Pingouin is designed for users who want simple yet exhaustive stats functions:
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- 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.