Select a data source…
Type Chart, then Shift-Enter. Ctrl-space for more options.
links = d3.csvParse(await FileAttachment("belichick_coaches_relationships.csv").text())
types = Array.from(new Set(links.map(d => d.type)))
data = ({nodes: Array.from(new Set(links.flatMap(l => [l.source, l.target])), id => ({id})), links})
height = 1000
color = d3.scaleOrdinal(types, d3.schemeCategory10)
function linkArc(d) {
const r = Math.hypot(d.target.x - d.source.x, d.target.y - d.source.y);
return `
M${d.source.x},${d.source.y}
A${r},${r} 0 0,1 ${d.target.x},${d.target.y}
`;
}
drag = simulation => {
function dragstarted(event, d) {
if (!event.active) simulation.alphaTarget(0.3).restart();
d.fx = d.x;
d.fy = d.y;
}
function dragged(event, d) {
d.fx = event.x;
d.fy = event.y;
}
function dragended(event, d) {
if (!event.active) simulation.alphaTarget(0);
d.fx = null;
d.fy = null;
}
return d3.drag()
.on("start", dragstarted)
.on("drag", dragged)
.on("end", dragended);
}
d3 = require("d3@6")
import {swatches} from "@d3/color-legend"
top = d3.csvParse(await FileAttachment("topcoach.csv").text())
Plot.plot({
marginLeft: 100,
marks: [
Plot.barX(top, {x: "years", y: "coach", fill: "purple", sort: {y: "x", reverse: true}}),
Plot.ruleX([0])
]
})
win_rates = d3.csvParse(await FileAttachment("belichick_coaches@3.csv").text())
Plot.rectY(win_rates, Plot.binX({y: "count"}, {x: "total_wr"})).plot()
Plot.plot({
round: true,
color: {legend: true},
marks: [
Plot.rectY(win_rates, Plot.binX({y2: "count"}, {x: "total_wr", fill: "type_of_coach", mixBlendMode: "multiply"})),
Plot.ruleY([0])
]
})
Plot.plot({
y: {
grid: true,
inset: 6,
type: "linear"
},
marks: [
Plot.boxY(win_rates, {x: "depth", y: "total_wr"}),
]
})
FileAttachment("sparql.txt").text()
Select a data source…
Type Table, then Shift-Enter. Ctrl-space for more options.
FileAttachment("belichick_preprocess.py").text()
FileAttachment("belichick_tree.txt").text()
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