Homelessness Risk Tutorial

Data related to homelessness from an ArcGIS tutorial

arcgis.com-risk-3

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

Resources

• resources. Homeless population, crime, and 311 calls by tract and community.
• county_outline. County bountry outline
• shelters_services. Locations and basic information for shelters and other services
• homeless_population. Detailed homeless population data per tract.
• risk_factors. Tract level neighborhood risk factors, probably from teh American Community Survey

Documentation

ESRI publishes a tutorial for creating maps for analyzing homelesness, with a link to the data used. Many of the data are from lahsa.org and economicrt.org, but the package also includes many other columns. The data download includes a .gdb file, which includes no documentation, although there may be documentation in the HomelessnessPkg.ppkx file.

For this data package, the files from the .gdb database have been converted to GeoJSON, to be imported into the package.

The files are interesting, but poorly documented and of unknown provenance, so probably should only be used for tutorials and demonstrations. Some information about the dataset can be inferred from an ESRI Homelessness Story Map, which appears to use these datasets.

Documentation Links

• TutorialTutorial web page
• Combating Homelessness in Los Angeles CountyHomelessness story map

Contacts

• Wrangler

  Eric Busboom, Civic Knowledge

Packages

• zip http://library.metatab.org/arcgis.com-risk-3.zip
• csv http://library.metatab.org/arcgis.com-risk-3.csv
• source https://github.com/SDRDLAnalysts/data-projects.git

Accessing Packages in Metapack

import metapack as mp
pkg = mp.open_package('http://library.metatab.org/arcgis.com-risk-3.zip')

# Create Dataframes
resources_gdf = pkg.resource('resources').geoframe()
county_outline_gdf = pkg.resource('county_outline').geoframe()
shelters_services_gdf = pkg.resource('shelters_services').geoframe()
homeless_population_gdf = pkg.resource('homeless_population').geoframe()
risk_factors_gdf = pkg.resource('risk_factors').geoframe()

Data Dictionary

resources | county_outline | shelters_services | homeless_population | risk_factors

resources

Column Name	Data Type	Description
id	integer
objectid	integer
tract	integer
uniqid	integer
totpop_cy	integer
totunsheltpeople	number
totsheltpeople	integer
totpeople	number
community	text
victimcount	integer
callcnt311	integer
chronic	integer
shape_length	number
shape_area	number
geometry	string

county_outline

Column Name	Data Type	Description
id	integer
objectid	integer
shape_length	number
shape_area	number
geometry	string

shelters_services

Column Name	Data Type	Description
id	integer
objectid	integer
source	integer
cat1	string
cat2	string
org_name	string
name	string
addrln1	string
addrln2	string
city	string
state	string
hours	string
phones	string
url	string
post_id	integer
description	text
zip	integer
link	string
use_type	string
latitude	number
longitude	number
date_updated	datetime
point_x	number
point_y	number
geometry	string

homeless_population

Column Name	Data Type	Description
id	integer
objectid	integer
tract	integer
uniqid	integer
totpop_cy	integer
totunsheltpeople	integer
totsheltpeople	integer
totpeople	integer
poly_area	number
popdensity	number
homelesspopdensity	number
unsheltereddensity	number
sheltereddensity	number
community	text
indfamcvc	integer
pindfamcvc	number
indfamte	integer
pindfamte	number
onstreet	integer
ponstreet	number
indfamesthsh	integer
pindfamesthsh	number
vets	integer
chronic	integer
addicted	number
braininjury	number
smi	number
hivaids	number
devdis	number
phydis	number
domviol	number
under18	number
over62	number
amerind	number
asian	number
black	number
hispanic	number
pacislalaskan	number
white	number
male	number
female	number
transgender	number
shape_length	number
shape_area	number
geometry	string

risk_factors

Column Name	Data Type	Description
id	integer
objectid	integer
tract	integer
uniqid	integer
acshhbpov	integer
pacshhbpov	number
changehhinpoverty	integer
acspubai	integer
ppublicassistanceinc	number
changehhpubassist	integer
acshhdis	integer
pdisabilities	number
acsgrnti50	integer
p50hhinc4rent	number
changehhs50pinc4rent	integer
unemp_cy	integer
unemprt_cy	number
changeunemprate	number
nohealthins	integer
pnohealthins	number
est_veteran_ptsd	number
ptsdvets	integer
estsmi	integer
pestsmi	number
subabuse	integer
psubabuse	number
domviol	integer
pdomviolrate	number
totpop_cy	integer
shape_length	number
shape_area	number
geometry	string

References

Urls used in the creation of this data package.

• Data package. Data package included in the tutorial.

Last Modified 2019-07-17T00:49:01

Packages

• zip http://library.metatab.org/arcgis.com-risk-3.zip
• csv http://library.metatab.org/arcgis.com-risk-3.csv
• source https://github.com/SDRDLAnalysts/data-projects.git

Accessing Packages in Metapack

import metapack as mp
pkg = mp.open_package('http://library.metatab.org/arcgis.com-risk-3.zip')

# Create Dataframes
resources_gdf = pkg.resource('resources').geoframe()
county_outline_gdf = pkg.resource('county_outline').geoframe()
shelters_services_gdf = pkg.resource('shelters_services').geoframe()
homeless_population_gdf = pkg.resource('homeless_population').geoframe()
risk_factors_gdf = pkg.resource('risk_factors').geoframe()