Graphing Data with R: An Introduction

by John Jay Hilfiger

It’s much easier to grasp complex data relationships with a graph than by scanning numbers in a spreadsheet. This introductory guide shows you how to use the R language to create a variety of useful graphs for visualizing and analyzing complex data for science, business, media, and many other fields. You’ll learn methods for highlighting important relationships and trends, reducing data to simpler forms, and emphasizing key numbers at a glance. Anyone who wants to analyze data will find something useful here―even if you don’t have a background in mathematics, statistics, or computer programming. If you want to examine data related to your work, this book is the ideal way to start.

Genres: Computer Science

333 pages, Paperback

First published November 13, 2015

Reviews

[Arthur · Rating 3 out of 5]

Not a boring read, I enjoyed it, but the book does only one thing well: it will make you comfortable charting the most commonly used in stats graphs. I desired the book could show more techniques on how to convert between various data storage (or representation) modes as it is likely my data could be produced differently or stored in odd formats.
Another snug a reader may hit is that too many packages used in the book do not work with the most recent version of R (3.2.2 as of the time of writing).
The book could include a chapter on how to package the graphs into presentable formats, e.g. made it a publication or an infographic.
Lastly, sadly, the animated graphics were not covered, but I suspect they constitute a necessary part.

[Oconnor · Rating 5 out of 5]

Its hard to believe that a book about R programming could read so easily. At first I thought that the graphs discussed were a little elementary. However, I got hooked on the author's command of the R packages and started keeping a list of the new-to-me packages and data sets. There were a lot! In addition, the appendix is awesome with hints about how to trouble shoot troubling R code as well as data resources and an index to packages and commands included in the book. And, there are fun R exercises with each chapter with answers in the back. An R lover's dream!