code: def test_column_transformer_fit_transform_should_support_indexes(
      test_case: ColumnChooserTestCase,
  ):
      data_inputs = test_case.data_inputs
      expected_outputs = test_case.expected_outputs
      p = ColumnTransformer(
          test_case.column_transformer_tuple_list, test_case.n_dimension
      )
  
      p, outputs = p.fit_transform(data_inputs, expected_outputs)
  
      assert np.array_equal(
          outputs, test_case.expected_processed_outputs
      )
      actual_fitted_data = p[test_case.expected_step_key][
          "MultiplyBy2"
      ].fitted_data
      expected_fitted_data = test_case.expected_fitted_data
      assert_data_fitted_properly(
          actual_fitted_data, expected_fitted_data
      )
  
imports: import copy
  from typing import Any, Tuple
  import numpy
  import pytest
  from neuraxle.base import BaseStep
  from neuraxle.steps.column_transformer import ColumnTransformer
label_desc: Use image node_id 2 for calling a global function with example usage: test_column_transformer_fit_transform_should_support_indexes(test_case) without return types