The box mark could use bin/rect instead of group/bar for quantitative data

As an approximation:

Plot.plot({
  marks: [
    Plot.ruleX(data, Plot.binX({y1: loqr1, y2: hiqr2}, {x, y})),
    Plot.rectY(data, Plot.binX({y1: "p25", y2: "p75"}, {x, y, fill: "#ccc"})),
    Plot.ruleY(data, Plot.binX({y: "p50"}, {x, y, strokeWidth: 2})),
    Plot.dot(data, Plot.map({y: oqr}, {x, y, z: ???}))
  ]
})

I couldn’t figure out how to compute the per-bin outliers, though. Maybe we need a Plot.binmapX transform where z can be imputed by binning x? Or maybe there’s a way to compose the bin and map transform? 🤔

Ref. https://talk.observablehq.com/t/how-to-label-a-boxplot-with-dates-format-axis/7739/3

Start by reviewing the box mark entry point and the existing Plot.binX and Plot.map transforms referenced in the issue. Determine whether the requested behavior should use bin/rect for quantitative data and how per-bin outliers would be represented; the work is done when the intended box-mark behavior and supporting API are implemented and verified.