Canvas Parallel Coordinates - 7637 Rows - Oridinal/Quantitative dimensions

An example of an SVG interaction layer over a canvas rendering layer. This example has 7637 data points from the USDA Nutrition Dataset. Uses requestAnimationFrame to prevent path rendering from locking up the UI. '''NEW''' support for ordinal dimensions!

Interactions done with the brush component

Based on d3.js Parallel Coordinates

Changes:

Map over each dimension. Assign quantitative scales to all dimensions where every value is a number or null. NOTE!: +"" = 0 AND parseFloat("") !== "". When setting the domain of a quantitative scale. Make sure to coerce "" or nulls to an appropriate value. If you use d3.extent w/o coercing the quantitative strings to numbers... it will grab the extent as if they are strings.
Set the domain of the ordinal scales to the unique values for that dimension (see line 133)
After brushing, convert ordinal dimension's values to pixels before checking if it lies with in the brushes extent. (see line 173) Pro tip: Use Mike's trick from axis.js to see if a scale is quantitative or not. d3.scale.linear().ticks = true d3.scale.ordinal().ticks = undefined

<!DOCTYPE html>
<html>
  <head>
    <meta http-equiv="Content-Type" content="text/html;charset=utf-8"/>
    <title>Canvas Parallel Coordinates</title>
    <style type="text/css">

svg {
  font: 10px sans-serif;
}

canvas, svg {
  position: absolute;
  top: 0;
  left: 0;
}

#chart {
  position: relative;
}

.brush .extent {
  fill-opacity: .3;
  stroke: #fff;
  shape-rendering: crispEdges;
}

.axis line, .axis path {
  fill: none;
  stroke: #000;
  shape-rendering: crispEdges;
}

.axis text {
  text-shadow: 0 1px 0 #fff;
}

</style>
  </head>
  <body>
    <div id="chart">
      <canvas id="foreground"></canvas>
      <svg></svg>
    </div>
    <script type="text/javascript" src="https://cdn.jsdelivr.net/npm/d3@2.10.3/d3.v2.js"></script>
    <script type="text/javascript">

// shim layer with setTimeout fallback
window.requestAnimFrame = (function(){
  return window.requestAnimationFrame       ||
         window.webkitRequestAnimationFrame ||
         window.mozRequestAnimationFrame    ||
         window.oRequestAnimationFrame      ||
         window.msRequestAnimationFrame     ||
         function( callback ){
           window.setTimeout(callback, 1000 / 60);
         };
})();

var m = [30, 10, 10, 10],
    w = 960 - m[1] - m[3],
    h = 340 - m[0] - m[2];

var x = d3.scale.ordinal().rangePoints([0, w], 1),
    y = {};

var line = d3.svg.line(),
    axis = d3.svg.axis().orient("left"),
    foreground,
    dimensions,
    brush_count = 0;

var colors = {
  "Dairy and Egg Products": "hsla(28.13278008298755,100%,52.74509803921569%,0.12)",
  "Spices and Herbs": "hsla(214.13793103448276,55.769230769230745%,79.6078431372549%,0.12)",
  "Baby Foods": "hsla(0,0%,33.33333333333333%,0.12)",
  "Fats and Oils": "hsla(29.77777777777777,100%,73.52941176470588%,0.12)",
  "Poultry Products": "hsla(359.6571428571429,69.1699604743083%,49.6078431372549%,0.12)",
  "Soups, Sauces, and Gravies": "hsla(110.11764705882352,57.04697986577182%,70.7843137254902%,0.12)",
  "Vegetables and Vegetable Products": "hsla(120,56.86274509803921%,40%,0.12)",
  "Sausages and Luncheon Meats": "hsla(1.1428571428571388,100%,79.41176470588236%,0.12)",
  "Breakfast Cereals": "hsla(271.3953488372093,39.44954128440367%,57.25490196078431%,0.12)",
  "Fruits and Fruit Juices": "hsla(274.05405405405406,30.57851239669423%,76.27450980392156%,0.12)",
  "Nut and Seed Products": "hsla(10.153846153846157,30.23255813953488%,42.156862745098046%,0.12)",
  "Beverages": "hsla(10,28.915662650602407%,67.45098039215686%,0.12)",
  "Finfish and Shellfish Products": "hsla(318.3333333333333,65.85365853658534%,67.84313725490196%,0.12)",
  "Legumes and Legume Products": "hsla(334.15384615384613,80.24691358024694%,84.11764705882354%,0.12)",
  "Baked Products": "hsla(0,0%,49.80392156862745%,0.12)",
  "Sweets": "hsla(0,0%,78.03921568627452%,0.12)",
  "Cereal Grains and Pasta": "hsla(0,0%,0%,0.12)",
  "Fast Foods": "hsla(60,51.99999999999999%,70.58823529411764%,0.12)",
  "Meals, Entrees, and Sidedishes": "hsla(185.54347826086956,80%,45.09803921568628%,0.12)",
  "Snacks": "hsla(189.29577464788733,57.72357723577235%,75.88235294117646%,0.12)",
  "Ethnic Foods": "hsla(41.87919463087248,75.63451776649744%,61.372549019607845%,0.12)",
  "Restaurant Foods": "hsla(204.56375838926175,70.61611374407583%,41.372549019607845%,0.12)"
};

d3.selectAll("canvas")
    .attr("width", w + m[1] + m[3])
    .attr("height", h + m[0] + m[2])
    .style("padding", m.join("px ") + "px");

foreground = document.getElementById('foreground').getContext('2d');

foreground.strokeStyle = "rgba(0,100,160,0.1)";

var svg = d3.select("svg")
    .attr("width", w + m[1] + m[3])
    .attr("height", h + m[0] + m[2])
  .append("svg:g")
    .attr("transform", "translate(" + m[3] + "," + m[0] + ")");

// Could value belong to a quantitative ordinal scale
var quant_p = function(v){return (parseFloat(v) == v) || (v == "")};

d3.csv("nutrients.csv", function(data) {
  //Reduce the number of unique names... their were > 7K.
  data.forEach(function(d){d["name"] = d["name"].slice(0,1);});

// Extract the list of dimensions.
  dimensions = d3.keys(data[0]).slice(1).concat(d3.keys(data[0]).slice(0,1)); //Put the ordinal dimensions on opposite sides of the chart for easier viewing
  x.domain(dimensions);

// Create a scale for each.
  dimensions.forEach(function(d) {
    var vals = data.map(function(p) {return p[d];}); 
    if (vals.every(quant_p)){ 
      y[d] = d3.scale.linear()
          .domain(d3.extent(vals.map(function(p){return +p})))
          .range([h, 0]);}
    else{           
      y[d] = d3.scale.ordinal()
          .domain(vals.filter(function(v, i) {return vals.indexOf(v) == i;}))
          .rangePoints([h, 0],1);}
  })
  // Render full foreground
  paths(data, foreground, brush_count);

// Add a group element for each dimension.
  var g = svg.selectAll(".dimension")
      .data(dimensions)
    .enter().append("svg:g")
      .attr("class", "dimension")
      .attr("transform", function(d) { return "translate(" + x(d) + ")"; });

// Add an axis and title.
  g.append("svg:g")
      .attr("class", "axis")
      .each(function(d) { d3.select(this).call(axis.scale(y[d])); })
    .append("svg:text")
      .attr("text-anchor", "middle")
      .attr("y", -9)
      .text(String);

// Add and store a brush for each axis.
  g.append("svg:g")
      .attr("class", "brush")
      .each(function(d) { d3.select(this).call(y[d].brush = d3.svg.brush().y(y[d]).on("brush", brush)); })
    .selectAll("rect")
      .attr("x", -12)
      .attr("width", 24);

// Handles a brush event, toggling the display of foreground lines.
  function brush() {
    brush_count++;
    var actives = dimensions.filter(function(p) { return !y[p].brush.empty(); }),
        extents = actives.map(function(p) { return y[p].brush.extent(); });

// Get lines within extents
    var selected = [];
    data.map(function(d) {
      return actives.every(function(p, i) {
        var p_new = (y[p].ticks)?d[p]:y[p](d[p]); //convert to pixel range if ordinal
          return extents[i][0] <= p_new && p_new <= extents[i][1];
      }) ? selected.push(d) : null;
    });

// Render selected lines
    foreground.clearRect(0,0,w+1,h+1);
    paths(selected, foreground, brush_count);
  }

</script>
  </body>
</html>

Modified http://mbostock.github.com/d3/d3.v2.js to a secure url

https://mbostock.github.com/d3/d3.v2.js