Core based statistical area

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The United States Office of Management and Budget (OMB) delineates metropolitan and micropolitan statistical areas according to published standards that are applied to Census Bureau data. The general concept of a metropolitan or micropolitan statistical area is that of a core area containing a substantial population nucleus, together with adjacent communities having a high degree of economic and social integration with that core.

Definitions

The term “core based statistical area” (CBSA) became effective in 2000 and refers collectively to metropolitan and micropolitan statistical areas. The 2010 standards provide that each CBSA must contain at least one urban area of 10,000 or more population. Each metropolitan statistical area must have at least one urbanized area of 50,000 or more inhabitants. Each micropolitan statistical area must have at least one urban cluster of at least 10,000 but less than 50,000 population. Combined statistical areas (CSAs) are aggregates of adjacent metropolitan or micropolitan statistical areas that are linked by commuting ties.

Counties or equivalent entities form the geographic “building blocks” for metropolitan and micropolitan statistical areas throughout the United States and Puerto Rico. Under the standards, the county (or counties) in which at least 50 percent of the population resides within urban areas of 10,000 or more population, or that contain at least 5,000 people residing within a single urban area of 10,000 or more population, is identified as a “central county” (counties). Additional “outlying counties” are included in the CBSA if they meet specified requirements of commuting to or from the central counties.

If specified criteria are met, a metropolitan statistical area containing a single core with a population of 2.5 million or more may be subdivided to form smaller groupings of counties referred to as “metropolitan divisions.”

The largest city in each metropolitan or micropolitan statistical area is designated a “principal city.”

In view of the importance of cities and town in New England, the 2010 standards also provide for a set of geographic areas that are delineated using cities and towns in the six New England states. The New England city and town areas (NECTAs) are delineated using the same criteria as metropolitan and micropolitan statistical areas. Similarly to CBSAs, there are metropolitan and micropolitan NECTAs, combined NECTAs, and NECTA divisions.

Delineation revisions

A metropolitan or micropolitan statistical area’s geographic composition, or list of geographic components at a particular point in time, is referred to as its “delineation.” Metropolitan and micropolitan statistical areas are delineated by the U.S. Office of Management and Budget (OMB) and are the result of the application of published standards to Census Bureau data. The standards for delineating the areas are reviewed and revised once every ten years, prior to each decennial census. Generally, the areas are delineated using the most recent set of standards following each decennial census. Between censuses, the delineations are revised to reflect Census Bureau population estimates and–once each decade–updated commuting-to-work data. Areas based on the 2010 standards and Census Bureau data were delineated in February of 2013, and updated in July of 2015, August of 2017, April of 2018, September of 2018, and March of 2020.

Changes in the delineations of these statistical areas since the 1950 census have consisted chiefly of: - the recognition of new areas as they reached the minimum required urban area or city population, and - the addition of counties (or cities and towns in New England) to existing areas as new commuting and urban area data showed them to qualify.

In some instances, formerly separate areas have been merged, components of an area have been transferred from one area to another, or components have been dropped from an area. The large majority of changes have taken place on the basis of decennial census (and more recently American Community Survey) data. However, Census Bureau Population Estimates Program and American Community Survey data serve as the basis for intercensal updates in specified circumstances.

Revision Census
Mar 2020 2010
Sep 2018 2010
Apr 2018 2010
Aug 2017 2010
Jul 2015 2010
Feb 2013 2010
Dec 2009 2000
Nov 2008 2000
Nov 2007 2000
Dec 2006 2000
Dec 2005 2000
Nov 2004 2000
Dec 2003 2000
Jun 2003 2000
Jun 1999 2000*
Jun 1993 1990**
Jun 1990 1990*
Jun 1983 1980**
Jun 1981 1980*
Apr 1973 1980**
Feb 1971 1970*
Oct 1963 1960**
Nov 1960 1960*
Oct 1950 1950*

* Delineations used for presenting metropolitan area statistics in upcoming Census publications.
** Delineations based on application of metropolitan area standards to preceding census data.

Delineation tables

Function get_cbsa_delin_df(year) returns delineation dataframe for a chosen year.

Examples

From 2020 CBSA delineation.

Combined statistical area (CSA) “Madison-Janesville-Beloit, WI” consists of three core based statistical areas (CBSAs): two metropolitan statistical areas (“Madison, WI” and “Janesville-Beloit, WI”) and one micropolitan statistical area (“Baraboo, WI”). No divisions exist within CBSAs, because neither CBSA has core of greater than 2.5 million people. “Madison, WI” metro area consists of the central Dane county and three adjacent outlying counties - Columbia, Green and Iowa.

Code
df = get_cbsa_delin_df(2020)
df.query('CSA_CODE == "357"')\
[['CSA_TITLE', 'CSA_CODE', 'CBSA_TITLE', 'CBSA_CODE', 'METRO_MICRO', 'STATE', 'COUNTY', 'STATE_CODE', 'COUNTY_CODE', 'CENTRAL_OUTLYING']]
CSA_TITLE CSA_CODE CBSA_TITLE CBSA_CODE METRO_MICRO STATE COUNTY STATE_CODE COUNTY_CODE CENTRAL_OUTLYING
151 Madison-Janesville-Beloit, WI 357 Baraboo, WI 12660 micro Wisconsin Sauk County 55 111 central
837 Madison-Janesville-Beloit, WI 357 Janesville-Beloit, WI 27500 metro Wisconsin Rock County 55 105 central
1028 Madison-Janesville-Beloit, WI 357 Madison, WI 31540 metro Wisconsin Columbia County 55 021 outlying
1029 Madison-Janesville-Beloit, WI 357 Madison, WI 31540 metro Wisconsin Dane County 55 025 central
1030 Madison-Janesville-Beloit, WI 357 Madison, WI 31540 metro Wisconsin Green County 55 045 outlying
1031 Madison-Janesville-Beloit, WI 357 Madison, WI 31540 metro Wisconsin Iowa County 55 049 outlying

All CBSAs that have divisions.

Code
df = get_cbsa_delin_df(2020)
d = df.query('DIVISION_CODE.notna()')[['CBSA_TITLE', 'CBSA_CODE', 'DIVISION_CODE']]
pd.concat([
    d.groupby(['CBSA_TITLE', 'CBSA_CODE']).size(),
    d.drop_duplicates().groupby(['CBSA_TITLE', 'CBSA_CODE']).size()
], axis=1).reset_index().rename(columns={0: 'counties', 1: 'divisions'})
CBSA_TITLE CBSA_CODE counties divisions
0 Boston-Cambridge-Newton, MA-NH 14460 7 3
1 Chicago-Naperville-Elgin, IL-IN-WI 16980 14 4
2 Dallas-Fort Worth-Arlington, TX 19100 11 2
3 Detroit-Warren-Dearborn, MI 19820 6 2
4 Los Angeles-Long Beach-Anaheim, CA 31080 2 2
5 Miami-Fort Lauderdale-Pompano Beach, FL 33100 3 3
6 New York-Newark-Jersey City, NY-NJ-PA 35620 23 4
7 Philadelphia-Camden-Wilmington, PA-NJ-DE-MD 37980 11 4
8 San Francisco-Oakland-Berkeley, CA 41860 5 3
9 Seattle-Tacoma-Bellevue, WA 42660 3 2
10 Washington-Arlington-Alexandria, DC-VA-MD-WV 47900 25 2

Geographic shapefiles

Boundary shapefiles, both TIGER (high res) and catrographic (low res) are available from Census Bureau geography program.

Function get_cbsa_shape_df() returns a geodataframe of a given year and scale.

Example dataframe head.

Code
get_cbsa_shape_df(year=2021, scale='20m', geometry=True).head(3)
CBSA_CODE CBSA_TITLE METRO_MICRO ALAND AWATER geometry
0 28500 Kerrville, TX micro 2857617603 10231764 POLYGON ((-99.75414 30.29070, -99.30172 30.286...
1 27540 Jasper, IN micro 1972458000 38481506 POLYGON ((-87.46288 38.53273, -87.35183 38.542...
2 29620 Lansing-East Lansing, MI metro 5772069690 70045237 POLYGON ((-85.07425 42.77078, -84.83709 42.770...
Code
df = get_cbsa_shape_df(year=2021, scale='20m', geometry=True)
df.query('CBSA_TITLE.str.contains("WI")').explore()
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CBSAs of Wisconsin, 2021.

New England

New England city and town areas (NECTAs) are an alternative delineation available for the six states of New England that uses county subdivisions as building blocks. Consequently, NECTA boundaries can cross county boundaries, as shown in the map below.

Code
import folium
m = dc.explore(name='county', color='red')
ds.explore(m=m, name='subdivision', color='blue')
dn.explore(m=m, name='NECTA', color='green')
folium.LayerControl(collapsed=False).add_to(m)
m
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