Earlier quoted context omitted.
I was quite psyched when I read this so maybe I can tell you why it's interesting to me, although I agree the announcement could have done a better job at it. In my experience, the only thing data fields share is SQL (analysts, scientists and engineers). As you said, you could do the same in R, but your project may not be written in R, or Python, but it likely uses an SQL database and some engine to access the data.…
But isn't this then just another tool that you're including in your project? I don't get why I would want to add this as a visualization tool to a project, if it's already using R, or Python, etc... I mean, is it to avoid loading the full data into a dataframe/table in memory? I just don't see what the pain point this solves is. ggplot solves quite a lot of this already, so I don't doubt that the authors know the dom…
In a sense I really get your complaint. It's the xkcd standard thing all over, we now have a new competing standard.
I think for me it's not so much the ggplot connection, or the fact that I won't need a dataframe library.
It's that this might be the first piece of a standard way of plotting: no matter which backend (matplotlib, vega, ggplot), no matter how you are getting your data (dataframes, database), where you're doing this (Jupyter or marimo notebook, python script, R, heck lokkerstudio?). You could have just one way of defining a plot. That's something I've genuinely dreamt about.
And what makes this different from yet another library api to me is that it's integrated within SQL. SQL has already won the query standardisation battle, so this is a very promising idea for the visualization standardisation.