input: 
  import numpy as np
  from sklearn import linear_model
  
  def predict_housing_price(data, prices, new_data):
      """ Create a Linear Regression model to predict housing prices based on living area and number of rooms.
      >>> data = [[2000, 3], [1600, 2.5], [2400, 3.5], [1400, 2], [3000, 4]]
      >>> prices = [75000, 43000, 59000, 32000, 85000]
      >>> new_data = [[2200, 3]]
      >>> predict_housing_price(data, prices, new_data)
      array([68000.])
      """
      X = np.array(data)
      y = np.array(prices)
      model = linear_model.LinearRegression()
      model.fit(X, y)
      prediction = model.predict(np.array(new_data))
      return prediction
  
output:     X = np.array(data)
      y = np.array(prices)
      model = linear_model.LinearRegression()
      model.fit(X, y)
      prediction = model.predict(np.array(new_data))
      return prediction