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Python Data Visualization Cookbook

You're reading from  Python Data Visualization Cookbook

Product type Book
Published in Nov 2013
Publisher Packt
ISBN-13 9781782163367
Pages 280 pages
Edition 1st Edition
Languages
Author (1):
Igor Milovanovic Igor Milovanovic
Profile icon Igor Milovanovic

Table of Contents (15) Chapters

Python Data Visualization Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Preparing Your Working Environment 2. Knowing Your Data 3. Drawing Your First Plots and Customizing Them 4. More Plots and Customizations 5. Making 3D Visualizations 6. Plotting Charts with Images and Maps 7. Using Right Plots to Understand Data 8. More on matplotlib Gems Index

Defining axis lengths and limits


This recipe will demonstrate a variety of useful axis properties around limits and lengths that we can configure in matplotlib.

Getting ready

For this recipe we want to fire up IPython:

$ ipython --pylab

How to do it...

Start experimenting with various properties of axes. Just calling an empty axis() function will return default values for the axis:

In [1]: axis()
Out[1]: (0.0, 1.0, 0.0, 1.0)

Note that if you are in interactive mode and are using a windowing backend, a figure with an empty axis will be displayed.

Here the values represent xmin, xmax, ymin, and ymax respectively. Similarly, we can set values for the x and y axes:

In [2]: l = [-1, 1, -10, 10]

In [3]: axis(l)
Out[3]: [-1, 1, -10, 10]

Again, if you are in interactive mode, this will update the same figure. Furthermore, we can also update any value separately using keyword arguments (**kwargs), setting just xmax to a certain value.

How it works...

If we don't use axis() or other settings, matplotlib...

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