# Source: https://www2.census.gov/geo/pdfs/maps-data/maps/reference/us_regdiv.pdf
state_table <-
data.frame(
state_name = state.name,
state_usps = state.abb,
census_region = as.character(state.region),
census_division = as.character(state.division),
stringsAsFactors = FALSE
)
state_table <-
rbind(
state_table,
data.frame(
state_name = "District of Columbia",
state_usps = "DC",
census_region = "",
census_division = "",
stringsAsFactors = FALSE
)
)
state_table <-
state_table[order(state_table$state_name), ]
state_table$census_region[
state_table$census_region == "North Central"
] <- "Midwest"
state_table$census_region[state_table$state_usps == "DC"] <- "South"
state_table$census_division[state_table$state_usps == "DC"] <- "South Atlantic"
region_map <- c(Northeast = 1, Midwest = 2, South = 3, West = 4)
division_map <- c(
"New England" = 1,
"Middle Atlantic" = 2,
"East North Central" = 3,
"West North Central" = 4,
"South Atlantic" = 5,
"East South Central" = 6,
"West South Central" = 7,
"Mountain" = 8,
"Pacific" = 9
)
state_table$census_region_number <- region_map[state_table$census_region]
state_table$census_division_number <- division_map[state_table$census_division]
fips_map <- c(
AL = "01",
AK = "02",
AZ = "04",
AR = "05",
CA = "06",
CO = "08",
CT = "09",
DE = "10",
DC = "11",
FL = "12",
GA = "13",
HI = "15",
ID = "16",
IL = "17",
IN = "18",
IA = "19",
KS = "20",
KY = "21",
LA = "22",
ME = "23",
MD = "24",
MA = "25",
MI = "26",
MN = "27",
MS = "28",
MO = "29",
MT = "30",
NE = "31",
NV = "32",
NH = "33",
NJ = "34",
NM = "35",
NY = "36",
NC = "37",
ND = "38",
OH = "39",
OK = "40",
OR = "41",
PA = "42",
RI = "44",
SC = "45",
SD = "46",
TN = "47",
TX = "48",
UT = "49",
VT = "50",
VA = "51",
WA = "53",
WV = "54",
WI = "55",
WY = "56"
)
state_table$state_fips <- fips_map[state_table$state_usps]
rownames(state_table) <- NULL
