Published
Edited
Oct 31, 2019
2 stars
html `
<style>
.bar { fill: skyblue; }
.bar-selected { fill: royalblue; }
</style>
`
data = getData(5000)
selectedValue = 58.2
getData = (count) => {
let data = [];
for (let i = 0; i < count; i++) {
let value = parseFloat((Math.random()*100).toFixed(1));
data.push(value);
}
return data;
}
chart = {
const svg = d3.create("svg")
.attr("viewBox", [0, 0, width, height]);
svg.append("g")
.selectAll("rect")
.data(bins)
.join("rect")
.attr("x", d => x(d.x0) + 1)
.attr("width", d => Math.max(0, x(d.x1) - x(d.x0) - 1))
// .attr("fill", d => d.includes(selectedValue) ? "royalblue" : "skyblue")
.attr("class", d => d.includes(selectedValue) ? "bar-selected" : "bar")
.attr("y", d => y(d.length))
.attr("height", d => y(0) - y(d.length));
svg.append("g")
.call(xAxis);
svg.append("g")
.call(yAxis);
return svg.node();
}
bins = d3.histogram()
.domain(x.domain())
.thresholds(x.ticks(binSize))
(data)
x = d3.scaleLinear()
.domain(d3.extent(data)).nice()
.range([margin.left, width - margin.right])
y = d3.scaleLinear()
.domain([0, d3.max(bins, d => d.length)]).nice()
.range([height - margin.bottom, margin.top])
xAxis = g => g
.attr("transform", `translate(0,${height - margin.bottom})`)
.call(d3.axisBottom(x).tickSizeOuter(0))
.call(g => g.append("text")
.attr("x", width - margin.right)
.attr("y", -4)
.attr("fill", "#000")
.attr("font-weight", "bold")
.attr("text-anchor", "end")
.text(data.x))
yAxis = g => g
.attr("transform", `translate(${margin.left},0)`)
.call(d3.axisLeft(y))
.call(g => g.select(".domain").remove())
.call(g => g.select(".tick:last-of-type text").clone()
.attr("x", 4)
.attr("text-anchor", "start")
.attr("font-weight", "bold")
.text(data.y))
binSize = Math.floor(width/barWidth)
barWidth = 20
height = 500
margin = ({top: 20, right: 20, bottom: 30, left: 40})
d3 = require("d3@5")
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.
