I've been shifting a bunch of data analysis out of spreadsheets (and some adhoc SQL) to Jupyter/Pandas, and we've found some unexpected tradeoffs on both sides.
The lack of testability and version control (and really, long-term maintainability) is what drove us out of spreadsheets into Jupyter. We've found though that the workflow in Jupyter, even with Pandas, is not great for exploring and getting a feel for data --- we end up missing the very quick "poking around" you can do in excel or in a good sql client.
I'd have to use Stencila more to know if it strikes the right balance for the kind of analysis work I do, but I'm glad to see such a thoughtful attempt to try a new balance.
The lack of testability and version control (and really, long-term maintainability) is what drove us out of spreadsheets into Jupyter. We've found though that the workflow in Jupyter, even with Pandas, is not great for exploring and getting a feel for data --- we end up missing the very quick "poking around" you can do in excel or in a good sql client.
I'd have to use Stencila more to know if it strikes the right balance for the kind of analysis work I do, but I'm glad to see such a thoughtful attempt to try a new balance.