Credit: Jordan Wirfs-Brock/Inside Energy

Coal production in the United States has dropped off a cliff. To illustrate that drop, Jordan Wirfs-Brock at Inside Energy used our MIDITime Python library to create a data sonification of the sudden change.

Wirfs-Brock used weekly coal production data from the Energy Information Administration from 1984 to 2016. She set up the sonification so that high piano notes showed high production and low notes showed low production. She then played them back at a rate of nine weeks per second.

Wirfs-Brock also did a great job of explaining to listeners what they’re going to hear and how the data works.

We developed this tool after we used it to turn earthquakes into sound for our Reveal radio episode about the increase in earthquakes in Oklahoma.

If you want to make your own data sonification with time-series data, check out our blog post on using MIDITime.

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Michael Corey is a former senior data editor. He led a team of data journalists who seek to distill large datasets into compelling and easily understandable stories using the tools of journalism, statistics and programming. His specialties include mapping, the U.S.-Mexico border, scientific data and working with remote sensing. Corey's work has been honored with an Online Journalism Award, an Emmy Award, a Polk Award, an IRE Medal and other national awards. He previously worked for the Des Moines Register and graduated from Drake University.