code: def test_usecols_dropcols_basic():
      """Tests various combinations of usecols and dropcols on a toy example."""
      assert basic(usecols=["X1"]).X.columns.tolist() == ["X1"]
      assert basic(usecols=["X1", "Z"]).X.columns.tolist() == [
          "X1",
          "Z",
      ]
  
      assert basic(dropcols=["X1"]).X.columns.tolist() == ["X2", "Z"]
      assert basic(dropcols=["X1", "Z"]).X.columns.tolist() == ["X2"]
  
      assert basic(
          usecols=["X1"], dropcols=["X2"]
      ).X.columns.tolist() == ["X1"]
      assert isinstance(
          basic(usecols=["X2"], dropcols=["X1", "X2"])[0], pd.DataFrame
      )
  
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 5 for calling a global function with example usage: test_usecols_dropcols_basic() without return types