Time-based k-fold validation splits for heterogeneous data.

Folds plotted on a two-by-two grid. See the examples page for more.

A library for creating time-based cross-validation splits of heterogeneous data, such as raw transaction data with strong non-stationary characteristics.

• Splitting schedules based on a fixed interval, a CRON-expression, or a pre-defined list.
• Data selection based on a timedelta, or the splitting schedule itself.
• Automatically extract and normalize data limits for supported data types.
• Plotting function for visualization of folds. Display fold sizes (hour/row count), or use custom text.
• Integrations for popular libraries such as pandas, polars and scikit-learn.

The package is published through the Python Package Index (PyPI). Source code is available on GitHub: https://github.com/rsundqvist/time-split

pip install -U time-split

This is the preferred method to install time-split, as it will always install the most recent stable release.

If you don't have pip installed, this Python installation guide can guide you through the process.

MIT

Hosted on Read the Docs: https://time-split.readthedocs.io

All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome. To get started, see the Contributing Guide and Code of Conduct.