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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 Layouts for Effective Presentation

While plotting multiple plots, it is always best to make use of layouts in order to display the plots side by side, or vertically on top of each other, in order to make statistical comparisons between the two plots and make them visually appealing at the same time.

The use of layouts, tabs, and grids effectively while creating plots with Bokeh will also allow you to link multiple plots together by making use of the same axes. This makes the comparison of multiple plots much more accurate than if you were to create the plots in separate cells in your Jupyter Notebook.

In this chapter, you will learn how to:

  • Create multiple plots along the same row
  • Create multiple plots along the same column
  • Create multiple plots in a row and column
  • Create multiple plots using a tabbed layout
  • Create a robust grid layout
  • Link multiple plots together
...
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