Script.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "crerec = pd.read_csv('credit_record.csv');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "apprec = pd.read_csv('application_record.csv');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1048575 entries, 0 to 1048574\n",
      "Data columns (total 3 columns):\n",
      " #   Column          Non-Null Count    Dtype \n",
      "---  ------          --------------    ----- \n",
      " 0   ID              1048575 non-null  int64 \n",
      " 1   MONTHS_BALANCE  1048575 non-null  int64 \n",
      " 2   STATUS          1048575 non-null  object\n",
      "dtypes: int64(2), object(1)\n",
      "memory usage: 24.0+ MB\n"
     ]
    }
   ],
   "source": [
    "crerec.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 438557 entries, 0 to 438556\n",
      "Data columns (total 18 columns):\n",
      " #   Column               Non-Null Count   Dtype  \n",
      "---  ------               --------------   -----  \n",
      " 0   ID                   438557 non-null  int64  \n",
      " 1   CODE_GENDER          438557 non-null  object \n",
      " 2   FLAG_OWN_CAR         438557 non-null  object \n",
      " 3   FLAG_OWN_REALTY      438557 non-null  object \n",
      " 4   CNT_CHILDREN         438557 non-null  int64  \n",
      " 5   AMT_INCOME_TOTAL     438557 non-null  float64\n",
      " 6   NAME_INCOME_TYPE     438557 non-null  object \n",
      " 7   NAME_EDUCATION_TYPE  438557 non-null  object \n",
      " 8   NAME_FAMILY_STATUS   438557 non-null  object \n",
      " 9   NAME_HOUSING_TYPE    438557 non-null  object \n",
      " 10  DAYS_BIRTH           438557 non-null  int64  \n",
      " 11  DAYS_EMPLOYED        438557 non-null  int64  \n",
      " 12  FLAG_MOBIL           438557 non-null  int64  \n",
      " 13  FLAG_WORK_PHONE      438557 non-null  int64  \n",
      " 14  FLAG_PHONE           438557 non-null  int64  \n",
      " 15  FLAG_EMAIL           438557 non-null  int64  \n",
      " 16  OCCUPATION_TYPE      304354 non-null  object \n",
      " 17  CNT_FAM_MEMBERS      438557 non-null  float64\n",
      "dtypes: float64(2), int64(8), object(8)\n",
      "memory usage: 60.2+ MB\n"
     ]
    }
   ],
   "source": [
    "apprec.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "438510"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "apprec['ID'].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "45985"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "crerec['ID'].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ID                          0\n",
       "CODE_GENDER                 0\n",
       "FLAG_OWN_CAR                0\n",
       "FLAG_OWN_REALTY             0\n",
       "CNT_CHILDREN                0\n",
       "AMT_INCOME_TOTAL            0\n",
       "NAME_INCOME_TYPE            0\n",
       "NAME_EDUCATION_TYPE         0\n",
       "NAME_FAMILY_STATUS          0\n",
       "NAME_HOUSING_TYPE           0\n",
       "DAYS_BIRTH                  0\n",
       "DAYS_EMPLOYED               0\n",
       "FLAG_MOBIL                  0\n",
       "FLAG_WORK_PHONE             0\n",
       "FLAG_PHONE                  0\n",
       "FLAG_EMAIL                  0\n",
       "OCCUPATION_TYPE        134203\n",
       "CNT_FAM_MEMBERS             0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "apprec.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df3 = pd.merge(crerec, apprec, on = 'ID')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>ID</th>\n",
       "      <th>MONTHS_BALANCE</th>\n",
       "      <th>STATUS</th>\n",
       "      <th>CODE_GENDER</th>\n",
       "      <th>FLAG_OWN_CAR</th>\n",
       "      <th>FLAG_OWN_REALTY</th>\n",
       "      <th>CNT_CHILDREN</th>\n",
       "      <th>AMT_INCOME_TOTAL</th>\n",
       "      <th>NAME_INCOME_TYPE</th>\n",
       "      <th>NAME_EDUCATION_TYPE</th>\n",
       "      <th>NAME_FAMILY_STATUS</th>\n",
       "      <th>NAME_HOUSING_TYPE</th>\n",
       "      <th>DAYS_BIRTH</th>\n",
       "      <th>DAYS_EMPLOYED</th>\n",
       "      <th>FLAG_MOBIL</th>\n",
       "      <th>FLAG_WORK_PHONE</th>\n",
       "      <th>FLAG_PHONE</th>\n",
       "      <th>FLAG_EMAIL</th>\n",
       "      <th>OCCUPATION_TYPE</th>\n",
       "      <th>CNT_FAM_MEMBERS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5008804</td>\n",
       "      <td>0</td>\n",
       "      <td>C</td>\n",
       "      <td>M</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>427500.0</td>\n",
       "      <td>Working</td>\n",
       "      <td>Higher education</td>\n",
       "      <td>Civil marriage</td>\n",
       "      <td>Rented apartment</td>\n",
       "      <td>-12005</td>\n",
       "      <td>-4542</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5008804</td>\n",
       "      <td>-1</td>\n",
       "      <td>C</td>\n",
       "      <td>M</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>427500.0</td>\n",
       "      <td>Working</td>\n",
       "      <td>Higher education</td>\n",
       "      <td>Civil marriage</td>\n",
       "      <td>Rented apartment</td>\n",
       "      <td>-12005</td>\n",
       "      <td>-4542</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5008804</td>\n",
       "      <td>-2</td>\n",
       "      <td>C</td>\n",
       "      <td>M</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>427500.0</td>\n",
       "      <td>Working</td>\n",
       "      <td>Higher education</td>\n",
       "      <td>Civil marriage</td>\n",
       "      <td>Rented apartment</td>\n",
       "      <td>-12005</td>\n",
       "      <td>-4542</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5008804</td>\n",
       "      <td>-3</td>\n",
       "      <td>C</td>\n",
       "      <td>M</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>427500.0</td>\n",
       "      <td>Working</td>\n",
       "      <td>Higher education</td>\n",
       "      <td>Civil marriage</td>\n",
       "      <td>Rented apartment</td>\n",
       "      <td>-12005</td>\n",
       "      <td>-4542</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5008804</td>\n",
       "      <td>-4</td>\n",
       "      <td>C</td>\n",
       "      <td>M</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>427500.0</td>\n",
       "      <td>Working</td>\n",
       "      <td>Higher education</td>\n",
       "      <td>Civil marriage</td>\n",
       "      <td>Rented apartment</td>\n",
       "      <td>-12005</td>\n",
       "      <td>-4542</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        ID  MONTHS_BALANCE STATUS CODE_GENDER FLAG_OWN_CAR FLAG_OWN_REALTY  \\\n",
       "0  5008804               0      C           M            Y               Y   \n",
       "1  5008804              -1      C           M            Y               Y   \n",
       "2  5008804              -2      C           M            Y               Y   \n",
       "3  5008804              -3      C           M            Y               Y   \n",
       "4  5008804              -4      C           M            Y               Y   \n",
       "\n",
       "   CNT_CHILDREN  AMT_INCOME_TOTAL NAME_INCOME_TYPE NAME_EDUCATION_TYPE  \\\n",
       "0             0          427500.0          Working    Higher education   \n",
       "1             0          427500.0          Working    Higher education   \n",
       "2             0          427500.0          Working    Higher education   \n",
       "3             0          427500.0          Working    Higher education   \n",
       "4             0          427500.0          Working    Higher education   \n",
       "\n",
       "  NAME_FAMILY_STATUS NAME_HOUSING_TYPE  DAYS_BIRTH  DAYS_EMPLOYED  FLAG_MOBIL  \\\n",
       "0     Civil marriage  Rented apartment      -12005          -4542           1   \n",
       "1     Civil marriage  Rented apartment      -12005          -4542           1   \n",
       "2     Civil marriage  Rented apartment      -12005          -4542           1   \n",
       "3     Civil marriage  Rented apartment      -12005          -4542           1   \n",
       "4     Civil marriage  Rented apartment      -12005          -4542           1   \n",
       "\n",
       "   FLAG_WORK_PHONE  FLAG_PHONE  FLAG_EMAIL OCCUPATION_TYPE  CNT_FAM_MEMBERS  \n",
       "0                1           0           0             NaN              2.0  \n",
       "1                1           0           0             NaN              2.0  \n",
       "2                1           0           0             NaN              2.0  \n",
       "3                1           0           0             NaN              2.0  \n",
       "4                1           0           0             NaN              2.0  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "shape(777715, 20)\n"
     ]
    }
   ],
   "source": [
    "print(\"shape\" + str(df3.shape))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "df4 = df3.dropna().drop_duplicates(subset='ID', keep='first')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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>ID</th>\n",
       "      <th>MONTHS_BALANCE</th>\n",
       "      <th>STATUS</th>\n",
       "      <th>CODE_GENDER</th>\n",
       "      <th>FLAG_OWN_CAR</th>\n",
       "      <th>FLAG_OWN_REALTY</th>\n",
       "      <th>CNT_CHILDREN</th>\n",
       "      <th>AMT_INCOME_TOTAL</th>\n",
       "      <th>NAME_INCOME_TYPE</th>\n",
       "      <th>NAME_EDUCATION_TYPE</th>\n",
       "      <th>NAME_FAMILY_STATUS</th>\n",
       "      <th>NAME_HOUSING_TYPE</th>\n",
       "      <th>DAYS_BIRTH</th>\n",
       "      <th>DAYS_EMPLOYED</th>\n",
       "      <th>FLAG_MOBIL</th>\n",
       "      <th>FLAG_WORK_PHONE</th>\n",
       "      <th>FLAG_PHONE</th>\n",
       "      <th>FLAG_EMAIL</th>\n",
       "      <th>OCCUPATION_TYPE</th>\n",
       "      <th>CNT_FAM_MEMBERS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>5008806</td>\n",
       "      <td>0</td>\n",
       "      <td>C</td>\n",
       "      <td>M</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>112500.0</td>\n",
       "      <td>Working</td>\n",
       "      <td>Secondary / secondary special</td>\n",
       "      <td>Married</td>\n",
       "      <td>House / apartment</td>\n",
       "      <td>-21474</td>\n",
       "      <td>-1134</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Security staff</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>5008808</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>F</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>270000.0</td>\n",
       "      <td>Commercial associate</td>\n",
       "      <td>Secondary / secondary special</td>\n",
       "      <td>Single / not married</td>\n",
       "      <td>House / apartment</td>\n",
       "      <td>-19110</td>\n",
       "      <td>-3051</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sales staff</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>5008809</td>\n",
       "      <td>-22</td>\n",
       "      <td>X</td>\n",
       "      <td>F</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>270000.0</td>\n",
       "      <td>Commercial associate</td>\n",
       "      <td>Secondary / secondary special</td>\n",
       "      <td>Single / not married</td>\n",
       "      <td>House / apartment</td>\n",
       "      <td>-19110</td>\n",
       "      <td>-3051</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sales staff</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>5008810</td>\n",
       "      <td>0</td>\n",
       "      <td>C</td>\n",
       "      <td>F</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>270000.0</td>\n",
       "      <td>Commercial associate</td>\n",
       "      <td>Secondary / secondary special</td>\n",
       "      <td>Single / not married</td>\n",
       "      <td>House / apartment</td>\n",
       "      <td>-19110</td>\n",
       "      <td>-3051</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sales staff</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>5008811</td>\n",
       "      <td>0</td>\n",
       "      <td>C</td>\n",
       "      <td>F</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>270000.0</td>\n",
       "      <td>Commercial associate</td>\n",
       "      <td>Secondary / secondary special</td>\n",
       "      <td>Single / not married</td>\n",
       "      <td>House / apartment</td>\n",
       "      <td>-19110</td>\n",
       "      <td>-3051</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sales staff</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         ID  MONTHS_BALANCE STATUS CODE_GENDER FLAG_OWN_CAR FLAG_OWN_REALTY  \\\n",
       "31  5008806               0      C           M            Y               Y   \n",
       "61  5008808               0      0           F            N               Y   \n",
       "66  5008809             -22      X           F            N               Y   \n",
       "71  5008810               0      C           F            N               Y   \n",
       "98  5008811               0      C           F            N               Y   \n",
       "\n",
       "    CNT_CHILDREN  AMT_INCOME_TOTAL      NAME_INCOME_TYPE  \\\n",
       "31             0          112500.0               Working   \n",
       "61             0          270000.0  Commercial associate   \n",
       "66             0          270000.0  Commercial associate   \n",
       "71             0          270000.0  Commercial associate   \n",
       "98             0          270000.0  Commercial associate   \n",
       "\n",
       "              NAME_EDUCATION_TYPE    NAME_FAMILY_STATUS  NAME_HOUSING_TYPE  \\\n",
       "31  Secondary / secondary special               Married  House / apartment   \n",
       "61  Secondary / secondary special  Single / not married  House / apartment   \n",
       "66  Secondary / secondary special  Single / not married  House / apartment   \n",
       "71  Secondary / secondary special  Single / not married  House / apartment   \n",
       "98  Secondary / secondary special  Single / not married  House / apartment   \n",
       "\n",
       "    DAYS_BIRTH  DAYS_EMPLOYED  FLAG_MOBIL  FLAG_WORK_PHONE  FLAG_PHONE  \\\n",
       "31      -21474          -1134           1                0           0   \n",
       "61      -19110          -3051           1                0           1   \n",
       "66      -19110          -3051           1                0           1   \n",
       "71      -19110          -3051           1                0           1   \n",
       "98      -19110          -3051           1                0           1   \n",
       "\n",
       "    FLAG_EMAIL OCCUPATION_TYPE  CNT_FAM_MEMBERS  \n",
       "31           0  Security staff              2.0  \n",
       "61           1     Sales staff              1.0  \n",
       "66           1     Sales staff              1.0  \n",
       "71           1     Sales staff              1.0  \n",
       "98           1     Sales staff              1.0  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "shape - (25134, 20)\n"
     ]
    }
   ],
   "source": [
    "print(\"shape - \" + str(df4.shape))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(19.951999999999998, 24.7]     630\n",
      "(24.7, 29.4]                  3375\n",
      "(29.4, 34.1]                  4267\n",
      "(34.1, 38.8]                  3539\n",
      "(38.8, 43.5]                  4350\n",
      "(43.5, 48.2]                  3566\n",
      "(48.2, 52.9]                  2490\n",
      "(52.9, 57.6]                  1924\n",
      "(57.6, 62.3]                   819\n",
      "(62.3, 67.0]                   174\n",
      "Name: Age, dtype: int64\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df4['Age']=-(df4['DAYS_BIRTH'])//365\n",
    "print(df4['Age'].value_counts(bins=10,normalize=False,sort=False))\n",
    "df4['Age'].plot(kind='hist',bins=20,density=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df4['Employed']=-(df4['DAYS_EMPLOYED'])//365\n",
    "df4[df4['Employed']<0] = np.nan\n",
    "df4['DAYS_EMPLOYED']\n",
    "df4['Employed'].fillna(df4['Employed'].mean(),inplace=False)\n",
    "df4['Employed'].plot(kind='hist',bins=20,density=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Laborers                 6211\n",
       "Core staff               3591\n",
       "Sales staff              3485\n",
       "Managers                 3012\n",
       "Drivers                  2138\n",
       "High skill tech staff    1383\n",
       "Accountants              1241\n",
       "Medicine staff           1207\n",
       "Cooking staff             655\n",
       "Security staff            592\n",
       "Cleaning staff            551\n",
       "Private service staff     344\n",
       "Low-skill Laborers        175\n",
       "Waiters/barmen staff      174\n",
       "Secretaries               151\n",
       "HR staff                   85\n",
       "Realty agents              79\n",
       "IT staff                   60\n",
       "Name: OCCUPATION_TYPE, dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4['OCCUPATION_TYPE'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df4['OCCUPATION_TYPE'].value_counts().sort_values().plot(kind='barh', figsize=(9,12))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "26.65% of people have no loans.\n"
     ]
    }
   ],
   "source": [
    "PNoLoan = (df4.loc[df4['STATUS'] == 'X'].shape[0]/df4.shape[0]) * 100\n",
    "print(str(round(PNoLoan, 2)) + \"% of people have no loans.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "49.01% of customers have paid off there dues.\n"
     ]
    }
   ],
   "source": [
    "PPaidOf = (df4.loc[df4['STATUS'] == 'C'].shape[0]/df4.shape[0]) * 100\n",
    "print(str(round(PPaidOf, 2)) + \"% of customers have paid off there dues.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "defaulters= ['0','1','2','3','4','5']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>ID</th>\n",
       "      <th>MONTHS_BALANCE</th>\n",
       "      <th>STATUS</th>\n",
       "      <th>CODE_GENDER</th>\n",
       "      <th>FLAG_OWN_CAR</th>\n",
       "      <th>FLAG_OWN_REALTY</th>\n",
       "      <th>CNT_CHILDREN</th>\n",
       "      <th>AMT_INCOME_TOTAL</th>\n",
       "      <th>NAME_INCOME_TYPE</th>\n",
       "      <th>NAME_EDUCATION_TYPE</th>\n",
       "      <th>...</th>\n",
       "      <th>DAYS_EMPLOYED</th>\n",
       "      <th>FLAG_MOBIL</th>\n",
       "      <th>FLAG_WORK_PHONE</th>\n",
       "      <th>FLAG_PHONE</th>\n",
       "      <th>FLAG_EMAIL</th>\n",
       "      <th>OCCUPATION_TYPE</th>\n",
       "      <th>CNT_FAM_MEMBERS</th>\n",
       "      <th>Age</th>\n",
       "      <th>Employed</th>\n",
       "      <th>OverDues</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>5008806.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>C</td>\n",
       "      <td>M</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>0.0</td>\n",
       "      <td>112500.0</td>\n",
       "      <td>Working</td>\n",
       "      <td>Secondary / secondary special</td>\n",
       "      <td>...</td>\n",
       "      <td>-1134.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Security staff</td>\n",
       "      <td>2.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>5008808.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>F</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "      <td>0.0</td>\n",
       "      <td>270000.0</td>\n",
       "      <td>Commercial associate</td>\n",
       "      <td>Secondary / secondary special</td>\n",
       "      <td>...</td>\n",
       "      <td>-3051.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Sales staff</td>\n",
       "      <td>1.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>5008809.0</td>\n",
       "      <td>-22.0</td>\n",
       "      <td>X</td>\n",
       "      <td>F</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "      <td>0.0</td>\n",
       "      <td>270000.0</td>\n",
       "      <td>Commercial associate</td>\n",
       "      <td>Secondary / secondary special</td>\n",
       "      <td>...</td>\n",
       "      <td>-3051.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Sales staff</td>\n",
       "      <td>1.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>5008810.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>C</td>\n",
       "      <td>F</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "      <td>0.0</td>\n",
       "      <td>270000.0</td>\n",
       "      <td>Commercial associate</td>\n",
       "      <td>Secondary / secondary special</td>\n",
       "      <td>...</td>\n",
       "      <td>-3051.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Sales staff</td>\n",
       "      <td>1.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>5008811.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>C</td>\n",
       "      <td>F</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "      <td>0.0</td>\n",
       "      <td>270000.0</td>\n",
       "      <td>Commercial associate</td>\n",
       "      <td>Secondary / secondary special</td>\n",
       "      <td>...</td>\n",
       "      <td>-3051.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Sales staff</td>\n",
       "      <td>1.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           ID  MONTHS_BALANCE STATUS CODE_GENDER FLAG_OWN_CAR FLAG_OWN_REALTY  \\\n",
       "31  5008806.0             0.0      C           M            Y               Y   \n",
       "61  5008808.0             0.0      0           F            N               Y   \n",
       "66  5008809.0           -22.0      X           F            N               Y   \n",
       "71  5008810.0             0.0      C           F            N               Y   \n",
       "98  5008811.0             0.0      C           F            N               Y   \n",
       "\n",
       "    CNT_CHILDREN  AMT_INCOME_TOTAL      NAME_INCOME_TYPE  \\\n",
       "31           0.0          112500.0               Working   \n",
       "61           0.0          270000.0  Commercial associate   \n",
       "66           0.0          270000.0  Commercial associate   \n",
       "71           0.0          270000.0  Commercial associate   \n",
       "98           0.0          270000.0  Commercial associate   \n",
       "\n",
       "              NAME_EDUCATION_TYPE  ... DAYS_EMPLOYED FLAG_MOBIL  \\\n",
       "31  Secondary / secondary special  ...       -1134.0        1.0   \n",
       "61  Secondary / secondary special  ...       -3051.0        1.0   \n",
       "66  Secondary / secondary special  ...       -3051.0        1.0   \n",
       "71  Secondary / secondary special  ...       -3051.0        1.0   \n",
       "98  Secondary / secondary special  ...       -3051.0        1.0   \n",
       "\n",
       "    FLAG_WORK_PHONE  FLAG_PHONE  FLAG_EMAIL  OCCUPATION_TYPE  CNT_FAM_MEMBERS  \\\n",
       "31              0.0         0.0         0.0   Security staff              2.0   \n",
       "61              0.0         1.0         1.0      Sales staff              1.0   \n",
       "66              0.0         1.0         1.0      Sales staff              1.0   \n",
       "71              0.0         1.0         1.0      Sales staff              1.0   \n",
       "98              0.0         1.0         1.0      Sales staff              1.0   \n",
       "\n",
       "     Age Employed  OverDues  \n",
       "31  58.0      3.0         0  \n",
       "61  52.0      8.0         1  \n",
       "66  52.0      8.0         0  \n",
       "71  52.0      8.0         0  \n",
       "98  52.0      8.0         0  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4['OverDues'] = np.where(df4.STATUS.isin(defaulters), 1, 0)\n",
    "df4.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pandas.core.groupby.generic.DataFrameGroupBy object at 0x7f8593c76190>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4.groupby('OCCUPATION_TYPE')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Number of Customers')"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "df4[df4['OverDues']==1]['AMT_INCOME_TOTAL'].hist(alpha=0.7,color='Red', bins=6,label='Defaulters')\n",
    "df4[df4['OverDues']==0]['AMT_INCOME_TOTAL'].hist(alpha=0.3,color='Blue', bins=6,label='PaidOff')\n",
    "                                                    \n",
    "plt.title('Customers around the income groups')                                                    \n",
    "plt.legend()\n",
    "plt.xlabel('Annual Income')\n",
    "plt.ylabel('Number of Customers')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    19018\n",
       "1     6116\n",
       "Name: OverDues, dtype: int64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4['OverDues'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([<matplotlib.axis.XTick at 0x7f859434a0d0>,\n",
       "  <matplotlib.axis.XTick at 0x7f859434a0a0>],\n",
       " [Text(0.0, 0, 'Female'), Text(1.0, 0, 'Male')])"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.crosstab(df4.CODE_GENDER,df4.OverDues).plot(kind='bar')\n",
    "plt.title('Gender vs Defaulters')\n",
    "plt.xlabel('Gender')\n",
    "plt.ylabel('Number of Customers')\n",
    "plt.legend(labels = [\"PaidOff\", \"Defaulters\"])\n",
    "plt.xticks(np.linspace(0, 1, 2), ['Female','Male'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f85943caf70>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.crosstab(df4.NAME_INCOME_TYPE, df4.OverDues).plot(kind='bar', figsize=(12,6))\n",
    "plt.title('Customers across various Income Types')\n",
    "plt.xlabel('Income Type')\n",
    "plt.ylabel('Number of Customers')\n",
    "plt.legend(labels = [\"PaidOff\", \"Defaulters\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "df7 = pd.get_dummies(df3, columns=['CODE_GENDER','FLAG_OWN_CAR','FLAG_OWN_REALTY','NAME_INCOME_TYPE','NAME_EDUCATION_TYPE','NAME_FAMILY_STATUS','NAME_HOUSING_TYPE'], drop_first = False)\n",
    "df7['OverDues'] = np.where(df7.STATUS.isin(defaulters), 1, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,10))\n",
    "\n",
    "corr = df7[['OverDues', 'DAYS_BIRTH', 'DAYS_EMPLOYED', 'AMT_INCOME_TOTAL', 'FLAG_PHONE', 'CNT_FAM_MEMBERS']].corr()\n",
    "sns.heatmap(corr, \n",
    "        xticklabels=corr.columns,\n",
    "        yticklabels=corr.columns,\n",
    "        annot=True, cmap=plt.cm.Reds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x7f859445d370>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 42 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(df7[['CNT_CHILDREN', 'AMT_INCOME_TOTAL', 'DAYS_BIRTH', 'DAYS_EMPLOYED', 'CNT_FAM_MEMBERS', 'OverDues']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "df5 = df4.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "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>ID</th>\n",
       "      <th>MONTHS_BALANCE</th>\n",
       "      <th>STATUS</th>\n",
       "      <th>CNT_CHILDREN</th>\n",
       "      <th>AMT_INCOME_TOTAL</th>\n",
       "      <th>DAYS_BIRTH</th>\n",
       "      <th>DAYS_EMPLOYED</th>\n",
       "      <th>FLAG_MOBIL</th>\n",
       "      <th>FLAG_WORK_PHONE</th>\n",
       "      <th>FLAG_PHONE</th>\n",
       "      <th>...</th>\n",
       "      <th>NAME_FAMILY_STATUS_Separated</th>\n",
       "      <th>NAME_FAMILY_STATUS_Single / not married</th>\n",
       "      <th>NAME_FAMILY_STATUS_Widow</th>\n",
       "      <th>NAME_HOUSING_TYPE_Co-op apartment</th>\n",
       "      <th>NAME_HOUSING_TYPE_House / apartment</th>\n",
       "      <th>NAME_HOUSING_TYPE_Municipal apartment</th>\n",
       "      <th>NAME_HOUSING_TYPE_Office apartment</th>\n",
       "      <th>NAME_HOUSING_TYPE_Rented apartment</th>\n",
       "      <th>NAME_HOUSING_TYPE_With parents</th>\n",
       "      <th>OverDues</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5008804</td>\n",
       "      <td>0</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>427500.0</td>\n",
       "      <td>-12005</td>\n",
       "      <td>-4542</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5008804</td>\n",
       "      <td>-1</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>427500.0</td>\n",
       "      <td>-12005</td>\n",
       "      <td>-4542</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5008804</td>\n",
       "      <td>-2</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>427500.0</td>\n",
       "      <td>-12005</td>\n",
       "      <td>-4542</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5008804</td>\n",
       "      <td>-3</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>427500.0</td>\n",
       "      <td>-12005</td>\n",
       "      <td>-4542</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5008804</td>\n",
       "      <td>-4</td>\n",
       "      <td>C</td>\n",
       "      <td>0</td>\n",
       "      <td>427500.0</td>\n",
       "      <td>-12005</td>\n",
       "      <td>-4542</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        ID  MONTHS_BALANCE STATUS  CNT_CHILDREN  AMT_INCOME_TOTAL  DAYS_BIRTH  \\\n",
       "0  5008804               0      C             0          427500.0      -12005   \n",
       "1  5008804              -1      C             0          427500.0      -12005   \n",
       "2  5008804              -2      C             0          427500.0      -12005   \n",
       "3  5008804              -3      C             0          427500.0      -12005   \n",
       "4  5008804              -4      C             0          427500.0      -12005   \n",
       "\n",
       "   DAYS_EMPLOYED  FLAG_MOBIL  FLAG_WORK_PHONE  FLAG_PHONE  ...  \\\n",
       "0          -4542           1                1           0  ...   \n",
       "1          -4542           1                1           0  ...   \n",
       "2          -4542           1                1           0  ...   \n",
       "3          -4542           1                1           0  ...   \n",
       "4          -4542           1                1           0  ...   \n",
       "\n",
       "   NAME_FAMILY_STATUS_Separated NAME_FAMILY_STATUS_Single / not married  \\\n",
       "0                             0                                       0   \n",
       "1                             0                                       0   \n",
       "2                             0                                       0   \n",
       "3                             0                                       0   \n",
       "4                             0                                       0   \n",
       "\n",
       "   NAME_FAMILY_STATUS_Widow  NAME_HOUSING_TYPE_Co-op apartment  \\\n",
       "0                         0                                  0   \n",
       "1                         0                                  0   \n",
       "2                         0                                  0   \n",
       "3                         0                                  0   \n",
       "4                         0                                  0   \n",
       "\n",
       "   NAME_HOUSING_TYPE_House / apartment  NAME_HOUSING_TYPE_Municipal apartment  \\\n",
       "0                                    0                                      0   \n",
       "1                                    0                                      0   \n",
       "2                                    0                                      0   \n",
       "3                                    0                                      0   \n",
       "4                                    0                                      0   \n",
       "\n",
       "   NAME_HOUSING_TYPE_Office apartment  NAME_HOUSING_TYPE_Rented apartment  \\\n",
       "0                                   0                                   1   \n",
       "1                                   0                                   1   \n",
       "2                                   0                                   1   \n",
       "3                                   0                                   1   \n",
       "4                                   0                                   1   \n",
       "\n",
       "   NAME_HOUSING_TYPE_With parents  OverDues  \n",
       "0                               0         0  \n",
       "1                               0         0  \n",
       "2                               0         0  \n",
       "3                               0         0  \n",
       "4                               0         0  \n",
       "\n",
       "[5 rows x 41 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df7.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['ID', 'MONTHS_BALANCE', 'STATUS', 'CNT_CHILDREN', 'AMT_INCOME_TOTAL',\n",
       "       'DAYS_BIRTH', 'DAYS_EMPLOYED', 'FLAG_MOBIL', 'FLAG_WORK_PHONE',\n",
       "       'FLAG_PHONE', 'FLAG_EMAIL', 'OCCUPATION_TYPE', 'CNT_FAM_MEMBERS',\n",
       "       'CODE_GENDER_F', 'CODE_GENDER_M', 'FLAG_OWN_CAR_N', 'FLAG_OWN_CAR_Y',\n",
       "       'FLAG_OWN_REALTY_N', 'FLAG_OWN_REALTY_Y',\n",
       "       'NAME_INCOME_TYPE_Commercial associate', 'NAME_INCOME_TYPE_Pensioner',\n",
       "       'NAME_INCOME_TYPE_State servant', 'NAME_INCOME_TYPE_Student',\n",
       "       'NAME_INCOME_TYPE_Working', 'NAME_EDUCATION_TYPE_Academic degree',\n",
       "       'NAME_EDUCATION_TYPE_Higher education',\n",
       "       'NAME_EDUCATION_TYPE_Incomplete higher',\n",
       "       'NAME_EDUCATION_TYPE_Lower secondary',\n",
       "       'NAME_EDUCATION_TYPE_Secondary / secondary special',\n",
       "       'NAME_FAMILY_STATUS_Civil marriage', 'NAME_FAMILY_STATUS_Married',\n",
       "       'NAME_FAMILY_STATUS_Separated',\n",
       "       'NAME_FAMILY_STATUS_Single / not married', 'NAME_FAMILY_STATUS_Widow',\n",
       "       'NAME_HOUSING_TYPE_Co-op apartment',\n",
       "       'NAME_HOUSING_TYPE_House / apartment',\n",
       "       'NAME_HOUSING_TYPE_Municipal apartment',\n",
       "       'NAME_HOUSING_TYPE_Office apartment',\n",
       "       'NAME_HOUSING_TYPE_Rented apartment', 'NAME_HOUSING_TYPE_With parents',\n",
       "       'OverDues'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df7.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "Features = ['CNT_CHILDREN', 'AMT_INCOME_TOTAL',\n",
    "       'DAYS_BIRTH', 'DAYS_EMPLOYED', 'FLAG_MOBIL', 'FLAG_WORK_PHONE',\n",
    "       'FLAG_PHONE', 'FLAG_EMAIL', 'CNT_FAM_MEMBERS',\n",
    "       'CODE_GENDER_F', 'CODE_GENDER_M', 'FLAG_OWN_CAR_N', 'FLAG_OWN_CAR_Y',\n",
    "       'FLAG_OWN_REALTY_N', 'FLAG_OWN_REALTY_Y',\n",
    "       'NAME_INCOME_TYPE_Commercial associate', 'NAME_INCOME_TYPE_Pensioner',\n",
    "       'NAME_INCOME_TYPE_State servant', 'NAME_INCOME_TYPE_Student',\n",
    "       'NAME_INCOME_TYPE_Working', 'NAME_EDUCATION_TYPE_Academic degree',\n",
    "       'NAME_EDUCATION_TYPE_Higher education',\n",
    "       'NAME_EDUCATION_TYPE_Incomplete higher',\n",
    "       'NAME_EDUCATION_TYPE_Lower secondary',\n",
    "       'NAME_EDUCATION_TYPE_Secondary / secondary special',\n",
    "       'NAME_FAMILY_STATUS_Civil marriage', 'NAME_FAMILY_STATUS_Married',\n",
    "       'NAME_FAMILY_STATUS_Separated',\n",
    "       'NAME_FAMILY_STATUS_Single / not married', 'NAME_FAMILY_STATUS_Widow',\n",
    "       'NAME_HOUSING_TYPE_Co-op apartment',\n",
    "       'NAME_HOUSING_TYPE_House / apartment',\n",
    "       'NAME_HOUSING_TYPE_Municipal apartment',\n",
    "       'NAME_HOUSING_TYPE_Office apartment',\n",
    "       'NAME_HOUSING_TYPE_Rented apartment', 'NAME_HOUSING_TYPE_With parents']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import model_selection\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "train, test = train_test_split(df7, test_size = 0.3, random_state=21)\n",
    "train = train.reset_index(drop=True)\n",
    "test = test.reset_index(drop=True)\n",
    "\n",
    "features_train = train[Features]\n",
    "label_train = train['OverDues']\n",
    "features_test = test[Features]\n",
    "label_test = test['OverDues']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "clf = RandomForestClassifier()\n",
    "\n",
    "clf.fit(features_train,label_train)\n",
    "\n",
    "pred_train = clf.predict(features_train)\n",
    "pred_test = clf.predict(features_test)\n",
    "\n",
    "from sklearn.metrics import accuracy_score\n",
    "RFCaccuracy_train = (accuracy_score(pred_train,label_train)) * 100\n",
    "RFCaccuracy_test = (accuracy_score(pred_test,label_test)) * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Accuracy is 72.3903%\n",
      "Test Accuracy is 71.439%\n"
     ]
    }
   ],
   "source": [
    "print('Training Accuracy is ' + str(round(RFCaccuracy_train, 4)) + '%')\n",
    "print('Test Accuracy is ' +  str(round(RFCaccuracy_test, 4)) + '%')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "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>PRED</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ACTUAL</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>122141</td>\n",
       "      <td>20456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>46181</td>\n",
       "      <td>44537</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "PRED         0      1\n",
       "ACTUAL               \n",
       "0       122141  20456\n",
       "1        46181  44537"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(label_test,pd.Series(pred_test),rownames=['ACTUAL'],colnames=['PRED'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy Score\n",
      "0.7143904163898592 \n",
      "\n",
      "Precision Score\n",
      "[0.72563895 0.68525841] \n",
      "\n",
      "Confusion Matrix\n",
      "               Non Defaulter  Defaulter\n",
      "Non Defaulter         122141      20456\n",
      "Defaulter              46181      44537 \n",
      "\n",
      "Classification Report\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.73      0.86      0.79    142597\n",
      "           1       0.69      0.49      0.57     90718\n",
      "\n",
      "    accuracy                           0.71    233315\n",
      "   macro avg       0.71      0.67      0.68    233315\n",
      "weighted avg       0.71      0.71      0.70    233315\n",
      " \n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import accuracy_score, f1_score, precision_score, recall_score\n",
    "\n",
    "print('Accuracy Score')\n",
    "print(accuracy_score(label_test, pred_test),'\\n')\n",
    "\n",
    "print('Precision Score')\n",
    "print(precision_score(label_test, pred_test,average = None),'\\n')\n",
    "\n",
    "print('Confusion Matrix')\n",
    "array = confusion_matrix(label_test, pred_test)\n",
    "columns = ['Non Defaulter','Defaulter'] \n",
    "print(pd.DataFrame(array,columns = columns, index = columns),'\\n')\n",
    "\n",
    "print('Classification Report')\n",
    "print(classification_report(label_test, pred_test),'\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier\n",
    "\n",
    "tree = DecisionTreeClassifier(random_state=0)\n",
    "tree.fit(features_train, label_train)\n",
    "\n",
    "pred_train=tree.predict(features_train)\n",
    "\n",
    "pred_test=tree.predict(features_test)\n",
    "\n",
    "from sklearn.metrics import accuracy_score\n",
    "DTCaccuracy_train = (accuracy_score(pred_train,label_train)) * 100\n",
    "DTCaccuracy_test = (accuracy_score(pred_test,label_test)) * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Accuracy is 72.3929%\n",
      "Test Accuracy is 71.439%\n"
     ]
    }
   ],
   "source": [
    "print('Training Accuracy is ' + str(round(DTCaccuracy_train, 4)) + '%')\n",
    "print('Test Accuracy is ' +  str(round(DTCaccuracy_test, 4)) + '%')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "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>PRED</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ACTUAL</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>122660</td>\n",
       "      <td>19937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>46700</td>\n",
       "      <td>44018</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "PRED         0      1\n",
       "ACTUAL               \n",
       "0       122660  19937\n",
       "1        46700  44018"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(label_test,pd.Series(pred_test),rownames=['ACTUAL'],colnames=['PRED'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy Score\n",
      "0.7143904163898592 \n",
      "\n",
      "Precision Score\n",
      "[0.72425602 0.68826519] \n",
      "\n",
      "Confusion Matrix\n",
      "               Non Defaulter  Defaulter\n",
      "Non Defaulter         122660      19937\n",
      "Defaulter              46700      44018 \n",
      "\n",
      "Classification Report\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.72      0.86      0.79    142597\n",
      "           1       0.69      0.49      0.57     90718\n",
      "\n",
      "    accuracy                           0.71    233315\n",
      "   macro avg       0.71      0.67      0.68    233315\n",
      "weighted avg       0.71      0.71      0.70    233315\n",
      " \n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import accuracy_score, f1_score, precision_score, recall_score\n",
    "\n",
    "print('Accuracy Score')\n",
    "print(accuracy_score(label_test, pred_test),'\\n')\n",
    "\n",
    "print('Precision Score')\n",
    "print(precision_score(label_test, pred_test,average = None),'\\n')\n",
    "\n",
    "print('Confusion Matrix')\n",
    "array = confusion_matrix(label_test, pred_test)\n",
    "columns = ['Non Defaulter','Defaulter']  \n",
    "print(pd.DataFrame(array,columns = columns, index = columns),'\\n')\n",
    "\n",
    "print('Classification Report')\n",
    "print(classification_report(label_test, pred_test),'\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Decision Tree Classifier\\nFeature Importances'}, ylabel='features'>"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x1584 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfz=pd.DataFrame({'features':features_train.columns,'importances':tree.feature_importances_})\n",
    "dfz.sort_values('importances',inplace=True)\n",
    "dfz.plot(kind='barh', title = 'Decision Tree Classifier\\nFeature Importances', y='importances',x='features',color='brown', figsize=(12,22))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "Pkl_Filename1 = \"modelrcf.pkl\"  \n",
    "\n",
    "with open(Pkl_Filename1, 'wb') as file:  \n",
    "    pickle.dump(clf, file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "Pkl_Filename2 = \"modeldtc.pkl\"  \n",
    "\n",
    "with open(Pkl_Filename2, 'wb') as file:  \n",
    "    pickle.dump(tree, file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}