— with Roland Toth (WI)
When: 11 November 2026, 10am-5pm
Where: WI Flexroom (A1_04)
Level: Intermediate/advanced
Category: Data wrangling/analysis
Seats: 20 (in-person only)
Abstract: Proper and reproducible data wrangling is the key to any successful data analysis. While traditional statistical software offers limited flexibility, R stands out as a powerful, open-source programming language tailored to working with data. With thousands of free packages and a vibrant community, R enables every stap from handling raw data, through intricate data wrangling and advanced statistical modeling to dynamic visualization and documentation.
In the workshop Advanced Data Wrangling with R, you will go beyond the basics to explore the full potential of R in real-world research scenarios. We will dive into the tidyverse ecosystem, focusing on efficient data manipulation using dplyr and pipes, advanced string handling with regular expressions, and creating reusable functions to automate repetitive tasks. A highlight is the integration of Quarto, the modern successor to R Markdown, which allows you to craft fully reproducible reports, presentations, and interactive web content directly from your R code. You’ll learn how to produce documentions of data wrangling procedurs that automatically update with new data and information. Over a single woprkshop day, you’ll progress from foundational concepts to hands-on project work, applying your skills to a real dataset to lay the foundation for any analysis. Whether you’re working with survey data, longitudinal panels, or complex text-based information, this workshop will equip you with the tools and confidence to transform raw data into cleanly structured information.
Participants need beginner/intermediate experience with R or another programming language and at least a basic understanding of (descriptive) statistics to be able to follow this workshop.
Roland Toth is a Data Scientist/Postdoctoral Researcher at the Methods Lab at the Weizenbaum Institute, where he supports the research groups at the institute methodologically. His research focuses on mobile media use and mobile methods, such as the Mobile Experience Sampling Method, logging, and data donations.