frontend + d3
Public
Edited
Dec 2, 2023
groupedData = d3.rollup(
schedules,
(v) => d3.sum(v, (d) => d.diff),
(d) => d.content
)
Array.from(groupedData)
config = ({
w: width,
h: 600,
mx: 50,
my: 50
})
DateTime = luxon.DateTime
{
const scaleCategX = d3
.scaleBand()
.domain(Object.keys(groupedData))
.range([0, 300]);
return Array.from(groupedData.keys());
}
chart = {
const svg = d3.create("svg").attr("width", config.w).attr("height", config.h);
const scaleTimeY = d3
.scaleTime()
.domain([essentials.start, essentials.end])
.range([config.my, config.h - config.my * 2]);
const axisY = d3
.axisLeft(scaleTimeY)
.tickFormat(d3.timeFormat("%H:%M"))
.ticks(d3.timeHour);
const gAxisY = svg.append("g");
gAxisY.attr("transform", `translate(${config.mx},0)`);
gAxisY.call(axisY);
gAxisY
.selectAll(".tick > line")
.attr("x1", -config.w + config.mx * 2)
.attr("transform", `translate(${config.w - config.mx * 2})`);
const chartMain = svg
.append("g")
.attr("transform", `translate(${config.mx},0)`);
const scaleColor = d3
.scaleOrdinal(d3.schemeCategory10)
.domain(Array.from(groupedData.keys()));
const chartCateg = svg
.append("g")
.attr("transform", `translate(${config.mx + 45},0)`);
const scaleCategX = d3
.scaleBand()
.domain(Array.from(groupedData.keys()))
.range([0, 150])
.paddingInner(0.5);
const gLegend = svg.append("g");
gLegend.attr("transform", `translate(${config.w - config.mx},${config.my})`);
function render() {
chartMain
.selectAll(".main-chart-item")
.data(schedules, (d) => d.id)
.join((enter) =>
enter
.append("rect")
.attr("class", "main-chart-item")
.attr("rx", 3)
.attr("ry", 3)
.attr("fill", (d) => scaleColor(d.content))
.attr("opacity", 0.5)
.attr("transform", (d) => `translate(0, ${scaleTimeY(d.time)})`)
.attr("width", (d) => 30)
.attr("height", (d) => scaleTimeY(d.nextTime) - scaleTimeY(d.time))
);
chartCateg
.selectAll(".categ-chart-item")
.data(schedules)
.join((enter) =>
enter
.append("rect")
.attr("class", "categ-chart-item")
.attr("rx", 3)
.attr("ry", 3)
.attr("fill", (d) => scaleColor(d.content))
.attr("width", (d) => scaleCategX.bandwidth())
.attr("height", (d) => scaleTimeY(d.nextTime) - scaleTimeY(d.time))
.attr(
"transform",
(d) => `translate(${scaleCategX(d.content)},${scaleTimeY(d.time)})`
)
);
gLegend
.selectAll(".legend-item")
.data(Array.from(groupedData))
.join((enter) =>
enter
.append("g")
.attr("class", "legend-item")
.attr("transform", (d, i) => `translate(-30, ${i * 30})`)
.attr("text-anchor", "end")
.attr("dominant-baseline", "hanging")
.call((l) =>
l
.append("text")
.text(
([k, v]) =>
`${k} - ${luxon.Duration.fromMillis(v).toFormat(
"hh'h'mm'm'"
)}`
)
)
.call((l) =>
l
.append("rect")
.attr("width", "10")
.attr("height", "10")
.attr("fill", ([k, v]) => scaleColor(k))
)
);
}
render();
return Object.assign(svg.node(), { render });
}
chartArc = {
const svg = d3.create("svg").attr("width", config.w).attr("height", config.h);
const scaleTimeRad = d3
.scaleRadial()
.domain([essentials.start, essentials.end])
.range([0, Math.PI * 2]);
const gArc = svg.append("g");
const arcRadii = d3.max([config.w, config.h]) / 2;
gArc.attr("transform", `translate(${config.w / 2},${config.h / 2})`);
const scaleColor = d3
.scaleOrdinal()
.domain(Array.from(groupedData.keys()))
.range(d3.schemeTableau10);
const scaleTypeY = d3
.scaleBand()
.domain(Array.from(groupedData.keys()))
.range([arcRadii / 3, arcRadii / 5]);
function render() {
const arc = d3
.arc()
.startAngle((d) => scaleTimeRad(d.time))
.endAngle((d) => scaleTimeRad(d.nextTime))
.innerRadius(arcRadii / 3)
.outerRadius(arcRadii / 5);
// .innerRadius((d) => scaleTypeY(d.content))
// .outerRadius((d) => scaleTypeY(d.content) + scaleTypeY.bandwidth());
gArc
.selectAll(".arc-item")
.data(schedules, (d) => d.id)
.join((enter) =>
enter.append("g").call((g) =>
g
.append("path")
.attr("d", arc)
.attr("fill", (d) => scaleColor(d.content))
)
);
}
render();
return Object.assign(svg.node(), { render });
}
luxon = require("luxon@3/build/global/luxon.min.js").catch(
() => window["luxon"]
)
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.