code: def get_data(directory: str, group: str, train: bool = True):
      Y_df, X_df, _ = EPF.load(directory, group)
      Y_df = Y_df.merge(X_df, how="left", on=["unique_id", "ds"])
      Y_df = Y_df.drop(["day_0", "week_day"], 1)
  
      horizon = 24 * 7
      Y_df = (
          Y_df.groupby("unique_id")
          .tail(7 * horizon)
          .reset_index(drop=True)
      )
      Y_df_test = Y_df.groupby("unique_id").tail(horizon)
      Y_df = Y_df.drop(Y_df_test.index)
  
      if train:
          return Y_df
  
      return Y_df_test
  
imports: import fire
  import pandas
  from neuralforecast.data.datasets.epf import EPF
label_desc: Use image node_id 1 for calling a global function with example usage: get_data(directory, group, train) and returns: Y_df_test, Y_df