Hi. I'm Nicolas Lambert, research engineer in geographic information science at CNRS (France). My job is to draw maps and teach cartography at the university. I am a geographer 🌎, and not really a developer 🖥️
Bertin.js: dorling cartogram
The Dorling cartogram (Dorling, 1996https://www.dannydorling.org/wp-content/files/dannydorling_publication_id1448.pdf), named after the geographer Danny Dorling, is a method of representing absolute quantitative data with proportional circles, while avoiding the superimposition of these. A Dorling cartogram does not preserve the shape, topology or centroids of the objects and is an abstract representation of the spatial configuration of the mapped phenomena. Often, this representation will be used without a background map on top. For this reason, this method can be classified in the family of cartograms.
In bertin.js, we can make Dorling cartograms by using the bubble type and setting the dorling parameter to true.
For this first map, we represent the population of the countries of the World in 2018 (data from the Maddison databasehttps://www.rug.nl/ggdc/historicaldevelopment/maddison/?lang=en). By hiding the basemap, a representation appears which allows to visualize a global shape of the world deformed according to the population.
data = bertin.merge(countries, "ISO3_CODE", maddison, "countrycode")
viewof hide = Inputs.toggle({ label: "Hide background", value: false })
viewof k = Inputs.range([10, 100], { label: "radius max", step: 1, value: 70 })
bertin.draw({
params: {
projection: d3.geoBertin1953()
},
layers: [
{
type: "bubble",
geojson: data,
values: "pop",
k: k,
dorling: true,
iteration: 100,
fill: "#E95B40",
tooltip: ["$country", "$pop", "(inh.)"],
leg_x: 720,
leg_y: 420,
leg_divisor: 1000,
leg_title: "World Population\nin 2018 (million inh.)",
leg_fill: "#E95B40",
leg_round: 0
},
{
type: "layer",
geojson: countries,
fill: "white",
fillOpacity: hide ? 0.01 : 0.3,
stroke: "none"
},
{ type: "graticule" },
{ type: "outline", fillOpacity: hide ? 0.01 : 1 }
]
})
For this second map, we represent cities with a population of more than one million. Here, Dorling's method does not produce an anamorphosis. The method allows us to move the circles away from each other in order to solve the problem of symbol overlap in areas where information is very dense.
dots = bertin.table2geo(cities, "lat", "lng")
bertin.draw({
params: { projection: d3.geoBertin1953() },
layers: [
{ type: "header", text: "Cities with more than one million inhabitants" },
{
type: "bubble",
geojson: dots,
values: "population",
k: 10,
dorling: true,
fill: "#5c7db8",
leg_x: 680,
leg_y: 410,
leg_fontSize2: 7,
leg_title: `Number of inhabitants
in the world's largest cities`,
tooltip: ["$city", "$population", "inh."],
leg_round: -2
},
{
type: "layer",
geojson: countries,
fill: "white",
fillOpacity: 0.3,
stroke: "none"
},
{ type: "graticule" },
{ type: "outline" }
]
})
Appendix
maddison = d3
.csv(
"https://raw.githubusercontent.com/neocarto/resources/master/datasets/maddison/output/maddison.csv"
)
.then((d) => d.filter((d) => d.year == "2018"))
countries = d3.json(
"https://gisco-services.ec.europa.eu/distribution/v2/countries/geojson/CNTR_RG_60M_2020_4326.geojson"
)
bertin = require("bertin@latest")
Type JavaScript, then Shift-Enter. Ctrl-space for more options. Arrow ↑/↓ to switch modes.
d3 = require("d3@7", "d3-geo-projection@4")
cities = d3
.csv(
"https://raw.githubusercontent.com/neocarto/resources/master/datasets/simplemaps_worldcities_basicv1.73/worldcities.csv"
)
.then((r) => r.filter((d) => +d.population > 1000000))
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