Working with jupyter, I'm seriously contemplating around how to bring the best of Excel into a pandas or jupyter workflow. Mostly for exploration but also making reports, statistics, aggregations
(I'm pretty biased since I wrote a book on this, Effective Pandas.)
My take is that if you embrace the limitation of chaining in Pandas it will force you to write better (easier to read, debug, deploy, share, collaborate) code.
I can't look very deeply into your link and see what the courses actually say, from here, so I'm not sure. I think you want to teach me to be better at pandas. That's fine and I learn pandas constantly, but not what I'm talking about. I want to mix in a different way of working with data, getting some of the best features of excel into the notebook workflow.
I also believe that getting to know your data means reading it in a grid, not just looking at aggregations. Both are important, and with aggregations you can miss important things! Sometimes the simplest solutions are the best.
