Hi John,
In examples like this I'd use set() and [[, since it's a bit easier to
write but memory efficient too.
for (x in c("foo", "bar", "qux")) set(fbq, is.na(fbq[[x]]), x,
FALSE) [untested]
A downside here is one repetition of the "fbq" symbol, but can live
with that. If you have a large number of columns (and I've been
surprised just how many columns some poeple have!) then calling set()
many times has lower overhead than DT[, :=], see ?set. Note also that
[[ is base R, doesn't copy the column and often useful to use with
data.table.
Or, use get() in either i or j rather than eval().
HTH, Matt
On 12/02/14 17:24, John Laing wrote:
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 <http://is.na>(foo), foo:=FALSE]
fbq.cp[is.na <http://is.na>(bar), bar:=FALSE]
fbq.cp[is.na <http://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 <http://is.na>(x),
eval(x):=FALSE]
for (x in c("foo", "bar", "qux")) fbq[is.na <http://is.na>(eval(x)),
eval(x):=FALSE]
for (x in c("foo", "bar", "qux")) fbq[eval(is.na <http://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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