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.
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
30 min Basic Plotting: Quick introduction to the
10 min Composing Plots: Overlaying and laying out
.hvplotoutputs to show relationships.
10 min Exercise 3: Add some
.hvplotvisualizations to your dashboard.
10 min Break
10 min Exercise 4: Add a linked visualization with HoloViews.
Building advanced dashboards
30 min Exercise 5: Build a new dashboard using everything you’ve learned so far.