How are data about migration portrayed visually, and what do these portrayals imply for communicating this salient issue? Data visualizations—comprising representations of information that aim to enhance understanding—are increasingly commonplace in journalistic and policy settings. Visualization’s popularity is partly motivated by assumptions that quantitative evidence ‘speaks for itself’, and that visual representations of data are more understandable for users. Scholars have begun to question these assumptions, especially in political domains where evidence and values potentially clash. This paper provides an empirical foundation for discussions about images’ roles in politics by contributing novel evidence of the characteristics present in data visualizations about migration that are publicly available. Theoretically, I draw upon frame-building to relate decisions about message content with effects on political behaviors and attitudes. Empirically, I present results analyzing 300 migration visualizations scraped from Google Images. Using content analysis (validated by inter-coder reliability tests) and qualitative social semiotic methods, I identify key patterns in these images, including the dominance of ‘clean’ white layouts and a limited variety of chart types. I conclude by considering the implications for visual framing and migration public opinion, as well as exploring how other computational techniques could be applied to study this dataset.