Pyriodicity provides an intuitive and easy-to-use Python implementation for periodicity detection in univariate signals. Pyriodicity supports the following detection methods:
To install pyriodicity, simply run:
pip install pyriodicityTo install the latest development version, you can run:
pip install git+https://github.com/iskandergaba/pyriodicity.gitPlease refer to the package documentation for more information.
For this example, start by loading Mauna Loa Weekly Atmospheric CO2 Data from statsmodels and downsampling its data to a monthly frequency.
>>> from statsmodels.datasets import co2
>>> data = co2.load().data
>>> data = data.resample("ME").mean().ffill()Use Autoperiod to find the list of periods based in this data (if any).
>>> from pyriodicity import Autoperiod
>>> Autoperiod.detect(data)
array([12])The detected periodicity length is 12 which suggests a strong yearly seasonality given that the data has a monthly frequency.
All the supported estimation algorithms can be used in the same manner as in the example above with different optional parameters. Check the API Reference for more details.
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