code: def test_multiindex_cols():
      """Tests DataFrame with MultiIndex columns."""
      cols = pd.MultiIndex.from_arrays(
          [["X", "X", "y", "Z"], [1, 2, "", ""]]
      )
      df = pd.DataFrame(
          [[1, 2, 3, "a"], [5, 6, 7, "b"], [None, 10, 11, "c"]],
          columns=cols,
      )
      multiindex = standardize_dataset(df, prot_attr="Z", target="y")
      assert multiindex.X.index.names == ["Z"]
      assert multiindex.y.name == "y"
      assert multiindex.X.columns.equals(cols.drop("y", level=0))
  
imports: from functools import partial
  import numpy
  from numpy.testing import assert_array_equal
  import pandas
  from pandas.api.types import is_numeric_dtype
  from pandas.testing import assert_frame_equal
  import pytest
  from sklearn.compose import make_column_transformer
  from sklearn.preprocessing import OneHotEncoder, minmax_scale
  from aif360.datasets import AdultDataset, GermanDataset, CompasDataset, LawSchoolGPADataset, MEPSDataset19, MEPSDataset20, MEPSDataset21
  from aif360.sklearn.datasets import standardize_dataset, NumericConversionWarning, fetch_adult, fetch_bank, fetch_german, fetch_compas, fetch_lawschool_gpa, fetch_meps
label_desc: Use image node_id 9 for calling a global function with example usage: test_multiindex_cols() without return types