sandiegodata.org-planning-tracts-6 Last Update: 2018-10-15T20:23:35
A collection of data for demographics and housing from the Census planning database. Files are broken into counties, for San Diego and Los Angeles
The Planing Database is a Census product that combines a range of data from the American Community Survey and 2010 Decenial Census into a single file, with one row per census tract. This version of the file includes only tracts in San Diego County. The file is linked to ACS format geoids to identify tracts, so it can be easily linked to other tracts data. This data package includes links to two such files, one for San Diego communities, and one for tract geographics.
The planning database has about 450 columns. For full definitions of the columns, refer to the upstream documentation for the source file. In general, the column names in the documentation must be lowercased for use with the file in this data package.
In Python, use metapack to open the data package.
import metapack as mp
pkg = mp.open_package('http://library.metatab.org/sandiegodata.org-planning-tracts-1.zip')
To display a simple map, link in the tract boundaries from the communities
dataset and use the Geopandas .plot() function. The column argument names
the column to use for coloring regions. Note that the column name is copied
from the documentation with mixed case, then lowercased to index the dataset.
tracts = pkg.reference('communities').geoframe().set_index('geoid').fillna('')
df = tracts.join(cpdb)
fig, ax = plt.subplots(1, figsize=(15,10))
df.plot(ax=ax, column='pct_MLT_U10p_ACS_12_16'.lower())
After linking in the communities, you can also use the community id columns to group by city or community:
seniors = dfg.df.groupby('city_name').pop_65plus_acs_12_16.sum()