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The Art of R Programming: A Tour of…
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The Art of R Programming: A Tour of Statistical Software Design (utgåvan 2011)

av Norman Matloff

MedlemmarRecensionerPopularitetGenomsnittligt betygDiskussioner
1966104,037 (4)Ingen/inga
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 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, more useful formats. You'll also learn to: Create artful graphs to visualize complex data sets and functions Write more efficient code using parallel R and vectorization Interface R with C/C++ and Python for increased speed or functionality Find n… (mer)
Medlem:tilke
Titel:The Art of R Programming: A Tour of Statistical Software Design
Författare:Norman Matloff
Info:No Starch Press (2011), Edition: 1, Paperback, 400 pages
Samlingar:Ditt bibliotek
Betyg:
Taggar:programming languages, R

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The Art of R Programming: A Tour of Statistical Software Design av Norman Matloff

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Visar 5 av 5
Read this after learning the tidyverse because I wanted to understand base R. To that end, the first twelve or so chapters deliver a thorough overview. The later chapters I suspect are woefully out of date. The coding style is awful, however. I understand print imposes limitations but there were many abbreviated variable and function names that I had to stop and parse what they could mean. I also wasn't able to track down all example source code and data, only some of which appeared to be available on the author's website. ( )
  encephalical | Apr 17, 2020 |
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.

Needless to say, I'll require a lot of practice to get comfortable thinking in R terms, but this book definitely laid the stepping stone for me. ( )
  nmarun | Sep 2, 2017 |
Great book for thinking in R. I'm not sure I would recommend it as your first source of information on how to use R unless you have a solid background in programming and statistics already. Definitely get your hands on this book once you've gotten a start and need to use R in a way that exploits its advantages and idiosyncrasies. ( )
  jbenson3 | Jun 24, 2016 |
Good book for learning the basics of R. Look elsewhere for how to do advanced R functionality. ( )
  jefware | Mar 31, 2014 |
Denna recension har flaggats av flera användare som missbruk av våra allmänna villkor och visas därför inte längre (visa).
  knol | Apr 18, 2012 |
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R is a scripting language for statistical data manipulation and analysis.
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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 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, more useful formats. You'll also learn to: Create artful graphs to visualize complex data sets and functions Write more efficient code using parallel R and vectorization Interface R with C/C++ and Python for increased speed or functionality Find n

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