Dataset Open Access

PUDL Data Release v2.0.0

Selvans, Zane A.; Gosnell, Christina M.; Sharpe, Austen; Winter, Steven; Welty, Ethan; Rousik, Jan

Dublin Core Export

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<oai_dc:dc xmlns:dc="" xmlns:oai_dc="" xmlns:xsi="" xsi:schemaLocation="">
  <dc:contributor>Dunkle Werner, Karl</dc:contributor>
  <dc:contributor>Schivley, Greg</dc:contributor>
  <dc:contributor>Kumar, Yash</dc:contributor>
  <dc:creator>Selvans, Zane A.</dc:creator>
  <dc:creator>Gosnell, Christina M.</dc:creator>
  <dc:creator>Sharpe, Austen</dc:creator>
  <dc:creator>Winter, Steven</dc:creator>
  <dc:creator>Welty, Ethan</dc:creator>
  <dc:creator>Rousik, Jan</dc:creator>
  <dc:description>PUDL Data Release 2.0.0

This is a data release from the Public Utility Data Liberation (PUDL) project.

	GitHub repository for the software used to generate this data.
	Zenodo archive of the particular version (v0.4.0) of the software that went into this release. For use in citations &amp; long-term accessibility you can use this doi:
	Documentation and release notes for the software and data.
	The software can be installed via the Python Package Index (PyPI) or from conda-forge.

Using This Data

The data in this archive is stored in a combination of SQLite database files, and Apache Parquet datasets. It can be used as a standalone resource, or in conjunction with the PUDL software. The PUDL documentation contains data dictionaries for many of the data tables.

If you want to use the data in conjunction with the PUDL software, we've included a Docker image within the archive that will run a Jupyter Notebook Server containing examples of use based on our PUDL Examples repository. This Docker image contains all of the required software, and can access the associated archived data.

Make sure that you've got Docker installed and running, and also have docker-compose. You'll want to allocate at least 8GB of memory to Docker.

To use the Docker container to access and work with the data, download and extract the compressed tar archive on you computer.

Inside the directory that is created when you extract the archive, you will find a Docker image. Load that image into your Docker environment locally with:  

docker load -i pudl-jupyter.tar

Then within that same directory, run:

docker-compose up

This should start a Jupyter Notebook Server, and provide you with a link to connect to the server running on your local computer, beginning with or https://localhost:48512

You can select the tutorial notebooks from within the notebook interface. The README file contained in the archive and the PUDL Examples repository both provide more details on how to access and work with the data.

Contact Us

If you're using PUDL, we would love to hear from you! Even if it's just a note to let us know that you exist, and how you're using the software or data. You can also:

	Subscribe to our announcements list for email updates.
	Use the Github issue tracker to file bugs, suggest improvements, or ask for help.
	Email the project team at for private communications.
	Follow @CatalystCoop on Twitter.
  <dc:subject>EIA 860</dc:subject>
  <dc:subject>EIA 923</dc:subject>
  <dc:subject>FERC Form 1</dc:subject>
  <dc:subject>EPA CEMS</dc:subject>
  <dc:subject>Environmental Protection Agency</dc:subject>
  <dc:subject>Energy Information Administration</dc:subject>
  <dc:subject>Federal Energy Regulatory Commission</dc:subject>
  <dc:title>PUDL Data Release v2.0.0</dc:title>
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