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The 14 Best Data Visualization Tools

The 14 Best Data Visualization Tools
Nishith Sharma is the co-founder of frrole, a social intelligence startup. Raw data is boring and it’s difficult to make sense of it in its natural form. Add visualization to it and you get something that everybody can easily digest. Not only you can make sense of it faster, but you can also observe interesting patterns that wouldn’t be apparent from looking only at stats. All Killer, No Filler This one’s different, trust us. To make the tedious task of making beautiful charts and maps easier, I’ve made the list of best data visualization tools available for the job. Let’s get started! For Developers D3.js D3.js, short for ‘Data Driven Documents’, is the first name that comes to mind when we think of a Data Visualization Software. It doesn’t ship with pre-built charts out of the box, but has a nice gallery which showcases what’s possible with D3. FusionCharts FusionCharts has probably the most exhaustive collection of charts and maps. Chart.js Google Charts Highcharts Leaflet dygraphs Datawrapper

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Tree diagrams in d3.js The following post is a portion of the D3 Tips and Tricks book which is free to download. To use this post in context, consider it with the others in the blog or just download the the book as a pdf / epub or mobi . What is a Tree Diagram? The ‘Tree layout’ is not a distinct type of diagram per se. Instead, it’s representative of D3’s family of hierarchical layouts.

A 5-step guide to data visualization Data has been described as the new raw material for business and the "oil of the 21st century." The volume of data used in business, research and technological development is massive and continues to grow. For instance at Elsevier, there are about 700 million articles per year downloaded from ScienceDirect, 80,000 institution profiles on Scopus, 13 million researcher profiles on Scopus and 3 million researcher profiles on Mendeley. It becomes harder and harder for a user to grab a key message from this universe of data. That's where data visualization comes in: summarizing and presenting large data in simple and easy-to-understand visualizations to give readers insightful information. There are many advanced visualizations (e.g., networks, 3D-models and map overlays) used for specialized purposes such as 3D medical imaging, urban transportation simulation, and disaster relief monitoring.

Starting with Canvas for a D3.js addict - Visual Cinnamon In this blog I’d like to take you through my learnings from last week when I finally started with canvas. I hope that, after reading this blog, I will have convinced you that canvas is a really good visualization option if you need better performance than d3.js can give you and that it’s actually really not that difficult to learn canvas. Last September I made a data visualization project about the age distribution across all ~550 occupations in the US. I came up with the idea of combining the standard d3.js circle pack layout with mini bar charts, or ‘small multiple packing’ as I started calling it. The size of the circles encodes how many people are employed in that occupation and the bar chart within the circle gives another level of detail by showing you how these people are spread across 7 different age bins.

Education Technology Tools for Teachers Massive Open Online Courses make it possible for students of all ages to access high-quality coursework at no cost. Colleges and universities across the country publish video lectures, podcasts, reading lists, practice exams and more for anyone who wants to learn about a particular subject and/or experience what it’s like to take a college class. Over the last decade, organizations such as Coursera and Khan Academy have taken MOOCs one step further by creating or aggregating thousands of free courses in areas ranging from early American history and civics to trigonometry and multivariable calculus. Khan Academy is a non-profit educational website created by educator Salman Khan in 2006. Parerga und Paralipomena » Blog Archive » Messing around wih D3.js and hierarchical data These days there are a lot of browser-oriented visualization toolkits, such d3.js or jit.js. They’re great and easy to use, but how much do they scale when used with medium-large or very large datasets? The subject ontology is a quite large (~2500 entities) taxonomical classification developed at Nature Publishing Group in order to classify scientific publications. The taxonomy is publicly available on data.nature.com, and is being encoded using the SKOS RDF vocabulary. In order to evaluate the scalability of various javascript tree visualizations I extracted a JSON version of the subject taxonomy and tried to render it on a webpage, using out-of-the-box some of the viz approaches made available; here are the results (ps: I added the option of selecting how many levels of the tree can be visualized, just to get an idea of when a viz breaks). Some conclusions:

The Best Infographics of the Year: Nate Silver on the 3 Keys to Great Information Design and the Line Between Editing and Censorship by Maria Popova “More isn’t always better: no more in information design than in poetry…” Once again this year, I was delighted to serve on the “Brain Trust” for an annual project by Pulitzer-Prize-winning journalist, New Yorker writer, and Scientific American neuroscience blog editor Gareth Cook, who culls the best, most thoughtful and illuminating infographics published each year, online and off, and invites the bearer of a sharp mind to contextualize both the individual selections and the premise of the project. Alongside the inaugural crop of infographic exemplars was David Byrne’s excellent essay on cultivating the ability to experience the “geeky rapture” of metaphorical thinking and pattern recognition. Silver, the author of The Signal and the Noise, considers the two factors that make an infographic compelling — providing a window into its creator’s mind and telling a story that “couldn’t be told in any other way.” He writes:

Data Structures D3.js Accepts The Goal In this section, you will understand how to structure data for better use of D3.js. We will cover where we have been, how D3.js thinks of selections, the basics of JavaScript objects and how to best structure our data. What we have seen thus far Every example we have done with D3.js thus far has included a data set at the top of the example like this one: The 31 Educational Web Tools Every Teacher Should Know about Below is a list I have been working on for the last couple of days. This list features some interesting web tools for teachers keen on integrating technology into their instruction and work routine. There are loads of web platforms that are educationally focused and to contain them all in one list is way beyond the scope of a short blog post like this , therefore I selected only what I deemed the most important.

Threejs Britzpetermann was commissioned to create an installation for the entrance hall that draws attention to the topic energy. The team decided to break down the topic energy and chose the 4 elements, the basis of all energy extractions which are used in the park and present in an elegant and interactive way. Driven by the idea of a droplet of water following a line, Manny Tan created this Three.Js experiment that explores a droplet shape and it’s associated views in 3d space. The web application allows you to click and drag to rotate the shape. Alternatively, you can use the scroll wheel or right click and drag to move […] The Carp and the Seagull is an interactive short film about one man’s encounter with the spirit world and his fall from grace.

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