Welcome to the HoloViz tutorial! These notebooks 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 thousands or 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, Lumen, Param, and Colorcet.
The HoloViz tools have been carefully designed to work together with each other and with the SciPy/PyData 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. Other Python viz tools not included in HoloViz are reviewed at PyViz.org.
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
.plotAPI: a data-centric approach to visualization
20 min Interlinked_Plots: Creating linkages between plots
15 min Exercise 2: Linking the plots from the first exercise
20 min Interactive_Pipelines: Creating interactive pipelines that display data, controlled by widgets
15 min Exercise 3: Building your own pipelines and visualizations controlled by widgets.
10 min Break
Building dashboards using Panel
Advanced dashboards (optional)