Tom,
Here is my solution. Note that I assume the columns are interleaved as you
describe below. I'm sure others will have better replies.
Note that using dput helps the helpers.
# From dput(mdat)
mdat-structure(list(x1 = c(2L, 2L, 2L, 3L, 3L, 30L, 32L, 33L, 33L),
y1 = c(100L, 100L, 100L,
HI,
You could also try:
dat2- dat1[-ncol(dat1)]
fun1- function(dat,value){
datNew- dat
n1- ncol(datNew)
indx1- seq(1,n1,by=2)
indx2- indx1+1
datNew[indx2][datNew[indx1] value]-NA
dat$output-rowMeans(datNew[indx2],na.rm=TRUE)
dat
}
fun1(dat2,10)
# x1 y1 x2
Hi
I have a dataframe as below:
x1y1x2y2x3y3output
21001909914307989
21001926314317569
21001926314445157
301959914995074.5
301989815008089
300198
HI,
May be this helps:
dat1- read.table(text=
x1 y1 x2 y2 x3 y3 output
2 100 190 99 1430 79 89
2 100 192 63 1431 75 69
2 100 192 63 1444 51 57
3 0 195 99 1499 50 74.5
3 0 198 98 1500 80 89
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