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Python Data Visualization Cookbook (Second Edition)

You're reading from  Python Data Visualization Cookbook (Second Edition)

Product type Book
Published in Nov 2015
Publisher
ISBN-13 9781784396695
Pages 302 pages
Edition 1st Edition
Languages

Table of Contents (16) Chapters

Python Data Visualization Cookbook Second Edition
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
Preparing Your Working Environment Knowing Your Data Drawing Your First Plots and Customizing Them More Plots and Customizations Making 3D Visualizations Plotting Charts with Images and Maps Using the Right Plots to Understand Data More on matplotlib Gems Visualizations on the Clouds with Plot.ly Index

Customizing grids


A grid is usually handy to have under lines and charts as it helps the human eye spot differences in patterns 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, you 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. The basic call to plt.grid() will toggle the grid visibility in the current interactive session started by the last IPythonPyLab 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:

We...

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