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, in writing general-purpose computer programs in Python, or in some other data analysis-specific language such as MATLAB or R.
This 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 be a master of Python. However, they will assume that you at least know the basics of Python scripting, including data structures such as lists and dictionaries, and the workings of class objects. If you don't feel confident about these subjects or have minimal knowledge of the Python language, before reading this book, we suggest that you take an online tutorial. There are many possible choices, but we suggest starting with the suggestions from the official beginner's guide to Python from the Python Foundation or directly going to the free Code Academy course at https://www.codecademy.com/learn/python. Using Code Academy's tutorial, or any other alternative you may find useful, in a matter of a few hours of study, you should acquire all the building blocks that will ensure you enjoy this book to the fullest. We have also prepared a tutorial of our own, which can be found in the last part of this book, 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 enough 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 doing 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 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 your browser as an interactive notebook, to code with Python using Jupyter
- An overview of the data that we are going to study in this book
