[R] Pipe operator

[Andrew Hart]

Keep in mind that in thie example you're processing x and placing the 
result back in x (so x must already exist). You can write this a bit 
more cleanly using the -> variant of the assignment operator as follows:

   x |> cos() |> max(pi/4) |> round(3) -> x

Hth,
Andrew.

On 3/01/2023 16:00, Boris Steipe wrote:
> 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.gross using 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-bounces using r-project.org> On Behalf Of Sorkin, John
>> Sent: Tuesday, January 3, 2023 11:49 AM
>> To: 'R-help Mailing List' <r-help using 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
>>
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>> ______________________________________________
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> 
> 
> --
> Boris Steipe MD, PhD
> 
> Professor em.
> Department of Biochemistry
> Temerty Faculty of Medicine
> University of Toronto
> 
> ______________________________________________
> R-help using 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.
>