text: # --------------
  #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'])
  property_and_loan = property_and_loan.size().unstack()
  property_and_loan.plot(kind='bar', stacked=False, figsize=(15,10))
  plt.xlabel('Property Area')
  plt.ylabel('Loan Status')
  plt.xticks(rotation=45)
  plt.show()
  
  
  # --------------
  #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.ylabel('Loan Status')
  plt.xticks(rotation = 45)
  plt.show()
  
  
  # --------------
  #Code starts here
  graduate = data[data['Education'] == 'Graduate']
  not_graduate = data[data['Education'] == 'Not 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
  fig ,(ax_1,ax_2,ax_3) = plt.subplots(nrows = 3 , ncols = 1)
  
  data.plot.scatter(x='ApplicantIncome', y='LoanAmount', ax=ax_1)
  ax_1.title.set_text('Applicant Income')
  
  data.plot.scatter(x='CoapplicantIncome', y='LoanAmount', ax=ax_2)
  ax_2.title.set_text('Coapplicant Income')
  
  data['TotalIncome'] = data['ApplicantIncome'] + data['CoapplicantIncome']
  
  data.plot.scatter(x='TotalIncome', y='LoanAmount', ax=ax_3)
  ax_3.title.set_text('Total Income')
  
  
  
  