| Tags | clean-code python |
Code is read more often than it is written. Notebooks, especially, are made to be looked at. Assist yourself and others by keeping your code and notebooks neat!
Naming conventions and other good python practices are listed in the PEP 8 Style Guide.
Also see these code quality best practices.
For Data Science workflow best practices, please familiarise yourself with the cookiecutter data science project and read this description of how to organise your projects using atom and Jupyter on LaptrinhX.