San Diego Police Regions and Demographics

Boundary shapes for San Diego neighborhoods, beats and divisions, with ACS estimates for populations, by race.

sandiego.gov-police_regions-1.1.2. Modified 2020-11-29T03:13:27

Resources | Packages | Documentation| Contacts| References| Data Dictionary

Resources

Documentation

This package links shapefiles for San Diego police beats to Census tracts and merges in ACS estimates for population, by race, from the 2016 5 year ACS. When a police beat boundry crosses a tract, the tract population is allocated to beats by the proportion of the overlap by area. See the Jupyter notebook that performs the procedure for details.

For the race/ethicty statistics, Hispanic (‘hisp’) refers to Hispanics of any race, while all other races refer to non-Hispanics of that race.

Contacts

Data Dictionary

pd_beats | pd_divisions | pd_neighborhoods | beat_demographics

pd_beats

Column NameData TypeDescription
idinteger
objectidinteger
beatinteger
divinteger
servinteger
nametext
geometrytext

pd_divisions

Column NameData TypeDescription
idinteger
objectidinteger
div_numinteger
div_nametext
geometrytext

pd_neighborhoods

Column NameData TypeDescription
idinteger
objectidinteger
div_numinteger
div_nametext
geometrytext

beat_demographics

Column NameData TypeDescription
beatintegerBeat number
totalintegerTotal population of beat
whiteintegerWhite population of beat
blackintegerBlack population of beat
aianintegerAmerican Indian population of beat
asianintegerAsian population of beat
nhopiintegerHawaiian population of beat
hispintegerHispanic population of beat

References

Urls used in the creation of this data package.

  • metapack+http://library.metatab.org/sandiegodata.org-communities-2018-7.csv#tracts. Census tracts from 2016 5 year ACS, for San Diego county
  • census://2016/5/CA/140/B03002. Race, by tract, in San Diego county

Packages

Accessing Data in Vanilla Pandas

import pandas as pd


pd_beats_df =  pd.read_csv('http://library.metatab.org/sandiego.gov-police_regions-1.1.2/data/pd_beats.csv')
pd_divisions_df =  pd.read_csv('http://library.metatab.org/sandiego.gov-police_regions-1.1.2/data/pd_divisions.csv')
pd_neighborhoods_df =  pd.read_csv('http://library.metatab.org/sandiego.gov-police_regions-1.1.2/data/pd_neighborhoods.csv')
beat_demographics_df =  pd.read_csv('http://library.metatab.org/sandiego.gov-police_regions-1.1.2/data/beat_demographics.csv')

Accessing Package in Metapack

import metapack as mp
pkg = mp.open_package('http://library.metatab.org/sandiego.gov-police_regions-1.1.2.csv')

# Create Dataframes
pd_beats_gdf = pkg.resource('pd_beats').geoframe()
pd_divisions_gdf = pkg.resource('pd_divisions').geoframe()
pd_neighborhoods_gdf = pkg.resource('pd_neighborhoods').geoframe()
beat_demographics_df = pkg.resource('beat_demographics').dataframe()