Public
Edited
Dec 23
data = FileAttachment("debate_analysis_data0-30WithRef.json").json()
viewof turn = Inputs.range([0, 30], {label: "Turn", step: 1})
clarityWeightedData.sort((a, b) => b.weightedValue - a.weightedValue);
Plot.plot({
marginLeft: 100,
marginRight: 100,
height: 100,
width: 800,
x: { label: "Total Weighted Value" },
y: { domain: ["Clarity"], label: "Clarity Category" }, // Single stacked bar for "Clarity"
marks: [
// Create the single stacked bar chart, using the aggregated main categories
Plot.barX(clarityWeightedData, {
x: "weightedValue",
y: () => "Clarity", // Single bar for clarity category
fill: "subcategory", // Stack by main category (e.g., Explicitness, Concision)
title: d => `${d.subcategory}: ${Math.floor(d.weightedValue)}`, // Tooltip with category and weighted value
sort: { x: "x", reverse: true },
tip: true,
})
]
});
tp.data(styleData)
.rect({
x: d => String(d.sentence),
y: '~style',
fill: '~score',
fillScheme: d3.interpolateBlues,
note: '~score',
noteColor: d => d.score > 500 ? '#eee' : '#000',
})
.option({
width: 660,
height: 420,
grid: false,
axis: false,
tickLength: 0,
xLabelFontSize: 12,
yLabelFontSize: 12,
xAxisPosition: 'top',
yReverse: true,
yTitle: false,
})
.plot()
tp = (await import('https://cdn.skypack.dev/@gjmcn/teapot@0.3.0')).tp
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.