Calculated mean value based on another column bin from dataframe.
Dear Henrique Dallazuanna, Thank you very much for your suggestion. It is obvious that your method is better than me. Is it possible to use cut, table,by etc? Whether there is some aggregate function in R can do this? Thanks.
On Wed, Apr 6, 2011 at 2:16 PM, Henrique Dallazuanna <wwwhsd at gmail.com> wrote:
Try this: fil <- sapply(ran, '<', e1 = dat[,1]) & sapply(ran[2:(length(ran) + 1)], '>=', e1 = dat[,1]) mm <- apply(fil, 2, function(idx)mean(dat[idx, 2])) On Wed, Apr 6, 2011 at 5:48 AM, Fabrice Tourre <fabrice.ciup at gmail.com> wrote:
Dear list, I have a dataframe with two column as fellow.
head(dat)
? ? ? V1 ? ? ?V2
?0.15624 0.94567
?0.26039 0.66442
?0.16629 0.97822
?0.23474 0.72079
?0.11037 0.83760
?0.14969 0.91312
I want to get the column V2 mean value based on the bin of column of
V1. I write the code as fellow. It works, but I think this is not the
elegant way. Any suggestions?
dat<-read.table("dat.txt",head=F)
ran<-seq(0,0.5,0.05)
mm<-NULL
for (i in c(1:(length(ran)-1)))
{
? ?fil<- dat[,1] > ran[i] & dat[,1]<=ran[i+1]
? ?m<-mean(dat[fil,2])
? ?mm<-c(mm,m)
}
mm
Here is the first 20 lines of my data.
dput(head(dat,20))
structure(list(V1 = c(0.15624, 0.26039, 0.16629, 0.23474, 0.11037,
0.14969, 0.16166, 0.09785, 0.36417, 0.08005, 0.29597, 0.14856,
0.17307, 0.36718, 0.11621, 0.23281, 0.10415, 0.1025, 0.04238,
0.13525), V2 = c(0.94567, 0.66442, 0.97822, 0.72079, 0.8376,
0.91312, 0.88463, 0.82432, 0.55582, 0.9429, 0.78956, 0.93424,
0.87692, 0.83996, 0.74552, 0.9779, 0.9958, 0.9783, 0.92523, 0.99022
)), .Names = c("V1", "V2"), row.names = c(NA, 20L), class = "data.frame")
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-- Henrique Dallazuanna Curitiba-Paran?-Brasil 25? 25' 40" S 49? 16' 22" O
______________________________________________ R-help at 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.