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Jupyter Cookbook

You're reading from   Jupyter Cookbook Over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788839440
Length 238 pages
Edition 1st Edition
Languages
Tools
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Author (1):
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Dan Toomey Dan Toomey
Author Profile Icon Dan Toomey
Dan Toomey
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Toc

Table of Contents (12) Chapters Close

Preface 1. Installation and Setting up the Environment FREE CHAPTER 2. Adding an Engine 3. Accessing and Retrieving Data 4. Visualizing Your Analytics 5. Working with Widgets 6. Jupyter Dashboards 7. Sharing Your Code 8. Multiuser Jupyter 9. Interacting with Big Data 10. Jupyter Security 11. Jupyter Labs

Another ipywidgets linking example


We can link one of the controls to a graphic display, which I think is much more interesting.

How to do it...

We can use the following code:

%matplotlib inline
from ipywidgets import interactive
import matplotlib.pyplot as plt
import numpy as np

def f(r):
 plt.axes()
 circle = plt.Circle((0, 0), radius=r, fc='y')
 plt.gca().add_patch(circle)
 plt.axis('scaled')
 plt.show()

interactive_plot = interactive(f, r=(0.0, 1.0))
output = interactive_plot.children[-1]
output.layout.height = '350px'
interactive_plot

The display looks like is:

How it works...

Changing the position of the slide bar changes the value of the slide bar. The new value of the slide bar is used to repaint the circle image using the slide bar value as the radius of the circle.

Just as we saw in the previous linking example, the underlying code is attaching an event listener (the f function we defined just now) to the slide bar. When the value of the slide bar changes, it calls upon the event handler...

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