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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

Creating multiple plots in the same column

In this section, you will learn how to stack multiple plots vertically on top of each other to create a column-wise comparison of plots. We will be using the two scatter plots that we created earlier in the chapter to achieve this.

In order to create a vertical layout of plots, we use the code shown here:

#Import the required packages

from bokeh.layouts import column
from bokeh.io import output_file, show

#Group the 2 plots into a 'column' layout

col_layout = column(plot1,plot2)

#Output the plot

output_file('vertical.html')

show(col_layout)

This results in a layout of plots, as illustrated here:

Plots 1 and 2 in a vertical layout

In the previous code, we used the column function, which takes in the plots that we want to stack vertically on top of each other as input arguments to create the vertical layout of plots. This...

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