Pingouin.jl

Reimplementation of Raphaelvallat's Pingouin in Julia
Popularity
45 Stars
Updated Last
10 Months Ago
Started In
September 2020

Pingouin.jl

Documentation

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 https://github.com/clementpoiret/Pingouin.jl.git

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.