Bokeh is a software package in the Python ecosystem for data science that provides support for interactive visualization of data. As such, it is complementary to other visualization packages that focus more on enabling the generation of static figures for inclusion in publications and reports. Bokeh renders data visualizations within web browsers and Jupyter notebooks, providing capabilities for inspecting different aspects of plotted data, selecting and highlighting subsets of data, setting parameters through graphical user interfaces and direct interactions with plots, and the construction of dashboards that integrate different data streams and analyses based on user interactions.


After you complete this workshop, you should be able to:

  • Decide whether Bokeh might be good for your data visualization needs
  • Understand the key concepts underlying Bokeh data visualizations
  • Understand some of the capabilities and functionality of Bokeh
  • Discuss how Bokeh server applications work

General familiarity with the Python programming language would be useful, but is not required.


If you wish to run some of the code examples presented here, you will need to have a working Python installation with Bokeh and a few other packages installed. See the section on Installing & Running Bokeh for more information.

©   Cornell University  |  Center for Advanced Computing  |  Copyright Statement  |  Inclusivity Statement