R data.table behavior while filtering rows

data.table, r

Solution

To remove the `NA` rows simply set `nomatch=0`:

Here is an example (I removed the random sampling so everyone can have the same results)

library(data.table)
dt = data.table(foo = 1:10, bar = letters[1:10])
setkey(dt, bar)
needed_letters = letters[c(1:8,11,12)] #1 - 8 are available, 11 and 12 are not
dt[J(needed_letters),nomatch=0]

Addition from Matt

Also, if you prefer `nomatch=0` to be the default, you can change the default :

options(datatable.nomatch=0)
dt[J(needed_letters)]    # now, no NAs will be returned

You can check all arguments like this :

> args(data.table:::`[.data.table`)

function (x, i, j, by, keyby,
    with = TRUE,
    nomatch = getOption("datatable.nomatch"), 
    mult = "all",
    roll = FALSE,
    rollends = if (roll=="nearest") c(TRUE,TRUE)
               else if (roll>=0) c(FALSE, TRUE)
               else c(TRUE,FALSE),
    which = FALSE,
    .SDcols,
    verbose = getOption("datatable.verbose"), 
    allow.cartesian = getOption("datatable.allow.cartesian"), 
    drop = NULL)

The arguments whose default is via `getOption` can therefore have their default changed.

Problem

I am creating a data.table in R and setting a column to be used as key. When I try to retrieve values from the data table; for the rows where there is no match I get NA values back. I typically dont want that behavior in my search. Example below ``` library(data.table) dt <- data.table('foo'=seq(10),bar=sample(letters,10)) setkey(dt,bar) dt[sample(letters,5)] > dt[sample(letters,5)] b foo 1: x 4 2: q 2 3: u 8 4: s NA 5: b NA ```

Original source