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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 Book
Published in Jun 2018
Publisher Packt
ISBN-13 9781789135404
Pages 174 pages
Edition 1st Edition
Languages
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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

Summary

This chapter has given you an introduction to what glyphs are and how you can use them to create fundamental plots using Bokeh. We also looked at how to customize these plots further.

Glyphs are the fundamental building blocks of Bokeh and are required in order to create more complex, and statistically significant, plots in the future.

In this chapter, you learned how to create four different plots using glyphs. Line plots are commonly used in time series analytics, bar plots are commonly used to compare counts between different categories, patch plots are commonly used to highlight an area of points, and scatter plots, are commonly used to map a relationship between two or more variables.

In the upcoming chapter, we will take these concepts and use them to plot diagrams using NumPy arrays and Pandas DataFrames.

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