input: from typing import List, Tuple
  import numpy as np
  from sklearn import linear_model
  
  def predict_housing_price(area_and_rooms: List[Tuple[int, float]], prices: List[int], new_area_and_room: Tuple[int, float]) -> float:
      """
      Train a Linear Regression model to predict housing prices based on given living area and number of rooms.
      Then use the trained model to predict the price for a new living area and number of rooms.
      
      >>> predict_housing_price([(2000, 3), (1600, 2.5), (2400, 3.5), (1400, 2), (3000, 4)], [75000, 43000, 59000, 32000, 85000], (2200, 3))
      70000.0
      """
      X = np.array(area_and_rooms)
      y = np.array(prices)
      
      model = linear_model.LinearRegression()
      model.fit(X, y)
      
      prediction = model.predict([new_area_and_room])
      return prediction[0]
output:     X = np.array(area_and_rooms)
      y = np.array(prices)
      
      model = linear_model.LinearRegression()
      model.fit(X, y)
      
      prediction = model.predict([new_area_and_room])
      return prediction[0]