fix: Normalize VCE RARE spellings of great lakes.

[krivard]

Overview

Closes #4007 .

What problem does this address?

The names of a couple of the great lakes in the VCE RARE dataset had unusual or creative spellings. This PR normalizes the spelling of Lake Huron and Lake Saint Clair in VCE RARE.

What did you change?

• New function _spot_fix_great_lakes_values called by _prep_lat_long_fips_df to catch the cell values
• New function _spot_fix_great_lakes_columns called by one_year_hourly_available_capacity_factor to catch the column names

Documentation

Make sure to update relevant aspects of the documentation.

Tasks

Preview Give feedback

1. Update the release notes: reference the PR and related issues.
2. Update relevant Data Source jinja templates (see docs/data_sources/templates).
3. Update relevant table or source description metadata (see src/metadata).
4. Review and update any other aspects of the documentation that might be affected by this PR.

Testing

How did you make sure this worked? How can a reviewer verify this?

1. Materialize the core_vcerare asset group in Dagster
2. Examine parquet file out_vcerare__hourly_available_capacity_factor and observe:
   • lake_hurron does not appear in column county_id_fips; lake_huron does appear
   • lake_st_clair does not appear in column county_id_fips; lake_saint_clair does appear

e.g.

import duckdb
from pudl.workspace.setup import PudlPaths

ddb = duckdb.read_parquet(str(PudlPaths().parquet_path("out_vcerare__hourly_available_capacity_factor")))
duckdb.query("""
SELECT county_or_lake_name, COUNT(*)
FROM ddb 
WHERE county_or_lake_name in ('lake_hurron', 'lake_st_clair')
GROUP BY county_or_lake_name""")
duckdb.query("""
SELECT county_or_lake_name, COUNT(*)
FROM ddb 
WHERE county_or_lake_name in ('lake_huron', 'lake_saint_clair')
GROUP BY county_or_lake_name""")

To-do list

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1. If updating analyses or data processing functions: make sure to update or write data validation tests (e.g. test_minmax_rows()).
2. Run make pytest-coverage locally to ensure that the merge queue will accept your PR.
3. Review the PR yourself and call out any questions or issues you have.
4. For minor ETL changes or data additions, once make pytest-coverage passes, make sure you have a fresh full PUDL DB downloaded locally, materialize new/changed assets and all their downstream assets and run relevant data validation tests using pytest and --live-dbs.
5. For bigger ETL or data changes run the full ETL locally and then run the data validations using make pytest-validate.
6. Alternatively, run the build-deploy-pudl GitHub Action manually.

[krivard]

RTD build is failing due to Dagster removing their intersphinx .inv file; see also dagster-io/dagster#27328

[zaneselvans]

I've commented out the Dagster intersphinx line on main so if you merge that in the docs build should work again.

[jdangerx]

Looks good! I think we're probably good to merge without this, but also we might consider adding lakes Hurron and St. Clair to the check_unexpected_counties asset check.

[jdangerx]

FMI: Is this is the default job name when you materialize an asset outside of a job?

[cmgosnell]

we could swap this to the annual checks like we do for ferc714