This tutorial will take you through all of the steps involved in exploring data of many different types and sizes, building simple and complex figures, working with billions of data points, adding interactive behavior, widgets and controls, and deploying full dashboards and applications.
We'll be using a wide range of open-source Python libraries, but focusing on the tools we help maintain as part of the HoloViz project: Panel, hvPlot, HoloViews, GeoViews, Datashader, Param, and Colorcet.
These tools were previously part of PyViz.org, but have been pulled out into HoloViz.org to allow PyViz to be fully neutral and general.
The HoloViz tools have been carefully designed to work together with each other and with the SciPy ecosystem to address a very wide range of data-analysis and visualization tasks, making it simple to discover, understand, and communicate the important properties of your data.
This notebook serves as the homepage of the tutorial, including a table of contents letting you launch each tutorial section.
Introduction and setup
Building dashboards using Panel
The .plot
API: a data-centric approach to visualization
.plot
interface..hvplot
outputs to show relationships..plot
or .hvplot
visualizations to your dashboard.Custom interactivity
Working with large datasets
Building advanced dashboards
You will find extensive support material on the websites for each package. You may find these links particularly useful during the tutorial:
.hvplot()