R devel - Dec 2021 - Dropping RHS of a formula using NULL assignment

Hello all,

In attempting to create a one-sided formula from a two-sided formula,
I discovered that the following syntax will successfully complete this
operation:
> f <- y ~ x + z
> f[2] <- NULL
> f
~x + z
> str(f)
Class 'formula'  language ~x + z
  ..- attr(*, ".Environment")=<environment: R_GlobalEnv>

In searching through the formula documentation, I couldn't find this
technique as documented and wondered whether or not it is expected and
if it makes sense to develop a package against the behavior. I'm using
R 4.1.0, but I see the same on R-devel (r81303). I asked on Twitter,
but someone thought this list might be a better venue.

Apologies if I missed some documentation and thanks in advance.

Cheers,
Matt

~~~~~~~~~~
Matthew Blackwell
Associate Professor of Government
Harvard University
https://www.mattblackwell.org

On 14/12/2021 3:26 p.m., Blackwell, Matthew wrote:
> Hello all,
> 
> In attempting to create a one-sided formula from a two-sided formula,
> I discovered that the following syntax will successfully complete this
> operation:
> 
>> f <- y ~ x + z
>> f[2] <- NULL
>> f
> ~x + z
>> str(f)
> Class 'formula'  language ~x + z
>    ..- attr(*, ".Environment")=<environment: R_GlobalEnv>
> 
> In searching through the formula documentation, I couldn't find this
> technique as documented and wondered whether or not it is expected and
> if it makes sense to develop a package against the behavior. I'm using
> R 4.1.0, but I see the same on R-devel (r81303). I asked on Twitter,
> but someone thought this list might be a better venue.
> 
> Apologies if I missed some documentation and thanks in advance.
The source "y ~ x + z" parses to a call to the `~` function with 
arguments y and x + z.  Calls have the function as the first element, 
and arguments follow:  so f[1] would be ~, f[2] would be y, f[3] would 
be x + z.

You can see this if you pass f through as.list():

 > as.list(f)
[[1]]
`~`

[[2]]
y

[[3]]
x + z

Setting element 2 to NULL removes it, so you see

 > f[2] <- NULL
 > as.list(f)
[[1]]
`~`

[[2]]
x + z

I think it's safe to make use of this even if it's undocumented. 
It's a
pretty basic aspect of formulas.  I'd guess there are lots of packages 
already using it, but I can't point to any particular examples.

(I've ignored the difference between an unevaluated formula and an 
evaluated one, but they're almost the same, the only important 
difference in the attributes:  evaluating it gives it a class and an 
environment.)

Duncan Murdoch

On 14/12/2021 20:26, Blackwell, Matthew wrote:
> Hello all,
> 
> In attempting to create a one-sided formula from a two-sided formula,
> I discovered that the following syntax will successfully complete this
> operation:
> 
>> f <- y ~ x + z
>> f[2] <- NULL
>> f
> ~x + z
>> str(f)
> Class 'formula'  language ~x + z
>    ..- attr(*, ".Environment")=<environment: R_GlobalEnv>
> 
> In searching through the formula documentation, I couldn't find this
> technique as documented and wondered whether or not it is expected and
> if it makes sense to develop a package against the behavior. I'm using
> R 4.1.0, but I see the same on R-devel (r81303). I asked on Twitter,
> but someone thought this list might be a better venue.
> 
> Apologies if I missed some documentation and thanks in advance.
See ?"~", which says

      A formula has mode ?call?.  It can be subsetted by ?[[?: the
      components are ?~?, the left-hand side (if present) and the
      right-hand side _in that order_.

That would suggest that

f <- y ~ x + z
f[[2]] <- NULL

was the documented way (and the one I would have used).   However,
?"[" says

      ?[? and ?[[? are sometimes applied to other recursive objects such
      as calls and expressions.  Pairlists are coerced to lists for
      extraction by ?[?, but all three operators can be used for
      replacement.

> 
> Cheers,
> Matt
> 
> ~~~~~~~~~~
> Matthew Blackwell
> Associate Professor of Government
> Harvard University
> https://www.mattblackwell.org
-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Emeritus Professor of Applied Statistics, University of Oxford