Published
Edited
Jun 14, 2020
3 stars
x = d3.scaleBand()
.domain(data.map(d => d.x))
.range([0, width - margin.right])
.padding(0.1);
xAxis = g => g
.attr("transform", `translate(0,${height - margin.bottom})`)
.call(d3.axisBottom(x).tickSizeOuter(0));
y = d3.scaleLinear()
.domain([0, d3.max(data, d => d.y)]).nice()
.range([height - margin.bottom, margin.top]);
yAxis = g => g
.attr("transform", `translate(${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")
.style("font-weight", 800)
.text(data.yAxisLabel));
lineGenerator = d3.line()
.x(d => x(d.x))
.y(d => y(d.y))
.curve(d3.curveMonotoneX);
height = 450;
typographyStyles = html`<style>
@import url('https://fonts.googleapis.com/css2?family=Noto+Sans:wght@400;700&display=swap');
text, table {
fill: #282541;
font: 400 16px/1.4 "Noto Sans", sans-serif;
}
.heading,
.paragraph {
fill: #282541;
font: 400 16px/1.4 "Noto Sans", sans-serif;
}
.heading {
font: 700 24px/1.4 "Noto Sans", sans-serif;
}
`
barChartStyles = html`<style>
.domain {
stroke: #cdcccf;
}
.tick line {
stroke: #cdcccf;
}
</style>
`
dataTableStyles = html`<style>
caption {
white-space: initial;
text-align: left;
padding: 8px 0;
max-width: 35em;
}
table {
border-collapse: collapse;
}
th {
background: #F6F6F6;
}
th, td {
border: 1px solid #ECECEF;
text-align: left;
padding: 8px;
}
td:first-of-type {
font-weight: 800;
}
.table-container {
overflow-x: auto;
white-space: nowrap;
width: ${width}px;
min-width: ${width}px;
}
</style>
`
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.
