code: def pandas_dummy(header):
      ratings_dict = {
          header["col_user"]: [1, 1, 1, 1, 2, 2, 2, 2, 2, 2],
          header["col_item"]: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
          header["col_rating"]: [
              1.0,
              2.0,
              3.0,
              4.0,
              5.0,
              1.0,
              2.0,
              3.0,
              4.0,
              5.0,
          ],
      }
      df = pd.DataFrame(ratings_dict)
      return df
  
imports: import calendar
  import datetime
  import os
  from pathlib import Path
  from tempfile import TemporaryDirectory
  import numpy
  import pandas
  import pytest
  from sklearn.model_selection import train_test_split
  from recommenders.utils.constants import DEFAULT_USER_COL, DEFAULT_ITEM_COL, DEFAULT_RATING_COL, DEFAULT_TIMESTAMP_COL
  from recommenders.datasets.python_splitters import numpy_stratified_split
  from recommenders.datasets.python_splitters import python_chrono_split
  from recommenders.utils.spark_utils import start_or_get_spark
label_desc: Use image node_id 8 for calling a global function with example usage: pandas_dummy(header) and returns: df