summing a range of columns in data frame - r

Question

I am having trouble summing select columns within a data frame, a basic problem that I've seen numerous similar, but not identical questions/answers for on StackOverflow.
With this perhaps overly complex data frame:
site<-c(223,257,223,223,257,298,223,298,298,211)
moisture<-c(7,7,7,7,7,8,7,8,8,5)
shade<-c(83,18,83,83,18,76,83,76,76,51)
sampleID<-c(158,163,222,107,106,166,188,186,262,114)
bluestm<-c(3,4,6,3,0,0,1,1,1,0)
foxtail<-c(0,2,0,4,0,1,1,0,3,0)
crabgr<-c(0,0,2,0,33,0,2,1,2,0)
johnson<-c(0,0,0,7,0,8,1,0,1,0)
sedge1<-c(2,0,3,0,0,9,1,0,4,0)
sedge2<-c(0,0,1,0,1,0,0,1,1,1)
redoak<-c(9,1,0,5,0,4,0,0,5,0)
blkoak<-c(0,22,0,23,0,23,22,17,0,0)
my.data<-data.frame(site,moisture,shade,sampleID,bluestm,foxtail,crabgr,johnson,sedge1,sedge2,redoak,blkoak)
I want to sum the counts of each plant species (bluestem, foxtail, etc. - columns 4-12 in this example) within each site, by summing rows that have the same site number. I also want to keep information about moisture and shade (these are consistant withing site, but may also be the same between sites), and want a new column that is the count of number of rows summed.
the result would look like this
site,moisture,shade,NumSamples,bluestm,foxtail,crabgr,johnson,sedge1,sedge2,redoak,blkoak
211,5,51,1,0,0,0,0,0,1,0,0
223,7,83,4,13,5,4,8,6,1,14,45
257,7,18,2,4,2,33,0,0,1,1,22
298,8,76,3,2,4,3,9,13,2,9,40
The problem I am having is that, my real data sets (and I have several of them) have from 50 to 300 plant species, and I want refer a range of columns (in this case, [5:12] ) instead of my.data$foxtail, my.data$sedge1, etc., which is going to be very difficult with 300 species.
I know I can start off by deleting the column I don't need (SampleID)
my.data$SampleID <- NULL
but then how do I get the sums? I've messed with the aggregate command and with ddply, and have seen lots of examples which call particular column names, but just haven't gotten anything to work. I recognize this is a variant of a commonly asked and simple type of question, but I've spent hours without resolving it on my own. So, apologies for my stupidity!

Answer 1

This works ok:
x <- aggregate(my.data[,5:12], by=list(site=my.data$site, moisture=my.data$moisture, shade=my.data$shade), FUN=sum, na.rm=T)
library(dplyr)
my.data %>%
group_by(site) %>%
tally %>%
left_join(x)
site n moisture shade bluestm foxtail crabgr johnson sedge1 sedge2 redoak blkoak
1 211 1 5 51 0 0 0 0 0 1 0 0
2 223 4 7 83 13 5 4 8 6 1 14 45
3 257 2 7 18 4 2 33 0 0 1 1 22
4 298 3 8 76 2 4 3 9 13 2 9 40
Or to do it all in dplyr
my.data %>%
group_by(site) %>%
tally %>%
left_join(my.data) %>%
group_by(site,moisture,shade,n) %>%
summarise_each(funs(sum=sum)) %>%
select(-sampleID)
site moisture shade n bluestm foxtail crabgr johnson sedge1 sedge2 redoak blkoak
1 211 5 51 1 0 0 0 0 0 1 0 0
2 223 7 83 4 13 5 4 8 6 1 14 45
3 257 7 18 2 4 2 33 0 0 1 1 22
4 298 8 76 3 2 4 3 9 13 2 9 40

Answer 2

Try following using base R:
outdf<-data.frame(site=numeric(),moisture=numeric(),shade=numeric(),bluestm=numeric(),foxtail=numeric(),crabgr=numeric(),johnson=numeric(),sedge1=numeric(),sedge2=numeric(),redoak=numeric(),blkoak=numeric())
my.data$basic = with(my.data, paste(site, moisture, shade))
for(b in unique(my.data$basic)) {
outdf[nrow(outdf)+1,1:3] = unlist(strsplit(b,' '))
for(i in 4:11)
outdf[nrow(outdf),i]= sum(my.data[my.data$basic==b,i])
}
outdf
site moisture shade bluestm foxtail crabgr johnson sedge1 sedge2 redoak blkoak
1 223 7 83 13 5 4 8 6 1 14 45
2 257 7 18 4 2 33 0 0 1 1 22
3 298 8 76 2 4 3 9 13 2 9 40
4 211 5 51 0 0 0 0 0 1 0 0