Multi-Series Line Chart

This line chart is constructed from a TSV file storing the daily average temperatures of New York, San Francisco and Austin over the last year. The chart employs conventional margins and a number of D3 features:

d3.tsv - load and parse data
d3.time.format - parse dates
d3.time.scale - x-position encoding
d3.scale.linear - y-position encoding
d3.scale.category10, a d3.scale.ordinal - color encoding
d3.extent, d3.min and d3.max - compute domains
d3.keys - compute column names
d3.svg.axis - display axes
d3.svg.line - display line shape

forked from mbostock's block: Multi-Series Line Chart

forked from anonymous's block: Multi-Series Line Chart

<!DOCTYPE html>
<meta charset="utf-8">
<style>

.axis--x path {
  display: none;
}

.line {
  fill: none;
  stroke: steelblue;
  stroke-width: 1.5px;
}

</style>
<svg width="960" height="500"></svg>
<script src="//d3js.org/d3.v4.min.js"></script>
<script>

var svg = d3.select("svg"),
    margin = {top: 20, right: 80, bottom: 30, left: 50},
    width = svg.attr("width") - margin.left - margin.right,
    height = svg.attr("height") - margin.top - margin.bottom,
    g = svg.append("g").attr("transform", "translate(" + margin.left + "," + margin.top + ")");

var parseTime = d3.timeParse("%Y%m%d");

var x = d3.scaleTime().range([0, width]),
    y = d3.scaleLinear().range([height, 0]),
    z = d3.scaleOrdinal(d3.schemeCategory10);

var line = d3.line()
    .curve(d3.curveBasis)
    .x(function(d) { return x(d.date); })
    .y(function(d) { return y(d.temperature); });

// manipulate data
d3.tsv("data.tsv", type, function(error, data) {
  if (error) throw error;

// remove the first column, then iterate over the cities  
  var cities = data.columns.slice(1).map(function(id) {
    // the id is the city name.
    return {
      id: id,
      values: data.map(function(d) {
        return {date: d.date, temperature: d[id]};
      })
    };
  });

// the data is going to be, the an array of 3 elements, one for each series, then for each element there is an id = name of the time series, and a data array, with the time, and the temperature data.
  
  // get the domain for the x axis
  x.domain(d3.extent(data, function(d) { return d.date; }));

// domain for the Y axis
  y.domain([
    d3.min(cities, function(c) { return d3.min(c.values, function(d) { return d.temperature; }); }),
    d3.max(cities, function(c) { return d3.max(c.values, function(d) { return d.temperature; }); })
  ]);

// domain for the colors
  z.domain(cities.map(function(c) { return c.id; }));

// append the x axis
  g.append("g")
      .attr("class", "axis axis--x")
      .attr("transform", "translate(0," + height + ")")
      .call(d3.axisBottom(x));

// append the y axis
  g.append("g")
      .attr("class", "axis axis--y")
      .call(d3.axisLeft(y))
    .append("text")
      .attr("transform", "rotate(-90)")
      .attr("y", 6)
      .attr("dy", "0.71em")
      .attr("fill", "#000")
      .text("Temperature, ºF");

// add 3 groups, one for each time series
  var city = g.selectAll(".city")
    .data(cities)
    .enter().append("g")
      .attr("class", "city");

// in each time series, append a path, in the attribute d, assign the temperature values with the function line, and the stroke is the color of the scale
  city.append("path")
      .attr("class", "line")
      .attr("d", function(d) { return line(d.values); })
      .style("stroke", function(d) { return z(d.id); });

city.append("text")
      .datum(function(d) { return {id: d.id, value: d.values[d.values.length - 1]}; })
      .attr("transform", function(d) { return "translate(" + x(d.value.date) + "," + y(d.value.temperature) + ")"; })
      .attr("x", 3)
      .attr("dy", "0.35em")
      .style("font", "10px sans-serif")
      .text(function(d) { return d.id; });
});

function type(d, _, columns) {
  d.date = parseTime(d.date);
  for (var i = 1, n = columns.length, c; i < n; ++i) d[c = columns[i]] = +d[c];
  return d;
}

</script>

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