Gallery · mbostock/d3 Wiki Wiki ▸ Gallery Welcome to the D3 gallery! More examples are available for forking on Observable; see D3’s profile and the visualization collection. Please share your work on Observable, or tweet us a link! Visual Index Basic Charts Techniques, Interaction & Animation Maps Statistics Examples Collections The New York Times visualizations Jerome Cukier Jason Davies Jim Vallandingham Institute for Health Metrics and Evaluation Peter Cook Charts and Chart Components Bar Chart Histogram Pareto Chart Line and Area Chart Pie Chart Scatterplot and Bubble chart Parallel Coordinates, Parallel sets and Sankey Sunburst and Partition layout Force Layout Tree Misc Trees and Graphs Chord Layout (Circular Network) Maps Misc Charts Miscellaneous visualizations Charts using the reusable API Useful snippets Tools Interoperability Online Editors Products Store Apps
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What Statistics Can and Can’t Tell Us About Ourselves Harold Eddleston, a seventy-seven-year-old from Greater Manchester, was still reeling from a cancer diagnosis he had been given that week when, on a Saturday morning in February, 1998, he received the worst possible news. He would have to face the future alone: his beloved wife had died unexpectedly, from a heart attack. Eddleston’s daughter, concerned for his health, called their family doctor, a well-respected local man named Harold Shipman. He came to the house, sat with her father, held his hand, and spoke to him tenderly. Harold Shipman was one of the most prolific serial killers in history. David Spiegelhalter, the author of an important and comprehensive new book, “The Art of Statistics” (Basic), was one of the statisticians tasked by the ensuing public inquiry to establish whether the mortality rate of Shipman’s patients should have aroused suspicion earlier. One person’s actions, written only in numbers, tell a profound story. Or maybe not so unpredictable. Peto objected.
yEd - Graph Editor yEd is a powerful desktop application that can be used to quickly and effectively generate high-quality diagrams. Create diagrams manually, or import your external data for analysis. Our automatic layout algorithms arrange even large data sets with just the press of a button. yEd is freely available and runs on all major platforms: Windows, Unix/Linux, and Mac OS X. The latest release is version 3.12.2 Key Features Import your own data from an Excel® spreadsheet (.xls) or XML Create diagrams with easevia an intuitive user interface. Automatically arrangeyour diagram elements. Export bitmap and vector graphicsas PNG, JPG, SVG, PDF, SWF yEd in 90 seconds Supported Diagrams yEd supports a wide variety of diagram types. Support Resources The yEd online support resources include the yEd Graph Editor manual and the yEd forum where you can give us feedback.
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Visualization choice depends on the data and the questions Visualization choice depends on the data and the questions March 15, 2017 Topic Design / questions When you don’t know where to start with a dataset, try to come up with a question. Related Become a member.Support an independent site. What you get Recently for Members Sorting Usefully – The Process 169 Get Input – The Process 168 Visualization Tools and Resources, November 2021 Roundup Connecting Data to Practicality – The Process 166 Goodbye, Chartjunk – The Process 164 Projects by FlowingData See All → 19 Maps That Will Blow Your Mind and Change the Way You See the World. Many lists of maps promise to change the way you see the world, but this one actually does. The real A/C repair schedule My central air conditioner started to suck about a month … Most Uniquely Popular Job in Each State These are the jobs in each state that are most specific to the place. Fatal Traffic, When and Where Copyright © 2007-Present FlowingData.
Infographic Taxonomy - Vizualism Download Often it’s hard to find the most appropriate visualization method. But by knowing the structure of the data-set and defining the basic journalistic questions, it becomes easier when you use the matrix above: form follows function. I use it during my workshops and in my talks with journalists and designers. I’ve also been working on a three dimensional, more compact version of the matrix, where each intersection reveals the visual solution based on the combination of questions. Back in 2013, on my way to Malofiej Infographic Summit in Pamplona judiging the annual awards, I worked out some ideas about a taxonomy which resulted in the matrix above. Thanks to a tweet of Maarten Lambrechts, the taxonomy drew a lot of new attention in 2017.
A deterministic statistical machine As Roger pointed out the most recent batch of Y Combinator startups included a bunch of data-focused companies. One of these companies, StatWing, is a web-based tool for data analysis that looks like an improvement on SPSS with more plain text, more visualization, and a lot of the technical statistical details “under the hood”. I first read about StatWing on TechCrunch, where the title, “How Statwing Makes It Easier To Ask Questions About Data So You Don’t Have To Hire a Statistical Wizard”. StatWing looks super user-friendly and the idea of democratizing statistical analysis so more people can access these ideas is something that appeals to me. But, as one of the aforementioned statistical wizards, this had me freaked out for a minute. Once I looked at the software though, I realized it suffers from the same problem that most “user-friendly” statistical software suffers from. The advantage is that people can get their data-related questions answered using a standard tool.
The Biggest Myth About P-Values Ninety years ago, Ronald Fisher changed science forever. With his book, Statistical Methods for Researchers, the eminent English statistician popularized P values for measuring statistical significance in a scientific result, noting, almost as an afterthought, "Personally, the writer prefers to set a low standard of significance at the 5 percent point..." P = 0.05 was born, and, as computer scientist Robert Matthews critiqued years later, scientists were bestowed with a "mathematical machine for turning baloney into breakthroughs, and flukes into funding." Researchers in a great many disciplines now operate on Fisher's personal recommendation for significance. If a single finding attains a P value of 0.05 or lower, it's published as a noteworthy discovery and a scientific "truth". But that is not actually what Fisher intended. The largest reason for this sorry state of affairs is a pervasive myth about the P value. Other scientists would prefer to ditch P values altogether.
Studiengang Interfacedesign an der Fachhochschule Potsdam Für die Entwicklung von Gestaltungskompetenzen bieten wir Kurse an, in denen in praktischen Übungen Themen wie Screen-Design, Typografie, grafische User-Interfaces, generatives Design, Webdesign und Datenvisualisierung vermittelt werden. Hier lernen die Studierenden, wie sie gestalten und sie ihre Gestaltungsentscheidungen begründen können. Aber Interfacedesign geht weit über die Oberflächen hinaus. Auch wenn es nicht möglich ist, die Zukunft des Berufsfeldes von Designer*innen exakt vorauszusagen, so ist unumstritten, dass technologische Entwicklungen wie AI (Artificial Intelligence) und Machine Learning, Robotik sowie Virtual und Augmented Reality sowohl zukünftige Gestaltungsprozesse – z.B. Eigenverantwortung Das Design-Studium in Potsdam zeichnet sich durch ein hohes Maß an Eigenverantwortung aus.
Infographics vs. Data Visualization People keep asking what the difference is between data visualization and infographics. Since I’m not completely satisfied with the available answers I thought I could return to the subject and write my own. First, you have to recognize that you can’t compare them because they are not at the same level. Things get much simpler if we assume that data visualization is an umbrella concept that means some kind of visual transformation of some underlying data. This transformation takes advantage of the human perception to reduce cognitive overload. That’s a fact, not a goal. You can’t say much more. Let’s look at one of the dimensions that more clearly define each group: the conscious use of design and aesthetics. On the left there is a group of visual statisticians like Cleveland and Tukey, and I’ll add Bertin to the mix (yes, I know he was a cartographer). When you walk towards the center you’ll find a large group of functionalists. Stephen Few wrote about this and he says: What about you?
Info Aesthetics Save Download PDF A semi-open source book/Web site in progress. Project started 8/00, last update 10/27/01. Summary (updated 10/28/01) Info-Aesthetics scans contemporary culture to detect emerging aesthetics and computer-based cultural forms specific to information society. Its method is a systematic comparison of our own period with the beginning of the 20th century when modernist artists created new aesthetics, new forms, new representational techniques, and new symbols of industrial society. There are radically new representational techniques unique to own time, given that new media has largely been used in the service of older visual languages and media practices: Web TV, electronic book, interactive cinema? In short, if the shift from modernism to informationalism (the term of Manual Castells) has been accompanied by a shift from form to information, can we reduce information to forms, meaningful to a human? Book 2001
Information Visualization Manifesto Posted: August 30th, 2009 | Author: Manuel Lima | Filed under: Uncategorized | – “The purpose of visualization is insight, not pictures” Ben Shneiderman (1999) – Over the past few months I’ve been talking with many people passionate about Information Visualization who share a sense of saturation over a growing number of frivolous projects. When Martin Wattenberg and Fernanda Viégas wrote about Vernacular Visualization, in their excellent article on the July-August 2008 edition of interactions magazine, they observed how the last couple of years have witnessed the tipping point of a field that used to be locked away in its academic vault, far from the public eye. I don’t tend to be harshly censorial of many of the projects that over-glorify aesthetics over functionality, because I believe they’re part of our continuous growth and maturity as a discipline. Even though a clear divide is necessary, it doesn’t mean that Information Visualization and Information Art cannot coexist.