code: def create_multi_clf_examples_from_excel(
      file_path: str, return_df: bool = False
  ):
      """Return dataframe from excel file or path to the csv file"""
      df = pd.read_excel(file_path, engine="openpyxl")
      train, test = split_data(df)
      file_dir_name = file_path.replace(".", "/").split("/")[-2]
      file_csv_name = f"{file_dir_name}.csv"
      directory_names = ["examples", "data", file_dir_name]
  
      # Check does obtained directory exist or not
      ensure_directory_exists(directory_names)
      if return_df:
          # Need to return dataframe and path to the file in csv format
          path = os.path.join(
              directory_names[0],
              directory_names[1],
              directory_names[2],
              file_csv_name,
          )
          full_file_path = os.path.join(str(fedot_project_root()), path)
          save_file_to_csv(df, full_file_path)
          return df, full_file_path
      else:
          # Need to return only paths to the files with train and test data
          (
              full_train_file_path,
              full_test_file_path,
          ) = get_split_data_paths(directory_names)
          save_file_to_csv(train, full_train_file_path)
          save_file_to_csv(train, full_test_file_path)
          return full_train_file_path, full_test_file_path
  
file_path: FEDOT/examples/simple/classification/multiclass_prediction.py
imports: import datetime
  import os
  import pandas
  from golem.utilities.requirements_notificator import warn_requirement
  from datetime import timedelta
  from fedot.core.composer.composer_builder import ComposerBuilder
  from fedot.core.pipelines.pipeline_composer_requirements import PipelineComposerRequirements
  from fedot.core.data.data import InputData
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.repository.operation_types_repository import OperationTypesRepository
  from fedot.core.repository.metrics_repository import ClassificationMetricsEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum
  from fedot.core.utils import ensure_directory_exists, fedot_project_root, get_split_data_paths, probs_to_labels, save_file_to_csv, split_data
  from sklearn.metrics import roc_auc_score
  from fedot.core.utils import set_random_seed
  from pathlib import Path
label_desc: Use image node_id 1 for calling a global function with example usage: create_multi_clf_examples_from_excel(file_path, return_df) and returns: df,  full_file_path, full_train_file_path,  full_test_file_path