On 26/10/11 10:46, Vining, Kelly wrote:
Dear UseRs,
I have a data frame that looks like this:
head(test2)
attributes start end StemExplant Callus RegenPlant
1 LTR_Unknown 120 535 3.198 1.931 1.927
3 LTR_Unknown 2955 3218 0.541 0.103 0.613
6 LTR_Unknown 6210 6423 6.080 4.650 9.081
9 LTR_Unknown 9658 10124 0.238 0.117 0.347
14 LTR_Unknown 14699 14894 3.545 3.625 2.116
25 LTR_Unknown 33201 33474 1.275 1.194 0.591
I need to subtract each value in the "end" column from its corresponding value in the
"start" column, then append that difference as a new column in this data frame.
It seems like apply could be the way to approach this, but I can't see any easy way to
designate "difference" as a function, like, say, sum or mean. Plus, all the
apply/lapply examples I'm looking at seem to depend on a data frame being just the two
columns on which to operate, without any way to designate which columns to use in the
function(x,y) part of an lapply statement. Another alternative would be a for loop, but
when I try this:
for(i in 1:nrow(test2)) {
testout[i]<- (test2$end[i] - test2$start[i])
}
I get an error. So I'm stuck at the first step here. I think that once I can
figure out how to get the differences, I can use cbind to append the data
frame. But if there is a better way to do it, I'd like to know that as well.
Any help is appreciated.
Learn to think the R-ish way.
test2$diff <- test2$end - test2$start
Simple as that. Your unnecessary and inefficient for-loop approach
probably would
have *worked* had you initialised "testout" before the for loop. Like:
testout <- numeric(nrow(2))
It's hard to be sure since you didn't say *what* error was thrown. But
anyhow, *don't* do
it that way.
cheers,
Rolf Turner
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