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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

Using Annotations, Widgets, and Visual Attributes for Visual Enhancement

Now that you have learned how to create plots and layouts in Bokeh, it is time to enhance them visually and add a layer of interactivity using annotations, widgets, and visual attributes.

Annotations are used to add supplemental information to your plots, such as titles, legends, and color maps that provide information about what the plot is trying to convey to the person who views your plot.

Widgets offer interactivity through buttons, drop-down menus, sliders, and textboxes. These widgets allow the person viewing the plot to interact with the plot and make changes to the way he or she wants to view it.

Visual attributes provide a vast range of visual enhancements to the plot, such as colors and fills for the lines and text, and interactivity enhancements such as the hover tool to hover over and select...

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