Bokeh is an interactive data visualization library for Python—and other languages—that targets modern web browsers for presentation. It can create versatile, data-driven graphics and connect the full power of the entire Python data science stack to create rich, interactive visualizations.
Basic plotting with BokehFree
This chapter provides an introduction to basic plotting with Bokeh. You will create your first plots, learn about different data formats Bokeh understands, and make visual customizations for selections and mouse hovering.
Layouts, Interactions, and Annotations
Learn how to combine multiple Bokeh plots into different kinds of layouts on a page, how to easily link different plots together, and how to add annotations such as legends and hover tooltips.
Building interactive apps with Bokeh
Bokeh server applications allow you to connect all of the powerful Python libraries for data science and analytics, such as NumPy and pandas to create rich, interactive Bokeh visualizations. Learn about Bokeh's built-in widgets, how to add them to Bokeh documents alongside plots, and how to connect everything to real Python code using the Bokeh server.
Putting It All Together! A Case Study
In this final chapter, you'll build a more sophisticated Bokeh data exploration application from the ground up based on the famous Gapminder dataset.
In the following tracksData Visualization
Data Science Training
This course was created in collaboration with Anaconda. With over 6 million users, the open source Anaconda Distribution is the fastest and easiest way to do Python data science and machine learning. It's the industry standard for developing, testing, and training on a single machine.