Working off Avi's example - would: x |> cos() |> max(pi/4) |> round(3) |> assign("x", value = _)
...be even more intuitive to read? Or are there hidden problems with that? Cheers, Boris > On 2023-01-03, at 12:40, avi.e.gr...@gmail.com wrote: > > John, > > The topic has indeed been discussed here endlessly but new people still > stumble upon it. > > Until recently, the formal R language did not have a built-in pipe > functionality. It was widely used through an assortment of packages and > there are quite a few variations on the theme including different > implementations. > > Most existing code does use the operator %>% but there is now a built-in |> > operator that is generally faster but is not as easy to use in a few cases. > > Please forget the use of the word FILE here. Pipes are a form of syntactic > sugar that generally is about the FIRST argument to a function. They are NOT > meant to be used just for the trivial case you mention where indeed there is > an easy way to do things. Yes, they work in such situations. But consider a > deeply nested expression like this: > > Result <- round(max(cos(x), 3.14159/4), 3) > > There are MANY deeper nested expressions like this commonly used. The above > can be written linearly as in > > Temp1 <- cos(x) > Temp2 <- max(Temp1, 3.14159/4) > Result <- round(Temp2, 3) > > Translation, for some variable x, calculate the cosine and take the maximum > value of it as compared to pi/4 and round the result to three decimal > places. Not an uncommon kind of thing to do and sometimes you can nest such > things many layers deep and get hopelessly confused if not done somewhat > linearly. > > What pipes allow is to write this closer to the second way while not seeing > or keeping any temporary variables around. The goal is to replace the FIRST > argument to a function with whatever resulted as the value of the previous > expression. That is often a vector or data.frame or list or any kind of > object but can also be fairly complex as in a list of lists of matrices. > > So you can still start with cos(x) OR you can write this where the x is > removed from within and leaves cos() empty: > > x %>% cos > or > x |> cos() > > In the previous version of pipes the parentheses after cos() are optional if > there are no additional arguments but the new pipe requires them. > > So continuing the above, using multiple lines, the pipe looks like: > > Result <- > x %>% > cos() %>% > max(3.14159/4) %>% > round(3) > > This gives the same result but is arguably easier for some to read and > follow. Nobody forces you to use it and for simple cases, most people don't. > > There is a grouping of packages called the tidyverse that makes heavy use of > pipes routine as they made most or all their functions such that the first > argument is the one normally piped to and it can be very handy to write code > that says, read in your data into a variable (a data.frame or tibble often) > and PIPE IT to a function that renames some columns and PIPE the resulting > modified object to a function that retains only selected rows and pipe that > to a function that drops some of the columns and pipe that to a function > that groups the items or sorts them and pipe that to a function that does a > join with another object or generates a report or so many other things. > > So the real answer is that piping is another WAY of doing things from a > programmers perspective. Underneath it all, it is mostly syntactic sugar and > the interpreter rearranges your code and performs the steps in what seems > like a different order at times. Generally, you do not need to care. > > > > -----Original Message----- > From: R-help <r-help-boun...@r-project.org> On Behalf Of Sorkin, John > Sent: Tuesday, January 3, 2023 11:49 AM > To: 'R-help Mailing List' <r-help@r-project.org> > Subject: [R] Pipe operator > > I am trying to understand the reason for existence of the pipe operator, > %>%, and when one should use it. It is my understanding that the operator > sends the file to the left of the operator to the function immediately to > the right of the operator: > > c(1:10) %>% mean results in a value of 5.5 which is exactly the same as the > result one obtains using the mean function directly, viz. mean(c(1:10)). > What is the reason for having two syntactically different but semantically > identical ways to call a function? Is one more efficient than the other? > Does one use less memory than the other? > > P.S. Please forgive what might seem to be a question with an obvious answer. > I am a programmer dinosaur. I have been programming for more than 50 years. > When I started programming in the 1960s the only pipe one spoke about was a > bong. > > John > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. -- Boris Steipe MD, PhD Professor em. Department of Biochemistry Temerty Faculty of Medicine University of Toronto ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.