Help with Julia becoming better

General Usage
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All,

I’m Andrew Ross, and I’m a 5th year phd student in statistics at the University of Missouri-Columbia. I’ve used Julia in my research, and I found it to be one of the most beautiful languages. As I’ve come to learn more about it, I find myself having issues with certain things such as documentation, lack of examples, etc. With that being said, I’d like to help the Julia community with documentation help or examples in areas of statistics. These include (but not limited to): DataFrames.jl (even though I like coding data cleaning myself. it’s beautiful in this language), Plots.jl, Turing.jl (love bayesian statistics), HypothesisTests.jl, GLM.jl, MixedModels.jl, Durbyn.jl, MLJ.jl (this is a big one for me as well), typical transformations used in stats, etc. So please, tell me how I can help with this. I can take datasets from TidyTuesday and do examples to publish, or I can do any other examples period. Also seeing Tidier.jl would be great to blossom more as well.

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I haven’t checked for a while, but all of DataFrames, Plots, MLJ, and Turing have had pretty exhaustive documentation including tutorials and usage examples for many years. If you’ve got additional examples it should be a easy as opening a PR?

For GLM things are a bit more basic, but I think that partly reflects the fact that GLM itself is a fairly basic package more of the “do one thing and do it well” ilk. I be believed for a while that the biggest win in Julia stats land would be more work on getting FixedEffectModels towards feature parity with fixest in R, but that probably reflects my own professional biases…