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.
Sections 0-13 of this tutorial have been given as a 1-day course led by trained instructors. For self-paced usage, you should expect this material to take between 1 and 3 days if you do all of it. But sections 0, 1, 2, 3, and 4 contain the most crucial and basic introductory material, and going through those should take a couple of hours of study. All later sections can be studied as needed or skipped if not relevant.
Once you've done section 0 Setup, you can choose between the default introductory section 01 Workflow Introduction, or A2 Dashboard Workflow if you are mainly interested in dashboards and want to get right into making widgets.
We'll be using a wide range of open-source Python libraries, including the Anaconda-supported tools HoloViews, GeoViews, Bokeh, Datashader, and Param:
These libraries have been carefully designed to work together 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 listing each tutorial section.
Overview
Making data visualizable
Datasets and collections of data
Dynamic interactions
Apps and dashboards
You will find extensive support material on the websites for each package. You may find these links particularly useful during the tutorial: