Hi Johnny,
If I understand correctly, I think you can use cut() to create a grouping
variable, and then calculate your summaries based on that. Something like
dat <- read.csv("~/Downloads/exampledata.csv")
dat$image.group <- cut(dat$a.ImageNumber, breaks = seq(0,
max(dat$a.ImageNumber), by = 3))
library(plyr)
ddply(dat, .(image.group), transform, measure.median = median(Measurement))
dat.med <- ddply(dat, .(image.group), summarize,
a.AreaShape_Area.median = median(a.AreaShape_Area),
a.Intensity_IntegratedIntensity_OrigRFP.median =
median(a.Intensity_IntegratedIntensity_OrigRFP),
a.Intensity_IntegratedIntensity_OrigGFP.median =
median(a.Intensity_IntegratedIntensity_OrigGFP),
b.Intensity_MeanIntensity_OrigGFP.median =
median(b.Intensity_MeanIntensity_OrigGFP),
EstCytoIntensity.median = median(EstCytoIntensity),
TotalIntensity.median = median(TotalIntensity),
NucToCytoRatio.median = median(NucToCytoRatio)
)
Best,
Ista
On Fri, Aug 27, 2010 at 5:28 PM, Johnny Tkach <johnny.tk...@utoronto.ca>wrote:
> Hi all,
>
>
> Since I could not attach a file to my original e-mail request, for those
> who want to look at an example of a data file I am working with, please use
> this link:
>
> http://dl.dropbox.com/u/4637975/exampledata.csv
>
> Thanks again,
>
> Johnny.
>
> ______________________________________________
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> PLEASE do read the posting guide
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> and provide commented, minimal, self-contained, reproducible code.
>
--
Ista Zahn
Graduate student
University of Rochester
Department of Clinical and Social Psychology
http://yourpsyche.org
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