code: def load_demo_dataset(version: str = "latest") -> pd.Series:
      """
      Load demo data set with monthly expenditure ($AUD) on corticosteroid drugs that
      the Australian health system had between 1991 and 2008. Obtained from the book:
      Forecasting: Principles and Practice by Rob J Hyndman and George Athanasopoulos.
      Index is set to datetime with monthly frequency and sorted.
  
      Parameters
      ----------
      version: str, default `'latest'`
          Version of the dataset to fetch. If 'latest', the lastest version will be
          fetched (the one in the main branch). For a list of available versions,
          see the repository branches.
  
      Returns
      -------
      df: pandas Series
          Dataset.
  
      """
  
      version = "main" if version == "latest" else f"{version}"
  
      url = (
          f"https://raw.githubusercontent.com/JoaquinAmatRodrigo/skforecast-datasets/{version}/"
          "data/h2o.csv"
      )
  
      df = pd.read_csv(url, sep=",", header=0, names=["y", "datetime"])
      df["datetime"] = pd.to_datetime(df["datetime"], format="%Y-%m-%d")
      df = df.set_index("datetime")
      df = df.asfreq("MS")
      df = df["y"]
      df = df.sort_index()
  
      return df
  
label_desc: Use image node_id 2 for calling a global function with example usage: load_demo_dataset(version) and returns: df