Thanks for your curiosity @Andrea!
Indeed, all current analyses are confidential and not accessible . But I show some parts of a real current project in a quick gist.
You are correct! Rmd notebooks may include tables, and do include analysis results (like linear model results), when these analyses are not complicated or don't involve large data. I usually import CSVs (they are not large, and can then be shared easily), created with my munging code, as follows.
/code is usually for data munging, or "ETL" stuff: this is the messy and time consuming part. As you point out, .R files are easier to debug, version control, and collaborate on (using github), and then I just import the derived datasets into the Rmd notebooks, which are lean and run quickly.
This is a living workflow, which works well for me and my stakeholders and that is why it exists.
However, I know lots of team members who write long Rmd notebooks which include everything: data munging, outputs, results, etc, following the literate programming paradigm.