[keeeba]

As a fairly extensive user of both Python and R, I net out similarly.

If I want to wrangle, explore, or visualise data I’ll always reach for R.

If I want to build ML/DL models or work with LLM’s I will usually reach for Python.

Often in the same document - nowadays this is very easy with Quarto.

[Joel_Mckay]

Python has a list of issues fundamentally broken in the language, and relies heavily on integrated library bindings to operate at reasonable speeds/accuracy.

Julia allows embedding both R and Python code, and has some very nice tools for drilling down into datasets:

https://www.queryverse.org/

It is the first language I've seen in decades that reduces entire paradigms into single character syntax, often outperforming both C and Numpy in many cases. =3

[pphysch]

Deeply ironic for a Julia proponent to smear a popular language as "fundamentally broken" without evidence.

https://yuri.is/not-julia/