Motivation and context:
Briefly describe the dataset. What is it, and why do we want to archive it regularly?
Include a link to the dataset webpage and any metadata documentation.
It's useful to have longer timeseries generation data, and EIA has a number of forms preceding EIA 923 that we aren't currently integrating:
As a first step towards integration, we can archive these datasets in our existing EIA 923 Zenodo repository.
Requirements for archiving
To be archived on Zenodo, a dataset must be:
Checklist for archive creation
Based on the README documentation on creating a new archive:
Links to published archives:
Include a link to the published sandbox archive for review.
Motivation and context:
Briefly describe the dataset. What is it, and why do we want to archive it regularly?
Include a link to the dataset webpage and any metadata documentation.
It's useful to have longer timeseries generation data, and EIA has a number of forms preceding EIA 923 that we aren't currently integrating:
As a first step towards integration, we can archive these datasets in our existing EIA 923 Zenodo repository.
Requirements for archiving
To be archived on Zenodo, a dataset must be:
Checklist for archive creation
Based on the README documentation on creating a new archive:
eia923metadata inpudl.metadata.sources.py. See Define the dataset's metadata for a description of how to do this. This can be done at any point prior to making the final archive and will not block development.src.archivers.eia.eia923.pyscript to also grab the 906 files on the existing page - these files should have the partitions:{'year': [year], 'respondents':'non-utility', frequency:'all'}{'year': [year], 'respondents':'utility', frequency: [annual or monthly]}, with the frequency matching the file source.--refresh-metadatato capture the changes made to the source metadata above.Links to published archives:
Include a link to the published sandbox archive for review.