D4 is a friendly charting DSL for D3. The goal of D4 is to allow developers to quickly build data-driven charts with little knowledge of the internals of D3.
For the bleeding edge version of d4 download it directly from the github repository. If you prefer a more stable release you can install the latest released tag using a package manager like bower.
$ bower install d4
or
$ npm install d4
Once you have a local copy of d4 simply include it after d3 in your source file.
<!DOCTYPE html>
<html>
<head>
<!-- sensible defaults for styles -->
<link href="d4.css" rel="stylesheet" />
</head>
<body>
...
<script src="d3.js"></script>
<script src="d4.js"></script>
</body>
</html>#####Hello World Here is the most basic example, which uses many of the preset defaults provided by d4.
var data = [
{ x : '2010', y : 5 },
{ x : '2011', y : 15 },
{ x : '2012', y : 20 }
];
var columnChart = d4.charts.column();
d3.select('someDomElement')
.datum(data)
.call(columnChart);#####Getting Fancy d4 allows you to quickly build up sophisticated charts using a declarative and highly contextual API that allows you to mixin or mixout features from your chart.
var data = [
{ x : '2010', y : 5 },
{ x : '2011', y : 15 },
{ x : '2012', y : 20 }
];
// Create a column chart without a yAxis, but with a grid in the background.
var columnChart = d4.charts.column()
.mixout('yAxis')
.mixin({ 'name' : 'grid', 'feature' : d4.features.grid, 'index' : 0 })
d3.select('someDomElement')
.datum(data)
.call(columnChart);#####Additional Examples
There are many more examples of d4 in the examples site inside the source code repository. Simply clone the repo and
open the examples/ folder in your favorite web browser.
You can find a hosted version of the example site here: http://visible.io/
You can find a quickstart presentation on d4 here.
Many charting libraries do a poor job when it comes to separations of concerns. They attempt to be an all-in-one tool, which is at odds with how modern applications are built. Developers do not want a monolith that owns the data transformation, visual aesthetics, and interactivity. This leads to enormous libraries with huge config files, where every minutia about the chart must be decided upon beforehand. This typically means developers must first learn a specialized API in order to control even the most basic aspects of the chart. d4 believes many of these responsibilities would be better delegated to other technologies. If developers were woodworkers then d4 would be a jig, which allows complex cuts to be made in fraction of the time it would normally take.
Many charting libraries make internal decisions on visual aesthetics, which may remove control from the graphic designer, who may or may not understand JavaScript let alone a specialized charting API. Choices on visual design like the colors for data series and font sizes are best made in CSS. d4 exposes convenient hooks in the generated markup to allow visual designer to get precise control over the look and feel without needing deep knowledge of d4.
Data is a stand-alone object, which can be relied upon by many other scripts on the page. Therefore, a charting library should not change the data object. It can make non-permanent transformations.
There is a software design concept called "convention over configuration," which states that software should specify a collection of opinionated defaults for the developer. The goal of this approach is to lessen the number of obvious choices a developer must make before they are able to use the software. Instead, configuration should be saved for instances where the defaults do not apply. d4 extends this concept a bit and suggests that configuration should also be highly contextual to the object the developer needs changed. Instead of making choices in some abstract config file, developers instead use a highly declarative API to make changes directly to the object they want augment.
d4 uses specific terms to describe the components of a chart.
Chart - The data rendered by d3 into a graphical representation.
Feature - A visual component of a chart, which helps convey meaning in the data.
Dimension - A segment of the data described by the chart.
Parser - A parser prepares the data for a chart.
####Base Charts
- Area Chart (Coming Soon)
- Column Chart
- Donut Chart
- Grouped Column Chart
- Grouped Row Chart
- Line Chart
- Row Chart
- Scatter Chart
- Stacked Column Chart
- Stacked Row Chart
- Waterfall Chart (both horizontal and vertical)
- Arc Labels
- Arc Series
- Arrows
- Brush
- Column Labels
- Grid
- Grouped Column Series
- Line Series Labels
- Line Series
- Reference Lines
- Stacked Column Connectors
- Stacked Labels
- Stacked Circle Series
- Stacked Ellipse Series
- Stacked Rect Series
- Trend Line
- Waterfall Column Connectors
- X Axis
- Y Axis
If you make improvements to d4, please share with others.
Fork the project on GitHub.
Make your feature addition or bug fix.
Commit with Git.
Send @heavysixer a pull request.
Where possible d4 follows existing d3 community best-practices. The inspiration of D4's modular and declarative structure came from Mike Bostock's article on writing reusable charts in d3. d4 also follows the general update pattern too. (mostly)