To expand on @Franks answer, if in your particular case you are appending a row, it's :
set.seed(12345)
dt1 <- data.table(a=rnorm(5), b=rnorm(5))
The following are equivalent; I find the first easier to read but the second faster:
microbenchmark(
rbind(dt1, list(5, 6)),
rbindlist(list(dt1, list(5, 6)))
)
As we can see:
expr min lq median uq max
rbind(dt1, list(5, 6)) 160.516 166.058 175.089 185.1470 457.735
rbindlist(list(dt1, list(5, 6))) 130.137 134.037 140.605 149.6365 184.326
If you want to insert the row elsewhere, the following will work, but it's not pretty:
rbindlist(list(dt1[1:3, ], list(5, 6), dt1[4:5, ]))
or even
rbindlist(list(dt1[1:3, ], as.list(c(5, 6)), dt1[4:5, ]))
giving:
a b
1: 0.5855288 -1.8179560
2: 0.7094660 0.6300986
3: -0.1093033 -0.2761841
4: 5.0000000 6.0000000
5: -0.4534972 -0.2841597
6: 0.6058875 -0.9193220
If you are modifying a row in place (which is the preferred approach), you will need to define the size of the data.table in advance i.e.
dt1 <- data.table(a=rnorm(6), b=rnorm(6))
set(dt1, i=6L, j="a", value=5) # refer to column by name
set(dt1, i=6L, j=2L, value=6) # refer to column by number
Thanks @Boxuan, I have modified this answer to take account of your suggestion, which is a little faster and easier to read.