The code examples that are provided along with the chapters don't require you to master Python. However, they will assume that you've previously obtained a working knowledge of at least the basics of Python scripting. They will also assume, in particular, that you know about data structures, such as lists and dictionaries, and you have an idea about how to make class objects work.
If you don't feel confident about the aforementioned subjects or have minimal knowledge of the Python language, we suggest that before you start reading this book, you should take an online tutorial, such as the Code Academy course at http://www.codecademy.com/en/tracks/python or Google's Python class at https://developers.google.com/edu/python/. Both the courses are free, and in a matter of a few hours of study, they should provide you with all the building blocks that will ensure that you enjoy this book to the fullest.
We have also prepared a few notes, which are arranged in this brief but challenging bonus chapter, in order to highlight the importance and strengthen your knowledge of certain aspects of the Python language.
In this bonus chapter, you will learn the following:
What you should know about Python to be an effective data scientist
The best resources to learn Python by watching videos
The best resources to learn Python by directly writing and testing code
The best resources to learn Python by reading