code: def load_lynx(as_series=False, dtype=DTYPE):
      """Annual numbers of lynx trappings for 1821–1934 in Canada.
  
      This time-series records the number of skins of predators (lynx) that were
      collected over several years by the Hudson's Bay Company. The dataset was
      taken from Brockwell & Davis (1991) and appears to be the series
      considered by Campbell & Walker (1977).
  
      Parameters
      ----------
      as_series : bool, optional (default=False)
          Whether to return a Pandas series. If True, the index will be set to
          the observed years. 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_lynx
      >>> load_lynx()
      array([ 269,  321,  585,  871, 1475, 2821, 3928, 5943, 4950, 2577,  523,
               98,  184,  279,  409, 2285, 2685, 3409, 1824,  409,  151,   45,
               68,  213,  546, 1033, 2129, 2536,  957,  361,  377,  225,  360,
              731, 1638, 2725, 2871, 2119,  684,  299,  236,  245,  552, 1623,
             3311, 6721, 4254,  687,  255,  473,  358,  784, 1594, 1676, 2251,
             1426,  756,  299,  201,  229,  469,  736, 2042, 2811, 4431, 2511,
              389,   73,   39,   49,   59,  188,  377, 1292, 4031, 3495,  587,
              105,  153,  387,  758, 1307, 3465, 6991, 6313, 3794, 1836,  345,
              382,  808, 1388, 2713, 3800, 3091, 2985, 3790,  674,   81,   80,
              108,  229,  399, 1132, 2432, 3574, 2935, 1537,  529,  485,  662,
             1000, 1590, 2657, 3396])
  
      >>> load_lynx(True).head()
      1821     269
      1822     321
      1823     585
      1824     871
      1825    1475
      dtype: int64
  
      Notes
      -----
      This is annual data and not seasonal in nature (i.e., :math:`m=1`)
  
      References
      ----------
      .. [1] Brockwell, P. J. and Davis, R. A. (1991)
             Time Series and Forecasting Methods. Second edition.
             Springer. Series G (page 557).
  
      .. [2] https://stat.ethz.ch/R-manual/R-devel/library/datasets/html/lynx.html
  
      Returns
      -------
      lynx : array-like, shape=(n_samples,)
          The lynx dataset. There are 114 observations.
      """  # noqa: E501
      rslt = np.array(
          [
              269,
              321,
              585,
              871,
              1475,
              2821,
              3928,
              5943,
              4950,
              2577,
              523,
              98,
              184,
              279,
              409,
              2285,
              2685,
              3409,
              1824,
              409,
              151,
              45,
              68,
              213,
              546,
              1033,
              2129,
              2536,
              957,
              361,
              377,
              225,
              360,
              731,
              1638,
              2725,
              2871,
              2119,
              684,
              299,
              236,
              245,
              552,
              1623,
              3311,
              6721,
              4254,
              687,
              255,
              473,
              358,
              784,
              1594,
              1676,
              2251,
              1426,
              756,
              299,
              201,
              229,
              469,
              736,
              2042,
              2811,
              4431,
              2511,
              389,
              73,
              39,
              49,
              59,
              188,
              377,
              1292,
              4031,
              3495,
              587,
              105,
              153,
              387,
              758,
              1307,
              3465,
              6991,
              6313,
              3794,
              1836,
              345,
              382,
              808,
              1388,
              2713,
              3800,
              3091,
              2985,
              3790,
              674,
              81,
              80,
              108,
              229,
              399,
              1132,
              2432,
              3574,
              2935,
              1537,
              529,
              485,
              662,
              1000,
              1590,
              2657,
              3396,
          ]
      ).astype(dtype)
  
      # Set the index if necessary
      if as_series:
          return pd.Series(rslt, index=range(1821, 1935))
      return rslt
  
label_desc: Use image node_id 1 for calling a global function with example usage: load_lynx(as_series, dtype) and returns: rslt, pd