code: def _stats(arr, percentiles=(2, 98), **kwargs):
      
      sample, edges = np.histogram(arr[~arr.mask], **kwargs)
      return {
          "pc": np.percentile(arr[~arr.mask], percentiles).astype(arr.dtype).tolist(),
          "min": arr.min().item(),
          "max": arr.max().item(),
          "std": arr.std().item(),
          "histogram": [sample.tolist(), edges.tolist()],
      }
docs: Calculate array statistics.
  
      Attributes
      ----------
      arr: numpy ndarray
          Input array data to get the stats from.
      percentiles: tuple, optional
          Tuple of Min/Max percentiles to compute.
      kwargs: dict, optional
          These will be passed to the numpy.histogram function.
  
      Returns
      -------
      dict
          numpy array statistics: percentiles, min, max, stdev, histogram
  
          e.g.
          {
              'pc': [38, 147],
              'min': 20,
              'max': 180,
              'std': 28.123562304138662,
              'histogram': [
                  [1625, 219241, 28344, 15808, 12325, 10687, 8535, 7348, 4656, 1208],
                  [20.0, 36.0, 52.0, 68.0, 84.0, 100.0, 116.0, 132.0, 148.0, 164.0, 180.0]
              ]
          }