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Created 4 years ago
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