Public
Edited
Dec 19
container={Plot.plot({
facet: {
data: olympians,
y: "sport",
marginLeft: 50
},
marks: [
Plot.frame({stroke: "#aaa", strokeWidth: 0.5}),
Plot.dot(olympians, {x: "weight", y: "sex", fill: "sex", r: 3})
],
height: 800,
marginTop: 0,
marginLeft: 100,
width,
x: {inset: 10, grid: true, label: "weight (kg) →"},
y: {axis: null, inset: 2},
color: {legend: true}
})}
Plot.plot({
x: {
axis: null,
domain: stateage.ages
},
y: {
grid: true,
tickFormat: "s"
},
color: {
domain: stateage.ages,
scheme: "spectral",
legend: true
},
fx: {
domain: d3.groupSort(stateage, v => d3.sum(v, d => -d.population), d => d.state).slice(0, 6),
label: null,
tickSize: 6
},
facet: {
data: stateage,
x: "state"
},
marks: [
Plot.barY(stateage, {x: "age", y: "population", fill: "age", title: "age"}),
Plot.ruleY([0])
],
width
})
import {stateage} from "@observablehq/plot-bar"
import {Plot} from "@mkfreeman/plot-tooltip"
viewof k = Inputs.range([1, 20], {label: "Window size", step: 1, value: 1})
viewof reducer = Inputs.select(["mean", "median", "min", "max", "sum", "ratio"], {label: "Reducer"})
smooth = Plot.plot({
marks: [
Plot.ruleY([0]),
Plot.lineY(aapl, Plot.windowY({x: "Date", y: "Close", reduce: reducer, k: k}))
]
})
Plot.plot({
marks: [
Plot.ruleY([1]),
Plot.line(stocks,
Plot.normalizeY({x: "Date", y: "Close", stroke: "Symbol", title: "Symbol"})),
],
y: {
type: "log",
grid: true,
label: "↑ Change in price (%)",
tickFormat: (f => x => f((x - 1) * 100))(d3.format("+d"))
},
})
import {stocks} from "@observablehq/plot-map"
Plot.plot({
marks: [
Plot.barY(alphabet, {x: "letter", y: "frequency",
title: b=> `${b.letter}: ${(b.frequency*100).toFixed(2)}%`,
sort: {x: "y", reverse: true}}),
Plot.ruleY([0])
]
})
alphabet
//selectedAthletes = olympians.filter(d=>d.nationality === "USA")
Plot.plot({
marks: [
Plot.rectY(selectedAthletes, Plot.binX({y: "count"}, {x: "weight", fill: "sex"})),
Plot.ruleY([0])
],
color: {
legend: true
},
x: {
domain: [0, 200]
}
})
viewof selectedAthletes = Inputs.select(d3.group(olympians, d=>d.sport),{label:"Sport: "})
Plot.plot({
marks: [
Plot.rectY(selectedAthletes, Plot.binX({y: "count"}, {x: "weight", fill: "sex"})),
Plot.ruleY([0])
],
color: {
legend: true
},
x: {
domain: [0, 200]
}
})
viewof minFrequency = Inputs.range([0, .15], {label: "Min Frequency", step: .01, value: 0})
alphaFiltered = alphabet.filter(d=>d.frequency >=minFrequency)
Plot.plot({
marks: [
Plot.barY(alphaFiltered, {x: "letter", y: "frequency" }),
Plot.ruleY([0])
],
x: {domain: d3.sort(alphabet.map(d=>d.letter))}
})
viewof minFreq2 = Inputs.range([0, .15], {label: "Min Frequency", step: .01, value: 1})
Plot.plot({
marks: [
Plot.ruleY([0, minFreq2]),
Plot.barY(alphabet, {x: "letter", y:"frequency",
fill: d=>d.frequency >=minFreq2 ? "steelblue" : "lightgray"})
]
})
viewof cylinders = Inputs.radio([3,4,5,6,8], {label: "Cylinders", value: 3})
viwofcylinders = Plot.plot({
marks: [
Plot.dot(cars, {x:"power (hp)", y: "economy (mpg)", title: "name",
fill: d=>d.cylinders === cylinders? "steelblue" : "lightgray",
fillOpacity: d=>d.cylinders === cylinders? 0.8 : 1,
r:d=>d.cylinders === cylinders ? 4:2
})
],
height: 600,
width
})
import {carMakes} from "@observablehq/lesson-2-data-representation"
carMakes
viewof xDimension = Inputs.select(["economy (mpg)", "displacement (cc)", "power (hp), weight (lb)", "0-60 mph(s)"], {label: "X Axis"})
viewof yDimension = Inputs.select(["make", "cylinders"], {label: "Y Axis"})
Plot.plot({
marks: [
Plot.dot(carMakes, {x:xDimension, y:yDimension, fill: "cylinders", title:"name",
sort:{y:"x", reverse: true, limit: 10}})
],
color:{
type: "ordinal",
legend: true
},
marginLeft: 100,
width
})
viewof duration = Inputs.range([1, 30], {label: "# of Years", step: 1, value: 30})
viewof purchasePrice = Inputs.range([100000, 1000000], {label: "Purchase PRice", step: 50000, value: 650000})
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