code: # --------------
  #Importing header files
  import pandas as pd
  import numpy as np
  import matplotlib.pyplot as plt
  
  
  #Reading the file
  data=pd.read_csv(path)
  print(data.iloc[25, 1])
  # df = pd.DataFrame(data)
  #Code starts here
  loan_status = data['Loan_Status'].value_counts()
  loan_status.plot(kind = 'bar')
  # # Step 1 
  #Reading the file
  
  property_and_loan = data.groupby(['Property_Area', 'Loan_Status'])
  #Creating a new variable to store the value counts
  property_and_loan = property_and_loan.size().unstack()
  property_and_loan = property_and_loan.plot(kind = 'bar', stacked = False)
  plt.xlabel('Property Area')
  plt.ylabel('Loan Status')
  plt.xticks(rotation = 45)
  plt.show()
  
  #Plotting bar plot
  
  
  
  # Step 2
  #Plotting an unstacked bar plot
  education_and_loan = data.groupby(['Education', 'Loan_Status']).size().unstack().plot(kind = 'bar', stacked = True)
  plt.xlabel('Education Status')
  plt.ylabel('Loan Status')
  plt.xticks(rotation = 45)
  plt.show()
  
  #Changing the x-axis label
  
  
  #Changing the y-axis label
  
  
  #Rotating the ticks of X-axis
  
  
  # Step 3
  #Plotting a stacked bar plot
  
  graduate = pd.DataFrame(data[data['Education'] == 'Graduate'])
  not_graduate = pd.DataFrame(data[data['Education'] == 'Not Graduate']) 
  
  #Changing the x-axis label
  pd.Series(graduate['LoanAmount']).plot(kind = 'density', label = 'Graduate')
  pd.Series(not_graduate['LoanAmount']).plot(kind = 'density', label = 'Not Graduate')
  #Changing the y-axis label
  
  
  #Rotating the ticks of X-axis
  
  
  # Step 4 
  #Subsetting the dataframe based on 'Education' column
  fig ,(ax_1,ax_2,ax_3) = plt.subplots(nrows = 3 , ncols = 1)
  
  #Subsetting the dataframe based on 'Education' column
  data.plot.scatter(x= 'ApplicantIncome', y = 'LoanAmount', ax = ax_1)
  ax_1.set_title('Applicant Income')
  
  # #Plotting density plot for 'Graduate'
  data.plot.scatter(x = 'CoapplicantIncome', y = 'LoanAmount', ax = ax_2)
  ax_2.set_title('Coapplicant Income')
  
  #Plotting density plot for 'Graduate'
  data['TotalIncome'] = data['ApplicantIncome'] + data['CoapplicantIncome']
  data.plot.scatter(x = 'TotalIncome', y = 'LoanAmount', ax = ax_3)
  ax_3.set_title('Total Income')
  #For automatic legend display
  print(data['TotalIncome'][1])
  
  # Step 5
  #Setting up the subplots
  
  
  #Plotting scatter plot
  
  
  #Setting the subplot axis title
  
  
  #Plotting scatter plot
  
  
  #Setting the subplot axis title
  
  
  #Creating a new column 'TotalIncome'
  
  
  #Plotting scatter plot
  
  
  
  #Setting the subplot axis title
  
  
  
  
apis: pandas.Series matplotlib.pyplot.xticks pandas.read_csv pandas.DataFrame matplotlib.pyplot.subplots matplotlib.pyplot.show matplotlib.pyplot.ylabel matplotlib.pyplot.xlabel