publicdata/j40-cejst-2
1
0
Fork 0
mirror of https://github.com/DOI-DO/j40-cejst-2.git synced 2025-08-03 09:34:19 -07:00
Code Issues Projects Releases Packages Wiki Activity Actions

Use Census Decennial 2020 data for territories

Browse source
This commit is contained in:
Carlos Felix 2024-11-21 10:40:51 -05:00 • committed by Carlos Felix
commit 6436dfa683
12 changed files with 767 additions and 513 deletions
Download patch file Download diff file Expand all files Collapse all files

8
data/data-pipeline/data_pipeline/etl/score/constants.py
View file

@ -315,18 +315,18 @@ TILES_SCORE_COLUMNS = {
field_names.ISLAND_AREAS_POVERTY_LOW_HS_EDUCATION_FIELD: "IAPLHSE",
field_names.ISLAND_AREAS_LOW_MEDIAN_INCOME_LOW_HS_EDUCATION_FIELD: "IALMILHSE",
# Percentiles for Island areas' workforce columns
field_names.LOW_CENSUS_DECENNIAL_AREA_MEDIAN_INCOME_PERCENT_FIELD_2009
field_names.LOW_CENSUS_DECENNIAL_AREA_MEDIAN_INCOME_PERCENT_FIELD_2019
+ field_names.PERCENTILE_FIELD_SUFFIX: "IALMILHSE_PFS",
field_names.CENSUS_DECENNIAL_POVERTY_LESS_THAN_100_FPL_FIELD_2009
field_names.CENSUS_DECENNIAL_POVERTY_LESS_THAN_100_FPL_FIELD_2019
+ field_names.ISLAND_AREAS_PERCENTILE_ADJUSTMENT_FIELD
+ field_names.PERCENTILE_FIELD_SUFFIX: "IAPLHSE_PFS",
field_names.CENSUS_DECENNIAL_UNEMPLOYMENT_FIELD_2009
field_names.CENSUS_DECENNIAL_UNEMPLOYMENT_FIELD_2019
+ field_names.ISLAND_AREAS_PERCENTILE_ADJUSTMENT_FIELD
+ field_names.PERCENTILE_FIELD_SUFFIX: "IAULHSE_PFS",
field_names.LOW_HS_EDUCATION_FIELD: "LHE",
field_names.ISLAND_AREAS_LOW_HS_EDUCATION_FIELD: "IALHE",
# Percentage of HS Degree completion for Islands
field_names.CENSUS_DECENNIAL_HIGH_SCHOOL_ED_FIELD_2009: "IAHSEF",
field_names.CENSUS_DECENNIAL_HIGH_SCHOOL_ED_FIELD_2019: "IAHSEF",
# Booleans for the front end about the types of thresholds exceeded
field_names.CLIMATE_THRESHOLD_EXCEEDED: "N_CLT_EOMI",
field_names.ENERGY_THRESHOLD_EXCEEDED: "N_ENY_EOMI",

18
data/data-pipeline/data_pipeline/etl/score/etl_score.py
View file

@ -166,7 +166,7 @@ class ScoreETL(ExtractTransformLoad):
census_decennial_csv = (
constants.DATA_PATH
/ "dataset"
/ "census_decennial_2010"
/ "census_decennial_2020"
/ "usa.csv"
)
self.census_decennial_df = pd.read_csv(
@ -470,13 +470,13 @@ class ScoreETL(ExtractTransformLoad):
field_names.EXPECTED_BUILDING_LOSS_RATE_FIELD,
field_names.EXPECTED_AGRICULTURE_LOSS_RATE_FIELD,
field_names.EXPECTED_POPULATION_LOSS_RATE_FIELD,
field_names.CENSUS_DECENNIAL_HIGH_SCHOOL_ED_FIELD_2009,
field_names.CENSUS_DECENNIAL_POVERTY_LESS_THAN_100_FPL_FIELD_2009,
field_names.CENSUS_DECENNIAL_POVERTY_LESS_THAN_200_FPL_FIELD_2009,
field_names.CENSUS_DECENNIAL_UNEMPLOYMENT_FIELD_2009,
field_names.CENSUS_DECENNIAL_HIGH_SCHOOL_ED_FIELD_2019,
field_names.CENSUS_DECENNIAL_POVERTY_LESS_THAN_100_FPL_FIELD_2019,
field_names.CENSUS_DECENNIAL_POVERTY_LESS_THAN_200_FPL_FIELD_2019,
field_names.CENSUS_DECENNIAL_UNEMPLOYMENT_FIELD_2019,
field_names.CENSUS_UNEMPLOYMENT_FIELD_2010,
field_names.CENSUS_POVERTY_LESS_THAN_100_FPL_FIELD_2010,
field_names.CENSUS_DECENNIAL_TOTAL_POPULATION_FIELD_2009,
field_names.CENSUS_DECENNIAL_TOTAL_POPULATION_FIELD_2019,
field_names.UST_FIELD,
field_names.DOT_TRAVEL_BURDEN_FIELD,
field_names.FUTURE_FLOOD_RISK_FIELD,
@ -542,8 +542,8 @@ class ScoreETL(ExtractTransformLoad):
low_field_name=field_names.LOW_LIFE_EXPECTANCY_FIELD,
),
ReversePercentile(
field_name=field_names.CENSUS_DECENNIAL_AREA_MEDIAN_INCOME_PERCENT_FIELD_2009,
low_field_name=field_names.LOW_CENSUS_DECENNIAL_AREA_MEDIAN_INCOME_PERCENT_FIELD_2009,
field_name=field_names.CENSUS_DECENNIAL_AREA_MEDIAN_INCOME_PERCENT_FIELD_2019,
low_field_name=field_names.LOW_CENSUS_DECENNIAL_AREA_MEDIAN_INCOME_PERCENT_FIELD_2019,
),
]
@ -658,7 +658,7 @@ class ScoreETL(ExtractTransformLoad):
df_copy[field_names.COMBINED_CENSUS_TOTAL_POPULATION_2010] = df_copy[
[
field_names.TOTAL_POP_FIELD,
field_names.CENSUS_DECENNIAL_TOTAL_POPULATION_FIELD_2009,
field_names.CENSUS_DECENNIAL_TOTAL_POPULATION_FIELD_2019,
]
].mean(axis=1, skipna=True)