{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "24495c28",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5c74b8f4",
   "metadata": {},
   "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>person_age</th>\n",
       "      <th>person_gender</th>\n",
       "      <th>person_education</th>\n",
       "      <th>person_income</th>\n",
       "      <th>person_emp_exp</th>\n",
       "      <th>person_home_ownership</th>\n",
       "      <th>loan_amnt</th>\n",
       "      <th>loan_intent</th>\n",
       "      <th>loan_int_rate</th>\n",
       "      <th>loan_percent_income</th>\n",
       "      <th>cb_person_cred_hist_length</th>\n",
       "      <th>credit_score</th>\n",
       "      <th>previous_loan_defaults_on_file</th>\n",
       "      <th>loan_status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>22.0</td>\n",
       "      <td>female</td>\n",
       "      <td>Master</td>\n",
       "      <td>71948.0</td>\n",
       "      <td>0</td>\n",
       "      <td>RENT</td>\n",
       "      <td>35000.0</td>\n",
       "      <td>PERSONAL</td>\n",
       "      <td>16.02</td>\n",
       "      <td>0.49</td>\n",
       "      <td>3.0</td>\n",
       "      <td>561</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>21.0</td>\n",
       "      <td>female</td>\n",
       "      <td>High School</td>\n",
       "      <td>12282.0</td>\n",
       "      <td>0</td>\n",
       "      <td>OWN</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>EDUCATION</td>\n",
       "      <td>11.14</td>\n",
       "      <td>0.08</td>\n",
       "      <td>2.0</td>\n",
       "      <td>504</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>25.0</td>\n",
       "      <td>female</td>\n",
       "      <td>High School</td>\n",
       "      <td>12438.0</td>\n",
       "      <td>3</td>\n",
       "      <td>MORTGAGE</td>\n",
       "      <td>5500.0</td>\n",
       "      <td>MEDICAL</td>\n",
       "      <td>12.87</td>\n",
       "      <td>0.44</td>\n",
       "      <td>3.0</td>\n",
       "      <td>635</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.0</td>\n",
       "      <td>female</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>79753.0</td>\n",
       "      <td>0</td>\n",
       "      <td>RENT</td>\n",
       "      <td>35000.0</td>\n",
       "      <td>MEDICAL</td>\n",
       "      <td>15.23</td>\n",
       "      <td>0.44</td>\n",
       "      <td>2.0</td>\n",
       "      <td>675</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.0</td>\n",
       "      <td>male</td>\n",
       "      <td>Master</td>\n",
       "      <td>66135.0</td>\n",
       "      <td>1</td>\n",
       "      <td>RENT</td>\n",
       "      <td>35000.0</td>\n",
       "      <td>MEDICAL</td>\n",
       "      <td>14.27</td>\n",
       "      <td>0.53</td>\n",
       "      <td>4.0</td>\n",
       "      <td>586</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   person_age person_gender person_education  person_income  person_emp_exp  \\\n",
       "0        22.0        female           Master        71948.0               0   \n",
       "1        21.0        female      High School        12282.0               0   \n",
       "2        25.0        female      High School        12438.0               3   \n",
       "3        23.0        female         Bachelor        79753.0               0   \n",
       "4        24.0          male           Master        66135.0               1   \n",
       "\n",
       "  person_home_ownership  loan_amnt loan_intent  loan_int_rate  \\\n",
       "0                  RENT    35000.0    PERSONAL          16.02   \n",
       "1                   OWN     1000.0   EDUCATION          11.14   \n",
       "2              MORTGAGE     5500.0     MEDICAL          12.87   \n",
       "3                  RENT    35000.0     MEDICAL          15.23   \n",
       "4                  RENT    35000.0     MEDICAL          14.27   \n",
       "\n",
       "   loan_percent_income  cb_person_cred_hist_length  credit_score  \\\n",
       "0                 0.49                         3.0           561   \n",
       "1                 0.08                         2.0           504   \n",
       "2                 0.44                         3.0           635   \n",
       "3                 0.44                         2.0           675   \n",
       "4                 0.53                         4.0           586   \n",
       "\n",
       "  previous_loan_defaults_on_file  loan_status  \n",
       "0                             No            1  \n",
       "1                            Yes            0  \n",
       "2                             No            1  \n",
       "3                             No            1  \n",
       "4                             No            1  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"loan_data.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "dd244811",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 45000 entries, 0 to 44999\n",
      "Data columns (total 14 columns):\n",
      " #   Column                          Non-Null Count  Dtype  \n",
      "---  ------                          --------------  -----  \n",
      " 0   person_age                      45000 non-null  float64\n",
      " 1   person_gender                   45000 non-null  object \n",
      " 2   person_education                45000 non-null  object \n",
      " 3   person_income                   45000 non-null  float64\n",
      " 4   person_emp_exp                  45000 non-null  int64  \n",
      " 5   person_home_ownership           45000 non-null  object \n",
      " 6   loan_amnt                       45000 non-null  float64\n",
      " 7   loan_intent                     45000 non-null  object \n",
      " 8   loan_int_rate                   45000 non-null  float64\n",
      " 9   loan_percent_income             45000 non-null  float64\n",
      " 10  cb_person_cred_hist_length      45000 non-null  float64\n",
      " 11  credit_score                    45000 non-null  int64  \n",
      " 12  previous_loan_defaults_on_file  45000 non-null  object \n",
      " 13  loan_status                     45000 non-null  int64  \n",
      "dtypes: float64(6), int64(3), object(5)\n",
      "memory usage: 4.8+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9a78850c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(45000, 14)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "55ed562c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['person_age', 'person_gender', 'person_education', 'person_income',\n",
       "       'person_emp_exp', 'person_home_ownership', 'loan_amnt', 'loan_intent',\n",
       "       'loan_int_rate', 'loan_percent_income', 'cb_person_cred_hist_length',\n",
       "       'credit_score', 'previous_loan_defaults_on_file', 'loan_status'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "281ae58b",
   "metadata": {},
   "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>person_age</th>\n",
       "      <th>person_income</th>\n",
       "      <th>person_emp_exp</th>\n",
       "      <th>loan_amnt</th>\n",
       "      <th>loan_int_rate</th>\n",
       "      <th>loan_percent_income</th>\n",
       "      <th>cb_person_cred_hist_length</th>\n",
       "      <th>credit_score</th>\n",
       "      <th>loan_status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>45000.000000</td>\n",
       "      <td>4.500000e+04</td>\n",
       "      <td>45000.000000</td>\n",
       "      <td>45000.000000</td>\n",
       "      <td>45000.000000</td>\n",
       "      <td>45000.000000</td>\n",
       "      <td>45000.000000</td>\n",
       "      <td>45000.000000</td>\n",
       "      <td>45000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>27.764178</td>\n",
       "      <td>8.031905e+04</td>\n",
       "      <td>5.410333</td>\n",
       "      <td>9583.157556</td>\n",
       "      <td>11.006606</td>\n",
       "      <td>0.139725</td>\n",
       "      <td>5.867489</td>\n",
       "      <td>632.608756</td>\n",
       "      <td>0.222222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>6.045108</td>\n",
       "      <td>8.042250e+04</td>\n",
       "      <td>6.063532</td>\n",
       "      <td>6314.886691</td>\n",
       "      <td>2.978808</td>\n",
       "      <td>0.087212</td>\n",
       "      <td>3.879702</td>\n",
       "      <td>50.435865</td>\n",
       "      <td>0.415744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>20.000000</td>\n",
       "      <td>8.000000e+03</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>500.000000</td>\n",
       "      <td>5.420000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>390.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>24.000000</td>\n",
       "      <td>4.720400e+04</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5000.000000</td>\n",
       "      <td>8.590000</td>\n",
       "      <td>0.070000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>601.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>26.000000</td>\n",
       "      <td>6.704800e+04</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>8000.000000</td>\n",
       "      <td>11.010000</td>\n",
       "      <td>0.120000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>640.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>30.000000</td>\n",
       "      <td>9.578925e+04</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>12237.250000</td>\n",
       "      <td>12.990000</td>\n",
       "      <td>0.190000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>670.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>144.000000</td>\n",
       "      <td>7.200766e+06</td>\n",
       "      <td>125.000000</td>\n",
       "      <td>35000.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>0.660000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>850.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         person_age  person_income  person_emp_exp     loan_amnt  \\\n",
       "count  45000.000000   4.500000e+04    45000.000000  45000.000000   \n",
       "mean      27.764178   8.031905e+04        5.410333   9583.157556   \n",
       "std        6.045108   8.042250e+04        6.063532   6314.886691   \n",
       "min       20.000000   8.000000e+03        0.000000    500.000000   \n",
       "25%       24.000000   4.720400e+04        1.000000   5000.000000   \n",
       "50%       26.000000   6.704800e+04        4.000000   8000.000000   \n",
       "75%       30.000000   9.578925e+04        8.000000  12237.250000   \n",
       "max      144.000000   7.200766e+06      125.000000  35000.000000   \n",
       "\n",
       "       loan_int_rate  loan_percent_income  cb_person_cred_hist_length  \\\n",
       "count   45000.000000         45000.000000                45000.000000   \n",
       "mean       11.006606             0.139725                    5.867489   \n",
       "std         2.978808             0.087212                    3.879702   \n",
       "min         5.420000             0.000000                    2.000000   \n",
       "25%         8.590000             0.070000                    3.000000   \n",
       "50%        11.010000             0.120000                    4.000000   \n",
       "75%        12.990000             0.190000                    8.000000   \n",
       "max        20.000000             0.660000                   30.000000   \n",
       "\n",
       "       credit_score   loan_status  \n",
       "count  45000.000000  45000.000000  \n",
       "mean     632.608756      0.222222  \n",
       "std       50.435865      0.415744  \n",
       "min      390.000000      0.000000  \n",
       "25%      601.000000      0.000000  \n",
       "50%      640.000000      0.000000  \n",
       "75%      670.000000      0.000000  \n",
       "max      850.000000      1.000000  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "27ecf097",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "person_age                        0\n",
       "person_gender                     0\n",
       "person_education                  0\n",
       "person_income                     0\n",
       "person_emp_exp                    0\n",
       "person_home_ownership             0\n",
       "loan_amnt                         0\n",
       "loan_intent                       0\n",
       "loan_int_rate                     0\n",
       "loan_percent_income               0\n",
       "cb_person_cred_hist_length        0\n",
       "credit_score                      0\n",
       "previous_loan_defaults_on_file    0\n",
       "loan_status                       0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "71d87189",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.int64(0)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1ea8ca48",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Master', 'High School', 'Bachelor', 'Associate', 'Doctorate'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"person_education\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "032e1e88",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['RENT', 'OWN', 'MORTGAGE', 'OTHER'], dtype=object)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"person_home_ownership\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "73f08741",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['PERSONAL', 'EDUCATION', 'MEDICAL', 'VENTURE', 'HOMEIMPROVEMENT',\n",
       "       'DEBTCONSOLIDATION'], dtype=object)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"loan_intent\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "db9e999d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['No', 'Yes'], dtype=object)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"previous_loan_defaults_on_file\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "101b2fd2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 0])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"loan_status\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0994cc08",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "person_age                     2.548154\n",
       "person_income                 34.137583\n",
       "person_emp_exp                 2.594917\n",
       "loan_amnt                      1.179731\n",
       "loan_int_rate                  0.213784\n",
       "loan_percent_income            1.034512\n",
       "cb_person_cred_hist_length     1.631720\n",
       "credit_score                  -0.610261\n",
       "loan_status                    1.336351\n",
       "dtype: float64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.select_dtypes(\"number\").skew()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "83d3b6ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df.select_dtypes(\"number\").corr(),annot=True,fmt=\".2f\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "1fa33671",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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c6WDx2NhYrxrtLtR9pwYAANRstXzdJbd69Wp5++23zVpNzhgkHcWuLUDaBafnBwwYII0aNTJjmqZPn25m1nXp0sXU6hIFGo5GjRplliLQa8yePdtc22kJ0nWddFbcjBkz5KmnnjIBbe3atWZGnUO72pKSkqRbt27So0cPM1tPlz4YM2aMjz4dAADgT3wampYtW+YuK+DptddekyeffNK0AL333ntugNExQ0OHDjWhyKHdatq1N2nSJNMqVK9ePRN+5s+f79ZoC5YGJA1cixcvNl2Ay5cvNzPoHMOGDTNLFOj6Thq8dJkDXY6g7OBwAABQM/nVOk1VGes0Ab7DOk0Aatw6TQAAAP6K0AQAAGCB0AQAAGCB0AQAAEBoAgAAqBy0NAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAPh7aEpLS5Pu3bvLnXfeKU2bNpXBgwdLXl6eV82lS5dk8uTJ0qhRI6lfv74MHTpUCgoKvGqOHTsmAwcOlLp165rrpKSkyJUrV7xqduzYIV27dpWQkBBp3769rFix4pr7Wbp0qbRp00Zq164tcXFxkpWVdYveOQAAqGp8Gpp27txpAtFHH30k27Ztk+LiYunXr59cuHDBrZk+fbps2LBB1q1bZ+pPnDghQ4YMcc9fvXrVBKaioiLZvXu3rFy50gSiOXPmuDVHjx41NX369JGcnByZNm2ajBs3TrZs2eLWrFmzRpKTk2Xu3Lmyd+9eiY6OlsTERCksLLyNnwgAAPBXAaWlpaXiJ06dOmVaijQc9erVS86ePStNmjSR1atXy49//GNTk5ubK506dZLMzEzp2bOnvPvuuzJo0CATppo1a2Zq0tPTZebMmeZ6wcHB5udNmzbJgQMH3NcaPny4nDlzRjZv3mz2tWVJW72WLFli9ktKSiQiIkKmTp0qs2bNuuG9nzt3TsLCwsw9h4aG3qJPSCQ25fVbdm2gqspeONrXtwCgirqZv98Vamnq27evCRzlvbCeqyi9YdWwYUPzmJ2dbVqfEhIS3JqOHTtKq1atTGhS+hgVFeUGJqUtRHovBw8edGs8r+HUONfQVip9Lc+awMBAs+/UlHX58mXzGp4bAACovioUmnR8kAaNsnT80V//+tcK3Yi27Gi32QMPPCCdO3c2x/Lz801LUYMGDbxqNSDpOafGMzA5551z16vRoHPx4kX5+uuvTTdfeTXONcobj6XJ1Nm0VQoAAFRftW6meN++fe7Pn3/+uVeg0NChXV0/+tGPKnQjOrZJu88++OADqQpSU1PNGCiHBjCCEwAA1ddNhaaYmBgJCAgwW3ndcHXq1JHf/va3N30TU6ZMkY0bN8quXbukZcuW7vHw8HDToqVdgZ6tTTp7Ts85NWVnuTmz6zxrys64033tu9R7DgoKMlt5Nc41ytJZeLoBAICa4aa653QW2pEjR0THjmtQ0X1n+/vf/25aW5566inr6+l1NDCtX79etm/fLm3btvU6HxsbK3fccYdkZGS4x3RJAl1iID4+3uzr4/79+71muelMPA1EkZGRbo3nNZwa5xraBaiv5Vmj3YW679QAAICa7aZamlq3bu0GisqgXXI6M+7tt982azU53X06RkhbgPRx7NixphtMB4drENLZbBpkdOac0iUKNByNGjVKFixYYK4xe/Zsc22nJWjixIlmVtyMGTNMqNOAtnbtWjOjzqGvkZSUJN26dZMePXrIokWLzNIHY8aMqZT3CgAAalBo8nTo0CF5//33TQtP2RDluUbS9Sxbtsw89u7d2+v4a6+9Jk8++aT5+cUXXzQz2XRRS52xprPeXn75ZbdWu9W0a2/SpEkmTNWrV8+En/nz57s12oKlAUnXfFq8eLHpAly+fLm5lmPYsGFmiQK9dw1e2hWpY7TKDg4HAAA1U4XWafr9739vQkrjxo3NmB8d4+ReMCDALA5Z07BOE+A7rNME4Hb8/a5QS9NvfvMb+c///E+zaCQAAEBNUKF1mk6fPi0/+clPKv9uAAAAqlNo0sC0devWyr8bAAAAP1Wh7rn27dvLr371K/NFu/oVJrosgKef//znlXV/AAAAVTc0vfLKK1K/fn3zxbq6edKB4IQmAABQ3VQoNOlilgAAADVJhcY0AQAA1DQVamm60VelvPrqqxW9HwAAgOoTmnTJAU/FxcVy4MAB88W65X2RLwAAQI0MTfoFu2XpV6noKuHt2rWrjPsCAAConmOa9Pvh9Etv9bviAAAAqptKHQh+5MgRuXLlSmVeEgAAoOp2z2mLkif9zt+TJ0/Kpk2bJCkpqbLuDQAAoGqHpk8//fSarrkmTZrICy+8cMOZdQAAADUmNL3//vuVfycAAADVLTQ5Tp06JXl5eebnDh06mNYmAACA6qhCA8EvXLhguuGaN28uvXr1MluLFi1k7Nix8v3331f+XQIAAFTF0KQDwfWLejds2GAWtNTt7bffNseefvrpyr9LAACAqtg99+c//1neeOMN6d27t3tswIABUqdOHfnpT38qy5Ytq8x7BAAAqJotTdoF16xZs2uON23alO45AABQLVUoNMXHx8vcuXPl0qVL7rGLFy/KvHnzzDkAAIDqpkLdc4sWLZJHH31UWrZsKdHR0ebYZ599JiEhIbJ169bKvkcAAICqGZqioqLk0KFDsmrVKsnNzTXHRowYISNHjjTjmgAAAKqbCoWmtLQ0M6Zp/PjxXsdfffVVs3bTzJkzK+v+AAAAqu6Ypt/97nfSsWPHa47fd999kp6eXhn3BQAAUPVDU35+vlnYsixdEVy/uBcAAKC6qVBoioiIkA8//PCa43pMVwYHAACobio0pknHMk2bNk2Ki4ulb9++5lhGRobMmDGDFcEBAEC1VKHQlJKSIt9884387Gc/k6KiInOsdu3aZgB4ampqZd8jAABA1QxNAQEB8l//9V/yq1/9Sr744guzzMA999xj1mkCAACojioUmhz169eX7t27V97dAAAAVKeB4AAAADUNoQkAAMACoQkAAMACoQkAAMACoQkAAMACoQkAAMACoQkAAMACoQkAAMDfQ9OuXbvkscceM1/yq6uMv/XWW17nn3zySXPcc3v00Ue9ar799lsZOXKkhIaGSoMGDWTs2LHy3XffedXs27dPHnroIfNVL/plwwsWLLjmXtatWycdO3Y0NVFRUfLOO+/concNAACqIp+GpgsXLkh0dLQsXbr0B2s0JJ08edLd/vjHP3qd18B08OBB2bZtm2zcuNEEsQkTJrjnz507J/369ZPWrVtLdna2LFy4UJ577jl55ZVX3Jrdu3fLiBEjTOD69NNPZfDgwWY7cODALXrnAACgqgkoLS0tFT+grUjr1683YcWzpenMmTPXtEA59HvvIiMj5ZNPPpFu3bqZY5s3b5YBAwbIV199ZVqwli1bJr/85S8lPz9fgoODTc2sWbPMNXNzc83+sGHDTIDT0OXo2bOnxMTESHp6utX9azgLCwuTs2fPmlavWyU25fVbdm2gqspeONrXtwCgirqZv99+P6Zpx44d0rRpU+nQoYNMmjRJvvnmG/dcZmam6ZJzApNKSEiQwMBA+fjjj92aXr16uYFJJSYmSl5enpw+fdqt0ed50ho9DgAA8E9/Ye+tpl1zQ4YMkbZt28qRI0fk2Weflf79+5swExQUZFqPNFB5qlWrljRs2NCcU/qoz/fUrFkz99xdd91lHp1jnjXONcpz+fJls3kmVQAAUH35dWgaPny4+7MOzu7SpYu0a9fOtD49/PDDPr23tLQ0mTdvnk/vAQAA3D5+3z3n6e6775bGjRvL4cOHzX54eLgUFhZ61Vy5csXMqNNzTk1BQYFXjbN/oxrnfHlSU1NN/6ezHT9+vJLeJQAA8EdVKjTp4G4d09S8eXOzHx8fbwaK66w4x/bt26WkpETi4uLcGp1RV1xc7NboTDsdI6Vdc05NRkaG12tpjR7/ISEhIWbAmOcGAACqL5+GJl1PKScnx2zq6NGj5udjx46ZcykpKfLRRx/Jl19+aULN448/Lu3btzeDtFWnTp3MuKfx48dLVlaWfPjhhzJlyhTTracz59QTTzxhBoHrcgK6NMGaNWtk8eLFkpyc7N7HL37xCzPr7oUXXjAz6nRJgj179phrAQAA+Dw0aTD5l3/5F7MpDTL685w5c8xAb12U8l//9V/l3nvvNaEnNjZW/vrXv5pWHseqVavMopQ6xkmXGnjwwQe91mDSaYRbt241gUyf//TTT5vre67ldP/998vq1avN83TdqDfeeMMsSdC5c+fb/IkAAAB/5TfrNFV1rNME+A7rNAGoqGq1ThMAAIA/IDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAABYIDQBAAD4e2jatWuXPPbYY9KiRQsJCAiQt956y+t8aWmpzJkzR5o3by516tSRhIQEOXTokFfNt99+KyNHjpTQ0FBp0KCBjB07Vr777juvmn379slDDz0ktWvXloiICFmwYME197Ju3Trp2LGjqYmKipJ33nnnFr1rAABQFfk0NF24cEGio6Nl6dKl5Z7XcPPSSy9Jenq6fPzxx1KvXj1JTEyUS5cuuTUamA4ePCjbtm2TjRs3miA2YcIE9/y5c+ekX79+0rp1a8nOzpaFCxfKc889J6+88opbs3v3bhkxYoQJXJ9++qkMHjzYbAcOHLjFnwAAAKgqAkq1OccPaEvT+vXrTVhRelvaAvX000/LM888Y46dPXtWmjVrJitWrJDhw4fLF198IZGRkfLJJ59It27dTM3mzZtlwIAB8tVXX5nnL1u2TH75y19Kfn6+BAcHm5pZs2aZVq3c3FyzP2zYMBPgNHQ5evbsKTExMSaw2dBwFhYWZu5RW71uldiU12/ZtYGqKnvhaF/fAoAq6mb+fvvtmKajR4+aoKNdcg59U3FxcZKZmWn29VG75JzApLQ+MDDQtEw5Nb169XIDk9LWqry8PDl9+rRb4/k6To3zOuW5fPmy+aA9NwAAUH3VEj+lgUlpy5In3XfO6WPTpk29zteqVUsaNmzoVdO2bdtrruGcu+uuu8zj9V6nPGlpaTJv3rx/6j0CgCdakgH/bkn225Ymf5eammqa8pzt+PHjvr4lAABQE0NTeHi4eSwoKPA6rvvOOX0sLCz0On/lyhUzo86zprxreL7GD9U458sTEhJi+j49NwAAUH35bWjSLjUNLRkZGe4xHTekY5Xi4+PNvj6eOXPGzIpzbN++XUpKSszYJ6dGZ9QVFxe7NTrTrkOHDqZrzqnxfB2nxnkdAAAAn4YmXU8pJyfHbM7gb/352LFjZjbdtGnT5De/+Y385S9/kf3798vo0aPNjDhnhl2nTp3k0UcflfHjx0tWVpZ8+OGHMmXKFDOzTuvUE088YQaB63ICujTBmjVrZPHixZKcnOzexy9+8Qsz6+6FF14wM+p0SYI9e/aYawEAAPh8ILgGkz59+rj7TpBJSkoyywrMmDHDLAWg6y5pi9KDDz5owo0uQOlYtWqVCTcPP/ywmTU3dOhQs7aT54y7rVu3yuTJkyU2NlYaN25sFsz0XMvp/vvvl9WrV8vs2bPl2WeflXvuuccsSdC5c+fb9lkAAAD/5jfrNFV1rNME+I4/za75ZzB7Drj9v9/VYp0mAAAAf0JoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAsEBoAgAAqOqh6bnnnpOAgACvrWPHju75S5cuyeTJk6VRo0ZSv359GTp0qBQUFHhd49ixYzJw4ECpW7euNG3aVFJSUuTKlSteNTt27JCuXbtKSEiItG/fXlasWHHb3iMAAKga/Do0qfvuu09Onjzpbh988IF7bvr06bJhwwZZt26d7Ny5U06cOCFDhgxxz1+9etUEpqKiItm9e7esXLnSBKI5c+a4NUePHjU1ffr0kZycHJk2bZqMGzdOtmzZctvfKwAA8F+1xM/VqlVLwsPDrzl+9uxZ+cMf/iCrV6+Wvn37mmOvvfaadOrUST766CPp2bOnbN26VT7//HN57733pFmzZhITEyO//vWvZebMmaYVKzg4WNLT06Vt27bywgsvmGvo8zWYvfjii5KYmHjb3y8AAPBPft/SdOjQIWnRooXcfffdMnLkSNPdprKzs6W4uFgSEhLcWu26a9WqlWRmZpp9fYyKijKByaFB6Ny5c3Lw4EG3xvMaTo1zjR9y+fJlcx3PDQAAVF9+HZri4uJMd9rmzZtl2bJlpivtoYcekvPnz0t+fr5pKWrQoIHXczQg6Tmlj56ByTnvnLtejYagixcv/uC9paWlSVhYmLtFRERU2vsGAAD+x6+75/r37+/+3KVLFxOiWrduLWvXrpU6der49N5SU1MlOTnZ3deQRXACAKD68uuWprK0Venee++Vw4cPm3FOOsD7zJkzXjU6e84ZA6WPZWfTOfs3qgkNDb1uMNOZdlrjuQEAgOqrSoWm7777To4cOSLNmzeX2NhYueOOOyQjI8M9n5eXZ8Y8xcfHm3193L9/vxQWFro127ZtMwEnMjLSrfG8hlPjXAMAAMDvQ9MzzzxjlhL48ssvzZIB//Zv/yZBQUEyYsQIM45o7Nixpovs/fffNwPDx4wZY8KOzpxT/fr1M+Fo1KhR8tlnn5llBGbPnm3WdtKWIjVx4kT529/+JjNmzJDc3Fx5+eWXTfefLmcAAABQJcY0ffXVVyYgffPNN9KkSRN58MEHzXIC+rPSZQECAwPNopY6m01nvWnocWjA2rhxo0yaNMmEqXr16klSUpLMnz/frdHlBjZt2mRC0uLFi6Vly5ayfPlylhsAAABeAkpLS0u9D6EidCC4tn7p+lG3cnxTbMrrt+zaQFWVvXC0VAf8fgO3//f7Zv5++3X3HAAAgL8gNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNAEAAFggNJWxdOlSadOmjdSuXVvi4uIkKyvL5nMEAADVHKHJw5o1ayQ5OVnmzp0re/fulejoaElMTJTCwkLf/QsBAAC/QGjy8N///d8yfvx4GTNmjERGRkp6errUrVtXXn31Vd/9CwEAAL9AaPqHoqIiyc7OloSEhP//4QQGmv3MzExf/fsAAAA/UcvXN+Avvv76a7l69ao0a9bM67ju5+bmXlN/+fJlsznOnj1rHs+dO3dL7/Pq5Yu39PpAVXSrf+9uF36/gdv/++1cv7S09Ia1hKYKSktLk3nz5l1zPCIioqKXBFBBYb+dyGcHVFNht+n3+/z58xIWFnbdGkLTPzRu3FiCgoKkoKDA6wPS/fDw8Gs+uNTUVDNo3FFSUiLffvutNGrUSAICAirnXxB+S/9nogH5+PHjEhoa6uvbAVCJ+P2uWUpLS01gatGixQ1rCU3/EBwcLLGxsZKRkSGDBw92g5DuT5ky5ZoPLiQkxGyeGjRoUDn/gqgyNDARmoDqid/vmiPsBi1MDkKTB205SkpKkm7dukmPHj1k0aJFcuHCBTObDgAA1GyEJg/Dhg2TU6dOyZw5cyQ/P19iYmJk8+bN1wwOBwAANQ+hqQztiiuvOw7wpF2zughq2S5aAFUfv9/4IQGlNnPsAAAAajgWtwQAALBAaAIAALBAaAIAALBAaAIqYOnSpdKmTRupXbu2xMXFSVZWFp8jUMXt2rVLHnvsMbPIoS5S/NZbb/n6luBnCE3ATVqzZo1Z00tnz+3du1eio6MlMTFRCgsL+SyBKkzX5dPfZ/1PEVAeZs8BN0lblrp37y5LlixxV47Xr1SZOnWqzJo1i88TqAa0pWn9+vXuN0QAipYm4CYUFRVJdna2JCQkuMcCAwPNfmZmJp8lAFRjhCbgJnz99ddy9erVa1aJ131dRR4AUH0RmgAAACwQmoCb0LhxYwkKCpKCggKv47ofHh7OZwkA1RihCbgJwcHBEhsbKxkZGe4xHQiu+/Hx8XyWAFCN8YW9wE3S5QaSkpKkW7du0qNHD1m0aJGZqjxmzBg+S6AK++677+Tw4cPu/tGjRyUnJ0caNmworVq18um9wT+w5ABQAbrcwMKFC83g75iYGHnppZfMUgQAqq4dO3ZInz59rjmu/0lasWKFT+4J/oXQBAAAYIExTQAAABYITQAAABYITQAAABYITQAAABYITQAAABYITQAAABYITQAAABYITQAAABYITQD8Su/evWXatGm+vg0AuAahCQAqqE2bNua7B28WwRComghNAAAAFghNAPzW6dOnZfTo0XLXXXdJ3bp1pX///nLo0CH3/DfffCMjRoyQH/3oR+Z8VFSU/PGPf7ymVefnP/+5zJgxw3xbfXh4uDz33HNWr19aWmpq9RvuQ0JCpEWLFuZaznX/7//+T6ZPny4BAQFms7mnJ598Unbu3CmLFy92n/fll1+aL4Rt0KCB1+u/9dZb7nXVZ599Zr5Q9s4775TQ0FCJjY2VPXv2VPDTBXCzCE0A/JYGDA0Ff/nLXyQzM9OEmAEDBkhxcbE5f+nSJRMcNm3aJAcOHJAJEybIqFGjJCsry+s6K1eulHr16snHH38sCxYskPnz58u2bdtu+Pp//vOf5cUXX5Tf/e53JqxpiNEQpN58801p2bKludbJkyfNZnNPGpbi4+Nl/Pjx7vMiIiKsPo+RI0ea1/zkk08kOztbZs2aJXfcccdNf64AKqZWBZ8HALeUhhQNSx9++KHcf//95tiqVatMwNDw8pOf/MS05jzzzDPuc6ZOnSpbtmyRtWvXSo8ePdzjXbp0kblz55qf77nnHlmyZIlkZGTII488ct17OHbsmGmZSkhIMOFEW5yc62qrVVBQkGn10RrHje4pLCxMgoODTSuU5/Ns6P2kpKRIx44d3fcC4PahpQmAX/riiy+kVq1aEhcX5x5r1KiRdOjQwZxTV69elV//+tem9UdDTP369U1A0XDhSUOTp+bNm0thYeEN70GD2cWLF+Xuu+82LUPr16+XK1euXPc5tvdUEcnJyTJu3DgT4p5//nk5cuTIP31NAPYITQCqrIULF5rurpkzZ8r7778vOTk5kpiYKEVFRV51ZbuwdJxQSUnJDa+vrVp5eXny8ssvS506deRnP/uZ9OrVy+0e/GfuqazAwEDT/eip7Ovo+KqDBw/KwIEDZfv27RIZGWmCHIDbg9AEwC916tTJtOroOCSHDrLWEKNhQWnX3eOPPy7//u//LtHR0aZF6H//938r9T40LD322GPy0ksvyY4dO8zYqv3795tz2s2mLUuebO6pvOc1adJEzp8/LxcuXHCPaeAq69577zWDz7du3SpDhgyR1157rVLfL4AfRmgC4Jd0vI6GD+0W++CDD8zMMQ0iOmZIjzs1OqB79+7dpsvuP/7jP6SgoKDS7kFntP3hD38wA7r/9re/yf/8z/+YENW6dWt3naZdu3bJ3//+d/n666+t70mfp2FQZ83p87TVS7shdZzTs88+a7rdVq9ebV7fod2EU6ZMMcFNZ+1pONMB4RouAdwehCYAfktbUXQm2qBBg8yMM+2+euedd9zuttmzZ0vXrl1N95cuAaADqwcPHlxpr69LAPz+97+XBx54wIyLeu+992TDhg1mbJXSmXMafNq1a2daimzvSQeK6yBybTHT5+l4Jx3/pKFM35+zTIHn0ghary1tugSDtjb99Kc/NUswzJs3r9LeL4DrCygt24kOAACAa9DSBAAAYIHQBKDG0nWfdEmA8rb77rvP17cHwM/QPQegxtLZaj80cFzHTTkDvgFAEZoAAAAs0D0HAABggdAEAABggdAEAABggdAEAABggdAEAABggdAEAABggdAEAABggdAEAAAgN/b/ABCH3ekfbEofAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(df,x=\"loan_status\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "06b97c90",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'loan_status'"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_cols = df.select_dtypes(\"number\").columns.tolist()\n",
    "cat_cols = df.drop(num_cols,axis=1).columns.tolist()\n",
    "\n",
    "num_cols.pop(-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "4c047086",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in cat_cols:\n",
    "    sns.countplot(df,x=i)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b5f41d60",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in num_cols:\n",
    "    sns.histplot(df,x=i,bins=25,kde=True)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "93c0da81",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in cat_cols:\n",
    "    sns.boxplot(df,x=i,y=\"loan_status\")\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "e3780e86",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler,OneHotEncoder,PowerTransformer\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.compose import ColumnTransformer\n",
    "from sklearn.model_selection import train_test_split,RandomizedSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "26b22486",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df.drop(\"loan_status\",axis=1)\n",
    "y = df[\"loan_status\"]\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.30, random_state=42,stratify=y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "cf446a25",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['person_age', 'person_income', 'person_emp_exp', 'loan_amnt', 'loan_int_rate', 'loan_percent_income', 'cb_person_cred_hist_length', 'credit_score']\n",
      "['person_gender', 'person_education', 'person_home_ownership', 'loan_intent', 'previous_loan_defaults_on_file']\n"
     ]
    }
   ],
   "source": [
    "print(num_cols)\n",
    "print(cat_cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "e5897150",
   "metadata": {},
   "outputs": [],
   "source": [
    "num_pipeline = Pipeline(steps=[\n",
    "    (\"skew\",PowerTransformer(\"yeo-johnson\")),\n",
    "    (\"scaler\",StandardScaler())\n",
    "])\n",
    "\n",
    "cat_pipeline = Pipeline(steps=[\n",
    "    (\"encode\",OneHotEncoder(handle_unknown=\"ignore\"))\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "0e0274db",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: #000;\n",
       "  --sklearn-color-text-muted: #666;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: flex;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "  align-items: start;\n",
       "  justify-content: space-between;\n",
       "  gap: 0.5em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label .caption {\n",
       "  font-size: 0.6rem;\n",
       "  font-weight: lighter;\n",
       "  color: var(--sklearn-color-text-muted);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  display: none;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  overflow: visible;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 0.5em;\n",
       "  text-align: center;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".estimator-table summary {\n",
       "    padding: .5rem;\n",
       "    font-family: monospace;\n",
       "    cursor: pointer;\n",
       "}\n",
       "\n",
       ".estimator-table details[open] {\n",
       "    padding-left: 0.1rem;\n",
       "    padding-right: 0.1rem;\n",
       "    padding-bottom: 0.3rem;\n",
       "}\n",
       "\n",
       ".estimator-table .parameters-table {\n",
       "    margin-left: auto !important;\n",
       "    margin-right: auto !important;\n",
       "}\n",
       "\n",
       ".estimator-table .parameters-table tr:nth-child(odd) {\n",
       "    background-color: #fff;\n",
       "}\n",
       "\n",
       ".estimator-table .parameters-table tr:nth-child(even) {\n",
       "    background-color: #f6f6f6;\n",
       "}\n",
       "\n",
       ".estimator-table .parameters-table tr:hover {\n",
       "    background-color: #e0e0e0;\n",
       "}\n",
       "\n",
       ".estimator-table table td {\n",
       "    border: 1px solid rgba(106, 105, 104, 0.232);\n",
       "}\n",
       "\n",
       ".user-set td {\n",
       "    color:rgb(255, 94, 0);\n",
       "    text-align: left;\n",
       "}\n",
       "\n",
       ".user-set td.value pre {\n",
       "    color:rgb(255, 94, 0) !important;\n",
       "    background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".default td {\n",
       "    color: black;\n",
       "    text-align: left;\n",
       "}\n",
       "\n",
       ".user-set td i,\n",
       ".default td i {\n",
       "    color: black;\n",
       "}\n",
       "\n",
       ".copy-paste-icon {\n",
       "    background-image: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCA0NDggNTEyIj48IS0tIUZvbnQgQXdlc29tZSBGcmVlIDYuNy4yIGJ5IEBmb250YXdlc29tZSAtIGh0dHBzOi8vZm9udGF3ZXNvbWUuY29tIExpY2Vuc2UgLSBodHRwczovL2ZvbnRhd2Vzb21lLmNvbS9saWNlbnNlL2ZyZWUgQ29weXJpZ2h0IDIwMjUgRm9udGljb25zLCBJbmMuLS0+PHBhdGggZD0iTTIwOCAwTDMzMi4xIDBjMTIuNyAwIDI0LjkgNS4xIDMzLjkgMTQuMWw2Ny45IDY3LjljOSA5IDE0LjEgMjEuMiAxNC4xIDMzLjlMNDQ4IDMzNmMwIDI2LjUtMjEuNSA0OC00OCA0OGwtMTkyIDBjLTI2LjUgMC00OC0yMS41LTQ4LTQ4bDAtMjg4YzAtMjYuNSAyMS41LTQ4IDQ4LTQ4ek00OCAxMjhsODAgMCAwIDY0LTY0IDAgMCAyNTYgMTkyIDAgMC0zMiA2NCAwIDAgNDhjMCAyNi41LTIxLjUgNDgtNDggNDhMNDggNTEyYy0yNi41IDAtNDgtMjEuNS00OC00OEwwIDE3NmMwLTI2LjUgMjEuNS00OCA0OC00OHoiLz48L3N2Zz4=);\n",
       "    background-repeat: no-repeat;\n",
       "    background-size: 14px 14px;\n",
       "    background-position: 0;\n",
       "    display: inline-block;\n",
       "    width: 14px;\n",
       "    height: 14px;\n",
       "    cursor: pointer;\n",
       "}\n",
       "</style><body><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>ColumnTransformer(transformers=[(&#x27;num&#x27;,\n",
       "                                 Pipeline(steps=[(&#x27;skew&#x27;, PowerTransformer()),\n",
       "                                                 (&#x27;scaler&#x27;, StandardScaler())]),\n",
       "                                 [&#x27;person_age&#x27;, &#x27;person_income&#x27;,\n",
       "                                  &#x27;person_emp_exp&#x27;, &#x27;loan_amnt&#x27;,\n",
       "                                  &#x27;loan_int_rate&#x27;, &#x27;loan_percent_income&#x27;,\n",
       "                                  &#x27;cb_person_cred_hist_length&#x27;,\n",
       "                                  &#x27;credit_score&#x27;]),\n",
       "                                (&#x27;cat&#x27;,\n",
       "                                 Pipeline(steps=[(&#x27;encode&#x27;,\n",
       "                                                  OneHotEncoder(handle_unknown=&#x27;ignore&#x27;))]),\n",
       "                                 [&#x27;person_gender&#x27;, &#x27;person_education&#x27;,\n",
       "                                  &#x27;person_home_ownership&#x27;, &#x27;loan_intent&#x27;,\n",
       "                                  &#x27;previous_loan_defaults_on_file&#x27;])])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>ColumnTransformer</div></div><div><a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.7/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for ColumnTransformer</span></a><span class=\"sk-estimator-doc-link \">i<span>Not fitted</span></span></div></label><div class=\"sk-toggleable__content \" data-param-prefix=\"\">\n",
       "        <div class=\"estimator-table\">\n",
       "            <details>\n",
       "                <summary>Parameters</summary>\n",
       "                <table class=\"parameters-table\">\n",
       "                  <tbody>\n",
       "                    \n",
       "        <tr class=\"user-set\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('transformers',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">transformers&nbsp;</td>\n",
       "            <td class=\"value\">[(&#x27;num&#x27;, ...), (&#x27;cat&#x27;, ...)]</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('remainder',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">remainder&nbsp;</td>\n",
       "            <td class=\"value\">&#x27;drop&#x27;</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('sparse_threshold',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">sparse_threshold&nbsp;</td>\n",
       "            <td class=\"value\">0.3</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('n_jobs',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">n_jobs&nbsp;</td>\n",
       "            <td class=\"value\">None</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('transformer_weights',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">transformer_weights&nbsp;</td>\n",
       "            <td class=\"value\">None</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('verbose',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">verbose&nbsp;</td>\n",
       "            <td class=\"value\">False</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('verbose_feature_names_out',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">verbose_feature_names_out&nbsp;</td>\n",
       "            <td class=\"value\">True</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('force_int_remainder_cols',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">force_int_remainder_cols&nbsp;</td>\n",
       "            <td class=\"value\">&#x27;deprecated&#x27;</td>\n",
       "        </tr>\n",
       "    \n",
       "                  </tbody>\n",
       "                </table>\n",
       "            </details>\n",
       "        </div>\n",
       "    </div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>num</div></div></label><div class=\"sk-toggleable__content \" data-param-prefix=\"num__\"><pre>[&#x27;person_age&#x27;, &#x27;person_income&#x27;, &#x27;person_emp_exp&#x27;, &#x27;loan_amnt&#x27;, &#x27;loan_int_rate&#x27;, &#x27;loan_percent_income&#x27;, &#x27;cb_person_cred_hist_length&#x27;, &#x27;credit_score&#x27;]</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>PowerTransformer</div></div><div><a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.7/modules/generated/sklearn.preprocessing.PowerTransformer.html\">?<span>Documentation for PowerTransformer</span></a></div></label><div class=\"sk-toggleable__content \" data-param-prefix=\"num__skew__\">\n",
       "        <div class=\"estimator-table\">\n",
       "            <details>\n",
       "                <summary>Parameters</summary>\n",
       "                <table class=\"parameters-table\">\n",
       "                  <tbody>\n",
       "                    \n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('method',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">method&nbsp;</td>\n",
       "            <td class=\"value\">&#x27;yeo-johnson&#x27;</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('standardize',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">standardize&nbsp;</td>\n",
       "            <td class=\"value\">True</td>\n",
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       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('copy',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">copy&nbsp;</td>\n",
       "            <td class=\"value\">True</td>\n",
       "        </tr>\n",
       "    \n",
       "                  </tbody>\n",
       "                </table>\n",
       "            </details>\n",
       "        </div>\n",
       "    </div></div></div><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>StandardScaler</div></div><div><a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.7/modules/generated/sklearn.preprocessing.StandardScaler.html\">?<span>Documentation for StandardScaler</span></a></div></label><div class=\"sk-toggleable__content \" data-param-prefix=\"num__scaler__\">\n",
       "        <div class=\"estimator-table\">\n",
       "            <details>\n",
       "                <summary>Parameters</summary>\n",
       "                <table class=\"parameters-table\">\n",
       "                  <tbody>\n",
       "                    \n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('copy',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">copy&nbsp;</td>\n",
       "            <td class=\"value\">True</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('with_mean',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">with_mean&nbsp;</td>\n",
       "            <td class=\"value\">True</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('with_std',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">with_std&nbsp;</td>\n",
       "            <td class=\"value\">True</td>\n",
       "        </tr>\n",
       "    \n",
       "                  </tbody>\n",
       "                </table>\n",
       "            </details>\n",
       "        </div>\n",
       "    </div></div></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>cat</div></div></label><div class=\"sk-toggleable__content \" data-param-prefix=\"cat__\"><pre>[&#x27;person_gender&#x27;, &#x27;person_education&#x27;, &#x27;person_home_ownership&#x27;, &#x27;loan_intent&#x27;, &#x27;previous_loan_defaults_on_file&#x27;]</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" ><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>OneHotEncoder</div></div><div><a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.7/modules/generated/sklearn.preprocessing.OneHotEncoder.html\">?<span>Documentation for OneHotEncoder</span></a></div></label><div class=\"sk-toggleable__content \" data-param-prefix=\"cat__encode__\">\n",
       "        <div class=\"estimator-table\">\n",
       "            <details>\n",
       "                <summary>Parameters</summary>\n",
       "                <table class=\"parameters-table\">\n",
       "                  <tbody>\n",
       "                    \n",
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       "            <td class=\"param\">dtype&nbsp;</td>\n",
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      ],
      "text/plain": [
       "ColumnTransformer(transformers=[('num',\n",
       "                                 Pipeline(steps=[('skew', PowerTransformer()),\n",
       "                                                 ('scaler', StandardScaler())]),\n",
       "                                 ['person_age', 'person_income',\n",
       "                                  'person_emp_exp', 'loan_amnt',\n",
       "                                  'loan_int_rate', 'loan_percent_income',\n",
       "                                  'cb_person_cred_hist_length',\n",
       "                                  'credit_score']),\n",
       "                                ('cat',\n",
       "                                 Pipeline(steps=[('encode',\n",
       "                                                  OneHotEncoder(handle_unknown='ignore'))]),\n",
       "                                 ['person_gender', 'person_education',\n",
       "                                  'person_home_ownership', 'loan_intent',\n",
       "                                  'previous_loan_defaults_on_file'])])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preprocessing = ColumnTransformer(transformers=[\n",
    "    (\"num\",num_pipeline,num_cols),\n",
    "    (\"cat\",cat_pipeline,cat_cols)\n",
    "])\n",
    "\n",
    "preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "1a470a63",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train_pre = preprocessing.fit_transform(X_train)\n",
    "X_test_pre = preprocessing.transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "2b3abee0",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.ensemble import RandomForestClassifier, GradientBoostingClassifier, ExtraTreesClassifier ,AdaBoostClassifier\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from xgboost import XGBClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "69e09238",
   "metadata": {},
   "outputs": [],
   "source": [
    "results = []\n",
    "models = {\n",
    "    \"logistic_regression\": LogisticRegression(class_weight=\"balanced\"),\n",
    "    \"Decision_tree\": DecisionTreeClassifier(class_weight=\"balanced\"),\n",
    "    \"knn\": KNeighborsClassifier(),\n",
    "    \"AdaBoostClassifier\": AdaBoostClassifier(),\n",
    "    \"XGBClassifier\": XGBClassifier(),\n",
    "    \"GradientBoostingClassifier\": GradientBoostingClassifier(),\n",
    "    \"RandomForestClassifier\": RandomForestClassifier(class_weight=\"balanced\")\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "b62eca70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>accuracy_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>logistic_regression</td>\n",
       "      <td>0.858519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Decision_tree</td>\n",
       "      <td>0.901852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>knn</td>\n",
       "      <td>0.897333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AdaBoostClassifier</td>\n",
       "      <td>0.909333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>XGBClassifier</td>\n",
       "      <td>0.931852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.923185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>RandomForestClassifier</td>\n",
       "      <td>0.926889</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Name  accuracy_score\n",
       "0         logistic_regression        0.858519\n",
       "1               Decision_tree        0.901852\n",
       "2                         knn        0.897333\n",
       "3          AdaBoostClassifier        0.909333\n",
       "4               XGBClassifier        0.931852\n",
       "5  GradientBoostingClassifier        0.923185\n",
       "6      RandomForestClassifier        0.926889"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for name,model in models.items():\n",
    "    model.fit(X_train_pre,y_train)\n",
    "    y_pred = model.predict(X_test_pre)\n",
    "    acc = accuracy_score(y_test,y_pred)\n",
    "    results.append({\n",
    "        \"Name\":name,\n",
    "        \"accuracy_score\":acc,\n",
    "    })\n",
    "\n",
    "results_df = pd.DataFrame(results)\n",
    "results_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "b765ef1c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9268888888888889\n",
      "0.9318518518518518\n"
     ]
    }
   ],
   "source": [
    "model_rt = models[\"RandomForestClassifier\"]\n",
    "model_xgb = models[\"XGBClassifier\"]\n",
    "\n",
    "y_pred = model_rt.predict(X_test_pre)\n",
    "acc = accuracy_score(y_test,y_pred)\n",
    "\n",
    "print(acc)\n",
    "\n",
    "y_pred = model_xgb.predict(X_test_pre)\n",
    "acc = accuracy_score(y_test,y_pred)\n",
    "\n",
    "print(acc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "ff7000b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['columns.pkl']"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from joblib import dump\n",
    "\n",
    "dump(model_xgb,\"model_xgb_b.pkl\")\n",
    "dump(model_xgb,\"model_ft_nb.pkl\")\n",
    "\n",
    "dump(preprocessing,\"preprocessing.pkl\")\n",
    "dump(X.columns.tolist(),\"columns.pkl\")"
   ]
  }
 ],
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