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Python Data Visualization Cookbook (Second Edition)

You're reading from   Python Data Visualization Cookbook (Second Edition) Visualize data using Python's most popular libraries

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Product type Paperback
Published in Nov 2015
Publisher
ISBN-13 9781784396695
Length 302 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (11) Chapters Close

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 the Right Plots to Understand Data 8. More on matplotlib Gems 9. Visualizations on the Clouds with Plot.ly Index

Creating contour plots


A contour plot displays the isolines of a matrix. Isolines are curves where a function of two variables has the same value.

In this recipe, you will learn how to create contour plots.

Getting ready

Contours are represented as contour plots of the matrix Z, where Z is interpreted as height with respect to the XY plane. Z is of minimum size 2 and must contain at least two different values.

The problem with contour plots is that if they are coded without labeling the isolines, they are rendered pretty useless as we cannot decode the high points from the low points or find local minimas.

Here, we need to label the contour as well. The labeling of isolines can be done by using either labels (clabel()) or colormaps. If your output medium permits the use of color, colormaps are preferred because viewers will be able to decode data more easily.

The other risk with contour plots is in choosing the number of isolines to plot. If we choose too many, the plot becomes too dense to decode...

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