Popular Books on R Programming

Popular Books on R Programming

Books in list (26)


Title: R Cookbook

With more than 200 practical recipes, this book helps you perform data analysis with R quickly and efficiently. The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of concise, task-oriented recipes makes you productive with R immediately, with solutions ranging from basic tasks to input and output, general statistics, graphics, and linear regression.

Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an experienced data programmer, it will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process.

  • Create vectors, handle variables, and perform other basic functions
  • Input and output data
  • Tackle data structures such as matrices, lists, factors, and data frames
  • Work with probability, probability distributions, and random variables
  • Calculate statistics and confidence intervals, and perform statistical tests
  • Create a variety of graphic displays
  • Build statistical models with linear regressions and analysis of variance (ANOVA)
  • Explore advanced statistical techniques, such as finding clusters in your data

"Wonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language—one practical example at a time." —Jeffrey Ryan, software consultant and R package author

Author(s): Paul Teetor
ISBN 13: 9780596809157
Pages: 438
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Title: 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 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 new R packages for text analysis, image manipulation, and more
  • 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.

Author(s): Norman Matloff
ISBN 13: 9781593273842
Pages: 400
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Title: An Introduction to Statistical Learning

This book presents some of the most important modeling and prediction techniques, along with relevant applications.
Author(s): Gareth James;Daniela Witten;Trevor Hastie;Robert Tibshirani
ISBN 13: 9781461471370
Pages: 426
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Title: R in a Nutshell

If you’re considering R for statistical computing and data visualization, this book provides a quick and practical guide to just about everything you can do with the open source R language and software environment. You’ll learn how to write R functions and use R packages to help you prepare, visualize, and analyze data. Author Joseph Adler illustrates each process with a wealth of examples from medicine, business, and sports.

Updated for R 2.14 and 2.15, this second edition includes new and expanded chapters on R performance, the ggplot2 data visualization package, and parallel R computing with Hadoop.

  • Get started quickly with an R tutorial and hundreds of examples
  • Explore R syntax, objects, and other language details
  • Find thousands of user-contributed R packages online, including Bioconductor
  • Learn how to use R to prepare data for analysis
  • Visualize your data with R’s graphics, lattice, and ggplot2 packages
  • Use R to calculate statistical fests, fit models, and compute probability distributions
  • Speed up intensive computations by writing parallel R programs for Hadoop
  • Get a complete desktop reference to R
Author(s): Joseph Adler
ISBN 13: 9781449312084
Pages: 724
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Title: The R Book

Hugely successful and popular text presenting an extensive and comprehensive guide for all R users

The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research.

This edition:

  • Features full colour text and extensive graphics throughout.
  • Introduces a clear structure with numbered section headings to help readers locate information more efficiently.
  • Looks at the evolution of R over the past five years.
  • Features a new chapter on Bayesian Analysis and Meta-Analysis.
  • Presents a fully revised and updated bibliography and reference section.
  • Is supported by an accompanying website allowing examples from the text to be run by the user.

Praise for the first edition:

‘…if you are an R user or wannabe R user, this text is the one that should be on your shelf. The breadth of topics covered is unsurpassed when it comes to texts on data analysis in R.’ (The American Statistician, August 2008)

‘The High-level software language of R is setting standards in quantitative analysis. And now anybody can get to grips with it thanks to The R Book…’ (Professional Pensions, July 2007)

Author(s): Michael J. Crawley
ISBN 13: 9780470973929
Pages: 1076
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Title: R in Action

Author(s): Robert Kabacoff
ISBN 13: 9781617291388
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Title: The Book of R

"A beginner's guide to programming with R, the statistical programming language.
Author(s): Tilman M. Davies
ISBN 13: 9781593276515
Pages: 432
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Title: R Packages: Organize, Test, Document, and Share Your Code

Turn your R code into packages that others can easily download and use. This practical book shows you how to bundle reusable R functions, sample data, and documentation together by applying author Hadley Wickham’s package development philosophy. In the process, you’ll work with devtools, roxygen, and testthat, a set of R packages that automate common development tasks. Devtools encapsulates best practices that Hadley has learned from years of working with this programming language. Ideal for developers, data scientists, and programmers with various backgrounds, this book starts you with the basics and shows you how to improve your package writing over time. You’ll learn to focus on what you want your package to do, rather than think about package structure. Learn about the most useful components of an R package, including vignettes and unit tests Automate anything you can, taking advantage of the years of development experience embodied in devtools Get tips on good style, such as organizing functions into files Streamline your development process with devtools Learn the best way to submit your package to the Comprehensive R Archive Network (CRAN) Learn from a well-respected member of the R community who created 30 R packages, including ggplot2, dplyr, and tidyr
Author(s): Hadley Wickham
ISBN 13: 9781491910597
Pages: 202
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Title: Learn R in a Day

Author(s): Steven Murray
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Title: R For Dummies

Mastering R has never been easier Picking up R can be tough, even for seasoned statisticians and data analysts. R For Dummies, 2nd Edition provides a quick and painless way to master all the R you'll ever need. Requiring no prior programming experience and packed with tons of practical examples, step-by-step exercises, and sample code, this friendly and accessible guide shows you how to know your way around lists, data frames, and other R data structures, while learning to interact with other programs, such as Microsoft Excel. You'll learn how to reshape and manipulate data, merge data sets, split and combine data, perform calculations on vectors and arrays, and so much more. R is an open source statistical environment and programming language that has become very popular in varied fields for the management and analysis of data. R provides a wide array of statistical and graphical techniques, and has become the standard among statisticians for software development and data analysis. R For Dummies, 2nd Edition takes the intimidation out of working with R and arms you with the knowledge and know-how to master the programming language of choice among statisticians and data analysts worldwide. Covers downloading, installing, and configuring R Includes tips for getting data in and out of R Offers advice on fitting regression models and ANOVA Provides helpful hints for working with graphics R For Dummies, 2nd Edition is an ideal introduction to R for complete beginners, as well as an excellent technical reference for experienced R programmers.
Author(s): Andrie de Vries;Joris Meys
ISBN 13: 9781119055808
Pages: 432
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Title: Machine Learning with R - Second Edition

Harness the power of R for statistical computing and data science. Explore, forecast, and classify data with R. Use R to apply common machine learning algorithms to real-world scenarios. Harness the power of R to build common machine learning algorithms with real-world data science applications. Get to grips with R techniques to clean and prepare your data for analysis, and visualize your results. Discover the different types of machine learning models and learn which is best to meet your data needs and solve your analysis problems. Classify your data with Bayesian and nearest neighbour methods. Predict values by using R to build decision trees, rules, and support vector machines. Forecast numeric values with linear regression, and model your data with neural networks. Evaluate and improve the performance of machine learning models. Learn specialized machine learning techniques for text mining, social network data, big data, and more.
Author(s): Brett Lantz
ISBN 13: 9781784393908
Pages: 454
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Title: R in 24 Hours, Sams Teach Yourself

In just 24 lessons of one hour or less, Sams Teach Yourself R in 24 Hours helps you learn all the R skills you need to solve a wide spectrum of real-world data analysis problems. You’ll master the entire data analysis workflow, learning to build code that’s efficient, reproducible, and suitable for sharing with others. This book’s straightforward, step-by-step approach teaches you how to import, manipulate, summarize, model, and plot data with R; formalize your analytical code; and build powerful R packages using current best practices. Practical, hands-on examples show you how to apply what you learn. Quizzes and exercises help you test your knowledge and stretch your skills. Learn How To Install, configure, and explore the R environment, including RStudio Use basic R syntax, objects, and packages Create and manage data structures, including vectors, matrices, and arrays Understand lists and data frames Work with dates, times, and factors Use common R functions, and learn to write your own Import and export data and connect to databases and spreadsheets Use the popular tidyr, dplyr and data.table packages Write more efficient R code with profiling, vectorization, and initialization Plot data and extend your graphical capabilities with ggplot2 and Lattice graphics Develop common types of models Construct high-quality packages, both simple and complex Write R classes: S3, S4, and Reference Classes Use R to generate dynamic reports Build web applications with Shiny Register your book at informit.com/register for convenient access to updates and corrections as they become available.
Author(s): Andy Nicholls;Richard Pugh;Aimee Gott
ISBN 13: 9780672338489
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Title: Learning R

Author(s): Richard Cotton
ISBN 13: 9781449357108
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Title: Data Science with R

What exactly is data science? With this book, you’ll gain a clear understanding of this discipline for discovering natural laws in the structure of data.
Author(s): Garrett Grolemund
ISBN 13: 9781491910399
Pages: 250
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Title: Data Analysis with R

Author(s): Garrett Grolemund
ISBN 13: 9781449359010
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Title: R Graphics Cookbook

This practical guide provides more than 150 recipes to help you generate high-quality graphs quickly, without having to comb through all the details of R’s graphing systems. Each recipe tackles a specific problem with a solution you can apply to your own project, and includes a discussion of how and why the recipe works.

Most of the recipes use the ggplot2 package, a powerful and flexible way to make graphs in R. If you have a basic understanding of the R language, you’re ready to get started.

  • Use R’s default graphics for quick exploration of data
  • Create a variety of bar graphs, line graphs, and scatter plots
  • Summarize data distributions with histograms, density curves, box plots, and other examples
  • Provide annotations to help viewers interpret data
  • Control the overall appearance of graphics
  • Render data groups alongside each other for easy comparison
  • Use colors in plots
  • Create network graphs, heat maps, and 3D scatter plots
  • Structure data for graphing
Author(s): Winston Chang
ISBN 13: 9781449316952
Pages: 416
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Title: Practical Data Science with R

This book is accessible to readers without a background in data science. Some familiarity with basic statistics, R, or another scripting language is assumed.
Author(s): Nina Zumel John Mount
ISBN 13: 9781617291562
Pages: 416
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Title: R for Non-Statisticians

Author(s): Jared Lander
ISBN 13: 9780321888037
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Title: R

R programming Language course is now available in Amazon and it is just for $10,99. This is a no-brainer!Crash it!Here Is A Preview Of What You'll Learn When You Download You Copy Today: What is R Programming? What is R used for?
Author(s): Acodemy
ISBN 13: 9781508593218
Pages: 396
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Title: Data Wrangling with R

Author(s): Bradley Boehmke
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