IPython Magic Functions

Both Python for Data Science for Dummies and Machine Learning for Dummies rely on a version of Anaconda that uses IPython as part of its offering.Theoretically, you could also use Anaconda with Beginning Programming with Python For Dummies, but that book is designed to provide you with an experience that relies on the strict Python offerings (without the use of external tools). In other words, the procedures in this third book are designed for use with IDLE, the IDE that comes with Python. IPython extends the development environment in a number of ways, one of which is the use of magic functions. You see the magic functions in the code of the first two books as calls that begin with either one or two percent signs (% or %%). The most common of these magic functions is %matplotlib, which controls how IPython Notebook or Jupyter Notebook display plot output from the code.

You can find a listing of the most common magic functions in the Python for Data Science for Dummies Cheat Sheet. Neither of the first two books use any other magic functions, so this is also a complete list of magic functions that you can expect to find in our books. However, you might want to know more. Fortunately, the site at https://damontallen.github.io/IPython-quick-ref-sheets/ provides you with a complete listing of the magic commands (and a wealth of other information about IPython).

Of course, you might choose to use another IDEā€”one that isn’t quite so magical as Anaconda provides through IPython. In this case, you need to remove those magic commands. Removing the commands won’t affect functionality of the code. The example will still work as explained in the book. However, the way that the IDE presents output could change. For example, instead of being inline, plots could appear in a separate window. Even though using a separate window is less convenient, either method works just fine. If you ever do encounter a magic function-related problem, please be sure to let me know at [email protected].

 

Author: John

John Mueller is a freelance author and technical editor. He has writing in his blood, having produced 122 books and over 600 articles to date. The topics range from networking to artificial intelligence and from database management to heads-down programming. Some of his current offerings include topics on machine learning, AI, Python programming, Android programming, and C++ programming. His technical editing skills have helped over more than 70 authors refine the content of their manuscripts. John also provides a wealth of other services, such as writing certification exams, performing technical edits, and writing articles to custom specifications. You can reach John on the Internet at [email protected]

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