# --------------
#Importing header files
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

#Code starts here
path

data = pd.read_csv(path, sep = ',', delimiter = None)

loan_status = data['Loan_Status'].value_counts()


loan_status.plot(kind = 'bar')

plt.show()


# --------------
#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(rotation=45) 


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

education_and_loan = data[['Education', 'Loan_Status']]

education_and_loan = education_and_loan.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(3, 1, figsize= (20, 40))

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['ApplicantIncome'].fillna(0)
data['CoapplicantIncome'].fillna(0)

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

data.plot.scatter(x ='TotalIncome' , y='LoanAmount', ax = ax_3)
ax_3.set_title('Total Income')



# --------------
#Importing header files
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

#Code starts here
path

data = pd.read_csv(path, sep = ',', delimiter = None)

loan_status = data['Loan_Status'].value_counts()


loan_status.plot(kind = 'bar')

plt.show()


# --------------
#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(rotation=45) 


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

education_and_loan = data[['Education', 'Loan_Status']]

education_and_loan = education_and_loan.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(3, 1, figsize= (20, 40))

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['ApplicantIncome'].fillna(0)
data['CoapplicantIncome'].fillna(0)

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

data.plot.scatter(x ='TotalIncome' , y='LoanAmount', ax = ax_3)
ax_3.set_title('Total Income')



# -------------- #Importing header files #Code starts here # -------------- #Code starts here # -------------- #Code starts here # -------------- #Code starts here #Code ends here #For automatic legend display # -------------- #Code starts here