385      0  \n",
       "307                   0.461538      0  \n",
       "512                   0.307692      1  \n",
       "\n",
       "[93 rows x 11 columns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "val"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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