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


#Reading the file
data=pd.read_csv(path)

#Code starts here

# Step 1 
#Reading the file


#Creating a new variable to store the value counts
loan_status=data.Loan_Status.value_counts()

#Plotting bar plot
loan_status.plot(kind='bar')
plt.xticks(rotation=360)
plt.title("Loan_status")
plt.legend()
plt.show()

# Step 2
#Plotting an unstacked bar plot
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)
plt.yticks(rotation=45)
#Changing the x-axis label


#Changing the y-axis label


#Rotating the ticks of X-axis


# Step 3
#Plotting a stacked bar plot
education_and_loan=data.groupby(['Education','Loan_Status']).size().unstack()
education_and_loan.plot(kind='bar',stacked=True)


#Changing the x-axis label
plt.xlabel('Education Status')

#Changing the y-axis label

plt.ylabel('Loan Status')
#Rotating the ticks of X-axis
plt.xticks(rotation=45)
plt.yticks(rotation=45)

# Step 4 
#Subsetting the dataframe based on 'Education' column
graduate=data[data['Education']=='Graduate']

#Subsetting the dataframe based on 'Education' column

not_graduate=data[data['Education']=='Not Graduate']
#Plotting density plot for 'Graduate'
graduate.plot(kind="density",label='Graduate',color='red')

#Plotting density plot for 'Graduate'

not_graduate.plot(kind="density",label='Not Graduate',color='blue')
#For automatic legend display
plt.legend()

# Step 5
#Setting up the subplots
fig ,(ax_1,ax_2,ax_3)=plt.subplots(3,1)

#Plotting scatter plot

ax_1.scatter(data['ApplicantIncome'],data['LoanAmount'])
#Setting the subplot axis title
plt.title('Applicant Income')

#Plotting scatter plot

ax_2.scatter(data['CoapplicantIncome'],data['LoanAmount'])
#Setting the subplot axis title
plt.title('Coapplicant Income')

#Creating a new column 'TotalIncome'
data['TotalIncome']=data['ApplicantIncome']+data['CoapplicantIncome']


#Plotting scatter plot

ax_3.scatter(data['TotalIncome'],data['LoanAmount'])
plt.title('Total  Income')
#Setting the subplot axis title



