Book Image

Python Data Visualization Cookbook (Second Edition)

Book Image

Python Data Visualization Cookbook (Second Edition)

Overview of this book

Python Data Visualization Cookbook will progress the reader from the point of installing and setting up a Python environment for data manipulation and visualization all the way to 3D animations using Python libraries. Readers will benefit from over 60 precise and reproducible recipes that will guide the reader towards a better understanding of data concepts and the building blocks for subsequent and sometimes more advanced concepts. Python Data Visualization Cookbook starts by showing how to set up matplotlib and the related libraries that are required for most parts of the book, before moving on to discuss some of the lesser-used diagrams and charts such as Gantt Charts or Sankey diagrams. Initially it uses simple plots and charts to more advanced ones, to make it easy to understand for readers. As the readers will go through the book, they will get to know about the 3D diagrams and animations. Maps are irreplaceable for displaying geo-spatial data, so this book will also show how to build them. In the last chapter, it includes explanation on how to incorporate matplotlib into different environments, such as a writing system, LaTeX, or how to create Gantt charts using Python.
Table of Contents (16 chapters)
Python Data Visualization Cookbook Second Edition
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
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...