Fast flag update (#1844)

Added additional flags for the front end based on our conversation in stand up this morning.

data/data-pipeline/data_pipeline/score/field_names.py

@@ -1,7 +1,7 @@
 # Suffixes
 PERCENTILE_FIELD_SUFFIX = " (percentile)"
 ISLAND_AREAS_PERCENTILE_ADJUSTMENT_FIELD = " for island areas"
-ADJACENT_MEAN_SUFFIX = " (including adjacency index)"
+ADJACENT_MEAN_SUFFIX = " (based on adjacency index and low income alone)"
 ADJACENCY_INDEX_SUFFIX = " (average of neighbors)"
 
 # Geographic field names
@@ -12,6 +12,9 @@ COUNTY_FIELD = "County Name"
 # Score file field names
 # Definition M fields
 SCORE_M = "Definition M"
+FINAL_SCORE_N_BOOLEAN = (
+    "Definition M community, including adjacency index tracts"
+)
 SCORE_M_COMMUNITIES = "Definition M (communities)"
 M_CLIMATE = "Climate Factor (Definition M)"
 M_ENERGY = "Energy Factor (Definition M)"
@@ -67,6 +70,9 @@ ADJUSTED_POVERTY_LESS_THAN_200_PERCENT_FPL_FIELD_NAME = (
 
 # this is what gets used in the score
 POVERTY_LESS_THAN_200_FPL_IMPUTED_FIELD = "Percent of individuals below 200% Federal Poverty Line, imputed and adjusted"
+IMPUTED_INCOME_FLAG_FIELD_NAME = (
+    "Income data has been estimated based on neighbor income"
+)
 POVERTY_LESS_THAN_150_FPL_FIELD = (
     "Percent of individuals < 150% Federal Poverty Line"
 )

data/data-pipeline/data_pipeline/score/score_narwhal.py

@@ -385,8 +385,10 @@ class ScoreNarwhal(Score):
 
         # Kitchen / plumbing
         self.df[field_names.NO_KITCHEN_OR_INDOOR_PLUMBING_PCTILE_THRESHOLD] = (
-            self.df[field_names.NO_KITCHEN_OR_INDOOR_PLUMBING_FIELD 
-                    + field_names.PERCENTILE_FIELD_SUFFIX]
+            self.df[
+                field_names.NO_KITCHEN_OR_INDOOR_PLUMBING_FIELD
+                + field_names.PERCENTILE_FIELD_SUFFIX
+            ]
             >= self.ENVIRONMENTAL_BURDEN_THRESHOLD
         )
 
@@ -971,8 +973,8 @@ class ScoreNarwhal(Score):
             >= self.SCORE_THRESHOLD_DONUT
         )
 
-        # This should be the "final list" of Score Narwhal communities, meaning that we would
-        # expect this to be True if either the tract is a donut hole community OR the tract is a DAC
+        # This constructs the boolean for whether it's a donut hole community
+        # This can also be true when the tract itself is a DAC on its own
         self.df[
             field_names.SCORE_N_COMMUNITIES + field_names.ADJACENT_MEAN_SUFFIX
         ] = (
@@ -980,6 +982,16 @@ class ScoreNarwhal(Score):
             & self.df[field_names.ADJACENT_TRACT_SCORE_ABOVE_DONUT_THRESHOLD]
         )
 
+        # This should be the "final list" of Score Narwhal communities, meaning that we would
+        # expect this to be True if either the tract is a donut hole community OR the tract is a DAC
+        self.df[field_names.FINAL_SCORE_N_BOOLEAN] = (
+            self.df[field_names.SCORE_N_COMMUNITIES]
+            | self.df[
+                field_names.SCORE_N_COMMUNITIES
+                + field_names.ADJACENT_MEAN_SUFFIX
+            ]
+        )
+
     def add_columns(self) -> pd.DataFrame:
         logger.info("Adding Score Narhwal")