Elizaveta Lutsenko · @LizLutsenko · Operations NPA · c11ba628 · c11ba628 · c11ba628
--- a/fedot/core/data/multi_modal.py
+++ b/fedot/core/data/multi_modal.py
+   except ValueError:
+       return False
+
+
+def prepare_multimodal_text_data(dataframe: pd.DataFrame, text_columns: List[str]) -> dict:
+   """ Prepares MultiModal text data in a form of dictionary
+
+   :param dataframe: pandas DataFrame to process
+   :param text_columns: list of text columns names
+
+   :return multimodal_text_data: dictionary with numpy arrays of text data
+   """
+   multi_modal_text_data = {}
+
+   for column in text_columns:
+
--- a/examples/advanced/multimodal_text_num_example.py
+++ b/examples/advanced/multimodal_text_num_example.py
-
-   data = MultiModalData({
-       'data_source_table': data_num,
-       'data_source_text': data_text
-   })
-
-   return data
-
-
-def run_multi_modal_example(files_path: str, is_visualise=True) -> float:
+def run_multi_modal_example(file_path: str, is_visualise=True) -> float:
   task = Task(TaskTypesEnum.classification)
-
-   data = prepare_multi_modal_data(files_path, task)
+   path = Path(fedot_project_root(), file_path)
+   data = MultiModalData.from_csv(file_path=path, task=task, target_columns='variety', index_col=None)