MissMecha v0.1.1 Bugfix Release

We are pleased to release MissMecha v0.1.1!

MissMecha is a flexible Python package for the simulation, visualization, and evaluation of missing data mechanisms (MCAR, MAR, MNAR).

This update (v0.1.1) fixes a minor bug affecting the handling of categorical variables during missingness generation.
Thanks to the fix, categorical columns are now fully supported with correct mapping restoration during fit_transform() operations.

Highlights:

• 3× MCAR strategies
• 8× MAR strategies
• 6× MNAR strategies
• Support for numerical, categorical, and time series data
• Heatmap and nullity correlation visualizations
• SimpleSmartImputer for baseline imputation
• Statistical analysis including Little’s MCAR test
• Live demo video and full documentation

Documentation: https://echoid.github.io/MissMecha/
PyPI: https://pypi.org/project/missmecha-py/

MissMecha provides a unified, principled, and reproducible framework for studying missing data mechanisms.

Thank you for your support and feedback!