Are you using Hadley Wickham's libraries in R? I think those go a long way toward fixing the problems you may have encountered -- i.e. API consistency, usabili

Are you using Hadley Wickham's libraries in R? I think those go a long way toward fixing the problems you may have encountered -- i.e. API consistency, usability, orthogonality, naming, etc. I also suggest reading some of his papers like "Tidy Data". R is weird in that you NEED a large set of CRAN libraries to do work, whereas in Python you can do a fair amount with the standard library, and PyPI is relatively weak in comparison. I'm also a programmer who learned R for data analysis. It does take quite awhile and some pain. Part of the difficulty is that R is weird and has warts, but an even bigger difficulty is that you are learning new concepts and programming abstractions (fundamental difficulty vs accidental difficulty). R passes the test of a language which changes the way you think. R has its warts but is likely the most practical choice. It has the full set of things you need -- data preparation and cleaning, exploratory analysis, model building, and visualization.