Hi,
You could also try:
library(plyr)
ddply(mutate(sardat,sec=as.numeric(gsub(".*:(.*)\\..*$","\\1",sardat$V1))),.(sec),
numcolwise(mean))
# sec V2 V3 V4 V5 V6
#1 46 15.00000 3.800000 11.200000 4.600000 17.80000
#2 47 14.28571 4.428571 9.857143 3.428571 16.85714
A.K.
On Tuesday, March 18, 2014 6:47 PM, Jim Lemon <j...@bitwrit.com.au> wrote:
On 03/19/2014 02:26 AM, Satish Anupindi Rao wrote:
> Hi,
> ...
> I would like to find the mean of the V2 to V6 columns on a per second
> interval. Would anyone please be able to help me with a function and
> implementation for that please?
>
Hi Satish,
If you don't care about the location of the intervals, try this:
sardat<-read.table(text="V0 V1 V2 V3 V4 V5 V6
2014-03-14 22:41:46.988804 10 2 8 3 14
2014-03-14 22:41:46.991126 13 4 9 5 15
2014-03-14 22:41:46.993506 12 4 8 3 14
2014-03-14 22:41:46.993755 19 4 15 5 22
2014-03-14 22:41:46.997780 21 5 16 7 24
2014-03-14 22:41:47.000154 18 5 13 3 21
2014-03-14 22:41:47.002376 21 5 16 6 23
2014-03-14 22:41:47.011106 12 4 8 3 14
2014-03-14 22:41:47.012691 12 4 8 3 16
2014-03-14 22:41:47.017579 11 2 9 3 12
2014-03-14 22:41:47.019463 12 5 7 3 15
2014-03-14 22:41:47.020247 14 6 8 3 17",
header=TRUE,stringsAsFactors=FALSE)
getsec<-function(x) {
unlist(strsplit(unlist(strsplit(x,":"))[3],"[.]"))[1]
}
sardat$sec<-sapply(sardat$V1,getsec)
sapply(sardat[,c("V2","V3","V4","V5","V6")],by,sardat$sec,mean)
Jim
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