Is this what you want:
> mdf <- read.table(text = " id samp1 samp2 samp2a
+ 1 A 100 110 110
+ 2 A 120 130 150
+ 3 C 101 131 151
+ 4 D 110 150 130
+ 5 E 132 122 122
+ 6 F 123 143 143", header = TRUE)
> result <- do.call(rbind, lapply(split(mdf, mdf$id), function(.id){
+ maxIndx <- which.max(rowMeans(.id[, -1L]))
+ .id[maxIndx, ]
+ }))
>
> result
id samp1 samp2 samp2a
A A 120 130 150
C C 101 131 151
D D 110 150 130
E E 132 122 122
F F 123 143 143
On Sun, Nov 4, 2012 at 2:25 PM, Adrian Johnson
<oriolebaltim...@gmail.com> wrote:
> Hi Group:
> I searched R groups before posting this question. I could not find the
> appropriate answer and I do not have clear understanding how to do
> this in R.
>
> I have a data frame with duplicated row identifiers but with different
> values across columns. I want to select the identifier with higher
> inter-quartile range or mean.
>
>
> id <- c("A", "A", "C", "D", "E", "F")
> year <- c(2000, 2001, 2001, 2002, 2003, 2004)
> samp1 <- c(100, 120, 101, 110, 132,123)
> samp2 <- c(110, 130, 131, 150, 122,143)
> mdf <- data.frame(id,samp1,samp2,samp2a)
>
>
>> mdf
> id samp1 samp2 samp2a
> 1 A 100 110 110
> 2 A 120 130 150
> 3 C 101 131 151
> 4 D 110 150 130
> 5 E 132 122 122
> 6 F 123 143 143
>
>
> There are two A ids in this df. I want to select the row with higher mean.
>
> How can I do this.
> Thanks
> Adrian
>
> ______________________________________________
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
--
Jim Holtman
Data Munger Guru
What is the problem that you are trying to solve?
Tell me what you want to do, not how you want to do it.
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