The end-to-end solution for building and hosting better data apps, dashboards, and reports.
myLinearScale = d3.scaleLinear().domain([0, 1]).range([0, 100])
myLinearScale1 = d3.scaleLinear([0, 1], [0, 100])
myLinearScale1(0.5)
iris
myValues = iris.map((d) => d.sepalLength)
minValue = d3.min(myValues)
maxValue = d3.max(myValues)
extentValues = d3.extent(myValues)
extentValues1 = d3.extent(iris, (d) => d.sepalLength)
d3.scaleLinear().domain(extentValues).range([0, 1])(5)
d3
.scaleLinear()
.domain(d3.extent(extract("sepalLength", iris)))
.range([0, 1])(5)
extract = (value, data) => {
return data.map((d) => d[value]);
}
myOrdinalScale = d3
.scaleOrdinal()
.domain(["apple", "orange", "banana"])
.range(["red", "orange", "yellow"])
htl.html`<div style='background-color: ${myOrdinalScale(
"banana"
)}'>${"banana"}</div>`
myOrdinalScale("apple")
myDataOrdinalScale = d3
.scaleOrdinal()
.domain(Array.from(new Set(iris.map((d) => d.species))))
.range(["red", "orange", "yellow"])
myDataOrdinalScale("setosa")
iris
Array.from(new Set(iris.map((d) => d.species)))
iris
{
const width = 600;
const height = 400;
const margin = { top: 20, bottom: 20, left: 50, right: 50 };
const svg = d3
.create("svg")
.attr("width", width + margin.left + margin.right)
.attr("height", height + margin.top + margin.bottom)
.style("border", "1px dotted #000");
const g = svg
.append("g")
.attr("transform", `translate(${margin.left}, ${margin.top})`);
// g.append("rect").attr("width", width).attr("height", height);
const x = d3
.scaleLinear()
.domain(d3.extent(iris, (d) => d["sepalLength"]))
.range([0, width]);
const y = d3
.scaleLinear()
.domain(d3.extent(iris, (d) => d["sepalWidth"]))
.range([height, 0]);
const colorScale = d3
.scaleOrdinal()
.domain(Array.from(new Set(iris.map((d) => d.species))))
.range(["red", "orange", "yellow"]);
g.append("g")
.selectAll("circle")
.data(iris)
.join("circle")
.attr("r", 3)
.attr("cx", (d) => x(d.sepalLength))
.attr("cy", (d) => y(d.sepalWidth))
.style("fill", (d) => colorScale(d.species));
return svg.node();
}
{
const width = 600;
const height = 400;
const margin = { top: 20, bottom: 20, left: 50, right: 50 };
const svg = d3
.create("svg")
.attr("width", width + margin.left + margin.right)
.attr("height", height + margin.top + margin.bottom)
.style("border", "1px dotted #000");
const g = svg
.append("g")
.attr("transform", `translate(${margin.left}, ${margin.top})`);
g.append("rect")
.attr("width", width)
.attr("height", height)
.style("fill", "#ccc");
return svg.node();
}
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.