I'm only thinking about CRAN > PyPI in terms of statistical packages. CRAN is where new statistical analysis techniques / packages are initially published. If you're lucky they might get ported to Python after the fact. I didn't even mention Bioconductor, which is another beast entirely. There isn't an equivalent of Bioconductor for Python at all.

And the last time I checked, "pip install numpy" could be quite a pain, especially if you needed to compile dependencies. Rstudio makes it ridiculously easy to install R and add packages.

However - for all other types of packages, PyPI is obviously superior. The breadth of packages on PyPI is much better than CRAN.

It about choosing the right tool for the job.