True story: writing tidyverse functions is so hard that I once worked for a company with business critical code running in incredibly long R-scripts with almost no functions, and 100 line pipes.
While that may be an extreme example, base-R is much, much easier to get started writing functions for (like I've been using R for a decade now, and the "idiomatic" way to use NSE with ggplot and dplyr has changed multiple times over that time).
Meanwhile, base-R is fugly, but its solid and backwards-compatible to a fault.
However, once they get that right, then tidyverse is close to perfection
I think the newish “interpolation” syntax with double braces {{ }} is getting there.
Damnit Hadley, why must you do this to me?
(Really I'm bitter because I know that I'll end up maintaining a bunch of important code in version N-2 of Hadley's NSE adventures at some point in the future).
https://www.tidyverse.org/blog/2020/02/glue-strings-and-tidy...
It’s interesting that you say this. I’ve been using R daily for almost 3 years now, and I was originally taught the Tidyverse.
However, I also tutored in biostats and have collaborated with many different faculty and students.
On one hand the Tidyverse created an opening for R learners especially, but it has lead to some controversy as well.
Trust me when I say there are plenty of R users who have never heard of or used the Tidyverse.
It leads to some difficulty in teaching/collaborating because do I use grepl or str_detect? lapply or map? Do they know the magrittr syntax (%>%)?
Then there’s non-standard evaluation, which often forces some arbitrary meta-programming on novice programmers.
R is foremost the stats language, and tidyverse has attempted to make it more general purpose, for better or worse depending on who you ask.