Subset data table without using <-

Question

I want to subset some rows of a data table. Like this:

# load data
  data("mtcars")

# convert to data table
  setDT(mtcars,keep.rownames = T)

# Subset data
  mtcars <- mtcars[like(rn,"Mer"),] # or
  mtcars <- mtcars[mpg > 20,]

However, I'm working with a huge data set and I wanted to avoid using <-, which is not memory efficient because it makes a copy of the data.

Is this correct? Is it possible to update the filtered data without <- ?

Answer 1

What you are asking would be delete rows by reference.

It is not yet possible, but there is FR for that #635.

Until then you need to copy (in-memory) your data.table subset, the copy is done by <- (or =) when is combined with subset (i arg) so for now you cannot avoid that.

If it will help somehow you can operate on language objects to predefine the operation and delay it's evaluation, also reuse predefined objects multiple times:

mtcars_sub <- quote(mtcars[like(rn,"Mer")])
mtcars_sub2 <- quote(eval(mtcars_sub)[mpg > 20])
eval(mtcars_sub2)
#           rn  mpg cyl  disp hp drat   wt qsec vs am gear carb
# 1: Merc 240D 24.4   4 146.7 62 3.69 3.19 20.0  1  0    4    2
# 2:  Merc 230 22.8   4 140.8 95 3.92 3.15 22.9  1  0    4    2

BTW. when subsetting data.table you don't need to use middle comma like dt[x==1,] you can use dt[x==1].