Odp: Calculated mean value based on another column bin from dataframe.

Hi


r-help-bounces at r-project.org napsal dne 06.04.2011 10:48:04:

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?

Do you want something like that?

#make data
x<-runif(100)
y<-runif(100)

#cut first column to bins (in your case dat[,1] and ran)
x.c<-cut(x, seq(0,1,.1))

#aggregate column 2 according to bins (in your case dat[,2])
aggregate(y,list(x.c), mean)
? ? Group.1 ? ? ? ? x
1 ? ?(0,0.1] 0.5868734
2 ?(0.1,0.2] 0.5436263
3 ?(0.2,0.3] 0.5099366
4 ?(0.3,0.4] 0.4815855
5 ?(0.4,0.5] 0.4137687
6 ?(0.5,0.6] 0.4698156
7 ?(0.6,0.7] 0.4687639
8 ?(0.7,0.8] 0.5661048
9 ?(0.8,0.9] 0.5489297
10 ? (0.9,1] 0.4812521

Regards
Petr

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")