Reimplementation of Raphaelvallat's Pingouin in Julia
39 Stars
Updated Last
1 Year Ago
Started In
September 2020



Pingouin is designed for users who want simple yet exhaustive stats functions: sample code

A reimplementation of Raphaelvallat's Pingouin in Julia, from scratch. Currently at a really early stage, usable, but please double check your results.

I'm a PhD student who has to do statistical analysis. I'm also interested in Julia. To learn Julia, I decided to reimplement my favorite stats lib I used in Python. I'm starting with the functions I use the most, and simple statistical tests. I'm open to every suggestions/contributions :)

I'm just starting in Julia, so if you find my code ugly, of if you want to suggest some good practices, feel free to open an issue <3

Pingouin.jl is an open-source statistical package written in pure Julia, and based mostly on DataFrames.jl, and HypothesisTests.jl. Some of its main features are listed below. For a full list of future functions, please refer to the original Python API documentation.

## Installation

You can install the latest table Pingouin through the official repo:

julia> using Pkg
julia> Pkg.add("Pingouin")

Or the latest version (maybe unstable) from github:

pkg> add

Current progress

  • Distribution,
  • Effect sizes,
  • Bayesian,
  • Non-parametric,
  • Correlation and regression [WIP],
  • ANOVA and T-test,
  • Multiple comparisons and post-hoc tests,
  • Circular,
  • Contingency,
  • Multivariate tests,
  • Plotting,
  • Power analysis,
  • Reliability and consistency,
  • Others.

_shapiro.jl is provided under MIT license.