code: def load_austres(as_series=False, dtype=DTYPE):
      """Quarterly residential data.
  
      Numbers (in thousands) of Australian residents measured quarterly from
      March 1971 to March 1994.
  
      Parameters
      ----------
      as_series : bool, optional (default=False)
          Whether to return a Pandas series. If False, will return a 1d
          numpy array.
  
      dtype : type, optional (default=np.float64)
          The type to return for the array. Default is np.float64, which is used
          throughout the package as the default type.
  
      Returns
      -------
      rslt : array-like, shape=(n_samples,)
          The austres vector.
  
      Examples
      --------
      >>> from pmdarima.datasets import load_austres
      >>> load_austres()
      np.array([13067.3, 13130.5, 13198.4, 13254.2, 13303.7, 13353.9,
                13409.3, 13459.2, 13504.5, 13552.6, 13614.3, 13669.5,
                13722.6, 13772.1, 13832.0, 13862.6, 13893.0, 13926.8,
                13968.9, 14004.7, 14033.1, 14066.0, 14110.1, 14155.6,
                14192.2, 14231.7, 14281.5, 14330.3, 14359.3, 14396.6,
                14430.8, 14478.4, 14515.7, 14554.9, 14602.5, 14646.4,
                14695.4, 14746.6, 14807.4, 14874.4, 14923.3, 14988.7,
                15054.1, 15121.7, 15184.2, 15239.3, 15288.9, 15346.2,
                15393.5, 15439.0, 15483.5, 15531.5, 15579.4, 15628.5,
                15677.3, 15736.7, 15788.3, 15839.7, 15900.6, 15961.5,
                16018.3, 16076.9, 16139.0, 16203.0, 16263.3, 16327.9,
                16398.9, 16478.3, 16538.2, 16621.6, 16697.0, 16777.2,
                16833.1, 16891.6, 16956.8, 17026.3, 17085.4, 17106.9,
                17169.4, 17239.4, 17292.0, 17354.2, 17414.2, 17447.3,
                17482.6, 17526.0, 17568.7, 17627.1, 17661.5])
  
      >>> load_austres(True).head()
      0    13067.3
      1    13130.5
      2    13198.4
      3    13254.2
      4    13303.7
      dtype: float64
  
      Notes
      -----
      This is quarterly data, so *m* should be set to 4 when using in a seasonal
      context.
  
      References
      ----------
      .. [1] P. J. Brockwell and R. A. Davis (1996)
             "Introduction to Time Series and Forecasting." Springer
      """
      rslt = np.array(
          [
              13067.3,
              13130.5,
              13198.4,
              13254.2,
              13303.7,
              13353.9,
              13409.3,
              13459.2,
              13504.5,
              13552.6,
              13614.3,
              13669.5,
              13722.6,
              13772.1,
              13832.0,
              13862.6,
              13893.0,
              13926.8,
              13968.9,
              14004.7,
              14033.1,
              14066.0,
              14110.1,
              14155.6,
              14192.2,
              14231.7,
              14281.5,
              14330.3,
              14359.3,
              14396.6,
              14430.8,
              14478.4,
              14515.7,
              14554.9,
              14602.5,
              14646.4,
              14695.4,
              14746.6,
              14807.4,
              14874.4,
              14923.3,
              14988.7,
              15054.1,
              15121.7,
              15184.2,
              15239.3,
              15288.9,
              15346.2,
              15393.5,
              15439.0,
              15483.5,
              15531.5,
              15579.4,
              15628.5,
              15677.3,
              15736.7,
              15788.3,
              15839.7,
              15900.6,
              15961.5,
              16018.3,
              16076.9,
              16139.0,
              16203.0,
              16263.3,
              16327.9,
              16398.9,
              16478.3,
              16538.2,
              16621.6,
              16697.0,
              16777.2,
              16833.1,
              16891.6,
              16956.8,
              17026.3,
              17085.4,
              17106.9,
              17169.4,
              17239.4,
              17292.0,
              17354.2,
              17414.2,
              17447.3,
              17482.6,
              17526.0,
              17568.7,
              17627.1,
              17661.5,
          ]
      ).astype(dtype)
  
      if as_series:
          return pd.Series(rslt)
      return rslt
  
label_desc: Use image node_id 1 for calling a global function with example usage: load_austres(as_series, dtype) and returns: rslt, pd