From cb4866b93ff453bc7d7813d545edad252ee26a14 Mon Sep 17 00:00:00 2001 From: Emma Nechamkin <97977170+emma-nechamkin@users.noreply.github.com> Date: Thu, 18 Aug 2022 13:32:29 -0400 Subject: [PATCH] Adding eamlis and fuds data to legacy pollution in score (#1832) Update to add EAMLIS and FUDS data to score --- .../data_pipeline/content/config/csv.yml | 12 ++++++++ .../data_pipeline/content/config/excel.yml | 12 ++++++++ .../data-pipeline/data_pipeline/etl/runner.py | 28 ++++++++++-------- .../data_pipeline/etl/score/constants.py | 2 ++ .../data_pipeline/etl/score/etl_score.py | 14 +++++++++ .../tests/sample_data/score_data_initial.csv | 6 ++-- .../snapshots/downloadable_data_expected.pkl | Bin 16485 -> 16901 bytes .../tests/snapshots/score_data_expected.pkl | Bin 23645 -> 24035 bytes .../snapshots/score_transformed_expected.pkl | Bin 23326 -> 23716 bytes .../tests/snapshots/tile_data_expected.pkl | Bin 4309 -> 4376 bytes .../etl/sources/us_army_fuds/etl.py | 4 +-- .../data_pipeline/score/field_names.py | 10 +++++++ .../data_pipeline/score/score_narwhal.py | 25 +++++++++++++--- .../tests/sources/eamlis/test_etl.py | 4 +-- 14 files changed, 93 insertions(+), 24 deletions(-) diff --git a/data/data-pipeline/data_pipeline/content/config/csv.yml b/data/data-pipeline/data_pipeline/content/config/csv.yml index 1d70cc7b..dccc8108 100644 --- a/data/data-pipeline/data_pipeline/content/config/csv.yml +++ b/data/data-pipeline/data_pipeline/content/config/csv.yml @@ -322,4 +322,16 @@ fields: format: percentage - score_name: Does the tract have at least 35 acres in it? label: Does the tract have at least 35 acres in it? + format: bool + - score_name: Is there at least one Formerly Used Defense Site (FUDS) in the tract? + label: Is there at least one Formerly Used Defense Site (FUDS) in the tract? + format: bool + - score_name: Is there at least one abandoned mine in this census tract? + label: Is there at least one abandoned mine in this census tract? + format: bool + - score_name: There is at least one abandoned mine in this census tract and the tract is low income. + label: There is at least one abandoned mine in this census tract and the tract is low income. + format: bool + - score_name: There is at least one Formerly Used Defense Site (FUDS) in the tract and the tract is low income. + label: There is at least one Formerly Used Defense Site (FUDS) in the tract and the tract is low income. format: bool \ No newline at end of file diff --git a/data/data-pipeline/data_pipeline/content/config/excel.yml b/data/data-pipeline/data_pipeline/content/config/excel.yml index 5ef93582..cdc1362b 100644 --- a/data/data-pipeline/data_pipeline/content/config/excel.yml +++ b/data/data-pipeline/data_pipeline/content/config/excel.yml @@ -326,4 +326,16 @@ sheets: format: percentage - score_name: Does the tract have at least 35 acres in it? label: Does the tract have at least 35 acres in it? + format: bool + - score_name: Is there at least one Formerly Used Defense Site (FUDS) in the tract? + label: Is there at least one Formerly Used Defense Site (FUDS) in the tract? + format: bool + - score_name: Is there at least one abandoned mine in this census tract? + label: Is there at least one abandoned mine in this census tract? + format: bool + - score_name: There is at least one abandoned mine in this census tract and the tract is low income. + label: There is at least one abandoned mine in this census tract and the tract is low income. + format: bool + - score_name: There is at least one Formerly Used Defense Site (FUDS) in the tract and the tract is low income. + label: There is at least one Formerly Used Defense Site (FUDS) in the tract and the tract is low income. format: bool \ No newline at end of file diff --git a/data/data-pipeline/data_pipeline/etl/runner.py b/data/data-pipeline/data_pipeline/etl/runner.py index 6d98b1ec..b4df63a9 100644 --- a/data/data-pipeline/data_pipeline/etl/runner.py +++ b/data/data-pipeline/data_pipeline/etl/runner.py @@ -93,21 +93,23 @@ def etl_runner(dataset_to_run: str = None) -> None: dataset for dataset in dataset_list if dataset["is_memory_intensive"] ] - logger.info("Running concurrent jobs") - with concurrent.futures.ThreadPoolExecutor() as executor: - futures = { - executor.submit(_run_one_dataset, dataset=dataset) - for dataset in concurrent_datasets - } + if concurrent_datasets: + logger.info("Running concurrent jobs") + with concurrent.futures.ThreadPoolExecutor() as executor: + futures = { + executor.submit(_run_one_dataset, dataset=dataset) + for dataset in concurrent_datasets + } - for fut in concurrent.futures.as_completed(futures): - # Calling result will raise an exception if one occurred. - # Otherwise, the exceptions are silently ignored. - fut.result() + for fut in concurrent.futures.as_completed(futures): + # Calling result will raise an exception if one occurred. + # Otherwise, the exceptions are silently ignored. + fut.result() - logger.info("Running high-memory jobs") - for dataset in high_memory_datasets: - _run_one_dataset(dataset=dataset) + if high_memory_datasets: + logger.info("Running high-memory jobs") + for dataset in high_memory_datasets: + _run_one_dataset(dataset=dataset) def score_generate() -> None: diff --git a/data/data-pipeline/data_pipeline/etl/score/constants.py b/data/data-pipeline/data_pipeline/etl/score/constants.py index 512c8822..081347cc 100644 --- a/data/data-pipeline/data_pipeline/etl/score/constants.py +++ b/data/data-pipeline/data_pipeline/etl/score/constants.py @@ -312,6 +312,8 @@ TILES_SCORE_COLUMNS = { field_names.TRACT_PERCENT_NON_NATURAL_FIELD_NAME + field_names.PERCENTILE_FIELD_SUFFIX: "IS_PFS", field_names.NON_NATURAL_LOW_INCOME_FIELD_NAME: "IS_ET", + field_names.AML_BOOLEAN: "AML_ET", + field_names.ELIGIBLE_FUDS_BINARY_FIELD_NAME: "FUDS_ET" ## FPL 200 and low higher ed for all others should no longer be M_EBSI, but rather ## FPL_200 (there is no higher ed in narwhal) } diff --git a/data/data-pipeline/data_pipeline/etl/score/etl_score.py b/data/data-pipeline/data_pipeline/etl/score/etl_score.py index 0d942d5c..4de0fd1e 100644 --- a/data/data-pipeline/data_pipeline/etl/score/etl_score.py +++ b/data/data-pipeline/data_pipeline/etl/score/etl_score.py @@ -14,6 +14,8 @@ from data_pipeline.etl.sources.dot_travel_composite.etl import ( from data_pipeline.etl.sources.fsf_flood_risk.etl import ( FloodRiskETL, ) +from data_pipeline.etl.sources.eamlis.etl import AbandonedMineETL +from data_pipeline.etl.sources.us_army_fuds.etl import USArmyFUDS from data_pipeline.etl.sources.nlcd_nature_deprived.etl import NatureDeprivedETL from data_pipeline.etl.sources.fsf_wildfire_risk.etl import WildfireRiskETL from data_pipeline.score.score_runner import ScoreRunner @@ -49,6 +51,8 @@ class ScoreETL(ExtractTransformLoad): self.fsf_flood_df: pd.DataFrame self.fsf_fire_df: pd.DataFrame self.nature_deprived_df: pd.DataFrame + self.eamlis_df: pd.DataFrame + self.fuds_df: pd.DataFrame def extract(self) -> None: logger.info("Loading data sets from disk.") @@ -139,6 +143,12 @@ class ScoreETL(ExtractTransformLoad): # Load NLCD Nature-Deprived Communities data self.nature_deprived_df = NatureDeprivedETL.get_data_frame() + # Load eAMLIS dataset + self.eamlis_df = AbandonedMineETL.get_data_frame() + + # Load FUDS dataset + self.fuds_df = USArmyFUDS.get_data_frame() + # Load GeoCorr Urban Rural Map geocorr_urban_rural_csv = ( constants.DATA_PATH / "dataset" / "geocorr" / "usa.csv" @@ -362,6 +372,8 @@ class ScoreETL(ExtractTransformLoad): self.fsf_flood_df, self.fsf_fire_df, self.nature_deprived_df, + self.eamlis_df, + self.fuds_df, ] # Sanity check each data frame before merging. @@ -457,6 +469,8 @@ class ScoreETL(ExtractTransformLoad): field_names.HISTORIC_REDLINING_SCORE_EXCEEDED, field_names.TRACT_ELIGIBLE_FOR_NONNATURAL_THRESHOLD, field_names.AGRICULTURAL_VALUE_BOOL_FIELD, + field_names.ELIGIBLE_FUDS_BINARY_FIELD_NAME, + field_names.AML_BOOLEAN, ] # For some columns, high values are "good", so we want to reverse the percentile diff --git a/data/data-pipeline/data_pipeline/etl/score/tests/sample_data/score_data_initial.csv b/data/data-pipeline/data_pipeline/etl/score/tests/sample_data/score_data_initial.csv index 9460fb26..050401d9 100644 --- a/data/data-pipeline/data_pipeline/etl/score/tests/sample_data/score_data_initial.csv +++ b/data/data-pipeline/data_pipeline/etl/score/tests/sample_data/score_data_initial.csv @@ -1,3 +1,3 @@ -GEOID10_TRACT,Persistent Poverty Census Tract,Tract-level redlining score meets or exceeds 3.25,Does the tract have at least 35 acres in it?,Contains agricultural value,Housing burden (percent),Share of homes with no kitchen or indoor plumbing (percent),Total population,Median household income (% of state median household income),Current asthma among adults aged greater than or equal to 18 years,Coronary heart disease among adults aged greater than or equal to 18 years,Cancer (excluding skin cancer) among adults aged greater than or equal to 18 years,Current lack of health insurance among adults aged 18-64 years,Diagnosed diabetes among adults aged greater than or equal to 18 years,Physical health not good for greater than or equal to 14 days among adults aged greater than or equal to 18 years,Percent of individuals < 100% Federal Poverty Line,Percent of individuals < 150% Federal Poverty Line,Percent of individuals below 200% Federal Poverty Line,Area Median Income (State or metropolitan),Median household income in the past 12 months,Energy burden,FEMA Risk Index Expected Annual Loss Score,Urban Heuristic Flag,Air toxics cancer risk,Respiratory hazard index,Diesel particulate matter exposure,PM2.5 in the air,Ozone,Traffic proximity and volume,Proximity to Risk Management Plan (RMP) facilities,Proximity to hazardous waste sites,Proximity to NPL sites,Wastewater discharge,Percent pre-1960s housing (lead paint indicator),Individuals under 5 years old,Individuals over 64 years old,Linguistic isolation (percent),Percent of households in linguistic isolation,Poverty (Less than 200% of federal poverty line),Percent individuals age 25 or over with less than high school degree,Unemployment (percent),Median value ($) of owner-occupied housing units,Percent enrollment in college or graduate school,Percent of population not currently enrolled in college or graduate school,Expected building loss rate (Natural Hazards Risk Index),Expected agricultural loss rate (Natural Hazards Risk Index),Expected population loss rate (Natural Hazards Risk Index),Percent individuals age 25 or over with less than high school degree in 2009,Percentage households below 100% of federal poverty line in 2009,Unemployment (percent) in 2009,Unemployment (percent) in 2010,Percent of individuals less than 100% Federal Poverty Line in 2010,Total population in 2009,Summer days above 90F,Percent low access to healthy food,Percent impenetrable surface areas,Leaky underground storage tanks,DOT Travel Barriers Score,Share of properties at risk of flood in 30 years,Share of properties at risk of fire in 30 years,Share of the tract's land area that is covered by impervious surface or cropland as a percent,"Percent of individuals below 200% Federal Poverty Line, imputed and adjusted",Third grade reading proficiency,Median household income as a percent of area median income,Life expectancy (years),Median household income as a percent of territory median income in 2009,Housing burden (percent) (percentile),Share of homes with no kitchen or indoor plumbing (percent) (percentile),Total population (percentile),Median household income (% of state median household income) (percentile),Current asthma among adults aged greater than or equal to 18 years (percentile),Coronary heart disease among adults aged greater than or equal to 18 years (percentile),Cancer (excluding skin cancer) among adults aged greater than or equal to 18 years (percentile),Current lack of health insurance among adults aged 18-64 years (percentile),Diagnosed diabetes among adults aged greater than or equal to 18 years (percentile),Physical health not good for greater than or equal to 14 days among adults aged greater than or equal to 18 years (percentile),Percent of individuals < 100% Federal Poverty Line (percentile),Percent of individuals < 150% Federal Poverty Line (percentile),Percent of individuals below 200% Federal Poverty Line (percentile),Area Median Income (State or metropolitan) (percentile),Median household income in the past 12 months (percentile),Energy burden (percentile),FEMA Risk Index Expected Annual Loss Score (percentile),Urban Heuristic Flag (percentile),Air toxics cancer risk (percentile),Respiratory hazard index (percentile),Diesel particulate matter exposure (percentile),PM2.5 in the air (percentile),Ozone (percentile),Traffic proximity and volume (percentile),Proximity to Risk Management Plan (RMP) facilities (percentile),Proximity to hazardous waste sites (percentile),Proximity to NPL sites (percentile),Wastewater discharge (percentile),Percent pre-1960s housing (lead paint indicator) (percentile),Individuals under 5 years old (percentile),Individuals over 64 years old (percentile),Linguistic isolation (percent) (percentile),Percent of households in linguistic isolation (percentile),Poverty (Less than 200% of federal poverty line) (percentile),Percent individuals age 25 or over with less than high school degree (percentile),Unemployment (percent) (percentile),Median value ($) of owner-occupied housing units (percentile),Percent enrollment in college or graduate school (percentile),Percent of population not currently enrolled in college or graduate school (percentile),Expected building loss rate (Natural Hazards Risk Index) (percentile),Expected agricultural loss rate (Natural Hazards Risk Index) (percentile),Expected population loss rate (Natural Hazards Risk Index) (percentile),Percent individuals age 25 or over with less than high school degree in 2009 (percentile),Percentage households below 100% of federal poverty line in 2009 (percentile),Unemployment (percent) in 2009 (percentile),Unemployment (percent) in 2010 (percentile),Percent of individuals less than 100% Federal Poverty Line in 2010 (percentile),Total population in 2009 (percentile),Summer days above 90F (percentile),Percent low access to healthy food (percentile),Percent impenetrable surface areas (percentile),Leaky underground storage tanks (percentile),DOT Travel Barriers Score (percentile),Share of properties at risk of flood in 30 years (percentile),Share of properties at risk of fire in 30 years (percentile),Share of the tract's land area that is covered by impervious surface or cropland as a percent (percentile),"Percent of individuals below 200% Federal Poverty Line, imputed and adjusted (percentile)",Low third grade reading proficiency (percentile),Low median household income as a percent of area median income (percentile),Low life expectancy (percentile),Low median household income as a percent of territory median income in 2009 (percentile),Total population in 2009 (island areas) and 2019 (states and PR),Total threshold criteria exceeded,Exceeds FPL200 threshold,Percent higher ed enrollment rate is less than 20%,Is low income and has a low percent of higher ed students?,Greater than or equal to the 90th percentile for expected population loss,Greater than or equal to the 90th percentile for expected agricultural loss,Greater than or equal to the 90th percentile for expected building loss,At least one climate threshold exceeded,"Greater than or equal to the 90th percentile for expected population loss rate, is low income, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for expected agriculture loss rate, is low income, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for expected building loss rate, is low income, and has a low percent of higher ed students?",Climate Factor (Definition M),Greater than or equal to the 90th percentile for energy burden,Greater than or equal to the 90th percentile for pm2.5 exposure,At least one energy threshold exceeded,"Greater than or equal to the 90th percentile for PM2.5 exposure, is low income, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for energy burden, is low income, and has a low percent of higher ed students?",Energy Factor (Definition M),Greater than or equal to the 90th percentile for diesel particulate matter,Greater than or equal to the 90th percentile for traffic proximity,At least one traffic threshold exceeded,"Greater than or equal to the 90th percentile for diesel particulate matter, is low income, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for traffic proximity, is low income, and has a low percent of higher ed students?",Transportation Factor (Definition M),Greater than or equal to the 90th percentile for lead paint and the median house value is less than 90th percentile,Greater than or equal to the 90th percentile for housing burden,At least one housing threshold exceeded,"Greater than or equal to the 90th percentile for lead paint, the median house value is less than 90th percentile, is low income, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for housing burden, is low income, and has a low percent of higher ed students?",Housing Factor (Definition M),Greater than or equal to the 90th percentile for RMP proximity,Greater than or equal to the 90th percentile for NPL (superfund sites) proximity,Greater than or equal to the 90th percentile for proximity to hazardous waste sites,At least one pollution threshold exceeded,"Greater than or equal to the 90th percentile for proximity to RMP sites, is low income, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for proximity to superfund sites, is low income, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for proximity to hazardous waste facilities, is low income, and has a low percent of higher ed students?",Pollution Factor (Definition M),Greater than or equal to the 90th percentile for wastewater discharge,At least one water threshold exceeded,"Greater than or equal to the 90th percentile for wastewater discharge, is low income, and has a low percent of higher ed students?",Water Factor (Definition M),Greater than or equal to the 90th percentile for diabetes,Greater than or equal to the 90th percentile for asthma,Greater than or equal to the 90th percentile for heart disease,Greater than or equal to the 90th percentile for low life expectancy,At least one health threshold exceeded,"Greater than or equal to the 90th percentile for diabetes, is low income, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for asthma, is low income, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for heart disease, is low income, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for low life expectancy, is low income, and has a low percent of higher ed students?",Health Factor (Definition M),Low high school education and low percent of higher ed students,Greater than or equal to the 90th percentile for unemployment,Greater than or equal to the 90th percentile for low median household income as a percent of area median income,Greater than or equal to the 90th percentile for households in linguistic isolation,Greater than or equal to the 90th percentile for households at or below 100% federal poverty level,"Greater than or equal to the 90th percentile for households in linguistic isolation, has low HS attainment, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for households at or below 100% federal poverty level, has low HS attainment, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for low median household income as a percent of area median income, has low HS attainment, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for unemployment, has low HS attainment, and has a low percent of higher ed students?",Unemployment (percent) in 2009 (island areas) and 2010 (states and PR),Unemployment (percent) in 2009 for island areas (percentile),Unemployment (percent) in 2009 exceeds 90th percentile,Percentage households below 100% of federal poverty line in 2009 (island areas) and 2010 (states and PR),Percentage households below 100% of federal poverty line in 2009 for island areas (percentile),Percentage households below 100% of federal poverty line in 2009 exceeds 90th percentile,Low median household income as a percent of territory median income in 2009 exceeds 90th percentile,Low high school education in 2009 (island areas),Greater than or equal to the 90th percentile for unemployment and has low HS education in 2009 (island areas)?,Greater than or equal to the 90th percentile for households at or below 100% federal poverty level and has low HS education in 2009 (island areas)?,Greater than or equal to the 90th percentile for low median household income as a percent of area median income and has low HS education in 2009 (island areas)?,At least one workforce threshold exceeded,Both workforce socioeconomic indicators exceeded,Workforce Factor (Definition M),Total categories exceeded,Definition M (communities),Any Non-Workforce Factor (Definition M),Definition M (percentile),Is low income (imputed and adjusted)?,Greater than or equal to the 90th percentile for share of properties at risk of flood in 30 years,Greater than or equal to the 90th percentile for share of properties at risk of fire in 30 years,Greater than or equal to the 90th percentile for expected population loss rate and is low income?,Greater than or equal to the 90th percentile for expected agriculture loss rate and is low income?,Greater than or equal to the 90th percentile for expected building loss rate and is low income?,Greater than or equal to the 90th percentile for share of properties at risk of flood in 30 years and is low income?,Greater than or equal to the 90th percentile for share of properties at risk of fire in 30 years and is low income?,Climate Factor (Definition N),Greater than or equal to the 90th percentile for PM2.5 exposure and is low income?,Greater than or equal to the 90th percentile for energy burden and is low income?,Energy Factor (Definition N),Greater than or equal to the 90th percentile for DOT travel barriers,Greater than or equal to the 90th percentile for diesel particulate matter and is low income?,Greater than or equal to the 90th percentile for traffic proximity and is low income?,Greater than or equal to the 90th percentile for DOT transit barriers and is low income?,Transportation Factor (Definition N),Tract-level redlining score meets or exceeds 3.25 and is low income,Greater than or equal to the 90th percentile for share of homes without indoor plumbing or a kitchen,Greater than or equal to the 90th percentile for share of homes with no kitchen or indoor plumbing and is low income?,Greater than or equal to the 90th percentile for lead paint and the median house value is less than 90th percentile and is low income?,Greater than or equal to the 90th percentile for housing burden and is low income?,Greater than or equal to the 90th percentile for share of the tract's land area that is covered by impervious surface or cropland as a percent,Greater than or equal to the 90th percentile for share of the tract's land area that is covered by impervious surface or cropland as a percent and is low income?,Housing Factor (Definition N),Greater than or equal to the 90th percentile for proximity to RMP sites and is low income?,Greater than or equal to the 90th percentile for proximity to superfund sites and is low income?,Greater than or equal to the 90th percentile for proximity to hazardous waste facilities and is low income?,Pollution Factor (Definition N),Greater than or equal to the 90th percentile for leaky underwater storage tanks,Greater than or equal to the 90th percentile for wastewater discharge and is low income?,Greater than or equal to the 90th percentile for leaky underground storage tanks and is low income?,Water Factor (Definition N),Greater than or equal to the 90th percentile for diabetes and is low income?,Greater than or equal to the 90th percentile for asthma and is low income?,Greater than or equal to the 90th percentile for heart disease and is low income?,Greater than or equal to the 90th percentile for low life expectancy and is low income?,Health Factor (Definition N),Low high school education,Greater than or equal to the 90th percentile for households in linguistic isolation and has low HS education?,Greater than or equal to the 90th percentile for households at or below 100% federal poverty level and has low HS education?,Greater than or equal to the 90th percentile for low median household income as a percent of area median income and has low HS education?,Greater than or equal to the 90th percentile for unemployment and has low HS education?,Workforce Factor (Definition N),Definition N (communities),Definition N (communities) (percentile),Meets the less stringent low income criterion for the adjacency index?,Definition N (communities) (average of neighbors),Is the tract surrounded by disadvantaged communities?,Definition N (communities) (including adjacency index) -01073001100,True,True,True,True,0.2752043596730245,0.0,4781.0,0.7327449738800064,11.2,7.2,6.7,16.6,19.3,15.1,0.150375939849624,0.318796992481203,0.3744360902255639,57447.0,37030.0,0.049,18.7674524286,1.0,40.0,0.5,0.467489734286576,9.8735797260274,43.056760130719,181.621925132718,2.0427358988323,0.702342755246247,0.134193041307899,4.45238981883771,0.168806466951973,0.035557414766785,0.203932231750679,0.0,0.0,0.374436090225563,0.0821917808219178,0.0092071611253196,85500.0,0.0890751899397432,0.9109248100602568,0.0004047858,5.6328e-05,2.8039e-06,,,,0.1536983669548511,0.3189099613330878,,62.666668,0.068036923,0.171,1.96440511031451,47.695227725,0.0754274220583305,0.6620851491786792,-77.7525,0.2853609002858206,58.143433,0.6445941476491375,70.3,,0.6466760729305078,0.2159833426939357,0.6290185267766651,0.2601978513507951,0.8509696039125366,0.7264920810941454,0.4789587420739856,0.6191105803406409,0.965388552418323,0.697012994398476,0.6204255784694491,0.7319894972922707,0.6305043487774192,0.3145069836211475,0.1524256393370651,0.864954517474865,0.6038301323911519,0.5972204988211937,0.9070825388177608,0.8818509942794879,0.8407790792699537,0.8257128232087766,0.5755156814188676,0.3920895082932574,0.9007580978635424,0.4820205132363076,0.7531654977635437,0.9619599422457518,0.3979135417088958,0.1737408953933055,0.7659355954649262,0.1287706711725437,0.13169416629505,0.6347481790786611,0.4189065592792301,0.029797296373751,0.1130218397675614,0.7459773722926589,0.2540362752992234,0.7846412062513758,0.2153147384849333,0.6143028498159407,,,,0.9349594607528132,0.8950599559730369,,0.7537922665342821,0.8019598155467721,0.4126953421856217,0.521114579532709,0.4517484245644384,0.4977059209088922,0.8410893082809093,0.2685589820648203,0.607629501459933,0.990724418702258,0.8218135517196475,0.97046998263836,,4781.0,0,False,True,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,True,False,False,True,False,False,False,False,True,False,False,False,True,False,False,True,True,False,False,False,False,False,False,False,False,False,False,False,False,False,False,0.1536983669548511,,False,0.3189099613330878,,False,False,False,False,False,False,False,False,False,0.0,False,False,0,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,0,True,0.8571428571428571,False,False -01073001400,True,True,True,True,0.1823529411764705,0.0047058823529411,1946.0,0.7136694633528574,11.1,9.1,7.3,21.4,22.4,17.4,0.2816032887975334,0.3679342240493319,0.4835560123329907,57447.0,36066.0,0.07,17.3011023381,1.0,40.0,0.6,0.655319095139786,9.945103013698628,43.1266823529412,3260.33374354854,1.81915896353987,3.34035680534013,0.214095348702766,0.103297800913177,0.647212543554006,0.054984583761562,0.189105858170606,0.0245098039215686,0.024509803921569,0.48355601233299,0.1742543171114599,0.1150121065375302,67800.0,0.0771549125979505,0.9228450874020494,0.0008951111,5.1282e-06,2.3791e-06,,,,0.0804953560371517,0.2950894905920146,,61.666668,0.087159691,0.34900002,3.16184976454882,44.7571359825,0.2384615384615384,0.0,-56.8746,0.4064010997350401,93.77919,0.6278134628440127,71.0,,0.3421186011150532,0.5051574635963891,0.0916001135119795,0.240302951305517,0.8385794307486707,0.9217563763541756,0.6048579715089994,0.7894025988796952,0.9878088657624612,0.8447283118655634,0.8689486351950112,0.8013648049887862,0.7892483999781194,0.3145069836211475,0.1404620788058391,0.970802270706518,0.5282998116553705,0.5972204988211937,0.9070825388177608,0.9704848815036776,0.9380686461454644,0.8391046304110233,0.5827649654828936,0.9563394697362702,0.8799745949379062,0.800259455953298,0.8653801975648978,0.8431750027766466,0.8462723476709774,0.471128768530155,0.6930041485925866,0.5867081244286861,0.5847015580870529,0.7916514641694031,0.7516347007030237,0.9067399297439892,0.0522639122516786,0.6434566620719774,0.356556985519905,0.9166162227602904,0.0865380767537716,0.558933421571466,,,,0.6917513228236646,0.8737301229199994,,0.7501654807214959,0.8647617479139218,0.6268497920495212,0.6418426778016514,0.3716517703914219,0.8849410093948001,0.3366245885930925,0.5569693544162451,0.7883908294582027,0.9537899773356836,0.8364273002184828,0.959938777375042,,1946.0,9,True,True,True,False,False,True,True,False,False,True,True,True,False,True,False,True,True,True,True,True,True,True,True,False,False,True,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,True,False,True,True,True,True,False,True,True,True,True,True,False,False,False,False,False,False,True,0.0804953560371517,,False,0.2950894905920146,,False,False,False,False,False,False,True,True,True,6.0,True,True,1,True,False,False,False,False,True,False,False,True,False,True,True,False,True,True,False,True,True,False,False,False,False,False,False,True,False,False,False,False,False,False,False,False,True,False,True,True,True,True,False,False,False,True,True,True,1,True,1.0,True,True +GEOID10_TRACT,Persistent Poverty Census Tract,Tract-level redlining score meets or exceeds 3.25,Does the tract have at least 35 acres in it?,Contains agricultural value,Is there at least one Formerly Used Defense Site (FUDS) in the tract?,Is there at least one abandoned mine in this census tract?,Housing burden (percent),Share of homes with no kitchen or indoor plumbing (percent),Total population,Median household income (% of state median household income),Current asthma among adults aged greater than or equal to 18 years,Coronary heart disease among adults aged greater than or equal to 18 years,Cancer (excluding skin cancer) among adults aged greater than or equal to 18 years,Current lack of health insurance among adults aged 18-64 years,Diagnosed diabetes among adults aged greater than or equal to 18 years,Physical health not good for greater than or equal to 14 days among adults aged greater than or equal to 18 years,Percent of individuals < 100% Federal Poverty Line,Percent of individuals < 150% Federal Poverty Line,Percent of individuals below 200% Federal Poverty Line,Area Median Income (State or metropolitan),Median household income in the past 12 months,Energy burden,FEMA Risk Index Expected Annual Loss Score,Urban Heuristic Flag,Air toxics cancer risk,Respiratory hazard index,Diesel particulate matter exposure,PM2.5 in the air,Ozone,Traffic proximity and volume,Proximity to Risk Management Plan (RMP) facilities,Proximity to hazardous waste sites,Proximity to NPL sites,Wastewater discharge,Percent pre-1960s housing (lead paint indicator),Individuals under 5 years old,Individuals over 64 years old,Linguistic isolation (percent),Percent of households in linguistic isolation,Poverty (Less than 200% of federal poverty line),Percent individuals age 25 or over with less than high school degree,Unemployment (percent),Median value ($) of owner-occupied housing units,Percent enrollment in college or graduate school,Percent of population not currently enrolled in college or graduate school,Expected building loss rate (Natural Hazards Risk Index),Expected agricultural loss rate (Natural Hazards Risk Index),Expected population loss rate (Natural Hazards Risk Index),Percent individuals age 25 or over with less than high school degree in 2009,Percentage households below 100% of federal poverty line in 2009,Unemployment (percent) in 2009,Unemployment (percent) in 2010,Percent of individuals less than 100% Federal Poverty Line in 2010,Total population in 2009,Summer days above 90F,Percent low access to healthy food,Percent impenetrable surface areas,Leaky underground storage tanks,DOT Travel Barriers Score,Share of properties at risk of flood in 30 years,Share of properties at risk of fire in 30 years,Share of the tract's land area that is covered by impervious surface or cropland as a percent,"Percent of individuals below 200% Federal Poverty Line, imputed and adjusted",Third grade reading proficiency,Median household income as a percent of area median income,Life expectancy (years),Median household income as a percent of territory median income in 2009,Housing burden (percent) (percentile),Share of homes with no kitchen or indoor plumbing (percent) (percentile),Total population (percentile),Median household income (% of state median household income) (percentile),Current asthma among adults aged greater than or equal to 18 years (percentile),Coronary heart disease among adults aged greater than or equal to 18 years (percentile),Cancer (excluding skin cancer) among adults aged greater than or equal to 18 years (percentile),Current lack of health insurance among adults aged 18-64 years (percentile),Diagnosed diabetes among adults aged greater than or equal to 18 years (percentile),Physical health not good for greater than or equal to 14 days among adults aged greater than or equal to 18 years (percentile),Percent of individuals < 100% Federal Poverty Line (percentile),Percent of individuals < 150% Federal Poverty Line (percentile),Percent of individuals below 200% Federal Poverty Line (percentile),Area Median Income (State or metropolitan) (percentile),Median household income in the past 12 months (percentile),Energy burden (percentile),FEMA Risk Index Expected Annual Loss Score (percentile),Urban Heuristic Flag (percentile),Air toxics cancer risk (percentile),Respiratory hazard index (percentile),Diesel particulate matter exposure (percentile),PM2.5 in the air (percentile),Ozone (percentile),Traffic proximity and volume (percentile),Proximity to Risk Management Plan (RMP) facilities (percentile),Proximity to hazardous waste sites (percentile),Proximity to NPL sites (percentile),Wastewater discharge (percentile),Percent pre-1960s housing (lead paint indicator) (percentile),Individuals under 5 years old (percentile),Individuals over 64 years old (percentile),Linguistic isolation (percent) (percentile),Percent of households in linguistic isolation (percentile),Poverty (Less than 200% of federal poverty line) (percentile),Percent individuals age 25 or over with less than high school degree (percentile),Unemployment (percent) (percentile),Median value ($) of owner-occupied housing units (percentile),Percent enrollment in college or graduate school (percentile),Percent of population not currently enrolled in college or graduate school (percentile),Expected building loss rate (Natural Hazards Risk Index) (percentile),Expected agricultural loss rate (Natural Hazards Risk Index) (percentile),Expected population loss rate (Natural Hazards Risk Index) (percentile),Percent individuals age 25 or over with less than high school degree in 2009 (percentile),Percentage households below 100% of federal poverty line in 2009 (percentile),Unemployment (percent) in 2009 (percentile),Unemployment (percent) in 2010 (percentile),Percent of individuals less than 100% Federal Poverty Line in 2010 (percentile),Total population in 2009 (percentile),Summer days above 90F (percentile),Percent low access to healthy food (percentile),Percent impenetrable surface areas (percentile),Leaky underground storage tanks (percentile),DOT Travel Barriers Score (percentile),Share of properties at risk of flood in 30 years (percentile),Share of properties at risk of fire in 30 years (percentile),Share of the tract's land area that is covered by impervious surface or cropland as a percent (percentile),"Percent of individuals below 200% Federal Poverty Line, imputed and adjusted (percentile)",Low third grade reading proficiency (percentile),Low median household income as a percent of area median income (percentile),Low life expectancy (percentile),Low median household income as a percent of territory median income in 2009 (percentile),Total population in 2009 (island areas) and 2019 (states and PR),Total threshold criteria exceeded,Exceeds FPL200 threshold,Percent higher ed enrollment rate is less than 20%,Is low income and has a low percent of higher ed students?,Greater than or equal to the 90th percentile for expected population loss,Greater than or equal to the 90th percentile for expected agricultural loss,Greater than or equal to the 90th percentile for expected building loss,At least one climate threshold exceeded,"Greater than or equal to the 90th percentile for expected population loss rate, is low income, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for expected agriculture loss rate, is low income, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for expected building loss rate, is low income, and has a low percent of higher ed students?",Climate Factor (Definition M),Greater than or equal to the 90th percentile for energy burden,Greater than or equal to the 90th percentile for pm2.5 exposure,At least one energy threshold exceeded,"Greater than or equal to the 90th percentile for PM2.5 exposure, is low income, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for energy burden, is low income, and has a low percent of higher ed students?",Energy Factor (Definition M),Greater than or equal to the 90th percentile for diesel particulate matter,Greater than or equal to the 90th percentile for traffic proximity,At least one traffic threshold exceeded,"Greater than or equal to the 90th percentile for diesel particulate matter, is low income, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for traffic proximity, is low income, and has a low percent of higher ed students?",Transportation Factor (Definition M),Greater than or equal to the 90th percentile for lead paint and the median house value is less than 90th percentile,Greater than or equal to the 90th percentile for housing burden,At least one housing threshold exceeded,"Greater than or equal to the 90th percentile for lead paint, the median house value is less than 90th percentile, is low income, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for housing burden, is low income, and has a low percent of higher ed students?",Housing Factor (Definition M),Greater than or equal to the 90th percentile for RMP proximity,Greater than or equal to the 90th percentile for NPL (superfund sites) proximity,Greater than or equal to the 90th percentile for proximity to hazardous waste sites,At least one pollution threshold exceeded,"Greater than or equal to the 90th percentile for proximity to RMP sites, is low income, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for proximity to superfund sites, is low income, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for proximity to hazardous waste facilities, is low income, and has a low percent of higher ed students?",Pollution Factor (Definition M),Greater than or equal to the 90th percentile for wastewater discharge,At least one water threshold exceeded,"Greater than or equal to the 90th percentile for wastewater discharge, is low income, and has a low percent of higher ed students?",Water Factor (Definition M),Greater than or equal to the 90th percentile for diabetes,Greater than or equal to the 90th percentile for asthma,Greater than or equal to the 90th percentile for heart disease,Greater than or equal to the 90th percentile for low life expectancy,At least one health threshold exceeded,"Greater than or equal to the 90th percentile for diabetes, is low income, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for asthma, is low income, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for heart disease, is low income, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for low life expectancy, is low income, and has a low percent of higher ed students?",Health Factor (Definition M),Low high school education and low percent of higher ed students,Greater than or equal to the 90th percentile for unemployment,Greater than or equal to the 90th percentile for low median household income as a percent of area median income,Greater than or equal to the 90th percentile for households in linguistic isolation,Greater than or equal to the 90th percentile for households at or below 100% federal poverty level,"Greater than or equal to the 90th percentile for households in linguistic isolation, has low HS attainment, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for households at or below 100% federal poverty level, has low HS attainment, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for low median household income as a percent of area median income, has low HS attainment, and has a low percent of higher ed students?","Greater than or equal to the 90th percentile for unemployment, has low HS attainment, and has a low percent of higher ed students?",Unemployment (percent) in 2009 (island areas) and 2010 (states and PR),Unemployment (percent) in 2009 for island areas (percentile),Unemployment (percent) in 2009 exceeds 90th percentile,Percentage households below 100% of federal poverty line in 2009 (island areas) and 2010 (states and PR),Percentage households below 100% of federal poverty line in 2009 for island areas (percentile),Percentage households below 100% of federal poverty line in 2009 exceeds 90th percentile,Low median household income as a percent of territory median income in 2009 exceeds 90th percentile,Low high school education in 2009 (island areas),Greater than or equal to the 90th percentile for unemployment and has low HS education in 2009 (island areas)?,Greater than or equal to the 90th percentile for households at or below 100% federal poverty level and has low HS education in 2009 (island areas)?,Greater than or equal to the 90th percentile for low median household income as a percent of area median income and has low HS education in 2009 (island areas)?,At least one workforce threshold exceeded,Both workforce socioeconomic indicators exceeded,Workforce Factor (Definition M),Total categories exceeded,Definition M (communities),Any Non-Workforce Factor (Definition M),Definition M (percentile),Is low income (imputed and adjusted)?,Greater than or equal to the 90th percentile for share of properties at risk of flood in 30 years,Greater than or equal to the 90th percentile for share of properties at risk of fire in 30 years,Greater than or equal to the 90th percentile for expected population loss rate and is low income?,Greater than or equal to the 90th percentile for expected agriculture loss rate and is low income?,Greater than or equal to the 90th percentile for expected building loss rate and is low income?,Greater than or equal to the 90th percentile for share of properties at risk of flood in 30 years and is low income?,Greater than or equal to the 90th percentile for share of properties at risk of fire in 30 years and is low income?,Climate Factor (Definition N),Greater than or equal to the 90th percentile for PM2.5 exposure and is low income?,Greater than or equal to the 90th percentile for energy burden and is low income?,Energy Factor (Definition N),Greater than or equal to the 90th percentile for DOT travel barriers,Greater than or equal to the 90th percentile for diesel particulate matter and is low income?,Greater than or equal to the 90th percentile for traffic proximity and is low income?,Greater than or equal to the 90th percentile for DOT transit barriers and is low income?,Transportation Factor (Definition N),Tract-level redlining score meets or exceeds 3.25 and is low income,Greater than or equal to the 90th percentile for share of homes without indoor plumbing or a kitchen,Greater than or equal to the 90th percentile for share of homes with no kitchen or indoor plumbing and is low income?,Greater than or equal to the 90th percentile for lead paint and the median house value is less than 90th percentile and is low income?,Greater than or equal to the 90th percentile for housing burden and is low income?,Greater than or equal to the 90th percentile for share of the tract's land area that is covered by impervious surface or cropland as a percent,Greater than or equal to the 90th percentile for share of the tract's land area that is covered by impervious surface or cropland as a percent and is low income?,Housing Factor (Definition N),Greater than or equal to the 90th percentile for proximity to RMP sites and is low income?,Greater than or equal to the 90th percentile for proximity to superfund sites and is low income?,Greater than or equal to the 90th percentile for proximity to hazardous waste facilities and is low income?,There is at least one abandoned mine in this census tract and the tract is low income.,There is at least one Formerly Used Defense Site (FUDS) in the tract and the tract is low income.,Pollution Factor (Definition N),Greater than or equal to the 90th percentile for leaky underwater storage tanks,Greater than or equal to the 90th percentile for wastewater discharge and is low income?,Greater than or equal to the 90th percentile for leaky underground storage tanks and is low income?,Water Factor (Definition N),Greater than or equal to the 90th percentile for diabetes and is low income?,Greater than or equal to the 90th percentile for asthma and is low income?,Greater than or equal to the 90th percentile for heart disease and is low income?,Greater than or equal to the 90th percentile for low life expectancy and is low income?,Health Factor (Definition N),Low high school education,Greater than or equal to the 90th percentile for households in linguistic isolation and has low HS education?,Greater than or equal to the 90th percentile for households at or below 100% federal poverty level and has low HS education?,Greater than or equal to the 90th percentile for low median household income as a percent of area median income and has low HS education?,Greater than or equal to the 90th percentile for unemployment and has low HS education?,Workforce Factor (Definition N),Definition N (communities),Definition N (communities) (percentile),Meets the less stringent low income criterion for the adjacency index?,Definition N (communities) (average of neighbors),Is the tract surrounded by disadvantaged communities?,Definition N (communities) (including adjacency index) +01073001100,True,True,True,True,,,0.2752043596730245,0.0,4781.0,0.7327449738800064,11.2,7.2,6.7,16.6,19.3,15.1,0.150375939849624,0.318796992481203,0.3744360902255639,57447.0,37030.0,0.049,18.7674524286,1.0,40.0,0.5,0.467489734286576,9.8735797260274,43.056760130719,181.621925132718,2.0427358988323,0.702342755246247,0.134193041307899,4.45238981883771,0.168806466951973,0.035557414766785,0.203932231750679,0.0,0.0,0.374436090225563,0.0821917808219178,0.0092071611253196,85500.0,0.0890751899397432,0.9109248100602568,0.0004047858,5.6328e-05,2.8039e-06,,,,0.1536983669548511,0.3189099613330878,,62.666668,0.068036923,0.171,1.96440511031451,47.695227725,0.0754274220583305,0.6620851491786792,-77.7525,0.2853609002858206,58.143433,0.6445941476491375,70.3,,0.6466760729305078,0.2159833426939357,0.6290185267766651,0.2601978513507951,0.8509696039125366,0.7264920810941454,0.4789587420739856,0.6191105803406409,0.965388552418323,0.697012994398476,0.6204255784694491,0.7319894972922707,0.6305043487774192,0.3145069836211475,0.1524256393370651,0.864954517474865,0.6038301323911519,0.5972204988211937,0.9070825388177608,0.8818509942794879,0.8407790792699537,0.8257128232087766,0.5755156814188676,0.3920895082932574,0.9007580978635424,0.4820205132363076,0.7531654977635437,0.9619599422457518,0.3979135417088958,0.1737408953933055,0.7659355954649262,0.1287706711725437,0.13169416629505,0.6347481790786611,0.4189065592792301,0.029797296373751,0.1130218397675614,0.7459773722926589,0.2540362752992234,0.7846412062513758,0.2153147384849333,0.6143028498159407,,,,0.9349594607528132,0.8950599559730369,,0.7537922665342821,0.8019598155467721,0.4126953421856217,0.521114579532709,0.4517484245644384,0.4973964722881056,0.8410893082809093,0.2685589820648203,0.607629501459933,0.990724418702258,0.8218135517196475,0.97046998263836,,4781.0,0,False,True,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,True,False,False,True,False,False,False,False,True,False,False,False,True,False,False,True,True,False,False,False,False,False,False,False,False,False,False,False,False,False,False,0.1536983669548511,,False,0.3189099613330878,,False,False,False,False,False,False,False,False,False,0.0,False,False,0,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,0,True,0.8571428571428571,False,False +01073001400,True,True,True,True,,,0.1823529411764705,0.0047058823529411,1946.0,0.7136694633528574,11.1,9.1,7.3,21.4,22.4,17.4,0.2816032887975334,0.3679342240493319,0.4835560123329907,57447.0,36066.0,0.07,17.3011023381,1.0,40.0,0.6,0.655319095139786,9.945103013698628,43.1266823529412,3260.33374354854,1.81915896353987,3.34035680534013,0.214095348702766,0.103297800913177,0.647212543554006,0.054984583761562,0.189105858170606,0.0245098039215686,0.024509803921569,0.48355601233299,0.1742543171114599,0.1150121065375302,67800.0,0.0771549125979505,0.9228450874020494,0.0008951111,5.1282e-06,2.3791e-06,,,,0.0804953560371517,0.2950894905920146,,61.666668,0.087159691,0.34900002,3.16184976454882,44.7571359825,0.2384615384615384,0.0,-56.8746,0.4064010997350401,93.77919,0.6278134628440127,71.0,,0.3421186011150532,0.5051574635963891,0.0916001135119795,0.240302951305517,0.8385794307486707,0.9217563763541756,0.6048579715089994,0.7894025988796952,0.9878088657624612,0.8447283118655634,0.8689486351950112,0.8013648049887862,0.7892483999781194,0.3145069836211475,0.1404620788058391,0.970802270706518,0.5282998116553705,0.5972204988211937,0.9070825388177608,0.9704848815036776,0.9380686461454644,0.8391046304110233,0.5827649654828936,0.9563394697362702,0.8799745949379062,0.800259455953298,0.8653801975648978,0.8431750027766466,0.8462723476709774,0.471128768530155,0.6930041485925866,0.5867081244286861,0.5847015580870529,0.7916514641694031,0.7516347007030237,0.9067399297439892,0.0522639122516786,0.6434566620719774,0.356556985519905,0.9166162227602904,0.0865380767537716,0.558933421571466,,,,0.6917513228236646,0.8737301229199994,,0.7501654807214959,0.8647617479139218,0.6268497920495212,0.6418426778016514,0.3716517703914219,0.8850358496224203,0.3366245885930925,0.5569693544162451,0.7883908294582027,0.9537899773356836,0.8364273002184828,0.959938777375042,,1946.0,9,True,True,True,False,False,True,True,False,False,True,True,True,False,True,False,True,True,True,True,True,True,True,True,False,False,True,False,False,False,False,False,False,False,False,False,False,False,False,False,False,False,True,False,True,True,True,True,False,True,True,True,True,True,False,False,False,False,False,False,True,0.0804953560371517,,False,0.2950894905920146,,False,False,False,False,False,False,True,True,True,6.0,True,True,1,True,False,False,False,False,True,False,False,True,False,True,True,False,True,True,False,True,True,False,False,False,False,False,False,True,False,False,False,False,False,False,False,False,False,False,True,False,True,True,True,True,False,False,False,True,True,True,1,True,1.0,True,True diff --git a/data/data-pipeline/data_pipeline/etl/score/tests/snapshots/downloadable_data_expected.pkl b/data/data-pipeline/data_pipeline/etl/score/tests/snapshots/downloadable_data_expected.pkl index d1f7b1f07f8069c1b5f4bb2ab125c8d22e1f8e74..3631bea34e74f500b7eaf3cc99ee98382c0d3448 100644 GIT binary patch delta 621 zcmaFbz}VWt$lAa%^_SyD);>@0ajVVgQ0EB~y|zL^8y^8Cs`gNVZQ2 znxf&&=&b?dD0VtIY}S-CX5`EPDFlMt$)QrJjLeg(rL+9N9Y4$$hn6rh1A3b~m;W5Jp-ixrZA#+3psu7~Ol z3jsR;D1+h(0=hw(6@ca=9HIa;At%2aXisu}ZmQmtoN zxv5k9O51?RAd7)z@(g=p78YRCOuon=Dwp*H7!#e&0?-&@V1zP25t~&xnaLp;0OeZ1 AY5)KL delta 194 zcmZo|VSL)a$lAa%HOgTlYo7$8+TV^sqbTBqk;1CQiwExA~g1 zDih W0GiV247ZOFYA?vXtis8Q9Fqa%A2wD1 diff --git a/data/data-pipeline/data_pipeline/etl/score/tests/snapshots/score_data_expected.pkl b/data/data-pipeline/data_pipeline/etl/score/tests/snapshots/score_data_expected.pkl index 1cb39981f9200e7da668b4a11fef97b3ead5be33..aef5fc0cde0f78bd2f4605463e355b8ea404b79a 100644 GIT binary patch delta 710 zcmcb+gYofhM%D(FsW)ObvIa6u7GxHgoW6rJ zc4o;2D7O(x?}yR{CNE$U=Q<1JF@bHL%q^NB$O#o{g3=cz7jWoK-Y9C!!Uhbu$uC4x z7`Z0$w)0qRY)vR$Vp8sE>XzOOI2{oFUn0V%BfTcEly2Qa7j%|%_~k- z2+k}?RnTw?bqUr~$jk%jQz$7)OfIpX(qo0)oW!KWycD2;DGIrnKx4t0GK&?GfyR{r zEiPgK>E6sCZeUj*76Nt#P!`1{giHV$pa8T3;TQ#=2|4-YK)aIjb5r%E^dw?87|n|| d1pJ8ClF1de3X?yCvuutEozKR2YVxn>WB~K1#~c6v delta 348 zcmaF7oAK@rM%D(FsX;LtSp%6^7#V$;CPy(vvoJIIvH%(Glb8i3hcSsvR%I4steI@i zti||aauW0H$&M_>Kz=EU7UP4-3s{sn8yO&=Y4aYI>x_c?q1;1I`tal>Z1$38puDqC z`aG1ru=x*LJR|2{DEI&56Qa6|4U;!=ygwm&>^go8l7e!Sj z`-^5su|tI#p!7K?{RgBZoP~+emu<3+SPCQCzOYw z3hrfqfPGN<;N%Ic_L8TeyfaYx9F#u4`2}k{qv0PY_b-(G2c`c*X+}l}gBeP*Opahz zWo(*U$F9Yqz`?*U*@jDD^BQ&mc0RjD>C6#V@7tgC+q>B;X!0q(A1Y0)Q!+d|odj4I z7+9g^u|a8eD9y3?8UJ=>$p$F55lZie(g!9tu!?h@h4Pp{mQQ{y9KqQH6}d1ufL(WT zrHCRkr#IK+xgrTHtc<>FlNm)*7}+MLiSDg;^($w)0qRY)vR$Vp8sE>XzOOI2{o zFUn0V%BfTcEly2Qa7j%|%_~k-2+k}?RnTw?bqUr~$jk%jQz$7)OfIpX(qo0)oW!KW zycD2;DGIrnKx4t0GK&?GfyR{rEiPgK>E5g;W?)wz76Nt#P!`1{giHV$pa8T3;TQ#= x2|4-YK)aIjb5r%E^dw?87|n||1pJ8ClF1Wo6eceSW!YRDqRqy*aPs`9dH_F%y>;mk3O+umXGjH9uw_JPtTz=r>e|$ew8d|4hcy>B5urM&NLiMsiX`nVR;M^=F zu$@_JFO<6vN*{pI2ch(7DE*INaxS~dWPOncp$4eXIVk-HBDGgUk(u3_WAa0h1Qtd{ qU#7{fqA83_lUIrE-TX#O&u(&zt=!}Z0W6z;hHA4h&Yi3pQx5>O^-E*` diff --git a/data/data-pipeline/data_pipeline/etl/score/tests/snapshots/tile_data_expected.pkl b/data/data-pipeline/data_pipeline/etl/score/tests/snapshots/tile_data_expected.pkl index bc372b5773f44060e88dc0255fb5772441df56a8..559fdcf2bfa1157070a65ea50b86efafd58952ec 100644 GIT binary patch delta 133 zcmcbrI75lGfn_SM;6~PMtc+}v_poX)CQN?L>Y%^?20!X?(UTuAiE*&CPRa1>bT*jm z%BH|rGx-mj?&M~+2FCiyacruaHQDzvGuBOh&XvK~usMLcnuW*F*C*aJWJ(XaTd2$A OBm8R_1tu2>Bm)3%X(n#~ delta 79 zcmV-V0I>g= self.ENVIRONMENTAL_BURDEN_THRESHOLD ) - self.df[field_names.POLLUTION_THRESHOLD_EXCEEDED] = ( - self.df[field_names.RMP_PCTILE_THRESHOLD] - | self.df[field_names.NPL_PCTILE_THRESHOLD] - ) | self.df[field_names.TSDF_PCTILE_THRESHOLD] + self.df[field_names.POLLUTION_THRESHOLD_EXCEEDED] = self.df[ + [ + field_names.RMP_PCTILE_THRESHOLD, + field_names.NPL_PCTILE_THRESHOLD, + field_names.TSDF_PCTILE_THRESHOLD, + field_names.AML_BOOLEAN, + field_names.ELIGIBLE_FUDS_BINARY_FIELD_NAME, + ] + ].any(axis="columns") # individual series-by-series self.df[field_names.RMP_LOW_INCOME_FIELD] = ( @@ -502,6 +509,16 @@ class ScoreNarwhal(Score): & self.df[field_names.FPL_200_SERIES_IMPUTED_AND_ADJUSTED] ) + self.df[field_names.AML_LOW_INCOME_FIELD] = ( + self.df[field_names.AML_BOOLEAN] + & self.df[field_names.FPL_200_SERIES_IMPUTED_AND_ADJUSTED] + ) + + self.df[field_names.ELIGIBLE_FUDS_LOW_INCOME_FIELD] = ( + self.df[field_names.ELIGIBLE_FUDS_BINARY_FIELD_NAME] + & self.df[field_names.FPL_200_SERIES_IMPUTED_AND_ADJUSTED] + ) + self._increment_total_eligibility_exceeded( pollution_eligibility_columns, skip_fips=constants.DROP_FIPS_FROM_NON_WTD_THRESHOLDS, diff --git a/data/data-pipeline/data_pipeline/tests/sources/eamlis/test_etl.py b/data/data-pipeline/data_pipeline/tests/sources/eamlis/test_etl.py index e4c7d8ac..2f85b55e 100644 --- a/data/data-pipeline/data_pipeline/tests/sources/eamlis/test_etl.py +++ b/data/data-pipeline/data_pipeline/tests/sources/eamlis/test_etl.py @@ -61,9 +61,9 @@ class TestAbandondedLandMineETL(TestETL): super().setup_method(_method=_method, filename=filename) def test_init(self, mock_etl, mock_paths): - """Tests that the mock NationalRiskIndexETL class instance was + """Tests that the mock class instance was initiliazed correctly. - """ + """ # setup etl = self._ETL_CLASS() # validation