Issue 1900: Tribal overlap with Census tracts #1903

lucasmbrown-usds · 2022-09-16T01:49:12Z

Issue #1900.

This PR creates the ETL, and merges the data in etl_score, but it does not put the new fields in the tiles or the download files. That's left to a next PR after we clarify our intentions.

Example output file:
usa.csv

lucasmbrown-usds · 2022-09-16T02:23:14Z

data/data-pipeline/data_pipeline/etl/sources/geo_utils.py

 def add_tracts_for_geometries(
-    df: gpd.GeoDataFrame, _tract_data_path: Optional[Path] = None
+    df: gpd.GeoDataFrame, tract_data: Optional[gpd.GeoDataFrame] = None


I refactored this a bit, so I could load the Tract geojson once in the tribal overlap ETL, and not just pass around a data path.

I like that change --- I had been passing the path just to make my tests faster, so this is a nice way of adding flexibility.

lucasmbrown-usds · 2022-09-16T02:26:33Z

data/data-pipeline/data_pipeline/tests/score/test_utils/data/us.geojson

-{ "type": "Feature", "properties": { "STATEFP10": "24", "COUNTYFP10": "027", "TRACTCE10": "603003", "GEOID10_TRACT": "24027603003", "NAME10": "6030.03", "NAMELSAD10": "Census Tract 6030.03", "MTFCC10": "G5020", "FUNCSTAT10": "S", "ALAND10": 45161338, "AWATER10": 174904, "INTPTLAT10": "+39.3192333", "INTPTLON10": "-076.9680454" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ -76.933499, 39.357602 ], [ -76.933409, 39.35756 ], [ -76.933305, 39.357502 ], [ -76.933213, 39.357448 ], [ -76.933124, 39.357401 ], [ -76.933052, 39.357343 ], [ -76.932917, 39.357247 ], [ -76.932699, 39.357065 ], [ -76.932616, 39.357003 ], [ -76.932564, 39.356949 ], [ -76.932501, 39.356879 ], [ -76.932492, 39.356869 ], [ -76.932417, 39.356799 ], [ -76.932331, 39.356719 ], [ -76.932256, 39.356625 ], [ -76.932148, 39.35643 ], [ -76.932073, 39.356265 ], [ -76.931978, 39.35611 ], [ -76.931915, 39.356003 ], [ -76.931858, 39.355938 ], [ -76.9318, 39.355878 ], [ -76.931708, 39.355802 ], [ -76.931565, 39.355672 ], 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Note: all I changed here is renaming the field GEOID10_TRACT as GEOID10. This is more realistic. And also, it will otherwise yell at us now that I set errors="raise" in

tract_data = tract_data.rename( columns={"GEOID10": "GEOID10_TRACT"}, errors="raise" )

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mattbowen-usds

Overall this is quite nice. I stepped through the ETL and made sure I understood why it was going what it was doing, and I do have one legit question about the suppressed warning, but overall this is great.

mattbowen-usds · 2022-09-16T14:11:45Z

data/data-pipeline/data_pipeline/etl/sources/geo_utils.py

 def add_tracts_for_geometries(
-    df: gpd.GeoDataFrame, _tract_data_path: Optional[Path] = None
+    df: gpd.GeoDataFrame, tract_data: Optional[gpd.GeoDataFrame] = None


haha I did not expect this to end up used this way, but now I'm glad it existed and could be easily adapted to this new use case.

it was awesome! loved reusable code!

mattbowen-usds · 2022-09-16T17:17:33Z

data/data-pipeline/data_pipeline/etl/runner.py

@@ -106,6 +106,8 @@ def etl_runner(dataset_to_run: str = None) -> None:
                # Otherwise, the exceptions are silently ignored.
                fut.result()

+    # Note: these high-memory datasets also usually require the Census geojson to be


Helpful, thank you.

data/data-pipeline/data_pipeline/etl/score/etl_score.py

mattbowen-usds · 2022-09-16T18:02:06Z

data/data-pipeline/data_pipeline/etl/sources/tribal_overlap/etl.py

+
+        # Create a measure for the entire census tract area
+        with warnings.catch_warnings():
+            # Note: geopandas will (helpfully) warn that area is not a useful metric


I ran the line and got this warning:

UserWarning: keep_geom_type=Truein overlay resulted in 348 dropped geometries of different geometry types than df1 has. Setkeep_geom_type=False to retain all geometries

That was not the warning I expected (I thought it would complain about projected vs geographic CRS. Both DFs have CRSes (they're both in WSG 84/EPSG:4326), so there wouldn't be a mismatch. Any idea what that warning is about? Also I feel like the comment suggests something else is going on.

Oh shoot! That is an error I missed. I built this using a subset file of the tracts to improve speed of development, it must not have been present in the subset I used.

Overlay requires the same geometry types, but it treats MultiPolygon and Polygon as compatible.

Because we drop the points in line 101 to create tribal_gdf_without_points, I wasn't expecting warnings. It turns out that there are some Tribal areas with a "none" geography type. I'm updating them now to fix!

I'm also more aggressively restricting the filter so it doesn't suppress other helpful warnings like this in the future.

Nice catch @mattbowen-usds !!

@mattbowen-usds -- I honestly have no idea what's going on here. I pushed some new code that removes both the Points and the None from tribal_gdf.

But, the warning is still there, even though it should be polygon/multipolygon to polygon/multipolygon, which should be fine.

Further, it says 348 dropped geometries -- which is more than the rows in tribal_gdf_without_points!

If this is urgent to get in Monday, do you mind investigating a little bit while I'm out?

From my commit

I looked into this a bit, and in general the geometry type mismatch
changes very little about the calculation; we have a mix of
multipolygons and polygons. The fastest thing to do is just not keep
geom type; I did some runs with it set to both True and False, and
they're the same within 9 digits of precision. Logically we just want to
overlaps, regardless of how the actual geometries are encoded between
the frames, so we can in this case ignore the geom types and feel OKAY.

I changed it to ignore the geometry types because that is what makes sense to me after really digging into it, and also it basically doesn't matter; whatever was dropping before is a TINY (< .00000001%) amount of actual area.

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esfoobar-usds

🍏 with some small comments

esfoobar-usds · 2022-09-19T18:19:57Z

data/data-pipeline/README.md

+as `poetry run tox`.
+
+Each run can take a while to build the whole environment. If you'd like to save time,
+you can use the previously built environment by running `poetry run tox -e lint` 


I didn't know this one!

That's a @sverchdotgov discovery!

esfoobar-usds · 2022-09-19T18:21:49Z

data/data-pipeline/data_pipeline/etl/sources/geo_utils.py

    return tract_data


+@lru_cache()


I am curious about the usage of lru_cache here. Is this function called multiple times?

I am guessing he was following the convention get_tract_geojson, and i was like "well, it won't hurt, since it is expensive. I believe at this time it isn't, so I'm good to drop the cache untel we need ot/

@esfoobar-usds @mattbowen-usds yes exactly I was just following conventions. Do we want to delete @lru_cache from both functions, or keep it on both?

It is actually useful on get_tract_geojson, so I vote keep it. And I'm about to merge so it's stayin'

esfoobar-usds · 2022-09-19T18:22:26Z

data/data-pipeline/data_pipeline/etl/sources/tribal/etl.py

+                "LARID": field_names.TRIBAL_ID,
+                "LARName": field_names.TRIBAL_LAND_AREA_NAME,


Nice catch!

esfoobar-usds · 2022-09-19T18:22:41Z

data/data-pipeline/data_pipeline/etl/sources/tribal/etl.py

+                "OBJECTID": field_names.TRIBAL_ID,
+                "Land_Area_": field_names.TRIBAL_LAND_AREA_NAME,


esfoobar-usds · 2022-09-19T18:23:25Z

data/data-pipeline/data_pipeline/etl/sources/tribal_overlap/etl.py

+        "10",
+        "11",
+        "13",
+        "15",
+        "17",
+        "18",
+        "21",
+        "24",
+        "33",
+        "34",
+        "39",
+        "50",
+        "51",
+        "54",


Can we document why this is?

Lol I honestly have no idea either, so I'll give that to @lucasmbrown-usds --- my best guess is those states have no tribal lands in them.

Yes exactly. I'll add a comment though, awesome point @esfoobar-usds that we should be commenting these.

I looked into this a bit, and in general the geometry type mismatch changes very little about the calculation; we have a mix of multipolygons and polygons. The fastest thing to do is just not keep geom type; I did some runs with it set to both True and False, and they're the same within 9 digits of precision. Logically we just want to overlaps, regardless of how the actual geometries are encoded between the frames, so we can in this case ignore the geom types and feel OKAY. I also moved to projected CRSes, since we are actually trying to do area calculations and so like, we should. Again, the change is small in magnitude but logically more sound.

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Find tiles here: https://justice40-data.s3.amazonaws.com/data-pipeline-staging/1903/4ce8f6aab45a7f1a950b5186ebfaf30fc94bf90c/data/score/tiles

* Create deploy_be_staging.yml (#1575) * Imputing income using geographic neighbors (#1559) 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. * Adding HOLC indicator (#1579) Added HOLC indicator (Historic Redlining Score) from NCRC work; included 3.25 cutoff and low income as part of the housing burden category. * Update backend for Puerto Rico (#1686) * Update PR threshold count to 10 We now show 10 indicators for PR. See the discussion on the github issue for more info: #1621 * Do not use linguistic iso for Puerto Rico Closes 1350. Co-authored-by: Shelby Switzer <shelbyswitzer@gmail.com> * updating * Do not drop Guam and USVI from ETL (#1681) * Remove code that drops Guam and USVI from ETL * Add back code for dropping rows by FIPS code We may want this functionality, so let's keep it and just make the constant currently be an empty array. Co-authored-by: Shelby Switzer <shelbyswitzer@gmail.com> * Emma nechamkin/holc patch (#1742) Removing HOLC calculation from score narwhal. * updating ejscreen data, try two (#1747) * Rescaling linguistic isolation (#1750) Rescales linguistic isolation to drop puerto rico * adds UST indicator (#1786) adds leaky underground storage tanks * Changing LHE in tiles to a boolean (#1767) also includes merging / clean up of the release * added indoor plumbing to chas * added indoor plumbing to score housing burden * added indoor plumbing to score housing burden * first run through * Refactor DOE Energy Burden and COI to use YAML (#1796) * 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> * Update etl_score_geo.py Yikes! Fixing merge messup! * Create deploy_be_staging.yml (#1575) * Imputing income using geographic neighbors (#1559) 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. * Adding HOLC indicator (#1579) Added HOLC indicator (Historic Redlining Score) from NCRC work; included 3.25 cutoff and low income as part of the housing burden category. * Update backend for Puerto Rico (#1686) * Update PR threshold count to 10 We now show 10 indicators for PR. See the discussion on the github issue for more info: #1621 * Do not use linguistic iso for Puerto Rico Closes 1350. Co-authored-by: Shelby Switzer <shelbyswitzer@gmail.com> * updating * Do not drop Guam and USVI from ETL (#1681) * Remove code that drops Guam and USVI from ETL * Add back code for dropping rows by FIPS code We may want this functionality, so let's keep it and just make the constant currently be an empty array. Co-authored-by: Shelby Switzer <shelbyswitzer@gmail.com> * Emma nechamkin/holc patch (#1742) Removing HOLC calculation from score narwhal. * updating ejscreen data, try two (#1747) * Rescaling linguistic isolation (#1750) Rescales linguistic isolation to drop puerto rico * adds UST indicator (#1786) adds leaky underground storage tanks * Changing LHE in tiles to a boolean (#1767) also includes merging / clean up of the release * added indoor plumbing to chas * added indoor plumbing to score housing burden * added indoor plumbing to score housing burden * first run through * Refactor DOE Energy Burden and COI to use YAML (#1796) * 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> * Update etl_score_geo.py Yikes! Fixing merge messup! * updated to fix linting errors (#1818) Cleans and updates base branch * Adding back MapComparison video * Add FUDS ETL (#1817) * 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) * Disable markdown check for link * Adding DOT composite to travel score (#1820) This adds the DOT dataset to the ETL and to the score. Note that currently we take a percentile of an average of percentiles. * Adding first street foundation data (#1823) Adding FSF flood and wildfire risk datasets to the score. * first run -- adding NCLD data to the ETL, but not yet to the score * Add abandoned mine lands data (#1824) * 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> * Adding NLCD data (#1826) Adding NLCD's natural space indicator end to end to the score. * Add donut hole calculation to score (#1828) Adds adjacency index to the pipeline. Requires thorough QA * Adding eamlis and fuds data to legacy pollution in score (#1832) Update to add EAMLIS and FUDS data to score * Update to use new FSF files (#1838) backend is partially done! * Quick fix to kitchen or plumbing indicator Yikes! I think I messed something up and dropped the pctile field suffix from when the KP score gets calculated. Fixing right quick. * Fast flag update (#1844) Added additional flags for the front end based on our conversation in stand up this morning. * Tiles fix (#1845) Fixes score-geo and adds flags * Update etl_score_geo.py * Issue 1827: Add demographics to tiles and download files (#1833) * Adding demographics for use in sidebar and download files * Updates backend constants to N (#1854) * updated to show T/F/null vs T/F for AML and FUDS (#1866) * fix markdown * just testing that the boolean is preserved on gha * checking drop tracts works * OOPS! Old changes persisted * adding a check to the agvalue calculation for nri * updated with error messages * updated error message * tuple type * Score tests (#1847) * update Python version on README; tuple typing fix * Alaska tribal points fix (#1821) * Bump mistune from 0.8.4 to 2.0.3 in /data/data-pipeline (#1777) Bumps [mistune](https://github.com/lepture/mistune) from 0.8.4 to 2.0.3. - [Release notes](https://github.com/lepture/mistune/releases) - [Changelog](https://github.com/lepture/mistune/blob/master/docs/changes.rst) - [Commits](lepture/mistune@v0.8.4...v2.0.3) --- updated-dependencies: - dependency-name: mistune dependency-type: indirect ... Signed-off-by: dependabot[bot] <support@github.com> Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> * poetry update * initial pass of score tests * add threshold tests * added ses threshold (not donut, not island) * testing suite -- stopping for the day * added test for lead proxy indicator * Refactor score tests to make them less verbose and more direct (#1865) * Cleanup tests slightly before refactor (#1846) * Refactor score calculations tests * Feedback from review * Refactor output tests like calculatoin tests (#1846) (#1870) * Reorganize files (#1846) * Switch from lru_cache to fixture scorpes (#1846) * Add tests for all factors (#1846) * Mark smoketests and run as part of be deply (#1846) * Update renamed var (#1846) * Switch from named tuple to dataclass (#1846) This is annoying, but pylint in python3.8 was crashing parsing the named tuple. We weren't using any namedtuple-specific features, so I made the type a dataclass just to get pylint to behave. * Add default timout to requests (#1846) * Fix type (#1846) * Fix merge mistake on poetry.lock (#1846) Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: Jorge Escobar <jorge.e.escobar@omb.eop.gov> Co-authored-by: Jorge Escobar <83969469+esfoobar-usds@users.noreply.github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Matt Bowen <83967628+mattbowen-usds@users.noreply.github.com> Co-authored-by: matt bowen <matthew.r.bowen@omb.eop.gov> * just testing that the boolean is preserved on gha (#1867) * updated with hopefully a fix; coercing aml, fuds, hrs to booleans for the raw value to preserve null character. * Adding tests to ensure proper calculations (#1871) * just testing that the boolean is preserved on gha * checking drop tracts works * adding a check to the agvalue calculation for nri * updated with error messages * tribal tiles fix (#1874) * Alaska tribal points fix (#1821) * tribal tiles fix * disabling child opportunity * lint * removing COI * removing commented out code * Pipeline tile tests (#1864) * temp update * updating with fips check * adding check on pfs * updating with pfs test * Update test_tiles_smoketests.py * Fix lint errors (#1848) * Add column names test (#1848) * Mark tests as smoketests (#1848) * Move to other score-related tests (#1848) * Recast Total threshold criteria exceeded to int (#1848) In writing tests to verify the output of the tiles csv matches the final score CSV, I noticed TC/Total threshold criteria exceeded was getting cast from an int64 to a float64 in the process of PostScoreETL. I tracked it down to the line where we merge the score dataframe with constants.DATA_CENSUS_CSV_FILE_PATH --- there where > 100 tracts in the national census CSV that don't exist in the score, so those ended up with a Total threshhold count of np.nan, which is a float, and thereby cast those columns to float. For the moment I just cast it back. * No need for low memeory (#1848) * Add additional tests of tiles.csv (#1848) * Drop pre-2010 rows before computing score (#1848) Note this is probably NOT the optimal place for this change; it might make more sense for each source to filter its own tracts down to the acceptable tract list. However, that would be a pretty invasive change, where this is central and plenty of other things are happening in score transform that could be moved to sources, so for today, here's where the change will live. * Fix typo (#1848) * Switch from filter to inner join (#1848) * Remove no-op lines from tiles (#1848) * Apply feedback from review, linter (#1848) * Check the values oeverything in the frame (#1848) * Refactor checker class (#1848) * Add test for state names (#1848) * cleanup from reviewing my own code (#1848) * Fix lint error (#1858) * Apply Emma's feedback from review (#1848) * Remove refs to national_df (#1848) * Account for new, fake nullable bools in tiles (#1848) To handle a geojson limitation, Emma converted some nullable boolean colunms to float64 in the tiles export with the values {0.0, 1.0, nan}, giving us the same expressiveness. Sadly, this broke my assumption that all columns between the score and tiles csvs would have the same dtypes, so I need to account for these new, fake bools in my test. * Use equals instead of my worse version (#1848) * Missed a spot where we called _create_score_data (#1848) * Update per safety (#1848) Co-authored-by: matt bowen <matthew.r.bowen@omb.eop.gov> * Add tests to make sure each source makes it to the score correctly (#1878) * Remove unused persistent poverty from score (#1835) * Test a few datasets for overlap in the final score (#1835) * Add remaining data sources (#1853) * Apply code-review feedback (#1835) * Rearrange a little for readabililty (#1835) * Add tract test (#1835) * Add test for score values (#1835) * Check for unmatched source tracts (#1835) * Cleanup numeric code to plaintext (#1835) * Make import more obvious (#1835) * Updating traffic barriers to include low pop threshold (#1889) Changing the traffic barriers to only be included for places with recorded population * Remove no land tracts from map (#1894) remove from map * Issue 1831: missing life expectancy data from Maine and Wisconsin (#1887) * Fixing missing states and adding tests for states to all classes * Removing low pop tracts from FEMA population loss (#1898) dropping 0 population from FEMA * 1831 Follow up (#1902) This code causes no functional change to the code. It does two things: 1. Uses difference instead of - to improve code style for working with sets. 2. Removes the line EXPECTED_MISSING_STATES = ["02", "15"], which is now redundant because of the line I added (in a previous pull request) of ALASKA_AND_HAWAII_EXPECTED_IN_DATA = False. * Add tests for all non-census sources (#1899) * Refactor CDC life-expectancy (1554) * Update to new tract list (#1554) * Adjust for tests (#1848) * Add tests for cdc_places (#1848) * Add EJScreen tests (#1848) * Add tests for HUD housing (#1848) * Add tests for GeoCorr (#1848) * Add persistent poverty tests (#1848) * Update for sources without zips, for new validation (#1848) * Update tests for new multi-CSV but (#1848) Lucas updated the CDC life expectancy data to handle a bug where two states are missing from the US Overall download. Since virtually none of our other ETL classes download multiple CSVs directly like this, it required a pretty invasive new mocking strategy. * Add basic tests for nature deprived (#1848) * Add wildfire tests (#1848) * Add flood risk tests (#1848) * Add DOT travel tests (#1848) * Add historic redlining tests (#1848) * Add tests for ME and WI (#1848) * Update now that validation exists (#1848) * Adjust for validation (#1848) * Add health insurance back to cdc places (#1848) Ooops * Update tests with new field (#1848) * Test for blank tract removal (#1848) * Add tracts for clipping behavior * Test clipping and zfill behavior (#1848) * Fix bad test assumption (#1848) * Simplify class, add test for tract padding (#1848) * Fix percentage inversion, update tests (#1848) Looking through the transformations, I noticed that we were subtracting a percentage that is usually between 0-100 from 1 instead of 100, and so were endind up with some surprising results. Confirmed with lucasmbrown-usds * Add note about first street data (#1848) * Issue 1900: Tribal overlap with Census tracts (#1903) * working notebook * updating notebook * wip * fixing broken tests * adding tribal overlap files * WIP * WIP * WIP, calculated count and names * working * partial cleanup * partial cleanup * updating field names * fixing bug * removing pyogrio * removing unused imports * updating test fixtures to be more realistic * cleaning up notebook * fixing black * fixing flake8 errors * adding tox instructions * updating etl_score * suppressing warning * Use projected CRSes, ignore geom types (#1900) I looked into this a bit, and in general the geometry type mismatch changes very little about the calculation; we have a mix of multipolygons and polygons. The fastest thing to do is just not keep geom type; I did some runs with it set to both True and False, and they're the same within 9 digits of precision. Logically we just want to overlaps, regardless of how the actual geometries are encoded between the frames, so we can in this case ignore the geom types and feel OKAY. I also moved to projected CRSes, since we are actually trying to do area calculations and so like, we should. Again, the change is small in magnitude but logically more sound. * Readd CDC dataset config (#1900) * adding comments to fips code * delete unnecessary loggers Co-authored-by: matt bowen <matthew.r.bowen@omb.eop.gov> * Improve score test documentation based on Lucas's feedback (#1835) (#1914) * Better document base on Lucas's feedback (#1835) * Fix typo (#1835) * Add test to verify GEOJSON matches tiles (#1835) * Remove NOOP line (#1835) * Move GEOJSON generation up for new smoketest (#1835) * Fixup code format (#1835) * Update readme for new somketest (#1835) * Cleanup source tests (#1912) * Move test to base for broader coverage (#1848) * Remove duplicate line (#1848) * FUDS needed an extra mock (#1848) * Add tribal count notebook (#1917) (#1919) * Add tribal count notebook (#1917) * test without caching * added comment Co-authored-by: lucasmbrown-usds <lucas.m.brown@omb.eop.gov> * Add tribal overlap to downloads (#1907) * Add tribal data to downloads (#1904) * Update test pickle with current cols (#1904) * Remove text of tribe names from GeoJSON (#1904) * Update test data (#1904) * Add tribal overlap to smoketests (#1904) * Issue 1910: Do not impute income for 0 population tracts (#1918) * should be working, has unnecessary loggers * removing loggers and cleaning up * updating ejscreen tests * adding tests and responding to PR feedback * fixing broken smoke test * delete smoketest docs * updating click * updating click * Bump just jupyterlab (#1930) * Fixing link checker (#1929) * Update deps safety says are vulnerable (#1937) (#1938) Co-authored-by: matt bowen <matt@mattbowen.net> * Add demos for island areas (#1932) * Backfill population in island areas (#1882) * Update smoketest to account for backfills (#1882) As I wrote in the commend: We backfill island areas with data from the 2010 census, so if THOSE tracts have data beyond the data source, that's to be expected and is fine to pass. If some other state or territory does though, this should fail This ends up being a nice way of documenting that behavior i guess! * Fixup lint issues (#1882) * Add in race demos to 2010 census pull (#1851) * Add backfill data to score (#1851) * Change column name (#1851) * Fill demos after the score (#1851) * Add income back, adjust test (#1882) * Apply code-review feedback (#1851) * Add test for island area backfill (#1851) * Fix bad rename (#1851) * Reorder download fields, add plumbing back (#1942) * Add back lack of plumbing fields (#1920) * Reorder fields for excel (#1921) * Reorder excel fields (#1921) * Fix formating, lint errors, pickes (#1921) * Add missing plumbing col, fix order again (#1921) * Update that pickle (#1921) * refactoring tribal (#1960) * updated with scoring comparison * updated for narhwal -- leaving commented code in for now * pydantic upgrade * produce a string for the front end to ingest (#1963) * wip * i believe this works -- let's see the pipeline * updated fixtures * Adding ADJLI_ET (#1976) * updated tile data * ensuring adjli_et in * Add back income percentile (#1977) * Add missing field to download (#1964) * Remove pydantic since it's unused (#1964) * Add percentile to CSV (#1964) * Update downloadable pickle (#1964) * Issue 105: Configure and run `black` and other pre-commit hooks (clean branch) (#1962) * Configure and run `black` and other pre-commit hooks Co-authored-by: matt bowen <matthew.r.bowen@omb.eop.gov> * Removing fixed python version for black (#1985) * Fixup TA_COUNT and TA_PERC (#1991) * Change TA_PERC, change TA_COUNT (#1988, #1989) - Make TA_PERC_STR back into a nullable float following the rules requestsed in #1989 - Move TA_COUNT to be TA_COUNT_AK, also add a null TA_COUNT_C for CONUS that we can fill in later. * Fix typo comment (#1988) * Issue 1992: Do not impute income for null population tracts (#1993) * Hotfix for DOT data source DNS issue (#1999) * Make tribal overlap set score N (#2004) * Add "Is a Tribal DAC" field (#1998) * Add tribal DACs to score N final (#1998) * Add new fields to downloads (#1998) * Make a int a float (#1998) * Update field names, apply feedback (#1998) * Add assertions around codebook (#2014) * Add assertion around codebook (#1505) * Assert csv and excel have same cols (#1505) * Remove suffixes from tribal lands (#1974) (#2008) * Data source location (#2015) * data source location * toml * cdc_places * cdc_svi_index * url updates * child oppy and dot travel * up to hud_recap * completed ticket * cache bust * hud_recap * us_army_fuds * Remove vars the frontend doesn't use (#2020) (#2022) I did a pretty rough and simple analysis of the variables we put in the tiles and grepped the frontend code to see if (1) they're ever accessed and (2) if they're used, even if they're read once. I removed everything I noticed was not accessed. * Disable file size limits on tiles (#2031) * Disable file size limits on tiles * Remove print debugs I know. * Update file name pattern (#2037) (#2038) * Update file name pattern (#2037) * Remove ETL from generation (2037) I looked more carefully, and this ETL step isn't used in the score, so there's no need to run it every time. Per previous steps, I removed it from constants so the code is there it won't run by default. * Round ALL the float fields for the tiles (#2040) * Round ALL the float fields for the tiles (#2033) * Floor in a simpler way (#2033) Emma pointed out that all teh stuff we're doing in floor_series is probably unnecessary for this case, so just use the built-in floor. * Update pickle I missed (#2033) * Clean commit of just aggregate burden notebook (#1819) added a burden notebook * Update the dockerfile (#2045) * Update so the image builds (#2026) * Fix bad dict (2026) * Rename census tract field in downloads (#2068) * Change tract ID field name (2060) * Update lockfile (#2061) * Bump safety, jupyter, wheel (#2061) * DOn't depend directly on wheel (2061) * Bring narwhal reqs in line with main * Update tribal area counts (#2071) * Rename tribal area field (2062) * Add missing file (#2062) * Add checks to create version (#2047) (#2052) * Fix failing safety (#2114) * Ignore vuln that doesn't affect us 2113 https://nvd.nist.gov/vuln/detail/CVE-2022-42969 landed recently and there's no fix in py (which is maintenance mode). From my analysis, that CVE cannot hurt us (famous last words), so we'll ignore the vuln for now. * 2113 Update our gdal ppa * that didn't work (2113) * Don't add the PPA, the package exists (#2113) * Fix type (#2113) * Force an update of wheel 2113 * Also remove PPA line from create-score-versions * Drop 3.8 because of wheel 2113 * Put back 3.8, use newer actions * Try another way of upgrading wheel 2113 * Upgrade wheel in tox too 2113 * Typo fix 2113 Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: Emma Nechamkin <97977170+emma-nechamkin@users.noreply.github.com> Co-authored-by: Shelby Switzer <shelby.c.switzer@omb.eop.gov> Co-authored-by: Shelby Switzer <shelbyswitzer@gmail.com> Co-authored-by: Emma Nechamkin <Emma.J.Nechamkin@omb.eop.gov> Co-authored-by: Matt Bowen <83967628+mattbowen-usds@users.noreply.github.com> 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: Jorge Escobar <jorge.e.escobar@omb.eop.gov> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: matt bowen <matthew.r.bowen@omb.eop.gov> Co-authored-by: matt bowen <matt@mattbowen.net>

lucasmbrown-usds requested review from esfoobar-usds, vim-usds, emma-nechamkin and mattbowen-usds as code owners September 16, 2022 01:49

lucasmbrown-usds changed the base branch from main to emma-nechamkin/release/score-narwhal September 16, 2022 01:56

lucasmbrown-usds commented Sep 16, 2022

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mattbowen-usds approved these changes Sep 16, 2022

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esfoobar-usds approved these changes Sep 19, 2022

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lucasmbrown-usds added 15 commits September 19, 2022 16:25

working notebook

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updating notebook

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wip

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fixing broken tests

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adding tribal overlap files

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WIP

c1a5561

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WIP, calculated count and names

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working

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partial cleanup

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partial cleanup

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updating field names

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fixing bug

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removing pyogrio

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removing unused imports

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lucasmbrown-usds and others added 9 commits September 19, 2022 16:27

updating test fixtures to be more realistic

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cleaning up notebook

81e3180

fixing black

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fixing flake8 errors

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adding tox instructions

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updating etl_score

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suppressing warning

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Readd CDC dataset config (#1900)

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mattbowen-usds force-pushed the issue-1900-tribal-overlap branch from f8f05aa to 52446b1 Compare September 19, 2022 20:37

lucasmbrown-usds added 2 commits September 20, 2022 11:38

adding comments to fips code

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delete unnecessary loggers

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mattbowen-usds merged commit aca2261 into emma-nechamkin/release/score-narwhal Sep 20, 2022

mattbowen-usds deleted the issue-1900-tribal-overlap branch September 20, 2022 18:53

		"LARID": field_names.TRIBAL_ID,
		"LARName": field_names.TRIBAL_LAND_AREA_NAME,

		"OBJECTID": field_names.TRIBAL_ID,
		"Land_Area_": field_names.TRIBAL_LAND_AREA_NAME,

Issue 1900: Tribal overlap with Census tracts #1903

Issue 1900: Tribal overlap with Census tracts #1903

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lucasmbrown-usds commented Sep 16, 2022 •

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