This seems like it should be simple but I can't get it to work properly. I'm
starting with a data frame like this:
Tract Pct Totpop
1 0.05 4000
2 0.03 3500
3 0.01 4500
4 0.12 4100
5 0.21 3900
6 0.04 4250
7 0.07 5100
8 0.09 4700
9 0.06 4950
10 0.03 4800
And I want to end up with a data frame with two columns, a "Cutoff" column that
is a simple sequence of equally spaced cutoffs (let's say in this case from
0-0.15 by 0.01) and a "Pop" column which equals the sum of "Totpop" in the
prior data frame in which "Pct" is greater than or equal to "cutoff." So in
this toy example, this is what I want for a result:
Cutoff Pop
1 0.00 43800
2 0.01 43800
3 0.02 39300
4 0.03 39300
5 0.04 31000
6 0.05 26750
7 0.06 22750
8 0.07 17800
9 0.08 12700
10 0.09 12700
11 0.10 8000
12 0.11 8000
13 0.12 8000
14 0.13 3900
15 0.14 3900
16 0.15 3900
I can do this with a for loop but it seems there should be an easier,
vectorized way that would be more efficient. Here is a reproducible example:
dummydata<-data.frame(Tract=seq(1,10,by=1),Pct=c(0.05,0.03,0.01,0.12,0.21,0.04,0.07,0.09,0.06,0.03),Totpop=c(4000,3500,4500,4100,
3900,4250,5100,4700,
4950,4800))
dfrm<-data.frame(matrix(ncol=2,nrow=0,dimnames=list(NULL,c("Cutoff","Pop"))))
for (i in seq(0,0.15,by=0.01)) {
temp<-sum(dummydata[dummydata$Pct>=i,"Totpop"])
dfrm[nrow(dfrm)+1,]<-c(i,temp)
}
Jason Stout, MD, MHS
Division of Infectious Diseases
Dept of Medicine
Duke University
Box 102359-DUMC
Durham, NC 27710
FAX 919-681-7494
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