pmdarima.datasets.load_woolyrnq

pmdarima.datasets.load_woolyrnq(as_series=False, dtype=<class 'numpy.float64'>)[source][source]

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.

Returns:

rslt : array-like, shape=(n_samples,)

The woolyrnq dataset. There are 119 observations.

Notes

This is quarterly data, so m should be set to 4 when using in a seasonal context.

References

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

Examples using pmdarima.datasets.load_woolyrnq

Dataset loading

Dataset loading