I learned r too long ago so I am pretty fluent writing readable data wrangling code in base R. But I'm a biologist first, in my community I see the value dplyr adds in making it approachable for people who need to do some basic stats but probably will never need to really understand the language or do any development.
It also provides guardrails and encourages best practices which I find a bit to paternalistic and annoying but again I can see the value.
I think most R users would be surprised and just how much tidyverse functionality is hidden in base R but majority of the dplyr versions of functions have at least some intended improvement over the base R versions, and some are a massive improvement in functionality.
For example in a typical script the only tidyverse package I may load besides ggplot2 is tidyr, because the pivot_ wider/longer() functions really do solve a problem that was not fun in base R.
It also provides guardrails and encourages best practices which I find a bit to paternalistic and annoying but again I can see the value.
I think most R users would be surprised and just how much tidyverse functionality is hidden in base R but majority of the dplyr versions of functions have at least some intended improvement over the base R versions, and some are a massive improvement in functionality.
For example in a typical script the only tidyverse package I may load besides ggplot2 is tidyr, because the pivot_ wider/longer() functions really do solve a problem that was not fun in base R.