Downside of all the ggplot-alikes in languages other than R is that they lose the enormous number of amazing add-on libraries[1] available for the original. Personally, where it's better I do a lot of data crunching in Python, then export to R and do all my graphics there. I feel like the statistics crowd just appreciates graphics more and has spent more time getting it perfect. Another plus is that Copilot really helps with R-based ggplot semantics and options because it's got so much to learn from. Not sure that would be true for the subtle differences in the ggplot clones.
Nice video. It definitely tells the story that R provides extra leverage in exposition. Might as well learn some R rather than yet another python plotting wrapper.
>Copilot really helps with R-based ggplot semantics and options because it's got so much to learn from. Not sure that would be true for the subtle differences in the ggplot clones
I would suspect this wouldn't be much of a hurdle for an LLM. If you've ever tried converting scripts from one language to another you can see how well LLMs generalise (not perfect ofc). So, as long as you give it enough context it will probably provide viable results.
Except if the range of the function given the same domain is much, much bigger. Extrapolation of a [massively multidimensional, non-linear] function is a lot harder than interpolation.
[1] https://youtu.be/7UjA_5gNvdw