[mdlincoln]

I find that a fascinating reaction given how rapidly %>% have been taken up across a large segment of the R universe, to great excitement! Personally, I find it far MORE legible than endlessly-nested function calls.

It results in code that more closely resembles executed order of operations (e.g. filter -> mutate -> group -> summarize). Context is also key: it's most often used for data processing pipelines in specific analytical scripts or literate-code documents - less so used when defining generalizable/testable functions in packages (again, just a personal perspective - YMMV of course)

[extr]

you nailed it. dplyr is better the further you are from doing heavy duty data analysis or creating production code. if you're writing some simple transforms to put data into a report, fine. someone is probably going to want to look at that at some point and it's much, much easier to understand. but for anything else i stick with data.table.