Published
Edited
Oct 19, 2021
chart = HighlightingHistogram(unemployment, {
value: d => d.rate,
label: "Unemployment rate (%) →",
width,
height: 500,
color: "steelblue"
});
function HighlightingHistogram(data, options) {
const chart = Histogram(data, options);
d3.select(chart).selectAll('.binRect')
.on('mouseover', (event,d) => {
d3.select(event.currentTarget)
.attr('fill', 'green');
})
.on('mouseout', (event,d) => {
d3.select(event.currentTarget)
.attr('fill', 'steelblue');
});
return chart;
}
unemployment = FileAttachment("unemployment-x.csv").csv({typed: true})
// Copyright 2021 Observable, Inc.
// Released under the ISC license.
// https://observablehq.com/@d3/histogram
function Histogram(data, {
value = d => d, // convenience alias for x
domain, // convenience alias for xDomain
label, // convenience alias for xLabel
format, // convenience alias for xFormat
x = value, // given d in data, returns the (quantitative) x-value
y = () => 1, // given d in data, returns the (quantitative) weight
thresholds = 40, // approximate number of bins to generate, or threshold function
marginTop = 20, // top margin, in pixels
marginRight = 30, // right margin, in pixels
marginBottom = 30, // bottom margin, in pixels
marginLeft = 40, // left margin, in pixels
width = 640, // outer width of chart, in pixels
height = 400, // outer height of chart, in pixels
insetLeft = 0.5, // inset left edge of bar
insetRight = 0.5, // inset right edge of bar
xType = d3.scaleLinear, // type of x-scale
xDomain = domain, // [xmin, xmax]
xRange = [marginLeft, width - marginRight], // [left, right]
xLabel = label, // a label for the x-axis
xFormat = format, // a format specifier string for the x-axis
yType = d3.scaleLinear, // type of y-scale
yDomain, // [ymin, ymax]
yRange = [height - marginBottom, marginTop], // [bottom, top]
yLabel = "↑ Frequency", // a label for the y-axis
yFormat, // a format specifier string for the y-axis
color = "currentColor" // bar fill color
} = {}) {
// Compute values.
const X = d3.map(data, x);
const Y = d3.map(data, y);
const I = d3.range(X.length);
// Compute bins.
const bins = d3.bin().thresholds(thresholds).value(i => X[i])(I);
// Compute default domains.
if (xDomain === undefined) xDomain = [bins[0].x0, bins[bins.length - 1].x1];
if (yDomain === undefined) yDomain = [0, d3.max(bins, I => d3.sum(I, i => Y[i]))];
// Construct scales and axes.
const xScale = xType(xDomain, xRange);
const yScale = yType(yDomain, yRange);
const xAxis = d3.axisBottom(xScale).ticks(width / 80, xFormat).tickSizeOuter(0);
const yAxis = d3.axisLeft(yScale).ticks(height / 40, yFormat);
yFormat = yScale.tickFormat(100, yFormat);
const svg = d3.create("svg")
.attr("width", width)
.attr("height", height)
.attr("viewBox", [0, 0, width, height])
.attr("style", "max-width: 100%; height: auto; height: intrinsic;");
svg.append("g")
.attr("transform", `translate(${marginLeft},0)`)
.call(yAxis)
.call(g => g.select(".domain").remove())
.call(g => g.selectAll(".tick line").clone()
.attr("x2", width - marginLeft - marginRight)
.attr("stroke-opacity", 0.1))
.call(g => g.append("text")
.attr("x", -marginLeft)
.attr("y", 10)
.attr("fill", "currentColor")
.attr("text-anchor", "start")
.text(yLabel));
svg.append("g")
.attr("class", "bins")
.attr("fill", color)
.selectAll("rect")
.data(bins)
.join("rect")
.attr("class", "binRect")
.attr("x", d => xScale(d.x0) + insetLeft)
.attr("width", d => Math.max(0, xScale(d.x1) - xScale(d.x0) - insetLeft - insetLeft))
.attr("y", d => yScale(d3.sum(d, i => Y[i])))
.attr("height", d => yScale(0) - yScale(d3.sum(d, i => Y[i])))
.append("title")
.text((d, i) => [`${d.x0} ≤ x < ${d.x1}`, yFormat(d3.sum(d, i => Y[i]))].join("\n"));
svg.append("g")
.attr("transform", `translate(0,${height - marginBottom})`)
.call(xAxis)
.call(g => g.append("text")
.attr("x", width - marginRight)
.attr("y", 27)
.attr("fill", "currentColor")
.attr("text-anchor", "end")
.text(xLabel));
return svg.node();
}
import {howto, altplot} from "@d3/example-components"
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.
