# --------------
#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=(10,20))
#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)

plt.xlabel="Property Area"
plt.ylabel="Loan Status"
plt.xticks= "45"


# --------------
#Code starts here
education_and_loan = data.groupby(['Education','Loan_Status']).size().unstack()
education_and_loan.plot(kind='bar',stacked=True)

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['LoanAmount'].plot(kind='density',label ='Graduate')
not_graduate['LoanAmount'].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(nrows=3,ncols=1)

data.plot.scatter(x='ApplicantIncome',y='LoanAmount' )
ax_1.set_title('Applicant Income')
data.plot.scatter(x='CoapplicantIncome',y='LoanAmount')
ax_2.set_title('CoapplicantIncome')

data['TotalIncome'] =data['ApplicantIncome']+data['CoapplicantIncome']

ax_3.scatter(x='ApplicantIncome',y='LoanAmount')
ax_3.set_title('Total Income') 


