I have a question similar to this one, but my dataset is a bit bigger: 50 columns with 1 column as UID and other columns carrying either TRUE
or NA
, I want to change all the NA
to FALSE
, but I don't want to use explicit loop.
Can plyr
do the trick? Thanks.
Thanks for quick reply, but what if my dataset is like below:
df <- data.frame(
id = c(rep(1:19),NA),
x1 = sample(c(NA,TRUE), 20, replace = TRUE),
x2 = sample(c(NA,TRUE), 20, replace = TRUE)
)
I only want X1
and X2
to be processed, how can this be done?
If you want to do the replacement for a subset of variables, you can still use the is.na(*) <-
trick, as follows:
df[c("x1", "x2")][is.na(df[c("x1", "x2")])] <- FALSE
IMO using temporary variables makes the logic easier to follow:
vars.to.replace <- c("x1", "x2")
df2 <- df[vars.to.replace]
df2[is.na(df2)] <- FALSE
df[vars.to.replace] <- df2