Public
Edited
Apr 21, 2024
populationByPrefecture
Type Table, then Shift-Enter. Ctrl-space for more options.
addTooltips(
Plot.plot({
marginLeft: 80,
x: {
grid: true,
tickFormat: "s"
},
color: {scheme: "spectral", domain: genders, legend: true},
marks: [
Plot.barX(populationByPrefectureGender, {
y: "district",
x: "population",
fill: "gender",
title: "population",
sort: {y: "x", reverse: true}
}),
Plot.ruleX([0])
]
})
)
chart = PieChart(populationByPrefecture, {
name: d => d["地区"],
value: d => d["男"] + d["女"],
})
addTooltips(
Plot.plot({
projection: {
type: "albers",
rotate: [-110, 0],
domain: prefectures
},
marks: [
Plot.geo(prefectures, {
fill: p => prefectureToPopulation.get(p.properties.fullname),
title: p => `${p.properties.name} \n ${prefectureToPopulation.get(p.properties.fullname).toLocaleString()}`
})
],
margin: 20,
color: {
scheme: "reds", // Change color scheme
unknown: "#ddd", // Polygons with unknown values are gray
type: "linear", // Linear scale for color progression
legend: true, // Add the legend
tickFormat: "s",
label: "Population", // Update legend label
}
})
)
populationByCounty
Type Table, then Shift-Enter. Ctrl-space for more options.
addTooltips(
Plot.plot({
projection: {
type: "albers",
rotate: [-110, 0],
domain: prefectures
},
marks: [
counties.map(county => Plot.geo(county, {
fill: p => countyToPopulation.get(p.properties.fullname),
title: p => {
let name = p.properties.fullname
return `${name} \n ${countyToPopulation.get(name).toLocaleString()}`
}
})),
Plot.geo(prefectures),
],
margin: 20,
color: {
scheme: "reds", // Change color scheme
unknown: "#ddd", // Polygons with unknown values are gray
type: "linear", // Linear scale for color progression
legend: true, // Add the legend
tickFormat: "s",
label: "Population", // Update legend label
}
})
)
import {addTooltips} from "@mkfreeman/plot-tooltip"
import {PieChart} from "@d3/pie-chart"
workbook = FileAttachment("人口普查.xlsx").xlsx()
populationByPrefecture = workbook.sheet("地级", { headers: true })
genders = ["男", "女"]
populationByPrefectureGender = genders.flatMap(gender => populationByPrefecture.map(d => ({district: d.地区, gender, population: d[gender]})))
prefectureToPopulation = new Map(populationByPrefecture.map(({地区, 男, 女}) => [地区, 男 + 女]))
populationByCounty = workbook.sheet("县级", { headers: true })
countyToPopulation = new Map(populationByCounty.map(({地区, 男, 女}) => [地区, 男 + 女]))
innerMongolia = d3.json("https://geojson.cn/api/data/150000.topo.json")
prefectures = topojson.feature(innerMongolia, innerMongolia.objects.default)
呼和浩特 = FileAttachment("150100.topo.json").json()
包头 = FileAttachment("150200.topo.json").json()
乌海 = FileAttachment("150300.topo.json").json()
赤峰 = FileAttachment("150400.topo.json").json()
通辽 = FileAttachment("150500.topo.json").json()
鄂尔多斯 = FileAttachment("150600.topo.json").json()
呼伦贝尔 = FileAttachment("150700.topo.json").json()
巴彦淖尔 = FileAttachment("150800.topo.json").json()
乌兰察布 = FileAttachment("150900.topo.json").json()
兴安 = FileAttachment("152200.topo.json").json()
锡林郭勒 = FileAttachment("152500.topo.json").json()
阿拉善 = FileAttachment("152900.topo.json").json()
counties = [呼和浩特,包头,乌海,赤峰,通辽,鄂尔多斯,呼伦贝尔,巴彦淖尔,乌兰察布,兴安,锡林郭勒,阿拉善].map(prefecture => topojson.feature(prefecture, prefecture.objects.default))
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
