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D3.js - Data-Driven Documents 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.

6 Great Interactive Data Visualization Tools (Part 2) | MSDS Welcome back for the second part of my series on interactive data visualization (dataviz) tools. In Part 1, we covered three cool tools for visualizing charts and graphs and many other data types on a webpage. In part two, we take a look at three more tools that are a bit more complex but have some incredible data visualization capabilities. 4. Simile Exhibit Exhibit is a very robust and customizable offering. Visualization Types Supported: Line Graphs, Maps, Scatter Plots, Multi-Filterable Lists, Timelines, Timeplots and more…with widgets! Flexible & Powerful Approach to Design I really like the approach of Exhibit, where data is presented through a “lens” – an HTML template shell that elements are placed into. Strong Filtering/Sorting/Search Letting users filter your data by any number of criteria is incredibly useful, and turns your information from static content into a real interactive feature. Widgets! 5. 6. Wow, D3.js is cool! D3 isn’t really like the others. Conclusion

ignacioola/insights Demos - JavaScript InfoVis Toolkit JavaScript InfoVis Toolkit Create Interactive Data Visualizations for the Web Home ● Download ● Builder ● Donate Area, Bar and Pie Charts Sunburst Icicle ForceDirected TreeMap SpaceTree RGraph HyperTree Advanced/Other copyright © 2013 SenchaLabs - Author: Nicolas Garcia Belmonte filter.js – Client side search filtering using JSON and jQuery Speed for search result filtering is critical. Its fine for site users to wait for some time (maybe a few seconds) to load the search results but after that filtering better be fast otherwise people lose interest. To give a simple example of how things are not user friendly is if you go to or Its frankly appalling! For every click and every selection, the entire page refreshes. Though its good for showing Ad impressions (which I hate) when browsing an e-commerce site, the usability is lost. On the other hand, have a look at or and it tells a different story. We did client-side search filtering in a couple of portals we built and realized that we should generalize this. Some key features are: Category and sub-category based filteringSlider based filteringTrigger on any HTML element.Date filtering (in process) To use filter.js is simple. There are dependencies on how to render HTML components. Defining the search criteria and the JSON objects Update1

6 Great Interactive Data Visualization Tools (Part 1) | MSDS Websites are loaded with eye candy these days — from slick user interfaces to interactive maps to cool photo slideshows — all achieved without Flash, just HTML, CSS and Javascript. And these technologies are free, open and can be utilized in essentially every current web-browsing device. While it’s tempting to just jump in and add the latest cool feature to your site, you have to first make sure it’s a good fit for your users and your brand. In this 2-part series, I’m going to focus on the rapidly changing world of interactive tools for data visualization, or dataviz. These tools are especially useful for nonprofits and financial organizations whose brands rely on sharing metrics to deliver impact and value. Recently, many exciting HTML/CSS/Javascript-based data visualization tools have emerged. In working with clients, we’ve researched and used numerous technologies for interactive charting. 1. jQuery Visualize 2. 3.

JavaScript Garden Although JavaScript deals fine with the syntax of two matching curly braces for blocks, it does not support block scope; hence, all that is left in the language is function scope. function test() { // a scope for(var i = 0; i < 10; i++) { // not a scope // count } console.log(i); // 10} There are also no distinct namespaces in JavaScript, which means that everything gets defined in one globally shared namespace. Each time a variable is referenced, JavaScript will traverse upwards through all the scopes until it finds it. The Bane of Global Variables // script Afoo = '42'; // script Bvar foo = '42' The above two scripts do not have the same effect. Again, that is not at all the same effect: not using var can have major implications. // global scopevar foo = 42;function test() { // local scope foo = 21;}test();foo; // 21 Leaving out the var statement inside the function test will override the value of foo. // global scopevar items = [/* some list */];for(var i = 0; i < 10; i++) { subLoop();}

Anonymous function Anonymous functions originate in the work of Alonzo Church in his invention of the lambda calculus in 1936 (prior to electronic computers), in which all functions are anonymous. In several programming languages, anonymous functions are introduced using the keyword lambda, and anonymous functions are often referred to as lambda functions. Uses[edit] Sorting[edit] When attempting to sort in a non-standard way it may be easier to contain the comparison logic as an anonymous function instead of creating a named function. Consider sorting a list of strings by length of the string: a = ['house', 'car', 'bike'] a.sort(lambda x,y: cmp(len(x), len(y)))print(a)['car', 'bike', 'house'] The anonymous function in this example is the lambda expression: The anonymous function accepts two arguments, x and y, and returns the comparison between them using the built-in function cmp(). a = [10, 'number', 11.2] a.sort(lambda x,y: cmp(x. Closures[edit] def comp(threshold): return lambda x: x < threshold Map[edit]

Application programming interface In computer programming, an application programming interface (API) specifies how some software components should interact with each other. Detailed explanation[edit] API in procedural languages[edit] In most procedural languages, an API specifies a set of functions or routines that accomplish a specific task or are allowed to interact with a specific software component. This specification is presented in a human readable format in paper books, or in electronic formats like ebooks or as man pages. For example, the math API on Unix systems is a specification on how to use the mathematical functions included in the math library. The Unix command man 3 sqrt presents the signature of the function sqrt in the form: SYNOPSIS #include <math.h> double sqrt(double X); float sqrtf(float X); DESCRIPTION sqrt computes the positive square root of the argument. ... $ perldoc -f sqrt sqrt EXPR sqrt #Return the square root of EXPR. API in object-oriented languages[edit] API libraries and frameworks[edit]