Description
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.