code: def test_merging_categorical_columns():
      try:
          from dask.dataframe.dispatch import (  # noqa: F401
              union_categoricals_dispatch,
          )
      except ImportError:
          pytest.skip(
              "need a version of dask that has union_categoricals_dispatch"
          )
  
      df_1 = cudf.DataFrame(
          {"id_1": [0, 1, 2, 3], "cat_col": ["a", "b", "f", "f"]}
      )
  
      ddf_1 = dgd.from_cudf(df_1, npartitions=2)
  
      ddf_1 = dd.categorical.categorize(ddf_1, columns=["cat_col"])
  
      df_2 = cudf.DataFrame(
          {"id_2": [111, 112, 113], "cat_col": ["g", "h", "f"]}
      )
  
      ddf_2 = dgd.from_cudf(df_2, npartitions=2)
  
      ddf_2 = dd.categorical.categorize(ddf_2, columns=["cat_col"])
      expected = cudf.DataFrame(
          {
              "id_1": [2, 3],
              "cat_col": cudf.Series(
                  ["f", "f"],
                  dtype=cudf.CategoricalDtype(
                      categories=["a", "b", "f", "g", "h"],
                      ordered=False,
                  ),
              ),
              "id_2": [113, 113],
          }
      )
      dd.assert_eq(ddf_1.merge(ddf_2), expected)
  
imports: import random
  import cupy
  import numpy
  import pandas
  import pytest
  from packaging import version
  import dask
  from dask import dataframe
  from dask.dataframe.core import make_meta, meta_nonempty
  from dask.utils import M
  import cudf
  import dask_cudf
label_desc: Use image node_id 48 for calling a global function with example usage: test_merging_categorical_columns() without return types