This book presumes some familiarity with Python 3 and general concepts of application development. We won't look deeply at subtle or complex features of Python; we'll avoid much consideration of the internals of the language.

We'll presume some familiarity with functional programming. Since Python is not a functional programming language, we can't dig deeply into functional concepts. We'll pick and choose the aspects of functional programming that fit well with Python and leverage just those that seem useful.

Some of the examples use Exploratory Data Analysis (EDA) as a problem domain to show the value of functional programming. Some familiarity with basic probability and statistics will help with this. There are only a few examples that move into more serious data science.

You'll need to have Python 3.3 or 3.4 installed and running. For more information on Python, visit http://www.python.org/.

In Chapter 14, The PyMonad Library, we'll look at installing this additional library. If you have Python 3.4 ,which includes pip and Easy Install, this will be very easy. If you have Python 3.3, you might have already installed pip or Easy Install or both. Once you have an installer, you can add PyMonad. Visit https://pypi.python.org/pypi/PyMonad/ for more details.