updated to fix linting errors (#1818)

Cleans and updates base branch

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

@@ -294,10 +294,10 @@ TILES_SCORE_COLUMNS = {
     # These are the booleans for socioeconomic indicators
     ## this measures low income boolean
     field_names.FPL_200_SERIES: "FPL200S",
-    ## Low high school and low higher ed for t&wd
+    ## Low high school for t&wd
     field_names.WORKFORCE_SOCIO_INDICATORS_EXCEEDED: "M_WKFC_EBSI",
-    ## FPL 200 and low higher ed for all others
-    field_names.FPL_200_SERIES: "M_EBSI",
+    ## 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)
 }
 
 # columns to round floats to 2 decimals

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

@@ -1,6 +1,5 @@
 import functools
 from collections import namedtuple
-from attr import field
 
 import numpy as np
 import pandas as pd

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

@@ -289,7 +289,7 @@ class GeoScoreETL(ExtractTransformLoad):
             shapefile_column_field = "shapefile_column"
             internal_column_name_field = "column_name"
             column_description_field = "column_description"
-            
+
             logger.info("Creating a codebook that uses the csv names")
             codebook = (
                 pd.Series(codebook)
@@ -299,7 +299,6 @@ class GeoScoreETL(ExtractTransformLoad):
                         0: internal_column_name_field,
                         "index": shapefile_column_field,
                     }
-
                 )
             )