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R Graphs Cookbook
R Graphs Cookbook
- GenresComputers
272 pages, Paperback
First published January 6, 2011
15 people want to read
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Displaying 1 - 3 of 3 reviews
July 13, 2012
I appreciate the author's work on this book: there are plenty of useful examples and helpful reference tables. But I see room for major improvements too.
This is VERY much just a cookbook: example after example, with little to no discussion of how R works in general. A few key concepts would be really helpful: scripts vs the console, functions and objects, vectors vs data frames vs matrices, square bracket array notation, etc. Some of these things come up often in many "recipes," but the explanations are either interspersed throughout the text or just omitted. So when you want to tweak a more-complicated recipe to plot your own data, you're likely to be confused about key concepts.
I'd love to see an appendix with this info, or at least some suggested links! Paul Murrell's R Graphics has a great example of such an appendix.
Also, some of the graphics examples could be much better. Many of R's built-in examples aren't great either! But I would expect more from a book that's explicitly meant to be an example-based intro for beginners. Consider the heatmap on p.25: what is this even trying to convey? Why is there no legend?
I find it hard to read when they omit spaces around the assignment operator, such as in "x<-3" ... It's assigning 3 to x, but it looks like it's checking whether x is less than -3.
Anyhow, this book is a good start, but I hope there's an improved second edition soon.
PS -- be aware that this book is in black-and-white, so it can't convey some of the color-based graphics well.
This is VERY much just a cookbook: example after example, with little to no discussion of how R works in general. A few key concepts would be really helpful: scripts vs the console, functions and objects, vectors vs data frames vs matrices, square bracket array notation, etc. Some of these things come up often in many "recipes," but the explanations are either interspersed throughout the text or just omitted. So when you want to tweak a more-complicated recipe to plot your own data, you're likely to be confused about key concepts.
I'd love to see an appendix with this info, or at least some suggested links! Paul Murrell's R Graphics has a great example of such an appendix.
Also, some of the graphics examples could be much better. Many of R's built-in examples aren't great either! But I would expect more from a book that's explicitly meant to be an example-based intro for beginners. Consider the heatmap on p.25: what is this even trying to convey? Why is there no legend?
I find it hard to read when they omit spaces around the assignment operator, such as in "x<-3" ... It's assigning 3 to x, but it looks like it's checking whether x is less than -3.
Anyhow, this book is a good start, but I hope there's an improved second edition soon.
PS -- be aware that this book is in black-and-white, so it can't convey some of the color-based graphics well.
June 12, 2014
I wanted automatic parsing, plotting and non-linear fits for several data sets. The book was perfect for this - all basic needs are covered in a series of example tasks. I would appreciate few extra links to further reading.
The tasks are well described, the provided code snippets work and are complete. Therefore - you can just look up your problem in the table of contents and start right there.
Basic preliminary knowledge of R is helpful, but even just a downloaded R, R-studio and some knowledge of Matlab, C or other programming language should be enough for start.
The tasks are well described, the provided code snippets work and are complete. Therefore - you can just look up your problem in the table of contents and start right there.
Basic preliminary knowledge of R is helpful, but even just a downloaded R, R-studio and some knowledge of Matlab, C or other programming language should be enough for start.
November 13, 2011
Exactly what I was looking for--a variety of plots, with the corresponding code and explanation. It doesn't assume you're a wizard with R or command line programming in general, which was very helpful. The final chapter on finalizing graphs for publication was also extremely useful. I recommend this book.
Displaying 1 - 3 of 3 reviews