Public
Edited
Mar 20, 2023
import {Plot} from "@mkfreeman/plot-tooltip"
viewof table = Inputs.table(alphabet)
alphabet
Plot.plot({
marks: [
Plot.barY(alphabet, {x: "letter", y: "frequency", sort: {x: "y", reverse: true}}),
Plot.ruleY([0])
]
})
olympians
Plot.plot({
marks: [
Plot.barX(olympians, Plot.groupY({x: "count"}, {y: "nationality", sort: {y: "x", reverse: true, limit: 10}})),
Plot.ruleX([0])
]
})
Plot.plot({
marks: [
Plot.barX(olympians, {x: ()=>1, y: "nationality", sort: {y: "x", reverse: true, limit: 10},
title: "name"}),
Plot.ruleX([0])
]
})
Plot.plot({
marks: [
Plot.barX(olympians, Plot.groupY({x: "count",title:"count"},
{y: "nationality",
sort: {y: "x", reverse: true,
limit: 20
}
})),
Plot.ruleX([0])
]
}) //팝업 확인해야겠다!
Plot.plot({
marks: [
Plot.barX(olympians, Plot.groupY({x: "count",title:"count"},
{y: d=>d.sport,
sort: {y: "x", reverse: true,
limit: 20
}
})),
Plot.ruleX([0])
]
}) //팝업 확인해야겠다!
Plot.plot({
marks: [
Plot.dot(olympians, Plot.dodgeY({x: "weight",stroke:"steelblue",
opacity:.3,
// r:1
})),
],
x:{
label:"weight (kg) →"
},
width,
height: 100
})
viewof numBins = Inputs.range([1, 100], {label: "Number of bins", step: 1})
Plot.plot({
marks: [
Plot.rectY(olympians, Plot.binX({y: "count"}, {x: "weight", thresholds:numBins})),//thresholds:가로축의 임계값
Plot.ruleY([0])
]
})
Plot.plot({
marks: [
Plot.barY(olympians, Plot.groupX({y: "count"}, {x: "nationality", fill:"sport", title:"sport",//"sport"별로 채우기
sort: {x: "y", reverse: true,
limit: 10
}})), //앞의 그래프랑 방향 바뀌며 세로형으로 셋팅
],
color: {
legend:true
},
width
})
Plot.plot({
marks: [
Plot.barY(olympians, Plot.groupX({y: "count"}, {x: "nationality", fill:"sex", title:"sport",//"sport"별로 채우기
sort: {x: "y", reverse: true,
limit: 10
}})), //앞의 그래프랑 방향 바뀌며 세로형으로 셋팅
],
color: {
legend:true
},
width
})
import {islands} from "@observablehq/datavis-course-lesson-1-introduction"
import {DonutChart} from "@d3/donut-chart"
DonutChart(islands, {name:d=>d.name, value: d=>d.value, innerRadius: 0})
viewof stacking = Inputs.select(["baseline", "silhouette", "wiggle", "expand"], {label: "Stacking method"})
Plot.plot({
y: {
tickFormat: "s"
},
marks: [
Plot.areaY(industries, {x: "date",title: "industry",
offset:stacking === "baseline"? null:stacking,
y: "unemployed", fill: "industry"}),
Plot.ruleY([0])
]
})
viewof table1 = Inputs.table(aapl)
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"})
Plot.plot({
marks: [
Plot.ruleY([0]),
Plot.lineY(aapl, Plot.windowY({x: "Date", y: "Close", reduce:reducer, k: k}))
]
})
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.