In this episode, I speak with Miles McBain, a data scientist and R package developer from Brisbane, Australia, about patterns and anti-patterns in data analysis reuse. Miles shares his journey from a generalist software developer to a data science specialist, his passion for R, and the evolution of his coding practices. We delve into the intricacies of code reuse in data analysis, discussing common pitfalls to avoid, the benefits of creating reusable code packages, the process of breaking down large codebases, and how teams can evolve their coding practices to enhance efficiency and maintainability.Important resources mentioned:Patterns and anti-patterns of data analysis reuse blog post by Miles McBainJenny Bryan’s talk ‘Code smells and feels’ presented during useR!2018Connect with Miles McBain:Website: milesmcbain.xyz/GitHub: @milesmcbainMastodon: https://fosstodon.org/@milesmcbainSubscribe to our newsletter: https://rfortherestofus.com/newsletter

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