Here is one way
Here is one way:
> con <- textConnection("
+ ID TIME OBS
+ 001 2200 23
+ 001 2400 11
+ 001 3200 10
+ 001 4500 22
+ 003 3900 45
+ 003 5605 32
+ 005 1800 56
+ 005 1900 34
+ 005 2300 23")
> dat <- read.table(con, header = TRUE,
+ colClasses = c("factor", "numeric", "numeric"))
> closeAllConnections()
>
> tmp <- lapply(split(dat, dat$ID),
+ function(x) within(x, TIME <- TIME - min(TIME)))
> split(dat, dat$ID) <- tmp
> dat
ID TIME OBS
1 001 0 23
2 001 200 11
3 001 1000 10
4 001 2300 22
5 003 0 45
6 003 1705 32
7 005 0 56
8 005 100 34
9 005 500 23
>
________________________________________
From: r-help-boun...@r-project.org [r-help-boun...@r-project.org] On Behalf Of
Matthew Strother [rstro...@gmail.com]
Sent: 16 January 2011 07:26
To: r-help@r-project.org
Subject: [R] data prep question
I have a data set with several thousand observations across time, grouped by
subject (example format below)
ID TIME OBS
001 2200 23
001 2400 11
001 3200 10
001 4500 22
003 3900 45
003 5605 32
005 1800 56
005 1900 34
005 2300 23
...
I would like to identify the first time for each subject, and then subtract
this value from each subsequent time. However, the number of observations per
subject varies widely (from 1 to 20), and the intervals between times varies
widely. Is there a package that can help do this, or a loop that can be set
up to evaluate ID, then calculate the values? The outcome I would like is
presented below.
ID TIME OBS
001 0 23
001 200 11
001 1000 10
001 2300 22
003 0 45
003 1705 32
005 0 56
005 100 34
005 500 23
...
Any help appreciated.
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______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
