code: def categorical_column_to_series(
      col: Column,
  ) -> tuple[pd.Series, Any]:
      """
      Convert a column holding categorical data to a pandas Series.
  
      Parameters
      ----------
      col : Column
  
      Returns
      -------
      tuple
          Tuple of pd.Series holding the data and the memory owner object
          that keeps the memory alive.
      """
      categorical = col.describe_categorical
  
      if not categorical["is_dictionary"]:
          raise NotImplementedError(
              "Non-dictionary categoricals not supported yet"
          )
  
      cat_column = categorical["categories"]
      if hasattr(cat_column, "_col"):
          # Item "Column" of "Optional[Column]" has no attribute "_col"
          # Item "None" of "Optional[Column]" has no attribute "_col"
          categories = np.array(cat_column._col)  # type: ignore[union-attr]
      else:
          raise NotImplementedError(
              "Interchanging categorical columns isn't supported yet, and our "
              "fallback of using the `col._col` attribute (a ndarray) failed."
          )
      buffers = col.get_buffers()
  
      codes_buff, codes_dtype = buffers["data"]
      codes = buffer_to_ndarray(
          codes_buff, codes_dtype, offset=col.offset, length=col.size()
      )
  
      # Doing module in order to not get ``IndexError`` for
      # out-of-bounds sentinel values in `codes`
      if len(categories) > 0:
          values = categories[codes % len(categories)]
      else:
          values = codes
  
      cat = pd.Categorical(
          values,
          categories=categories,
          ordered=categorical["is_ordered"],
      )
      data = pd.Series(cat)
  
      data = set_nulls(data, col, buffers["validity"])
      return data, buffers
  
imports: from __future__ import annotations
  import ctypes
  import re
  from typing import Any, overload
  import numpy
  from pandas.compat._optional import import_optional_dependency
  from pandas.errors import SettingWithCopyError
  import pandas
  from pandas.core.interchange.dataframe_protocol import Buffer, Column, ColumnNullType, DataFrame, DtypeKind
  from pandas.core.interchange.utils import ArrowCTypes, Endianness
label_desc: Use image node_id 5 for calling a global function with example usage: categorical_column_to_series(col) and returns: data,  buffers