>Hi Petr,
>
>thank you, I got it. In fact I was looking for the function aggregate()
which I didn't know.
>
>aggregate(x = t(data), by = list(cov$Month, cov$Area), FUN =
"sum")
>
>that is doing exactly what I need.
>
>Anne
>-----Urspr?ngliche Nachricht-----
>Von: "Petr PIKAL"
>Gesendet: 20.12.2010 14:23:50
>An: "Anne-Christine Mupepele" [
>Betreff: Odp: [R] For-loop
>
>>Hi
>>
>>r-help-bounces at r-project.org napsal dne 20.12.2010 11:48:51:
>>
>>> Hi,
>>> I have the following problem:
>>>
>>> I have a data.frame with 36 sample sites (colums) for which I have
>>covariates
>>> in 3 categories: Area, Month and River. Each Area consists of 3
rivers,
>>which
>>> were sampled over 3 month. Now I want to fuse River 1-3 for one
area in
>>one
>>> month. To get a data.frame with 12 colums.
>>> I am trying to do a "for loop" (which may be a
complicated solution, but
>>I
>>> don't see an easier way), which is not working, apparently
because
>>a[,ij] or a
>>> [,c(i,j)] is not working as a definition of the matrix with a
double
>>condition
>>> in the colums.
>>> How can I make it work or what would be an easier solution?
>>>
>>> Thank you for your help,
>>> Anne
>>>
>>> data=data.frame(matrix(1:99,nrow=5,ncol=36))
>>> colnames(data)=c(paste("plot",1:36))
>>>
>>cov=data.frame(rep(1:3,12),c(rep("Jan",12),rep("Feb",12),rep("Mar",12)),rep(c
>>> (1,1,1,2,2,2,3,3,3,4,4,4),3))
>>>
dimnames(cov)=list(colnames(data),c("River","Month","Area"))
>>>
>>> ###loop###
>>>
a=matrix(nrow=dim(data)[1],ncol=length(levels(factor(cov$Month)))*length
>>> (levels(factor(cov$Area))))
>>>
>>> for(i in 1:length(levels(factor(cov$Month))))
>>> {
>>> for(j in 1:length(levels(factor(cov$Area))))
>>> {
>>>
>>a[,ij]=as.numeric(rowSums(data[,factor(cov$Month)==levels(factor(cov$Month))
>>> [i]&factor(cov$Area)==levels(factor(cov$Area))[j]]))
>>> }
>>> }
>>
>>I am not exactly sure what you want to do. What operation is fuse? If it
>>is sum so having you data you can do
>>
>>area<-rep(1:12, each=3)
>>data.t<-t(data)
>>> aggregate(data.t, list(area), sum)
>> Group.1 V1 V2 V3 V4 V5
>>1 1 18 21 24 27 30
>>2 2 63 66 69 72 75
>>3 3 108 111 114 117 120
>>4 4 153 156 159 162 165
>>5 5 198 201 204 207 210
>>6 6 243 246 249 252 255
>>7 7 189 192 195 198 102
>>8 8 36 39 42 45 48
>>9 9 81 84 87 90 93
>>10 10 126 129 132 135 138
>>11 11 171 174 177 180 183
>>12 12 216 219 222 225 228
>>> t(aggregate(data.t, list(area), sum))
>> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12]
>>Group.1 1 2 3 4 5 6 7 8 9 10 11 12
>>V1 18 63 108 153 198 243 189 36 81 126 171 216
>>V2 21 66 111 156 201 246 192 39 84 129 174 219
>>V3 24 69 114 159 204 249 195 42 87 132 177 222
>>V4 27 72 117 162 207 252 198 45 90 135 180 225
>>V5 30 75 120 165 210 255 102 48 93 138 183 228
>>
>>but then there is Month value, which is not apparent from your example.
>>Maybe
>>
>>t(aggregate(data.t, list(area, data.t$Month), sum))
>>
>>Could do the trick but you probably need to show us maybe str and/or
head
>>of your real data.
>>
>>Regards
>>Petr
>>
>>>
>>> ______________________________________________
>>> 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.
>>
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