MOS 26/01 iris

See code on blockbuilder.org/tblondelle/...

Thomas Blondelle, École Centrale de Lyon, janvier 2018

<!DOCTYPE html>
<head>
  <meta charset="utf-8">
  <script src="https://d3js.org/d3.v4.min.js"></script>
  <style>
    body { margin:0;position:fixed;top:0;right:0;bottom:0;left:0; }
  </style>
</head>

var graph_height = height - margin.top - margin.bottom - 100,
        graph_width = width- margin.left - margin.right;
  
    var svg = d3.select("svg")
      .attr("width", 960)
      .attr("height", 500);

// Set the ranges
    var x = d3.scaleLinear().range([0, graph_width]),
        y = d3.scaleLinear().range([graph_height, 0]),
        color = d3.scaleOrdinal(d3.schemeCategory10),
        symbol = d3.symbol().size(50);

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

// Get Regression Data
      var xSeries = []
      var ySeries = []
      data.forEach(function(d) {
        xSeries.push(+d.petal_length)
        ySeries.push(+d.sepal_length)
      });

var leastSquaresCoeff = leastSquares(xSeries, ySeries);
      var x1 = x(0),
          y1 = leastSquaresCoeff[0] * x1 + leastSquaresCoeff[1],
          x2 = x(d3.max(data, function(d) { return d.sepal_length; })),
          y2 = leastSquaresCoeff[0] * x2 + leastSquaresCoeff[1];
      var trendData = [x1, y1, x2, y2];

// Scale the range of the data
      x.domain([0, d3.max(data, function(d) { return d.petal_length; })]);
      y.domain([0, d3.max(data, function(d) { return d.sepal_length; })]);
      var scales = d3.scaleOrdinal()
        .domain(function(d){return d.species})
        .range([0, 1, 2]);

// Add title
      var title = svg.append("g")
        .attr("class", "title")
        .attr("transform",  "translate(" +  60 + "," +0 + ")");

title.append("text")
        .attr("x", 10)
        .attr("y", 60)
        .text("Longueur de sépale en fonction de la longueur de pétale (en cm)")
        .attr("font-family", "sans-serif")
        .attr("font-size", "20px")

// Add graph.
      var graph = svg.append("g")
        .attr("class", 'graph')
        .attr("transform",  "translate(" + margin.left + "," + +(margin.top + 60) + ")");
      
      graph.selectAll(".dot").data(data).enter()
        .append("path")
        .attr("class", "dot")
        .attr("d", function(d) {  
            return symbol.type(d3.symbols[ scales(d.species) ])(); })
        .attr("transform", function(d,i) {
            return "translate(" + x(d.petal_length) + ", " + y(d.sepal_length) + ")"})
        .attr("fill", function(d){
            return color(d.species)})

// Add the X Axis.
      graph.append("g")
          .attr("transform", "translate(0," + graph_height + ")")
          .call(d3.axisBottom(x));

// Add the Y Axis.
      graph.append("g")
          .call(d3.axisLeft(y));

// Add regression line
      graph.selectAll(".trend").data([trendData]).enter()
        .append("line")
        .attr("class", "trend")
        .attr("x1", function(d) { return x(d[0]) })
        .attr("y1", function(d) { return y(d[1]) })
        .attr("x2", function(d) { return x(d[2]) })
        .attr("y2", function(d) { return y(d[3]) })
        .attr('stroke', "red")
    
    });

//https://bl.ocks.org/benvandyke/8459843
    // returns slope, intercept and r-square of the line
    function leastSquares(xSeries, ySeries) {
      var reduceSumFunc = function(prev, cur) { return prev + cur; };
      
      var xBar = xSeries.reduce(reduceSumFunc) * 1.0 / xSeries.length;
      var yBar = ySeries.reduce(reduceSumFunc) * 1.0 / ySeries.length;

</script>
</body>

https://d3js.org/d3.v4.min.js