Add income back, adjust test (#1882)

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

@@ -679,6 +679,10 @@ def _backfill_island_demographics(self, df: pd.DataFrame) -> pd.DataFrame:
             ]
         df = df.drop(columns=self.ISLAND_DEMOGRAPHIC_BACKFILL_FIELDS)
 
+        df.loc[island_index, field_names.TOTAL_POP_FIELD] = df.loc[
+            island_index, field_names.COMBINED_CENSUS_TOTAL_POPULATION_2010
+        ]
+
         return df
 
     def transform(self) -> None:

data/data-pipeline/data_pipeline/etl/sources/census_decennial/etl.py

@@ -367,6 +367,7 @@ def extract(self) -> None:
                     island["fips"],
                     county,
                 )
+                logger.debug(f"CENSUS: Requesting {api_url}")
                 download = requests.get(
                     api_url,
                     timeout=settings.REQUESTS_DEFAULT_TIMOUT,

data/data-pipeline/data_pipeline/tests/score/test_output.py

@@ -5,6 +5,7 @@
 import pytest
 import pandas as pd
 import numpy as np
+from data_pipeline.etl.score import constants
 from data_pipeline.score import field_names
 from data_pipeline.score.field_names import GEOID_TRACT_FIELD
 from data_pipeline.etl.score.constants import TILES_ISLAND_AREA_FIPS_CODES
@@ -383,8 +384,16 @@ def test_imputed_tracts(final_score_df):
     )
 
     # Make sure that no tracts with population have null imputed income
+    # We DO NOT impute income 
+    is_island_area = (
+        final_score_df[field_names.GEOID_TRACT_FIELD]
+        .str[:2]
+        .isin(constants.TILES_ISLAND_AREA_FIPS_CODES)
+    )
+
     tracts_with_some_population_df = final_score_df[
-        final_score_df[field_names.TOTAL_POP_FIELD] > 0
+        (final_score_df[field_names.TOTAL_POP_FIELD] > 0)
+        & ~is_island_area
     ]
     assert (
         not tracts_with_some_population_df[