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NASSI-SHNEIDERMAN DIAGRAMS Nassi-Shneiderman Diagrams. Programming languages use words and symbols to represent structures like blocks and conditions. A visual representation of these structures seems useful to keep track of all the different cases, see the scope of variables, etc. Nassi-Shneiderman diagrams offer just such a representation. UNDERSTANDING PIE CHARTS DATA: CONTINUOUS VS. CATEGORICAL Data comes in a number of different types, which determine what kinds of mapping can be used for them. The most basic distinction is that between continuous (or quantitative) and categorical data, which has a profound impact on the types of visualizations that can be used. WHAT IS A MISLEADING CHART? The goal of this chart is to downplay the danger of global warming, and it does that quite well. It shows the data correctly without distorting it. It’s not the chart’s problem that it’s used for propaganda any more than a particular font is responsible for TUFTE AND THE TRUTH ABOUT THE CHALLENGER PEER REVIEW, PART 5: THE IMPORTANCE OF GATEKEEPERSSEE MORE ONEAGEREYES.ORG
REVIEW: ALBERTO CAIRO, HOW CHARTS LIE Review: Alberto Cairo, How Charts Lie. Alberto Cairo’s new book, How Charts Lie, takes readers on a tour of how charts are used and misused, and teaches them how to not be misled. It’s a useful book for both makers and consumers of charts, in the news, business, and pretty much anywhere else. When Alberto started talking about thetitle on
WHY IS METADATA SO HARD? The U.S. Department of Education just released an amazing dataset about the costs of going to college, earnings potential, etc.They’re doing so many things right, it’s really great. But what is still lacking is the metadata, making analysis harder than it needs to be. EAGEREYES – VISUALIZATION AND VISUAL COMMUNICATIONEXPLOREACADEMICADMINBLOG CALENDARBLOGROLLPIE CHARTS When I publish scientific papers, I write about them here. There's research on visualization techniques, perception, and other topics. Calendar. eagereyes has been around for a bit! This interactive calendar lets you explore more than ten years' worth of content. TRACKING 19,000 RUNNERS OVER 1,000KM ACROSS VIRTUAL TENNESSEESEE MOREON EAGEREYES.ORG
NASSI-SHNEIDERMAN DIAGRAMS Nassi-Shneiderman Diagrams. Programming languages use words and symbols to represent structures like blocks and conditions. A visual representation of these structures seems useful to keep track of all the different cases, see the scope of variables, etc. Nassi-Shneiderman diagrams offer just such a representation. UNDERSTANDING PIE CHARTS DATA: CONTINUOUS VS. CATEGORICAL Data comes in a number of different types, which determine what kinds of mapping can be used for them. The most basic distinction is that between continuous (or quantitative) and categorical data, which has a profound impact on the types of visualizations that can be used. WHAT IS A MISLEADING CHART? The goal of this chart is to downplay the danger of global warming, and it does that quite well. It shows the data correctly without distorting it. It’s not the chart’s problem that it’s used for propaganda any more than a particular font is responsible for TUFTE AND THE TRUTH ABOUT THE CHALLENGER PEER REVIEW, PART 5: THE IMPORTANCE OF GATEKEEPERSSEE MORE ONEAGEREYES.ORG
REVIEW: ALBERTO CAIRO, HOW CHARTS LIE Review: Alberto Cairo, How Charts Lie. Alberto Cairo’s new book, How Charts Lie, takes readers on a tour of how charts are used and misused, and teaches them how to not be misled. It’s a useful book for both makers and consumers of charts, in the news, business, and pretty much anywhere else. When Alberto started talking about thetitle on
WHY IS METADATA SO HARD? The U.S. Department of Education just released an amazing dataset about the costs of going to college, earnings potential, etc.They’re doing so many things right, it’s really great. But what is still lacking is the metadata, making analysis harder than it needs to be. ARTICLES - EAGEREYES This little book covers a large number of different ways of showing data. There are also some mathematical graphs, but the focus is on representations of data “from all areas of science and practice.”. It’s a fascinating look into what was known in the early 1900s, and how people thought about graphical representations as tools. CONTINUOUS VALUES AND BASELINES A bar that is twice as long represents a value that’s twice as big. But that is only true if that bar starts from zero. If it was cut off, that is no longer true. The following image shows the monthly sales of a fictitious coffee chain over a few months. The left bar chart starts at zero, the right one at $29K.AFFORDANCES
Robert, Great post! I talk about affordances when it comes to designing data visualizations (even static, offline data viz) in my workshops. For me, these are visual (rather than physical) characteristics of the graph that help make it clear to the user how to interact with it (e.g. selective strategic use of size, color, etc. to make it clear what is the most important that should be paid DATA: CONTINUOUS VS. CATEGORICAL Data comes in a number of different types, which determine what kinds of mapping can be used for them. The most basic distinction is that between continuous (or quantitative) and categorical data, which has a profound impact on the types of visualizations that can be used. SPREADSHEET THINKING VS. DATABASE THINKING Spreadsheet Thinking vs. Database Thinking. The shape of a dataset is hugely important to how well it can be handled by different software. The shape defines how it is laid out: wide as in a spreadsheet, or long as in a database table. Each has its use, but it’s important to understand their differences and when each is the right choice. LINEAR VS. QUADRATIC CHANGE License. Robert Kosara / September 19, 2008. Linear vs. Quadratic Change. One of the most common mistakes in chart design is to scale an area by two sides at the same time, producing a quadratic effect for a linear change. That overstates the larger numbers and produces a badly skewed chart. A little care and some basic high-school math can SPEAKING: HOW TO USE A MICROPHONE When you’re speaking in front of an audience, you’re almost always using a microphone.The point of the microphone is to help your audience hear you. But it can’t do that if you don’t know how to use it or if you actively work against it. SONIFICATION: THE POWER, THE PROBLEMS Robert Kosara / March 2, 2017. Sonification: The Power, The Problems. Sonification turns data into sound, just like visualization turns data into pictures. Except it’s a lot more complicated and limited. Something about sonification has always bugged me, and I think I’ve finally figured out what: the crowding on the time axis. A BETTER DEFINITION OF CHART JUNK A Better Definition of Chart Junk. Maximizing the data-ink ratio sounds like a good idea, but when actually followed to the letter produces terrible and nonsensical results. Here is a more reasonable definition of chart junk that does away with the pretense of a mathematical formula and puts some common sense back into the questionof good
THE BIKINI CHART
The Bikini Chart. The Obama administration released a chart a while ago that shows job losses during the last year of the Bush administration and the first year after Obama took office. The chart is simple yet effective in the way it communicates a message. It also has some very subtle design elements that communicate a much morenegative
EAGEREYES – VISUALIZATION AND VISUAL COMMUNICATIONEXPLOREACADEMICADMINBLOG CALENDARBLOGROLLPIE CHARTS When I publish scientific papers, I write about them here. There's research on visualization techniques, perception, and other topics. Calendar. eagereyes has been around for a bit! This interactive calendar lets you explore more than ten years' worth of content.AFFORDANCES
Robert, Great post! I talk about affordances when it comes to designing data visualizations (even static, offline data viz) in my workshops. For me, these are visual (rather than physical) characteristics of the graph that help make it clear to the user how to interact with it (e.g. selective strategic use of size, color, etc. to make it clear what is the most important that should be paid UNDERSTANDING PIE CHARTS NASSI-SHNEIDERMAN DIAGRAMS Nassi-Shneiderman Diagrams. Programming languages use words and symbols to represent structures like blocks and conditions. A visual representation of these structures seems useful to keep track of all the different cases, see the scope of variables, etc. Nassi-Shneiderman diagrams offer just such a representation. TRACKING 19,000 RUNNERS OVER 1,000KM ACROSS VIRTUAL TENNESSEESEE MOREON EAGEREYES.ORG
DATA: CONTINUOUS VS. CATEGORICAL Data comes in a number of different types, which determine what kinds of mapping can be used for them. The most basic distinction is that between continuous (or quantitative) and categorical data, which has a profound impact on the types of visualizations that can be used. ANSCOMBE’S QUARTET Anscombe’s Quartet is a case in point, showing that four datasets that have identical statistical properties can indeed be very different. Arguing for Graphics in 1973. In 1973, Francis J. Anscombe published a paper titled, Graphs in Statistical Analysis. The idea of using graphical methods had been established relatively recently byJohn
A PAIR OF PIE CHART PAPERS How do we read pie charts? Do they differ from the even more reviled donut charts? What about common pie chart designs like exploded pies? In two papers to be presented at EuroVis next week, Drew Skau and I show that the common wisdom about how we read these charts (by angle) is almost certainly wrong, and that things are much more complicatedthan we thought.
WHAT IS A MISLEADING CHART? The goal of this chart is to downplay the danger of global warming, and it does that quite well. It shows the data correctly without distorting it. It’s not the chart’s problem that it’s used for propaganda any more than a particular font is responsible for REVIEW: ALBERTO CAIRO, HOW CHARTS LIE Review: Alberto Cairo, How Charts Lie. Alberto Cairo’s new book, How Charts Lie, takes readers on a tour of how charts are used and misused, and teaches them how to not be misled. It’s a useful book for both makers and consumers of charts, in the news, business, and pretty much anywhere else. When Alberto started talking about thetitle on
EAGEREYES – VISUALIZATION AND VISUAL COMMUNICATIONEXPLOREACADEMICADMINBLOG CALENDARBLOGROLLPIE CHARTS When I publish scientific papers, I write about them here. There's research on visualization techniques, perception, and other topics. Calendar. eagereyes has been around for a bit! This interactive calendar lets you explore more than ten years' worth of content.AFFORDANCES
Robert, Great post! I talk about affordances when it comes to designing data visualizations (even static, offline data viz) in my workshops. For me, these are visual (rather than physical) characteristics of the graph that help make it clear to the user how to interact with it (e.g. selective strategic use of size, color, etc. to make it clear what is the most important that should be paid UNDERSTANDING PIE CHARTS NASSI-SHNEIDERMAN DIAGRAMS Nassi-Shneiderman Diagrams. Programming languages use words and symbols to represent structures like blocks and conditions. A visual representation of these structures seems useful to keep track of all the different cases, see the scope of variables, etc. Nassi-Shneiderman diagrams offer just such a representation. TRACKING 19,000 RUNNERS OVER 1,000KM ACROSS VIRTUAL TENNESSEESEE MOREON EAGEREYES.ORG
DATA: CONTINUOUS VS. CATEGORICAL Data comes in a number of different types, which determine what kinds of mapping can be used for them. The most basic distinction is that between continuous (or quantitative) and categorical data, which has a profound impact on the types of visualizations that can be used. ANSCOMBE’S QUARTET Anscombe’s Quartet is a case in point, showing that four datasets that have identical statistical properties can indeed be very different. Arguing for Graphics in 1973. In 1973, Francis J. Anscombe published a paper titled, Graphs in Statistical Analysis. The idea of using graphical methods had been established relatively recently byJohn
A PAIR OF PIE CHART PAPERS How do we read pie charts? Do they differ from the even more reviled donut charts? What about common pie chart designs like exploded pies? In two papers to be presented at EuroVis next week, Drew Skau and I show that the common wisdom about how we read these charts (by angle) is almost certainly wrong, and that things are much more complicatedthan we thought.
WHAT IS A MISLEADING CHART? The goal of this chart is to downplay the danger of global warming, and it does that quite well. It shows the data correctly without distorting it. It’s not the chart’s problem that it’s used for propaganda any more than a particular font is responsible for REVIEW: ALBERTO CAIRO, HOW CHARTS LIE Review: Alberto Cairo, How Charts Lie. Alberto Cairo’s new book, How Charts Lie, takes readers on a tour of how charts are used and misused, and teaches them how to not be misled. It’s a useful book for both makers and consumers of charts, in the news, business, and pretty much anywhere else. When Alberto started talking about thetitle on
ABOUT - EAGEREYES
About. The Site. EagerEyes is Robert Kosara’s place to reflect on the world of information visualization and visual communication of data. The goal is to help digest things that are happening in the field and discuss developments that may be tangential or early, but that are likely to have an impact. The opinions expressed here areRobert’s
ARTICLES - EAGEREYES This little book covers a large number of different ways of showing data. There are also some mathematical graphs, but the focus is on representations of data “from all areas of science and practice.”. It’s a fascinating look into what was known in the early 1900s, and how people thought about graphical representations as tools. TRACKING 19,000 RUNNERS OVER 1,000KM ACROSS VIRTUAL TENNESSEE In an animated visualization I’ve built of the progress of over 19,000 runners across a virtual 1000km (635mi) race over 123 days, I’ve tried to solve some of these issues. The Great Virtual Race Across Tennessee (GVRAT) is about 1022km or 635mi long, which makes it a 1000K. This is different from a 50K, 100K, or even a 100-mile racein
CONTINUOUS VALUES AND BASELINES A bar that is twice as long represents a value that’s twice as big. But that is only true if that bar starts from zero. If it was cut off, that is no longer true. The following image shows the monthly sales of a fictitious coffee chain over a few months. The left bar chart starts at zero, the right one at $29K. PARALLEL COORDINATES Parallel coordinates are a very versatile and useful technique for finding structures in moderately-sized datasets. With a bit of experience, it is possible to very quickly recognize patterns and even estimate the strength of correlations, etc. While they may look frightening at first, they’re actually very approachable. UNDERSTANDING PIE CHARTS The Part-Whole Relationship. The pie chart is actually a very clever visual design that conveys one fact above all others with a minimum of visual cues: that the circle (the “pie”) represents some kind of whole, which is made up of the slices. Add up all the slices and you get the complete pie. TUFTE AND THE TRUTH ABOUT THE CHALLENGER Robert Kosara / February 2, 2011. Tufte and the Truth about the Challenger. Almost exactly 25 years ago, on January 28, 1986, Space Shuttle Challenger disintegrated seconds after lift-off. One of Edward Tufte’s most famous examples of bad charts are the ones used by engineers who argued against the launch, and who failed to convince. A CRITIQUE OF CHERNOFF FACES A Critique of Chernoff Faces. Chernoff Faces are discussed in every information visualization course, and are referenced in many papers that talk about glyphs. Yet the only serious use of faces in visualization is for calibration, not for data display. Faces are so special that we better know their perceptual properties really wellbefore we
SPREADSHEET THINKING VS. DATABASE THINKING Spreadsheet Thinking vs. Database Thinking. The shape of a dataset is hugely important to how well it can be handled by different software. The shape defines how it is laid out: wide as in a spreadsheet, or long as in a database table. Each has its use, but it’s important to understand their differences and when each is the right choice. THE SIMPLE WAY TO SCRAPE AN HTML TABLE: GOOGLE DOCS Raw data is the best data, but a lot of public data can still only be found in tables rather than as directly machine-readable files.One example is the FDIC’s List of Failed Banks.Here is a simple trick to scrape such data from a website: Use Google Docs. The table on that page is even relatively nice because it includes some JavaScript tosort it.
EAGEREYES – VISUALIZATION AND VISUAL COMMUNICATIONEXPLOREACADEMICADMINBLOG CALENDARBLOGROLLPIE CHARTS When I publish scientific papers, I write about them here. There's research on visualization techniques, perception, and other topics. Calendar. eagereyes has been around for a bit! This interactive calendar lets you explore more than ten years' worth of content. ARTICLES - EAGEREYES This little book covers a large number of different ways of showing data. There are also some mathematical graphs, but the focus is on representations of data “from all areas of science and practice.”. It’s a fascinating look into what was known in the early 1900s, and how people thought about graphical representations as tools.AFFORDANCES
Robert, Great post! I talk about affordances when it comes to designing data visualizations (even static, offline data viz) in my workshops. For me, these are visual (rather than physical) characteristics of the graph that help make it clear to the user how to interact with it (e.g. selective strategic use of size, color, etc. to make it clear what is the most important that should be paid UNDERSTANDING PIE CHARTS TRACKING 19,000 RUNNERS OVER 1,000KM ACROSS VIRTUAL TENNESSEESEE MOREON EAGEREYES.ORG
DATA: CONTINUOUS VS. CATEGORICAL Data comes in a number of different types, which determine what kinds of mapping can be used for them. The most basic distinction is that between continuous (or quantitative) and categorical data, which has a profound impact on the types of visualizations that can be used. NASSI-SHNEIDERMAN DIAGRAMS Nassi-Shneiderman Diagrams. Programming languages use words and symbols to represent structures like blocks and conditions. A visual representation of these structures seems useful to keep track of all the different cases, see the scope of variables, etc. Nassi-Shneiderman diagrams offer just such a representation. UNDERSTANDING PIE CHARTS The Part-Whole Relationship. The pie chart is actually a very clever visual design that conveys one fact above all others with a minimum of visual cues: that the circle (the “pie”) represents some kind of whole, which is made up of the slices. Add up all the slices and you get the complete pie. SPREADSHEET THINKING VS. DATABASE THINKING Spreadsheet Thinking vs. Database Thinking. The shape of a dataset is hugely important to how well it can be handled by different software. The shape defines how it is laid out: wide as in a spreadsheet, or long as in a database table. Each has its use, but it’s important to understand their differences and when each is the right choice. REVIEW: ALBERTO CAIRO, HOW CHARTS LIE Review: Alberto Cairo, How Charts Lie. Alberto Cairo’s new book, How Charts Lie, takes readers on a tour of how charts are used and misused, and teaches them how to not be misled. It’s a useful book for both makers and consumers of charts, in the news, business, and pretty much anywhere else. When Alberto started talking about thetitle on
EAGEREYES – VISUALIZATION AND VISUAL COMMUNICATIONEXPLOREACADEMICADMINBLOG CALENDARBLOGROLLPIE CHARTS When I publish scientific papers, I write about them here. There's research on visualization techniques, perception, and other topics. Calendar. eagereyes has been around for a bit! This interactive calendar lets you explore more than ten years' worth of content. ARTICLES - EAGEREYES This little book covers a large number of different ways of showing data. There are also some mathematical graphs, but the focus is on representations of data “from all areas of science and practice.”. It’s a fascinating look into what was known in the early 1900s, and how people thought about graphical representations as tools.AFFORDANCES
Robert, Great post! I talk about affordances when it comes to designing data visualizations (even static, offline data viz) in my workshops. For me, these are visual (rather than physical) characteristics of the graph that help make it clear to the user how to interact with it (e.g. selective strategic use of size, color, etc. to make it clear what is the most important that should be paid UNDERSTANDING PIE CHARTS TRACKING 19,000 RUNNERS OVER 1,000KM ACROSS VIRTUAL TENNESSEESEE MOREON EAGEREYES.ORG
DATA: CONTINUOUS VS. CATEGORICAL Data comes in a number of different types, which determine what kinds of mapping can be used for them. The most basic distinction is that between continuous (or quantitative) and categorical data, which has a profound impact on the types of visualizations that can be used. NASSI-SHNEIDERMAN DIAGRAMS Nassi-Shneiderman Diagrams. Programming languages use words and symbols to represent structures like blocks and conditions. A visual representation of these structures seems useful to keep track of all the different cases, see the scope of variables, etc. Nassi-Shneiderman diagrams offer just such a representation. UNDERSTANDING PIE CHARTS The Part-Whole Relationship. The pie chart is actually a very clever visual design that conveys one fact above all others with a minimum of visual cues: that the circle (the “pie”) represents some kind of whole, which is made up of the slices. Add up all the slices and you get the complete pie. SPREADSHEET THINKING VS. DATABASE THINKING Spreadsheet Thinking vs. Database Thinking. The shape of a dataset is hugely important to how well it can be handled by different software. The shape defines how it is laid out: wide as in a spreadsheet, or long as in a database table. Each has its use, but it’s important to understand their differences and when each is the right choice. REVIEW: ALBERTO CAIRO, HOW CHARTS LIE Review: Alberto Cairo, How Charts Lie. Alberto Cairo’s new book, How Charts Lie, takes readers on a tour of how charts are used and misused, and teaches them how to not be misled. It’s a useful book for both makers and consumers of charts, in the news, business, and pretty much anywhere else. When Alberto started talking about thetitle on
ABOUT
About. The Site. EagerEyes is Robert Kosara’s place to reflect on the world of information visualization and visual communication of data. The goal is to help digest things that are happening in the field and discuss developments that may be tangential or early, but that are likely to have an impact. The opinions expressed here areRobert’s
ARTICLES - EAGEREYES This little book covers a large number of different ways of showing data. There are also some mathematical graphs, but the focus is on representations of data “from all areas of science and practice.”. It’s a fascinating look into what was known in the early 1900s, and how people thought about graphical representations as tools. THE EAGEREYES STARTER PACK The EagerEyes Starter Pack. There’s a lot of stuff on this site. Where to start? Here is a little introduction and a number of pointers to get you started. Visualization is so fascinating because it’s done in so many ways and touches so many other fields: perceptual psychology, statistics, TRACKING 19,000 RUNNERS OVER 1,000KM ACROSS VIRTUAL TENNESSEE In an animated visualization I’ve built of the progress of over 19,000 runners across a virtual 1000km (635mi) race over 123 days, I’ve tried to solve some of these issues. The Great Virtual Race Across Tennessee (GVRAT) is about 1022km or 635mi long, which makes it a 1000K. This is different from a 50K, 100K, or even a 100-mile racein
NASSI-SHNEIDERMAN DIAGRAMS Nassi-Shneiderman Diagrams. Programming languages use words and symbols to represent structures like blocks and conditions. A visual representation of these structures seems useful to keep track of all the different cases, see the scope of variables, etc. Nassi-Shneiderman diagrams offer just such a representation.VENN DIAGRAMS
Venn diagrams are a great way to visualize the structure of set relationships. They’re also an example of a technique that works very well for a particular purpose, but that entirely fails outside its well-defined scope or when the number of sets gets too large. The idea of the Venn diagram is simple: sets are shown as regions,typically circles.
TUFTE AND THE TRUTH ABOUT THE CHALLENGER Robert Kosara / February 2, 2011. Tufte and the Truth about the Challenger. Almost exactly 25 years ago, on January 28, 1986, Space Shuttle Challenger disintegrated seconds after lift-off. One of Edward Tufte’s most famous examples of bad charts are the ones used by engineers who argued against the launch, and who failed to convince.THE BIKINI CHART
Thanks for writing this up! The Bikini Chart will serve as a prime example of a rhetorical visualization for years to come, I’m sure. I’ve always thought this chart was a good response to the bikini chart. The power lies in the data set chosen – job gains/losses per month, which provided such a pleasing, symmetrical (and political valuable) chart formation. SPEAKING: HOW TO USE A MICROPHONE When you’re speaking in front of an audience, you’re almost always using a microphone.The point of the microphone is to help your audience hear you. But it can’t do that if you don’t know how to use it or if you actively work against it. A BETTER DEFINITION OF CHART JUNK A Better Definition of Chart Junk. Maximizing the data-ink ratio sounds like a good idea, but when actually followed to the letter produces terrible and nonsensical results. Here is a more reasonable definition of chart junk that does away with the pretense of a mathematical formula and puts some common sense back into the questionof good
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VISUALIZATION AND VISUAL COMMUNICATION What's happening in information visualization? Robert Kosara digests new and emerging developments and explores what we know and don't know – so we can be less wrong about visualization. IN PRAISE OF THE DIAGONAL REFERENCE LINE March 23, 2020 6 Comments Annotations are what set visual communication and journalism apart from just visualization. They often consist of text, but some of the most useful annotations are graphical elements, and many of them are very simple. One type I have a particular fondness for is the diagonal reference line, which has been used to provide powerful context in past news pieces, and is making a comeback in the COVID-19 charts. THE VISUAL EVOLUTION OF THE “FLATTENING THE CURVE” INFORMATIONGRAPHIC
March 15, 2020 4 Comments Communication has been quite a challenge during the COVID-19 pandemic, and data visualization hasn't been the most helpful given the low quality of the data – see Amanda Makulec's plea to think harder about making another coronavirus chart.
A great example of how to do things right is the widely-circulated _Flatten the Curve_ information graphic/cartoon. Here's a look at the work it is built on and how that has evolved from a figure in an academic paper to one of the clearest pieces of visual communicationin some time.
EAGEREYESTV: WHAT IS DATA? PART 2, ARE IMAGES DATA? December 16, 2019 Leave a Comment Visualization turns data into images, but are images themselves data? There are often claims that they are, but then you mostly see the images themselves without much additional data. In this video, I look at image browsers, a project classifying selfies along a number of criteria, and the additional information stored in HEIC that makes ISOTYPE BOOK: YOUNG, PRAGER, THERE’S WORK FOR ALL December 1, 2019 2 Comments This book from 1945 contains a very interesting mix of different charts made by the ISOTYPE Institute, some classic and some quite unusual. As a book about labor and unemployment, it also makes extensive use of Gerd Arntz’s famous unemployed man icon.MORE ARTICLES
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What happens when you connect all the ZIP codes in the U.S. in order? It's a surprising and interesting pattern. Explore yourself!PIE CHARTS
Think you know pie charts? Here's an overview, tips&tricks, and cutting-edge research on the chart everybody loves to hate.TECHNIQUES
Bar charts, pie charts, parallel coordinates, Venn diagrams, … What are they? How do they work? Which one do you use for what?PAPERS
When I publish scientific papers, I write about them here. There's research on visualization techniques, perception, and other topics.CALENDAR
eagereyes has been around for a bit! This interactive calendar lets you explore more than ten years' worth of content.FOOTER
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