code: def _merge_categorical(discrete_fs: List[np.ndarray]) -> Any:
      """Merges a list of categorical features into a single categorical feature."""
      if not discrete_fs:
          return None
      operand_list = []
      for i in range(2 * len(discrete_fs) - 1):
          if i % 2 == 0:
              operand_list.append(discrete_fs[i // 2].astype(bytes))
          else:
              operand_list.append(b":")  # use ':' to join values
      return functools.reduce(np.char.add, operand_list)
  
imports: import functools
  import itertools
  import math
  from typing import Any, List, Optional, Tuple, Union
  import uuid
  import numpy
  import pandas
  import scipy.special
  import sklearn.neighbors
label_desc: Use image node_id 8 for calling a global function with example usage: _merge_categorical(discrete_fs) and returns: functools, None