input: 
  import numpy as np
  from sklearn import linear_model
  
  def predict_housing_price(data, living_area, number_of_rooms):
      """ Use Linear Regression to predict the housing price based on the given data
      which contains living area and number of rooms.
      >>> data = [[2000, 3], [1600, 2.5], [2400, 3.5], [1400, 2], [3000, 4]]
      >>> y_true = [75000, 43000, 59000, 32000, 85000]
      >>> predict_housing_price(data, 2200, 3)
      78421.05
      """
      X = np.array(data)
      y = np.array([75000, 43000, 59000, 32000, 85000])
      model = linear_model.LinearRegression()
      model.fit(X, y)
      prediction = model.predict([[living_area, number_of_rooms]])
      return prediction[0].round(2)
  
output:     X = np.array(data)
      y = np.array([75000, 43000, 59000, 32000, 85000])
      model = linear_model.LinearRegression()
      model.fit(X, y)
      prediction = model.predict([[living_area, number_of_rooms]])
      return prediction[0].round(2)