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)
  
  #Code starts here
  
  # Step 1 
  #Reading the file
  
  
  #Creating a new variable to store the value counts
  loan_status=data['Loan_Status'].value_counts()
  loan_status.plot(kind="bar")
  #Plotting bar plot
  
  
  
  # 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, figsize=(15,10))
  # Label X-axes and Y-axes
  plt.xlabel('Property Area')
  plt.ylabel('Loan Status')
  # Rotate X-axes labels
  plt.xticks(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, figsize=(15,10))
  # Label X-axes and Y-axes
  plt.xlabel('Education Status')
  plt.ylabel('Loan Status')
  # Rotate X-axes labels
  plt.xticks(rotation=45)
  
  
  #Changing the x-axis label
  
  
  #Changing the y-axis label
  
  
  #Rotating the ticks of X-axis
  
  
  # Step 4 
  #Subsetting the dataframe based on 'Education' column
  graduate=data[data['Education'] == 'Graduate']
  not_graduate=data[data['Education'] == 'Not Graduate']
  #Subsetting the dataframe based on 'Education' column
  graduate['LoanAmount'].plot(kind='density',label='Graduate')
  not_graduate['LoanAmount'].plot(kind='density',label='Not Graduate')
  #Plotting density plot for 'Graduate'
  
  
  #Plotting density plot for 'Graduate'
  
  
  #For automatic legend display
  
  
  # Step 5
  #Setting up the subplots
  # Initialize figure and axes
  fig, (ax_1, ax_2,ax_3) = plt.subplots(3,1, 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')
  
  
  #Setting the subplot axis title
  
  
  
  
apis: matplotlib.pyplot.xticks pandas.read_csv matplotlib.pyplot.subplots matplotlib.pyplot.ylabel matplotlib.pyplot.xlabel