From 314c7552e88d98460b94067460fb32929e80b4a0 Mon Sep 17 00:00:00 2001 From: lucasmbrown-usds Date: Mon, 6 Dec 2021 00:23:28 -0500 Subject: [PATCH] adding college to score --- data/data-pipeline/data_pipeline/score/score_l.py | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/data/data-pipeline/data_pipeline/score/score_l.py b/data/data-pipeline/data_pipeline/score/score_l.py index 2b7fbd9e..eb870fb3 100644 --- a/data/data-pipeline/data_pipeline/score/score_l.py +++ b/data/data-pipeline/data_pipeline/score/score_l.py @@ -14,6 +14,7 @@ class ScoreL(Score): self.ENVIRONMENTAL_BURDEN_THRESHOLD: float = 0.90 self.MEDIAN_HOUSE_VALUE_THRESHOLD: float = 0.90 self.LACK_OF_HIGH_SCHOOL_MINIMUM_THRESHOLD: float = 0.10 + self.COLLEGE_ATTENDANCE_MAXMIMUM_THRESHOLD: float = 0.30 super().__init__(df) @@ -107,6 +108,9 @@ class ScoreL(Score): + field_names.PERCENTILE_FIELD_SUFFIX ] >= self.LOW_INCOME_THRESHOLD + ) & ( + self.df[field_names.COLLEGE_ATTENDANCE_FIELD] + <= self.COLLEGE_ATTENDANCE_MAXMIMUM_THRESHOLD ) def _increment_total_eligibility_exceeded( @@ -581,9 +585,13 @@ class ScoreL(Score): field_names.LOW_READING_LOW_HS_EDUCATION_FIELD, ] + # TODO: if we proceed, rename all these vars to also reference college. high_scool_achievement_rate_threshold = ( self.df[field_names.HIGH_SCHOOL_ED_FIELD] >= self.LACK_OF_HIGH_SCHOOL_MINIMUM_THRESHOLD + ) & ( + self.df[field_names.COLLEGE_ATTENDANCE_FIELD] + <= self.COLLEGE_ATTENDANCE_MAXMIMUM_THRESHOLD ) unemployment_threshold = (