Book Image

Learning R Programming

By : Kun Ren
Book Image

Learning R Programming

By: Kun Ren

Overview of this book

R is a high-level functional language and one of the must-know tools for data science and statistics. Powerful but complex, R can be challenging for beginners and those unfamiliar with its unique behaviors. Learning R Programming is the solution - an easy and practical way to learn R and develop a broad and consistent understanding of the language. Through hands-on examples you'll discover powerful R tools, and R best practices that will give you a deeper understanding of working with data. You'll get to grips with R's data structures and data processing techniques, as well as the most popular R packages to boost your productivity from the offset. Start with the basics of R, then dive deep into the programming techniques and paradigms to make your R code excel. Advance quickly to a deeper understanding of R's behavior as you learn common tasks including data analysis, databases, web scraping, high performance computing, and writing documents. By the end of the book, you'll be a confident R programmer adept at solving problems with the right techniques.
Table of Contents (21 chapters)
Learning R Programming
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface

Profiling code


In the previous section, you learned how to use microbenchmark() to benchmark expressions. This can be useful when we have several alternative solutions to a problem and want to see which has better performance and when we optimize an expression and want to see whether the performance actually gets better than the original code.

However, it is usually the case that, when we feel the code is slow, it is not easy to locate the expression that contributes most to slowing down the entire program. Such an expression is called a "performance bottleneck." To improve code performance, it is best to resolve the bottleneck first.

Fortunately, R provides profiling tools to help us find the bottleneck, that is, the code that runs most slowly, which should be the top focus for improving code performance.

Profiling code with Rprof

R provides a built-in function, Rprof(), for code profiling. When profiling starts, a sampling procedure is running with all subsequent code until the profiling is...