61–70 of 150 posts
This sounds promising, but how do we type that pipe easily if we're going to be using it all the time? I actually like %>% because it's easy to reach the keys and hammer it out. Agreed on the ugly stack traces.
Your hands are obviously quite different than mine, because |> is so much easier to reach than %>%
Well, afaik it isn't really a pipe but syntactic sugar. A pipe streams data from one output stream to an input stream. This rewrites the code as if the input were passed as an argument.
This is not a pipe -René Magritte
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 they wanted to not replace magrittr pipes. R is introspective, and some reckless people (like myself) will mess with functions' guts in a few scripts. Replacing the `%>%` function with a syntax symbol will break those scripts. Even with scripts that don't metaphorically shove their hands down the garbage disposal, programmers might've relied on certain behaviors of the magrittr pipe. The R Core team is very…
That backslash syntax is pretty funky, but then again all of R is a little funky. Very nice addition to the language though!
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 know R because that's what we used at my first company. I would love to switch to Python/Pandas but I'm comfortable with R and it does everything I need it to with one exception over ten years of heavy use. Python is wonderful but the cognitive load for switching in industry and academia without a clear cost benefit isn't worth it to most people I know in my shoes. I encourage new coders to learn Python but discoun…
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…
> The lambda syntax (\(x) -> x + 1) is similar to Haskell's (\x -> x + 1). The proposed lambda syntax for R is `\(x) x+1` so `\` will just be shorthand for `function`.
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 know R because that's what we used at my first company. I would love to switch to Python/Pandas but I'm comfortable with R and it does everything I need it to with one exception over ten years of heavy use. Python is wonderful but the cognitive load for switching in industry and academia without a clear cost benefit isn't worth it to most people I know in my shoes. I encourage new coders to learn Python but discoun…
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…
https://stat.ethz.ch/pipermail/r-devel/2020-December/080173....
The reason for announcing the new lambda syntax at the same time seems to be to enable certain workflows that the magrittr pipe supports. The %>% operator, by default, pipes to the first argument of a function. If you want to pipe to a different argument, you can do:
a %>% func(x, arg2 = .)
It seems like the native pipe doesn't support a placement argument, but you can use the new, more concise lambda operator:
a |> \(d) func(x, arg2 = d)
A little more verbose, but it's not a very common use case, it's more general, and I'd happily trade a little more verbosity for the rest of the improvements. (That said, I haven't played around with the magrittr 2.0 improvements yet, so maybe the difference is going to end up being less than the presentation suggests.)
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.
R vs. Python flamewars always strike me as a Budweiser vs. Miller kind of argument. Neither is really a “craft beer” of programming languages. Neither are super remarkable as programming languages. Both made a bunch pragmatic tradeoffs to appeal to large audiences that share similar values—both are “average joe” beers. Python has comparative advantages over R in production roles. R has comparative advantage in statis…
Yeah, you've probably never heard of it