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Scatterplot Matrix

The scatterplot matrix visualizations pairwise correlations for multi-dimensional data; each cell in the matrix is a scatterplot. This example uses Anderson's data of iris flowers on the Gaspé Peninsula. Scatterplot matrix design invented by J. A. Hartigan; see also R and GGobi. Data on Iris flowers collected by Edgar Anderson and published by Ronald Fisher.

See also this version with brushing.

<!DOCTYPE html>
<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;
}

</style>
<body>
<script src="//d3js.org/d3.v3.min.js"></script>
<script>

var width = 960,
    size = 230,
    padding = 20;

var x = d3.scale.linear()
    .range([padding / 2, size - padding / 2]);

var y = d3.scale.linear()
    .range([size - padding / 2, padding / 2]);

var xAxis = d3.svg.axis()
    .scale(x)
    .orient("bottom")
    .ticks(6);

var yAxis = d3.svg.axis()
    .scale(y)
    .orient("left")
    .ticks(6);

var color = d3.scale.category10();

d3.csv("flowers.csv", function(error, data) {
  if (error) throw error;

var domainByTrait = {},
      traits = d3.keys(data[0]).filter(function(d) { return d !== "species"; }),
      n = traits.length;

traits.forEach(function(trait) {
    domainByTrait[trait] = d3.extent(data, function(d) { return d[trait]; });
  });

xAxis.tickSize(size * n);
  yAxis.tickSize(-size * n);

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 + ")");

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) { x.domain(domainByTrait[d]); d3.select(this).call(xAxis); });

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) { y.domain(domainByTrait[d]); d3.select(this).call(yAxis); });

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) { return x(d[p.x]); })
        .attr("cy", function(d) { return y(d[p.y]); })
        .attr("r", 4)
        .style("fill", function(d) { return color(d.species); });
  }
});

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>

https://d3js.org/d3.v3.min.js