Monitor performance issues & errors in your code

Maintainable data science: Tips for non-developers

Episode #227, published Wed, Aug 28, 2019, recorded Tue, Aug 6, 2019

Did you come to software development outside of traditional computer science? This is common, and even how I got into programming myself. I think it's especially true for data science and scientific computing. That's why I'm thrilled to bring you an episode with Daniel Chen about maintainable data science tips and techniques.

Links from the show

Daniel on Twitter: @chendaniely
Pandas for Everyone book:
pyprojroot project:

Jenny Bryan naming things:

Jenny Bryan’s code smells:

3 papers that are highly relevant papers:
A Quick Guide to Organizing Computational Biology Projects:
Best Practices for Scientific Computing:
Good enough practices in scientific computing:
Episode transcripts:

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Daniel Chen
Daniel Chen
Daniel is a Ph.D. student at Virginia Tech in the Genetics, Bioinformatics, and Computational Biology program. His current research topic is in education, where he is aiming to bring data science skills to medical practitioners.

He's also finishing up his summer internship at RStudo working on a library to grade student's code that gives meaningful feedback to why the solution is wrong.
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