San Diego county Tracts, MSAs and SRAs, based on 2010 Census boundaries, as extracted by SANGIS.
OrderedDict([('dataset', 'census-regions'), ('time', '2010'), ('version', '4'), ('space', 'sandiego'), ('origin', 'sangis.org'), ('@value', 'sangis.org-census_regions-2010-sandiego-4')])
Resources | Packages | Documentation| Contacts
Resources
- tracts. 2010 Census Tract boundaries
- msa. 2010 Metro Statistical Area boundaries
- sra. San Diego County Sub-Regional Areas boundaries
- zip. ZIP Code boundaries
- tract-sra-msa-xwalk. Crosswalk between crosswalks, tracts, zip codes and SRAs.
Documentation
Documentation Links
- docs/tracts-sras-and-msaaOverview of how SRAs are composed of tracts and related to MSAs.
Contacts
- Origin
- Wrangler
Packages
- xlsx http://s3.amazonaws.com/library.metatab.org/sangis.org-census_regions-2010-sandiego-4.xlsx
- zip http://s3.amazonaws.com/library.metatab.org/sangis.org-census_regions-2010-sandiego-4.zip
- csv http://s3.amazonaws.com/library.metatab.org/sangis.org-census_regions-2010-sandiego-4.csv
Accessing Packages in Metapack
import metapack as mp
# ZIP Package
pkg = mp.open_package('http://s3.amazonaws.com/library.metatab.org/sangis.org-census_regions-2010-sandiego-4.zip')
# CSV Package
pkg = mp.open_package('http://s3.amazonaws.com/library.metatab.org/sangis.org-census_regions-2010-sandiego-4.csv')
resource = pkg.resource('resource_name') # Get a resource
df = resource.dataframe() # Create a pandas Dataframe
gdf = resource.geoframe() # Create a GeoPandas GeoDataFrame
Last Modified 2017-04-03T20:16:31