Book Image

Matplotlib for Python Developers

Book Image

Matplotlib for Python Developers

Overview of this book

Providing appealing plots and graphs is an essential part of various fields such as scientific research, data analysis, and so on. Matplotlib, the Python 2D plotting library, is used to produce publication-quality figures in a variety of hardcopy formats and interactive environments across platforms. This book explains creating various plots, histograms, power spectra, bar charts, error charts, scatter-plots and much more using the powerful Matplotlib library to get impressive out-of-the-box results. This book gives you a comprehensive tour of the key features of the Matplotlib Python 2D plotting library, right from the simplest concepts to the most advanced topics. You will discover how easy it is to produce professional-quality plots when you have this book to hand. The book introduces the library in steps. First come the basics: introducing what the library is, its important prerequisites (and terminology), installing and configuring Matplotlib, and going through simple plots such as lines, grids, axes, and charts. Then we start with some introductory examples, and move ahead by discussing the various programming styles that Matplotlib allows, and several key features. Further, the book presents an important section on embedding applications. You will be introduced to three of the best known GUI libraries 'GTK+, Qt, and wxWidgets' and presented with the steps to implement to include Matplotlib in an application written using each of them. You will learn through an incremental approach: from a simple example that presents the peculiarities of the GUI library, to more complex ones, using GUI designer tools. Because the Web permeates all of our activities, a part of the book is dedicated to showing how Matplotlib can be used in a web environment, and another section focuses on using Matplotlib with common Python web frameworks, namely, Pylons and Django. Last, but not least, you will go through real-world examples, where you will see some real situations in which you can use Matplotlib.
Table of Contents (14 chapters)
Matplotlib for Python Developers
About the Author
About the Reviewers

IPython support

We have already used IPython throughout the chapter, and we saw how useful it is. Therefore, we want to give it a better introduction.

Matplotlib tends to defer drawing till the end, since it's an expensive operation, and updating the plot at every property change would slow down the execution.

That's fine for batch operations, but when we're working with the Python shell, we want to see updates at every command we type. Easy to say, but difficult to implement.

Most GUI libraries need to control the main loop of execution of Python, thus preventing any further interaction (that is, you can't type while viewing the image). The only GUI that plays nice with Python's standard shell is Tkinter.


Tkinter is the standard Python interface to the Tk GUI library.

So you might want to set the backend property to TkAgg and interactive to True when using the Python interpreter interactively.

IPython uses a smart method to handle this situation—it spawns a thread to execute GUI library...