ggplot2: Elegant Graphics for Data Analysis (Use R!)

ggplot2: Elegant Graphics for Data Analysis (Use R!)

ggplot2: Elegant Graphics for Data Analysis (Use R!)

  • Used Book in Good Condition

Provides both rich theory and powerful applications

Figures are accompanied by code required to produce them

Full color figures

List Price: $ 69.95

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3 comments

  1. 56 of 57 people found the following review helpful
    5.0 out of 5 stars
    create elegant plots with ease, August 18, 2009
    By 
    Sunny (Chapel Hill, NC) –

    This review is from: ggplot2: Elegant Graphics for Data Analysis (Use R!) (Paperback)
    ggplot2 is an R package for creating graphs. If you have used R, you may have observed that you can control almost all aspects of a graph you create. This flexibility can come at a price in having to be familiar with several options and syntax that is not always intuitive. ggplot2 overcomes this hurdle because it is based on a grammar. After one invests the time to learn this grammar, one can create customizable plots with default settings that are aesthetically pleasing. ggplot2 automatically takes care of details such as legends. This book covers ggplot2 plotting in a clear manner. It is filled with examples, simple and complex, and all code is available from the author’s website. It covers the logic of the grammar, basic plots, combining plots, how to represent subsets, and even how to format data so that it can be plotted. I highly recommend this book. You will produce plots exactly as you want them (with ease), and learn about different ways to display your data. Be sure to invest some time up front to develop an understanding rather than cutting and pasting code. This investment will pay off.

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  2. 32 of 32 people found the following review helpful
    5.0 out of 5 stars
    shows how to build gorgeous statistical graphics, August 20, 2009
    By 
    M. Driscoll (San Francisco, CA) –
    (REAL NAME)
      

    This review is from: ggplot2: Elegant Graphics for Data Analysis (Use R!) (Paperback)
    This book is a practical overview of ggplot2, a new graphics package available for R – and I would argue the best statistical graphics package for any language. Why? Because it allows users to create gorgeous, elegant graphics with a minimum of effort.

    As Wickham details in this lucid book, ggplot2 is based on a grammar of graphics, which conceives of statistical plots not as fixed chart typologies (bar, line, pie) to be filled with data, but as graphical compositions built up from component parts (scales, coordinate systems, geometric objects).

    Before embarking on several chapters describing how to control various elements of the grammar, Wickham dives in (with Chapter 2, “Getting started with qplot”) and guides users on how to rapidly create graphics with the qplot (for “quick plot”).

    Two elements struck me in reading this book and beginning to use ggplot2:

    (i) It possesses excellent defaults. Wickham has put an enormous amount of thought into the default aesthetics. From light gray plotting backgrounds to monochromatically spaced color palettes, ggplot2 builds on decades of work done in the information visualization space.

    (ii) It possesses an intuitive syntax. Creating graphics in R often requires specifying an enormous number of parameters. ggplot2’s syntax – the ability to “build up” a graph from layer by layer – allows for an intuitive way to control complexity.

    If you are serious about statistical graphics — and even if you are new to R — this book is an essential volume.

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  3. 26 of 26 people found the following review helpful
    4.0 out of 5 stars
    Nice resource, but already out of date, March 5, 2012
    By 
    Joshua A. Shapiro (Princeton, NJ) –
    (REAL NAME)
      

    Verified Purchase(What’s this?)
    This review is from: ggplot2: Elegant Graphics for Data Analysis (Use R!) (Paperback)
    ggplot2 is a great plotting packaged for R, and this is a good reference for the system, written by the author of the package. It does a good job of explaining the grammar of graphics on which the plotting system is based, and how that is implemented in the R package. While it can takes some time to adapted to a syntax that is very different from the base plotting syntax, the overall flexibility of the system is worth the effort, and the plots it produces are quite beautiful.

    Fortunately for users of ggplot2, but unfortunately for my review of this book, the ggplot2 package is still rapidly evolving. Much has already changed since the publication of this book, so there are many parts of the ggplot2 system that are not covered by this book. I do not think there are many places that the code in the book will not work anymore, but there are some significant recent additions that are completely unmentioned. Since most of the important information is available online, it is hard to recommend the book too strongly, as the cost is not insignificant. On the other hand, I am happy to have supported the further development of the ggplot2 package (and other R projects) by whatever portion of the proceeds made it back to Hadley Wickham.

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