code: def data_with_text_features_and_nans():
      """Generate tabular data with text features"""
      task = Task(TaskTypesEnum.classification)
      features = np.array(
          [
              np.nan,
              "",
              "that can be stated,",
              "is not the eternal",
              np.nan,
          ],
          dtype=object,
      )
  
      target = np.array([[0], [1], [0], [1], [0]])
      train_input = InputData(
          idx=np.array([0, 1, 2, 3, 4]),
          features=features,
          target=target,
          task=task,
          data_type=DataTypesEnum.text,
          supplementary_data=SupplementaryData(),
      )
  
      return train_input
  
imports: import numpy
  from fedot import Fedot
  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.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum
  from fedot.preprocessing.data_types import TYPE_TO_ID
label_desc: Use image node_id 9 for calling a global function with example usage: data_with_text_features_and_nans() and returns: train_input