It's About Time: Strategies for Wrangling Temporal Data with R (Harrison Dekker, Tim Dennis)
Time measurement variables often play a fundamental role in social science data analysis. To accommodate this, statistical software typically includes a data type specifically for temporal variables to allow for proper ordering and time-specific measurement. In addition to these data types, statistical programming languages also provide a variety of functions for working with time variables. Examples include functions for converting strings to dates or for reformatting dates into a standard form. Despite these programming language accommodations, temporal variables are often the source of unique data wrangling challenges. This workshop will review the basics then explore some typical challenges encountered when working with dates. Also included will be strategies for effectively plotting and visualizing temporal data. Some prior experience with R will be required.