Best in class - data visualization
354194
Best of best. Master Edward lead us through a journey of visualization across centuries. It is the utmost important book to start studying data visualization and the nuts and bolts of its application to meaningful business cases.
1618463
This is definitely a series I will go back to for introductions to other topics. The presentation was great. The graphics were well done. It really did feel like an introduction with ideas about all kinds of things to look at about fractals. I think it would be especially useful in a high school classroom library.
4388129
I would recommend this atlas over any of the atlases recommended by my school.  The labeling is clear, and the pictures are really nice.  It was especially great for horse and ruminant anatomy.  Also good for helping picture organs in 3 dimensions.
4362820
Stephanie Evergreen's work has made my work better.  This is a great intro tool for anyone trying to up their game presenting their data.  I was put in charge of data translation with NO graphic design experience. Evergreen's tools have made me look like I know what I am doing.  Buy it.  You won't regret.
1372529
Good primer on how to think about how to visualize data.  Lots of examples of cool visualization but doesn't talk much about the actual iteration of junk to amazing that actually takes place.
3583721
It is cool to have a book about various real life data visualization cases. Some of the articles are hard to read while some others are inspiring. This book kind of opens the door for me into Processing. And the beauty of some of the diagrams just gave me some new idea about how to put my own data onto computer screen. Currently I would give Processing a try and at the mean time stick to R for a while.

A particularly interesting chapter is about postmortem visualization. Not saying I am going to become a CSI, but reading it at least give me a hope about combining the thing I learn and the profession I want to join.
4744597
This is the best book for graphic organizers I have seen, and I have several.  The first chapter provides blackline master graphs with instructions for using each one.  The remaining chapters show the graphic  organizers being utilized in specific lessons for the content areas.  Completed examples are also provided.  This book helped me understand  graphic organizers so well that I now create my own graphic organizers  customized for a particular lesson or reading assignment.
1120031
A few years ago D3.js and html5 were the future on data visualization, today D3.js is the present and this book explains every little piece of the library, from the basic principles of data visualization to optimization techniques to improve the performance when you are working with large datasets.

D3.js in Action has a clear roadmap to introduce you the basic concepts, and when you have a well-grounded knowledge, you can learn from the complexity of the explained examples and this book serves as a reference guide. If you are planning to build your next interactive infographic, or thinking on build an easy to consume representation of complex data, definitely this book is for you.
1959317
Absolutely excellent. Being a visual learner, these high quality graphics have proven to be an invaluable companion the book itself.
1591956
I have been working in architectural visualization for 7 years. I've never taken a formal class, only internet tutorials. I have not finished studying the entire book, but I found a clear method, which seems to ensure proper workflow. I will write another review when I finish reading it.
4831946
A reviewer (W Boudville) claims that C++ may lack the glamour of Java/C#. To me, C++ is the most beautiful amongst the three languages. The more I learn about and program in C++, the more beaustiful I think it gets.

This is the second book exclusively on Boost library, the first (published) being "The Boost Graph Library." Both books are beautiful, in both their content and typesetting (Adobe/Times rocks).
2328767
I found Mapsource to be a top rated program with a short learning curve. I Like It!
2874133
If you haven't been anywhere near the data visualization world this is a huge first step for you, the book can be a little slow sometimes because of the examples that Nathan uses, they tend to be that way because im a computer scientist, but i can say that even taking that into account they are just awesome is a really nice place to start.
788096
This was a great book. The negative visualization technique mentioned in the text is brilliant. I highly recommend this book.
57808
Data Analysis with Open Source Tools is an excellent book for experienced analysts of data.  The author is obviously enthusiastic about his topic and presents the information in a lucid, readable format.  The book is not, however, a cookbook, or step-by-step guide to using a tool or suite for delving into data and would not be suitable for a neophyte.

Within the first two chapters I had  jotted down a number of ideas to apply to my own work ( DBA primarily applying  analyses as a data quality tool ), and continued this pattern throughout the book.  However, if you are math-phobic, as I am, you may quickly find yourself skimming portions which delve into formulas and mathematical concepts.  The author does indicate in his introduction that none of the math involved is particularly difficult, it's just that if you don't view the world in mathematical terms, you'll have some work to do in order to fully grasp the concepts presented.  References are provided in most chapters for further reading.

"Workshops" using open source products are provided in the majority of chapters; these primarily use various Python libraries but obviously use other tools for appropriate tasks (e.g., R and gnuplot).  To get the most value you from the text you should have a working Python environment and be able to handle the installation of various Python libraries within your environment.
1810082
Summary: Data Analysis with Open Source Tools is a reference book that explains in detail the many ways to make sense of data. You will find ways to interpret data using statistics, plots, and mathematics. It also covers traditional data mining (simulation, clustering) and fun topics on modeling for making estimates.

You should get this book if your education was below average in statistics and math, or if it was average and you forgot about it already. It is quite good to refresh your memory and to learn interesting stuff that is good to know in case you need it. For example, the time value of money is clearly explained. The author goes in length to warn you of common mistakes in processing data. Every graduate student in a science major should know about the topics covered in this book. That is, read about it once, you will know what it is when someone mentions it (such as k-means), and if needed, go back again to the book for details or pointers for further information.

Once you reach 80% of the book, there are two big appendixes left: one is a refresher on math, the other on additional details on working on data. Throughout, the book has workshops/exercises, but unless you are familiar with Phyton, you might as well skip them (not too big of a loss).

Disclaimer: I was provided a electronic-copy of the book from O'Reilly for review.
486956
I divide my graphics work into two categories: BT (Before Tufte) and AT (After Tufte). I rarely acknowledge any involvement of a publication from those dark BT days.
Tufte's masterful and dead-on takes about how to communicate statistical and quantitative data challenges standard assumptions about developing graphical information and reveals, though it is not his stated intention, the weakness of so many graphics software packages. Just look at his collection of chartjunk and "ducks" (his term for hideous graphics) to see how all the whistles and bells available to us via computer graphics programs actually obfuscate the interpretation of visual information. By the time you read how much ink and paper are wasted by created bad graphics, you should be a convert.
And if you are ever lucky enough to have the chance to attend one of Tufte's seminars, pawn your PC if that's what it takes.