A data science cookiecutter

Is Your Feature Request Related to a Problem? Please Describe

We recently chatted with @samcunliffe and Niko from SWC (cannot tag him) about a cookiecutter for data science / scientific analysis / exploratory Python projects.

The idea would be to have some lighter requirements than for a fully-fledged Python package. And maybe some data science specific additions (like for example functionality for formatting and checking notebooks). This could be useful for many researchers, and maybe a good entry point to getting into good software practices.

Describe the Solution You'd Like

If we find this could be useful, we could have it:

• in a separate repo, or
• as part of this repo, and ask the user in the initial config phase which version they want to instantiate. @samcunliffe mentioned we could maybe use hidden variables for this.

Alternatively, we can just point to a good cookiecutter for this purpose if that already exists.

Describe Alternatives You've Considered

There are some examples of research cookiecutter:

• this one is very basic (mostly a directory structure) but maybe a good starting point if we decide we want to implement this ourselves.
• this one seems more recent and quite well documented. It may be a good one to point to if we decide that doing one ourselves is out of scope

Additional Context

No response

Start by reviewing the proposed data-science cookiecutter goals and comparing the two linked research cookiecutter examples. The issue names no files, tests, or implementation entry point; the work is done when the project scope and whether to implement or recommend an existing template are decided and documented.