Unlike choropleth maps, cartograms encode data using area rather than color, resulting in distorted geographic boundaries. In this example, states are rescaled around their centroid, preserving local shape but not topology. Inspired by Zachary Johnson. Non-continguous cartogram design invented by Judy Olsen. U.S. state and county boundaries from the U.S. Census Bureau, simplified using GDAL and MapShaper.
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February 13, 2020 18:29
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Non-Contiguous Cartogram
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license: gpl-3.0 | |
redirect: https://observablehq.com/@d3/non-contiguous-cartogram |
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<!DOCTYPE html> | |
<meta charset="utf-8"> | |
<title>Non-Contiguous Cartogram</title> | |
<style> | |
.land { | |
fill: #fff; | |
stroke: #ccc; | |
} | |
.state { | |
fill: #ccc; | |
stroke: #666; | |
} | |
</style> | |
<body> | |
<script src="//d3js.org/d3.v3.min.js"></script> | |
<script src="//d3js.org/topojson.v1.min.js"></script> | |
<script> | |
// Ratio of Obese (BMI >= 30) in U.S. Adults, CDC 2008 | |
var valueById = [ | |
NaN, .187, .198, NaN, .133, .175, .151, NaN, .100, .125, | |
.171, NaN, .172, .133, NaN, .108, .142, .167, .201, .175, | |
.159, .169, .177, .141, .163, .117, .182, .153, .195, .189, | |
.134, .163, .133, .151, .145, .130, .139, .169, .164, .175, | |
.135, .152, .169, NaN, .132, .167, .139, .184, .159, .140, | |
.146, .157, NaN, .139, .183, .160, .143 | |
]; | |
var path = d3.geo.path(); | |
var svg = d3.select("body").append("svg") | |
.attr("width", 960) | |
.attr("height", 500); | |
d3.json("/mbostock/raw/4090846/us.json", function(error, us) { | |
if (error) throw error; | |
svg.append("path") | |
.datum(topojson.feature(us, us.objects.land)) | |
.attr("class", "land") | |
.attr("d", path); | |
svg.selectAll(".state") | |
.data(topojson.feature(us, us.objects.states).features) | |
.enter().append("path") | |
.attr("class", "state") | |
.attr("d", path) | |
.attr("transform", function(d) { | |
var centroid = path.centroid(d), | |
x = centroid[0], | |
y = centroid[1]; | |
return "translate(" + x + "," + y + ")" | |
+ "scale(" + Math.sqrt(valueById[d.id] * 5 || 0) + ")" | |
+ "translate(" + -x + "," + -y + ")"; | |
}) | |
.style("stroke-width", function(d) { | |
return 1 / Math.sqrt(valueById[d.id] * 5 || 1); | |
}); | |
}); | |
</script> |
Yes, the ability to zoom states forward on the z axis would be remarkable, and you could tie this to dimensions such as populations, incarcerated population, metrics for total lobby dollars received are available through the opensecrets.org api. I would be glad to assist.
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Looking at this, it occurred to me that it might be interesting to scale each state by its population in addition to centering on the centroid.