# define standard county names
county_name <- c(
"Adams", "Alexander", "Bond", "Boone", "Brown",
"Bureau", "Calhoun", "Carroll", "Cass", "Champaign",
"Christian", "Clark", "Clay", "Clinton", "Coles",
"Cook", "Crawford", "Cumberland", "DeKalb", "De Witt",
"Douglas", "DuPage", "Edgar", "Edwards", "Effingham",
"Fayette", "Ford", "Franklin", "Fulton", "Gallatin",
"Greene", "Grundy", "Hamilton", "Hancock", "Hardin",
"Henderson", "Henry", "Iroquois", "Jackson", "Jasper",
"Jefferson", "Jersey", "Jo Daviess", "Johnson", "Kane",
"Kankakee", "Kendall", "Knox", "Lake", "LaSalle",
"Lawrence", "Lee", "Livingston", "Logan", "McDonough",
"McHenry", "McLean", "Macon", "Macoupin", "Madison",
"Marion", "Marshall", "Mason", "Massac", "Menard",
"Mercer", "Monroe", "Montgomery", "Morgan", "Moultrie",
"Ogle", "Peoria", "Perry", "Piatt", "Pike",
"Pope", "Pulaski", "Putnam", "Randolph", "Richland",
"Rock Island", "St. Clair", "Saline", "Sangamon", "Schuyler",
"Scott", "Shelby", "Stark", "Stephenson", "Tazewell",
"Union", "Vermilion", "Wabash", "Warren", "Washington",
"Wayne", "White", "Whiteside", "Will", "Williamson",
"Winnebago", "Woodford"
)
county_std <- data.frame(
fips_number = seq(1, 203, 2) + 17000,
county_name,
stringsAsFactors = FALSE
)
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