code: def rmspe(actual, predicted):
      
      
      actual = np.array(actual)
      predicted = np.array(predicted)
      zeros = actual == 0
      actual = actual[~zeros]
      predicted = predicted[~zeros]
      return np.sqrt(np.sum(np.power((actual - predicted) / actual, 2)) / len(actual))
docs: Computes the root mean square percentage error between two lists
      of numbers. Ignores elements where actual[n] == 0.
      
      Parameters
      ----------
      actual : list of numbers, numpy array
               The ground truth value
      predicted : same type as actual
                  The predicted value
  
      Returns
      -------
      score : double
              The root mean squared percentage error between actual and predicted