Join us for the April edition of SheffieldR User Group, where we continue to explore the exciting world of R programming and its applications. This month, we’re thrilled to feature two insightful talks from experts in the field.
Our first speaker, Daniel Brady, will delve into the intricacies of profiling and code optimization in R. Discover how to streamline your code for improved efficiency and performance, as Dan shares practical tips and techniques to enhance your programming skills.
Following Dan’s presentation, we’ll hear from Joe Heffer, who will introduce us to strategies used in R while implementing a pipeline. Dive into the world of health data as Joe walks us through packaging, ensuring data integrity, and handling sensitive data securely through the development and implementation of a pipeline.
Meeting is 2024-04-22 12:00-1:30 in Regent Court, John Pemberton LT B (40). Sign up here. Remote attendance is possible using Google Meet.
If you have any questions or enquiries please email us sheffieldr@sheffield.ac.uk.
Profiling and optimising your R code
Nobody likes slow code, luckily most programming languages provide you with tools to help you analyse and enhance your code’s performance and R is no exception.
In this session we’ll cover some of the tools and strategies available in the R ecosystem to optimise your code. We’ll start by giving a brief introduction to profiling, and then we’ll use the {profvis} to profile some code to determine which parts are taking up the most execution time. Then we’ll move on to discuss potential strategies that reduce execution time, and we’ll use the {bench} to compare these different strategies against one another to find the best performing solution.
Biography - Daniel Brady
Dr Daniel Brady is a Research Software Engineer in the RSE team at the University of Sheffield. His background is in Cognitive Neuroscience, completing his PhD at Goldsmiths in 2016. Since then he has worked as a Research Fellow at Birkbeck and the University of Surrey and as Research Technician at the University of Reading. He has experience of writing research software and analysis pipelines using R, Python and Julia. He is also a keen advocate of open and reproducible research practices.
R Strategies for Health Data Pipelines
In this session, we delve into the intricate world of health data. Our discussion encompasses crucial aspects such as data packaging, ensuring data integrity, and handling sensitive health data securely.
Navigating the complexities of health data, we address the challenges associated with the arrival of unforeseen data volumes. With a focus on scalability, we examine techniques to handle unexpectedly large data sets using packages like {arrow} and {DuckDB} and {dplyr}.
Biography - Joe Heffer
Dr Joe Heffer is a Research Data Engineer at the University of Sheffield where he has worked on various project across the University. He actively assists researchers in leveraging data engineering techniques to uncover insights and drive impactful research outcomes. Additionally, Joe advocates for best practices and fosters an open community of collaboration among researchers and data professionals.