CodeLin: An in situ visualization method for understanding data transformation scripts
Xiwen Cai, Kai Xiong, Zhongsu Luo, Di Weng, Shuainan Ye, Yingcai Wu · Visual Informatics · 2025
Understanding data transformation scripts is an essential task for data analysts who write code to process data. However, this can be challenging, especially when encountering unfamiliar scripts. Comments can help users understand data transformation code, but well-written comments are not always present. Visualization methods have been proposed to help analysts understand data transformations, but they generally require a separate view, which may distract users and entail efforts for connecting visualizations and code. In this work, we explore the use of in situ program visualization to help data analysts understand data transformation scripts. We present CodeLin, a new visualization method that combines word-sized glyphs for presenting transformation semantics and a lineage graph for presenting data lineage in an in situ manner. Through a use case, code pattern demonstrations, and a preliminary user study, we demonstrate the effectiveness and usability of CodeLin. We further discuss how visualization can help users understand data transformation code.