The R package {fips} makes it easier to merge geographic identifiers such as state FIPS, county FIPS, urban-rural codes, BEA region codes, and census region and division codes.
For an overview of regions of the United States, see the wiki page for List of regions of the United States.
The following datasets are available:
fips::fips
,fips::state
, andfips::lower48
:- State-level FIPS codes. (Source)
fips::fips
contains 50 states, the District of Columbia, and the Outlying Areas of the United States.fips::state
contains 50 states and the District of Columbia.fips::lower48
contains the 48 Contiguous Continental States and the District of Columbia.
fips::county
,fips::county_ipums_usa
fips::nchs_urc
:- NCHS Urban-Rural Classification Scheme for Counties. (Source)
fips::bea_region
:- BEA Region codes. (Source)
fips::census_region_division
:- Census Bureau region and division codes. (Source)
I might add other crosswalks for OMB standard federal regions, federal reserve districts, courts of appeals circuits, and Agricultural Research Service regions.
Similar implementation in Stata:
Similar R packages:
You can install the development version of {fips} from Github with:
# install.packages("remotes")
remotes::install_github("jjchern/fips")
Or install the most recent released version of {fips} from Github with:
remotes::install_github("jjchern/fips@v0.0.5")
library(tidyverse)
fips::state
#> # A tibble: 51 x 3
#> fips usps state
#> <chr> <chr> <chr>
#> 1 01 AL Alabama
#> 2 02 AK Alaska
#> 3 04 AZ Arizona
#> 4 05 AR Arkansas
#> 5 06 CA California
#> 6 08 CO Colorado
#> 7 09 CT Connecticut
#> 8 10 DE Delaware
#> 9 11 DC District of Columbia
#> 10 12 FL Florida
#> # … with 41 more rows
# fips::fips includes FIPS code for other outlying areas
fips::fips
#> # A tibble: 57 x 3
#> fips usps state
#> <chr> <chr> <chr>
#> 1 01 AL Alabama
#> 2 02 AK Alaska
#> 3 04 AZ Arizona
#> 4 05 AR Arkansas
#> 5 06 CA California
#> 6 08 CO Colorado
#> 7 09 CT Connecticut
#> 8 10 DE Delaware
#> 9 11 DC District of Columbia
#> 10 12 FL Florida
#> # … with 47 more rows
fips::fips %>% tail(10)
#> # A tibble: 10 x 3
#> fips usps state
#> <chr> <chr> <chr>
#> 1 53 WA Washington
#> 2 54 WV West Virginia
#> 3 55 WI Wisconsin
#> 4 56 WY Wyoming
#> 5 60 AS American Samoa
#> 6 66 GU Guam
#> 7 69 MP Northern Mariana Islands
#> 8 72 PR Puerto Rico
#> 9 74 UM U.S. Minor Outlying Islands
#> 10 78 VI U.S. Virgin Islands
# fips::lower48 includes the 48 continental states and DC
fips::lower48
#> # A tibble: 49 x 3
#> fips usps state
#> <chr> <chr> <chr>
#> 1 01 AL Alabama
#> 2 04 AZ Arizona
#> 3 05 AR Arkansas
#> 4 06 CA California
#> 5 08 CO Colorado
#> 6 09 CT Connecticut
#> 7 10 DE Delaware
#> 8 11 DC District of Columbia
#> 9 12 FL Florida
#> 10 13 GA Georgia
#> # … with 39 more rows
fips::county
#> # A tibble: 3,235 x 4
#> usps state fips county
#> <chr> <chr> <chr> <chr>
#> 1 AL Alabama 01001 Autauga County
#> 2 AL Alabama 01003 Baldwin County
#> 3 AL Alabama 01005 Barbour County
#> 4 AL Alabama 01007 Bibb County
#> 5 AL Alabama 01009 Blount County
#> 6 AL Alabama 01011 Bullock County
#> 7 AL Alabama 01013 Butler County
#> 8 AL Alabama 01015 Calhoun County
#> 9 AL Alabama 01017 Chambers County
#> 10 AL Alabama 01019 Cherokee County
#> # ... with 3,225 more rows
fips::county_ipums_usa %>%
select(state, countyfip, county_name,
`2000 5% & 1% unwt, acs 2005`,
`acs 2006-2011`,
`2010 10%, acs 2012-onward`) %>%
na.omit() %>%
select(state, countyfip, county_name) %>%
knitr::kable()
state | countyfip | county_name |
---|---|---|
Alabama | 01003 | Baldwin |
Alabama | 01015 | Calhoun/Benton |
Alabama | 01055 | Etowah |
Alabama | 01073 | Jefferson |
Alabama | 01081 | Lee |
Alabama | 01097 | Mobile |
Alabama | 01117 | Shelby |
Alaska | 02020 | Anchorage |
Arizona | 04005 | Coconino |
Arizona | 04013 | Maricopa |
Arizona | 04019 | Pima |
Arizona | 04025 | Yavapai |
Arizona | 04027 | Yuma |
Arkansas | 05007 | Benton |
Arkansas | 05119 | Pulaski |
Arkansas | 05143 | Washington |
California | 06001 | Alameda |
California | 06007 | Butte |
California | 06013 | Contra Costa |
California | 06017 | El Dorado |
California | 06019 | Fresno |
California | 06023 | Humboldt |
California | 06025 | Imperial |
California | 06029 | Kern |
California | 06031 | Kings |
California | 06037 | Los Angeles |
California | 06039 | Madera |
California | 06041 | Marin |
California | 06047 | Merced |
California | 06055 | Napa |
California | 06059 | Orange |
California | 06061 | Placer |
California | 06065 | Riverside |
California | 06067 | Sacramento |
California | 06071 | San Bernardino |
California | 06073 | San Diego |
California | 06075 | San Francisco |
California | 06077 | San Joaquin |
California | 06079 | San Luis Obispo |
California | 06081 | San Mateo |
California | 06083 | Santa Barbara |
California | 06085 | Santa Clara |
California | 06087 | Santa Cruz |
California | 06089 | Shasta |
California | 06095 | Solano |
California | 06097 | Sonoma |
California | 06099 | Stanislaus |
California | 06107 | Tulare |
California | 06111 | Ventura |
California | 06113 | Yolo |
Connecticut | 09001 | Fairfield |
Connecticut | 09003 | Hartford |
Connecticut | 09005 | Litchfield |
Connecticut | 09007 | Middlesex |
Connecticut | 09009 | New Haven |
Connecticut | 09011 | New London |
Connecticut | 09013 | Tolland |
Connecticut | 09015 | Windham |
Delaware | 10001 | Kent |
Delaware | 10003 | New Castle |
Delaware | 10005 | Sussex |
District of Columbia | 11001 | District of Columbia |
Florida | 12001 | Alachua |
Florida | 12009 | Brevard/St Lucie |
Florida | 12011 | Broward |
Florida | 12015 | Charlotte |
Florida | 12019 | Clay |
Florida | 12021 | Collier |
Florida | 12033 | Escambia |
Florida | 12053 | Hernando/Benton |
Florida | 12057 | Hillsborough |
Florida | 12071 | Lee |
Florida | 12081 | Manatee |
Florida | 12083 | Marion |
Florida | 12085 | Martin |
Florida | 12091 | Okaloosa |
Florida | 12095 | Orange/Mesquito |
Florida | 12097 | Osceola |
Florida | 12099 | Palm Beach |
Florida | 12101 | Pasco |
Florida | 12103 | Pinellas |
Florida | 12105 | Polk |
Florida | 12111 | St Lucie |
Florida | 12113 | Santa Rosa |
Florida | 12115 | Sarasota |
Florida | 12117 | Seminole |
Georgia | 13021 | Bibb |
Georgia | 13051 | Chatham |
Georgia | 13057 | Cherokee |
Georgia | 13063 | Clayton |
Georgia | 13067 | Cobb |
Georgia | 13135 | Gwinnett |
Georgia | 13139 | Hall |
Georgia | 13151 | Henry |
Georgia | 13245 | Richmond |
Hawaii | 15001 | Hawaii |
Hawaii | 15003 | Honolulu |
Illinois | 17019 | Champaign |
Illinois | 17031 | Cook |
Illinois | 17043 | Du Page |
Illinois | 17091 | Kankakee |
Illinois | 17097 | Lake |
Illinois | 17099 | LaSalle |
Illinois | 17113 | McLean |
Illinois | 17115 | Macon |
Illinois | 17179 | Tazewell |
Indiana | 18003 | Allen |
Indiana | 18035 | Delaware |
Indiana | 18039 | Elkhart |
Indiana | 18081 | Johnson |
Indiana | 18089 | Lake |
Indiana | 18091 | La Porte |
Indiana | 18097 | Marion |
Indiana | 18105 | Monroe |
Indiana | 18127 | Porter |
Indiana | 18141 | St Joseph |
Iowa | 19013 | Black Hawk |
Iowa | 19103 | Johnson |
Iowa | 19113 | Linn |
Iowa | 19163 | Scott |
Kansas | 20091 | Johnson |
Kansas | 20209 | Wyandotte |
Kentucky | 21067 | Fayette |
Kentucky | 21111 | Jefferson |
Kentucky | 21117 | Kenton |
Louisiana | 22017 | Caddo |
Louisiana | 22073 | Ouachita |
Louisiana | 22109 | Terrebonne |
Maine | 23001 | Androscoggin |
Maine | 23011 | Kennebec |
Maryland | 24003 | Anne Arundel |
Maryland | 24005 | Baltimore |
Maryland | 24013 | Carroll |
Maryland | 24017 | Charles |
Maryland | 24021 | Frederick |
Maryland | 24025 | Harford |
Maryland | 24027 | Howard |
Maryland | 24031 | Montgomery |
Maryland | 24033 | Prince Georges |
Maryland | 24043 | Washington |
Maryland | 24510 | Baltimore City |
Massachusetts | 25025 | Suffolk |
Michigan | 26021 | Berrien |
Michigan | 26075 | Jackson |
Michigan | 26081 | Kent |
Michigan | 26093 | Livingston |
Michigan | 26099 | Macomb |
Michigan | 26115 | Monroe |
Michigan | 26121 | Muskegon |
Michigan | 26125 | Oakland |
Michigan | 26139 | Ottawa |
Michigan | 26145 | Saginaw |
Michigan | 26161 | Washtenaw |
Michigan | 26163 | Wayne |
Minnesota | 27003 | Anoka |
Minnesota | 27037 | Dakota |
Minnesota | 27053 | Hennepin |
Minnesota | 27109 | Olmsted |
Minnesota | 27123 | Ramsey |
Minnesota | 27163 | Washington |
Mississippi | 28033 | De Soto |
Mississippi | 28047 | Harrison |
Mississippi | 28059 | Jackson |
Missouri | 29019 | Boone |
Missouri | 29099 | Jefferson |
Missouri | 29183 | St Charles |
Missouri | 29189 | St Louis |
Missouri | 29510 | St Louis City |
Nebraska | 31055 | Douglas |
Nebraska | 31109 | Lancaster |
Nevada | 32003 | Clark |
Nevada | 32031 | Washoe |
New Jersey | 34003 | Bergen |
New Jersey | 34005 | Burlington |
New Jersey | 34007 | Camden |
New Jersey | 34013 | Essex |
New Jersey | 34017 | Hudson |
New Jersey | 34019 | Hunterdon |
New Jersey | 34021 | Mercer |
New Jersey | 34023 | Middlesex |
New Jersey | 34025 | Monmouth |
New Jersey | 34027 | Morris |
New Jersey | 34029 | Ocean |
New Jersey | 34031 | Passaic |
New Jersey | 34035 | Somerset |
New Jersey | 34037 | Sussex |
New Jersey | 34039 | Union |
New Jersey | 34041 | Warren |
New Mexico | 35013 | Dona Ana |
New York | 36001 | Albany |
New York | 36005 | Bronx |
New York | 36013 | Chautauqua |
New York | 36027 | Dutchess |
New York | 36029 | Erie |
New York | 36047 | Kings |
New York | 36059 | Nassau |
New York | 36061 | New York |
New York | 36063 | Niagara |
New York | 36071 | Orange |
New York | 36075 | Oswego |
New York | 36081 | Queens |
New York | 36083 | Rensselaer |
New York | 36085 | Richmond |
New York | 36087 | Rockland |
New York | 36089 | St Lawrence |
New York | 36091 | Saratoga |
New York | 36093 | Schenectady |
New York | 36103 | Suffolk |
North Carolina | 37001 | Alamance |
North Carolina | 37035 | Catawba |
North Carolina | 37051 | Cumberland |
North Carolina | 37057 | Davidson |
North Carolina | 37067 | Forsyth |
North Carolina | 37081 | Guilford |
North Carolina | 37119 | Mecklenburg |
North Carolina | 37147 | Pitt |
North Carolina | 37151 | Randolph |
North Carolina | 37159 | Rowan |
North Carolina | 37191 | Wayne |
North Dakota | 38017 | Cass |
Ohio | 39007 | Ashtabula |
Ohio | 39017 | Butler |
Ohio | 39029 | Columbiana |
Ohio | 39035 | Cuyahoga |
Ohio | 39041 | Delaware |
Ohio | 39045 | Fairfield |
Ohio | 39049 | Franklin |
Ohio | 39057 | Greene |
Ohio | 39061 | Hamilton |
Ohio | 39089 | Licking |
Ohio | 39093 | Lorain |
Ohio | 39103 | Medina |
Ohio | 39113 | Montgomery |
Ohio | 39133 | Portage |
Ohio | 39139 | Richland |
Ohio | 39153 | Summit |
Ohio | 39165 | Warren |
Ohio | 39169 | Wayne |
Oregon | 41017 | Deschutes |
Oregon | 41019 | Douglas |
Oregon | 41029 | Jackson |
Oregon | 41039 | Lane |
Oregon | 41047 | Marion |
Pennsylvania | 42003 | Allegheny |
Pennsylvania | 42011 | Berks |
Pennsylvania | 42017 | Bucks |
Pennsylvania | 42019 | Butler |
Pennsylvania | 42027 | Centre |
Pennsylvania | 42029 | Chester |
Pennsylvania | 42043 | Dauphin |
Pennsylvania | 42045 | Delaware |
Pennsylvania | 42049 | Erie |
Pennsylvania | 42051 | Fayette |
Pennsylvania | 42071 | Lancaster |
Pennsylvania | 42075 | Lebanon |
Pennsylvania | 42085 | Mercer |
Pennsylvania | 42089 | Monroe |
Pennsylvania | 42091 | Montgomery |
Pennsylvania | 42101 | Philadelphia |
Pennsylvania | 42107 | Schuylkill |
Pennsylvania | 42129 | Westmoreland |
Pennsylvania | 42133 | York |
Rhode Island | 44003 | Kent |
Rhode Island | 44007 | Providence |
Rhode Island | 44009 | Washington |
South Carolina | 45007 | Anderson |
South Carolina | 45051 | Horry |
South Carolina | 45083 | Spartanburg |
South Carolina | 45091 | York |
Tennessee | 47009 | Blount |
Tennessee | 47037 | Davidson |
Tennessee | 47149 | Rutherford |
Tennessee | 47157 | Shelby |
Tennessee | 47179 | Washington |
Tennessee | 47187 | Williamson |
Texas | 48029 | Bexar |
Texas | 48039 | Brazoria |
Texas | 48041 | Brazos |
Texas | 48061 | Cameron |
Texas | 48085 | Collin |
Texas | 48113 | Dallas |
Texas | 48121 | Denton |
Texas | 48135 | Ector |
Texas | 48139 | Ellis |
Texas | 48141 | El Paso |
Texas | 48157 | Fort Bend |
Texas | 48167 | Galveston |
Texas | 48201 | Harris |
Texas | 48215 | Hidalgo |
Texas | 48245 | Jefferson |
Texas | 48251 | Johnson |
Texas | 48303 | Lubbock |
Texas | 48309 | McLennan |
Texas | 48329 | Midland |
Texas | 48375 | Potter |
Texas | 48381 | Randall |
Texas | 48423 | Smith |
Texas | 48441 | Taylor |
Texas | 48479 | Webb |
Texas | 48485 | Wichita |
Texas | 48491 | Williamson |
Utah | 49011 | Davis |
Utah | 49035 | Salt Lake |
Utah | 49049 | Utah |
Utah | 49057 | Weber |
Virginia | 51013 | Arlington/Alexandria |
Virginia | 51041 | Chesterfield |
Virginia | 51087 | Henrico |
Virginia | 51510 | Alexandria City |
Virginia | 51550 | Chesapeake City |
Virginia | 51650 | Hampton |
Virginia | 51700 | Newport News |
Virginia | 51760 | Richmond City |
Virginia | 51810 | Virginia Beach City |
Washington | 53011 | Clark |
Washington | 53033 | King |
Washington | 53035 | Kitsap |
Washington | 53053 | Pierce |
Washington | 53061 | Snohomish |
Washington | 53063 | Spokane |
Washington | 53067 | Thurston |
Washington | 53073 | Whatcom |
Washington | 53077 | Yakima |
Wisconsin | 55009 | Brown |
Wisconsin | 55025 | Dane |
Wisconsin | 55059 | Kenosha |
Wisconsin | 55063 | La Crosse |
Wisconsin | 55073 | Marathon |
Wisconsin | 55101 | Racine |
Wisconsin | 55105 | Rock |
Wisconsin | 55117 | Sheboygan |
fips::census_region_division
#> # A tibble: 51 x 7
#> fips usps state region_cd region_name division_cd division_name
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 01 AL Alabama 3 South 6 East South Ce…
#> 2 02 AK Alaska 4 West 9 Pacific
#> 3 04 AZ Arizona 4 West 8 Mountain
#> 4 05 AR Arkansas 3 South 7 West South Ce…
#> 5 06 CA California 4 West 9 Pacific
#> 6 08 CO Colorado 4 West 8 Mountain
#> 7 09 CT Connecticut 1 Northeast 1 New England
#> 8 10 DE Delaware 3 South 5 South Atlantic
#> 9 11 DC District o… 3 South 5 South Atlantic
#> 10 12 FL Florida 3 South 5 South Atlantic
#> # … with 41 more rows
fips::bea_region
#> # A tibble: 51 x 7
#> fips usps state short_region_na… region_code region_name region_abbr
#> <chr> <chr> <chr> <chr> <int> <chr> <chr>
#> 1 09 CT Connec… New England 1 New Englan… NENG
#> 2 23 ME Maine New England 1 New Englan… NENG
#> 3 25 MA Massac… New England 1 New Englan… NENG
#> 4 33 NH New Ha… New England 1 New Englan… NENG
#> 5 44 RI Rhode … New England 1 New Englan… NENG
#> 6 50 VT Vermont New England 1 New Englan… NENG
#> 7 10 DE Delawa… Mideast 2 Mideast Re… MEST
#> 8 11 DC Distri… Mideast 2 Mideast Re… MEST
#> 9 24 MD Maryla… Mideast 2 Mideast Re… MEST
#> 10 34 NJ New Je… Mideast 2 Mideast Re… MEST
#> # … with 41 more rows
fips::nchs_urc
#> # A tibble: 3,147 x 10
#> usps statefip fips county code2013 code2006 code1990 cbsatitle cbsapop
#> <chr> <chr> <chr> <chr> <dbl+lb> <dbl+lb> <dbl+lb> <chr> <dbl>
#> 1 AL 01 01001 Autau… 3 3 3 Montgome… 377149
#> 2 AL 01 01003 Baldw… 4 5 3 Daphne-F… 190790
#> 3 AL 01 01005 Barbo… 6 5 5 "" NA
#> 4 AL 01 01007 Bibb … 2 2 6 Birmingh… 1136650
#> 5 AL 01 01009 Bloun… 2 2 3 Birmingh… 1136650
#> 6 AL 01 01011 Bullo… 6 6 6 "" NA
#> 7 AL 01 01013 Butle… 6 6 6 "" NA
#> 8 AL 01 01015 Calho… 4 4 4 Anniston… 117296
#> 9 AL 01 01017 Chamb… 5 5 6 Valley, … 34064
#> 10 AL 01 01019 Chero… 6 6 6 "" NA
#> # … with 3,137 more rows, and 1 more variable: ctypop <dbl>
The {fips} package are available under the Creative Commons CC0 1.0 License, so feel free (literally) to use it for any purpose without any attribution.