input: Write a function to create a Linear Regression model that can predict housing prices based on the living area and number of rooms. The function should take in the training data and return the prediction for a given test data.
  
  def predict_housing_price(data, prices, test_data):
      import numpy as np
      from sklearn import linear_model
      
      X = np.array(data)
      y = np.array(prices)
      
      model = linear_model.LinearRegression()
      model.fit(X, y)
      
      prediction = model.predict(np.array([test_data]))
      return prediction
  
  assert predict_housing_price([[2000, 3], [1600, 2.5], [2400, 3.5], [1400, 2], [3000, 4]], [75000, 43000, 59000, 32000, 85000], [2200, 3])==[51562.5]
output: def predict_housing_price(data, prices, test_data):
      import numpy as np
      from sklearn import linear_model
      
      X = np.array(data)
      y = np.array(prices)
      
      model = linear_model.LinearRegression()
      model.fit(X, y)
      
      prediction = model.predict(np.array([test_data]))
      return prediction