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Efficient R Programming A Practical Guide to Smarter Programming [Paperback]

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  • Category: Books (Computers)
  • Author:  Gillespie, Colin, Lovelace, Robin
  • Author:  Gillespie, Colin, Lovelace, Robin
  • ISBN-10:  1491950781
  • ISBN-10:  1491950781
  • ISBN-13:  9781491950784
  • ISBN-13:  9781491950784
  • Publisher:  O'Reilly Media
  • Publisher:  O'Reilly Media
  • Pages:  222
  • Pages:  222
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-May-2017
  • Pub Date:  01-May-2017
  • SKU:  1491950781-11-MPOD
  • SKU:  1491950781-11-MPOD
  • Item ID: 100187295
  • List Price: $39.99
  • Seller: ShopSpell
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  • Delivery by: Jun 30 to Jul 02
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There are many excellent R resources for visualization, data science, and package development. Hundreds of scattered vignettes, web pages, and forums explain how to use R in particular domains. But little has been written on how to simply make R work effectively—until now. This hands-on book teaches novices and experienced R users how to write efficient R code.

Drawing on years of experience teaching R courses, authors Colin Gillespie and Robin Lovelace provide practical advice on a range of topics—from optimizing the set-up of RStudio to leveraging C++—that make this book a useful addition to any R user’s bookshelf. Academics, business users, and programmers from a wide range of backgrounds stand to benefit from the guidance in Efficient R Programming.

  • Get advice for setting up an R programming environment
  • Explore general programming concepts and R coding techniques
  • Understand the ingredients of an efficient R workflow
  • Learn how to efficiently read and write data in R
  • Dive into data carpentry—the vital skill for cleaning raw data
  • Optimize your code with profiling, standard tricks, and other methods
  • Determine your hardware capabilities for handling R computation
  • Maximize the benefits of collaborative R programming
  • Accelerate your transition from R hacker to R programmer

Colin Gillespie is Senior lecturer (Associate professor) at Newcastle University, UK. His research interests are high-performance computing and Bayesian statistics. He is regularly employed as a consultant by Jumping Rivers and has been teaching R since 2005.

Robin Lovelace is a researcher at the Leeds Institute for Transport Studies (ITS) and the Leeds Institute for Data Analytics (LIDA). Robin has many years using R for academic research and has taught numerous R courses at all levels. He has developed a number of popular R resources, includil3Ä