code: def test_data_from_csv_load_correctly():
      """
      Check if data obtained from csv files processed correctly for fit and
      predict stages when for predict stage there is no target column in csv file
      """
      task = Task(TaskTypesEnum.regression)
      project_root = fedot_project_root()
      path_train = "test/data/empty_target_tables/train.csv"
      path_test = "test/data/empty_target_tables/test.csv"
      full_path_train = project_root.joinpath(path_train)
      full_path_test = project_root.joinpath(path_test)
  
      data_loader = ApiDataProcessor(task)
      train_input = data_loader.define_data(
          features=full_path_train, target="class"
      )
      test_input = data_loader.define_data(
          features=full_path_test, is_predict=True
      )
  
      assert train_input.target.shape == (14, 1)
      assert test_input.target is None
  
file_path: FEDOT/test/unit/api/test_main_api.py
imports: import numpy
  import pandas
  import pytest
  from fedot import Fedot
  from fedot.api.api_utils.api_data import ApiDataProcessor
  from fedot.core.data.data import InputData
  from fedot.core.data.multi_modal import MultiModalData
  from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
  from fedot.core.utils import fedot_project_root
  from test.data.datasets import data_with_binary_features_and_categorical_target, get_dataset, load_categorical_multidata, get_split_data_paths, get_split_data, get_multimodal_ts_data, load_categorical_unimodal
label_desc: Use image node_id 2 for calling a global function with example usage: test_data_from_csv_load_correctly() without return types