Data Blogging.
Published
Edited
Aug 24, 2021
Importers
chart = {
const svg = d3.create("svg")
.attr("viewBox", [0, 0, width, height]);
svg.append("g")
.attr("fill", color)
.selectAll("rect")
.data(data)
.join("rect")
.attr("x", x(0))
.attr("y", (d, i) => y(i))
.attr("width", d => x(d.value) - x(0))
.attr("height", y.bandwidth());
svg.append("g")
.attr("fill", "white")
.attr("text-anchor", "end")
.attr("font-family", "sans-serif")
.attr("font-weight", "bolder")
.attr("font-size", 14)
.selectAll("text")
.data(data)
.join("text")
.attr("x", d => x(d.value))
.attr("y", (d, i) => y(i) + y.bandwidth() / 2)
.attr("dy", "0.35em")
.attr("dx", -4)
.text(d => textFormat(d.value))
.call(text => text.filter(d => x(d.value) - x(0) < textOut) // short bars
.attr("dx", +4)
.attr("fill", "black")
.attr("text-anchor", "start"));
svg.append("g")
.call(yAxis);
return svg.node();
}
data = Object.assign(d3.csvParse(await FileAttachment("alphabet.csv").text(), ({letter, frequency}) => ({name: letter, value: +frequency})).sort((a, b) => d3.descending(a.value, b.value)), {format: "%"})
x = d3.scaleLinear()
.domain([0, d3.max(data, d => d.value)])
.range([margin.left, width - margin.right])
y = d3.scaleBand()
.domain(d3.range(data.length))
.rangeRound([margin.top, height - margin.bottom])
.padding(0.08)
yAxis = g => g
.attr("transform", `translate(${margin.left},0)`)
.call(d3.axisLeft(y).tickFormat(i => data[i].name).tickSizeOuter(0))
.call(g => g.selectAll(".domain").remove())
barHeight = 25
height = Math.ceil((data.length + 0.1) * barHeight) + margin.top + margin.bottom
textOut = 20
color = "#ED2F94"
margin = ({top: 0, right: 0, bottom: 0, left: 30})
d3 = require("d3@6")
function textFormat(x) {
return x.toString().replace(/\B(?<!\.\d*)(?=(\d{3})+(?!\d))/g, ",");
}
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.
