Qualitative research often involves the use of codes as a way to label and organize data. These codes become the basis of analysis and the way researchers both choose to understand and explain their data. While some qualitative software packages offer ways to view analytical choices, visualisation of analysis is not standard to either analytical or communicative steps in qualitative research. In contrast, data science practitioners have long argued for visualisation as a standard step in data analysis, arguing that it assists with understanding and aids transparent reporting. Using theories and practices from data science and qualitative analysis, this presentation will make a case for visualisation as a standard tool of analytical thinking in qualitative research, and will offer a solution that is both reproducible for researchers and visually simple for readers. Applying visualisation methods to qualitative analysis can help researchers better understand their data set, and offers an additional way to communicate one’s analyses and conclusions.