الكتاب جيد جدا لفهم حزمة
ggplot
ولكن لأني بدأت بقراءة أول طبعة فهي الى حد ما قديمة وبعض الأكواد لم تعد تعمل في النسخ الحديثة لل
R

ولكن مجملا الكتاب جيد لمن يريد فهم أجزاء تكوين الصور التوضيحية في برام الإحصاء ( )

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.] ( )

ggplot2 is a really fun R package to use and it produces awesome results BUT this book is not for R beginners. It requires a general sense of the R syntax and grammar. But with a little R knowledge, and this book in hand, it is easy to quickly produce nice plots.
Like most programming books, one doesn't just read them cover to cover and then put them on a shelf. They are meant as references to have handy when needed. I recommend using this book in conjunction with Winston Chang's R Graphics cookbook. ( )

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.
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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. ( )