Learn to be a full-stack developer.
Published
Edited
Sep 18, 2020
3 forks
3 stars
d3 = require('d3@6')
function createData(size) {
let data = [];
for (let i = 0; i < size; ++i) {
data.push({
x: Math.random() * 1000,
y: Math.random() * 1000,
size: Math.floor(Math.random() * 200 + 1)
});
}
return data;
}
data = createData(100)
minData = ({ x: d3.min(data, d => d.x), y: d3.min(data, d => d.y), size: d3.min(data, d => d.size) })
maxData = ({ x: d3.max(data, d => d.x), y: d3.max(data, d => d.y), size: d3.max(data, d => d.size) })
medianData = ({ x: d3.median(data, d => d.x), y: d3.median(data, d => d.y), size: d3.median(data, d => d.size) })
extentX = d3.extent(data, d => d.x)
extentY = d3.extent(data, d => d.y)
extentSize = d3.extent(data, d => d.size)
margin = ({ left: 30, top: 30, right: 30, bottom: 30 })
width = 900
height = 480
gHeight = height - margin.top - margin.bottom
gWidth = width - margin.left - margin.right
x = d3.scaleLinear()
.domain(extentX)
.range([0, gWidth])
cx = d3.scaleLinear()
.domain(extentX)
.range([margin.left, gWidth + margin.left])
[ x(minData.x), x(maxData.x), x(medianData.x) ]
y = d3.scaleLinear()
.domain(extentY)
.range([0, gHeight])
[ y(minData.y), y(maxData.y), y(medianData.y) ]
cy = d3.scaleLinear()
.domain(extentY)
.range([margin.top, gHeight + margin.top])
[ cy(minData.y), cy(maxData.y), cy(medianData.y) ]
size = d3.scaleLinear()
.domain(extentSize)
.range([1, gWidth / 20])
xAxis = d3.axisTop(x)
yAxis = d3.axisLeft(y)
md `## Draw`
function setupCanvas() {
// 1. Clear last painted
d3.select('.canvas').selectAll('svg').remove();
// 2. Create svg
const svg = d3.select('.canvas').append('svg')
.attr('width', width)
.attr('height', height)
.append('g')
.attr('transform', `translate(${margin.left}, ${margin.top})`);
// 3. Define clip-path to clip graph out of the bounds
svg.append('defs')
.append('svg:clipPath')
.attr('id', 'clip')
.append('svg:rect')
.attr('width', gWidth)
.attr('height', gHeight)
.attr('x', 0)
.attr('y', 0);
// 4. Append x axis
svg.append('g')
.attr('id', 'axis_x')
.call(xAxis);
// 5. Append y axis
svg.append('g')
.attr('id', 'axis_y')
.attr('transform', `translate(0,0)`)
.call(yAxis);
return svg;
}
svg = setupCanvas()
function setupScatter() {
// 6. Create scatter section to place circles
const scatter = svg.append('g')
.attr('id', 'scatterplot')
.attr('clip-path', 'url(#clip)')
.on('dblclick', onDblClicked);
// 7. Add circles
scatter.selectAll('.dot')
.data(data)
.join('circle')
.attr('class', 'dot')
.attr('r', d => size(d.size))
.attr('cx', d => cx(d.x))
.attr('cy', d => cy(d.y))
.attr('opacity', 0.5)
.style('fill', '#d989d6');
return scatter;
}
scatter = setupScatter()
function setupBrush() {
const brush = d3.brush()
.extent([[0,0],[gWidth, gHeight]])
.on('end', onBrushEnd);
return brush;
}
brush = setupBrush()
scatter.append('g')
.attr('class', 'brush')
.call(brush)
function onBrushEnd(ev) {
const s = ev.selection;
if (!!s) {
x.domain([s[0][0], s[1][0]].map(x.invert, x));
y.domain([s[0][1], s[1][1]].map(y.invert, y));
cx.domain([s[0][0], s[1][0]].map(cx.invert, cx));
cy.domain([s[0][1], s[1][1]].map(cy.invert, cy));
scatter.selectAll('.brush').call(ev.target.clear);
zoom();
}
}
function zoom() {
scatter.transition().duration(750);
svg.select('#axis_x').transition().call(xAxis);
svg.select('#axis_y').transition().call(yAxis);
scatter.selectAll('circle')
.transition()
.attr('cx', d => cx(d.x))
.attr('cy', d => cy(d.y))
.attr('r', d => size(d.size));
}
function onDblClicked() {
x.domain(extentX);
y.domain(extentY);
cx.domain(extentX);
cy.domain(extentY);
svg.select('#axis_x').transition().call(xAxis);
svg.select('#axis_y').transition().call(yAxis);
// avoid circular definition
d3.select('#scatterplot')
.selectAll('circle')
.transition()
.attr('cx', d => cx(d.x))
.attr('cy', d => cy(d.y))
.attr('r', d => size(d.size));
}
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.