code: def test_standardize_dataset_basic():
      """Tests standardize_dataset on a toy example."""
      dataset = basic()
      X, y = dataset
      X, y = dataset.X, dataset.y
      with pytest.raises(ValueError):
          X, y, sample_weight = dataset
      with pytest.raises(AttributeError):
          dataset.sample_weight
      assert isinstance(X, pd.DataFrame)
      assert isinstance(y, pd.Series)
      assert X.index.equals(y.index)
      assert X.shape == (3, 3)
  
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 1 for calling a global function with example usage: test_standardize_dataset_basic() without return types