code: def test_categorical_set_index(shuffle_method):
      df = pd.DataFrame({"x": [1, 2, 3, 4], "y": ["a", "b", "b", "c"]})
      df["y"] = pd.Categorical(
          df["y"], categories=["a", "b", "c"], ordered=True
      )
      a = dd.from_pandas(df, npartitions=2)
  
      with dask.config.set(scheduler="sync"):
          b = a.set_index("y", npartitions=a.npartitions)
          d1, d2 = b.get_partition(0), b.get_partition(1)
          assert list(d1.index.compute()) == ["a"]
          assert list(sorted(d2.index.compute())) == ["b", "b", "c"]
  
          b = a.set_index(a.y, npartitions=a.npartitions)
          d1, d2 = b.get_partition(0), b.get_partition(1)
          assert list(d1.index.compute()) == ["a"]
          assert list(sorted(d2.index.compute())) == ["b", "b", "c"]
  
          b = a.set_index(
              "y", divisions=["a", "b", "c"], npartitions=a.npartitions
          )
          d1, d2 = b.get_partition(0), b.get_partition(1)
          assert list(d1.index.compute()) == ["a"]
          assert list(sorted(d2.index.compute())) == ["b", "b", "c"]
  
imports: from __future__ import annotations
  import contextlib
  import operator
  import warnings
  import numpy
  import pandas
  import pytest
  import dask
  import dask.dataframe
  from dask.dataframe import _compat
  from dask.dataframe._compat import PANDAS_GE_150, PANDAS_GE_200, PANDAS_GE_210, tm
  from dask.dataframe._pyarrow import to_pyarrow_string
  from dask.dataframe.core import _concat
  from dask.dataframe.utils import assert_eq, clear_known_categories, get_string_dtype, make_meta, pyarrow_strings_enabled
label_desc: Use image node_id 6 for calling a global function with example usage: test_categorical_set_index(shuffle_method) without return types