D3 Tutorials, Screencasts and a Newsletter | DashingD3js.com. Cubism.js. Time Series Visualization foo7.6 bar−6.2 foo + bar1.4 foo - bar14 Cubism.js is a D3 plugin for visualizing time series. Scalable Cubism fetches time series data incrementally: after the initial display, Cubism reduces server load by polling only the most recent values.
Effective Cubism also scales in terms of perception: small multiples aligned by time facilitate rapid comparison. Area (120px)7.6 Area (30px)7.6 In contrast, horizon charts reduce vertical space without losing resolution. Horizon, 1-band (120px)7.6 Horizon, 2-band (60px)7.6 Horizon, 3-band (40px)7.6 Horizon, 4-band (30px)7.6 By combining position and color, horizon charts improve perception: position is highly effective at discriminating small changes, while color differentiates large changes. Flexible Cubism is data-source agnostic. Want to learn more? Cytoscape.js. This is how easy it is to get started with Cytoscape.js (this code creates the instance you see on the bottom-right: About Cytoscape.js is an open-source graph theory library written in JavaScript. You can use Cytoscape.js for graph analysis and visualisation. Cytoscape.js allows you to easily display and manipulate rich, interactive graphs. Because Cytoscape.js allows the user to interact with the graph and the library allows the client to hook into user events, Cytoscape.js is easily integrated into your webapp, especially since Cytoscape.js supports both desktop browsers, like Chrome, and mobile browsers, like on the iPad.
Cytoscape.js also has graph analysis in mind: The library contains a slew of useful functions in graph theory. Cytoscape.js is an open-source project, and anyone is free to contribute. The library was developed at the Donnelly Centre at the University of Toronto. Cytoscape.js & Cytoscape Funding Funding for Cytoscape.js and Cytoscape is provided by NRNB (U.S. Notation. Speeding Up D3.js: A Checklist | Safari Blog.
A guest post by Peter Le Bek, founder of RethinkUI, an frontend development agency based in Glasgow, UK. He tweets at @_lebek and writes code at github.com/lebek. D3.js is a bit like the C of visualization frameworks. Programmers are often surprised to learn that D3.js doesn’t include high-level charting functions (e.g. plot(), bar(), or line()). Most of the work is left to the programmer, and there are few surprises in the output SVG. It might seem that D3.js code is almost optimized-by-default – it draws what you tell it to draw and nothing else. This isn’t quite true. In my last post I showed you how to build responsive visualizations with D3.js.
Does your code generate many SVG elements? SVG performance varies across browsers and devices, but they all have their limits. Solution: Remove non-essential elements (e.g. group elements) Group elements (<g></g>) are useful when a set of elements need to share some properties. Alternative solution: Use a canvas element instead of SVG. D3.js. D3.js (or just D3 for Data-Driven Documents) is a JavaScript library that uses digital data to drive the creation and control of dynamic and interactive graphical forms which run in web browsers.
It is a tool for data visualization in W3C-compliant computing, making use of the widely implemented Scalable Vector Graphics (SVG), JavaScript, HTML5, and Cascading Style Sheets (CSS3) standards. It is the successor to the earlier Protovis framework.[2] In contrast to many other libraries, D3 allows great control over the final visual result.[3] Its development was noted in 2011,[4] as version 2.0.0 was released in August 2011.[5] Context[edit] The first web browsers appeared in the early 1990s. They were initially capable of displaying static web pages only: the only way for a user to interact with the web was through clicking links and scrolling pages. In 2011, the development of Protovis was stopped to focus on a new project, D3.js. Technical principles[edit] Selections[edit] Transitions[edit] Sankey Diagram. Source: Department of Energy & Climate Change, Tom Counsell.
Sankey diagrams visualize the magnitude of flow between nodes in a network. This intricate diagram shows a possible scenario for UK energy production and consumption in 2050: energy supplies are on the left, and demands are on the right. Intermediate nodes group related forms of production and show how energy is converted and transmitted before it is consumed (or lost!). The thickness of each link encodes the amount of flow from source to target. This example is built with D3’s Sankey plugin. The fully automatic layout is convenient for rapid visualization—positioning nodes manually is tedious! Many thanks to Tom Counsell, whose Sankey library provided inspiration for this example. Tutorials · mbostock/d3 Wiki. Wiki ▸ Tutorials Please feel free to add links to your work!! Tutorials may not be up-to-date with the latest version 4.0 of D3; consider reading them alongside the latest release notes, the 4.0 summary, and the 4.0 changes.
Introductions & Core Concepts Specific Techniques D3 v4 Blogs Books Courses D3.js in Motion (Video Course)Curran Kelleher, Manning Publications, September 2017D3 4.x: Mastering Data Visualization Nick Zhu & Matt Dionis, Packt. Talks and Videos Meetups Research Papers D3: Data-Driven DocumentsMichael Bostock, Vadim Ogievetsky, Jeffrey HeerIEEE Trans.