Add tests for all non-census sources (#1899)

* Refactor CDC life-expectancy (1554)

* Update to new tract list (#1554)

* Adjust for tests (#1848)

* Add tests for cdc_places (#1848)

* Add EJScreen tests (#1848)

* Add tests for HUD housing (#1848)

* Add tests for GeoCorr (#1848)

* Add persistent poverty tests (#1848)

* Update for sources without zips, for new validation (#1848)

* Update tests for new multi-CSV but (#1848)

Lucas updated the CDC life expectancy data to handle a bug where two
states are missing from the US Overall download. Since virtually none of
our other ETL classes download multiple CSVs directly like this, it
required a pretty invasive new mocking strategy.

* Add basic tests for nature deprived (#1848)

* Add wildfire tests (#1848)

* Add flood risk tests (#1848)

* Add DOT travel tests (#1848)

* Add historic redlining tests (#1848)

* Add tests for ME and WI (#1848)

* Update now that validation exists (#1848)

* Adjust for validation (#1848)

* Add health insurance back to cdc places (#1848)

Ooops

* Update tests with new field (#1848)

* Test for blank tract removal (#1848)

* Add tracts for clipping behavior

* Test clipping and zfill behavior (#1848)

* Fix bad test assumption (#1848)

* Simplify class, add test for tract padding (#1848)

* Fix percentage inversion, update tests (#1848)

Looking through the transformations, I noticed that we were subtracting
a percentage that is usually between 0-100 from 1 instead of 100, and so
were endind up with some surprising results. Confirmed with lucasmbrown-usds

* Add note about first street data (#1848)

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

@@ -20,6 +20,7 @@ class NatureDeprivedETL(ExtractTransformLoad):
     )
     GEO_LEVEL = ValidGeoLevel.CENSUS_TRACT
     PUERTO_RICO_EXPECTED_IN_DATA = False
+    LOAD_YAML_CONFIG: bool = True
     ALASKA_AND_HAWAII_EXPECTED_IN_DATA = False
 
     # Output score variables (values set on datasets.yml) for linting purposes
@@ -65,7 +66,7 @@ class NatureDeprivedETL(ExtractTransformLoad):
             df_ncld[self.TRACT_ACRES_FIELD_NAME] >= self.TRACT_ACRES_LOWER_BOUND
         )
         df_ncld[self.TRACT_PERCENT_NON_NATURAL_FIELD_NAME] = (
-            1 - df_ncld[self.PERCENT_NATURAL_FIELD_NAME]
+            100 - df_ncld[self.PERCENT_NATURAL_FIELD_NAME]
         )
 
         # Assign the final df to the class' output_df for the load method with rename