code: def test_compas_matches_old():
      """Tests COMPAS Recidivism dataset matches original version."""
      X, y = fetch_compas()
      X.race = X.race.cat.set_categories(
          ["Not Caucasian", "Caucasian"]
      ).fillna("Not Caucasian")
  
      compas = CompasDataset()
      compas = compas.convert_to_dataframe(de_dummy_code=True)[0].drop(
          columns=compas.label_names
      )
  
      assert_frame_equal(
          X.reset_index(drop=True),
          compas.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 16 for calling a global function with example usage: test_compas_matches_old() without return types