This R rant by @hendrikerz has got quite some attention on the bird site. The R community over here might have missed it due to the missing #RStats tag.
I don‘t agree with much, but some points are worth for discussion / improvement.
Here is a quick run down of the arguments against R together with a short reply / assessment from my point of view - any comments welcome.
> No flexible & reliable descriptives and regression tables
Can’t agree here. I‘m using the {modelsummary} 📦 package to compare many models in Excel, and I haven’t run into problems yet. I don‘t use LaTeX though and I don’t care much for descriptive tables.
> Relatedly: the R community has no naming conventions for packages which makes it hard to find the best tool for the job
Due to the mere mass of available packages it is indeed not easy to find the right one - especially since package authors (including me) actually do try to come up with funny names and puns 😅
@TimTeaFan I would add here that although not the prettiest, the CRAN task views can be helpful as a first port of call for finding the right package for the job.
@statsrhian@TimTeaFan chiming in with my 2 cents: r-universe’s search is currently the best keyword / topic package discovery option if you know vaguely what you want. And you’ll find a bunch of gems not on CRAN mixed in: https://r-universe.dev/search/
@TimTeaFan@hendrikerz I do statistical analysis and data visualization in R (and automated reporting in Quarto) so maybe I'm one of those users for whom R works well for many tasks. (And Alt+Arrow works too!)
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