code: def robust_zscore(x: pd.Series, zscore=False):
      """Robust ZScore Normalization
  
      Use robust statistics for Z-Score normalization:
          mean(x) = median(x)
          std(x) = MAD(x) * 1.4826
  
      Reference:
          https://en.wikipedia.org/wiki/Median_absolute_deviation.
      """
      x = x - x.median()
      mad = x.abs().median()
      x = np.clip(x / mad / 1.4826, -3, 3)
      if zscore:
          x -= x.mean()
          x /= x.std()
      return x
  
file_path: qlib/qlib/utils/data.py
imports: from copy import deepcopy
  from typing import List, Union
  import pandas
  import numpy
label_desc: Use image node_id 1 for calling a global function with example usage: robust_zscore(x, zscore) and returns: x