Is `aggregate` doing anything for you? You can specify, with a formula
interface, which column in a data.frame is the variable to summarise and
which are used as factors by which to "cut" the data.
Cheers,
Roman
On Sun, May 1, 2016 at 5:30 PM, Miluji Sb <milujisb at 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
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