Loan Status Classification with the help of Classification Algorithms

#imported all the required packages
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from sklearn.impute import KNNImputer
from sklearn.model_selection import KFold
from sklearn.model_selection import cross_val_score
import seaborn as sns
from sklearn import metrics

df_train=pd.read_csv('https://raw.githubusercontent.com/Yogita98/Loan-Status-Classification/master/train_AV3.csv?token=AI66AL4HZBEKUVFEMHB2PBK6WVXZO')
df_test=pd.read_csv('https://raw.githubusercontent.com/Yogita98/Loan-Status-Classification/master/test_AV3.csv?token=AI66AL6IBRBDU2CGVIDOXT26WVXV2')
df_train.head(20)

df_train.isnull().sum()

Loan_ID               0
Gender               13
Married               3
Dependents           15
Education             0
Self_Employed        32
ApplicantIncome       0
CoapplicantIncome     0
LoanAmount           22
Loan_Amount_Term     14
Credit_History       50
Property_Area         0
Loan_Status           0
dtype: int64

df_test.isnull().sum()

Loan_ID               0
Gender               11
Married               0
Dependents           10
Education             0
Self_Employed        23
ApplicantIncome       0
CoapplicantIncome     0
LoanAmount            5
Loan_Amount_Term      6
Credit_History       29
Property_Area         0
Loan_Status           0
dtype: int64