Any of the following will remove column foo
from the data.table df3
:
# Method 1 (and preferred as it takes 0.00s even on a 20GB data.table)
df3[,foo:=NULL]
df3[, c("foo","bar"):=NULL] # remove two columns
myVar = "foo"
df3[, (myVar):=NULL] # lookup myVar contents
# Method 2a -- A safe idiom for excluding (possibly multiple)
# columns matching a regex
df3[, grep("^foo$", colnames(df3)):=NULL]
# Method 2b -- An alternative to 2a, also "safe" in the sense described below
df3[, which(grepl("^foo$", colnames(df3))):=NULL]
data.table also supports the following syntax:
## Method 3 (could then assign to df3,
df3[, !"foo"]
though if you were actually wanting to remove column "foo"
from df3
(as opposed to just printing a view of df3
minus column "foo"
) you'd really want to use Method 1 instead.
(Do note that if you use a method relying on grep()
or grepl()
, you need to set pattern="^foo$"
rather than "foo"
, if you don't want columns with names like "fool"
and "buffoon"
(i.e. those containing foo
as a substring) to also be matched and removed.)
Less safe options, fine for interactive use:
The next two idioms will also work -- if df3
contains a column matching "foo"
-- but will fail in a probably-unexpected way if it does not. If, for instance, you use any of them to search for the non-existent column "bar"
, you'll end up with a zero-row data.table.
As a consequence, they are really best suited for interactive use where one might, e.g., want to display a data.table minus any columns with names containing the substring "foo"
. For programming purposes (or if you are wanting to actually remove the column(s) from df3
rather than from a copy of it), Methods 1, 2a, and 2b are really the best options.
# Method 4:
df3[, .SD, .SDcols = !patterns("^foo$")]
Lastly there are approaches using with=FALSE
, though data.table
is gradually moving away from using this argument so it's now discouraged where you can avoid it; showing here so you know the option exists in case you really do need it:
# Method 5a (like Method 3)
df3[, !"foo", with=FALSE]
# Method 5b (like Method 4)
df3[, !grep("^foo$", names(df3)), with=FALSE]
# Method 5b (another like Method 4)
df3[, !grepl("^foo$", names(df3)), with=FALSE]