R is an extremely powerful tool for data modeling, visualization, and general programming. In many practical applications of statistics, the vast majority of time is spent preparing the data for eventual analysis. However, this also where many practitioners who use R often have relatively little training. In recent years, a variety of packages have become available to make data wrangling, summarizing, generation and other common operations more straightforward, and easier to read for future use (e.g. via piping and clearer syntax). In addition, some newer visualization packages work these approaches, allowing one to go quite seamlessly from raw data to interactive graphics. This workshop will introduce participants to a handful of tools that can make their data exploration and analytical flow more streamlined and reproducible.