code: def get_small_cat_data():
      """Generate tabular data with categorical features."""
      features = np.array(
          [
              ["a", "qq", 0.5],
              ["b", "pp", 1],
              ["c", np.nan, 3],
              ["d", "oo", 3],
              ["d", "oo", 3],
              ["d", "oo", 3],
              ["d", "oo", 3],
              ["d", "oo", 3],
          ],
          dtype=object,
      )
      target = np.array([0, 0, 0, 0, 1, 1, 1, 1])
      input_data = InputData(
          idx=np.arange(features.shape[0]),
          features=features,
          target=target,
          data_type=DataTypesEnum.table,
          task=Task(TaskTypesEnum.classification),
      )
      input_data = DataPreprocessor().obligatory_prepare_for_fit(
          input_data
      )
      return input_data
  
file_path: FEDOT/test/unit/api/test_api_safety.py
imports: import numpy
  from fedot.api.api_utils.api_data import ApiDataProcessor
  from fedot.api.api_utils.input_analyser import InputAnalyser
  from fedot import Fedot
  from fedot.core.data.data import InputData
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import TaskTypesEnum, Task
  from fedot.preprocessing.preprocessing import DataPreprocessor
  from test.integration.api.test_main_api import TESTS_MAIN_API_DEFAULT_PARAMS
label_desc: Use image node_id 2 for calling a global function with example usage: get_small_cat_data() and returns: input_data