Map challenge
Source data
cartographers_2019 = d3.csv(
"https://raw.githubusercontent.com/dakvid/30DayMapChallenge/master/data/cartographers.csv",
d => ({ country: d.location, ...d, year: 2019 })
)
days_2020 = d3.csv("https://raw.githubusercontent.com/dakvid/30DayMapChallenge2020/main/data/day_matrix_for_heatmap.csv")
Merge cartographers
rename = new Map([
["UK", "United Kingdom"],
["LUK", "United Kingdom"],
["USA", "United States of America"],
["Oslo, Norway", "Norway"],
])
cartographers = [
...cartographers_2019,
...cartographers_2020
].map(d => ({ countryName: rename.get(d.country) || d.country, ...d }))
Plot.plot({
width : 300,
marks: [
Plot.barY(cartographers, Plot.groupX({y: "count"}, {x: "year"})),
Plot.ruleY([0])
]
})
Where are cartographers ?
locatedCartographers = cartographers.filter(({ country }) => country !== "")
countryList = cartographers.map(({ country }) => country)
countryRollup = d3.rollups(cartographers, v => v.length, d => d.countryName, d => d.year)
countryCount = countryRollup
.map(([ country, [count19, count20]]) => ({ country, count19, count20 })) // to handle undefined values
.map(({ country, count19, count20 }) => ({
country,
count2019: getcount(count19),
count2020: getcount(count20),
}))
import {serialize} from "@palewire/saving-csv"
DOM.download(serialize(countryCount), 'countryCount.csv', "Download CSV")
Choropleth(countryCount, {
id: d => d.country, // country name, e.g. Zimbabwe
value: d => d.count2019,
range: d3.interpolateYlGnBu,
domain: countryCountRange,
features: countries,
featureId: d => d.properties.name,
borders: countrymesh,
projection: d3.geoEqualEarth(),
})
chart = Choropleth(countryCount, {
id: d => d.country, // country name, e.g. Zimbabwe
value: d => d.count2020, // health-adjusted life expectancy
range: d3.interpolateYlGnBu,
features: countries,
featureId: d => d.properties.name, // i.e., not ISO 3166-1 numeric
borders: countrymesh,
projection: d3.geoEqualEarth(),
})
import {countries} from "@d3/world-choropleth"
import {countrymesh} from "@d3/world-choropleth"
Cartographers that are coming back
cartographers_2019_handles = cartographers_2019.map(({ handle }) => handle)
serailcartographers = cartographers
.filter(({ year }) => year === 2020)
.map(c => ({
serial : cartographers_2019_handles.includes(c.handle),
isNew : !cartographers_2019_handles.includes(c.handle),
...c }))
d3.rollups(
serailcartographers.filter(({ isNew }) => isNew),
v => v.length, d => d.countryName
)
domain = [true, false]
textDomain = ["Serial cartographer (here in 2019)", "New in 2020"]
colorscale = ['#03045e', '#0077b6']
Imports
import {legend} from "@d3/color-legend"
import {Choropleth} from "@d3/choropleth"
Sources
https://observablehq.com/@d3/world-choropleth
world = FileAttachment("countries-50m.json").json()
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