code: def test_use_categorical(self, daskify):
      data = pd.Series(
          ["b", "c"],
          dtype=pd.api.types.CategoricalDtype(["c", "a", "b"]),
      )
      if daskify:
          data = dd.from_pandas(data, npartitions=2)
      a = dpp.LabelEncoder(use_categorical=False).fit(data)
      b = spp.LabelEncoder().fit(data)
      assert_estimator_equal(a, b, exclude={"dtype_"})
      assert a.dtype_ is None
  
      da.utils.assert_eq(a.transform(data), b.transform(data))
      a_trn = a.transform(data)
      b_trn = b.transform(data)
      da.utils.assert_eq(a_trn, b_trn)
      da.utils.assert_eq(
          a.inverse_transform(a_trn), b.inverse_transform(b_trn)
      )
  
imports: import dask
  import dask.array
  import dask.dataframe
  import numpy
  import pandas
  import pytest
  import sklearn.preprocessing
  from dask.array.utils import assert_eq
  import dask_ml.preprocessing
  from dask_ml.utils import assert_estimator_equal
label_desc: Use image node_id 9 for calling the TestLabelEncoder obj's underlying member method code with example usage: obj.test_use_categorical(daskify) without return types