text: # --------------
  #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
  data=pd.read_csv(path)
  
  #Creating a new variable to store the value counts
  loan_status=data['Loan_Status'].value_counts()
  
  #Plotting bar plot
  plt.bar(loan_status.index, loan_status)
  plt.show()
  
  # Step 2
  
  #Plotting an unstacked bar plot
  property_and_loan=data.groupby(['Property_Area', 'Loan_Status'])
  property_and_loan=property_and_loan.size().unstack()
  property_and_loan.plot(kind='bar', stacked=False, figsize=(15,10))
  
  #Changing the x-axis label
  plt.xlabel('Property_Area')
  
  #Changing the y-axis label
  plt.ylabel('Loan_Status')
  
  #Rotating the ticks of X-axis
  plt.xticks(rotation=45)
  
  # Step 3
  
  #Plotting a stacked bar plot
  education_and_loan=data.groupby(['Education', 'Loan_Status'])
  education_and_loan=education_and_loan.size().unstack()
  education_and_loan.plot(kind='bar', stacked=True, figsize=(15,10))
  
  
  #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)
  
  # 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['LoanAmount'].plot(kind='density', label='Graduate')
  
  
  #Plotting density plot for 'Graduate'
  not_graduate['LoanAmount'].plot(kind='density',label='Not Graduate')
  
  #For automatic legend display
  plt.legend()
  
  # Step 5
  
  #Setting up the subplots
  fig, (ax_1, ax_2,ax_3) = plt.subplots(1,3, figsize=(20,8))
  
  #Plotting scatter plot
  ax_1.scatter(data['ApplicantIncome'],data["LoanAmount"])
  
  #Setting the subplot axis title
  ax_1.set(title='Applicant Income')
  
  
  #Plotting scatter plot
  ax_2.scatter(data['CoapplicantIncome'],data["LoanAmount"])
  
  #Setting the subplot axis title
  ax_2.set(title='Coapplicant Income')
  
  
  #Creating a new column 'TotalIncome'
  data['TotalIncome']= data['ApplicantIncome']+ data['CoapplicantIncome']
  
  #Plotting scatter plot
  ax_3.scatter(data['TotalIncome'],data["LoanAmount"])
  
  #Setting the subplot axis title
  ax_3.set(title='Total Income')
  print(data['TotalIncome'][1])
  
  
  
  