Published
Edited
May 16, 2022
md`# D3.js TimeLine`
//require('d3-scale-chromatic');
d3tip = require('d3-tip');
//vegalite = require("@observablehq/vega-lite@0.1");
d3 = require('d3@5');
_ = require('lodash');
data = {
const text = await FileAttachment("appear_dct_CustNo_35.csv").text();
const parseDate = d3.utcParse("%Y-%m-%d");
return d3.csvParse(text, ({custNo, date, type, count}) => ({
custNo: +custNo,
date: parseDate(date),
dateStr: date,
type: type,
count: +count
}));
};
typetoName = ({
"104": "104 人力銀行",
"1111": "1111 人力銀行",
"yes123": "Yes123 人力銀行",
"518": "518 熊班"
});
filterData = data.filter(d => Object.keys(typetoName).includes(d.type) && d.count > 0).sort((a, b) => a.date - b.date);
filterDataGroupbyDate = _.groupBy(filterData, 'date');
json2array = function json2array(json){
var result = [];
var keys = Object.keys(json);
keys.forEach(function(key){
result.push(json[key]);
});
return result;
};
dateStats = json2array(filterDataGroupbyDate).map(d => d.length);
eventTypes = d3.nest()
.key(d => typetoName[d.type])
.rollup(event => ({
success: d3.sum(event, e => e.count),
scale: d3.scaleSqrt()
.domain([0, d3.max(event, e => e.count)])
.range([0, rowHeight / 2]),
count: event.length
}))
.object(filterData);
eventTypeEntries = d3.entries(eventTypes);
x = d3.scaleTime()
.domain(d3.extent(filterData.map(d=>d.date)))
.range([120, innerWidth - 200]);
rightBarX = d3.scaleLinear()
.domain([0, d3.max(eventTypeEntries, d => d.value.success)])
.range([x.range()[1] + 16, innerWidth]);
//the right half width
[0, dateStats.length]
dateStats.map((d, i) => i);
d3.max(dateStats.map((d, i) => d));
topBarX = d3.scaleLinear()
.domain([0, dateStats.length])
.range([120, innerWidth - 200]);
numTypes = d3.keys(eventTypes).length
y = d3.scaleOrdinal()
.domain(eventTypeEntries.sort((a, b) => {
return b.value.success - a.value.success
}).map(t => t.key))
.range(d3.range(numTypes).map(d => (d * (rowHeight + rowPadding)) + rowHeight));
topBarY = d3.scaleLinear()
.domain([0, d3.max(dateStats.map((d , i) => d))])
.range([0, margin.top]);
// exp = d3.scaleSqrt()
// .domain([0, 1])
// .range([0, rowHeight / 2]);
// pow = d3.scalePow()
// .exponent(10)
// .domain([0, d3.max(filterData, d => d.count)])
// .range([0, 1])
// r = function(d) {
// return exp(pow(d));
// }
multiFormat = {
var formatMillisecond = d3.timeFormat(".%L"),
formatSecond = d3.timeFormat(":%S"),
formatMinute = d3.utcFormat("%H:%M:%S"),
formatHour = d3.timeFormat("%I %p"),
formatDay = d3.timeFormat("%a %d"),
formatWeek = d3.timeFormat("%b %d"),
formatMonth = d3.timeFormat("%b"),
formatYear = d3.timeFormat("%Y"),
formatYm = d3.timeFormat("%Y-%m"),
formatYmd = d3.timeFormat("%Y-%m");
function multiFormat(date) {
// return (d3.timeSecond(date) < date ? formatMillisecond
// : d3.timeMinute(date) < date ? formatSecond
// : d3.timeHour(date) < date ? formatMinute
// : d3.timeDay(date) < date ? formatHour
// : d3.timeMonth(date) < date ? (d3.timeWeek(date) < date ? formatDay : formatWeek)
// : d3.timeYear(date) < date ? formatMonth
// : formatYear)(date);
return formatYm(date);
}
return multiFormat;
}
xAxis = g => g.attr("transform", `translate(0, ${numTypes * (rowHeight + rowPadding) + rowHeight})`)
.call(d3.axisBottom(x).ticks(innerWidth / 100).tickFormat(multiFormat))
.call(g => g.select(".domain").remove())
colorOfType = ({
"104 人力銀行": "#FF9100",
"1111 人力銀行": "#009CD8",
"Yes123 人力銀行": "#E40177",
"518 熊班": "#FA1E50"
})
viewof rowHeight = html`
<input type=range value=16 min=12 max=64 />
`
D3 畫圖
{
const svg = d3.select(DOM.svg(innerWidth + margin.left + margin.right, (numTypes * (rowHeight + rowPadding)) + margin.top + margin.bottom+50));
let chart = svg.append("g").attr("transform", `translate(${margin.left}, ${margin.top})`);
const tooltipCircle = d3tip()
.attr('class', 'd3-tip')
.html(d =>`<div style='float: right'>
類型: ${typetoName[d.type]} <br/>
時間: ${d.dateStr} <br/>
</div>`);
svg.call(tooltipCircle);
const tooltipTopbar = d3tip()
.attr('class', 'd3-tip')
.html(d =>`<div style='float: right'>
同時刊登家數: ${d} <br/>
</div>`);
svg.call(tooltipTopbar);
const tooltipRightbar = d3tip()
.attr('class', 'd3-tip')
.html(d =>`<div style='float: right'>
類型: ${d.key} <br/>
累計刊登: ${d.value.count} <br/>
</div>`);
svg.call(tooltipRightbar);
let topBars = chart.append("g")
.selectAll("rect")
.data(dateStats)
.enter().append("rect")
.attr("x", (d,i) => topBarX(i))
.attr("y", d => -topBarY(d))
.attr("height", d => topBarY(d))
.attr("width", d => topBarX(d + 1) - topBarX(d))
.attr("fill", "#53A851")
.attr("opacity", 0.5)
.on('mouseover', tooltipTopbar.show)
.on('mouseout', tooltipTopbar.hide);
chart.append("g")
.call(xAxis);
let typeRows = chart.append("g")
.selectAll("g")
.data(eventTypeEntries)
.enter().append("g");
typeRows.append("text")
.text(d => `${d.key}`)
.attr("class", "label")
.style("font-size", "13px")
.attr("x", -margin.left)
.attr("y", d => y(d.key) + textOffset);
typeRows.append("line")
.attr("x1", x.range()[0])
.attr("x2", x.range()[1])
.attr("stroke", "rgba(0,0,0,0.05)")
.attr("y1", d => y(d.key))
.attr("y2", d => y(d.key));
typeRows.append("rect")
.attr("x", rightBarX.range()[0])
.attr("y", d => y(d.key) - rowHeight / 2)
.attr("height", rowHeight)
.attr("width", d => rightBarX(d.value.success) - rightBarX.range()[0])
.attr("fill", d => colorOfType[d.key])
.attr("opacity", 0.5)
.on('mouseover', tooltipRightbar.show)
.on('mouseout', tooltipRightbar.hide);
typeRows.append("text")
.text(d => d.value.success)
.attr("class", "label")
.style("font-size", "13px")
.attr("text-anchor", "end")
.attr("x", rightBarX.range()[1] - 4)
.attr("y", d => y(d.key) + textOffset);
chart.append("g")
.selectAll("circle")
.data(filterData)
.enter().append("circle")
.attr("cx", d => x(d.date))
.attr("cy", d => y(typetoName[d.type]))
.attr("r", d => eventTypes[typetoName[d.type]].scale(d.count)/2)
.attr("fill", d=>colorOfType[typetoName[d.type]])
.attr("opacity", 0.25)
.on('mouseover', tooltipCircle.show)
.on('mouseout', tooltipCircle.hide);
return svg.node();
}
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.