* Add notebook to generate test data (#1780)
* Add Abandoned Mine Land data (#1780)
Using a similar structure but simpler apporach compared to FUDs, add an
indicator for whether a tract has an abandonded mine.
* Adding some detail to dataset readmes
Just a thought!
* Apply feedback from revieiw (#1780)
* Fixup bad string that broke test (#1780)
* Update a string that I should have renamed (#1780)
* Reduce number of threads to reduce memory pressure (#1780)
* Try not running geo data (#1780)
* Run the high-memory sets separately (#1780)
* Actually deduplicate (#1780)
* Add flag for memory intensive ETLs (#1780)
* Document new flag for datasets (#1780)
* Add flag for new datasets fro rebase (#1780)
Co-authored-by: Emma Nechamkin <97977170+emma-nechamkin@users.noreply.github.com>
* Add spatial join method (#1871)
Since we'll need to figure out the tracts for a large number of points
in future tickets, add a utility to handle grabbing the tract geometries
and adding tract data to a point dataset.
* Add FUDS, also jupyter lab (#1871)
* Add YAML configs for FUDS (#1871)
* Allow input geoid to be optional (#1871)
* Add FUDS ETL, tests, test-datae noteobook (#1871)
This adds the ETL class for Formerly Used Defense Sites (FUDS). This is
different from most other ETLs since these FUDS are not provided by
tract, but instead by geographic point, so we need to assign FUDS to
tracts and then do calculations from there.
* Floats -> Ints, as I intended (#1871)
* Floats -> Ints, as I intended (#1871)
* Formatting fixes (#1871)
* Add test false positive GEOIDs (#1871)
* Add gdal binaries (#1871)
* Refactor pandas code to be more idiomatic (#1871)
Per Emma, the more pandas-y way of doing my counts is using np.where to
add the values i need, then groupby and size. It is definitely more
compact, and also I think more correct!
* Update configs per Emma suggestions (#1871)
* Type fixed! (#1871)
* Remove spurious import from vscode (#1871)
* Snapshot update after changing col name (#1871)
* Move up GDAL (#1871)
* Adjust geojson strategy (#1871)
* Try running census separately first (#1871)
* Fix import order (#1871)
* Cleanup cache strategy (#1871)
* Download census data from S3 instead of re-calculating (#1871)
* Clarify pandas code per Emma (#1871)
* added tribalId for Supplemental dataset (#1804)
* Setting zoom levels for tribal map (#1810)
* NRI dataset and initial score YAML configuration (#1534)
* update be staging gha
* NRI dataset and initial score YAML configuration
* checkpoint
* adding data checks for release branch
* passing tests
* adding INPUT_EXTRACTED_FILE_NAME to base class
* lint
* columns to keep and tests
* update be staging gha
* checkpoint
* update be staging gha
* NRI dataset and initial score YAML configuration
* checkpoint
* adding data checks for release branch
* passing tests
* adding INPUT_EXTRACTED_FILE_NAME to base class
* lint
* columns to keep and tests
* checkpoint
* PR Review
* renoving source url
* tests
* stop execution of ETL if there's a YAML schema issue
* update be staging gha
* adding source url as class var again
* clean up
* force cache bust
* gha cache bust
* dynamically set score vars from YAML
* docsctrings
* removing last updated year - optional reverse percentile
* passing tests
* sort order
* column ordening
* PR review
* class level vars
* Updating DatasetsConfig
* fix pylint errors
* moving metadata hint back to code
Co-authored-by: lucasmbrown-usds <lucas.m.brown@omb.eop.gov>
* Correct copy typo (#1809)
* Add basic test suite for COI (#1518)
* Update COI to use new yaml (#1518)
* Add tests for DOE energy budren (1518
* Add dataset config for energy budren (1518)
* Refactor ETL to use datasets.yml (#1518)
* Add fake GEOIDs to COI tests (#1518)
* Refactor _setup_etl_instance_and_run_extract to base (#1518)
For the three classes we've done so far, a generic
_setup_etl_instance_and_run_extract will work fine, for the moment we
can reuse the same setup method until we decide future classes need more
flexibility --- but they can also always subclass so...
* Add output-path tests (#1518)
* Update YAML to match constant (#1518)
* Don't blindly set float format (#1518)
* Add defaults for extract (#1518)
* Run YAML load on all subclasses (#1518)
* Update description fields (#1518)
* Update YAML per final format (#1518)
* Update fixture tract IDs (#1518)
* Update base class refactor (#1518)
Now that NRI is final I needed to make a small number of updates to my
refactored code.
* Remove old comment (#1518)
* Fix type signature and return (#1518)
* Update per code review (#1518)
Co-authored-by: Jorge Escobar <83969469+esfoobar-usds@users.noreply.github.com>
Co-authored-by: lucasmbrown-usds <lucas.m.brown@omb.eop.gov>
Co-authored-by: Vim <86254807+vim-usds@users.noreply.github.com>
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.
* update be staging gha
* NRI dataset and initial score YAML configuration
* checkpoint
* adding data checks for release branch
* passing tests
* adding INPUT_EXTRACTED_FILE_NAME to base class
* lint
* columns to keep and tests
* update be staging gha
* checkpoint
* update be staging gha
* NRI dataset and initial score YAML configuration
* checkpoint
* adding data checks for release branch
* passing tests
* adding INPUT_EXTRACTED_FILE_NAME to base class
* lint
* columns to keep and tests
* checkpoint
* PR Review
* renoving source url
* tests
* stop execution of ETL if there's a YAML schema issue
* update be staging gha
* adding source url as class var again
* clean up
* force cache bust
* gha cache bust
* dynamically set score vars from YAML
* docsctrings
* removing last updated year - optional reverse percentile
* passing tests
* sort order
* column ordening
* PR review
* class level vars
* Updating DatasetsConfig
* fix pylint errors
* moving metadata hint back to code
Co-authored-by: lucasmbrown-usds <lucas.m.brown@omb.eop.gov>
* starting tribal pr
* further pipeline work
* bia merge working
* alaska villages and tribal geo generate
* tribal folders
* adding data full run
* tile generation
* tribal tile deploy
* installation step
* trigger action
* installing to home dir
* dry-run
* pyenv
* py 2.8
* trying s4cmd
* removing pyenv
* poetry s4cmd
* num-threads
* public read
* poetry cache
* s4cmd all around
* poetry cache
* poetry cache
* install poetry packages
* poetry echo
* let's do this
* s4cmd install on run
* s4cmd
* ad aws back
* add aws back
* testing census api key and poetry caching
* census api key
* census api
* census api key #3
* 250
* poetry update
* poetry change
* check census api key
* force flag
* update score gen and tilefy; remove cached fips
* small gdal update
* invalidation
* missing cache ids
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.
Did some quick, mostly cosmetic changes and updates to the quick launch changes. This mostly entailed changing strings to constants and cleaning up some code to make it neater.
Changes -- PR AMI, updating ag loss, and dropping pr from some threshold counts.
we wanted to implement a slightly different FEMA AG LOSS indicator. Here, we take the 90th percentile only of tracts that have agvalue, and then we also floor the denominator of the rate calculation (loss/total value) at $408k
* WIP on parallelizing
* switching to get_tmp_path for nri
* switching to get_tmp_path everywhere necessary
* fixing linter errors
* moving heavy ETLs to front of line
* add hold
* moving cdc places up
* removing unnecessary print
* moving h&t up
* adding parallel to geo post
* better census labels
* switching to concurrent futures
* fixing output
* Re-export requirements.txt to fix version errors
The version of lxml in this file had a known vulnerability that got
caught by the "safety" checker, but it is updated in the poetry files.
Regenerated using:
https://github.com/usds/justice40-tool/tree/main/data/data-pipeline#miscellaneous
* Fix lint error
* Run lint on all envs and add comments
* Ignore testst that fail lint because of dev deps
* Ignore medium.com in link checker
It's returning 403s to github actions...
* draft wip
* initial commit
* clear output from notebook
* revert to 65ceb7900f
* draft wip
* initial commit
* clear output from notebook
* revert to 65ceb7900f
* make michigan prefix for readable
* standardize Michigan names and move all constants from class into field names module
* standardize Michigan names and move all constants from class into field names module
* include only pertinent columns for scoring comparison tool
* michigan EJSCREEN standardization
* final PR feedback
* added exposition and summary of Michigan EJSCREEN
* added exposition and summary of Michigan EJSCREEN
* fix typo
Co-authored-by: Saran Ahluwalia <ahlusar.ahluwalia@gmail.com>
* Update Side Panel Tile Data
* Update Side Panel Tile Data
* Correct indicator names to match csv
* Replace Score with Rate
* Comment out FEMA Loss Rate to troubleshoot
* Removes all "FEMA Loss Rate" array elements
* Revert FEMA to Score
* Remove expected loss rate
* Remove RMP and NPL from BASIC array
* Attempt to make shape mismatch align
- update README typo
* Add Score L indicators to TILE_SCORE_FLOAT_COLUMNS
* removing cbg references
* completes the ticket
* Update side panel fields
* Update index file writing to create parent dir
* Updates from linting
* fixing missing field_names for island territories 90th percentile fields
* Update downloadable fields and fix field name
* Update file fields and tests
* Update ordering of fields and leave TODO
* Update pickle after re-ordering of file
* fixing bugs in etl_score_geo
* Repeating index for diesel fix
* passing tests
* adding pytest.ini
Co-authored-by: Vim USDS <vimal.k.shah@omb.eop.gov>
Co-authored-by: Shelby Switzer <shelby.switzer@cms.hhs.gov>
Co-authored-by: lucasmbrown-usds <lucas.m.brown@omb.eop.gov>
* 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.
* added fieldnames
* todo pollution, water, health & workforce
* workforce
* work in progress
* add utility function to replace duplicate summation logic
* move fpl series into add columns - run black .
* added revisions - still a wip
* added fieldnames
* todo pollution, water, health & workforce
* workforce
* work in progress
* add utility function to replace duplicate summation logic
* move fpl series into add columns - run black .
* added revisions - still a wip
* revise workforce and water
* revise housing and add incremental counter for workforce
* last PR nit
* revise workforce
* more PR feedback in score l
* more PR feedback in score l
* more PR feedback in score l
* addd FPL_SERIES and update references in score 1
* fix bugs
* reparameterize function
* final revisions in fieldnames
* make computations all consistent so we assing with FPL_200_SERIES
* fieldnames refactor after clarification and PR review
* finalize
* finalize with no typos
* fix length
* added median income var
* swap thresholds
* remove iteration
* remove stray '
* address flake 8
* added f string formatting and fixed typos
* added f string formatting and fixed typos
* move up
* remove dupes
* reformat
* fix bugs
* fix bugs
* initialize
Co-authored-by: Saran Ahluwalia <sarahluw@cisco.com>
