Dear Dennis,
Thank you for your reply. I can use the dplyr/data.table packages to
aggregate - its the matching FIPS codes to their states that I am having
trouble. Thanks again.
Sincerely,
Milu
On Sun, May 1, 2016 at 6:20 PM, Dennis Murphy <djmu...@gmail.com> wrote:
> Hi:
>
> Several such packages exist. Given the size of your data, it's likely
> that the dplyr and data.table packages would be worth investigating.
> Both are well documented.
>
> Dennis
>
> On Sun, May 1, 2016 at 8:30 AM, Miluji Sb <miluj...@gmail.com> wrote:
> > Dear all,
> >
> > I have the following data by US FIPS code. Is there a package to
> aggregate
> > the data by State and Census divisions?
> >
> > temp <- dput(head(pop1,5))
> > structure(list(FIPS = c("01001", "01003", "01005", "01007", "01009"
> > ), death_2050A1 = c(18.19158, 101.63088, 13.18896, 10.30068,
> > 131.91798), death_2050A2 = c(22.16349, 116.58387, 15.85324, 12.78564,
> > 155.20506), death_2050B1 = c(21.38906, 76.23018, 21.38218, 17.14269,
> > 151.64466), death_2050B2 = c(23.43543, 81.39378, 22.96802, 18.76926,
> > 161.86404), death_2050BC = c(21.89947, 93.88002, 18.60352, 15.1032,
> > 152.43414)), .Names = c("FIPS", "death_2050A1", "death_2050A2",
> > "death_2050B1", "death_2050B2", "death_2050BC"), row.names = c(NA,
> > 5L), class = "data.frame")
> >
> > Thank you!
> >
> > Sincerely,
> >
> > Milu
> >
> > [[alternative HTML version deleted]]
> >
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