Trevor Manz
Hi, I'm Trevor 👋 I'm a PhD student and visualization researcher in the HIDIVE Lab at Harvard Medical School. I build interactive visualization tools for computational biologists to analyze data more effectively.
I want to make the web platform more accessible to Python developers and help data scientists bring interactive visualizations in their workflows. I maintain anywidget and am involved in the Zarr community. Last year was my first SciPy and I'm very excited to be returning.
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Sessions
Jupyter Widgets connect Python objects with web-based visualizations and UIs, enabling both programmatic and interactive manipulation of data and code. For example, lasso some points in a scatterplot visualization and access that selection in Python as a DataFrame.
anywidget makes it simple and enjoyable to bring these capabilities to your own Python classes, and it ensures easy installation and usage by end users in various environments. In this tutorial, you will create your own custom widgets with anywidget and learn the skills to be effective in extending your own Python classes with web-based superpowers.
Visualization plays a critical role in the analysis and decision making with data, yet the manner in which state-of-the-art visualization approaches are disseminated limit their adoption into modern analytical workflows. Jupyter Widgets bridge this gap between Python and interactive web interfaces, allowing for both programmatic and interactive manipulation of data and code. However, their development has historically been tedious and error-prone.
In this talk, you will learn about anywidget, a Python library that simplifies widgets, making their development more accessible, reliable, and enjoyable. I will showcase new visualization libraries built with anywidget and explain how its design enables environments beyond Jupyter to add support.