autorank

Spec sheet

Purpose

Autorank is a Python package for comparing and ranking multiple paired populations, such as machine learning algorithms evaluated on multiple data sets.Read 8 Oct 2026 · sherbold.github.io

Intended users

The project aims to simplify statistical analysis for people who are not statistics experts.Read 8 Oct 2026 · sherbold.github.io

Deployment

desktopRead 23 Sep 2026 · sherbold.github.io

Free plan

YesRead 23 Sep 2026 · sherbold.github.io

Support

The project invites questions, bug reports, and feature requests through GitHub issues, and welcomes pull requests.Read 8 Oct 2026 · sherbold.github.io

License

Autorank is published under the Apache 2.0 License.Read 8 Oct 2026 · sherbold.github.io

Founded

2020Read 19 Oct 2026 · sherbold.github.io

Analysis approaches

It supports frequentist analysis based on 2006 guidelines and Bayesian analysis based on 2017 guidelines.Read 8 Oct 2026 · sherbold.github.io

Analysis methods

It supports frequentist analysis following 2006 guidelines and Bayesian analysis following 2017 guidelines.Read 8 Oct 2026 · sherbold.github.io

API documentation

The site links to online API documentation for the current master version.Read 8 Oct 2026 · sherbold.github.io

Automatic test selection

It checks normality and homogeneity to select statistical tests and reporting measures for the data.Read 8 Oct 2026 · sherbold.github.io

Bayesian analysis

Its Bayesian approach uses a Bayesian Signed Rank test and a Region of Practical Equivalence (ROPE).Read 8 Oct 2026 · sherbold.github.io

Bayesian performance

The site notes that Bayesian analysis can take seconds or, with many populations, minutes because it is computationally expensive.Read 8 Oct 2026 · sherbold.github.io

Data import formats

pandas DataFrameRead 23 Sep 2026 · sherbold.github.io

Dependencies

The implementation uses SciPy, statsmodels, and baycomp for statistical tests.Read 8 Oct 2026 · sherbold.github.io

Dependencies used

The documentation says it uses SciPy, statsmodels, and baycomp for statistical tests.Read 8 Oct 2026 · sherbold.github.io

Input format

The package expects population data in a Pandas dataframe.Read 8 Oct 2026 · sherbold.github.io

Input limits

The documented analysis requires at least five measurements, does not accept NaNs, and is described as reliable only for fewer than 5,000 measurements.Read 8 Oct 2026 · sherbold.github.io

Installation

The package can be installed from PyPI with pip or from the GitHub repository.Read 8 Oct 2026 · sherbold.github.io

Regression models

NoRead 23 Sep 2026 · sherbold.github.io

Reporting

It can generate plots, result tables, and LaTeX reports, including a complete LaTeX document.Read 8 Oct 2026 · sherbold.github.io

Scripting support

YesRead 23 Sep 2026 · sherbold.github.io

Statistical tests

For frequentist analysis, it selects tests based on normality, homogeneity, and the number of populations.Read 8 Oct 2026 · sherbold.github.io

Support and contributions

The project invites questions, bug reports, and feature requests through GitHub issues and welcomes pull requests.Read 8 Oct 2026 · sherbold.github.io

Plans and prices

Every autorank plan and price →

Where Specifiction places it

• Statistical Analysis Software#23 of 1068.4