  This paper explores an innovative approach to teaching data wrangling skills
to students through hands-on activities before transitioning to coding. Data
wrangling, a critical aspect of data analysis, involves cleaning, transforming,
and restructuring data. We introduce the use of a physical tool, mathlink
cubes, to facilitate a tangible understanding of data sets. This approach helps
students grasp the concepts of data wrangling before implementing them in
coding languages such as R. We detail a classroom activity that includes
hands-on tasks paralleling common data wrangling processes such as filtering,
selecting, and mutating, followed by their coding equivalents using R's `dplyr`
package.
