Transform PHMSA company data

[e-belfer]

Overview

Addresses part of #3770. Taking over @seeess1 's #3929 PR.

What problem does this address?

Goal of the PR is to complete the first transformation of raw PHMSA data into a core asset.

What did you change?

• Added a new transform script for PHMSA data.
• Made one helper method (fix_eia_na) more generic since it can be applied across data sets (and updated references accordingly).
• Added a few other helper methods.
• Updated column map files with 2023 values (pulled from whatever was in 2022).
• Specifically changed the ordering of columns in /Users/sam/Documents/pudl/src/pudl/package_data/phmsagas/column_maps/yearly_distribution.csv since we had fax columns mapped to emails and vice versa.

Remaining tasks

• Update data DOI
• Write to alembic
• Fix test failures
• Get validation asset checks running
• Run entire ETL to make sure state encoding doesn't cause problems anywhere else!

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?

To-do list

Preview Give feedback

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.

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