Imputes income field with a light refactor. Needs more refactor and more tests (I spotchecked). Next ticket will check and address but a lot of "narwhal" architecture is here.
Summary In this PR, we create a new variable so that the % college students is expressed as % not college students. This means that the front end can display % not college students.
Includes old variables so that this will not break fe.
* Adds four fields:
* Summer days above 90F
* Percent low access to healthy food
* Percent impenetrable surface areas
* Low third grade reading proficiency
* Each of these four gets added into Definition L in various factors.
* Additionally, I add college attendance fields to the ETL for Census ACS.
* This PR also introduces the notion of "reverse percentiles", relevant to ticket #970.
This ended up being a pretty large task. Here's what this PR does:
1. Pulls in Vincent's data from island areas into the score ETL. This is from the 2010 decennial census, the last census of any kind in the island areas.
2. Grabs a few new fields from 2010 island areas decennial census.
3. Calculates area median income for island areas.
4. Stops using EJSCREEN as the source of our high school education data and directly pulls that from census (this was related to this project so I went ahead and fixed it).
5. Grabs a bunch of data from the 2010 ACS in the states/Puerto Rico/DC, so that we can create percentiles comparing apples-to-apples (ish) from 2010 island areas decennial census data to 2010 ACS data. This required creating a new class because all the ACS fields are different between 2010 and 2019, so it wasn't as simple as looping over a year parameter.
6. Creates a combined population field of island areas and mainland so we can use those stats in our comparison tool, and updates the comparison tool accordingly.
* Use tract instead of block group when calling census API
* fixing merge conflicts
Co-authored-by: Shelby Switzer <shelby.switzer@cms.hhs.gov>
Co-authored-by: lucasmbrown-usds <lucas.m.brown@omb.eop.gov>
* WIP refactor
* Exract score calculations into their own methods
* do all initial df prep in single method
* Fix error in docs for running etl for single dataset
* WIP understanding HUD and linguistic iso data
* Add comments from initial group review on PR
Co-authored-by: Shelby Switzer <shelby.switzer@cms.hhs.gov>
* Fixes#456 - Our data directory should adopt standard python package structure
* a few missed references
* updating readme
* updating requirements
* Running Black
* Fixes for flake8
* updating pylint
2021-08-05 15:35:54 -04:00
Renamed from data/data-pipeline/etl/sources/census_acs/etl.py (Browse further)
