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Too many R packages: CRAN is inundated with submissions

https://rworks.dev/posts/too-many-R-packages/
21•ionychal•1h ago

Comments

jdw64•38m ago
People would typically choose based on CRAN TaskViews or follow conventional methodologies, but what I notice from this is that R is truly a language used only by those who use it. And the people who use it are usually master's students or professors; it's rarely used at the undergraduate level. So even those with that level of academic background and training must have had their own implementation roadblocks. Could that be why the use of R has exploded with the help of AI? Looking at this, I think it's fair to understand that even domain experts found programming difficult. Seeing this, can we really say that AI is always bad? For some people, it has become both the hands and a voice for their words.
RA_Fisher•15m ago
Programming is a lot easier than statistics bc it’s deterministic, whereas statistics is stochastic (that extends and encompasses deterministic functions).

AI speeds up learning, so I bet that’s what you’re noticing with R.

As an aside, the best programmers these days are probabilistic programmers (who write stochastic functions). Our languages are Stan and PyMC. Both can be called by Python or R, and AI writes all of them extremely well. So it seems to me that the underlying language matters less than ever.

Mairoce•33m ago
Frankly the bigger problem is an over reliance among R instructors on the tidyverse, an ever-expanding ecosystem of redundant functions and anti-patterns. They’re teaching new R users that everything can be solved with yet another package import and skipping over teaching them how to use the already powerful and intuitive base packages.
mjhay•20m ago
I’m not saying it doesn’t have flaws, but the tidyverse is still the most coherent and functional ML/stat computing ecosystem I’ve ever used. R packages outside of the tidyverse can get pretty gnarly. Even the R stdlib is usually considered to be inconsistent and riddled with legacy cruft.
331c8c71•9m ago
It's certainly quite pleasant to work with...but I would rather use sql for etl, the backend be whatever it needs to be...

The real world data transformations can get gnarly very quickly and sql is the perfect common debiminator compared to dplyr which is still niche...

How do you feel about polars?

nswizzle31•15m ago
I couldn’t disagree more. The base packages are a complete mess. If R was subset to only the tidyverse 5 years ago then it wouldn’t have lost so much ground to Python in nearly all fields.

Posit is obviously the only organization with the pull to do that, and I feel like they got pulled in 10 directions during the move to AI and trying to also support Python. R Shiny is dead too which sucks because reflex.dev just copied them and ate their lunch in 3 months.

AI cannot read between the lines

https://zencapital.substack.com/p/ai-cannot-read-between-the-lines
1•germanrabbit•40s ago•0 comments

Your Interface Has Two Channels

https://tomeraberba.ch/your-interface-has-two-channels
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