Maps, Data, Viz, UX, Design
Published
Edited
Mar 4, 2022
Importers
2 stars
// where 80% of counties fall into
d3.rollup(
joined
.filter((d) => d.designation)
.filter((d) => d.ratio_without >= 0.11 && d.ratio_without < 0.333333),
(v) => v.length,
(d) => d.designation
)
// beeswarmChartUrban
// beeswarmChartRural
format = d3.format(".3f")
sortedWith = data
.map((d) => d.ratio_with)
.filter((d) => d !== null && !isNaN(d))
.sort(d3.ascending)
sortedWithout = data
.map((d) => d.ratio_without)
.filter((d) => d !== null && !isNaN(d))
.sort(d3.ascending)
data.length
urban.length + rural.length
urban = joined.filter((d) => d.designation === "urban")
rural = joined.filter((d) => d.designation === "rural")
joined = {
const urbanRuralLookup = new Map(
designationUrbanRural.map(({ geoid, pct_rural_2010 }) => [
geoid,
pct_rural_2010 >= 50 ? "rural" : "urban"
])
);
return data.map((d) => {
const designation = urbanRuralLookup.get(d.fips);
return {
...d,
designation
};
});
}
data
fipsToCounty = new Map(data.map(({ fips, name }) => [fips, name]))
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