code: def median_of_means(arr, num_batches, axis=0):
      r"""
      The median of means of the given array.
  
      The array is split into the specified number of batches. The mean value
      of each batch is taken, then the median of the mean values is returned.
  
      Args:
          arr (tensor-like[float]): The 1-D array for which the median of means
              is determined
          num_batches (int): The number of batches to split the array into
  
      Returns:
          float: The median of means
      """
      batch_size = int(np.ceil(arr.shape[0] / num_batches))
      means = [
          qml.math.mean(arr[i * batch_size : (i + 1) * batch_size], 0)
          for i in range(num_batches)
      ]
  
      return np.median(means, axis=axis)
  
file_path: pennylane/pennylane/shadows/classical_shadow.py
imports: import warnings
  from collections.abc import Iterable
  from string import ascii_letters
  import numpy
  import pennylane
label_desc: Use image node_id 2 for calling a global function with example usage: median_of_means(arr, num_batches, axis) and returns: np