code: def test_transform_slices(self):
      names = self.data.index.names
      transformed_slices = self.grouping.transform_slices(
          self.data.values, lambda x, idx: x.mean(0), level=0  # noqa
      )
      expected = (
          self.data.reset_index()
          .groupby(names[0])[self.data.columns]
          .mean()
      )
      np.testing.assert_allclose(
          transformed_slices, expected.values, rtol=1e-12, atol=1e-25
      )
  
      if len(names) > 1:
          transformed_slices = self.grouping.transform_slices(
              self.data.values,
              lambda x, idx: x.mean(0),  # noqa
              level=1,
          )
          expected = (
              self.data.reset_index()
              .groupby(names[1])[self.data.columns]
              .mean()
          )
          np.testing.assert_allclose(
              transformed_slices,
              expected.values,
              rtol=1e-12,
              atol=1e-25,
          )
  
imports: from statsmodels.compat.pandas import assert_frame_equal, assert_series_equal
  import numpy
  from numpy.testing import assert_equal
  import pandas
  import pytest
  from scipy import sparse
  from statsmodels.tools.grouputils import dummy_sparse, Grouping, Group, combine_indices, group_sums
  from statsmodels.datasets import grunfeld, anes96
label_desc: Use image node_id 6 for calling the CheckGrouping obj's underlying member method code with example usage: obj.test_transform_slices() without return types