Visualize any Data Easily, from Notebooks to Dashboards-SOLD OUT
James Bednar, Anaconda, Inc.
Philipp Rudiger, Anaconda, Inc.
Julia Signell, Anaconda, Inc.
In this tutorial you will see how to visualize and communicate your data easily and effectively using Python tools. You'll learn how to use Panel to lay out your existing plots with widgets to make apps in the notebook or as deployed dashboards, hvPlot to make your Pandas or Xarray .plot() API calls return interactive, explorable plots, HoloViews and GeoViews to help you explore multidimensional data naturally without having to build a plot for each combination or sample of the data space, and Datashader to visualize even the very largest datasets faithfully in a web browser. See pyviz.org for links to all these tools and more.
Basic familiarity with NumPy or Pandas will help you work with the data you are visualizing. Experience plotting data in any visualization system should be sufficient background for understanding and appreciating the approach used here.