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.
doehelper is an Optimisation & solvers project. Manually setting up and analyzing complex Design of Experiments in statistics and engineering. doehelper is an open-source project aimed at data scientists. doehelper is open source under the GPL-3.0 license. It ships for the command line.
MartinGallagher-code builds and maintains doehelper, and it 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.
Summary written by a language model from the project’s public pages.
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