input: Write a function that demonstrates how to implement a simple linear regression model in Python using pandas, sklearn, and matplotlib. The function should read data from a CSV file, fit a linear regression model, make predictions, and visualize the results.
  
  assert simple_linear_regression()==None
output: def simple_linear_regression():
      import pandas as pd
      from sklearn.linear_model import LinearRegression
      import matplotlib.pyplot as plt
  
      data = pd.read_csv('data.csv')
      X = data[['X']]
      y = data['y']
  
      model = LinearRegression()
      model.fit(X, y)
  
      predictions = model.predict(X)
  
      plt.scatter(X, y, color='blue')
      plt.plot(X, predictions, color='red')
      plt.xlabel('X')
      plt.ylabel('y')
      plt.title('Simple Linear Regression')
      plt.show()