code: def test_dropna_basic():
      """Tests dropna on a toy example."""
      basic_dropna = partial(
          standardize_dataset,
          df=df,
          prot_attr="Z",
          target="y",
          dropna=True,
      )
      assert basic_dropna().X.shape == (2, 3)
      assert basic(dropcols=["X1"]).X.shape == (3, 2)
  
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 6 for calling a global function with example usage: test_dropna_basic() without return types