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Plot.plot({
x: {
// map all dates to 2000 by removing n * 365.24 days; Feb 29 will not create a gap
transform: (d) => d3.utcDay.offset(d, (2000 - d.getUTCFullYear()) * 365.24),
tickFormat: "%b",
line: true
},
y: { nice: true, grid: true, zero: true },
marks: [
Plot.line(data, {
x: "date",
y: "extent",
stroke: ({ date }) => date.getUTCFullYear(), // z separates the lines
})
]
})
Plot.plot({
x: {
// map all dates to 2000 (a *leap-year*) by removing n years; Feb 29 will be skipped if missing
transform: (d) => d3.utcYear.offset(d, 2000 - d.getUTCFullYear()),
tickFormat: "%b",
line: true
},
y: { nice: true, grid: true, zero: true, label: "↑ ice extent" },
marks: [
Plot.line(data, {
x: "date",
y: "extent",
stroke: ({ date }) => date.getUTCFullYear()
})
]
})
data = FileAttachment("sea-ice-extent.csv").csv({ typed: true })
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.