Using IPython Notebooks with matplotlib

Python virtual environments are the recommended way of working with Python projects. They keep your system, Python, and default libraries safe from disruption. We will continue this tradition in this book, but you are welcome to transcend tradition and utilize the matplotlib library and the provided code in whatever way you see fit.

Using the native venv Python environment management package, each project may define its own versions of dependent libraries, including those of matplotlib and IPython. The sample code for this book does just that—listing the dependencies in one or more requirements.txt files.

With the addition of the nbagg IPython Notebook backend to matplotlib in version 1.4, users can now work with plots in a browser very much like they've been able to do in the GTK and Qt apps on the desktop. We will take full advantage of this new feature.

In the IPython examples of this book, most of the notebooks will start off with the following:

In [1]: import matplotlib matplotlib.use('nbagg')
In [2]: %matplotlib inline
In [3]: import matplotlib.pyplot as plt

A final note about IPython—the project has recently changed its name to Jupyter in an effort to embrace the language-agnostic growth the project and community has experienced as well as the architectural changes that will make the adding of new language backends much easier. The user experience will not change (except for the better), but you will notice a different name and logo when you open the chapter notebooks for this book.