Data Science at the Command Line

Chapter 1. Introduction

This book is about doing data science at the command line. Our aim is to make you a more efficient and productive data scientist by teaching you how to leverage the power of the command line.

Having both the terms “data science” and “command line” in the title requires an explanation. How can a technology that’s over 40 years old¹ be of any use to a field that’s only a few years young?

Today, data scientists can choose from an overwhelming collection of exciting technologies and programming languages. Python, R, Hadoop, Julia, Pig, Hive, and Spark are but a few examples. You may already have experience in one or more of these. If so, then why should you still care about the command line for doing data science? What does the command line have to offer that these other technologies and programming languages do not?

These are all valid questions. This first chapter will answer these questions as follows. First, we provide a practical definition of data science that will act as the backbone of this book. Second, we’ll list five important advantages of the command line. Third, we demonstrate the power and flexibility of the command line through a real-world use case. By the end of this chapter we hope to have convinced you that the command line is indeed worth learning for doing data science.

Overview

In this chapter, you’ll learn:

• A practical definition of data science

• What the command line is exactly and how you can use it

• Why the command line is a ...