[R] Odp: For-loop

[Anne-Christine Mupepele]

>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
>-----Ursprüngliche 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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