r - Weighting maximum abundance by the number of samples -

i have dataset contains data on abundance of organism , sediment mud content % in found.

i have subsequently partitioned mud content data 10 bins (i.e. 0 - 10%, 10.1 - 20% etc) , placed abundance data each bin accordingly.

the primary aim plot maximum abundance in each mud bin on mud gradient (i.e. 0 - 100 %) these maximums weighted number of samples in each bin.

so, question how weight maximum abundance in given mud bin number of samples in each bin?

here simple subset of data:

mud % bins: |     0 - 9      |     9.1 - 18      |     18.1 - 27    | abundance:   10,10,2,2,2,1,1      15,15,15,2      20,20,20,1,1,1,1,1 

you can use ddply plyr package that. in following code,wtdabundance weighted abundance= (max of bin*number of observation of bin)/total observation sample data,

mydata<-structure(list(id = 1:19, bin = structure(c(1l, 1l, 1l, 1l, 1l,  1l, 1l, 3l, 3l, 3l, 3l, 2l, 2l, 2l, 2l, 2l, 2l, 2l, 2l), .label = c("0-9",  "18.1-27", "9.1-18"), class = "factor"), abundance = c(10l, 10l,  2l, 2l, 2l, 1l, 1l, 15l, 15l, 15l, 2l, 20l, 20l, 20l, 1l, 1l,  1l, 1l, 1l)), .names = c("id", "bin", "abundance"), class = "data.frame", row.names = c(na,  -19l)) > mydata    id     bin abundance 1   1     0-9        10 2   2     0-9        10 3   3     0-9         2 4   4     0-9         2 5   5     0-9         2 6   6     0-9         1 7   7     0-9         1 8   8  9.1-18        15 9   9  9.1-18        15 10 10  9.1-18        15 11 11  9.1-18         2 12 12 18.1-27        20 13 13 18.1-27        20 14 14 18.1-27        20 15 15 18.1-27         1 16 16 18.1-27         1 17 17 18.1-27         1 18 18 18.1-27         1 19 19 18.1-27         1    ddply(dat,.(bin), summarize, max.abundance=max(abundance), freq=length(bin),mwtdabundance=((max.abundance*freq/nrow(dat))))       bin max.abundance freq mwtdabundance 1     0-9            10    7      3.684211 2 18.1-27            20    8      8.421053 3  9.1-18            15    4      3.157895