On Jul 11, 2011, at 11:55 AM, Martin Batholdy wrote:
Hi,
I have a data.frame that looks like this:
Subject <- c(rep(1,4), rep(2,4), rep(3,4))
y <- rnorm(12, 3, 2)
gender <- c(rep("w",4), rep("m",4), rep("w",4))
comment <- c(rep("comment A",4), rep("comment B",4), rep("comment C",
4))
data <- data.frame(Subject,y,gender,comment)
data
Subject y gender comment
1 1 2.86495339 w comment A
2 1 3.33758993 w comment A
3 1 7.00301094 w comment A
4 1 3.81585998 w comment A
5 2 2.50300460 m comment B
6 2 4.93830489 m comment B
7 2 5.08184289 m comment B
8 2 4.00552691 m comment B
9 3 3.16131181 w comment C
10 3 4.61620021 w comment C
11 3 3.68288799 w comment C
12 3 -0.05049953 w comment C
So I have multiple lines for one subject because of a repeated
measurement of variable y
(the rest of the variables stay the same, like gender).
Now I would like to transform this data.frame in two ways:
1. a aggregated form,
where I only have one row left for each subject - for numerical
variables within the data.frame (like y) a mean should be calculated.
?aggregate # seems that you _should_ have already looked here.
2. a restructured form,
where I only have one row for each subject, but four different y-
columns (y1, y2, y3, y4).
You can use xtab .
data$seqvar <- ave(data$y, data$Subject, FUN=seq)
xtabs(y ~ Subject +seqvar, data=data)
or ..
# reshape (the function)
> data$seqvar <- ave(data$y, data$Subject, FUN=seq)
> reshape(data, idvar=c("Subject", "gender", "comment"),
timevar="seqvar", direction="wide")
or the easier to understand reshape or reshape2 packages.
--
David Winsemius, MD
West Hartford, CT
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