data.table subsetting rows using a logical column: why do I have to explicitly compare with TRUE? [duplicate]

Question

I'm wondering why for the given data.table:

library(data.table)
DT <- structure(list(number = 1:5, bmask = c(FALSE, TRUE, FALSE, TRUE, 
FALSE)), .Names = c("number", "bmask"), row.names = c(NA, -5L
), class = c("data.table", "data.frame"))

> DT
   number bmask
1:      1 FALSE
2:      2  TRUE
3:      3 FALSE
4:      4  TRUE
5:      5 FALSE

the expression DT[bmask==T,.(out=number)] works as expected:

   out
1:   2
2:   4

but DT[bmask,.(out=number)] causes error:

> DT[bmask,.(out=number)]
Error in eval(expr, envir, enclos) : object 'bmask' not found

Is it a proper behavior of the data.table package?

Answer 1

Use this instead:

DT[(bmask), .(out=number)]
#    out
# 1:   2
# 2:   4

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The role of the parentheses is to put the symbol bmask inside of a function call, from whose evaluation environment the columns of the DT will be visible¹. Any other function call that simply returns bmask's value (e.g. c(bmask), I(bmask), or bmask==TRUE) or the indices of its true elements (e.g. which(bmask)) will work just as well but may take slightly longer to compute.

If bmask is not located inside a function call, it will be searched for in calling scope (here the global environment), which can also be handy at times. Here's the relevant explanation from ?data.table:

Advanced: When 'i' is a single variable name, it is not considered an expression of column names and is instead evaluated in calling scope.

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¹To see that () is itself a function call, type is(`(`).