People have tried to port core R data science packages like dplyr to Python many times now and all that's happened is Python has fallen further behind.
It's not just a matter of manpower and funding, which Python has more of. Python is actually a less capable language in some important ways. It's not that expressive, and has basically no affordances for domain-specific languages.
I'll be happy when we have a successor language for R, but it won't be 2024 Python.
> I'll be happy when we have a successor language for R, but it won't be 2024 Python.
When it comes to statistics, and especially having to program stats analysis instead of just calling libraries, R is a much better language than Python or Julia. When it comes to other things, they are better than R. I use all 3 daily.
And with Quarto being available, why wouldn't you switch to whatever language is best for the current task? I'm throwing ObservableJS in there now too with the Quarto compatibility. You can do your data cleanup in R/Python, then use native web libraries for displaying pretty plots in the browser.
It is clear that R is not doing as well as Python. It is not clear that it is not doing well overall. It is still the best in statistical analysis and interactive usage (sklearn, statmodels, etc are not good enough). Maybe there is a healthy community that can thrive. For the moment being it seems that they are trying to eat SAS userbase.
It's not just a matter of manpower and funding, which Python has more of. Python is actually a less capable language in some important ways. It's not that expressive, and has basically no affordances for domain-specific languages.
I'll be happy when we have a successor language for R, but it won't be 2024 Python.