On Jun 28, 2012, at 09:42 , Rui Barradas wrote:
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
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
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
Yeah, the reason I didn't use ifelse is because I've got multiple variables
to manipulate based on the if statement, some factors and some numeric. I
have to look at the factor variables, and based on that, either use one
series of variables or another.
With the multiple if statements I need to
On Thu, Jun 28, 2012 at 8:47 PM, James Holland holland.ag...@gmail.com wrote:
With the multiple if statements I need to check for, I though for statements
with the if/else if conditional statement was better than nested ifelse
functions.
for () gives you a lot of flexibility at the expense of
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
6 matches
Mail list logo
