I'm not sure I'd have the same take. Yes, R as a language is kind of wonky and people who use R tend to not be good programmers. However, the APIs of some packages are designed well enough that even with all of those barriers it can still be easy to use for many scientists. I wouldn't copy the language, 6 different object systems and non-standard evaluation is weird. But there is a lot to learn from the APIs of the tidyverse and how it has somehow been able to cover for all of those shortcomings. It would be great to see those aspects with the data science libraries of the Julia language.