Replace NA with 0 in a data frame column
Since nobody so far felt fit to point out why what you're trying doesn't work:
NA == NA
doesn't returnTRUE
, it returnsNA
(since comparing to undefined values should yield an undefined result).- You're trying to call
apply
on an atomic vector. You can't useapply
to loop over the elements in a column. - Your subscripts are off - you're trying to give two indices into
a$x
, which is just the column (an atomic vector).
I'd fix up 3. to get to a$x[is.na(a$x)] <- 0
First, here's some sample data:
set.seed(1)
dat <- data.frame(one = rnorm(15),
two = sample(LETTERS, 15),
three = rnorm(15),
four = runif(15))
dat <- data.frame(lapply(dat, function(x) { x[sample(15, 5)] <- NA; x }))
head(dat)
# one two three four
# 1 NA M 0.80418951 0.8921983
# 2 0.1836433 O -0.05710677 NA
# 3 -0.8356286 L 0.50360797 0.3899895
# 4 NA E NA NA
# 5 0.3295078 S NA 0.9606180
# 6 -0.8204684 <NA> -1.28459935 0.4346595
Here's our replacement:
dat[["four"]][is.na(dat[["four"]])] <- 0
head(dat)
# one two three four
# 1 NA M 0.80418951 0.8921983
# 2 0.1836433 O -0.05710677 0.0000000
# 3 -0.8356286 L 0.50360797 0.3899895
# 4 NA E NA 0.0000000
# 5 0.3295078 S NA 0.9606180
# 6 -0.8204684 <NA> -1.28459935 0.4346595
Alternatively, you can, of course, write dat$four[is.na(dat$four)] <- 0