I think the most useful comparison is between languages have an org that makes a little money and uses it to hire top notch developers to work 100% of the time

I think the most useful comparison is between languages have an org that makes a little money and uses it to hire top notch developers to work 100% of the time on OSS [1], VS languages that don't have that. RStudio's contributions to the R ecosystem have been magical, most notably the RStudio IDE and the tidyverse set of libraries. When I need to get anything done quickly that involves working with data, I reach for R immediately, long before even considering python, ruby, SQL or any of the more constrained tools like tableau or (uggh) SAS/SPSS/et al. R is just so fast to develop in, and so reliable. I feel like I hit more walls in other languages ecosystems; not so much the actual syntaxes, but more oddities/bugs/incompatibilities in the way/place/environment in which I use the code. [1] RStudio (the org) has 40 (!!) devs full time on OSS! (and many more who aren't full time)