code: def hourly_data_with_reg():
      df = generate_df_for_tests(
          freq="H",
          periods=24 * 7 * 8,
          train_start_date=datetime.datetime(2018, 1, 1),
          conti_year_origin=2018,
      )["df"]
      df["regressor"] = np.arange(len(df))
      return df
  
imports: import datetime
  import numpy
  import pandas
  import pytest
  from testfixtures import LogCapture
  import greykite.common.constants
  from greykite.common.testing_utils import generate_df_for_tests
  from greykite.sklearn.estimator.lag_based_estimator import LagBasedEstimator
  from greykite.sklearn.estimator.multistage_forecast_estimator import MultistageForecastEstimator
  from greykite.sklearn.estimator.multistage_forecast_estimator import MultistageForecastModelConfig
  from greykite.sklearn.estimator.simple_silverkite_estimator import SimpleSilverkiteEstimator
  from greykite.sklearn.uncertainty.uncertainty_methods import UncertaintyMethodEnum
label_desc: Use image node_id 3 for calling a global function with example usage: hourly_data_with_reg() and returns: df