code: def _get_categories_agg(parts):
      res = defaultdict(list)
      res_ind = []
      for p in parts:
          for k, v in p[0].items():
              res[k].append(v)
          res_ind.append(p[1])
      res = {
          k: methods.concat(v, ignore_index=True).drop_duplicates()
          for k, v in res.items()
      }
      if res_ind[0] is None:
          return res, None
      return res, res_ind[0].append(res_ind[1:]).drop_duplicates()
  
imports: from __future__ import annotations
  from collections import defaultdict
  from numbers import Integral
  import pandas
  from pandas.api.types import is_scalar
  from tlz import partition_all
  from dask.base import compute_as_if_collection, tokenize
  from dask.dataframe import methods
  from dask.dataframe.accessor import Accessor
  from dask.dataframe.dispatch import categorical_dtype, categorical_dtype_dispatch, is_categorical_dtype
  from dask.dataframe.utils import AttributeNotImplementedError, clear_known_categories, has_known_categories
  from dask.highlevelgraph import HighLevelGraph
label_desc: Use image node_id 3 for calling a global function with example usage: _get_categories_agg(parts) and returns: res,  res_ind, res,  None