Analyzing US Census Data in R
Kyle Walker
Instructor
library(tigris) missouri <- tracts("MO", cb = TRUE) kansas <- tracts("KS", cb = TRUE)
attr(missouri, "tigris")
"tract"
attr(kansas, "tigris")
"tract"
kansas_missouri <- rbind_tigris(kansas, missouri)
plot(kansas_missouri$geometry)
library(tidyverse) new_england <- c("ME", "NH", "VT", "MA")
ne_tracts <- map(new_england, function(x) { tracts(state = x, cb = TRUE)}) %>% rbind_tigris()
library(tidyverse) library(sf) tx_house <- state_legislative_districts(state = "TX", house = "lower", cb = TRUE)
tx_joined <- left_join(tx_house, tx_members, by = c("NAME" = "District"))
glimpse(tx_joined)
Observations: 150
Variables: 13
$ STATEFP <chr> "48", "48", "48", "48", "48", "48", "48", ...
$ SLDLST <chr> "030", "060", "007", "109", "073", "028", ...
$ AFFGEOID <chr> "620L500US48030", "620L500US48060", "620L5...
$ GEOID <chr> "48030", "48060", "48007", "48109", "48073...
$ NAME <chr> "30", "60", "7", "109", "73", "28", "10", ...
$ LSAD <chr> "LL", "LL", "LL", "LL", "LL", "LL", "LL", ...
$ LSY <chr> "2016", "2016", "2016", "2016", "2016", "2...
$ ALAND <dbl> 10806729636, 18689750348, 2217822139, 4498...
$ AWATER <dbl> 2240468800, 297318151, 31225452, 10302637,...
$ Name <chr> "Morrison, Geanie W.", "Lang, Mike", "Dean...
$ City <chr> "Victoria", "Granbury", "Longview", "DeSot...
$ Party <chr> "R", "R", "R", "D", "R", "R", "R", "D", "D...
$ geometry <MULTIPOLYGON [°]> MULTIPOLYGON (((-97.07866 2.....
Analyzing US Census Data in R