The Bokeh data visualization library allows you to build interactive visualizations for the web in python. This training gives a quick introduction to Bokeh's unique features. We'll do exercixes building up a variety of visualizations and finish discussing topics and questions from participants related to their own datasets & needs.
The Bokeh data visualization library allows you to build interactive visualizations for the web in python. It has a range of capabilities from quick "one-line" charts to streaming datasets to integrating with your existing plot libraries such as matplotlib or ggplot.
This training gives a quick hands-on introduction to Bokeh's core features. We'll do exercises building up a variety of visualizations and finish up discussing topics and questions from participants related to their own datasets & needs.
This is the planned outline:
- (20 minutes) Bokeh feature walk-through. The relationship between bokeh, bokehjs and bokeh-server. The various API levels of bokeh (models, plotting, charts). And, examples of a variety of visualizations.
- (20 minutes): Exercises - 1 - The charts & plotting interface. Get quickly plotting in an ipython notebook. Different types of data accepted, and how to customize a plot.
- (10 minutes): Tips for navigating the Bokeh docs and examples as you're getting up to speed.
- (20 minutes): Exercises - 2 - (a) The models interface. Build a custom plot from the ground up using the Models API. (b) Quick, yet custom, using the charts interface and models together.
- (10 minutes): Sharing your plots. Overview of the different ways to share your plots with your colleagues and the world.
- (20 minutes): Exercises - 3 - Add custom interactivity - Customize your hover and selections. Implement linked selection, brushing, and panning.
- (20 minutes): open space for questions and interactively solving Bokeh problems on your real-life problems & data as time permits.