code: def load_woolyrnq(as_series=False, dtype=DTYPE):
      """Quarterly production of woollen yarn in Australia.
  
      This time-series records the quarterly production (in tonnes) of woollen
      yarn in Australia between Mar 1965 and Sep 1994.
  
      Parameters
      ----------
      as_series : bool, optional (default=False)
          Whether to return a Pandas series. If True, the index will be set to
          the observed years/quarters. 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.
  
      Examples
      --------
      >>> from pmdarima.datasets import load_woolyrnq
      >>> load_woolyrnq()
      array([6172, 6709, 6633, 6660, 6786, 6800, 6730, 6765, 6720, 7133, 6946,
             7095, 7047, 6757, 6915, 6921, 7064, 7206, 7190, 7402, 7819, 7300,
             7105, 7259, 7001, 7475, 6840, 7061, 5845, 7529, 7819, 6943, 5714,
             6556, 7045, 5947, 5463, 6127, 5540, 4235, 3324, 4793, 5906, 5834,
             5240, 5458, 5505, 5002, 3999, 4826, 5318, 4681, 4442, 5305, 5466,
             4995, 4573, 5081, 5696, 5079, 4373, 4986, 5341, 4800, 4161, 5007,
             5464, 5127, 4240, 5338, 5129, 4437, 3642, 4602, 5524, 4895, 4380,
             5186, 6080, 5588, 5009, 5663, 6540, 6262, 5169, 5819, 6339, 5981,
             4766, 5976, 6590, 5590, 5135, 5762, 6077, 5882, 4247, 5264, 5146,
             4868, 4329, 4869, 5127, 4868, 3827, 4987, 5222, 4928, 3930, 4469,
             4954, 4752, 3888, 4588, 5309, 4732, 4837, 6135, 6396])
  
      >>> load_woolyrnq(True).head()
      Q1 1965    6172
      Q2 1965    6709
      Q3 1965    6633
      Q4 1965    6660
      Q1 1966    6786
      dtype: int64
  
      Notes
      -----
      This is quarterly data, so *m* should be set to 4 when using in a seasonal
      context.
  
      References
      ----------
      .. [1] https://www.rdocumentation.org/packages/forecast/versions/8.1/topics/woolyrnq
  
      Returns
      -------
      rslt : array-like, shape=(n_samples,)
          The woolyrnq dataset. There are 119 observations.
      """  # noqa: E501
      rslt = np.array(
          [
              6172,
              6709,
              6633,
              6660,
              6786,
              6800,
              6730,
              6765,
              6720,
              7133,
              6946,
              7095,
              7047,
              6757,
              6915,
              6921,
              7064,
              7206,
              7190,
              7402,
              7819,
              7300,
              7105,
              7259,
              7001,
              7475,
              6840,
              7061,
              5845,
              7529,
              7819,
              6943,
              5714,
              6556,
              7045,
              5947,
              5463,
              6127,
              5540,
              4235,
              3324,
              4793,
              5906,
              5834,
              5240,
              5458,
              5505,
              5002,
              3999,
              4826,
              5318,
              4681,
              4442,
              5305,
              5466,
              4995,
              4573,
              5081,
              5696,
              5079,
              4373,
              4986,
              5341,
              4800,
              4161,
              5007,
              5464,
              5127,
              4240,
              5338,
              5129,
              4437,
              3642,
              4602,
              5524,
              4895,
              4380,
              5186,
              6080,
              5588,
              5009,
              5663,
              6540,
              6262,
              5169,
              5819,
              6339,
              5981,
              4766,
              5976,
              6590,
              5590,
              5135,
              5762,
              6077,
              5882,
              4247,
              5264,
              5146,
              4868,
              4329,
              4869,
              5127,
              4868,
              3827,
              4987,
              5222,
              4928,
              3930,
              4469,
              4954,
              4752,
              3888,
              4588,
              5309,
              4732,
              4837,
              6135,
              6396,
          ]
      ).astype(dtype)
  
      if not as_series:
          return rslt
  
      # Otherwise we want a series and have to cleverly create the index
      # (with quarters, and we don't want Q4 in 1994)
      index = [
          "Q%i %i" % (i + 1, year)
          for year in range(1965, 1995)
          for i in range(4)
      ][
          :-1
      ]  # trim off the last one.
  
      return pd.Series(rslt, index=index)
  
label_desc: Use image node_id 1 for calling a global function with example usage: load_woolyrnq(as_series, dtype) and returns: pd, rslt