Kyle Sunden
Kyle is a Research Software Engineer with Matplotlib under the NASA ROSES grant.
Kyle holds a PhD in Chemistry from the University of Wisconsin where he did nonlinear spectroscopy.
Session
Matplotlib is already a favorite plotting library for creating static data visualizations in Python.
Here, we discuss the development of a new DataContainer interface and accompanying transformation pipeline which enable easier dynamic data visualization in Matplotlib.
This improves the experience of plotting pure functions, automatically recomputing when you pan and zoom.
Data containers can ingest data from a variety of sources, including structured data such as Pandas Dataframes or Xarrays, up to live updating data from web services or databases.
The flexible transformation pipeline allows for control over how your data is encoded into a plot.