select duplicate identifier with higher mean across sample columns
Hello, Thanks for the data example. (You forgot samp2a). Try the following. 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) idx <- ave(rowMeans(mdf[,-1]), mdf$id, FUN = function(x) x == max(x)) mdf[as.logical(idx), ] Hope this helps, Rui Barradas Em 04-11-2012 19:25, Adrian Johnson escreveu:
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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