[datatable-help] Force evaluation of first argument to [

[John Laing]

Let's say I merge together several data.tables such that I wind up
with lots of NAs:

require(data.table)
foo <- data.table(k=1:4, foo=TRUE, key="k")
bar <- data.table(k=3:6, bar=TRUE, key="k")
qux <- data.table(k=5:8, qux=TRUE, key="k")
fbq <- merge(merge(foo, bar, all=TRUE), qux, all=TRUE)
print(fbq)
#    k  foo  bar  qux
# 1: 1 TRUE   NA   NA
# 2: 2 TRUE   NA   NA
# 3: 3 TRUE TRUE   NA
# 4: 4 TRUE TRUE   NA
# 5: 5   NA TRUE TRUE
# 6: 6   NA TRUE TRUE
# 7: 7   NA   NA TRUE
# 8: 8   NA   NA TRUE

I want to go through those columns and turn each NA into FALSE. I can
do this by writing code for each column:

fbq.cp <- copy(fbq)
fbq.cp[is.na(foo), foo:=FALSE]
fbq.cp[is.na(bar), bar:=FALSE]
fbq.cp[is.na(qux), qux:=FALSE]
print(fbq.cp)
#    k   foo   bar   qux
# 1: 1  TRUE FALSE FALSE
# 2: 2  TRUE FALSE FALSE
# 3: 3  TRUE  TRUE FALSE
# 4: 4  TRUE  TRUE FALSE
# 5: 5 FALSE  TRUE  TRUE
# 6: 6 FALSE  TRUE  TRUE
# 7: 7 FALSE FALSE  TRUE
# 8: 8 FALSE FALSE  TRUE

But I can't figure out how to do it in a loop. More precisely, I can't
figure out how to make the [ operator evaluate its first argument in
the context of the data.table. All of these have no effect:
for (x in c("foo", "bar", "qux")) fbq[is.na(x), eval(x):=FALSE]
for (x in c("foo", "bar", "qux")) fbq[is.na(eval(x)), eval(x):=FALSE]
for (x in c("foo", "bar", "qux")) fbq[eval(is.na(x)), eval(x):=FALSE]

I'm running R 3.0.2 on Linux, data.table 1.8.10.

Thanks in advance,
John
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