Dataset loading

In this example, we demonstrate pyramid’s built-in toy datasets that can be used for benchmarking or experimentation. Pyramid has several built-in datasets that exhibit seasonality, non-stationarity, and other time series nuances.

Out:

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.]

Lynx series head:
1821     269.0
1822     321.0
1823     585.0
1824     871.0
1825    1475.0
dtype: float64

print(__doc__)

# Author: Taylor Smith <taylor.smith@alkaline-ml.com>

import pmdarima as pm

# #############################################################################
# You can load the datasets via load_<name>
lynx = pm.datasets.load_lynx()
print("Lynx array:")
print(lynx)

# You can also get a series, if you rather
print("\nLynx series head:")
print(pm.datasets.load_lynx(as_series=True).head())

# Several other datasets:
air_passengers = pm.datasets.load_airpassengers()
austres = pm.datasets.load_austres()
heart_rate = pm.datasets.load_heartrate()
wineind = pm.datasets.load_wineind()
woolyrnq = pm.datasets.load_woolyrnq()

Total running time of the script: ( 0 minutes 0.002 seconds)