code: def make_categorical(n, rstate, choices=None, nunique=None, **kwargs):
      kwargs.pop("args", None)
      if nunique is not None:
          cat_len = len(str(nunique))
          choices = [str(x + 1).zfill(cat_len) for x in range(nunique)]
      else:
          choices = choices or names
      return pd.Categorical.from_codes(
          rstate.randint(0, len(choices), size=n), choices
      )
  
imports: from __future__ import annotations
  import re
  import string
  from dataclasses import asdict, dataclass, field
  from typing import Any, Callable, cast
  import numpy
  import pandas
  from dask.dataframe._compat import PANDAS_GE_220
  from dask.dataframe._pyarrow import is_object_string_dtype
  from dask.dataframe.core import tokenize
  from dask.dataframe.io.io import from_map
  from dask.dataframe.io.utils import DataFrameIOFunction
  from dask.utils import random_state_data
label_desc: Use image node_id 5 for calling a global function with example usage: make_categorical(n, rstate, choices, nunique) and returns: pd