Computing, and thus software, is one of the foundations of modern technical work across a broad range of fields. Like anything, all software has attributes: slow, fast, buggy, robust, etc. However, these attributes are not passive and neutral. In this talk I will describe how the attributes of software have a profound affect on human behavior, attitudes and thought patterns. These attributes, for better or worse, infect all of the work that is done using the software. To explore these ideas, I will provide an attribute based tour of the IPython Notebook. This tour will elucidate the overall vision for the project and cover our recent work on interactive widgets and converting notebooks to different formats.
Brian Granger is an Assistant Professor of Physics at Cal Poly State University in San Luis Obispo, CA. He has a background in theoretical atomic, molecular and optical physics, with a Ph.D from the University of Colorado. His current research interests include quantum computing, parallel and distributed computing and interactive computing environments for scientific and technical computing. He is a core developer of the IPython project, the creator of PyZMQ and a contributor to SymPy. Contact him at firstname.lastname@example.org or @ellisonbg (Twitter, GitHub).
What is PyData?
PyData.org 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: email@example.com
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: firstname.lastname@example.org