code: def zscore(arr):
      
      arr = arr - np.mean(arr)
      std = np.std(arr)
      if std != 0:
          arr /= std
      return arr
docs: Return arr normalized with mean 0 and unit variance.
  
      If the input has 0 variance, the result will also have 0 variance.
  
      Parameters
      ----------
      arr : array-like
  
      Returns
      -------
      zscore : array-like
  
      Examples
      --------
      Compute the z score for a small array:
  
      >>> result = zscore([1, 0])
      >>> result
      array([ 1., -1.])
      >>> np.mean(result)
      0.0
      >>> np.std(result)
      1.0
  
      Does not re-scale in case the input is constant (has 0 variance):
  
      >>> zscore([1, 1])
      array([ 0., 0.])