In notebooks, visualizations and code are siloed: interactive visualizations must be manually specified as they are divorced from the analysis provenance expressed via dataframes, while code cells have no access to users’ interactions with visualizations, and hence no way to operate on the results of interaction. To bridge this divide, we present a Jupyter extension, B2.
This talk is based on a year long research project from UC Berkeley (Yifan Wu, Joe Hellerstein) and MIT (Arvind Satyanarayan). The work is to appear at ACM User Interface Software and Technology Symposium 2020.
In the talk, we will first point out the gaps and opportunities to bring frictionless interactive visualizations to notebooks. We then present the set of techniques used to bridge these gaps, which uses concepts at the intersection of databases and interactive data visualizations. Attendees will learn new concepts, ways to extend the Jupyter notebook, and how to more effectively explore data using our Jupyter extension, B2!
The code is open source at https://github.com/yifanwu/b2.