# --------------
#Importing header files
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
data=pd.read_csv(path)
loan_status =data['Loan_Status'].value_counts()
loan_status.plot(kind='bar',figsize=(15,10))


#Code starts here


# --------------
#Code starts here
property_and_loan=data.groupby(['Property_Area','Loan_Status']).size().unstack()
property_and_loan.plot(kind='bar',stacked=False, figsize=(15,10))
plt.xlabel('Property Area')
plt.ylabel('Loan Status')
plt.xticks(rotation=45)


# --------------
#Code starts here
education_and_loan=data.groupby(['Education','Loan_Status']).size().unstack()
education_and_loan.plot(kind='bar',stacked=True,figsize=(15,10))
plt.xlabel('Education Status')
plt.ylabel('Loan Status')
plt.xticks(rotation=45)


# --------------
#Code starts here
graduate=data[data['Education']=='Graduate']
not_graduate=data[data['Education']=='Not Graduate']
graduate.plot(kind='density',label='Graduate')
not_graduate.plot(kind='density',label='Not Graduate')











#Code ends here

#For automatic legend display
plt.legend()


# --------------
#Code starts here
fig ,(ax_1,ax_2,ax_3)=plt.subplots(3,1,figsize=(20,10))
plt.scatter(data['ApplicantIncome'],data['LoanAmount'])
ax_1.set_title('Applicant Income')
plt.scatter(data['CoapplicantIncome'],data['LoanAmount'])
#data.plot(kind='scatter',x=CoapplicantIncome,y=LoanAmount)
ax_2.set_title('Coapplicant Income')
data['TotalIncome']=data['ApplicantIncome']+data['CoapplicantIncome']
plt.scatter(data['TotalIncome'],data['LoanAmount'])
#data.plot.scatter(x=TotalIncome,y=LoanAmount,ax=ax_3)
ax_3.set_title('Total Income')


