Customer Reviews

Programming with Data: A Guide to the S Language

5 star:		(1)
4 star:		(1)
3 star:		(0)
2 star:		(0)
1 star:		(0)

 

 

This is the first book I've found that approaches the S programming language as more than an inconvenient detail that you have to learn to get to the cool statistics functions in "S-Plus." It's much more accessible than most of the books on S or S-Plus for people who aren't actually statisticians, but need to use the language for some reason.

This book was originally published in 1998 by MathSoft, and now with more demand I'm glad that it will be redistributed by Springer. As co-developer of the orginal S language, John Chambers new book is supposed to provide the most authorative reference on defining new, object-oriented (OOP)-style S for the current version of S-PLUS, and R. I think it may not have reached its full promise yet, partly, maybe because of its terse style and not-so-easy read for beginners. I have to admit myself I have ignored of it for quite a while until recently when I see its full power realized in the now fast developing R project, particularly Bioconductor project Bioinformatics and Computational Biology Solutions Using R and Bioconductor (Statistics for Biology and Health). I think it may be a dream work for software developers to have such a flexible and extensible computing environment in R and S so that much involved data objects and methods can be built so easily for many complex data mining and bioinformatics tasks. I think a big benefit of the open source approach to software developments is to enable researchers to reach quickly to users and to deliver the final promised land for collaboration and sharing of ideas and data. I think John Chambers truly deserves all the credit he gets for this work and for inspiring the R project, which is now beginning to gain widespread acceptance by the data mining and bioinformatic research communities.