From: Christoph Lehmann <christoph.lehmann_at_gmx.ch>

Date: Sat 16 Apr 2005 - 00:51:54 EST

data <- data.frame(c(rep("a", 4), rep("b", 4), rep("c", 4)),

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Sat Apr 16 00:40:19 2005

Date: Sat 16 Apr 2005 - 00:51:54 EST

Hi I have a question concerning aggregation

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

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")

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Sat Apr 16 00:40:19 2005

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