For R users who have started using Julia how's the datascience stack compare to tidyverse? The advertised speed of Julia seems great so I want to ask someone else who's made the switch how's life on the other side?
I think if you compare R's tidyverse to Julia, you aren't at all in Julia's wheelhouse. Julia's value comes from algorithm development primarily, not from interacting with data.frame type objects. If you really want to speed up that, use data.table in R. It'll provide you with the fastest data.frame implementation around.