Totally agree, I think this whole conversation is a first language thing. I learned pandas first, and found the whole R ecosystem to be a complete mess.
So many different types of object, so many different syntaxes. The tidyverse makes sense, and sure, is elegant, but if your colleagues are using base R. Don't even get me started on docs and Stackoverflow for R. I much, and always will prefer Python.
The one area I still go back to R is on proper survey work. I've looked for years and haven't found anything equivalent to the survey package for Python. I do like that R tends to start from the assumption that data is weighted.
Survey people use r already, or maybe stata, so there isn’t any need for a python package. It’s sort of trivial to implement a jackknife loop in python, if you really had to. A python survey package would not be pythonic.
Yeah, I've cludged together all sorts of stuff, just to avoid working in R. Terrible use of my time.
The big issue isn't necessarily around jackknife etc. (as you say, pretty trivial and I think perhaps in statsmodels), but around regression weighting and ensuring compatibility with colleague's work.
The R survey package, Stata and SPSS all support things like survey design in their regressions, python does not out of the box. Even simple things like weighted frequencies end up with some pretty awkward code in Python.
I can imagine a pythonic survey package that extends pandas and statsmodels, but as you say, survey people use R and there's just not a scene for it.
So many different types of object, so many different syntaxes. The tidyverse makes sense, and sure, is elegant, but if your colleagues are using base R. Don't even get me started on docs and Stackoverflow for R. I much, and always will prefer Python.
The one area I still go back to R is on proper survey work. I've looked for years and haven't found anything equivalent to the survey package for Python. I do like that R tends to start from the assumption that data is weighted.
Fortunately I don't do surveys much anymore.