What is the logic of Function(x) and Function(x,y) in R?

Question

In the execution of loops with functions apply, is always used function(x). Example:

lapply(df,function(x)gsub('[^A-Z]','',x))

In other functions, however, it is used function(x,y). Example:

Reduce(function(x,y)merge(x,y,all=TRUE,by='row.names'),list)

I always wear them, but I don’t understand them clearly.

What is the logic of using these functions?

Answer 1

The function lapply takes two arguments - the first is a list (can be a data.frame - since it is also a list) and the second argument is a function that will be applied to each element of the list passed as the first argument.

Therefore, we could create a function and then pass it to the lapply, for example:

my_fun <- function(x) gsub('[^A-Z]','',x)
lapply(df, my_fun)

It turns out that in R, functions can be created even without having a name, and that’s what we do when we pass:

lapply(df,function(x)gsub('[^A-Z]','',x))

Like the lapply will pass each element of the list as argument of this function, only one parameter will be changed, so in general we use only functions with only one argument.

Already the Reduce uses a binary function because it will combine element 1 with element 2 and then the result with element 3 and so on.

It would be the same thing as creating a function:

my_fun2 <- function(x, y) merge(x,y,all=TRUE,by='row.names'),list)
Reduce(my_fun2,list)

In both cases, the name of the argument is irrelevant, it could be any name, since both the lapply as to the Reduce use the order of arguments.