background preloader

RAW

RAW

http://app.raw.densitydesign.org/#%2F

Related:  Outils - logicielsDatavisualisationDATAVIZTools and productsvisualization tools

Creating Animated Bubble Charts in D3 - Jim Vallandingham Update: I moved the code to its own github repo – to make it easier to consume and maintain. Recently, the New York Times featured a bubble chart of the proposed budget for 2013 by Shan Carter . It features some nice, organic, animations, and smooth transitions that add a lot of visual appeal to the graphic. This was all done using D3.js . As FlowingData commenters point out , the use of bubbles may or may not be the best way to display this dataset.

Data visualisation DIY: our top tools What data visualisation tools are out there on the web that are easy to use - and free? Here on the Datablog and Datastore we try to do as much as possible using the internet's powerful free options. That may sound a little disingenuous, in that we obviously have access to the Guardian's amazing Graphics and interactive teams for those pieces where we have a little more time - such as this map of public spending (created using Adobe Illustrator) or this Twitter riots interactive. But for our day-to-day work, we often use tools that anyone can - and create graphics that anyone else can too. So, what do we use?

Parallel Sets Parallel Sets (ParSets) is a visualization application for categorical data, like census and survey data, inventory, and many other kinds of data that can be summed up in a cross-tabulation. ParSets provide a simple, interactive way to explore and analyze such data. Even though the screenshots here show the Mac version, the program also runs on Windows and Linux. Links to the executables are in the Download Section. Basic Operation 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

Demos - JavaScript InfoVis Toolkit JavaScript InfoVis Toolkit Create Interactive Data Visualizations for the Web Home ● Download ● Builder ● Donate Literature and Latte - Scapple for Mac OS X and Windows Rough It Out Scapple doesn’t force you to make connections, and it doesn’t expect you to start out with one central idea off of which everything else is branched. There’s no built-in hierarchy at all, in fact—in Scapple, every note is equal, so you can connect them however you like. The idea behind Scapple is simple: when you are roughing out ideas, you need complete freedom to experiment with how those ideas best fit together. It’s Scapple Simple Creating notes is as easy as double-clicking anywhere on the canvas and then typing; making connections between ideas is as painless as dragging and dropping one note onto another.

DView DView displays hourly time series data in a variety of formats. We developed DView for NREL to help with the visual analysis of all kinds of hourly time series data, with a particular emphasis on "typical meteorological year" data. DView opens text files and Excel files containing any type of hourly data, and it recognizes several particular file formats, including TMY2, TMY3, and EPW files. The 36 best tools for data visualization It's often said that data is the new world currency, and the web is the exchange bureau through which it's traded. As consumers, we're positively swimming in data; it's everywhere from labels on food packaging design to World Health Organisation reports. As a result, for the designer it's becoming increasingly difficult to present data in a way that stands out from the mass of competing data streams.

Customizing Phrase Net Many Eyes Log in Explore Visualizations Data sets Comments Big Ladder Software Welcome! Kiva is a free and open source ground heat transfer calculation tool written in C++. Specifically, Kiva is used to calculate heat loss and gain on a timestep basis from building foundations. Data Visualization Libraries Based on D3.JS - Mike McDearmon There are a lot of ways to visualize data on the Web (with more emerging every day), but the flexibility, versatility, and energized development community surrounding D3.js makes it a great option to explore. The following list of D3 plugins, extensions, and applications below is by no means comprehensive, but oughta be enough to keep you busy for a while. If you’re just getting your feet wet with D3.js, here are some great learning resources to get you acclimated:D3 for mere mortals: Great introductory lessons for those starting from scratch.Try D3 Now: Another great resource for learning about core D3 concepts.Data-Driven Documents (paper): An academic article by Mike Bostock with loads of footnotes.Learning D3, Scott Becker: A quick and effective tutorial series to get yourself up and running.Dashing D3: A very thorough tutorial series covering a LOT more than just D3.Interactive Data Visualization for the Web is a fantastic book by Scott Murray.

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.

Data Visualization 101: Pie Charts In our Data Visualization 101 series, we cover each chart type to help you sharpen your data visualization skills. Pie charts are one of the oldest and most popular ways to visualize data. This classic chart is the perfect example of the power of data visualization: a simple, easy-to-understand presentation that helps readers instantly identify the parts of a whole. Without further ado, here’s everything you need to know about the pie chart. What It Is

Related:  DataJournalisme