Efficient R Programming: A Practical Guide to Smarter Programming Contributor(s): Gillespie, Colin (Author), Lovelace, Robin (Author) |
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ISBN: 1491950781 ISBN-13: 9781491950784 Publisher: O'Reilly Media OUR PRICE: $35.99 Product Type: Paperback - Other Formats Published: January 2017 |
Additional Information |
BISAC Categories: - Computers | Programming Languages - General - Computers | Programming - Object Oriented - Computers | Databases - Data Mining |
Physical Information: 0.4" H x 6.9" W x 9.1" (0.70 lbs) 219 pages |
Descriptions, Reviews, Etc. |
Publisher Description: 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.
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Contributor Bio(s): Gillespie, Colin: - 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. Lovelace, Robin: -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, including Introduction to Visualising Spatial Data in R and Spatial Microsimulation with R (Lovelace and Dumont 2016). These skills have been applied on a number of projects with real-world applications, including the Propensity to Cycle Tool, a nationally scalable interactive online mapping application and the stplanr package. |