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.
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.
Index and Schedule¶
Introduction and setup
Building dashboards using Panel
- 15 min Building_Panels: How to make apps and dashboards from Python objects.
- 5 min Exercise 1: Using a mix of visualizable types, create a panel and serve it.
- 10 min Interlinked Panels: Customizing linkages between widgets and displayable objects.
- 5 min Exercise 2: Add widgets to control your dashboard.
- 10 min Break
.plotAPI: a data-centric approach to visualization
- Custom interactivity
- Working with large datasets
- 20 min Large Data: Using Datashader to pre-render data in Python
- 10 min Break
You will find extensive support material on the websites for each package. You may find these links particularly useful during the tutorial: