doehelper is a Python library designed to simplify Design of Experiments (DOE). It supports creating factorial experiments, performing statistical analysis such as ANOVA, and modeling response surfaces. It is intended for researchers, engineers, and data scientists conducting structured experimentation.
In the Data science & ML workbench space, doehelper takes a focused approach. Manually setting up and analyzing complex Design of Experiments in statistics and engineering. doehelper is an open-source project aimed at data scientists. The project is open source (GPL-3.0). The product ships for the command line.
It is developed by MartinGallagher-code, and the product first shipped in 2026. The project is developed in the open on GitHub with 55 commits in the last 90 days. Among its 4 catalogued features are Factorial Design, ANOVA Analysis, and Response Surface.
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