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This line chart is constructed from a CSV in the "Multi-Series Format" from Bureau of Labor Statistics Consumer Price Index data. The chart employs conventional margins and a number of D3 features:

• d3.csv - load and parse data
• d3.time.format - parse dates
• d3.time.scale - x-position encoding
• d3.scale.linear - y-position encoding
• d3.hcl - a perceptual color space
• d3.extent, d3.min and d3.max - compute domains
• d3.svg.axis - display axes
• [d3.svg.line](https://github.com/mbostock/d3/wiki/SVG

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d3.legend

d3.legend is a quick hack to add a legend to a d3 chart. Simply add a g and .call(d3.legend). Any elements that have a title set in the "data-legend" attribute will be included when d3.legend is called. Each title will appear only once (even when multiple items define the same data-legend) as the process uses a set based on a existing names, not an array of all items.

Color

By default the color in the legend will try to match the fill attribute or the stroke attribute of the relevant items. Color can be explicitly defined by attribute "data-legend-color"

Order

The order of items in the legend will be sorted using the top of the bounding box for each included item. The order can be explicitly defined by attribute "data-legend-pos"

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See demo http://bl.ocks.org/4241973 for the original

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Changes in this fork:

• index.html : Original file looped through all nodes: point.each(function(d) { d.scanned = d.selected = false; }); This version only touches the nodes scanned by the quadtree (and the previous selection), resulting in faster response
• quadtree.js : Experiment in internalizing the area (x1,x2,y1,y2) of each quadrant within each node-object

See original here

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var stream = require("stream"),
  util = require("util");

function QueueWrite(maxOpen,fn,options) {
  this.maxOpen = maxOpen;
  this.open = 0;
  this.queue = [];
  this.fn = fn;
  stream.Writable.call(this,options);
}

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Pan and Zoom (mousewheel) to explore the randomized data.

This experiment uses d3.js, dpl.js and pyfy.js to simulate geometric brownian motion with brownian bridge between any "known points" (either given values or already-randomized values). Active caching is utilized to ensure that any base random number stays in place until the world is re-randomized (i.e. I keep filling in missing information). This means that when volatility or drift is changed, the path is recalculated using the previously established Gaussian random outcomes.

The blue dots are known monthly closing values for APPL and the gray line is the simulated brownian motion Pan and zoom to look deeper and further. As you move around the cache will grow larger, but pressing "randomize" will reset the world to a new initial vector.

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Testing automatic pause/resume in node-mysql Query.stream() in https://github.com/ZJONSSON/node-mysql/commit/eb4410bbc1e4496cbac66fe56f32225e55f7e463

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var data;

d3.csv("data.csv",function(err,d) {
  data = {};
  d.forEach(function(d) {
    var kyn = d.kyn, aldur = +d.aldur;
    Object.keys(d)
    .filter(function(d) { return d != 'kyn' && d != 'aldur';})
    .forEach(function(e,i) {
      var born = +e-aldur;

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UPDATE: The Vector Tiles are not being served at this time by Openstreetmap. Try later or a different provider (example) Services seem to have resumed

A simple test of extending the L.TileLayer to fetch geoJSON tiles from openstreetmap and render them with d3. This is probably not the most efficient way to do this, as we accept empty image tags (from the standard TileLayer) and use them as containers for the data/requests.