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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

Understanding the difference between pyplot and OO API


This recipe will try to explain some of the programming interfaces in matplotlib and make a comparison of pyplot and object-oriented API (Application Programming Interface). Depending on the task at hand, this will allow us to decide why and when to use either of these interfaces.

Getting ready

When the matplotlib library was introduced, it was similar to many open source projects—there was no proper (free) solution to the problem a person had, so he wrote one. The problem encountered with MATLAB® was with respect to performance for the task in hand (http://www.aosabook.org/en/matplotlib.html), and the original author already had knowledge of both MATLAB® and Python, so he started writing matplotlib as a solution for his need for the current project.

This is the main reason matplotlib has a MATLAB®-like interface that allows one to quickly plot data without worrying about background details, such as which platform matplotlib is running...

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