Are your data too complicated to visualize? Have you considered complimenting your visualizations with music? In this session, we'll analyze data from the American Community Survey by composing data-driven music with the ddpy package (

Thomas Levine

Playing with computers since he was young, Tom eventually developed back and wrist pain, so he started studying ergonomics and conducting quantitative ergonomics research. Then he realized that he’d accidentally become a data scientist. And his back and wrists now hurt less. Tom likes using data to help people work less and think more.

What is PyData? is the home for all things related to the use of Python in data management and analysis. This site aims to make open source data science tools easily accessible by listing the links in one location. If you would like to submit a download link or any items to be listed in PyData News, please let us know at:

PyData conferences are a gathering of users and developers of data analysis tools in Python. The goals are to provide Python enthusiasts a place to share ideas and learn from each other about how best to apply the language and tools to ever-evolving challenges in the vast realm of data management, processing, analytics, and visualization.

We aim to be an accessible, community-driven conference, with tutorials for novices, advanced topical workshops for practitioners, and opportunities for package developers and users to meet in person.

A major goal of PyData events and conferences is to provide a venue for users across all the various domains of data analysis to share their experiences and their techniques, as well as highlight the triumphs and potential pitfalls of using Python for certain kinds of problems.

PyData is organized by NumFOCUS with the generous help and support of our sponsors. Proceeds from PyData are donated to NumFOCUS and used for the continued development of the open-source tools used by data scientists If you would like to volunteer to be a part of the PyData team contact us at:

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