text: # --------------
  #Importing header files
  import pandas as pd
  import numpy as np
  import matplotlib.pyplot as plt
  
  
  
  
  #Code starts here
  data = pd.read_csv(path)
  loan_status = data['Loan_Status'].value_counts()
  
  plt.bar(loan_status.index, loan_status)
  plt.show()
  
  
  # --------------
  #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, figsize=(15,10))
  
  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']
  
  pd.Series(graduate['LoanAmount']).plot(kind='density', label='Graduate')
  pd.Series(not_graduate['LoanAmount']).plot(kind='density', label='Not Graduate')
  
  
  
  
  
  
  #Code ends here
  
  #For automatic legend display
  plt.legend()
  plt.show()
  
  
  # --------------
  #Code starts here
  fig, (ax_1,ax_2,ax_3) = plt.subplots(nrows = 3 , ncols = 1, figsize=(20,10))
  
  ax_1.scatter(data['ApplicantIncome'], data['LoanAmount'])
  ax_1.set_title('Applicant Income')
  
  ax_2.scatter(data['CoapplicantIncome'], data['LoanAmount'])
  ax_2.set_title('Coapplicant Income')
  
  data['TotalIncome'] = data['ApplicantIncome'] + data['CoapplicantIncome']
  ax_3.scatter(data['TotalIncome'], data['LoanAmount'])
  ax_3.set_title('Total Income')
  
  plt.show()
  
  
  