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ACCLAB/DABEST-python

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View on GitHub↗
0 stars·0 forks·8 views

DABEST Python

Features

  • Statistical Analysis - Estimation statistics and mean difference plotting.

Star history

Star history chart for acclab/dabest-pythonStar history chart for acclab/dabest-python

How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.

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Open-source alternatives to DABEST Python

Similar open-source projects, ranked by how many features they share with DABEST Python.
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See all 7 alternatives to DABEST Python→

Frequently asked questions

What are the main features of acclab/dabest-python?

The main features of acclab/dabest-python are: Statistical Analysis.

What are some open-source alternatives to acclab/dabest-python?

Open-source alternatives to acclab/dabest-python include: bashtage/linearmodels — Additional linear models including instrumental variable and panel data models that are missing from statsmodels. gostevehoward/confseq. josipd/torch-two-sample. maximtrp/scikit-posthocs — Multiple Pairwise Comparisons (Post Hoc) Tests in Python. pzivich/zepid. raphaelvallat/pingouin — Statistical package in Python based on Pandas.