Software Engineering for Data Scientists: From Notebooks to Scalable Systems

Data science happens in code. The ability to write reproducible, robust, scaleable code is key to a data science project's success—and is absolutely essential for those working with production code. This practical book bridges the gap between data science and software engineering, and clearly explains how to apply the best practices from software engineering to data science.

Examples are provided in Python, drawn from popular packages such as NumPy and pandas. If you want to write better d...