code: def outputs_table_with_different_types():
      """Create datasets with different types of columns in predictions"""
      task = Task(TaskTypesEnum.regression)
      idx = [0, 1, 2]
      target = [1, 2, 10]
      data_info_first = SupplementaryData(
          col_type_ids={
              "features": np.array(
                  [TYPE_TO_ID[str], TYPE_TO_ID[float]]
              ),
              "target": np.array([TYPE_TO_ID[int]]),
          }
      )
      output_first = OutputData(
          idx=idx,
          features=None,
          predict=np.array(
              [["a", 1.1], ["b", 2], ["c", 3]], dtype=object
          ),
          task=task,
          target=target,
          data_type=DataTypesEnum.table,
          supplementary_data=data_info_first,
      )
  
      data_info_second = SupplementaryData(
          col_type_ids={
              "features": np.array([TYPE_TO_ID[float]]),
              "target": np.array([TYPE_TO_ID[int]]),
          }
      )
      output_second = OutputData(
          idx=idx,
          features=None,
          predict=np.array([[2.5], [2.1], [9.3]], dtype=float),
          task=task,
          target=target,
          data_type=DataTypesEnum.table,
          supplementary_data=data_info_second,
      )
  
      return [output_first, output_second]
  
file_path: FEDOT/test/unit/data/test_supplementary_data.py
imports: import numpy
  import pytest
  from fedot.core.data.data import OutputData
  from fedot.core.data.merge.data_merger import DataMerger
  from fedot.core.data.merge.supplementary_data_merger import SupplementaryDataMerger
  from fedot.core.data.supplementary_data import SupplementaryData
  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.tasks import Task, TaskTypesEnum
  from fedot.preprocessing.data_types import TYPE_TO_ID
  from test.unit.data.test_data_merge import unequal_outputs_table
  from test.unit.tasks.test_regression import get_synthetic_regression_data
label_desc: Use image node_id 1 for calling a global function with example usage: outputs_table_with_different_types() and returns: list