Efficient R Programming: A Practical Guide to Smarter Programming

Gillespie, Colin; Lovelace, Robin

ISBN 10: 1491950781 / ISBN 13: 9781491950784

Published by O'Reilly Media, 2017

About this Item

This is a well-cared-for used book with light signs of previous use. There may be minor cover wear, a faint crease, or slight spine wear, but overall it's in great shape and fully readable.Please note:-May contain library or rental stickers.-Supplemental materials e.g., CDs, access codes, inserts are not guaranteed.-Box sets may not include original exterior box.-Sourced from donation centers; authenticity not verified with publisher. Your satisfaction is our top priority! If you have any questions or concerns about your order, please don't hesitate to reach out. Thank you for shopping with us and supporting small businessâ happy reading!

Seller Inventory # STM.P4N

Bibliographic Details

• Title: Efficient R Programming: A Practical Guide to Smarter Programming
• Publisher: O'Reilly Media
• Publication Date: 2017
• Language: English
• ISBN 10: 1491950781
• ISBN 13: 9781491950784
• Binding: Soft cover
• Condition: very_good

About this title

Synopsis

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

About the Authors

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, 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.