How to Vectorize `[`

Question

I'm having trouble getting Vectorize to work with [, getting the error shown below. From the help("[") it seems like [ has arguments named x, i, and j - but they don't seem to work when I used them as vectorize.args. Can I do this?

## Some data
dat <- data.frame(a=1:10, b=11:20, c=21:30)

## Vectorize with mapply, seems to work
f <- function(i, j, dat) list(dat[i, j])
mapply(f, list(1:2, 3:4), list(1:2, 2:3), MoreArgs = list(dat=dat))
# [[1]]
#   a  b
# 1 1 11
# 2 2 12
# 
# [[2]]
#    b  c
# 3 13 23
# 4 14 24

## Now using Vectorize, apply to data
Vectorize(`[`, c("i", "j"))(x=dat, i=list(1:2, 2:3), j=list(1:2, 2:3))

Error in Vectorize([, c("i", "j")) : must specify names of formal arguments for 'vectorize'

But, this works (with a warning for naming the arguments)

`[`(x=dat, i=1:2, j=1:2)

Also, if I do this, it's ok

Vectorize(`[.data.frame`, c("i", "j"))(dat, list(1:2, 2:3), list(1:2, 2:3))

Answer 1

Vectorize() is documented to not be usable with primitive functions. From ?Vectorize

 ‘Vectorize’ cannot be used with primitive functions as they do not
 have a value for ‘formals’.

And [ is a primitive in R:

> `[`
.Primitive("[")

As [ is already vectorized I don't see the point of even trying this. The usual idiom for your `[`(x=dat, i=1:2, j=1:2) is simply:

dat[1:2, 1:2]

> dat[1:2, 1:2]
  a  b
1 1 11
2 2 12

This indices can be (pre-existing) objects too:

i <- 1:2
j <- 1:2
dat[i, j]

> dat[i, j]
  a  b
1 1 11
2 2 12

If you have more than one set of extractions, then I suppose you could call the [.data.frame method directly in Vectorise. The examples for ?Vectorize illustrate doing this sort of thing for function rep(), which is primitive, so uses rep.int() instead.