Create new data frame with conditional sums

dd2 <- dummydata[order(dummydata$Pct),]
dd2$Cum <- rev(cumsum(rev(dd2$Totpop)))
use <- !duplicated(dd2$Pct)
approx(dd2$Pct[use], dd2$Cum[use], ctof, method="constant", f=1, rule=2)

On 14 Oct 2023, at 17:10 , Bert Gunter <bgunter.4567 at gmail.com> wrote:

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.stout at 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


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