Bokeh documentation

Bokeh provides tools for creating interactive visualizations for modern web browsers, with a Python library and BokehJS for JavaScript. It helps you build interactive graphics, ranging from simple plots to complex dashboards with streaming datasets. With the Python library, you can create JavaScript-powered visualizations without writing any JavaScript yourself.

Finding the right documentation resources

Bokeh’s documentation consists of several components:

If you are new to Bokeh

Follow these guides to get started:

• First steps: simple tutorials that walk you through installing Bokeh and creating your first visualizations.

• User guide: explanations of all key functionalities of Bokeh and how to use them. Includes several standalone examples.

If you have some basic knowledge of Bokeh

Learn more by exploring examples:

• Gallery: a collection of examples with source code.

• Interactive tutorial notebooks: a collection of interactive notebooks to experiment with all elements of Bokeh.

• User guide: explanations of all key functionalities of Bokeh and how to use them, including examples.

If you need more advanced information

Get to know every aspect of Bokeh:

• Reference guide: detailed information about all of Bokeh’s components.

• Contributor guide: information on the various ways you can contribute to the Bokeh project.

Connecting with the Bokeh community

There are various ways to get in touch with the Bokeh community:

• The Bokeh Discourse is the best place to ask usage questions and is a great way to get feedback from other users on how to approach a problem.

• Questions involving pandas or other libraries may find a wider audience by posting with the “bokeh” tag on Stack Overflow.

• If you think you’ve found a bug, or would like to request a feature, please report an issue at Bokeh’s GitHub repository.

You can also find more information about Bokeh on Medium, and LinkedIn.