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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
Languages
Tools
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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

Plotting with glyphs

In this section, we will learn how to plot the following types of plot using glyphs:

  • Line plots: Line plots offer a way of visualizing the movements of points along the x-and y-axes in the form of a line. These plots are useful for performing time series analytics.
  • Bar plots: Bar plots are useful for indicating the count of each category of a particular column or field in your dataset.
  • Patch plots: Patch plots are used to indicate a region of points in a particular shade of color. Such plots can be used to distinguish different groups within the same dataset.
  • Scatter plots: Scatter plots are used to visualize the relationship between two variables and to indicate the strength of correlation between them.

Creating line plots

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