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/etl/score/constants.py

@@ -208,9 +208,10 @@ TILES_SCORE_COLUMNS = {
     field_names.M_HEALTH: "M_HLTH",
     # temporarily update this so that it's the Narwhal score that gets visualized on the map
     # The NEW final score value INCLUDES the adjacency index.
-    field_names.SCORE_N_COMMUNITIES + field_names.ADJACENT_MEAN_SUFFIX: "SM_C",
+    field_names.FINAL_SCORE_N_BOOLEAN: "SM_C",
     field_names.SCORE_N_COMMUNITIES
-    + field_names.PERCENTILE_FIELD_SUFFIX: "SM_PFS",
+    + field_names.ADJACENT_MEAN_SUFFIX: "SM_DON",
+    field_names.SCORE_N_COMMUNITIES: "SM_NO_DON",
     field_names.EXPECTED_POPULATION_LOSS_RATE_LOW_INCOME_LOW_HIGHER_ED_FIELD: "EPLRLI",
     field_names.EXPECTED_AGRICULTURE_LOSS_RATE_LOW_INCOME_LOW_HIGHER_ED_FIELD: "EALRLI",
     field_names.EXPECTED_BUILDING_LOSS_RATE_LOW_INCOME_LOW_HIGHER_ED_FIELD: "EBLRLI",
@@ -313,7 +314,8 @@ TILES_SCORE_COLUMNS = {
     + field_names.PERCENTILE_FIELD_SUFFIX: "IS_PFS",
     field_names.NON_NATURAL_LOW_INCOME_FIELD_NAME: "IS_ET",
     field_names.AML_BOOLEAN: "AML_ET",
-    field_names.ELIGIBLE_FUDS_BINARY_FIELD_NAME: "FUDS_ET"
+    field_names.ELIGIBLE_FUDS_BINARY_FIELD_NAME: "FUDS_ET",
+    field_names.IMPUTED_INCOME_FLAG_FIELD_NAME: "IMP_FLG"
     ## FPL 200 and low higher ed for all others should no longer be M_EBSI, but rather
     ## FPL_200 (there is no higher ed in narwhal)
 }

data/data-pipeline/data_pipeline/etl/score/etl_score.py

@@ -471,6 +471,7 @@ class ScoreETL(ExtractTransformLoad):
             field_names.AGRICULTURAL_VALUE_BOOL_FIELD,
             field_names.ELIGIBLE_FUDS_BINARY_FIELD_NAME,
             field_names.AML_BOOLEAN,
+            field_names.IMPUTED_INCOME_FLAG_FIELD_NAME,
         ]
 
         # For some columns, high values are "good", so we want to reverse the percentile

data/data-pipeline/data_pipeline/etl/score/etl_score_post.py

@@ -521,8 +521,6 @@ class PostScoreETL(ExtractTransformLoad):
         score_tiles_df.to_csv(tile_score_path, index=False, encoding="utf-8")
 
     def _load_downloadable_zip(self, downloadable_info_path: Path) -> None:
-        logger.info("Saving Downloadable CSV")
-
         downloadable_info_path.mkdir(parents=True, exist_ok=True)
         csv_path = constants.SCORE_DOWNLOADABLE_CSV_FILE_PATH
         excel_path = constants.SCORE_DOWNLOADABLE_EXCEL_FILE_PATH