code: def test_adult_matches_old():
      """Tests Adult Income dataset matches original version."""
      X, y, _ = fetch_adult()
      X.race = X.race.cat.set_categories(["Non-white", "White"]).fillna(
          "Non-white"
      )
  
      adult = AdultDataset()
      adult = adult.convert_to_dataframe(de_dummy_code=True)[0].drop(
          columns=adult.label_names
      )
  
      assert_frame_equal(
          X.reset_index(drop=True),
          adult.reset_index(drop=True),
          check_dtype=False,
          check_categorical=False,
          check_like=True,
      )
  
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 11 for calling a global function with example usage: test_adult_matches_old() without return types