Preface
A NOTE FOR EARLY RELEASE READERS
With Early Release ebooks, you get books in their earliest form—the
author’s raw and unedited content as they write—so you can take
advantage of these technologies long before the official release of these
titles.
If you have comments about how we might improve the content and/or
examples in this book, or if you notice missing material within this
chapter, please reach out to the editor at jleonard@oreilly.com.
What Is Data Science?
This is a book about doing data science with Python, which immediately
begs the question: what is data science? It’s a surprisingly hard definition to
nail down, especially given how ubiquitous the term has become. Vocal
critics have variously dismissed the term as a superfluous label (after all,
what science doesn’t involve data?) or a simple buzzword that only exists to
salt resumes and catch the eye of overzealous tech recruiters.
In my mind, these critiques miss something important. Data science, despite
its hype-laden veneer, is perhaps the best label we have for the cross-
disciplinary set of skills that are becoming increasingly important in many
applications across industry and academia. This cross-disciplinary piece is
key: in my mind, the best extisting definition of data science is illustrated
by Drew Conway’s Data Science Venn Diagram, first published on his blog
in September 2010:
