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Hands-On Data Visualization with Bokeh

You're reading from   Hands-On Data Visualization with Bokeh Interactive web plotting for Python using Bokeh

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Product type Paperback
Published in Jun 2018
Publisher Packt
ISBN-13 9781789135404
Length 174 pages
Edition 1st Edition
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Author (1):
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Kevin Jolly Kevin Jolly
Author Profile Icon Kevin Jolly
Kevin Jolly
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Table of Contents (10) Chapters Close

Preface 1. Bokeh Installation and Key Concepts FREE CHAPTER 2. Plotting using Glyphs 3. Plotting with different Data Structures 4. Using Layouts for Effective Presentation 5. Using Annotations, Widgets, and Visual Attributes for Visual Enhancement 6. Building and Hosting Applications Using the Bokeh Server 7. Advanced Plotting with Networks, Geo Data, WebGL, and Exporting Plots 8. The Bokeh Workflow – A Case Study 9. Other Books You May Enjoy

Creating visual attributes to enhance style and interactivity

Visual attributes can broadly be classified into two categories:

  • Attributes that add interactivity to your plot
  • Attributes that enhance the visual style of your plot

This section will lay the foundation for both these categories and show how you can fully utilize and exploit Bokeh to get the most out of your plots.

Attributes that add interactivity to the plot

The visual attributes that further enhance the interactivity of your plots are as follows:

  • Hover Tooltip: Lets you point the mouse at a specific point in the plot and displays associated information
  • Selection: Lets you select a region of the plot and colors that region a different color
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