input: Write a function that reads data from a CSV file and performs a simple linear regression model using Python. The function should visualize the results by plotting the actual data points and the linear regression line on the same graph. 
  
  
  import pandas as pd
  import matplotlib.pyplot as plt
  from sklearn import linear_model
  
  def perform_linear_regression(csv_file_path):
      # Read data from CSV
      data = pd.read_csv(csv_file_path)
      
      # Set X and Y
      X = data[['X']]
      Y = data['Y']
      
      # Create linear regression model
      model = linear_model.LinearRegression()
      
      # Train the model
      model.fit(X, Y)
      
      # Make predictions
      Y_pred = model.predict(X)
      
      # Visualize the results
      plt.scatter(X, Y)
      plt.plot(X, Y_pred, color='red')
      plt.show()
  
  # Example usage
  perform_linear_regression('data.csv')
  
  assert perform_linear_regression('data1.csv')==None
  assert perform_linear_regression('data2.csv')==None
  assert perform_linear_regression('data3.csv')==None
output: def perform_linear_regression(csv_file_path):
      data = pd.read_csv(csv_file_path)
      X = data[['X']]
      Y = data['Y']
      model = linear_model.LinearRegression()
      model.fit(X, Y)
      Y_pred = model.predict(X)
      plt.scatter(X, Y)
      plt.plot(X, Y_pred, color='red')
      plt.show()