populationData
Type Table, then Shift-Enter. Ctrl-space for more options.
populationData
keys = ["<10", "10-19", "20-29", "30-39", "40-49", "50-59", "60-69", "70-79", "≥80"]
stackLayout = d3.stack().keys(keys).offset(d3.stackOffsetExpand)(populationData)
{
const width = 900;
const height = 300;
const marginTop = 25;
const marginRight = 20;
const marginBottom = 35;
const marginLeft = 60;
const x = d3
.scaleBand()
.domain(Array.from(new Set(populationData.map((d) => d.name))))
.range([0, width]);
const y = d3
.scaleLinear()
.domain([0, d3.max(stackLayout, (d) => d3.max(d, (d) => d[1]))])
.nice()
.range([height, 0]);
const color = d3
.scaleOrdinal()
.domain(keys)
.range(d3.schemeSpectral[keys.length]);
const svg = d3
.create("svg")
.attr("width", width + marginLeft + marginRight)
.attr("height", height + marginTop + marginBottom);
const g = svg
.append("g")
.attr("transform", `translate(${marginLeft}, ${marginTop})`);
// Append a group for each series, and a rect for each element in the series.
g.append("g")
.selectAll(".bucket")
.data(stackLayout)
.join("g")
.attr("class", "bucket")
.attr("fill", (_, i) => color(keys[i]))
.selectAll("rect")
.data((d) => d)
.join("rect")
.attr("x", (d) => x(d.data.name))
.attr("y", (d) => y(d[1]))
.attr("height", (d) => y(d[0]) - y(d[1]))
.attr("width", x.bandwidth());
g.append("g")
.attr("transform", `translate(0,${height})`)
.call(d3.axisBottom(x));
g.append("g").call(d3.axisLeft(y));
return svg.node();
}
{
const width = 200;
const height = 200;
const margin = { top: 20, bottom: 20, left: 20, right: 20 };
const svg = d3
.create("svg")
.attr("width", width + margin.left + margin.right)
.attr("height", height + margin.top + margin.bottom);
const g = svg
.append("g")
.attr("transform", `translate(${margin.left}, ${margin.top})`);
const rectangle = g
.append("rect")
.attr("width", width)
.attr("height", height)
.style("fill", "#ddd")
.style("stroke", "#000")
.on("mouseenter", (event) => {
rectangle.style("fill", "magenta");
})
.on("mouseleave", (event) => {
rectangle.style("fill", "blue");
})
.on("click", (events) => {
rectangle
.transition()
.duration(2000)
.attr("width", 0)
.attr("height", 0)
.attr("x", width / 2)
.attr("y", height / 2);
});
const circle = g
.append("circle")
.style("pointer-events", "none")
.attr("r", 5);
svg.on("mousemove", (event) => {
console.log(event);
circle.attr("cx", event.layerX - 20);
circle.attr("cy", event.layerY - 20);
});
return svg.node();
}
{
const width = 600;
const height = 400;
const margin = { top: 30, bottom: 20, left: 50, right: 50 };
const div = htl.html`<div></div>`;
const categories = d3.groups(iris, (d) => d.species);
const buttons = d3
.select(div)
.selectAll("button")
.data(categories)
.join("button");
buttons.text((d) => d[0]);
const svg = d3
.select(div)
.append("div")
.append("svg")
.attr("width", width + margin.left + margin.right)
.attr("height", height + margin.top + margin.bottom);
const g = svg
.append("g")
.attr("transform", `translate(${margin.left}, ${margin.top})`);
g.append("rect")
.attr("width", width)
.attr("height", height)
.style("fill", "#eee");
const text = svg
.append("text")
.style("font", "12px sans-serif")
.attr("y", 15)
.text("Click on a circle to read the data!");
const x = d3
.scaleLinear()
.domain(d3.extent(iris, (d) => d["sepalLength"]))
.nice()
.range([0, width]);
const y = d3
.scaleLinear()
.domain(d3.extent(iris, (d) => d["sepalWidth"]))
.nice()
.range([height, 0]);
const color = d3
.scaleOrdinal()
.domain(categories.map((d) => d[0]))
.range(d3.schemeDark2);
const yAxis = g.append("g").call(d3.axisLeft(y).tickSize(-width));
const xAxis = g
.append("g")
.attr("transform", `translate(0, ${height})`)
.call(d3.axisBottom(x).tickSize(-height));
yAxis.selectAll("line").style("stroke", "#fff");
xAxis.selectAll("line").style("stroke", "#fff");
const circles = g
.selectAll("circle")
.data(iris.filter((d) => d.species == "setosa"))
.join("circle")
.attr("r", 4)
.style("stroke", "#000")
.attr("cx", (d) => x(d.sepalLength))
.attr("cy", (d) => y(d.sepalWidth))
.style("fill", (d) => color(d.species))
.style("cursor", "pointer")
.on("click", (event, d) => {
text.text(JSON.stringify(d));
});
buttons.on("click", (event, d) => {
g.selectAll("circle")
.data(d[1], (d) => d)
.join(
(enter) =>
enter
.append("circle")
.attr("r", 4)
.style("stroke", "#000")
.attr("cx", (d) => x(d.sepalLength))
.attr("cy", (d) => y(d.sepalWidth))
.style("fill", (d) => color(d.species))
.style("cursor", "pointer")
.on("click", (event, d) => {
text.text(JSON.stringify(d));
}),
(update) =>
update
.attr("cx", (d) => x(d.sepalLength))
.attr("cy", (d) => y(d.sepalWidth))
.style("fill", (d) => color(d.species)),
(exit) =>
exit
.attr("fill", "red")
.call((exit) =>
exit.transition().duration(1000).attr("r", 0).remove()
)
);
});
return div;
}
iris.csv
Type Table, then Shift-Enter. Ctrl-space for more options.
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.