Loan_prediction_model.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = pd.read_csv(\"loan train.csv\") #reading the dataset\n",
    "test = pd.read_csv(\"loan test.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# EXPLORING THE DATA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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",
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       "    }\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>Loan_ID</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Married</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>Education</th>\n",
       "      <th>Self_Employed</th>\n",
       "      <th>ApplicantIncome</th>\n",
       "      <th>CoapplicantIncome</th>\n",
       "      <th>LoanAmount</th>\n",
       "      <th>Loan_Amount_Term</th>\n",
       "      <th>Credit_History</th>\n",
       "      <th>Property_Area</th>\n",
       "      <th>Loan_Status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>LP001002</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>No</td>\n",
       "      <td>5849</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>LP001003</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>No</td>\n",
       "      <td>4583</td>\n",
       "      <td>1508.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Rural</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>LP001005</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LP001006</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0</td>\n",
       "      <td>Not Graduate</td>\n",
       "      <td>No</td>\n",
       "      <td>2583</td>\n",
       "      <td>2358.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>LP001008</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>No</td>\n",
       "      <td>6000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Loan_ID Gender Married Dependents     Education Self_Employed  \\\n",
       "0  LP001002   Male      No          0      Graduate            No   \n",
       "1  LP001003   Male     Yes          1      Graduate            No   \n",
       "2  LP001005   Male     Yes          0      Graduate           Yes   \n",
       "3  LP001006   Male     Yes          0  Not Graduate            No   \n",
       "4  LP001008   Male      No          0      Graduate            No   \n",
       "\n",
       "   ApplicantIncome  CoapplicantIncome  LoanAmount  Loan_Amount_Term  \\\n",
       "0             5849                0.0         NaN             360.0   \n",
       "1             4583             1508.0       128.0             360.0   \n",
       "2             3000                0.0        66.0             360.0   \n",
       "3             2583             2358.0       120.0             360.0   \n",
       "4             6000                0.0       141.0             360.0   \n",
       "\n",
       "   Credit_History Property_Area Loan_Status  \n",
       "0             1.0         Urban           Y  \n",
       "1             1.0         Rural           N  \n",
       "2             1.0         Urban           Y  \n",
       "3             1.0         Urban           Y  \n",
       "4             1.0         Urban           Y  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.head() #checking the first few rows and columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>Loan_ID</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Married</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>Education</th>\n",
       "      <th>Self_Employed</th>\n",
       "      <th>ApplicantIncome</th>\n",
       "      <th>CoapplicantIncome</th>\n",
       "      <th>LoanAmount</th>\n",
       "      <th>Loan_Amount_Term</th>\n",
       "      <th>Credit_History</th>\n",
       "      <th>Property_Area</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>LP001015</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>No</td>\n",
       "      <td>5720</td>\n",
       "      <td>0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>LP001022</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>No</td>\n",
       "      <td>3076</td>\n",
       "      <td>1500</td>\n",
       "      <td>126.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>LP001031</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>2</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>No</td>\n",
       "      <td>5000</td>\n",
       "      <td>1800</td>\n",
       "      <td>208.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LP001035</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>2</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>No</td>\n",
       "      <td>2340</td>\n",
       "      <td>2546</td>\n",
       "      <td>100.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>LP001051</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>Not Graduate</td>\n",
       "      <td>No</td>\n",
       "      <td>3276</td>\n",
       "      <td>0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Loan_ID Gender Married Dependents     Education Self_Employed  \\\n",
       "0  LP001015   Male     Yes          0      Graduate            No   \n",
       "1  LP001022   Male     Yes          1      Graduate            No   \n",
       "2  LP001031   Male     Yes          2      Graduate            No   \n",
       "3  LP001035   Male     Yes          2      Graduate            No   \n",
       "4  LP001051   Male      No          0  Not Graduate            No   \n",
       "\n",
       "   ApplicantIncome  CoapplicantIncome  LoanAmount  Loan_Amount_Term  \\\n",
       "0             5720                  0       110.0             360.0   \n",
       "1             3076               1500       126.0             360.0   \n",
       "2             5000               1800       208.0             360.0   \n",
       "3             2340               2546       100.0             360.0   \n",
       "4             3276                  0        78.0             360.0   \n",
       "\n",
       "   Credit_History Property_Area  \n",
       "0             1.0         Urban  \n",
       "1             1.0         Urban  \n",
       "2             1.0         Urban  \n",
       "3             NaN         Urban  \n",
       "4             1.0         Urban  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>ApplicantIncome</th>\n",
       "      <th>CoapplicantIncome</th>\n",
       "      <th>LoanAmount</th>\n",
       "      <th>Loan_Amount_Term</th>\n",
       "      <th>Credit_History</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>614.000000</td>\n",
       "      <td>614.000000</td>\n",
       "      <td>592.000000</td>\n",
       "      <td>600.00000</td>\n",
       "      <td>564.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5403.459283</td>\n",
       "      <td>1621.245798</td>\n",
       "      <td>146.412162</td>\n",
       "      <td>342.00000</td>\n",
       "      <td>0.842199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>6109.041673</td>\n",
       "      <td>2926.248369</td>\n",
       "      <td>85.587325</td>\n",
       "      <td>65.12041</td>\n",
       "      <td>0.364878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>150.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>12.00000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2877.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>360.00000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3812.500000</td>\n",
       "      <td>1188.500000</td>\n",
       "      <td>128.000000</td>\n",
       "      <td>360.00000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>5795.000000</td>\n",
       "      <td>2297.250000</td>\n",
       "      <td>168.000000</td>\n",
       "      <td>360.00000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>81000.000000</td>\n",
       "      <td>41667.000000</td>\n",
       "      <td>700.000000</td>\n",
       "      <td>480.00000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ApplicantIncome  CoapplicantIncome  LoanAmount  Loan_Amount_Term  \\\n",
       "count       614.000000         614.000000  592.000000         600.00000   \n",
       "mean       5403.459283        1621.245798  146.412162         342.00000   \n",
       "std        6109.041673        2926.248369   85.587325          65.12041   \n",
       "min         150.000000           0.000000    9.000000          12.00000   \n",
       "25%        2877.500000           0.000000  100.000000         360.00000   \n",
       "50%        3812.500000        1188.500000  128.000000         360.00000   \n",
       "75%        5795.000000        2297.250000  168.000000         360.00000   \n",
       "max       81000.000000       41667.000000  700.000000         480.00000   \n",
       "\n",
       "       Credit_History  \n",
       "count      564.000000  \n",
       "mean         0.842199  \n",
       "std          0.364878  \n",
       "min          0.000000  \n",
       "25%          1.000000  \n",
       "50%          1.000000  \n",
       "75%          1.000000  \n",
       "max          1.000000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.describe() #summary of the statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Loan_ID', 'Gender', 'Married', 'Dependents', 'Education',\n",
       "       'Self_Employed', 'ApplicantIncome', 'CoapplicantIncome', 'LoanAmount',\n",
       "       'Loan_Amount_Term', 'Credit_History', 'Property_Area', 'Loan_Status'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.columns #checking all the columns in the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(614, 13)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.shape #checking the number of rows and columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Loan_ID               0\n",
       "Gender               13\n",
       "Married               3\n",
       "Dependents           15\n",
       "Education             0\n",
       "Self_Employed        32\n",
       "ApplicantIncome       0\n",
       "CoapplicantIncome     0\n",
       "LoanAmount           22\n",
       "Loan_Amount_Term     14\n",
       "Credit_History       50\n",
       "Property_Area         0\n",
       "Loan_Status           0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Loan_ID               0\n",
       "Gender               11\n",
       "Married               0\n",
       "Dependents           10\n",
       "Education             0\n",
       "Self_Employed        23\n",
       "ApplicantIncome       0\n",
       "CoapplicantIncome     0\n",
       "LoanAmount            5\n",
       "Loan_Amount_Term      6\n",
       "Credit_History       29\n",
       "Property_Area         0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 614 entries, 0 to 613\n",
      "Data columns (total 13 columns):\n",
      "Loan_ID              614 non-null object\n",
      "Gender               601 non-null object\n",
      "Married              611 non-null object\n",
      "Dependents           599 non-null object\n",
      "Education            614 non-null object\n",
      "Self_Employed        582 non-null object\n",
      "ApplicantIncome      614 non-null int64\n",
      "CoapplicantIncome    614 non-null float64\n",
      "LoanAmount           592 non-null float64\n",
      "Loan_Amount_Term     600 non-null float64\n",
      "Credit_History       564 non-null float64\n",
      "Property_Area        614 non-null object\n",
      "Loan_Status          614 non-null object\n",
      "dtypes: float64(4), int64(1), object(8)\n",
      "memory usage: 62.4+ KB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FILLING MISSING AND NAN VALUES"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "train[\"LoanAmount\"].fillna((train[\"LoanAmount\"].median()), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "train[\"Loan_Amount_Term\"].fillna((train[\"Loan_Amount_Term\"].median()), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "train[\"Credit_History\"].fillna((train[\"Credit_History\"].median()), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "train[\"Married\"].fillna((train[\"Married\"].mode()[0]), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "train[\"Gender\"].fillna((train[\"Gender\"].mode()[0]), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "train[\"Self_Employed\"].fillna((train[\"Self_Employed\"].mode()[0]), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "train[\"Dependents\"].fillna((train[\"Dependents\"].mode()[0]), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "test[\"Gender\"].fillna((test[\"Gender\"].mode()[0]), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "test[\"Self_Employed\"].fillna((test[\"Self_Employed\"].mode()[0]), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "test[\"Dependents\"].fillna((test[\"Dependents\"].mode()[0]), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "test[\"LoanAmount\"].fillna((test[\"LoanAmount\"].median()), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "test[\"Loan_Amount_Term\"].fillna((test[\"Loan_Amount_Term\"].median()), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "test[\"Credit_History\"].fillna((test[\"Credit_History\"].median()), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Loan_ID              0\n",
       "Gender               0\n",
       "Married              0\n",
       "Dependents           0\n",
       "Education            0\n",
       "Self_Employed        0\n",
       "ApplicantIncome      0\n",
       "CoapplicantIncome    0\n",
       "LoanAmount           0\n",
       "Loan_Amount_Term     0\n",
       "Credit_History       0\n",
       "Property_Area        0\n",
       "Loan_Status          0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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>ApplicantIncome</th>\n",
       "      <th>CoapplicantIncome</th>\n",
       "      <th>LoanAmount</th>\n",
       "      <th>Loan_Amount_Term</th>\n",
       "      <th>Credit_History</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>614.000000</td>\n",
       "      <td>614.000000</td>\n",
       "      <td>614.000000</td>\n",
       "      <td>614.000000</td>\n",
       "      <td>614.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5403.459283</td>\n",
       "      <td>1621.245798</td>\n",
       "      <td>145.752443</td>\n",
       "      <td>342.410423</td>\n",
       "      <td>0.855049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>6109.041673</td>\n",
       "      <td>2926.248369</td>\n",
       "      <td>84.107233</td>\n",
       "      <td>64.428629</td>\n",
       "      <td>0.352339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>150.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2877.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>100.250000</td>\n",
       "      <td>360.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3812.500000</td>\n",
       "      <td>1188.500000</td>\n",
       "      <td>128.000000</td>\n",
       "      <td>360.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>5795.000000</td>\n",
       "      <td>2297.250000</td>\n",
       "      <td>164.750000</td>\n",
       "      <td>360.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>81000.000000</td>\n",
       "      <td>41667.000000</td>\n",
       "      <td>700.000000</td>\n",
       "      <td>480.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ApplicantIncome  CoapplicantIncome  LoanAmount  Loan_Amount_Term  \\\n",
       "count       614.000000         614.000000  614.000000        614.000000   \n",
       "mean       5403.459283        1621.245798  145.752443        342.410423   \n",
       "std        6109.041673        2926.248369   84.107233         64.428629   \n",
       "min         150.000000           0.000000    9.000000         12.000000   \n",
       "25%        2877.500000           0.000000  100.250000        360.000000   \n",
       "50%        3812.500000        1188.500000  128.000000        360.000000   \n",
       "75%        5795.000000        2297.250000  164.750000        360.000000   \n",
       "max       81000.000000       41667.000000  700.000000        480.000000   \n",
       "\n",
       "       Credit_History  \n",
       "count      614.000000  \n",
       "mean         0.855049  \n",
       "std          0.352339  \n",
       "min          0.000000  \n",
       "25%          1.000000  \n",
       "50%          1.000000  \n",
       "75%          1.000000  \n",
       "max          1.000000  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(614, 13)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# DATA VISUALIZATION"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Male      502\n",
       "Female    112\n",
       "Name: Gender, dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train[\"Gender\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     360\n",
       "1     102\n",
       "2     101\n",
       "3+     51\n",
       "Name: Dependents, dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train[\"Dependents\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Yes    401\n",
       "No     213\n",
       "Name: Married, dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train[\"Married\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Graduate        480\n",
       "Not Graduate    134\n",
       "Name: Education, dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train[\"Education\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No     532\n",
       "Yes     82\n",
       "Name: Self_Employed, dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train[\"Self_Employed\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x180fca99c18>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x180f6a54c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(train, hue=\"Self_Employed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x180fdee4f60>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x180fdedacc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(train, hue=\"Married\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x180fffa2630>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x180fffa2780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(train, hue=\"Education\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x1808177edd8>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1808177e320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(train, hue=\"Dependents\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x18082d16278>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1808247dba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=\"Gender\", y=\"ApplicantIncome\", data=train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FEATURE ENGINEERING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = train.drop([\"Loan_ID\", \"Dependents\"], axis=1) #dropping a column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>Gender</th>\n",
       "      <th>Married</th>\n",
       "      <th>Education</th>\n",
       "      <th>Self_Employed</th>\n",
       "      <th>ApplicantIncome</th>\n",
       "      <th>CoapplicantIncome</th>\n",
       "      <th>LoanAmount</th>\n",
       "      <th>Loan_Amount_Term</th>\n",
       "      <th>Credit_History</th>\n",
       "      <th>Property_Area</th>\n",
       "      <th>Loan_Status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>No</td>\n",
       "      <td>5849</td>\n",
       "      <td>0.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>No</td>\n",
       "      <td>4583</td>\n",
       "      <td>1508.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Rural</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Not Graduate</td>\n",
       "      <td>No</td>\n",
       "      <td>2583</td>\n",
       "      <td>2358.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>No</td>\n",
       "      <td>6000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Gender Married     Education Self_Employed  ApplicantIncome  \\\n",
       "0   Male      No      Graduate            No             5849   \n",
       "1   Male     Yes      Graduate            No             4583   \n",
       "2   Male     Yes      Graduate           Yes             3000   \n",
       "3   Male     Yes  Not Graduate            No             2583   \n",
       "4   Male      No      Graduate            No             6000   \n",
       "\n",
       "   CoapplicantIncome  LoanAmount  Loan_Amount_Term  Credit_History  \\\n",
       "0                0.0       128.0             360.0             1.0   \n",
       "1             1508.0       128.0             360.0             1.0   \n",
       "2                0.0        66.0             360.0             1.0   \n",
       "3             2358.0       120.0             360.0             1.0   \n",
       "4                0.0       141.0             360.0             1.0   \n",
       "\n",
       "  Property_Area Loan_Status  \n",
       "0         Urban           Y  \n",
       "1         Rural           N  \n",
       "2         Urban           Y  \n",
       "3         Urban           Y  \n",
       "4         Urban           Y  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Loan_ID</th>\n",
       "      <th>Gender</th>\n",
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       "      <th>Education</th>\n",
       "      <th>Self_Employed</th>\n",
       "      <th>ApplicantIncome</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>LP001015</td>\n",
       "      <td>Male</td>\n",
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       "      <td>No</td>\n",
       "      <td>5720</td>\n",
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       "      <td>110.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>LP001022</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>No</td>\n",
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       "      <td>1500</td>\n",
       "      <td>126.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>LP001031</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>No</td>\n",
       "      <td>5000</td>\n",
       "      <td>1800</td>\n",
       "      <td>208.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LP001035</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>No</td>\n",
       "      <td>2340</td>\n",
       "      <td>2546</td>\n",
       "      <td>100.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>LP001051</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Not Graduate</td>\n",
       "      <td>No</td>\n",
       "      <td>3276</td>\n",
       "      <td>0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Loan_ID Gender Married     Education Self_Employed  ApplicantIncome  \\\n",
       "0  LP001015   Male     Yes      Graduate            No             5720   \n",
       "1  LP001022   Male     Yes      Graduate            No             3076   \n",
       "2  LP001031   Male     Yes      Graduate            No             5000   \n",
       "3  LP001035   Male     Yes      Graduate            No             2340   \n",
       "4  LP001051   Male      No  Not Graduate            No             3276   \n",
       "\n",
       "   CoapplicantIncome  LoanAmount  Loan_Amount_Term  Credit_History  \\\n",
       "0                  0       110.0             360.0             1.0   \n",
       "1               1500       126.0             360.0             1.0   \n",
       "2               1800       208.0             360.0             1.0   \n",
       "3               2546       100.0             360.0             1.0   \n",
       "4                  0        78.0             360.0             1.0   \n",
       "\n",
       "  Property_Area  \n",
       "0         Urban  \n",
       "1         Urban  \n",
       "2         Urban  \n",
       "3         Urban  \n",
       "4         Urban  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test = test.drop(\"Dependents\", axis=1)\n",
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "#converting categorical data into vectors that machine can deal with\n",
    "cleanup_num = {\"Loan_Status\":   {\"Y\": 1, \"N\": 0},\n",
    "              \"Gender\":  {\"Male\": 1, \"Female\": 0},\n",
    "              \"Married\": {\"Yes\": 1, \"No\": 0}, \"Self_Employed\": {\"Yes\": 1, \"No\": 0},\n",
    "              \"Education\": {\"Graduate\": 0, \"Not Graduate\": 1} }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>Gender</th>\n",
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       "      <th>Self_Employed</th>\n",
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       "      <th>Loan_Status</th>\n",
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       "      <th>0</th>\n",
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       "      <td>128.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
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       "      <td>1.0</td>\n",
       "      <td>Rural</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <td>66.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2583</td>\n",
       "      <td>2358.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Gender  Married  Education  Self_Employed  ApplicantIncome  \\\n",
       "0       1        0          0              0             5849   \n",
       "1       1        1          0              0             4583   \n",
       "2       1        1          0              1             3000   \n",
       "3       1        1          1              0             2583   \n",
       "4       1        0          0              0             6000   \n",
       "\n",
       "   CoapplicantIncome  LoanAmount  Loan_Amount_Term  Credit_History  \\\n",
       "0                0.0       128.0             360.0             1.0   \n",
       "1             1508.0       128.0             360.0             1.0   \n",
       "2                0.0        66.0             360.0             1.0   \n",
       "3             2358.0       120.0             360.0             1.0   \n",
       "4                0.0       141.0             360.0             1.0   \n",
       "\n",
       "  Property_Area  Loan_Status  \n",
       "0         Urban            1  \n",
       "1         Rural            0  \n",
       "2         Urban            1  \n",
       "3         Urban            1  \n",
       "4         Urban            1  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.replace(cleanup_num, inplace=True)\n",
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <td>1</td>\n",
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       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Gender  Married  Education  Self_Employed  ApplicantIncome  \\\n",
       "0       1        0          0              0             5849   \n",
       "1       1        1          0              0             4583   \n",
       "2       1        1          0              1             3000   \n",
       "3       1        1          1              0             2583   \n",
       "4       1        0          0              0             6000   \n",
       "\n",
       "   CoapplicantIncome  LoanAmount  Loan_Amount_Term  Credit_History  \\\n",
       "0                0.0       128.0             360.0             1.0   \n",
       "1             1508.0       128.0             360.0             1.0   \n",
       "2                0.0        66.0             360.0             1.0   \n",
       "3             2358.0       120.0             360.0             1.0   \n",
       "4                0.0       141.0             360.0             1.0   \n",
       "\n",
       "   Property_Area  Loan_Status  \n",
       "0              2            1  \n",
       "1              0            0  \n",
       "2              2            1  \n",
       "3              2            1  \n",
       "4              2            1  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train['Property_Area'].replace({'Urban':2,'Semiurban':1,'Rural':0},inplace=True)\n",
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "cleanup_num1 = {\"Dependents\":   {\"O\": 0, \"1\": 1, \"2\": 2, \"3+\": 3},\n",
    "              \"Gender\":  {\"Male\": 1, \"Female\": 0},\"Married\": {\"Yes\": 1, \"No\": 0}, \n",
    "              \"Self_Employed\": {\"Yes\": 1, \"No\": 0},\n",
    "              \"Education\": {\"Graduate\": 0, \"Not Graduate\": 1} }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Loan_ID</th>\n",
       "      <th>Gender</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>LP001015</td>\n",
       "      <td>1</td>\n",
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       "      <td>110.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>LP001022</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>3076</td>\n",
       "      <td>1500</td>\n",
       "      <td>126.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>LP001031</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5000</td>\n",
       "      <td>1800</td>\n",
       "      <td>208.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LP001035</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2340</td>\n",
       "      <td>2546</td>\n",
       "      <td>100.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>LP001051</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3276</td>\n",
       "      <td>0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Urban</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Loan_ID  Gender  Married  Education  Self_Employed  ApplicantIncome  \\\n",
       "0  LP001015       1        1          0              0             5720   \n",
       "1  LP001022       1        1          0              0             3076   \n",
       "2  LP001031       1        1          0              0             5000   \n",
       "3  LP001035       1        1          0              0             2340   \n",
       "4  LP001051       1        0          1              0             3276   \n",
       "\n",
       "   CoapplicantIncome  LoanAmount  Loan_Amount_Term  Credit_History  \\\n",
       "0                  0       110.0             360.0             1.0   \n",
       "1               1500       126.0             360.0             1.0   \n",
       "2               1800       208.0             360.0             1.0   \n",
       "3               2546       100.0             360.0             1.0   \n",
       "4                  0        78.0             360.0             1.0   \n",
       "\n",
       "  Property_Area  \n",
       "0         Urban  \n",
       "1         Urban  \n",
       "2         Urban  \n",
       "3         Urban  \n",
       "4         Urban  "
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.replace(cleanup_num, inplace=True)\n",
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "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>Loan_ID</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Married</th>\n",
       "      <th>Education</th>\n",
       "      <th>Self_Employed</th>\n",
       "      <th>ApplicantIncome</th>\n",
       "      <th>CoapplicantIncome</th>\n",
       "      <th>LoanAmount</th>\n",
       "      <th>Loan_Amount_Term</th>\n",
       "      <th>Credit_History</th>\n",
       "      <th>Property_Area</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>LP001015</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5720</td>\n",
       "      <td>0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>LP001022</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3076</td>\n",
       "      <td>1500</td>\n",
       "      <td>126.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>LP001031</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5000</td>\n",
       "      <td>1800</td>\n",
       "      <td>208.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LP001035</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2340</td>\n",
       "      <td>2546</td>\n",
       "      <td>100.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>LP001051</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3276</td>\n",
       "      <td>0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Loan_ID  Gender  Married  Education  Self_Employed  ApplicantIncome  \\\n",
       "0  LP001015       1        1          0              0             5720   \n",
       "1  LP001022       1        1          0              0             3076   \n",
       "2  LP001031       1        1          0              0             5000   \n",
       "3  LP001035       1        1          0              0             2340   \n",
       "4  LP001051       1        0          1              0             3276   \n",
       "\n",
       "   CoapplicantIncome  LoanAmount  Loan_Amount_Term  Credit_History  \\\n",
       "0                  0       110.0             360.0             1.0   \n",
       "1               1500       126.0             360.0             1.0   \n",
       "2               1800       208.0             360.0             1.0   \n",
       "3               2546       100.0             360.0             1.0   \n",
       "4                  0        78.0             360.0             1.0   \n",
       "\n",
       "   Property_Area  \n",
       "0              2  \n",
       "1              2  \n",
       "2              2  \n",
       "3              2  \n",
       "4              2  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test['Property_Area'].replace({'Urban':2,'Semiurban':1,'Rural':0},inplace=True)\n",
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((614, 10), (614,))"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data = train.drop('Loan_Status', axis=1)\n",
    "target = train['Loan_Status']\n",
    "\n",
    "train_data.shape, target.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# MODELLING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn import metrics\n",
    "from sklearn.metrics import accuracy_score, f1_score, classification_report \n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import KFold\n",
    "from sklearn.model_selection import cross_val_score\n",
    "k_fold = KFold(n_splits=10, shuffle=True, random_state=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "model=LogisticRegression()\n",
    "scoring = \"accuracy\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "score = cross_val_score(model, train_data, target, cv=k_fold, n_jobs=1, scoring = scoring)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.74193548 0.85483871 0.77419355 0.77419355 0.8852459  0.86885246\n",
      " 0.7704918  0.83606557 0.75409836 0.85245902]\n"
     ]
    }
   ],
   "source": [
    "print(score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "81.12"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "round(np.mean(score)*100, 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "clf = DecisionTreeClassifier()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.70967742 0.74193548 0.64516129 0.64516129 0.7704918  0.73770492\n",
      " 0.73770492 0.72131148 0.54098361 0.70491803]\n"
     ]
    }
   ],
   "source": [
    "scoring = 'accuracy'\n",
    "score = cross_val_score(clf, train_data, target, cv=k_fold, n_jobs=1, scoring=scoring)\n",
    "print(score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "69.55"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "round(np.mean(score)*100, 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.77419355 0.85483871 0.74193548 0.79032258 0.81967213 0.80327869\n",
      " 0.7704918  0.75409836 0.72131148 0.7704918 ]\n"
     ]
    }
   ],
   "source": [
    "R_clf = RandomForestClassifier(n_estimators=13)\n",
    "scoring = 'accuracy'\n",
    "score = cross_val_score(R_clf, train_data, target, cv=k_fold, n_jobs=1, scoring=scoring)\n",
    "print(score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "78.01"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "round(np.mean(score)*100, 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.fit(train_data, target)\n",
    "\n",
    "test_data = test.drop(\"Loan_ID\", axis=1).copy()\n",
    "prediction = model.predict(test_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "pickle.dump(model, open('model.pkl','wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_cols = pd.DataFrame({\n",
    "        \"Loan_ID\": test[\"Loan_ID\"],\n",
    "        \"Loan_Status\": prediction\n",
    "    })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "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>Loan_ID</th>\n",
       "      <th>Loan_Status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>LP001015</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>LP001022</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>LP001031</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LP001035</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>LP001051</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Loan_ID  Loan_Status\n",
       "0  LP001015            1\n",
       "1  LP001022            1\n",
       "2  LP001031            1\n",
       "3  LP001035            1\n",
       "4  LP001051            1"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred_cols.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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