DataVis Tutorials - Principles
Book published and available now! A week or so ago I shared details of the imminent release of my first book, well I’m thrilled to say my book is now published and available to buy! The best place to get the book will be direct via Packt publishing’s website. At the time of writing this the eBook is available at £9.59 (€13.59, $14.39) and the print book/eBook bundle is £17.09 (€25.19, $26.99).
Clarity or Aesthetics? Part 3 – Tips for Achieving Both | DataRemixed Previous Post (Part 2 of 3): A Tale of Four Quadrants We started this series by introducing the notion of a two dimensional plane on which to assess all data graphics, and then followed it up with an example of visualizations in four different quadrants on the plane to illustrate the differences between the two axes, clarity and aesthetics, that define the plane. Now, let’s review some of the basic principles & tips that you will find in the data visualization resources out there. All I have done here is I have applied these well-known best practices to the four quadrant system. Those of my readers who are familiar with the field of data visualization will recognize these tips – they are not new.
. Unfortunately, world class educational materials are normally hidden behind payment systems or in expensive textbooks. If you want this to change, you should . As such, these copyright terms are designed for the author and the reader, not the publisher and the profit. Except as otherwise noted, this work is copyright of Stephen Few and The Interaction Design Foundation (Chr.
I’ve been interested lately in finding examples of online-only, collaborative, non-profit newsrooms who’ve utilized the power of data visualization techniques to give added value to stories that otherwise wouldn’t necessarily be unique, and in doing so beat out legacy news organizations who published a text narrative alone. Take, for example, this data-rich story and interactive map displaying statewide testing results published by NJSpotlight Friday. While the news that only 8 out of 10 graduating seniors had passed New Jersey’s current standardized test in 2011 was widely reported across the state last week, including by the Star-Ledger in Newark and by The Press of Atlantic City, only NJSpotlight took advantage of the story’s strong data element to produce a more concise, data-driven visual narrative. So NJSpotlight obviously deserves kudos for the gap they’re filling in New Jersey journalism. Using data-viz to make a wire story stand out from the pack | Carl V. Lewis
Numbers don't lie, but a bad chart decision makes it extremely difficult to understand what those numbers mean. Before you put together another PowerPoint presentation, make sure your pick the right type of chart to clearly communicate the information you want to share. Here's how. How to Choose the Best Chart for Your Data
Previous Post (1 of 3): Data Visualization: Clarity or Aesthetics? Part 2 of 3: A Tale of Four Quadrants: In Part 1, we introduced the notion of a two dimensional plane on which a data visualization can be mapped as a single point using the x,y coordinates [clarity, aesthetics], where clarity ranges from confusing to clear, and aesthetics ranges from ugly to beautiful. The single point can then be transformed into a circle with area proportional to the impact of the work. While not perfect, such a system just might be useful to determine how to assess and ultimately improve a given data visualization. Clarity or Aesthetics? Part 2 – A Tale of Four Quadrants | DataRemixed
Information can be useful--and even beautiful--but only when it’s presented well. In an age of information overload, any guidance through the clutter comes as a welcome relief. That’s one reason for the recent popularity of information graphics. Infographics are visual designs that help to explain complicated data in a simple way (mental-health emergencies at Burning Man, anyone?). But how are they created? What can we learn from the designer’s process?
Article: The 8 hats of data visualisation design Last week I posted a slideshare version of my slides from a recent pair of presentation events in Chicago. The title of this talk was “The 8 hats of data visualisation”. In this article I want to follow up these slides with a written accompaniment to contextualise and explain what I was presenting, as slides alone don’t really manage to achieve this effectively.
Alan Smithee Presents
"The success of companies like Google, Facebook, Amazon, and Netflix, not to mention Wall Street firms and industries from manufacturing and retail to healthcare, is increasingly driven by better tools for extracting meaning from very large quantities of data. 'Data Scientist' is now the hottest job title in Silicon Valley." – Tim O'Reilly From basic statistics to machine learning and new ways to think about visualization, the Data Science Starter Kit gives you the tools you need to get started with data. If you haven't yet taken the leap, why wait? Data Science Kit - Deals
by Maria Popova What 12 million human emotions have to do with civilian air traffic and the order of the universe. I’ve spent the past week being consistently blown away at the EyeO Festival of data visualization and computational arts, organized by my friend Jer Thorp, New York Times data artist in residence, and Dave Schroeder of Flashbelt fame. While showcasing their mind-blowing, eye-blasting work, the festival’s all-star speakers have been recommending their favorite books on the subject matter, so I’ve compiled the top recommendations for your illuminating pleasure. Enjoy.
Is it possible to create a “data visualization hierarchy of needs” like Maslow’s hierarchy of human needs? I’ve tried that in the pyramid above. Here are the details: Data Visualization Hierarchy of Needs The Excel Charts Blog
Which Visualization Type Should I Use? Ever spend several hours putting together what you think is a killer presentation, only to step back and realize that your visuals aren’t quite cutting it? That was me this weekend. There I was working on, what I thought was a killer project when my friend came in and said how my charts just really sucked. They were too complex and actually ended up taking away from the project instead of helping it. One of the trickier aspects with visualizations can be determining which visual technique best displays information.
Some thoughts on visualisation
had.co.nz This is the website of Hadley Wickham. I'm an Assistant Professor of Statistics at Rice University, interested in interactive and dynamic graphics, in developing practical tools for data analysis, and in gaining better understanding of complex statistical models through visualisation. In July 2008, I completed my PhD in statistics at Iowa State University with Di Cook and Heike Hofmann. Professional resources Teaching stat645: Data visualisation.
10 significant visualisation developments: 2011 Back in July I published a collection of the 10 most significant visualisation developments from the first half of 2011. These were a very personal view of the most prominent, memorable, significant, progressive and appealing developments of the year so far. As we prepare to bid farewell to 2011 I am now looking back over the latter half of the year with a follow up collection of developments that I perceive to have had most significance during the period July to December. As I made clear in the previous post, there will be selections here that won’t or wouldn’t make other peoples’ top 10s but I wouldn’t expect them to.
At the end of each month I pull together a collection of links to some of the most relevant, interesting or thought-provoking web content I’ve come across during the previous month. Here’s the latest collection from February 2014. Includes static and interactive visualisation examples, infographics and galleries/collections of relevant imagery. Data Remixed | ‘Visualizing History’ via a Presidential Gantt chart
An Information Visualization Exercise | Dashboard Spy
Paper: Privacy-Preserving Visualization
Newsletter. ASA Statistics Computing and Graphics
Data visualisation: in defence of bad graphics | News
How to create a terrible visualization
2011W MAT259 - Visualizing Information
Report Builder 3.0 – Chart Types, Visualizations, and Properties
International Statistical Literacy Project home
A Case Study In How Infographics Can Bend The Truth
Creating your own data visualisations | Louise Brown
Visualization series: Insight from Cleveland and Tufte on plotting numeric data by groups | Solomon Messing
Concept-driven versus Data-driven visualizations
VennStorming: The Good, the Bad and The Ugly of Visual storytelling «
001.1 Graphing Fundamentals - chrisgemignani
How to create a visualization
7 Key Tips for Big Data
001.2 Graphing Fundamentals - Principles 1 - chrisgemignani
001.3 Graphing Fundamentals - Principles 2 - chrisgemignani