code: def preprocess_dates(df):
      # Make integer Year,Month,Day columns instead of Date
      dates = np.array(
          [[int(v) for v in s.split("-")] for s in df["Date"]]
      )
      df = df.drop(["Date"], axis=1)
      df["Year"] = dates[:, 0]
      df["Month"] = dates[:, 1]
      df["Day"] = dates[:, 2]
      return df
  
file_path: ludwig/ludwig/datasets/loaders/rossman_store_sales.py
imports: import calendar
  import os
  from typing import List
  import numpy
  import pandas
  from ludwig.datasets.loaders.dataset_loader import DatasetLoader
label_desc: Use image node_id 1 for calling a global function with example usage: preprocess_dates(df) and returns: df