Why is [- subsetting (i.e. deletion) of columns not possible with names?

Question

I fear greatly that this has been asked and will be downvoted, but I have not found the answer in the docs (?"["), and discovered that it is hard to search for.

data(wines)
# This is allowed:
alcoholic <- wines[, 1]
alcoholic <- wines[, "alcohol"]
nonalcoholic <- wines[, -1]
# But this is not:
fail <- wines[, -"alcohol"]

I know of two solutions, but am frustrated for need of them.

win <- wines[, !colnames(wines) %in% "alcohol"]  # snappy
win <- wines[, -which(colnames(wines) %in% "alcohol")]  # snappier!

Answer 1

When you do

wines[, -1]

-1 is evaluated before it is used by [. As you know, the - unary operator won't work with object of class character, so doing the same with "alcohol" will lead you to:

Error in -"alcohol" : invalid argument to unary operator

You can add the following to your alternatives:

wines[, -match("alcohol", colnames(wines))]
wines[, setdiff(colnames(wines), "alcohol")]

but you should know about the risks of negative indexing, e.g., see what happens if you mistype "alcool" (sic.) So your first suggestion and the last one here (@Ananda's) should be preferred. You might also want to write a function that will error out if you provide a name that is not part of your data.

Answer 2

Another possibility:

subset(wines,select=-alcohol)

You can even do

subset(wines,select=-c(alcohol,other_drop))

In fact, if you have a contiguous set of columns you want to drop, you can even

subset(wines,select=-(first_drop:last_drop))

which can be handy (although IMO it depends dangerously on the order of columns, which is something that might be fragile: I might prefer a grep-based solution if there were some way to identify columns, or a more explicit separate definition of column groups).

In this case subset is using non-standard evaluation, which as has been discussed elsewhere can be dangerous in some contexts. But I still like it for simple, top-level data manipulation because of its readability.