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ggplot2: Elegant Graphics for Data Analysis
Provides both rich theory and powerful applications Figures are accompanied by code required to produce them Full color figures
213 pages, Paperback
First published January 1, 2009
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553 people want to read
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Displaying 1 - 29 of 29 reviews
April 4, 2016
I only include this to compete with Al. The book is just ok, but ggplot2 is very sweet. [Check out R Graphics Cookbook by Winston Chang. It is mostly ggplot2 and I find it (and its website) a much better how to do it source than Hadley Wickhams's book - especially since ggplot2 was revised so that themes are so important. Note added 2-5-13.]
May 3, 2022
I read the in-development web version of the 3rd edition located here: , which sees Wickham joined by two co-authors that have written R packages that build on ggplot2.
I've been using ggplot2 for three years in earnest, although have dabbled for about five years now. I find myself constantly googling for ways to do the things that I want, and decided to just buckle down and spend a little time reading this book. I think I read the whole thing in about 2 hours on my phone (thank you Yihui Xie for making this possible with the bookdown package), although I skimmed the development chapters knowing that I am not yet ready to develop an extension to ggplot2.
I don't know why you're reading my review if you don't already know this, but ggplot2 is the de facto standard for static plots made in R for its extreme flexibility and adaptability. Base R plots are starting to look quite dated.
I've been using ggplot2 for three years in earnest, although have dabbled for about five years now. I find myself constantly googling for ways to do the things that I want, and decided to just buckle down and spend a little time reading this book. I think I read the whole thing in about 2 hours on my phone (thank you Yihui Xie for making this possible with the bookdown package), although I skimmed the development chapters knowing that I am not yet ready to develop an extension to ggplot2.
I don't know why you're reading my review if you don't already know this, but ggplot2 is the de facto standard for static plots made in R for its extreme flexibility and adaptability. Base R plots are starting to look quite dated.
January 29, 2015
It's the third book to conquer R from the painting perspective.So delicious !
December 13, 2014
ggplot2 is an elegant system. Would be interesting to know if incanted has/will get a similarly expressive plotting lib with sensible defaults.
It's temping to just jump in with a plotting library, but my guess is investing in learning how it works is both instructive as a case study in engineering something you may not think often, and to give yourself more direct feel for data. If you want to be a serious data scientist, you need to master all the basic ways of looking at data (including pivot charts and conditional coloring in spreadsheets btw)
So, this books should probably be part of solid data science prep.
Nits: look past these and focus on what the book has to offer. The book has some rough editorial spots (3d color space being related to 3 color sensing cells in the retina, which is misleading at best; calls a rel exponential to get a straight line on log log plot -- it has to be a polynomial (x^n, not n^x) to be a straight line.
It's temping to just jump in with a plotting library, but my guess is investing in learning how it works is both instructive as a case study in engineering something you may not think often, and to give yourself more direct feel for data. If you want to be a serious data scientist, you need to master all the basic ways of looking at data (including pivot charts and conditional coloring in spreadsheets btw)
So, this books should probably be part of solid data science prep.
Nits: look past these and focus on what the book has to offer. The book has some rough editorial spots (3d color space being related to 3 color sensing cells in the retina, which is misleading at best; calls a rel exponential to get a straight line on log log plot -- it has to be a polynomial (x^n, not n^x) to be a straight line.
January 7, 2018
Non è un libro che puoi leggere tutto di un fiato e poi riporlo dicendo “ok, ho capito�. È molto complesso ed è necessario utilizzarlo mentre si sperimenta la creazione di nuovi grafici in ggplot2 in ambiente R studio. I suggerimenti sono utilissimi per creare grafici che non hanno nulla da invidiare ai più blasonati (e costosi) software in circolazione.
Ggplot2 con altri packages di contorno dá modo di creare grafici a layers con multiple estetiche, facetting, colori e categorizzazioni che non hanno praticamente limiti. Non puoi farne a meno se produci informazioni visuali.
This book is essential for everyone interested in graphic production. With this packages of Hadley Wickham you can deal with every data and give to your audience beautiful and informative plot.
Don’t miss this book in your shelves. Ggplot2 is fantastic.
Ggplot2 con altri packages di contorno dá modo di creare grafici a layers con multiple estetiche, facetting, colori e categorizzazioni che non hanno praticamente limiti. Non puoi farne a meno se produci informazioni visuali.
This book is essential for everyone interested in graphic production. With this packages of Hadley Wickham you can deal with every data and give to your audience beautiful and informative plot.
Don’t miss this book in your shelves. Ggplot2 is fantastic.
May 23, 2020
If you're a beginner and want to learn ggplot2, this is the resource! End of story. Read this book first. Written by the creator of ggplot2 and the person who probably knows most about it. In addition the author has written multiple books and tutorials on R and he is an excellent communicator. Let me say it again, this is the one book to read about ggplot2.
It won't get you doing super advanced stuff, but it will cover VERY well the basics that most people never get and thus end up complicating their lives when dealing with ggplot2. This is an easy-to-read book that will set up solid foundations for doing all kinds of complicated graphs later on. However, trust me, you'll most likely not need those advanced stuff when you realize all the power that basic ggplot2 has.
In addition, this book will serve you as a reference guide whenever you forget how to do stuff with ggplot2. It is superbly and elegantly organized.
Do yourself a favor and get this book. (pdf available for free online)
It won't get you doing super advanced stuff, but it will cover VERY well the basics that most people never get and thus end up complicating their lives when dealing with ggplot2. This is an easy-to-read book that will set up solid foundations for doing all kinds of complicated graphs later on. However, trust me, you'll most likely not need those advanced stuff when you realize all the power that basic ggplot2 has.
In addition, this book will serve you as a reference guide whenever you forget how to do stuff with ggplot2. It is superbly and elegantly organized.
Do yourself a favor and get this book. (pdf available for free online)
March 22, 2018
If you use R and ggplot, this is the book to read to understand the principles behind ggplot so that you can fluently construct your own never-before-seen graphs by composing the library features. You'll also learn how to clean up all the labels and formatting so that your graphs look presentable. I recommend it for anyone who works in R and shows their graphs to others.
Do not get the older 2009 edition. Wickham has changed ggplot2 considerably since then and the older edition is now hopelessly obsolete; the examples will not work and you will only be confused.
Note that the source code for this book is online, so if you're willing to set up the somewhat fussy toolchain, you can build your own PDF.
Do not get the older 2009 edition. Wickham has changed ggplot2 considerably since then and the older edition is now hopelessly obsolete; the examples will not work and you will only be confused.
Note that the source code for this book is online, so if you're willing to set up the somewhat fussy toolchain, you can build your own PDF.
March 11, 2018
Having a "grammar of graphics" is such a useful and appealing concept. After years of hacking at the inconsistencies between various versions of the industry's dominant tool, I was quickly drawn to ggplot2. This guide by the package's creator is necessary and sufficient. The concepts are concise but thorough. Wickham often includes external examples to push the reader's thinking about what makes for an effective visualization. Working my way through the theory and the practice examples quickly accelerated my skills. More importantly, it's given me a framework for thinking about visualization in general.
December 16, 2020
I'm addicted to the statistical programming tool R. If you handle statistics in any way at all, it's a must. This book is really one man getting a grip on the visual display of quantitative information (incidentally, the title of another must-have book, by Edward Tufte) by producing some moderately easy packages to master. The output you can produce following Wickham is great. But this is more than a technical book, though it is that: it's an aid to thinking sensibly about the use and misuse of data.
May 4, 2020
Very good book in case you are looking to improve the quality of your graphs in R. I read it from cover to cover and although not everything was helfull, I found many tips that allowed me to further refine the appearance of my illustrations for journal purposes.
This is a good reference to go back in the future when I need more information specially if I need to develop new Additional graphs.
This is a good reference to go back in the future when I need more information specially if I need to develop new Additional graphs.
April 23, 2021
Great book for an even greater package. I found it just the right level, you can either read the documentation of everything as you go along and try out each one until this becomes a full reference book or just read the text as is and do the exercises as a learn-it-in-X-hours kind of book.
June 15, 2018
A must read for all R users
This is one of those books that is classed as a Classic. It should be part of anyones library who is serious about data analysis using R.
This is one of those books that is classed as a Classic. It should be part of anyones library who is serious about data analysis using R.
August 22, 2018
A definitive guide of visualization for R user.
October 9, 2018
A straightforward book describing how ggplot2 works through layers, with reproducible and enlightening code. It also goes beyond and describes briefly how dplyr package works.
December 28, 2018
I enjoyed this book very much. I understand ggplot2 quite a bit better now, which should improve my graphs. In addition, the book is organized well so you can use this as a reference while coding.
March 19, 2019
Good overview of the ggplot library with all the different types of graphics and functionality. However, it still is missing quite advanced stuff which you will need to look online for.
October 26, 2019
Essential resource for anyone who is serious about data visualization.
August 15, 2020
love it!
December 13, 2023
Not as good as R4DS, but awesome
March 23, 2024
Potencjalnie najgorsze co przeczytałem w tym roku (a w planach jest zakon drzewa pomarańczy). Mam nadzieję, że nikt tego nie wydrukował bo szkoda drzew na to.
April 2, 2014
This tutorial explains ggplot2 in detail with the best-organized and lucid explanation of the underlying logic I've seen. The examples are real and reproducible (a few typos but nothing drastic) and very revealing of the major features. The color pictures are color, a very nice touch in a graphics book, not all of them do that. I found the index very useful. There might be more examples and coverage of some of the edge features (radar charts, for example), and I think data preparation and handling deserves more detail (but you can get that elsewhere too). This is one of the more worthwhile R tutorials available. And the graphics are Great!
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December 28, 2021Nice and comprehensive tutorial on ggplot2, a plotting system implementing the grammar of graphics for R.
ggplot documentation .
I've put some code from the book into a markdown file. The code and the generated plots are available .
Python port for ggplot, aiming to have the same API, is available .
ggplot documentation .
I've put some code from the book into a markdown file. The code and the generated plots are available .
Python port for ggplot, aiming to have the same API, is available .
December 21, 2014
It is not common to get an introduction to a such a high quality software library by its developer.
ggPlot2 - is the R package which implements the grammar of graphics. The book contains many examples and successfuly explains how the library can be extended.
ggPlot2 - is the R package which implements the grammar of graphics. The book contains many examples and successfuly explains how the library can be extended.
June 15, 2016
Very comprehensive book on ggplot2. Lots of example code, so very useful for inspiration. The final few chapters includes stuff related to plotting such as wrangling (with tidyr) or summarizing (with dplyr) data before it can be plotted.
October 3, 2013
Un manuale di riferimento per disegnare grafici in R con ggplot2.
April 19, 2017
Unfortunatelly the fact the plots are printed in grayscale is making the reading impossible.
This does not take away the value of the book when used interactively...
This does not take away the value of the book when used interactively...
December 4, 2016
More theory than I wanted. Got to see the grammar of graphics. It won't be sitting close at hand as I code.
April 17, 2017
Great book. I decided it was time to stop doing all of my data viz in Excel, but ggplot syntax always confused me. After a brief introduction in Wickham's "R for Data Science" (also great), I took the time to acquaint myself with ggplot via this book, and am extremely pleased with the results - I feel much more confident in my ability to both choose a good visualization for the data I'm analyzing, and build beautiful graphics quickly.
February 10, 2019
This is another book that applies to one of my nascent passions: Statistical programming with R. This book brings forth the central visualization package in ggplot by its author Hadley Wickham. Like most of Hadley's works, the book is meticulously researched and extremely clear. It is a winner in accomplishing its goals of introducing visualization in R. It even contains a short section on modeling in R.
For those who don't know what R is, it is a statistical programming language. It helps statisticians (or programmers like myself) do statistical work efficiently. Hadley is a strong exponent in the community, and this work tells advanced users of R how to do visualization work. It is not meant as an introduction to R (i.e., R for beginners), but as a follow-up book, much like two of Hadley's other works, Advanced R or R Packages.
Hadley uses Leland Wilkinson's The Grammar of Graphics to dissect how graphing works. Data is abstracted from an aesthetic mapping which controls how the data is communicated (e.g., through bar graphs, line graphs, pie graphs). Then these are combined together to give the programmer more control of the graph.
By existing within a programming language (R), this method gives the programmer/user much more control over the final product. Thus, high quality visualizations become a reality with ggplot. Unfortunately, one has to spend time reading a book in order to learn how to do that, but that is a small price to pay for enhanced quality and control. This book is worth the time.
For those who don't know what R is, it is a statistical programming language. It helps statisticians (or programmers like myself) do statistical work efficiently. Hadley is a strong exponent in the community, and this work tells advanced users of R how to do visualization work. It is not meant as an introduction to R (i.e., R for beginners), but as a follow-up book, much like two of Hadley's other works, Advanced R or R Packages.
Hadley uses Leland Wilkinson's The Grammar of Graphics to dissect how graphing works. Data is abstracted from an aesthetic mapping which controls how the data is communicated (e.g., through bar graphs, line graphs, pie graphs). Then these are combined together to give the programmer more control of the graph.
By existing within a programming language (R), this method gives the programmer/user much more control over the final product. Thus, high quality visualizations become a reality with ggplot. Unfortunately, one has to spend time reading a book in order to learn how to do that, but that is a small price to pay for enhanced quality and control. This book is worth the time.
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