timefiller
A package for imputing missing data in time series, or forecasting in missing data contexts
A package for imputing missing data in time series, or forecasting in missing data contexts
To install this package, run one of the following:
timefiller is a Python package for time series imputation and forecasting. When applied to a set of correlated time series, each series is processed individually, leveraging correlations with the other series as well as its own auto-regressive patterns. The package is designed to be easy to use, even for non-experts.
Summary
A package for imputing missing data in time series, or forecasting in missing data contexts
Last Updated
Jan 12, 2025 at 16:41
License
MIT
Supported Platforms
GitHub Repository
https://github.com/CyrilJl/TimeFillerDocumentation
https://timefiller.readthedocs.io/en/latest/index.html