The Art of R Programming: A Tour of Statistical Software Design

The Art of R Programming: A Tour of Statistical Software Design

Norman Matloff / May 24, 2019

The Art of R Programming A Tour of Statistical Software Design R is the world s most popular language for developing statistical software Archaeologists use it to track the spread of ancient civilizations drug companies use it to discover which medications are s

  • Title: The Art of R Programming: A Tour of Statistical Software Design
  • Author: Norman Matloff
  • ISBN: 9781593273842
  • Page: 496
  • Format: Paperback
  • R is the world s most popular language for developing statistical software Archaeologists use it to track the spread of ancient civilizations, drug companies use it to discover which medications are safe and effective, and actuaries use it to assess financial risks and keep economies running smoothly.The Art of R Programming takes you on a guided tour of software developmR is the world s most popular language for developing statistical software Archaeologists use it to track the spread of ancient civilizations, drug companies use it to discover which medications are safe and effective, and actuaries use it to assess financial risks and keep economies running smoothly.The Art of R Programming takes you on a guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anonymous functions No statistical knowledge is required, and your programming skills can range from hobbyist to pro.Along the way, you ll learn about functional and object oriented programming, running mathematical simulations, and rearranging complex data into simpler, useful formats You ll also learn to Create artful graphs to visualize complex data sets and functions Write efficient code using parallel R and vectorization Interface R with C C and Python for increased speed or functionality Find new R packages for text analysis, image manipulation, and Squash annoying bugs with advanced debugging techniques Whether you re designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing.

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    About "Norman Matloff"

      • Norman Matloff

        Norman Matloff Is a well-known author, some of his books are a fascination for readers like in the The Art of R Programming: A Tour of Statistical Software Design book, this is one of the most wanted Norman Matloff author readers around the world.


    399 Comments

    1. First things first, this book really lives up to its name! It’s a thorough introduction to programming in R, aimed at software developers. This is not the book for you if you want to learn about the statistics side of R or how to make prettier plots, there are plenty of books about that anyway.What I really like is that the author never tries to “sell” R to the reader. This is rather refreshing, because I always get turned off when books start with a sales pitch for something I already cle [...]


    2. You are about to get superpowers by mastering this art. As a result, the digital world will look quite different. Big blobs of bytes are suddenly playgrounds. You will load "whatever" to your vectorized universe just like creating a swimming pool with many many lanes. Then you deploy your mighty sharks (statistics?) to fetch the sexy stuff hidden. If you don't feel like swimming today, just fly, run, crawl, dance… this R thing is so flexible that you can even throw numbers in the air like a ma [...]


    3. If you're looking for a book to read as a full-on introduction to R (and advanced R), take this book. Not only does it go through all of the basics of the language, it also recommends some modern packages which make everything easier (plyr for example) - with copious examples and "advanced examples".I only have two problems with the book:1) Sometimes, the advanced examples are too clever for their own good. They're meant to exhibit the advanced usage of the main focus of the current chapter, but [...]


    4. This book IMHO is an excellent starting point for learning R. I'm finding it really useful for beginners like me to learn this new programming language. The book is comprehensive and well-illustrated. The initial chapters talk about the foundation concepts like vectors and matrices. The examples are simple enough to start with, while the author leaves some room for self-experimentation. The latter chapters describe the advanced capabilities like graphics, debugging and performance tuning.Needles [...]


    5. This is one of the best books for learning R. I have read numerous R books and this is my favorite. It is also the preferred text of students who work under me. They are constantly borrowing my copy of this book.


    6. Well, I read somewhere, an opportunity for publishing a review online is a tribune for a fool. I will exercise my right whether you agree or not. I don't. In short, overall, it is a worthy book. It touches most of the aspects when programming in a modern, Big Data capable language R. And not quite at the same time. To elaborate more, let me state right away this is not Norman's fault. Its R's. Carry on. Starting from the first pages till the last you will be made very well aware that R is slow. [...]


    7. There is much that I didn't like about this book. Programming examples in the first two thirds of the text are mostly irrelevant and contrived, like doing quick sort by hand, or calculating probabilities by basic arithmetic operations. R is treated as a general purpose programming language, and almost no direction is given in how any real world statistical code would be written in it. Some good insights are provided on how R works, or how it's different from what programmers coming from other la [...]


    8. This book is more of a CS text than a stats text and the author makes this very clear. Regardless, it is a very good overview of R's data types and features. Great emphasis is placed on performance and properly vectorizing code witha brief overview of useful vectorized functions. The debugging section is more readable than Chamber's "Software for Data Analysis", but not as complete. The author recommends his own book for better understanding of debugging. There is a useful section on integrating [...]


    9. This book provides a good R overview and I did enjoy it. That said, I will point out two perceived flaws. First, some of the examples involve an underlying mathematics and statistics knowledge. I didn't spend the time to try to research but would have like an overview in some places. Secondly, perhaps compounding this, example data is available for only a small set of problems. This does make it difficult to follow along.


    10. This book introduces with the fundamental data structures like vectors,factors, matrices, dataframes, lists, etc. with a chapter dedicated to each. Book serves the purpose to introduce the programming structure to those new to R. After getting good at the basics of R, one can go for other books for specific requirements (like whether you want to focus on graphics/plots or on statistical modelling).


    11. This was my first R book. I worked through a good bit of it but still felt that there was a lot missing in my understanding of R. Something about the way it is organized or the way it explains things didn't quite do it for me. I ended up getting another book that explained R a lot better to me. I still refer to this book on occasion but I have found R in Action to be much more helpful.


    12. LIKE: 1) It takes readers from non-programming background on a wide range of topics from data structures to parallel. Esp, vectorization is the core art of R. 2) Extended examples (functions) are very practical. UNLIKE: 1) No exercise at the end of each chapter. 2) Variable & function names aren't that readable. Lots of abbreviation involved.


    13. Like most programming books, this one focuses too much on syntax and data structures, and not enough on problems you can solve with the language. But other than that it's well-written. If you want to do anything having to do with statistics, R is a great language, and this book will teach you how to use it.


    14. This book is very serious. It gets you way beyond the beginners books, and in fact, there is more material than I need here, but it is what I asked for. It does an exceptional job explaining how to think about vectorized programming, which is one of the big shifts for typical programmers.


    15. This is a great resource for anyone that is looking at learning R. The strengths of this book come from it's examples and great organization.



    16. This is one of the best book to learn R programming language, it's complete and with details. I recommend it to everyone that want to learn this programming language. (Lebanese Book Lover)



    17. This is a great introduction to base R and also a good reference for some more intermediate-advanced topics (vectorization, paralellization, etc.). The writing is very clear and accessible.




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