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Python Data Visualization Cookbook

You're reading from   Python Data Visualization Cookbook As a developer with knowledge of Python you are already in a great position to start using data visualization. This superb cookbook shows you how in plain language and practical recipes, culminating with 3D animations.

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Product type Paperback
Published in Nov 2013
Publisher Packt
ISBN-13 9781782163367
Length 280 pages
Edition 1st Edition
Languages
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Author (1):
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Igor Milovanovic Igor Milovanovic
Author Profile Icon Igor Milovanovic
Igor Milovanovic
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Table of Contents (15) Chapters Close

Python Data Visualization Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Preparing Your Working Environment FREE CHAPTER 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

Customizing grids


A grid is usually handy to have under lines and charts as it helps the human eye spot differences in pattern and compare plots visually in the figure. To be able to set up how visibly, how frequently, and in what style the grid is displayed—or whether it is displayed at all—we should use matplotlib.pyplot.grid.

In this recipe we will be learning how to turn the grid on and off, and how to change the major and minor ticks on a grid.

Getting ready

The most frequent grid customization is reachable in the matplotlib.pyplot.grid helper function.

To see the interactive effect of this, you should run the following under ipython –pylab. The basic call to plt.grid() will toggle grid visibility in the current interactive session started by the last IPython PyLab environment:

In [1]: plt.plot([1,2,3,3.5,4,4.3,3])
Out[1]: [<matplotlib.lines.Line2D at 0x3dcc810>]

Now we can toggle the grid on the same figure:

In [2]: plt.grid()

We turn the grid back on, as shown in the following plot...

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