The intersect-community-data from npr99

build conda package

Started slack channel on IN-CORE
https://in-core.slack.com/archives/C03MLKDV4ER

change main folder pyhui

pyhui stands for python housing unit inventory... need to change the name but have not decided on the future package name

options
pyicd - python intersect community data
pyincoda
pyintcomdat
pyintersectcd
pyntrsctcmntydt

pyixcommunitydata

Get "Used By" section on repo

requirements.txt

https://github.com/Kanaries/pygwalker/tree/main

https://docs.github.com/en/code-security/supply-chain-security/understanding-your-software-supply-chain/about-the-dependency-graph#supported-package-ecosystems

I noticed in pygwalker github page that they have a used by section. Also the package has a nice readme page.

It looks like a package that uses another package needs to have a requirments.txt file - then github can identify the package that depends on another package and will make a used by section on the repository.

Add job record file and establishment intersection

code in population inventory private github

explore sex by age - looks like missing values and clusters

Notice that histogram shows clustering of ages around every 10 years. Also looks like there is a gap between 80 and 85

Get "Used By

requirements.txt

https://github.com/Kanaries/pygwalker/tree/main

https://docs.github.com/en/code-security/supply-chain-security/understanding-your-software-supply-chain/about-the-dependency-graph#supported-package-ecosystems

I noticed in pygwalker github page that they have a used by section. Also the package has a nice readme page.

It looks like a package that uses another package needs to have a requirments.txt file - then github can identify the package that depends on another package and will make a used by section on the repository.

why are there 2 data-axel folders?

see if the 2 folders can be combined

Work on entity relationship figure

I have started a entity relationship figure in LUCID chart here is the link:
https://lucid.app/lucidchart/aaa0a9d7-087e-4a23-8e75-67feb6efb684/edit?viewport_loc=19%2C179%2C3762%2C1893%2C0_0&invitationId=inv_9dc49768-f696-4dcd-990f-a92a5d52a56b

workflow for prechui

getting ready to publish example files for the person record files, with student and staff examples.
prechui_v0-2-0_37155_2010_rs9876.csv
prec_v0-2-0_Lumberton_NC_2010_rs9876_schoolstaff.csv
prec_v0-2-0_Lumberton_NC_2010_rs9876_students.csv

I need to work on getting this workflow up-to-date on github. Right now it is not clear who these files could be replicated.
The code was from 2022-03-02

Idea for visualizing data flow

https://github.com/transitland/transitland-processing-animation

Github repo has python code for animating points on a map over time

Consider adding Homeless

https://data.census.gov/table?q=foster+child&g=0100000US_0500000US37155_1600000US3739700&tid=ACSST5Y2019.S0901

https://data.census.gov/cedsci/table?q=foster%20child&g=0100000US_0500000US37155_1600000US3739700&tid=ACSST5Y2019.S0901

Homeless students
share housing with other persons due to loss of housing or economic hardship, live in hotels or motels, trailer parks, or campgrounds due to lack of alternative arrangements, those awaiting foster care placement, living in substandard housing, and children of migrant workers (CRS, 2018)

good list of characteristics - some of these are in the housing unit and person record inventory. Shared housing, trailer parks - could be identified in the data. Foster care might be something to summarize - the census bureau has counts of people in foster care.

I will see if I can flag shared housing. The person record inventory has household structure - could be based on number of adults to children. I would assume that shared housing would have multiple adults (3-4+) and multiple children (3+)

According to the National School Boards Association, during the 2018-2019 school year, 77% of homeless students lived in shared housing, 12% lived in shelters, transitional housing, or were awaiting foster care, 7% lived in hotels or motels, and 4% were unsheltered (Cai, 2021).

Cai, Jinghong. (2021). Homeless Students in Public Schools Across America: Down but Not Out. National School Boards Association.
Congressional Research Service (CRS). (2018). Homelessness: Targeted Federal Programs. CRS Report.

Run code in codespace

GitHub has a new option to run code in a virtual environment called codespace. This sounds like a good idea but - when I initially launch the codespace the environment is not setup. I had expected the environment to be based on the .yml file. But it looks like I need to make a .dev file.

Following these instructions:
https://docs.github.com/en/codespaces/setting-up-your-project-for-codespaces/adding-a-dev-container-configuration/setting-up-your-python-project-for-codespaces

Update LODES job record generation and run for multiple counties

Research Idea

We could use ipums to see what the general likelihood is that households have 0 to x number of vulnerabilities
Also could perform PCF to see how vulnerabilities relate to each other and which ones are highlighly correlated, the way the different categories weight could help guide the synthetic population variables to include

Issue with family variable in Oceana County

running code for oceana county
found that there is an issue with the family variable having missing values.
The code did not run the first time - error at the point of making the figure for family income.
The code ran fine the second time through.

Also an error with building available table. Might be an issue with the data not having anyone in missing buildings.

Modify housing unit inventory income model

Modify housing unit inventory income model to include race, ethnicity, age of householder, and tenure

some of the code in population inventory private github

Run HUA with non incore building inventory

working on workflow to run the Housing Unit Inventory on a non incore dataset
For example - in southeast texas we have National Address Data Inventory and Parcel data. What do I need to do to make the hua work with this type of file

Validate poverty results

U.S. Poverty Rates Differ by Age and County

https://www.census.gov/library/stories/2022/12/poverty-rates-by-age-county-region.html?utm_campaign=20221208msacos2ccstonl&utm_medium=email&utm_source=govdelivery

Can ncoda output replicate poverty by age?

Add HUA Application Section to Annotated Bibliography

Google scholar search Housing Unit Allocation
Add general articles that use HUA to the annotated bibliography

https://scholar.google.com/scholar?hl=en&as_sdt=0%2C23&as_ylo=2019&inst=14379318592444324147&q=%22housing+unit+allocation%22+Rosenheim&btnG=

For each citation provide a short description of how the article uses HUA data

references HUA but may not uses CGE data. Think about including it.

directory design - use community name

intersect-community-data/pyncoda/ncoda_00b_directory_design.py

Line 11 in f7503b7

def directory_design(state_county_name,

current code uses the county name as the primary folder for the directory structure
consider using the community name instead and put all files inside the same folder for the county loop

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