Isabelle Vea thecochenille

UPDATE: I have baked the ideas in this file inside a Python CLI tool called pyds-cli. Please find it here: https://github.com/ericmjl/pyds-cli

How to organize your Python data science project

Having done a number of data projects over the years, and having seen a number of them up on GitHub, I've come to see that there's a wide range in terms of how "readable" a project is. I'd like to share some practices that I have come to adopt in my projects, which I hope will bring some organization to your projects.

Disclaimer: I'm hoping nobody takes this to be "the definitive guide" to organizing a data project; rather, I hope you, the reader, find useful tips that you can adapt to your own projects.

Disclaimer 2: What I’m writing below is primarily geared towards Python language users. Some ideas may be transferable to other languages; others may not be so. Please feel free to remix whatever you see here!

##GTR lset applyto=() nst=6 # GTR lset applyto=() nst=6 rates=propinv # GTR + I lset applyto=() nst=6 rates=gamma # GTR + gamma lset applyto=() nst=6 rates=invgamma # GTR + I + gamma

##SYM

lset applyto=() nst=6                           # SYM

prset applyto=() statefreqpr=fixed(equal)

##GTR lset applyto=() nst=6 # GTR lset applyto=() nst=6 rates=propinv # GTR + I lset applyto=() nst=6 rates=gamma # GTR + gamma lset applyto=() nst=6 rates=invgamma # GTR + I + gamma

##SYM

lset applyto=() nst=6                           # SYM

prset applyto=() statefreqpr=fixed(equal)

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