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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

The Bokeh Workflow – A Case Study

When it comes to building your very own Bokeh visualization from scratch, a good practice to develop is to never start with Bokeh. Instead, the ideal approach is to perform a little exploratory analysis on your data first, in order to visualize the application you can create using Bokeh that can deliver the most value to your users.

Such an approach, of first exploring your dataset, helps you formulate the ideal visualization that you might want to present to your audience.

In this chapter, you will learn the exact workflow that you need to follow, from when you get the data to the final visualization that you want to present.

Bokeh, like most data visualization tools, is best used in a workflow that follows a logical sequence of steps, which will allow you to deliver impactful insights to your audience. This workflow can be summarized...

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