# --------------
#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()
print(loan_status)
loan_status.plot(kind="bar")
#Code starts here


# --------------
#Code starts here

property_and_loan = data.groupby(['Property_Area','Loan_Status'])
print(property_and_loan.head(5))

property_and_loan = property_and_loan.size().unstack()
property_and_loan.plot(kind='bar', stacked=False)


# --------------
#Code starts here


education_and_loan = data.groupby(['Education','Loan_Status'])
education_and_loan = education_and_loan.size().unstack()

education_and_loan.plot(kind='bar', stacked=True)

plt.xlabel('Education Status')
plt.xlabel('Loan Status')
plt.xticks(rotation=45)
plt.show()


# --------------
#Code starts here

graduate = data[data['Education'] == 'Graduate']
not_graduate = data[data['Education'] != '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
#print(data.head(5))
fig ,(ax_1,ax_2,ax_3) = plt.subplots(3,1, figsize=(20,10))

data.plot.scatter(x='ApplicantIncome',y='LoanAmount', ax=ax_1)
ax_1.set_title('Applicant Income')
data.plot.scatter(x='CoapplicantIncome',y='LoanAmount', ax=ax_2)
ax_2.set_title('Coapplicant Income')
data['TotalIncome'] = data['ApplicantIncome'] + data['CoapplicantIncome']
data.plot.scatter(x='TotalIncome',y='LoanAmount', ax=ax_3)
ax_3.set_title('Total Income')


