code: def get_data_with_string_columns():
      file_path = fedot_project_root().joinpath(
          "test/data/data_with_mixed_column.csv"
      )
      df = pd.read_csv(file_path)
  
      task = Task(TaskTypesEnum.classification)
      input_data = InputData(
          idx=np.arange(len(df)),
          features=np.array(df[["mixed_column", "numerical_column"]]),
          target=np.array(df["target"]).reshape(-1, 1),
          task=task,
          data_type=DataTypesEnum.table,
      )
  
      return input_data
  
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 2 for calling a global function with example usage: get_data_with_string_columns() and returns: input_data