Bug reports provide insight about the quality of an evolving software and about its development process. Such data, however, is often incomplete and inaccurate, and thus should be cleaned before analysis. In this paper, we present patterns that help both novice and experienced data scientists to discard invalid bug data that could lead to wrong conclusions.