chart = {
const svg = d3.create("svg")
.attr("viewBox", [0, 0, width, height])
.style("overflow", "visible");
svg.append("g")
.call(xAxis);
svg.append("g")
.call(yAxis);
const path = svg.append("g")
.attr("fill", "none")
.attr("stroke", "steelblue")
.attr("stroke-width", 1.5)
.attr("stroke-linejoin", "round")
.attr("stroke-linecap", "round")
.selectAll("path")
.data(data.series)
.join("path")
.style("mix-blend-mode", "multiply")
.attr("d", d => line(d.values));
//svg.call(hover, path);
return svg.node();
}
datacsv = FileAttachment("covid_6.csv").csv();
data = {
const data = d3.csvParse(await FileAttachment("covid_6.csv").text(), d3.autoType);
const columns = data.columns.slice(1);
return {
y: "Number of COVID 19 Cases",
series: data.map(d => ({
name: d.name.replace(/, ([\w-]+).*/, " $1"),
values: columns.map(k => +d[k])
})),
dates: columns.map(d3.utcParse("%Y-%m-%d"))
};
}
height = 600
margin = ({top: 20, right: 20, bottom: 30, left: 30})
x = d3.scaleUtc()
.domain(d3.extent(data.dates))
.range([margin.left, width - margin.right])
y = d3.scaleLinear()
.domain([0, d3.max(data.series, d => d3.max(d.values))]).nice()
.range([height - margin.bottom, margin.top])
xAxis = g => g
.attr("transform", `translate(0,${height - margin.bottom})`)
.call(d3.axisBottom(x).ticks(width / 80).tickSizeOuter(0))
yAxis = g => g
.attr("transform", `translate(${margin.left},0)`)
.call(d3.axisLeft(y))
.call(g => g.select(".domain").remove())
.call(g => g.select(".tick:last-of-type text").clone()
.attr("x", 3)
.attr("text-anchor", "start")
.attr("font-weight", "bold")
.text(data.y))
line = d3.line()
.defined(d => !isNaN(d))
.x((d, i) => x(data.dates[i]))
.y(d => y(d))
d3 = require("d3@^6.1")
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.
