HoloViz Tutorial

Welcome to HoloViz tutorial! In this tutorial, you will make an interactive dashboard like in the image below. You will go through the steps involved in exploring data of different types and sizes, building simple and complex figures, adding interactive behavior and widgets, and deploying full applications. While the tutorial dataset describes earthquake events, the same principles that you will employ in this tutorial can be used for visualization tasks across any domain.

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, which include: Panel, hvPlot, HoloViews, GeoViews, Datashader, Lumen, Param, and Colorcet.

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

  •   5 min  Setup: Setting up the environment and data files.

  • 10 min  Overview: Overview of the HoloViz tools, philosophy, and approach.

• The .plot API: a data-centric approach to visualization

  • 30 min  Plotting: Quick introduction to the .plot interface.

  • 20 min  Composing Plots: Overlaying and laying out .hvplot outputs to show relationships.

  • 15 min     Exercise 1: Building some .hvplot visualizations and composing them together

• Building interactivity

  • 20 min  Interlinked Plots: Creating linkages between plots

  • 15 min    Exercise 2: Linking the plots from the first exercise

  • 20 min  Reactive Pipelines: Creating reactive pipelines that display data, controlled by widgets

  • 15 min     Exercise 3: Building your own pipelines and visualizations controlled by widgets.

• Building dashboards using Panel

  • 30 min  Dashboards: How to make apps and dashboards from Python objects.

  • 30 min     Exercise 4: Using a mix of visualizable types, create a panel and serve it.

• Advanced dashboards (optional)

  • 15 min  Custom Interactivity: Customizing interactivity in detail.

  • 15 min  Custom Dashboards: Building fully custom dashboards.

  • 15 min  Advanced Dashboards: Building complex dashboards.

  • 30 min     Exercise 5: Build your own, advanced dashboard.

This web page was generated from a Jupyter notebook and not all interactivity will work on this website. Right click to download and run locally for full Python-backed interactivity.