Add missing eia923 file mappings discovered in audit

[krivard]

Overview

What problem does this address?

While checking mappings for #4312 we discovered some pages of existing source spreadsheets weren't being mapped but sh/could have been. This PR adds those missing mappings back in.

NOTE: we're not currently extracting any of this data because it's not column-mapped...but it is file and pagemapped, and we seem to be maintaining those mappings, so this correction is still probably good to do

What did you change?

• New file mappings for coal_stocks and petcoke_stocks for 2021, 2022, 2023
• Fixed off-by-one error in page mappings for coal_stocks 2017

Documentation

Make sure to update relevant aspects of the documentation:

• Update the release notes: reference the PR and related issues.
• Update relevant Data Source jinja templates (see docs/data_sources/templates).
• Update relevant table or source description metadata (see src/metadata).
• 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?

from pudl.extract.eia923 import Extractor as Extractor923
from pudl.workspace.datastore import Datastore
from pudl.workspace.setup import PudlPaths
from io import BytesIO
import pandas as pd

pp = PudlPaths()
ds = Datastore(local_cache_path=pp.data_dir)
ex = Extractor923(ds=ds)

pagehits = {}
names = pd.DataFrame(data={}, index=range(2001, 2026))
for yr in range(2001, 2026):
    for page in ex._metadata._file_name.index:
        source_filename = ex.source_filename(page, year=yr)
        if source_filename == "-1": continue
        if source_filename not in ex._file_cache:
            with ds.get_zipfile_resource("eia923", **ex.zipfile_resource_partitions(page, year=yr)) as zf:
                ex._file_cache[source_filename] = pd.ExcelFile(BytesIO(zf.read(source_filename)), engine="calamine")
        excelf = ex._file_cache[source_filename]
        pageid = ex._metadata._sheet_name.at[page, str(yr)]
        if source_filename not in pagehits: pagehits[source_filename] = { sni: False for sni in excelf.sheet_names }
        if pageid != "-1": pagehits[source_filename][excelf.sheet_names[pageid]] = True
        names.loc[yr, f"{page}.source"] = source_filename
        names.loc[yr, f"{page}.page"] = excelf.sheet_names[pageid]
for src in sorted(pagehits.keys()):
    miss = [k for k in pagehits[src] if not pagehits[src][k]]
    miss = [m for m in miss if (m.find("Layout") < 0) and (m.find("Codes") < 0)]
    if miss:
        print("="*80)
        print(f"{src}\n{', '.join(miss)}")

& the results are all Puerto Rico (which is getting handled in #4312) and Boiler/Generator (which all have identical counterparts already mapped; apparently EIA includes those tables in two separate spreadsheets):

================================================================================
EIA923_Schedules_2_3_4_5_M_12_2017_Final_Revision.xlsx
Page 6 Plant Frame Puerto Rico
================================================================================
EIA923_Schedules_2_3_4_5_M_12_2018_Final_Revision.xlsx
Page 6 Plant Frame Puerto Rico
================================================================================
SCHEDULE 3A 5A 8A 8B 8C 8D 8E 8F 2008.xlsm
Boiler Fuel Data, Generator Data
================================================================================
SCHEDULE 3A 5A 8A 8B 8C 8D 8E 8F 2010 on NOV 30 2011.xls
Boiler, Generator
================================================================================
SCHEDULE 3A 5A 8A 8B 8C 8D 8E 8F REVISED 2009 04112011.xls
Boiler, Generator

To-do list

• If updating analyses or data processing functions: make sure to update row count expectations in dbt tests.
• Run make pytest-coverage locally to ensure that the merge queue will accept your PR.
• Review the PR yourself and call out any questions or issues you have.
• 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.
• For bigger ETL or data changes run the full ETL locally and then run the data validations using make pytest-validate.
• Alternatively, run the build-deploy-pudl GitHub Action manually.