xxxxxxxxxx
<meta charset="utf-8">
<style>
svg {
font: 10px sans-serif;
padding: 10px;
}
.axis,
.frame {
shape-rendering: crispEdges;
}
.axis line {
stroke: #ddd;
}
.axis path {
display: none;
}
.cell text {
font-weight: bold;
text-transform: capitalize;
}
.frame {
fill: none;
stroke: #aaa;
}
circle {
fill-opacity: .7;
}
circle.hidden {
fill: #ccc !important;
}
</style>
<body>
<!-- load the d3.js library -->
<script src="https://d3js.org/d3.v4.min.js"></script>
<script>
var width = 960,
size = 230,
padding = 30;
var x = d3.scaleLinear()
.range([padding / 2, size - padding / 2]);
var y = d3.scaleLinear()
.range([size - padding / 2, padding / 2]);
var gxScale = d3.scaleBand()
.range([padding / 2, size - padding / 2]);
var gyScale = d3.scaleBand()
.range([size - padding / 2, padding / 2])
color = d3.scaleOrdinal(d3.schemeCategory20);
d3.csv("billionaires.csv", function(error, data) {
if (error) throw error;
var domainByTrait = {},
traits = d3.keys(data[0]).filter(function(d) { return d == "gender" || d == "age" || d == "worth in billions"; }),
n = traits.length;
console.log(traits);
traits.forEach(function(trait) {
if(trait == "gender"){
domainByTrait[trait] = data.map(function(d) { return d['gender']; })
}else {
domainByTrait[trait] = d3.extent(data, function(d) {
return +d[trait]; });
}
});
var svg = d3.select("body").append("svg")
.attr("width", size * n + padding)
.attr("height", size * n + padding)
.append("g")
.attr("transform", "translate(" + padding + "," + padding / 2 + ")");
// X axes
svg.selectAll(".x.axis")
.data(traits)
.enter().append("g")
.attr("class", "x axis")
.attr("transform", function(d, i) { return "translate(" + ((n - i - 1) * size) + ",0)"; })
.each(function(d) {
if (d == "gender"){
gxScale.domain(domainByTrait[d]);
d3.select(this).call(d3.axisTop(gxScale));
} else {
x.domain(domainByTrait[d]);
d3.select(this).call(d3.axisTop(x).ticks(5));
}
});
// Y axes
svg.selectAll(".y.axis")
.data(traits)
.enter().append("g")
.attr("class", "y axis")
.attr("transform", function(d, i) { return "translate(0," + i * size + ")"; })
.each(function(d) {
if (d == "gender"){
gyScale.domain(domainByTrait[d]);
d3.select(this).call(d3.axisLeft(gyScale));
} else {
y.domain(domainByTrait[d]); d3.select(this).call(d3.axisLeft(y).ticks(5));
}
});
var cell = svg.selectAll(".cell")
.data(cross(traits, traits))
.enter().append("g")
.attr("class", "cell")
.attr("transform", function(d) { return "translate(" + ((n - d.i - 1) * size) + "," + (d.j * size) + ")"; })
.each(plot)
// Titles for the diagonal.
cell.filter(function(d) { return d.i === d.j; }).append("text")
.attr("x", padding)
.attr("y", padding)
.attr("dy", ".71em")
.text(function(d) { return d.x; });
function plot(p) {
var cell = d3.select(this);
x.domain(domainByTrait[p.x]);
y.domain(domainByTrait[p.y]);
cell.append("rect")
.attr("class", "frame")
.attr("x", padding / 2)
.attr("y", padding / 2)
.attr("width", size - padding)
.attr("height", size - padding);
cell.selectAll("circle")
.data(data)
.enter().append("circle")
.attr("cx", function(d) {
console.log(p.x);
if(p.x == "gender"){
console.log("in gen", p.x);
return gxScale(d[p.x]);
}else {
return x(d[p.x]);
}
})
.attr("cy", function(d) {
if(p.y == "gender"){
return gyScale(d[p.y]);
}else {
return y(d[p.y]);
}
})
.attr("r", 2)
.style("fill", function(d) { return color(d.gender); });
}
function cross(a, b) {
var c = [], n = a.length, m = b.length, i, j;
for (i = -1; ++i < n;) for (j = -1; ++j < m;) c.push({x: a[i], i: i, y: b[j], j: j});
return c;
}
});
</script>
<p><a href = "https://bl.ocks.org/mbostock/3213173">Reference</a>
</p>
</body>
https://d3js.org/d3.v4.min.js