For instance, integer indexing in base R is df[row,col] rather than the iloc pandas stuff.
plot, print and summary (and generic function OOP more generally is really underappreciated).
Python is a better programming language, but R is a better data analysis environment.
And dplyr is an incredibly fluent DSL for doing data analysis (not quite as good for modelling though).
Seriously, I read the original vignette for dplyr in late 2013/early 2014 and within two weeks I'd switched most of my new analytical code over to it. So very, very good. Less idea-impedance match than any other environment, in my experience.
Base R is OK, but dplyr is magical.
For instance, integer indexing in base R is df[row,col] rather than the iloc pandas stuff.
plot, print and summary (and generic function OOP more generally is really underappreciated).
Python is a better programming language, but R is a better data analysis environment.
And dplyr is an incredibly fluent DSL for doing data analysis (not quite as good for modelling though).
Seriously, I read the original vignette for dplyr in late 2013/early 2014 and within two weeks I'd switched most of my new analytical code over to it. So very, very good. Less idea-impedance match than any other environment, in my experience.