Reusing already existing is a widely considered as a popular software development practices which provides both benefits and drawbacks for all stakeholders. Prior work reports on how code reuse is a common practice in software development projects, and data science projects such as machine learning pipelines. Recently, there has been much code reuse work in the context of competitive programming. Although there is work such as detecting plagiarism, there is no work that studies how a competitor will reuse their own code. In this paper, we present a preliminary study on the code reuse behavior of three grandmasters EJupyter notebooks in the Kaggle Competitions, an online competition platform for data scientists. and report the types of code they often reuse. We find that Grandmasters are less likely to reuse specialized code, but instead tend to reuse common functions like importing packages (importing the pandas library). They are most likely to reuse common abstractions like importing packages, configurations, file IO operations, show data, plot graphs, define functions and explore files. The work opens up new research potential into recommending how developers can reuse their own code.