code: def test_lawschool_matches_old():
      """Tests Law School GPA dataset matches original version."""
      X, y = fetch_lawschool_gpa(numeric_only=True)
  
      law = LawSchoolGPADataset()
      law = law.convert_to_dataframe()[0].drop(columns=law.label_names)
  
      assert_array_equal(minmax_scale(X), law)
  
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 18 for calling a global function with example usage: test_lawschool_matches_old() without return types