Python is rapidly emerging as the programming language of choice for data analysis inthe atmosphere and ocean sciences. By consulting online tutorials and help pages, mostresearchers in this community are able to pick up the basic syntax and programmingconstructs (e.g., loops, lists and conditionals). This self-taught knowledge is sufficient toget work done, but it often involves spending hours to do things that should take minutes,reinventing a lot of wheels, and a nagging uncertainty at the end of it all regarding thereliability and reproducibility of the results. To help address these issues, the Pythonfor Atmosphere and Ocean Scientists educational materials cover a suite of programmingand data management best practices that are not so easy to glean from a quick Googlesearch.