August 2021
Beginner to intermediate
280 pages
6h 12m
English
Content preview from Data Science at the Command Line, 2nd Edition
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.
Chapter 1. Introduction
This book is about doing data science at the command line. My 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 data science and command line in the book’s title requires an explanation. How can a technology that is more than 50 years old1 be of any use to a field that is only a few years young?
Today, data scientists can choose from an overwhelming collection of exciting technologies and programming languages. Python, R, Julia, and Apache Spark are but a few examples. You may already have experience in one or more of these. And if so, 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 valid questions. In this opening chapter I will answer these questions as follows. First, I provide a practical definition of data science that will act as the backbone of this book. Second, I’ll list five important advantages of the command line. By the end of this chapter, I hope to have convinced you that the command line is indeed worth learning for doing data science.
Data Science Is OSEMN
The field of data science is still in its infancy, and as such, there exist various definitions of what it encompasses. Throughout this book I employ a very practical definition devised by Hilary Mason and Chris H. Wiggins.2 They define data science according ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.