Hello,
Another way is to use index vectors:
v1.factor <- c("S","S","D","D","D",NA)
v2.factor <- c("D","D","S","S","S","S")
td2 <- test.data <- data.frame(v1.factor,v2.factor)
for (i in 1:nrow(test.data) ) {
[... etc ...]
} #End FOR
# Create index vectors
na1 <- is.na(v1.factor)
na2 <- is.na(v2.factor)
# Create 'newvar' with default value
td2$newvar <- NA
# Now, set values if condition is met.
td2$newvar[!na1 & !na2] <- as.character(td2$v1.factor[!na1 &!na2])
all.equal(test.data, td2)
[1] TRUE
I find this way better when doing a multiple if/else based on
combinations of a small number of conditions. It's also very readable.
Hope this helps,
Rui Barradas
Em 28-06-2012 08:00, Miguel Manese escreveu:
Hi James,
On Thu, Jun 28, 2012 at 12:33 AM, James Holland <holland.ag...@gmail.com> wrote:
I need to look through a dataset with two factor variables, and depending
on certain criteria, create a new variable containing the data from one of
those other variables.
The problem is, R keeps making my new variable an integer and saving the
data as a 1 or 2 (I believe the levels of the factor).
I've tried using as.factor in the IF output statement, but that doesn't
seem to work.
Any help is appreciated.
#Sample code
rm(list=ls())
v1.factor <- c("S","S","D","D","D",NA)
v2.factor <- c("D","D","S","S","S","S")
test.data <- data.frame(v1.factor,v2.factor)
The vectorized way to do that would be
# v1.factor if present, else v2.factor
test.data$newvar <- ifelse(!is.na(v1.factor), v1.factor, v2.factor)
I suggest you work with the character levels first then convert it
into a factor, e.g. if v1.factor & v2.factor are already factors, do:
test.data$newvar <- as.factor(ifelse(!is.na(v1.factor),
as.character(v1.factor), as.character(v2.factor)))
Regards,
Jon
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