code: def test_imputation_with_binary_correct():
      """
      Check if SimpleImputer can process mixed data with both numerical and categorical
      features correctly. Moreover, check if the imputer swaps the columns (it shouldn't)
      """
      nan_data = get_nan_binary_data(
          task=Task(TaskTypesEnum.classification)
      )
  
      # Create node with imputation operation
      imputation_node = PipelineNode("simple_imputation")
      imputation_node.fit(nan_data)
      predicted = imputation_node.predict(nan_data)
  
      assert np.isclose(predicted.predict[1, 0], 1.75)
      assert predicted.predict[1, 1] == "1"
      assert np.isclose(predicted.predict[1, 2], 1)
  
imports: import os
  import numpy
  import pytest
  from examples.simple.classification.classification_with_tuning import get_classification_dataset
  from examples.simple.regression.regression_with_tuning import get_regression_dataset
  from examples.simple.time_series_forecasting.gapfilling import generate_synthetic_data
  from fedot.core.data.data import InputData
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.data.supplementary_data import SupplementaryData
  from fedot.core.operations.evaluation.operation_implementations.data_operations.sklearn_imbalanced_class import ResampleImplementation
  from fedot.core.operations.evaluation.operation_implementations.data_operations.sklearn_transformations import ImputationImplementation
  from fedot.core.operations.evaluation.operation_implementations.data_operations.ts_transformations import CutImplementation, LaggedTransformationImplementation
  from fedot.core.operations.operation_parameters import OperationParameters
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.operation_types_repository import OperationTypesRepository
  from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
  from fedot.preprocessing.data_types import TYPE_TO_ID
  from test.unit.preprocessing.test_preprocessing_through_api import data_with_only_categorical_features
label_desc: Use image node_id 22 for calling a global function with example usage: test_imputation_with_binary_correct() without return types