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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

Creating widgets to add interactivity to plots

One of Bokeh's most unique features is the ability to add widgets that add interactivity to plots. Widgets allow the user of the plot to change what they want to see by making selections, clicking on buttons, and typing into textboxes. In this section, you will learn about all the widgets that Bokeh can add to your Toolbelt.

The two imports that you will need to create and output any kind of widget are given here:

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

Creating a button widget

Buttons allow a user to click and make a selection. We can create a button widget in Bokeh by using the code shown here:

#Import the required packages

from bokeh.models...
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