I'm a recently retired investment analyst and consultant. I've long been a data nerd, and have pretty good database skills. I am trying to marry these two areas of expertise with data visualization.
md`# State Choropleth - Average Daily % Growth Rate Over the Past Month
Average Daily Covid Case Growth Rate Over The Past Month. Data: [Johns Hopkins University](https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6)`
chart = {
const svg = d3.create("svg")
.attr("viewBox", [0, 0, 975, 610]);
svg.append("g")
.attr("transform", "translate(610,20)")
.append(() => legend({color, title: data.title, width: 260}));
svg.append("g")
.selectAll("path")
.data(topojson.feature(us, us.objects.states).features)
.join("path")
.attr("fill", d => color(data.get(d.properties.name)))
.attr("d", path)
.append("title")
.text(d => `${d.properties.name}
${format(data.get(d.properties.name))}`);
svg.append("path")
.datum(topojson.mesh(us, us.objects.states, (a, b) => a !== b))
.attr("fill", "none")
.attr("stroke", "white")
.attr("stroke-linejoin", "round")
.attr("d", path);
return svg.node();
}
data = Object.assign(new Map(d3.csvParse(await FileAttachment("StateChoroplethCaseLastMonth@98.csv").text(), ({name, rate}) => [name, +rate])), {title: "Covid-19 Case Growth Rate (%)"})
color = d3.scaleSequential()
.domain(d3.extent(Array.from(data.values())))
.interpolator(d3.interpolateReds)
.unknown("#ccc")
path = d3.geoPath()
format = d => `${d}%`
us = FileAttachment("states-albers-10m.json").json()
topojson = require("topojson-client@3")
d3 = require("d3@5")
import {legend} from "@d3/color-legend"
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.
