Hi I have a question concerning aggregation
(simple demo code S. below)
I have the data.frame
id meas date 1 a 0.637513747 1 2 a 0.187710063 2 3 a 0.247098459 2 4 a 0.306447690 3 5 b 0.407573577 2 6 b 0.783255085 2 7 b 0.344265082 3 8 b 0.103893068 3 9 c 0.738649586 1 10 c 0.614154037 2 11 c 0.949924371 3 12 c 0.008187858 4
When I want for each id the sum of its meas I do:
aggregate(data$meas, list(id = data$id), sum)
If I want to know the number of meas(ures) for each id I do, eg
aggregate(data$meas, list(id = data$id), length)
NOW: Is there a way to compute the number of meas(ures) for each id with not identical date (e.g using diff()?
so that I get eg:
id x 1 a 3 2 b 2 3 c 4
I am sure it must be possible
thanks for any (even short) hint
cheers Christoph
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data <- data.frame(c(rep("a", 4), rep("b", 4), rep("c", 4)),
runif(12), c(1, 2, 2, 3, 2, 2, 3, 3, 1, 2, 3, 4))
names(data) <- c("id", "meas", "date")m <- aggregate(data$meas, list(id = data$id), sum)
names(m) <- c("id", "cum.meas")______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
