Maps, Data, Viz, UX, Design
Published
Edited
Dec 2, 2020
Importers
1 star
Introduction to Data Visualization for the MSM / SHLI FellowshipHealth Equity Tracker Data Visualization PrecedenceCOVID-19 Vulnerability IndexU.S. Hexagon Map SVG with Data JoinedViz Ideas for U.S. Chronic Disease Indicators: DiabetesU.S. Diabetes Prevalence by CountyU.S. Obesity Prevalence by CountyVisualizing Racial/Ethnic Disparities in COVID-19 DeathsHET Vis Prototype: Provisional COVID-19 Death Counts by County and RaceCompare U.S. State DemographicsCompare Chronic Diseases in U.S. StatesCompare Chronic Diseases in U.S. States (V2)Chronic Diseases, U.S. State Small MultiplesACS Race/Ethnicity Characteristics by StatePopulation Age Distribution by Race/Ethnicity ChartU.S. County Population Age DistributionU.S. Census Population Age Distributions by County by Race / EthnicityNY Times COVID-19 Cases by Race/EthnicityU.S. Coronavirus Cumulative Cases Animated MapHello, CARTO-VLCARTO-VL: Update Vis Layer
U.S. County Population Density Choropleth
Also listed in…
maps and geo
colorScale = d3
.scaleThreshold()
.domain([10, 100, 1000, 10000, Math.ceil(d3.max(data, d => d.value))])
.range(d3.schemeRdPu[5])
tooltipContents = ({ id, value }) =>
`${countyFipsToName.get(id)}<br>~<strong>${d3.format(",.2f")(
value
)}</strong> ppl/sqkm`
data = Array.from(countyPopDensityByFips).map(([id, props]) => ({
id,
value: props.pop_density
}))
import { drawChoroplethMap } from "@clhenrick/reusable-choropleth-map"
import { countyPopDensityByFips } from "@clhenrick/us-county-population-density"
import { countyFipsToName } from "@clhenrick/us-census-constants"
import { legend } from "@d3/color-legend"
d3 = require("d3-scale@2", "d3-scale-chromatic@2", "d3-array@2", "d3-format@2")
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.
