This 2-part workshop series for intermediate R programmers focuses on how to load and prepare data for analysis. We’ll explore how to screen a data set for potential problems with its structure and data types, as well as how to correct these issues. For example, it is increasingly popular to to use datasets loaded from text files or scraped from the web, but these data often have formatting features that need additional processing before they can be used. Thus, we’ll take a deep dive into R’s “stringr” package for text processing. Dates and times are another kind of data that can be difficult to work with, and we’ll cover the basics of using the “lubridate” package for processing temporal data. You’ll also learn how to reshape data with structural problems and how to combine linked data sets.

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.)

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.

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