Well, here's one way to do it:
(dat is your example data frame)
Cutoff <- seq(0, .15, .01)
Pop <- with(dat, sapply(Cutoff, \(p)sum(Totpop[Pct >= p])))
I think there must be a more efficient way to do it with cumsum(), though.
Cheers,
Bert
On Sat, Oct 14, 2023 at 12:53 AM Jason Stout, M.D. <jason.st...@duke.edu> wrote:
>
> 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
>
>
> [[alternative HTML version deleted]]
>
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