Chapter 1. First Steps

Whether you are an eager learner of data science or a well-grounded data science practitioner, you can take advantage of this essential introduction to Python for data science. You can use it to the fullest if you already have at least some previous experience in basic coding, writing general-purpose computer programs in Python, or some other data analysis-specific language, such as MATLAB or R.

The book will delve directly into Python for data science, providing you with a straight and fast route to solve various data science problems using Python and its powerful data analysis and machine learning packages. The code examples that are provided in this book don't require you to master Python. However, they will assume that you at least know the basics of Python scripting, data structures such as lists and dictionaries, and the working of class objects. If you don't feel confident about this subject or have minimal knowledge of the Python language, we suggest that before you read 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 tutorial of our own, which you can download from the Packt Publishing website, in order to provide an integration of the two aforementioned free courses.

In any case, don't be intimidated by our starting requirements; mastering Python for data science applications isn't as arduous as you may think. It's just that we have to assume some basic knowledge on the reader's part because our intention is to go straight to the point of using data science without having to explain too much about the general aspects of the language that we will be using.

Are you ready, then? Let's start!

In this short introductory chapter, we will work out the basics to set off in full swing and go through the following topics:

• How to set up a Python Data Science Toolbox
• Using IPython
• An overview of the data that we are going to study in this book