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/tests/sources/doe_energy_burden/test_etl.py

@@ -59,3 +59,13 @@ class TestDOEEnergyBurdenETL(TestETL):
             data_path / "dataset" / "doe_energy_burden" / "usa.csv"
         )
         assert output_file_path == expected_output_file_path
+
+    def test_tract_id_lengths(self, mock_etl, mock_paths):
+        etl = self._setup_etl_instance_and_run_extract(
+            mock_etl=mock_etl, mock_paths=mock_paths
+        )
+        etl.transform()
+        etl.validate()
+        etl.load()
+        df = etl.get_data_frame()
+        assert (df[etl.GEOID_TRACT_FIELD_NAME].str.len() == 11).all()