Yes, I don't necessarily disagree with anything you said. I didn't mean to imply that SQL was ideal for very good beyond a fairly limited set of functionality, which I would loosely describe as: a system for which many stored operations and refactoring becomes a necessity.
The use case I have in mind is with wrangling multiple, disparate datasets, into a normalized format that can be piped into a visualization function, or into a Rails app (for which an ORM like ActiveRecord can suffice going forward). And also, I'm thinking of people relatively new to data in general. I find SQL as a language offers a more explicit and rigid way of communicating data transformation concepts. After that, for most people who end up learning pandas/R, it's generally easier to do all the work in those frameworks (especially if you like notebooks).