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adding reading

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lucasmbrown-usds 2021-12-05 21:04:12 -05:00
parent 5e19dac35b
commit e695e7a43d
1 changed files with 26 additions and 3 deletions
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29
data/data-pipeline/data_pipeline/score/score_l.py
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@ -251,9 +251,7 @@ class ScoreL(Score):
& self.df[field_names.FPL_200_SERIES]
)
self.df[
field_names.IMPENETRABLE_SURFACES_LOW_INCOME_FIELD
] = (
self.df[field_names.IMPENETRABLE_SURFACES_LOW_INCOME_FIELD] = (
impenetrable_surfaces_threshold
& self.df[field_names.FPL_200_SERIES]
)
@ -522,6 +520,15 @@ class ScoreL(Score):
>= self.ENVIRONMENTAL_BURDEN_THRESHOLD
)
life_expectancy_threshold = (
self.df[
field_names.LIFE_EXPECTANCY_FIELD
+ field_names.PERCENTILE_FIELD_SUFFIX
]
# Note: a high life expectancy is good, so take 1 minus the threshold to invert it,
# and then look for life expenctancies lower than that (not greater than).
<= 1 - self.ENVIRONMENTAL_BURDEN_THRESHOLD
)
self.df[field_names.DIABETES_LOW_INCOME_FIELD] = (
diabetes_threshold & self.df[field_names.FPL_200_SERIES]
@ -565,6 +572,15 @@ class ScoreL(Score):
field_names.LOW_MEDIAN_INCOME_LOW_HS_EDUCATION_FIELD,
]
# Workforce criteria for states fields.
workforce_eligibility_columns = [
field_names.UNEMPLOYMENT_LOW_HS_EDUCATION_FIELD,
field_names.POVERTY_LOW_HS_EDUCATION_FIELD,
field_names.LINGUISTIC_ISOLATION_LOW_HS_EDUCATION_FIELD,
field_names.MEDIAN_INCOME_LOW_HS_EDUCATION_FIELD,
field_names.READING_LOW_HS_EDUCATION_FIELD,
]
high_scool_achievement_rate_threshold = (
self.df[field_names.HIGH_SCHOOL_ED_FIELD]
>= self.LACK_OF_HIGH_SCHOOL_MINIMUM_THRESHOLD
@ -602,6 +618,13 @@ class ScoreL(Score):
>= self.ENVIRONMENTAL_BURDEN_THRESHOLD
)
reading_threshold = (
self.df[
field_names.READING_FIELD + field_names.PERCENTILE_FIELD_SUFFIX
]
>= self.ENVIRONMENTAL_BURDEN_THRESHOLD
)
self.df[field_names.LINGUISTIC_ISOLATION_LOW_HS_EDUCATION_FIELD] = (
linguistic_isolation_threshold
& high_scool_achievement_rate_threshold