Census Geography: Maps & Apps Joe Germuska NewsApps Developer Chicago Tribune 0:00.

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Presentation transcript:

Census Geography: Maps & Apps Joe Germuska NewsApps Developer Chicago Tribune 0:00

Census Geographies 1:30

SUMLEV 3:03

Key Summary Levels Block (~ 8M): basis for all tabulated data Block Group (~211K): smallest geography for which sample data is published Tract (~74K): relatively permanent; people (optimum: 4000) County (3,143) State (52) Division (9) Region (4) Nation (1) (and then there are the “Island Areas”) 4:57

Other Groupings Place (7,438): Incorporated and Census Designated (CDP) County Subdivision (36,642) Core Based Statistical Areas (942) 7:20

Geographic Components about 100 different geographic components, with most focusing on urban/rural or metropolitan/non-metropolitan distinctions Nation Region Division State CBSA 9:00

TIGER Shapefiles 9:46

Shapefiles In addition to tabulation geographies: Roads Hydrography Landmarks Military Installations 10:40

Gazetteer Delimited text files provide IDs, names, area, centroid for: 111th Congressional Districts Census Tracts Counties County Subdivisions School Districts - Elementary, Secondary, Unified State Legislative Districts - Lower & Upper Places ZIP Code Tabulation Areas GeoID not always exact match for shapefile (prefix, etc) 11:10

Keep in Mind Geos can change between “vintages”: compare with caution. Consult “crosswalk” Know which geos are contained by larger geos and which can “overlap” Choose your summary level carefully 080 “Census Tract” ≠ 140 “Census Tract” Exercise extreme caution when aggregating to non-census geographies 11:50

Population Change Map 14:54

WNYC Map 15:28

Know Spokane 15:35

Options Chicago TribuneWNYC Spokesman- Review Tile Mill Google Fusion Tables GeoDjango + Google Maps 15:44

Tile Mill 16:17

Tile Mill Can be entirely hosted on any simple web server (Amazon S3) Tile generation can be slow, especially for close zoom levels Evolving rapidly, especially interactivity 18:14

Fusion Tables 19:33

Fusion Tables Can import KML for shapes, sometimes data More often, KML for shapes, then join with data Easy to embed 20:10

GeoDjango 21:02

GeoDjango Highly customizable Well-documented, healthy user community Hosting adds extra layer of complexity 21:37

22:32

23:45

24:00

24:04

24:15

census.ire.org Browse and compare Correctly computed changes since 2010 Export as CSV, JSON, KML JSON available for web apps 26:30

Example JSON data 27:12

You can join the fun CENSUS -L » CENSUS -L » :17

Questions? Links for this presentation: 32:07

Links Census Geographic Resources Example Apps change/index.html change/index.html How-tos: geo-stack-on-snow-leopard/ geo-stack-on-snow-leopard/ geodjango-application/ geodjango-application/ :17