I love to build dataviz for insight discovery. I also love to put technology to the service of humanity
Published unlisted
Edited
Jun 18, 2022
{
const highlight = vl.selectPoint("highlight");
return vl
.markRect({ strokeWidth: 2 })
.select(highlight)
.encode(
vl.y().fieldN("actual"),
vl.x().fieldN("predicted"),
vl.fill().fieldQ("count"),
vl
.stroke()
.condition({ param: "highlight", empty: false, value: "black" })
.value(null)
)
.data([
{ actual: "A", predicted: "A", count: 13 },
{ actual: "A", predicted: "B", count: 0 },
{ actual: "A", predicted: "C", count: 0 },
{ actual: "B", predicted: "A", count: 0 },
{ actual: "B", predicted: "B", count: 10 },
{ actual: "B", predicted: "C", count: 6 },
{ actual: "C", predicted: "A", count: 0 },
{ actual: "C", predicted: "B", count: 0 },
{ actual: "C", predicted: "C", count: 9 }
])
.config({
scale: {
bandPaddingInner: 0,
bandPaddingOuter: 0
},
view: { step: 40 },
range: {
ramp: {
scheme: "yellowgreenblue"
}
},
axis: {
domain: false
}
})
.render();
}
err = {
const highlight = vl.selectPoint("highlight").empty(false);
return vl
.markRect({ strokeWidth: 2 })
.select(highlight)
.encode(
vl.y().fieldN("actual"),
vl.x().fieldN("predicted"),
vl.fill().fieldQ("count"),
vl.stroke().if(highlight, vl.value("black")).value(null)
)
.data()
.config({
scale: {
bandPaddingInner: 0,
bandPaddingOuter: 0
},
view: { step: 40 },
range: {
ramp: {
scheme: "yellowgreenblue"
}
},
axis: {
domain: false
}
})
.render();
}
data = [
{ actual: "A", predicted: "A", count: 13 },
{ actual: "A", predicted: "B", count: 0 },
{ actual: "A", predicted: "C", count: 0 },
{ actual: "B", predicted: "A", count: 0 },
{ actual: "B", predicted: "B", count: 10 },
{ actual: "B", predicted: "C", count: 6 },
{ actual: "C", predicted: "A", count: 0 },
{ actual: "C", predicted: "B", count: 0 },
{ actual: "C", predicted: "C", count: 9 }
]
embed({
data: {
values: [
{ actual: "A", predicted: "A", count: 13 },
{ actual: "A", predicted: "B", count: 0 },
{ actual: "A", predicted: "C", count: 0 },
{ actual: "B", predicted: "A", count: 0 },
{ actual: "B", predicted: "B", count: 10 },
{ actual: "B", predicted: "C", count: 6 },
{ actual: "C", predicted: "A", count: 0 },
{ actual: "C", predicted: "B", count: 0 },
{ actual: "C", predicted: "C", count: 9 }
]
},
params: [{ name: "highlight", select: "point" }],
mark: { type: "rect", strokeWidth: 2 },
encoding: {
y: {
field: "actual",
type: "nominal"
},
x: {
field: "predicted",
type: "nominal"
},
fill: {
field: "count",
type: "quantitative"
},
stroke: {
condition: {
param: "highlight",
empty: false,
value: "black"
},
value: null
},
opacity: {
condition: { param: "highlight", value: 1 },
value: 0.5
},
order: { condition: { param: "highlight", value: 1 }, value: 0 }
},
config: {
scale: {
bandPaddingInner: 0,
bandPaddingOuter: 0
},
view: { step: 40 },
range: {
ramp: {
scheme: "yellowgreenblue"
}
},
axis: {
domain: false
}
}
})
import { vl } from "@vega/vega-lite-api-v5"
embed = require("vega-embed@6")
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