Press reviews, feedbacks, …

Paul Murrell updated his R package ‘dvir’ and added support for the LuaTeX engine to draw typeset text in R. He reconstructed my example „Areas Under a Time Series“. His result is obviously convincing (04/2020).

*„The main change from the second edition is that Part IV has been restructured. In the second edition, this part of the book attempted to cover a wide range of applications of R Graphics, but the number of ways that R graphics can be used has grown to the point that Part IV would require several volumes by itself; something that is reflected in the fact that there are now many more books that cover different aspects of producing plots in R (e.g., Thomas Rahlf’s Data Visualisation with R and Ocar Perpinan Lamigueiro’s Displaying Time Series, Spatial, and Space-time Data with R).“*

Paul Murrell, R Graphics, Third Edition, Boca Raton: Chapman and Hall/CRC 2018.

*„This is the book I would recommend for those who want to teach data visualisation. Examples are nice, and ready to be published. From one example to the following one, the difficulty is very progressive. It’s a very good teaching material.“*

Sébastien Lê, Co-author of Exploratory Multivariate Analysis by Example Using R and the FactoMineR package, a package dedicated to multivariate exploratory analysis. (11/2018)

Good news: The book is free for all ACM Members (Association for Computing Machinery):

Simple Bar Chart Example adopted with ggplot2 on RPubs by Nguyen Chi Dung (6/2018)

*„…provides the reader with a broad and excellent overview of the various possibilities offered by R’s standard graphics package. (…) Overall, the book can especially be recommended for students and researchers that are already familiar with R and who intend to find suitable methods for visualizing their data in real world applications. Furthermore, it can also be helpful for students who want a broad overview of R and its visualization capabilities.“*

M. Hüsch, Statistical Papers (2018).

Ulrike Grömping was inspired by the book to develope a package prepplot for making it easier to customize figure regions for base R graphics. See also her Vignette.

Recommendation by Frank E Harrell (Statistical Graphics Course and Graphics for Clinical Trials).

Recommendation INSTITUTE FOR WEB TECHNOLOGIES & APPLICATIONS

*„Very interesting book to get into R for and data visualisation, with great examples on a diversity of topics.“*

Andre R. S. Marcal, Assistant Professor, Faculdade de Ciencias, Universidade do Porto, Departamento de Matematica, 2017/12.

Some examples of the book have been added to the list Great dataviz examples in rstats, Prof. S. Sauer, Institute of Business Psychology, FOM Munich, 2017/11.

*„I definitely recommend this book. The example-based approach is very successful for introducing readers to R’s graphical capabilities; readers can learn proficiency in using base R graphics for obtaining exactly the static presentation figure they envision – including ambitious infographics. (…) Last but (by far) not least, the book can be used as a collection of ideas for useful, informative and beautiful graphical displays.“*

Prof. Dr. Ulrike Grömping, Journal of Statistical Software 81 (2017).

Nice application of the book’s Polar Area Charts example in: „Decision Support for Policymaking: Causal Inference Algorithm and Case Study“ from Data Science department at the IBM T. J. Watson Research Center, 2017/7.

*„I like the book. With my two doctoral course students, I use it as a text book for my ‚Doctoral Dissertation Research‘ course in this semester.“*

Prof. Dae-Heung Jang, Department of Statistics, Pukyong National University, Busan, South Korea, 2017/9.

*Listed on Springer’s Print Bestsellers (Top 100 print titles) in Computer Science (August 2017).*

„*I really like this book: those 100 interesting real data examples with the detailed R-scripts for producing beautiful graphical visualisation are particularly helpful for learning R graphics. I will use it as a main textbook for data visualization for my statistics course.*“

Prof. Qiwei Yao, Department of Statistics, London School of Economics, 2017/7.

„*This is a well written book for designers… Enjoy this book. I am having fun getting the code to work on other data. „*

*Mary Anne Thygesen, Book Review, Cats and Dogs with Data, 2017/5*

„*If you’ve ever been interested in coding using R, then this book is for you. (…) If like me, you need hands-on guidance the examples (which use real data) are shown with a step-by-step walkthrough teaching you everything that you need to know.*“

Sandro Sorrentino, The 8 books that you need to succeed as a data journalist in 2017, 2017/4

*Top Ten #ddj: The Week’s Most Popular Data Journalism Links.*

Global Investigative Journalism Network (GIJN), 2017/3

How to draw a scatter plot with quadrants (Brexit correlation between education and results). 2017/2

## Reviews to the German Edition

*„.NET developers who are interested in R can significantly expand the possibilities to develop charts.“*

Buchempfehlung in dotnet*pro*. Das Profimagazin für Entwickler, 2/2015.

*„The core of the book, and the actual purchase reason, are the 100 visualization examples, which are actually visually convincing, comprehensibly prepared and also beautiful to look at.“*

Benjamin Aunkofer, Data Analytics mit R – Buchempfehlung: www.der-wirtschaftsingenieur.de, Dez. 2014

*„The diagram examples are selected for practical purposes and illustrate interesting and relevant data. (…) Rahlf’s attention to detail makes the book an eye-candy and at the same time a treasure trove of useful approaches.“*

c’t Magazin für Computertechnik 22/2014

*„… an extraordinarily useful companion who is able to convey a wide range of representations.“*

*„The diagrams and illustrations shown are really well done and make you want to follow.“*

## Further feedback (in German)

*A good overview of data visualization is provided by the book by Rahlf (2014), in which the practical implementation with the statistical environment R is explained.“*

Joachim König, Praxisforschung in der Sozialen Arbeit: Ein Lehr- und Arbeitsbuch, Stuttgart: Kohlhammer 2016.

*„The book Datendesign mit R by Thomas Rahlf offers almost 300 pages of examples for all possible visualizations which are essentially ready for publication. A great advantage of the book is that only the basic graphic of R is used so that the concepts with lattice or ggplot2, which have more learning curve, can be ignored. This allows beginners in R to create very appealing and informative graphics, with courage for partial long-term writing.“*

Karl-Kuno Kunze, R-Institute, Autor von „Ökonometrie für Dummies“, 5/2016.

*„Thomas Rahlf is concerned only with the graphic functions of Base R; ggplot by Hadley Wickham is not used. Nevertheless, I appreciate the work very much, since it contains a lot of tricks and with the 100 examples very practice-oriented. You do not have to work it out in chronological order, but you can pick up what you find exciting.“*

Wolf Riepe, Social Science Research, 3/2016.

*„The book is really great. We have already bought two at the institute and will also recommend it.“*

Oliver Gansser, stellv. Direktor ifes Institut für Empirie & Statistik Forschungsbüro Süd, FOM Hochschule für Oekonomie & Management, München, 12/2015.

*„provides extensive code examples for producing elegant images.“*

Antony Unwin, Graphical Data Analysis with R, Boca Raton, Fla. [u.a.]: Chapman and Hall/CRC 2015.

*„The book is great, gives many examples.“*

Zhengfeng Wang, South China Botanical Garden, Chinese Academy of Sciences, 2014/9

*„At first I was somewhat disappointed. I purchased the e-book and found the first 100 to 200 pages for the first time superfluous. But then this book was a revelation: R and nice graphical representations were for me up until then two areas. This has probably changed for me now (finally)! The standard graphs in R work, but are not beautiful without any effort. How to do this is shown in this book. The examples will save you a lot of research in the documentation and lengthy experimentation. And on the whole, the foundations of the first pages have opened up to me. It may not be necessary for everyone, but they should not be lacking. Many Thanks“*

Jan Kräck on opensourcepress.de, 2014/6

*„Overall for me a successful book, which is very nice to look and read.“*

Andreas Krause, Author of „The Basics of S and S-Plus“, Editor von „Statistical Applications in the Pharmaceutical Industry“ und „A Picture is Worth a Thousand Tables – Graphics in Life Sciences„, 2014/4

*„The book fills a gap. The code is well structured, the examples are not only functional, but also aesthetic. It was really fun to scroll around in the graphics.“*

Mark Heckmann, talkingdata.de / Lecturer Universität Bremen, 2013/11

*„Very impressive examples of visualizing data with R which are backed by very readable code.“*

Joseph Rickert – http://blog.revolutionanalytics.com, 2013/11

*„The images look REALLY nice!“*

Paul Murrell, Department of Statistics, University of Auckland, R core group, Autor von R Graphics, 2013/11

*„The graphics look VERY professional, with some I would not have thought that they come from R.“*

Uwe Ligges, Fakultät für Statistik, Universität Dortmund, R core group, Autor von Programmieren mit R, 2013/11

*„Besides the beautiful images on it you will also find the codes and spreadsheets used.“*

João Victor, www.estatisti.co, 2013/11

*„The book is great! The introduction to the design of a graphic is very good and can be read fluently!“*

Günter Faes, Deutsches R-Forum, 2013/11

## Use Cases…

Anastasia Arkhipova, Ernst & Young Valuation and Advisory Services, Moscow, Prioritization of russian regions for Sustainable Investing Purposes using Data Envelopment Analysis, in: Review of Business and Economics Studies 2/3 (2014).

papers.ssrn.com/sol3/papers.cfm?abstract_id=2525139

Google Trends: blog.r-institute.com

ggplot2 versus Base Graphics with examples from the book: Variance Explained.

What’s the best way to learn R language? Chung I Yen.

*„Without data design with R: 100 visualization examples, I could not create the graphic.“*

Wolf Riepl, Bevölkerungsdichte in Dresden: Visualisierungsbeispiel mit R (Choroplethenkarte), 05/2015.