code: def test_numerical_column_with_string_nans():
      """
      A table is generated in which one column contains numeric data along with the
      characters '?' and 'x'. These cells replace the nan. This column must be removed
      from the table.
      """
      input_data = get_data_with_string_columns()
  
      types_corr = TableTypesCorrector()
      # Set maximum allowed unique classes in categorical column
      types_corr.categorical_max_uniques_th = 5
      data = types_corr.convert_data_for_fit(input_data)
  
      n_rows, n_cols = data.features.shape
      assert n_cols == 1
  
imports: import numpy
  import pandas
  from golem.core.log import default_log
  from fedot.core.data.data import InputData
  from fedot.core.data.data_split import train_test_data_setup
  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.core.utils import fedot_project_root
  from fedot.preprocessing.data_types import TYPE_TO_ID
  from fedot.preprocessing.data_types import TableTypesCorrector, apply_type_transformation
  from fedot.preprocessing.structure import DEFAULT_SOURCE_NAME
  from test.unit.preprocessing.test_pipeline_preprocessing import correct_preprocessing_params, data_with_mixed_types_in_each_column
label_desc: Use image node_id 8 for calling a global function with example usage: test_numerical_column_with_string_nans() without return types