Gaslamp Homeless Counts – SDRDL Data Repository

Monthly homeless counts for the Gaslamp district in Downtown San Diego

downtownsandiego.org-homeless_count-gaslamp-2

Resources | Packages | Documentation| Contacts| Data Dictionary

Resources

gaslamp.

Documentation

Since 2014, the Downtown San Diego Partnership has been conducting monthly counts of the homeless in the Downtown neighborhood. The positions of homeless sleepers are recorded on paper maps, which are compiled into a spreadsheet. The San Diego Regional Data Library is running a project to digitize these paper maps](https://downtown-homelesness.sandiegodata.org/) into geographic datasets.

This dataset covers only the Gaslamp district, from 2014-01-01 to 2018-06-28.

The data were digitized by students of Corri-Anne Burgess at Kearney Senior High as a year-end class project. The digitization procedure involved estimateing the positions of each point from a PDF scan of the each map, placing the digitized point on a map in a web form. Although the procedure is less accurate that traditional digitization points, spot checking suggests the additional digitization error is much less than the positional error of the original data collection and recording, and the result is suficient to place each point to a parcel.

Corrections

Corrections made during wranging include:

One point for map 42 was given the incorrect date of 2019-05-26, which was corrected to 2017005-26
The value “individual_sleeper” was shortened to ‘ind’
In the rain column, the value ‘na’ was replaced with blanks.

Contacts

Wrangler
Eric Busboom, Civic Knowledge

Packages

Accessing Packages in Metapack

import metapack as mp
# ZIP Package
pkg = mp.open_package('http://library.metatab.org/downtownsandiego.org-homeless_count-gaslamp-2.zip')
# CSV Package
pkg = mp.open_package('http://library.metatab.org/downtownsandiego.org-homeless_count-gaslamp-2.csv') 

resource = pkg.resource('resource_name') # Get a resource
df = resource.dataframe() # Create a pandas Dataframe
gdf = resource.geoframe() # Create a GeoPandas GeoDataFrame

Data Dictionary

gaslamp

Column Name	Data Type	Description
id	integer
date	date
neighborhood	string	Neighborhood name; always ‘gaslamp’
map_id	integer	Map number
type	string	Type of group: ‘ind’ for individuals, or ‘encampment’
count	integer	Number of homeless people in the count point
rain	string	Does the map record rain? ‘yes’, ‘no’ or blank if no record
temperature	string	Temperature in F, if recorded on the map
lon	number	Longitude of count point
lat	number	Latitude of count point

Last Modified 2019-09-30T22:07:44