Idiom for dropping a single column in a data.table

Question

I need to drop one column from a data.frame containing a few hundred columns.

With a data.frame, I'd use subset to do this conveniently:

> dat <- data.table( data.frame(x=runif(10),y=rep(letters[1:5],2),z=runif(10)),key='y' )
> subset(dat,select=c(-z))
            x y
 1: 0.1969049 a
 2: 0.7916696 a
 3: 0.9095970 b
 4: 0.3529506 b
 5: 0.4923602 c
 6: 0.5993034 c
 7: 0.1559861 d
 8: 0.9929333 d
 9: 0.3980169 e
10: 0.1921226 e

Obviously this still works, but it seems like not a very data.table-like idiom. I could manually construct a list of the column names I wanted to keep, which seems a little more data.table-like:

> dat[,list(x,y)]
            x y
 1: 0.1969049 a
 2: 0.7916696 a
 3: 0.9095970 b
 4: 0.3529506 b
 5: 0.4923602 c
 6: 0.5993034 c
 7: 0.1559861 d
 8: 0.9929333 d
 9: 0.3980169 e
10: 0.1921226 e

But then I have to construct such a list, which is clunky.

Is subset the proper way to conveniently drop a column or two, or does it cause a performance hit? If not, what's the better way?

Edit

Benchmarks:

> dat <- data.table( data.frame(x=runif(10^7),y=rep(letters[1:10],10^6),z=runif(10^7)),key='y' )
> microbenchmark( subset(dat,select=c(-z)), dat[,list(x,y)] )
Unit: milliseconds
                         expr       min        lq    median        uq      max
1           dat[, list(x, y)] 102.62826 167.86793 170.72847 199.89789 792.0207
2 subset(dat, select = c(-z))  33.26356  52.55311  53.53934  55.00347 180.8740

But really where it may matter more is for memory if subset copies the whole data.table.

Answer 1

If you are wanting to remove the column permanently use := NULL

dat[, z := NULL]

If you have your columns to drop as a character string use () to force evaluation as a character string, not as the character name.

toDrop <- c('z')

dat[, (toDrop) := NULL]

If you want to limit the availability of the columns in .SD, you can pass the .SDcols argument

dat[,lapply(.SD, somefunction) , .SDcols = setdiff(names(dat),'z')]

However, data.table inspects the j arguments and only gets the columns you use any way. See FAQ 1.12

When you write X[Y,sum(foo*bar)], data.table automatically inspects the j expression to see which columns it uses.

and doesn't try and load all the data for .SD (unless you have .SD within your call to j)

---

subset.data.table is processing the call and eventually evaluating dat[, c('x','y'), with=FALSE]

using := NULL should be basically instantaneous, howveer t does permanently delete the column.