Data Visualization and Data Science consultant.
Currently at UFRJ/PPGI Master's program in Computer Science (Data Visualization and Machine Learning).
chart = {
replay;
const svg = d3.select(DOM.svg(width, height));
const l = length(line(data));
svg.append("g")
.call(xAxis);
svg.append("g")
.call(yAxis);
svg.append("path")
.datum(data)
.attr("fill", "none")
.attr("stroke", "black")
.attr("stroke-width", 2.5)
.attr("stroke-linejoin", "round")
.attr("stroke-linecap", "round")
.attr("stroke-dasharray", `0,${l}`)
.attr("d", line)
.transition()
.duration(5000)
.ease(d3.easeLinear)
.attr("stroke-dasharray", `${l},${l}`);
svg.append("g")
.attr("fill", "white")
.attr("stroke", "black")
.attr("stroke-width", 2)
.selectAll("circle")
.data(data)
.enter().append("circle")
.attr("cx", d => x(d.x))
.attr("cy", d => y(d.y))
.attr("r", 3);
const label = svg.append("g")
.attr("font-family", "sans-serif")
.attr("font-size", 10)
.selectAll("g")
.data(data)
.enter().append("g")
.attr("transform", d => `translate(${x(d.x)},${y(d.y)})`)
.attr("opacity", 0);
label.append("text")
.text(d => d.name)
.each(function(d) {
const t = d3.select(this);
switch (d.orient) {
case "top": t.attr("text-anchor", "middle").attr("dy", "-0.7em"); break;
case "right": t.attr("dx", "0.5em").attr("dy", "0.32em").attr("text-anchor", "start"); break;
case "bottom": t.attr("text-anchor", "middle").attr("dy", "1.4em"); break;
case "left": t.attr("dx", "-0.5em").attr("dy", "0.32em").attr("text-anchor", "end"); break;
}
})
.call(halo);
label.transition()
.delay((d, i) => length(line(data.slice(0, i + 1))) / l * (5000 - 125))
.attr("opacity", 1);
return svg.node();
}
height = 720
margin = ({top: 20, right: 30, bottom: 30, left: 40})
x = d3.scaleLinear()
.domain(d3.extent(data, d => d.x)).nice()
.range([margin.left, width - margin.right])
y = d3.scaleLinear()
.domain(d3.extent(data, d => d.y)).nice()
.range([height - margin.bottom, margin.top])
xAxis = g => g
.attr("transform", `translate(0,${height - margin.bottom})`)
.call(d3.axisBottom(x).ticks(width / 80))
.call(g => g.select(".domain").remove())
.call(g => g.selectAll(".tick line").clone()
.attr("y2", -height)
.attr("stroke-opacity", 0.1))
.call(g => g.append("text")
.attr("x", width - 4)
.attr("y", -4)
.attr("font-weight", "bold")
.attr("text-anchor", "end")
.attr("fill", "black")
.text(data.x)
.call(halo))
yAxis = g => g
.attr("transform", `translate(${margin.left},0)`)
.call(d3.axisLeft(y).ticks(null, "$.2f"))
.call(g => g.select(".domain").remove())
.call(g => g.selectAll(".tick line").clone()
.attr("x2", width)
.attr("stroke-opacity", 0.1))
.call(g => g.select(".tick:last-of-type text").clone()
.attr("x", 4)
.attr("text-anchor", "start")
.attr("font-weight", "bold")
.attr("fill", "black")
.text(data.y)
.call(halo))
function halo(text) {
text.select(function() { return this.parentNode.insertBefore(this.cloneNode(true), this); })
.attr("fill", "none")
.attr("stroke", "white")
.attr("stroke-width", 4)
.attr("stroke-linejoin", "round");
}
function length(path) {
return d3.create("svg:path").attr("d", path).node().getTotalLength();
}
line = d3.line()
.curve(d3.curveCatmullRom)
.x(d => x(d.x))
.y(d => y(d.y))
data = {
const data = await d3.csv("https://gist.githubusercontent.com/mbostock/bd35887eafa65347debee780753c43a9/raw/bf812ca674d62101e144dad8003107124bf8d1ea/driving.csv", ({side, year, miles, gas}) => ({orient: side, name: year, x: +miles, y: +gas}));
data.x = "Miles per person per year";
data.y = "Cost per gallon";
return data;
}
d3 = require("d3@5")
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
