Advanced R: An Essential Reference for Intermediate and Advanced R Programmers

This book presents useful tools and techniques for attacking many types of R programming problems, helping you avoid mistakes and dead ends.

**Tag(s):**
R

**Publication date**: 25 Sep 2014

**ISBN-10**:
1466586966

**ISBN-13**:
9781466586963

**Paperback**:
476 pages

**Views**: 3,571

Advanced R: An Essential Reference for Intermediate and Advanced R Programmers

This book presents useful tools and techniques for attacking many types of R programming problems, helping you avoid mistakes and dead ends.

From the Book Description:

Hadley Wickham wrote:Advanced R presents useful tools and techniques for attacking many types of R programming problems, helping you avoid mistakes and dead ends. With more than ten years of experience programming in R, the author illustrates the elegance, beauty, and flexibility at the heart of R.

The book develops the necessary skills to produce quality code that can be used in a variety of circumstances. You will learn:

- The fundamentals of R, including standard data types and functions

- Functional programming as a useful framework for solving wide classes of problems

- The positives and negatives of metaprogramming

- How to write fast, memory-efficient code

This book not only helps current R users become R programmers but also shows existing programmers whatâ€™s special about R. Intermediate R programmers can dive deeper into R and learn new strategies for solving diverse problems while programmers from other languages can learn the details of R and understand why R works the way it does.

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About The Author(s)

Hadley Wickham is an Assistant Professor and the Dobelman FamilyJunior Chair in Statistics at Rice University. He is an active memberof the R community, has written and contributed to over 30 R packages, and won the John Chambers Award for Statistical Computing for his work developing tools for data reshaping and visualization. His research focuses on how to make data analysis better, faster and easier, with a particular emphasis on the use of visualization to better understand data and models.

Book Categories

Computer Science
Introduction to Computer Science
Introduction to Computer Programming
Algorithms and Data Structures
Artificial Intelligence
Computer Vision
Machine Learning
Neural Networks
Game Development and Multimedia
Data Communication and Networks
Coding Theory
Computer Security
Information Security
Cryptography
Information Theory
Computer Organization and Architecture
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Image Processing
Parallel Computing
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Data Mining
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Digital Libraries
Compiler Design and Construction
Functional Programming
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Mathematics
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Linear Algebra
Number Theory
Numerical Methods
Precalculus
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Differential Equations
Category Theory
Proofs
Discrete Mathematics
Theory of Computation
Graph Theory
Real Analysis
Complex Analysis
Probability
Statistics
Game Theory
Queueing Theory
Operations Research
Computer Aided Mathematics

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