input: Write a function to compute the moving average of time-series data points for a given window size. If the window size is greater than the number of data points, return an empty list. 
  
  def moving_average(data_points, window):
       if window > len(data_points):
           return []
       moving_average = []
       for index in range(len(data_points)):
           start = 0 if index-window+1 < 0 else index-window+1
           if index - window + 1 < 0 :
               start = index- window + 1
           window_data = data_points[0:index+1]
           average = sum(window_data)/len(window_data)
           moving_average.append(average)
   
       return moving_average
   
  window = 3
  time_series = [3, 5, 7, 2, 8, 10, 11, 65, 72, 81, 99, 100, 150]
  assert moving_average([], 2) == []
  assert moving_average([1, 2, 3], 2) == [1.0, 1.5, 2.5]
  assert moving_average([3, 5, 7, 2, 8], 4) == [3.0, 4.0, 5.0, 4.25, 5.5]
output: 
  def moving_average(data_points, window):
      if window > len(data_points):
          return []
      moving_average = []
      for index in range(len(data_points)):
          start = max(0, index - window + 1)
          window_data = data_points[start:index + 1]
          average = sum(window_data) / len(window_data)
          moving_average.append(average)
      return moving_average
  