Single functions and libraries can easily be imported in R, just like Python. It’s not necessary though, because the R community does a good job avoiding name conflicts (MASS aside).
I think the core issue is that the coordination benefits of having everyone use Python are overestimated, and the benefit of better statistical tools in R and SWE skilling up in statistics is underestimated.
Completely understand the annoyance of different results on order of package import. https://cran.r-project.org/web/packages/conflicted/ goes some way to solving this.
I understand the tidyverse perfectly well. Unfortunately it's become a habit of R users to import it at the top of every R script without thinking of the consequences of other users/maintainers.
Yes, because tidyverse should be called tidycurse. It's designed to be easy to teach, under the assumption that ALL you learn is tidycurse. Just don't use it!
Use datatable instead.
> It’s not necessary though, because the R community does a good job avoiding name conflicts
That has not at all been my experience. Loading the tidyverse pulls over 1000 things into your global namespace and clobbers several standard library functions in the process. Never mind that seemingly every single package has its own "filter" function.
When you start getting different results based on the order you import packages it's usually a bad sign.