How to use magrittr piping with multi-argument functions?

Question

For single argument functions, it is reasonably trivial to translate "standard" R code to the magrittr pipe style.

mean(rnorm(100))

becomes

rnorm(100) %>% mean

For multi-argument functions, it isn't clear to me what the best way to proceed is. There are two cases.

Firstly, the case when additional arguments are constants. In this case, you can create an anonymous function which changes the constant values. For example:

mean(rnorm(100), trim = 0.5)

becomes

rnorm(100) %>% (function(x) mean(x, trim = 0.5))

Secondly, the case where multiple vector arguments are required. In this case, you can combine inputs into a list, and create an anonymous function that operates on list elements.

cor(rnorm(100), runif(100))

becomes

list(x = rnorm(100), y = runif(100)) %>% (function(l) with(l, cor(x, y)))  

In both cases my solutions seem clunky enough that I feel like I'm missing a better way to do this. How should I pipe multiple arguments to functions?

Answer 1

In v. 1.5 there are two options:

list(x = rnorm(100), y = runif(100)) %$% cor(x, y) 

Which is essemtially the same as

list(x = rnorm(100), y = runif(100)) %>% with(cor(x, y)) # you could also do this earlier  

Or

list(x = rnorm(100), y = runif(100)) %>% { cor(.$x, .$y) } 

The { pair creates a lambda (unary function) on the fly so you don't have to do the whole (function(x) { ... }) thing.

As a side note, the inset and inset2 aliases can be used to "pick up" values in a pipeline, in e.g. lists.