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This workshop is offered in person in DataLab’s classroom in Shields Library. A Zoom broadcast option is also available. Advance registration required: https://reservations.library.ucdavis.edu/event/11931823

Description

This intermediate R workshop focuses on how to find and fix bugs in your R code, as well as how to make code more reliable and efficient in the first place. We’ll cover how to raise and handle messages, warnings and errors in R, how to use R’s built-in debugger, and how to estimate or measure the performance of your code. We’ll also discuss programming strategies you can use to help keep your code efficient and bug-free!

This workshop is NOT an introduction to R and is intended for motivated intermediate to advanced learners from all domains at UC Davis who want to hone their R skills. Please make sure you meet the prerequisites before registering as we will be unable to answer introductory R questions during this session. (Want to brush up on R? Check out our R Basics 4-part introductory series.)

Objectives

After completing this workshop, learners should be able to:
– Interpret and catch warnings and errors;
– Plan a strategy for debugging code;
– Determine the cause(s) of bugs in code using R’s debugging tools;
– Compute ballpark estimates of memory requirements for code;
– Use benchmarking to reliably measure how fast code runs;
– Explain what profiling is and how it’s used;

Prerequisites

Participants must have taken DataLab’s “R Basics” workshop series and/or have prior experience using R, be comfortable with basic R syntax, and have the latest versions of R and RStudio pre-installed and running on their laptops.

Instructors

Nick Ulle is a statistician and computer scientist. Prior to DataLab he was a visiting assistant professor of Statistics at UC Berkeley, where he designed and taught courses in data science. During his PhD in Statistics at UC Davis, he developed source code analysis techniques for the R programming language. His research interests include statistical computing, programming languages, data visualization, and pedagogy.

Wesley Brooks holds a Statistics Ph.D. from the University of Wisconsin. He works at the DataLab as a Data Scientist.

Cover photo attribution: Guilherme Tavares.