From e695e7a43df01bfa0843d2d32f15a5022d14a712 Mon Sep 17 00:00:00 2001
From: lucasmbrown-usds <lucas.m.brown@omb.eop.gov>
Date: Sun, 5 Dec 2021 21:04:12 -0500
Subject: [PATCH] adding reading

---
 .../data_pipeline/score/score_l.py            | 29 +++++++++++++++++--
 1 file changed, 26 insertions(+), 3 deletions(-)

diff --git a/data/data-pipeline/data_pipeline/score/score_l.py b/data/data-pipeline/data_pipeline/score/score_l.py
index ffb90df5..c24f43da 100644
--- a/data/data-pipeline/data_pipeline/score/score_l.py
+++ b/data/data-pipeline/data_pipeline/score/score_l.py
@@ -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