Book Image

Data Smart

By : John W. Foreman
Book Image

Data Smart

By: John W. Foreman

Overview of this book

Data Science gets thrown around in the press like it's magic. Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions. But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope. Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, math and the magic, behind big data.
Table of Contents (18 chapters)
Free Chapter
1
Cover
2
Credits
3
About the Author
4
About the Technical Editors
5
Acknowledgments
18
End User License Agreement

Doing Some Actual Data Science

At this point you've learned how to work with variables and datatypes, hand-jam data, and read it in from a CSV. But how do you actually use the algorithms you learned earlier in this book? Since you already have the wine data loaded up, you'll start with a little k-means clustering.

Spherical K-Means on Wine Data in Just a Few Lines

In this section, you'll cluster based on cosine similarity (also called spherical k-means). And in R, there's a spherical k-means package you can load, called skmeans. But skmeans doesn't come baked into R; it's written by a third party as a package that you can load into R and use. Essentially, these geniuses have done all the work for you, and you just have to stand on their shoulders.

Like most R packages, you can read up on it and install it from the Comprehensive R Archive Network (CRAN). CRAN is a repository of many of the useful packages that can be loaded into R to extend its functionality...