PUMA Maps and Geographic Equivalencies
The Census Bureau publishes PUMA reference material at
https://www.census.gov/geo/reference/puma.html. Included on this page is a link
to a set of individual PUMA maps organized by state. These can be useful when you one to zero in on a single PUMA or set of PUMAs.
But normally we prefer a map product that can show us an entire state's worth of PUMA's or a metro region overview. For that type of map
see our reference below to the Proximity One PUMA maps products.
PUMA codes (both the old - 2000 vintage - and the new (2010 vintage, aka "2012" PUMAs - our alias) are included in the Missouri Census Data Center's MABLE database, which means they can be used within the MABLE/Geocorr14 web application. See more detailed discussion, below.
Using MABLE/Geocorr we generated a 2000-PUMA to 2012-PUMA equivalency file in both csv (comma-separated) and SAS data set formats. The csv file is
puma2k_puma2010.csv in our corrlst ("correlation lists") data directory. We used the 2010 pop as the weight variable so this file tries to measure the overlaps as of 4-1-10. The variable afact indicates the
portion of the 2000 PUMA;s 2010 pop living in the 2010 PUMA; the variable afact2 goes the other way, showing what portion of the 2010 PUMA's pop
also resides (resided) in the 2000 PUMA. The SAS data set version is accessible using our Dexter utility
(access corrlst.puma2k_puma2010 which lets you easily create state-based subsets). To help you see what these data look like we generated a nicely formatted
listing of the Missouri subset of this data set.
The folks at IPUMS have created an interactive map showing the 2000 and 2010 boundaries overlaid.
Using Maps to See Which PUMAs Are Where
By far the best resource we have found for letting you actually see where the PUMAs are located within a state is at this
ProximityOne puma2010 web page. In addition to some excellent general background info and
access to the latest 1-year (2012 currently) ACS data profiles at the 2010 PUMA level, you can find a box on the right labeled PUMA Map Views by State. Scroll down (if necessary) and find your state and click on it. You'll get an excellent overview map of the state, clearly displaying the PUMA boundaries on a based map that shows county boundaries and major towns. Urban areas get their own separate inset maps. It's a .com site but access to these maps is free. (Each click on this site opens a new window or tab so you might want to start in a new browser window).
PUMA Master Dataset and Web Application
We have created a special puma_master dataset in our public data archive. Each observation (record/row) in the dataset describes a single
2010 PUMA. It provides information regarding the PUMA's location by indicating intersections with other more familiar geographies. For example, what
county/counties, place(s), metro area, Congressional District(s), etc. it intersects with. It is like somebody ran a bunch of MABLE/Geocorr runs (see below for a description of the geocorr application) and merged them altogether in this single resource. The dataset also contains a set of
key indicator variables from a recent set of ACS summary data.
Using MABLE/Geocorr to Relate PUMAs to Other Geographic Codes
If you not familiar with this geographic utility application we suggest you start by looking at the explanation and example from the MCDC Quick Tour page . There is also a powerpoint tutorial that should help you get started. (It describes the "2k" edition of the application, which is not the one you'll need for the 2010 PUMAs, but the application works the same, just different geographic choices.)
What the geocorr apps do is create reports (and/or comma-delimited files) showing how different geographic layers correspond to one another. A good example relevant to the current topic involves using the application to generate a report showing how PUMAs relate to counties in the state of Colorado. To do this, invoke the application (at ) and fill out the form as follows:
- Choose Colorado as the state to process.
- From the "Select 1 or more "SOURCE" Geocode(s)" select list choose PUMA ("2012") .
- From the "Select 1 or more "TARGET" Geocode(s)" select list choose County .
- Skip down a short ways to the Output Options section, and check the box labeled "Generate 2nd allocation factor (AFACT2): portion of target geocodes in source geocodes". This means that our report will not only show us what portion of the PUMA population resided in the county in 2000, but also what portion of the county population resided within the PUMA.
- Accept defaults (ignore) the rest of the options. Find the first "Run Request" button you can and click it to invoke the geocorr program.
It should take less than 2 seconds to process this request. In your browser a page will be generated summarizing the results and providing hyperlinks to the 2 Output Files. If you click on the Listing (report format) link you should see a report, the first few lines of which should look like this:
(We removed the 2 state FIPS/state abbreviation columns at left to make it easier to read here).
These are just the lines of the report dealing with the first five values of the "source" geocode, which is called puma12 in the MABLE database being used by geocorr. Each line of the report represents the intersection of the PUMA area with a "target" geocode -- a county. The first line of the report tells us that the intersection of PUMA 00100 (Northeast Colorado...) with Bent county had 6499 persons living in it according to the 2010 census. The first "alloc factor" column has a value of 0.059, which is telling is what portion of the PUMA's total population is represented by this intersection. So just under 6% of this PUMA's population is in Bent county. The last column, titled "county to puma12 alloc factor" is the allocation factor going the other way, the one we only get because we checked that special option ("Generate 2nd allocation factor (AFACT2)") on the input form. The value of 1.000 tells us that the entire county of Bent is (was) contained in this PUMA. In fact, as you scan the 7 lines of the report you see there are a dozen counties listed that have a value of 1.000 in this column, indicating that they fall entirely within the PUMA. Two other counties (Elbert and Weld) are just partially contained in the PUMA.
2010 PUMA to County Equivalency File for Colorado
Total Pop, puma12 to county to
2010 county alloc puma12 alloc
puma12 PUMA12 Name county cntyname census factor factor
00100 Northeast Colorado--Eastern Plains Region 08011 Bent CO 6499 0.059 1.000
08017 Cheyenne CO 1836 0.017 1.000
08025 Crowley CO 5823 0.053 1.000
08039 Elbert CO 3717 0.034 0.161
08061 Kiowa CO 1398 0.013 1.000
08063 Kit Carson CO 8270 0.075 1.000
08073 Lincoln CO 5467 0.050 1.000
08075 Logan CO 22709 0.206 1.000
08087 Morgan CO 28159 0.255 1.000
08095 Phillips CO 4442 0.040 1.000
08115 Sedgwick CO 2379 0.022 1.000
08121 Washington CO 4814 0.044 1.000
08123 Weld CO 4843 0.044 0.019
08125 Yuma CO 10043 0.091 1.000
00102 Larimer County (South)--Loveland City 08069 Larimer CO 115164 1.000 0.384
00103 Larimer County (North)--Fort Collins City 08069 Larimer CO 184466 1.000 0.616
00200 Northwest Colorado--Garfield, Routt, Moffat & Rio Blanco Counties 08045 Garfield CO 56389 0.562 1.000
08081 Moffat CO 13795 0.137 1.000
08103 Rio Blanco CO 6666 0.066 1.000
08107 Routt CO 23509 0.234 1.000
00300 Weld County (South Central)--Greeley, Windsor & Evans Cities 08123 Weld CO 172967 1.000 0.684
00400 Eagle, Summit, Grand & Jackson Counties 08037 Eagle CO 52197 0.460 1.000
08049 Grand CO 14843 0.131 1.000
08057 Jackson CO 1394 0.012 1.000
08097 Pitkin CO 17148 0.151 1.000
08117 Summit CO 27994 0.246 1.000
This example shows us how to relate the PUMA areas to counties. We can just as easily (by changing our selection in the Target Geocodes select list) get comparable reports for other geographic levels such as places (cities), congressional districts, CBSA's (metropolitan and micropolitan statistical areas), Urbanized Areas/Urban Clusters, etc. You can also select "PUMA (2000)" as the target to get the relationship between the new 2010/2012 PUMAs to the old 2000 PUMAs. Note that there are no names associated with the 2000 PUMAs, except in Missouri.
Summary Data at the PUMA Level
The Census Bureau did not publish any summary data for these units based on the 2010 census. You will not be able to find a PUMA summary level on sf1 or using the American FactFinder web site. However, it would be possible to aggregate data at the census tract level to create such summaries. You could use geocorr to generate the required tract-to-PUMA equivalency file.
Data from the American Community Survey are available at the PUMA level. Data published for vintage years 2011 and earlier use the old 2000 PUMAs as the units. Starting with vintage 2012 they will be by the new 2010/2012 PUMAs. Such data can be accessed via American FactFinder or from the MCDC web site. Both our ACS Profiles and ACS Profile extract app (accessible via our Quick Links box) can be used to access PUMA-level data.
PUMA data can also be extracted using Uexplore/Dexter from our various acs2006 thru acs2012 data directories. The usmcdcprofiles and usmcdcprofiles3yr data sets contain summaries at the PUMA level; just filter using the SumLev = 795 filter spec.
Detailed tables in our basetbls and btabs5yr subdirectories of the more recent acs subdirectories also contain data at the PUMA level.