# -*- coding: utf-8 -*-
#
# Author: Taylor Smith <taylor.smith@alkaline-ml.com>
#
# This is the lynx dataset found in R.
from __future__ import absolute_import
import numpy as np
import pandas as pd
__all__ = [
'load_lynx'
]
[docs]def load_lynx(as_series=False):
"""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.
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
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 # noqa: E501
Returns
-------
lynx : array-like, shape=(n_samples,)
The lynx dataset. There are 114 observations.
"""
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])
# Set the index if necessary
if as_series:
return pd.Series(rslt, index=range(1821, 1935))
return rslt