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()
  plt.bar(loan_status.index,loan_status)
  plt.show()
  
  
  #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))
  #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)
  
  #Code ends here
  
  
  # --------------
  #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=False,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)
  
  
  
  # --------------
  #Code starts here
  graduate=data[data['Education']=='Graduate']
  not_graduate=data[data['Education']=='Not Graduate']
  graduate['LoanAmount'].plot(kind='density',label='Graduate')
  not_graduate['LoanAmount'].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)
  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")
  
  
  
  
  