> What we found was that R had alot of packages but most haven't been touched in years and when you contact the owner you find they've often moved onto the python/pandas/scikit eco system
As a "bilingual" R & Python user, I've found this to be true for the latter language as well :)
I don't have much to add on top of what other useRs have mentioned, except another testimonial that our company has successfully used R in production for 6+ years, from data "pipeline" stuff you mentioned to dozens upon dozens of predictive models of varying complexities.
When faced with a new data analysis ask, 99%+ of the time I reach for R (although without the tidyverse, that number would be much lower). Like another commenter said, the ease by which you can plot in R blows Python away. Seaborn seems like a decent compromise in my limited experience, but plotting in "base" matplotlib makes me want to die.
Iff the customers have the requisite knowledge of what "responsible AI" should look like within a given domain. Sometimes you may have customers whose analytical skills are so basic there's no way they're thinking about bias, which would push the onus back onto the creator of the AI product to complete any ethical evaluations themselves (or try and train customers?)
As a "bilingual" R & Python user, I've found this to be true for the latter language as well :)
I don't have much to add on top of what other useRs have mentioned, except another testimonial that our company has successfully used R in production for 6+ years, from data "pipeline" stuff you mentioned to dozens upon dozens of predictive models of varying complexities.
When faced with a new data analysis ask, 99%+ of the time I reach for R (although without the tidyverse, that number would be much lower). Like another commenter said, the ease by which you can plot in R blows Python away. Seaborn seems like a decent compromise in my limited experience, but plotting in "base" matplotlib makes me want to die.