21–30 of 150 posts
Kind of odd they didn't decide to go with the magrittr syntax, which is in common use and heavily promoted in dplyr / tidyverse. I wonder if RStudio will change its `ctrl` + `shift` + m shortcut from the magrittr ( %>% ) style pipes to these new pipes ( |> )
I'm sure some of us who are out of the loop might be wondering: what about the magrittr pipe operator (%>%) that we all know and love? Luke Tierney explains the move from %>% to a native pipe |> here [1]. The native pipe aims to be more efficient as well as addresses issues with the magrittr pipe like complex stack traces. Turns out the |> syntax is also used in Julia, Javascript and F#. The lambda syntax (\(x) -> x…
Note that for JS it's still just a proposal and has been stuck in an indeterminable bikeshedding phase for most of this year.
Kind of odd they didn't decide to go with the magrittr syntax, which is in common use and heavily promoted in dplyr / tidyverse. I wonder if RStudio will change its `ctrl` + `shift` + m shortcut from the magrittr ( %>% ) style pipes to these new pipes ( |> )
also just discovered that ctrl shift m in firefox does something weird, looks like mobile view or something..
personally Im surprised R is still in active development when the main use case for people to use R (at least when I was using it) was for statistical analysis. Python with its libraries (a lot I believe ported from R) just does is nicer, and faster.
I'm sure some of us who are out of the loop might be wondering: what about the magrittr pipe operator (%>%) that we all know and love? Luke Tierney explains the move from %>% to a native pipe |> here [1]. The native pipe aims to be more efficient as well as addresses issues with the magrittr pipe like complex stack traces. Turns out the |> syntax is also used in Julia, Javascript and F#. The lambda syntax (\(x) -> x…
> Turns out the |> syntax is also used in Julia, Javascript and F#. Note that for JS it's still just a proposal and has been stuck in an indeterminable bikeshedding phase for most of this year.
I'm excited for it, though, and if the partial application syntax `func(a, ?)` gets ratified then we'll have a nice concise way of describing operations.
I'm sure some of us who are out of the loop might be wondering: what about the magrittr pipe operator (%>%) that we all know and love? Luke Tierney explains the move from %>% to a native pipe |> here [1]. The native pipe aims to be more efficient as well as addresses issues with the magrittr pipe like complex stack traces. Turns out the |> syntax is also used in Julia, Javascript and F#. The lambda syntax (\(x) -> x…
personally Im surprised R is still in active development when the main use case for people to use R (at least when I was using it) was for statistical analysis. Python with its libraries (a lot I believe ported from R) just does is nicer, and faster.
Nah, it's not nicer. dplyr is way better than pandas. But there is no end to the supply of Python fanbois who only know Python and assume that whatever's in Python just has to be better
ggplot is something that I don't think matplotlib is comparable to at all, though. I am so much faster at iterating on a visualization with R/ggplot than Python/matplotlib. Maybe it is my tooling, though. How about others who have used both? What are your experiences?