Description
How do you know if your data science results are correct? Robust software usually has tests asserting that certain conditions hold, but as a data scientist it’s often not straightforward or obvious how to integrate these best practices. Our workflow includes exploration, statistical models, and one-off analysis. This talk will give concrete examples of when and how testing should play a role, and provide you with enough introduction to get started writing your first data science tests using pytest & hypothesis.