input: Write a function to compute the moving average of time-series data points given a window size. The function should return a list of moving averages for each point in the data. If the window size is greater than the length of the data, the function should return an empty list.
  def moving_average(data_points, window):
      if window > len(data_points):
          return []
      moving_averages = []
      for index in range(len(data_points)):
          start = 0 if index - window + 1 < 0 else index - window + 1
          window_data = data_points[start:index + 1]
          average = sum(window_data) / len(window_data)
          moving_averages.append(average)
      return moving_averages
  
  window = 3
  time_series = [3, 5, 7, 2, 8, 10, 11, 65, 72, 81, 99, 100, 150]
  assert moving_average(time_series, window) == [3.0, 4.0, 5.0, 4.666666666666667, 5.666666666666667, 6.666666666666667, 9.666666666666666, 28.666666666666668, 49.333333333333336, 72.66666666666667, 84.0, 93.33333333333333, 116.33333333333333]
  assert moving_average([], 3) == []
  assert moving_average([1, 2, 3, 4], 5) == []
output: def moving_average(data_points, window):
      if window > len(data_points):
          return []
      moving_averages = []
      for index in range(len(data_points)):
          start = 0 if index - window + 1 < 0 else index - window + 1
          window_data = data_points[start:index + 1]
          average = sum(window_data) / len(window_data)
          moving_averages.append(average)
      return moving_averages