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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

Verifying your installation

Once you have installed Bokeh, you will want to verify that it is correctly installed. In order to verify the installation and create all your Bokeh plots, you'll need a Jupyter Notebook. If you are not familiar with working with a Jupyter Notebook before or have installed, the following link will provide you with a step-by-step tutorial on how to install and work with Jupyter Notebook: http://jupyter.org/install.

You can verify your installation of Bokeh by generating a simple line plot using a Jupyter Notebook with the following code:

from bokeh.plotting import figure, output_file, show

#HTML file to output your plot into
output_file("bokeh.html")

#Constructing a basic line plot

x = [1,2,3]
y = [4,5,6]

p = figure()

p.line(x,y)

show(p)

This should open up a new tab on your browser with a plot illustrated as follows:

Don't worry too much about what the code does for now. If you have got the preceding plot, you should be satisfied that Bokeh has been successfully installed on your local machine.
You have been reading a chapter from
Hands-On Data Visualization with Bokeh
Published in: Jun 2018
Publisher: Packt
ISBN-13: 9781789135404
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