Package: scikit-hts
Hierarchical Time Series with a familiar API. This is the result from not having found any good implementations
of HTS on-line, and my work in the mobility space while working at Circ (acquired by Bird scooters).My work on this is purely out of passion, so contributions are always
welcomed. You can also buy me a coffee if you’d like:ETH / BSC Address:0xbF42b9c8F7B69D52b8b986AA4E0BAc6838Af6698MIT LicenseDocumentation:https://scikit-hts.readthedocs.io/en/latest/OverviewBuilding on the excellent work by Hyndman[1], we developed this package in order to provide a python implementation
of general hierarchical time series modeling.[1]Forecasting Principles and Practice. Rob J Hyndman and George Athanasopoulos. Monash University, Australia.NoteSTATUS: alpha. Active development, but breaking changes may come.FeaturesSupported and tested onpython 3.6,python 3.7andpython 3.8Implementation of Bottom-Up, Top-Down, Middle-Out, Forecast Proportions, Average Historic Proportions,
Proportions of Historic Averages and OLS revision methodsSupport for representations of hierarchical and grouped time seriesSupport for a variety of underlying forecasting models, inlcuding: SARIMAX, ARIMA, Prophet, Holt-WintersScikit-learn-like APIGeo events handling functionality for geospatial data, including visualisation capabilitiesStatic typing for a nice developer experienceDistributed training & Dask integration: perform training and prediction in parallel or in a cluster with DaskExamplesYou can find code usages here:https://github.com/carlomazzaferro/scikit-hts-examplesRoadmapMore flexible underlying modeling support[P] AR, ARIMAX, VARMAX, etc[P] Bring-Your-Own-Model[P] Different parameters for each of the modelsDecoupling reconciliation methods from forecast fitting[W] Enable to use the reconciliation methods with pre-fitted modelsP: PlannedW: WIPCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2020-01-02)First release on PyPI.0.2.0 (2018-02-13)Major feature implementation and documentationStatic typingTesting - 44% coverage0.2.3 (2020-03-28)Testing up to 75%Exogenous variable supportExtensive docs0.3.0 (2020-03-28)Parallel and distributed training0.4.0 (2020-03-28)Testing for all reconciliation methods, line coverage > 80%0.4.1 (2020-03-28)Python 3.6 support0.5.2 (2020-03-28)Added support for no revision, thanks @ryanvolpiAdded multiple example athttps://github.com/carlomazzaferro/scikit-hts-examples, thanks @vtoliveiraLogging fixes and usability improvements0.5.3 (2021-02-23)Support for grouped time series, thanks to @noahsa! See:https://github.com/carlomazzaferro/scikit-hts/pull/510.5.4 (2021-04-20)Fixed long-standing BU forcasting bug, thanks to @javierhuertay! See:https://github.com/carlomazzaferro/scikit-hts/issues/350.5.6 (2021-04-20)Fixed input sanitization for convenience methods. See:https://github.com/carlomazzaferro/scikit-hts/issues/650.5.7 (2021-05-30)Ability to build hierarchies from tabular data. Thanks @noahsa! See:https://github.com/carlomazzaferro/scikit-hts/pull/700.5.8 (2021-05-30)Fix long-standing bugs related to transformers implementation. See:https://github.com/carlomazzaferro/scikit-hts/issues/66,https://github.com/carlomazzaferro/scikit-hts/issues/33,https://github.com/carlomazzaferro/scikit-hts/issues/380.5.9 (2021-05-30)Fix long-standing bugs related to handling exogenous variables. See:https://github.com/carlomazzaferro/scikit-hts/issues/550.5.10 (2021-06-5)Minor bug fix for transforms fixed:https://github.com/carlomazzaferro/scikit-hts/issues/66#issuecomment-8552238920.5.11 (2021-06-5)Further fix to exogenous variable handling, thanks to @wilfreddesert! See:https://github.com/carlomazzaferro/scikit-hts/issues/75