Agree. While R's statistical stuff is much more polished, doing anything but running the regressions is a royal PITA.
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You got it the other way around. Doing anything but model specification (i.e. regression) is royal PITA in python.
Regression in sci-kit learn is like 2 lines. It's hard to understand where your painpoint is?
That's my point. Specification of the model is not (usually a problem). The other tasks are the problem.
That would be so because with R you get access to a myriad of statistical packages or because the functionality of numpy etc. is already included? IMHO the only real shortcoming is the lack of 64 bit integers, which is of course ridiculous.