code: def ca_hourly_electricity_data():
      """This dataset contains energy consumption of the entire region in southern CA served by the SDGE
      (San Diego Gas and electric) utility in the year of 2018.
  
      Sources: https://github.com/pratha19/Hourly_Energy_Consumption_Prediction
      """
      test_file = (
          importlib_resources.files("tests")
          / "resources/hourly1418CA_2018.csv"
      )
      df = pd.read_csv(
          test_file,
          parse_dates=["Dates", "Date"],
      )
  
      # train_df = df[df['Date'] < '2018-07-01']
      # test_df = df[df['Date'] >= '2018-07-01']
  
      return df
  
file_path: orbit/tests/conftest.py
imports: import pytest
  import pandas
  import numpy
  import importlib_resources
  from copy import deepcopy
  from orbit.utils.simulation import make_trend, make_seasonality, make_regression
label_desc: Use image node_id 8 for calling a global function with example usage: ca_hourly_electricity_data() and returns: df