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5. Using Annotations, Widgets, and Visual Attributes for Visual Enhancement

714 views · Published 11 June 2018 · 3:25 · Indexed 23 September 2026

Channel: Packt · 2018 · Science & Technology

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This is the “Code in Action” video for chapter 5 of Hands-on Data Visualization with Bokeh by Kevin Jolly, published by Packt. It includes the following topics:

00:00 Adding titles to plots
00:18 Adding legends to plots
00:35 Adding color maps to plots
 00:50 Creating a button widget
01:03 Creating the checkbox widget
01:13 Creating a drop-down menu widget
01:23 Creating the radio button widget
01:32 Creating a slider widget
01:41 Creating a text input widget
01:53 Creating a hover tooltip
02:18 Creating selections
02:30 Styling the title 
02:40 Styling the background
02:50 Styling the outline of the plot
03:05 Styling the labels


Hands-on Data Visualization is available from: 
Packt.com: 
Amazon: https://amzn.to/2LGvRlG

Adding a layer of interactivity to your plots and converting these plots into applications hold immense value in the field of data science. The standard approach to adding interactivity would be to use paid software such as Tableau, but the Bokeh package in Python offers users a way to create both interactive and visually aesthetic plots for free.

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Video created by Kevin Jolly

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