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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

Adding a data table to the figure


Although matplotlib is mainly a plotting library, it helps us with small errands when we are creating a chart, such as having a neat data table beside our beautiful chart. In this recipe we will be learning how to display a data table alongside the plots in the figure.

Getting ready

It is important to understand why we are adding a table to a chart. The main intention of plotting data visually is to explain the otherwise not understandable (or hardly understandable) data values. Now, we want to add that data back. It is not wise just to cram a big table with values underneath the chart.

But, carefully picked, maybe the summed or highlighted values from the whole, charted dataset can identify important parts of the chart or emphasize the important values for those places where the exact value (for example, yearly sales in USD) is important (or even required).

How to do it...

Here's the code to add a sample table to our figure:

import matplotlib.pylab as plt
import...
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