Interactive Data Visualization with Bokeh

Learn how to create versatile and interactive data visualizations using Bokeh.
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4 Hours17 Videos63 Exercises51,778 Learners
5100 XP

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Course Description

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.

  1. 1

    Basic plotting with Bokeh

    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.
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  2. 2

    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.
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  3. 3

    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.
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  4. 4

    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.
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Data Visualization
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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.
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