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Adding DOT composite to travel score (#1820)

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This adds the DOT dataset to the ETL and to the score. Note that currently we take a percentile of an average of percentiles.
This commit is contained in:
Emma Nechamkin 2022-08-16 14:44:39 -04:00 • committed by GitHub
commit ebac552d75
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17 changed files with 553 additions and 354 deletions
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9
data/data-pipeline/data_pipeline/score/field_names.py
View file

@ -344,6 +344,9 @@ CDC_SVI_INDEX_RPL_THEMES_OVERALL_FIELD: str = (
)
CDC_SVI_INDEX_THEMES_PRIORITY_COMMUNITY: str = "At or above 90 for overall percentile ranking according to Social Vulnerability Indices"
# DOT Travel Burden Data
DOT_TRAVEL_BURDEN_FIELD: str = "DOT Travel Barriers Score"
# Maryland EJSCREEN Data.
MARYLAND_EJSCREEN_SCORE_FIELD: str = "Maryland Environmental Justice Score"
@ -416,6 +419,7 @@ DIESEL_PARTICULATE_MATTER_LOW_INCOME_FIELD = (
)
TRAFFIC_PROXIMITY_LOW_INCOME_FIELD = f"Greater than or equal to the {PERCENTILE}th percentile for traffic proximity and is low income?"
# Affordable and Sustainable Housing
LEAD_PAINT_MEDIAN_HOUSE_VALUE_LOW_INCOME_FIELD = (
f"Greater than or equal to the {PERCENTILE}th percentile for lead paint and"
@ -494,6 +498,10 @@ TRAFFIC_PROXIMITY_LOW_INCOME_LOW_HIGHER_ED_FIELD = (
f"traffic proximity{SCORE_M_LOW_INCOME_SUFFIX}?"
)
DOT_TRAVEL_BURDEN_LOW_INCOME_FIELD = (
f"Greater than or equal to the {PERCENTILE}th percentile "
f"for DOT transit barriers and is low income?"
)
# Affordable and Sustainable Housing
LEAD_PAINT_MEDIAN_HOUSE_VALUE_LOW_INCOME_LOW_HIGHER_ED_FIELD = (
f"Greater than or equal to the {PERCENTILE}th percentile for lead paint,"
@ -624,6 +632,7 @@ PM25_EXCEEDS_PCTILE_THRESHOLD = (
)
DIESEL_EXCEEDS_PCTILE_THRESHOLD = f"Greater than or equal to the {PERCENTILE}th percentile for diesel particulate matter"
TRAFFIC_PROXIMITY_PCTILE_THRESHOLD = f"Greater than or equal to the {PERCENTILE}th percentile for traffic proximity"
DOT_BURDEN_PCTILE_THRESHOLD = f"Greater than or equal to the {PERCENTILE}th percentile for DOT travel barriers"
LEAD_PAINT_PROXY_PCTILE_THRESHOLD = (
f"Greater than or equal to the {PERCENTILE}th percentile for lead paint and"
f" the median house value is less than {MEDIAN_HOUSE_VALUE_PERCENTILE}th "

17
data/data-pipeline/data_pipeline/score/score_narwhal.py
View file

@ -246,6 +246,8 @@ class ScoreNarwhal(Score):
# In Xth percentile or above for PM 2.5 (Source: EPA, Office of Air and Radiation (OAR) fusion of model and monitor data)]
# or
# In Xth percentile or above traffic proximity and volume (Source: 2017 U.S. Department of Transportation (DOT) traffic data
# or
# In Xth percentile or above for DOT Travel Disadvantage
# AND
# Low income: In Nth percentile or above for percent of block group population
# of households where household income is less than or equal to twice the federal
@ -255,6 +257,7 @@ class ScoreNarwhal(Score):
transportion_eligibility_columns = [
field_names.DIESEL_PARTICULATE_MATTER_LOW_INCOME_FIELD,
field_names.TRAFFIC_PROXIMITY_LOW_INCOME_FIELD,
field_names.DOT_TRAVEL_BURDEN_LOW_INCOME_FIELD,
]
self.df[field_names.DIESEL_EXCEEDS_PCTILE_THRESHOLD] = (
@ -264,6 +267,14 @@ class ScoreNarwhal(Score):
>= self.ENVIRONMENTAL_BURDEN_THRESHOLD
)
self.df[field_names.DOT_BURDEN_PCTILE_THRESHOLD] = (
self.df[
field_names.DOT_TRAVEL_BURDEN_FIELD
+ field_names.PERCENTILE_FIELD_SUFFIX
]
>= self.ENVIRONMENTAL_BURDEN_THRESHOLD
)
self.df[field_names.TRAFFIC_PROXIMITY_PCTILE_THRESHOLD] = (
self.df[
field_names.TRAFFIC_FIELD + field_names.PERCENTILE_FIELD_SUFFIX
@ -274,6 +285,7 @@ class ScoreNarwhal(Score):
self.df[field_names.TRAFFIC_THRESHOLD_EXCEEDED] = (
self.df[field_names.TRAFFIC_PROXIMITY_PCTILE_THRESHOLD]
| self.df[field_names.DIESEL_EXCEEDS_PCTILE_THRESHOLD]
| self.df[field_names.DOT_BURDEN_PCTILE_THRESHOLD]
)
self.df[field_names.DIESEL_PARTICULATE_MATTER_LOW_INCOME_FIELD] = (
@ -286,6 +298,11 @@ class ScoreNarwhal(Score):
& self.df[field_names.FPL_200_SERIES_IMPUTED_AND_ADJUSTED]
)
self.df[field_names.DOT_TRAVEL_BURDEN_LOW_INCOME_FIELD] = (
self.df[field_names.DOT_BURDEN_PCTILE_THRESHOLD]
& self.df[field_names.FPL_200_SERIES_IMPUTED_AND_ADJUSTED]
)
self._increment_total_eligibility_exceeded(
transportion_eligibility_columns,
skip_fips=constants.DROP_FIPS_FROM_NON_WTD_THRESHOLDS,