
    Dj                     2    d dl Zd dlZddlmZ dgZdefdZy)    N   )DTYPEload_woolyrnqFc                     t        j                  g d      j                  |      }| s|S t        dd      D cg c]  }t        d      D ]  }d|dz   |fz    c}}dd }t	        j
                  ||	      S c c}}w )
a   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.
    )wi  i5  i  i  i  i  iJ  im  i@  i  i"  i  i  ie  i  i	  i  i&  i  i    i  i  i[  iY  i3  i  i  i  ii  r   i  iR  i  i  i;  iW  i  i  i  i  i  i  i  ix  iR  i  i  i  i  i  iI  iZ  i  iZ  i  i  i  i@  i  i  iz  i  i  iA  i  iX    i  i  i	  iU  i:  i  i  i  i  iB  i  i  i  i  i  iv  i1  i  i  i]  i  iX  i  i  i  i  i  i  i  i  i    i  i  r   r	   i  i{  if  i@  iZ  iu  iZ  i  i0  i  i  i|  i  i  i  i  i     zQ%i %i   N)index)nparrayastyperangepdSeries)	as_seriesdtypersltyearir   s         ^C:\Crop_Prediction\Backend\crop-ai-system\venv\Lib\site-packages\pmdarima/datasets/woolyrnq.pyr   r      s    l 88  < "6%== 	@  $%q  	AE4=   
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