HUD Point in Time Counts by CoC

Combined years of sheltered and unsheltered homeless counts, by CoC.

hudexchange.info-pit-coc-1

Documentation

HUD publishes an Excel workbook with sheltered and unsheltered counts, aggregated to CoC, for the whole country, for 2007 on. In this dataset, each year is in a seperate worksheet, and later years have more columns than earlier years, and most column names include the year as a suffix.

This data package combines al of these years into a single file, with normalized column names. Cells in years that don’t have a column that are in later years are filled with nulls, and each row is prefixed with the year of the file that the original row was sourced from.

For a graphic view of which columns are missing, by year ( actually by position in the dataset ) see the null map at the end of the EDA notebook.

Revisions to the Historic Point-in-Time Estimates

The data source file includes this note:

On rare occasions, the Point-in-Time estimates published in prior editions of the AHAR have been subsequently updated. The estimates described in this file represent the latest versions of these data (as of the publication of this file). The revisions are summarized below:

1. Beginning in the 2014 AHAR Part 1, the PIT estimates of unsheltered people experiencing homelessness in the Los Angeles City and County CoC, CA-600, were updated for the years 2007–2013. Within the CoC, the adjustments subtracted: 20,746 total people from 2007 and 2008; 9,451 total people in 2009 and 2010; 10,800 total people in 2011 and 2012; and 18,274 total people from 2013. These adjustments also caused drops in the key unsheltered populations reported on the AHAR, individuals, people in families, veterans, and chronically homeless individuals. More details on the size of each adjustment, by population, can be found in the 2014 AHAR Part 1.

2. Beginning in the 2014 AHAR Part 1, the PIT estimate of veterans experiencing homelessness in shelter projects in the Phoenix/Mesa/Maricopa County Regional CoC, AZ-502, was updated for the year 2013, increasing by 214 veterans. This update did not change the total number of people experiencing homelessness in shelter projects (or overall) in the CoC—just the number of those people who were classified as veterans.

3. Beginning in the 2015 AHAR Part 1, the PIT estimates of unsheltered people experiencing homelessness in the Las Vegas/Clark County CoC, NV-500, were updated for the years 2007–2014. Within the CoC, the adjustments subtracted: 3,884 total people from 2007 and 2008; 3,389 total people in 2009 and 2010; 1,429 total people in 2011 and 2012; 1,404 total people from 2013; and 1,974 total people from 2014. These adjustments also caused drops in the key unsheltered populations reported on the AHAR, individuals, people in families, veterans, and chronically homeless individuals. More details on the size of each adjustment, by population, can be found in the 2015 AHAR Part 1.

4. Beginning in the 2015 AHAR Part 1, the PIT estimates of veterans experiencing homelessness in the Anchorage CoC, AK-500, were updated for the year 2014. The sheltered estimate for this CoC increased by 71 veterans, and the unsheltered estimate increased by 18 veterans. Neither of these updates changed the total number of people experiencing homelessness in the CoC—just the number of those people who were classified as veterans.

5. Beginning in the 2017 AHAR Part 2 and the 2018 AHAR Part 1, the PIT estimates of unsheltered people experiencing homelessness in the Los Angeles City and County CoC, CA-600, were updated for the year 2017, decreasing by a total of 2,746 people. The adjustment also caused drops in the key unsheltered populations reported on the AHAR, individuals, people in families, veterans, and chronically homeless individuals. More details on the size of each adjustment, by population, can be found in the 2017 AHAR Part 2 and the 2018 AHAR Part 1.

Packages

Accessing Packages in Metapack

import metapack as mp
pkg = mp.open_package('http://library.metatab.org/hudexchange.info-pit-coc-1.zip')

# Create Dataframes

pitc_coc_df = pkg.resource('pitc_coc').dataframe()

Data Dictionary

pitc_coc

pitc_coc

Column NameData TypeDescription
yearinteger
coc_numberstring
coc_nametext
coc_categorystring
chronically_homelessinteger
chronically_homeless_individualsinteger
chronically_homeless_people_in_familiesinteger
homeless_children_of_parenting_youthinteger
homeless_family_householdsinteger
homeless_individualsinteger
homeless_parenting_youth_age_18_24integer
homeless_parenting_youth_under_18integer
homeless_parenting_youth_under_25integer
homeless_people_in_familiesinteger
homeless_unaccompanied_youth_age_18_24integer
homeless_unaccompanied_youth_under_18integer
homeless_unaccompanied_youth_under_25integer
homeless_veteransinteger
overall_homelessinteger
sheltered_es_chronically_homelessinteger
sheltered_es_chronically_homeless_individualsinteger
sheltered_es_chronically_homeless_people_in_familiesinteger
sheltered_es_homelessinteger
sheltered_es_homeless_children_of_parenting_youthinteger
sheltered_es_homeless_family_householdsinteger
sheltered_es_homeless_individualsinteger
sheltered_es_homeless_parenting_youth_age_18_24integer
sheltered_es_homeless_parenting_youth_under_18integer
sheltered_es_homeless_parenting_youth_under_25integer
sheltered_es_homeless_people_in_familiesinteger
sheltered_es_homeless_unaccompanied_youth_age_18_24integer
sheltered_es_homeless_unaccompanied_youth_under_18integer
sheltered_es_homeless_unaccompanied_youth_under_25integer
sheltered_es_homeless_veteransinteger
sheltered_sh_chronically_homelessinteger
sheltered_sh_chronically_homeless_individualsinteger
sheltered_sh_homelessinteger
sheltered_sh_homeless_individualsinteger
sheltered_sh_homeless_unaccompanied_youth_age_18_24integer
sheltered_sh_homeless_unaccompanied_youth_under_18integer
sheltered_sh_homeless_unaccompanied_youth_under_25integer
sheltered_sh_homeless_veteransinteger
sheltered_th_homelessinteger
sheltered_th_homeless_children_of_parenting_youthinteger
sheltered_th_homeless_family_householdsinteger
sheltered_th_homeless_individualsinteger
sheltered_th_homeless_parenting_youth_age_18_24integer
sheltered_th_homeless_parenting_youth_under_18integer
sheltered_th_homeless_parenting_youth_under_25integer
sheltered_th_homeless_people_in_familiesinteger
sheltered_th_homeless_unaccompanied_youth_age_18_24integer
sheltered_th_homeless_unaccompanied_youth_under_18integer
sheltered_th_homeless_unaccompanied_youth_under_25integer
sheltered_th_homeless_veteransinteger
sheltered_total_chronically_homelessinteger
sheltered_total_chronically_homeless_individualsinteger
sheltered_total_chronically_homeless_people_in_familiesinteger
sheltered_total_homelessinteger
sheltered_total_homeless_children_of_parenting_youthinteger
sheltered_total_homeless_family_householdsinteger
sheltered_total_homeless_individualsinteger
sheltered_total_homeless_parenting_youth_age_18_24integer
sheltered_total_homeless_parenting_youth_under_18integer
sheltered_total_homeless_parenting_youth_under_25integer
sheltered_total_homeless_people_in_familiesinteger
sheltered_total_homeless_unaccompanied_youth_age_18_24integer
sheltered_total_homeless_unaccompanied_youth_under_18integer
sheltered_total_homeless_unaccompanied_youth_under_25integer
sheltered_total_homeless_veteransinteger
unsheltered_chronically_homelessinteger
unsheltered_chronically_homeless_individualsinteger
unsheltered_chronically_homeless_people_in_familiesinteger
unsheltered_homelessinteger
unsheltered_homeless_children_of_parenting_youthinteger
unsheltered_homeless_family_householdsinteger
unsheltered_homeless_individualsinteger
unsheltered_homeless_parenting_youth_age_18_24integer
unsheltered_homeless_parenting_youth_under_18integer
unsheltered_homeless_parenting_youth_under_25integer
unsheltered_homeless_people_in_familiesinteger
unsheltered_homeless_unaccompanied_youth_age_18_24integer
unsheltered_homeless_unaccompanied_youth_under_18integer
unsheltered_homeless_unaccompanied_youth_under_25integer
unsheltered_homeless_veteransinteger

References

Urls used in the creation of this data package.

import metapack as mp
pitc_coc_df = pkg.resource('pitc_coc').dataframe()