[kanitw]

Vega author here. We actually disagree with the last part.

For visual analysis tools (not just UI charting library), having the ability to quickly summarize data is very useful for analyses (esp exploratory ones).

We are not alone with this design choice. ggplot2 in R and GUIs like Tableau also includes data aggregation as first class citizen in their tools.

[breck]

I think I misread the OP that they were talking about separating the implementation code at the vis and data layer (rereading I think they were talking about the user's experience). I disagree and think for a user it's great to have your visualizations and transformations work seamlessly.

My memory of Vega was that it mixed data transform code with vis code. So I didn't have like a dplyr + ggplot2 combo. I thought design wise that was a mistake, because nailing the transforms from an edge case and performance perspective is hard and doing it 2x doesn't make sense to me. So decoupling the vis code from the data engine I think is better.

But I took a fresh look at the Vega repo and it is indeed nicely decoupled, and the transforms look usable standalone. So maybe it sort of already has the Dplyr+GGPlot2 style decoupled architecture that I thought Arquero would bring.

I had thought of Vega as "a monolith for datavis", but now looks like there's lots of smaller usable packages in there.

[jules]

I've only used ggplot2 and found it fantastic compared to standard plotting tools. What has been improved about the design of these type of visualization tools since then?