Interactive data visualization with Bokeh - Pavithra, Ian Thomas, Bryan Van de Ven, Timo, V. Adesoba

Presenters - Pavithra, Ian Thomas, Bryan Van de Ven, Timo, Victoria Adesoba | SciPy 2023

Bokeh is a library for interactive data visualization. You can use it with Jupyter Notebooks or create standalone web applications, all using Python. This tutorial is a complete guide to Bokeh, where we start with a basic line plot and step-by-step make our way to creating a dashboard with several interacting components. This tutorial will be helpful for scientists who are looking to level-up their analysis and presentations, and tool developers interested in adding custom plotting functionally or dashboards.

Bokeh is a Python library for creating interactive data visualizations. Bokeh allows you to create plots that can be displayed in a web browser, without needing to write HTML and JavaScript. In development for over 10 years, Bokeh has become a core tool for Python data science workflows, used for both exploratory analysis and in presentations. It is actively used in scientific domains including bioscience, geoscience, and astrophysics. Moreover, other useful libraries in the PyData ecosystem, like Dask, ArViz, and the Holoviz tools, build custom applications and workflows with Bokeh.

In this tutorial, you’ll learn everything you need to know to create beautiful and powerful interactive plots from scratch. We’ll start by introducing core Bokeh concepts, creating simple static plots like line and bar charts, and customizing them. We’ll then gradually introduce layers of interactivity, create specialized plots like geographic maps, and discuss new features like contour plots. By the end, you will be able to create a complete interactive dashboard using Bokeh.

This tutorial is presented by Bokeh core team members and is fully hands-on with several examples and exercises in every section. We hope to enable more people, especially scientists and tool developers, to create pretty yet powerful visualizations.

[djl]

"Introduction":"00:00:39",
"Accessing the tutorial notebooks":"00:05:25",
"Chapter 01: Overview":"00:17:30",
"Chapter 02: Bokeh Installation and Setup":"00:28:36",
"Chapter 03: Basic Concepts":"00:29:09",
"Chapter 04: Basic Plotting":"00:36:48",
"Chapter 05: Styling plots":"00:50:09",
"Chapter 06: Data sources":"01:10:28",
"Chapter 07: Adding annotations":"01:24:00",
"Chapter 08: Plot tools and tooltips": "01:32:57",
"Chapter 09: More plot types":"01:48:38",
"Chapter 10: Layouts":"02:03:02",
"Chapter 11: Widgets and interactivity":"02:14:55",
"Chapter 12: Building the demo dashboard":"02:41:50",
"Appendix A: WebGL":"02:45:29",
"Chapter 13: Exporting and embedding":"02:51:38",
"Appendix B: Contour plots":"03:01:15",
"Chapter 14: Next Steps":"03:03:13",
"Q&A":"03:10:34"