Design

7 Basic Rules for Making Charts and Graphs

July 22, 2010 to Design • Nathan Yau • Share on Twitter

Charts and graphs have found their way into news, presentations, and comics, with users from art to design to statistics. The design principles for these data graphics will vary depending on what you're using it for. Making something for a presentation? You'll want to keep it extremely simple and avoid using a lot of text. Designing a graphic for a newspaper? You'll have to deal with size constraints and try to explain the important parts of your graphic.

However, whatever you're making your charts and graphs for, whether it be for a report, an infographic online, or a piece of data art, there are a few basic rules that you should follow.

There's wiggle room with all of them, and you should think of what follows as more of a framework than a hard set of rules, but this is a good place to start for those just getting into data graphics.
Continue Reading
Why context is as important as the data itself

May 21, 2010 to Design, Statistics • Nathan Yau • Share on Twitter

John Allen Paulos, a math professor at Temple University, explains, in the New York Times, the importance of the before and after of when you get that data blobby thing in your hands.

The problem isn’t with statistical tests themselves but with what we do before and after we run them. First, we count if we can, but counting depends a great deal on previous assumptions about categorization. Consider, for example, the number of homeless people in Philadelphia, or the number of battered women in Atlanta, or the number of suicides in Denver. Is someone homeless if he’s unemployed and living with his brother’s family temporarily? Do we require that a women self-identify as battered to count her as such? If a person starts drinking day in and day out after a cancer diagnosis and dies from acute cirrhosis, did he kill himself?

In a nutshell, statistics is a game of estimation. More often than not, the numbers in front of you aren't an exact count. They could easily change if you shift the criteria of what was counted. As a result, there's always some amount of uncertainty attached to your data, and it's the statistician, analyst, and data scientist's job to minimize that uncertainty.

So the next time you see a list of rankings like "fattest city" or "dumbest town," don't take it for absolute truth. Instead, think of it as an educated guess. Similarly, when you analyze and visualize, remember the context of your data.

Catch Paulos' full article here.
The path to successful infographics

May 11, 2010 to Design, Infographics • Nathan Yau • Share on Twitter

Most people don't know what actually goes into a good infographic. There's a lot more to it than just the design. There's research, analysis, and fact-checking that you have to do long before you open Illustrator. Sarah Slobin, from the Wall Street Journal, explains how to create successful infographics. Have an idea, get the data, choose your tools, edit wisely, and above all else, pay close attention to detail.
Major wood pallet fires?

May 4, 2010 to Design, Mapping • Nathan Yau • Share on Twitter

I put this up only because I had no idea wood pallet risks were such a hot topic. No pun intended.

Of course, if you compare number of pallet fires to number of residential fires, the above almost seems like nothing. There were 20 major pallet fires between 2008 and 2010. There were 403,000 residential structure fires, causing an estimated $8.6 billion in damage - in 2008 alone.

While I'm sure the pallet fires caused plenty of problems, it's always good to put things in perspective.

Update: As Douglas points out, the site reeks of plastic pallet propaganda. Another case of forcing an issue by exaggerating the numbers. Tsk.

[Thanks, John]
Visualizing data: ask a question first

April 29, 2010 to Design, Quotes • Nathan Yau • Share on Twitter

There is no way to think up an original and extraordinary design—it can only come as a result of pursuing a given task. In the same way running down a list of words is different from making a narrative.

— Artemy Lebedev, Designer’s block, February 16, 2010

This applies to visualization too. When you don't have a question to answer or a simple wonderment about something, you end up staring at a bunch of numbers with no clue what to do with them. Want to test this out? Go to data.gov and make something useful.

[via @Coudal]
Graphical perception – learn the fundamentals first
Before you dive into the advanced stuff - like just about everything in your life - you have to learn the fundamentals before you know when you can break the rules.
Think like a statistician – without the math
I call myself a statistician, because, well, I'm a statistics graduate student. However, the most important things I've learned are less formal, but have proven extremely useful when working/playing with data.
11 Ways to Visualize Changes Over Time – A Guide

January 7, 2010 to Design • Nathan Yau • Share on Twitter

Deal with data? No doubt you've come across the time-based variety. The visualization you use to explore and display that data changes depending on what you're after and data types. Maybe you're looking for increases and decreases, or maybe seasonal patterns.

This is a guide to help you figure out what type of visualization to use to see that stuff.
Continue Reading
9 Ways to Visualize Proportions – A Guide

November 25, 2009 to Design • Nathan Yau • Share on Twitter

With all the visualization options out there, it can be hard to figure out what graph or chart suits your data best. This is a guide to make your decision easier for one particular type of data: proportions.

Maybe you want to show poll results or the types of crime over time, or maybe you're interested in a single percentage. Here's how you can show it.
Continue Reading
Chart Junk vs. Eye Candy: What’s the Difference?

September 25, 2009 to Design • Nathan Yau • Share on Twitter

Photo by horizontal.integration

There's this one phrase that really bothers me when it comes to data graphics. No doubt you've heard it or read it, and maybe it even popped into your head once or twice.

The phrase I'm talking about is: "Edward Tufte is crying."

People like to say this when they see a graphic that doesn't fit the ET law of high data/ink ratio. Then after the commenter has declared that ET is in fact a very emotional man, the graphic is classified "chart junk."

First off, I'm pretty sure ET isn't that melodramatic. He doesn't cry over a bad graph nor does he die a little inside or roll over in his grave if he were dead. I don't think an angel get its wings every time he rings a bell either. Although I could be wrong about the latter.

Second, not everything that fails to fit the mold of a traditional graph, visualization, or whatever you want to call it, is chart junk. One person's chart junk is another person's eye candy. What you see just depends on what angle you're looking at it from.
Continue Reading
What Visualization Tool/Software Should You Use? – Getting Started

September 3, 2009 to Design • Nathan Yau • Share on Twitter

Are you looking to get into data visualization, but don't quite know where to begin?

With all of the available tools to help you visualize data, it can be confusing where to start. The good news is, well, that there are a lot of (free) available tools out there to help you get started. It's just a matter of deciding which one suits you best. This is a guide to help you figure that out.
Continue Reading
Important Data – Please Act Responsibily

July 20, 2009 to Design • Nathan Yau • Share on Twitter

Photo by nyki_m

Data visualization and infographics come in many forms. Some are comical and purely made for entertainment. Others are made for decisions, and important decisions at that. Let's focus on the latter right now.

To make educated decisions based on graphics, you need accurate ones, and to make accurate graphics, you need a full understanding of the data.

If you don't know about the data - the context of where it came from or how it was collected - your visualization or infographic is simply a data comic that could potentially misinform its readers.
Continue Reading
6 Easy Steps to Make Your Graph (Really) Ugly

June 15, 2009 to Design • Nathan Yau • Share on Twitter

We spend so much time trying to make our graphs accurate, simple, understandable, etc that we forget the lost art of making graphs that are inaccurate, unreadable, make absolutely no sense, and make your eyes want to vomit. I'm so tired of understanding data. I want to experience it, and I know you want to also.

So this one's for you, crappy graph.
Continue Reading
Rise of the Data Scientist

June 4, 2009 to Design, Statistics • Nathan Yau • Share on Twitter

Photo by majamarko

As we've all read by now, Google's chief economist Hal Varian commented in January that the next sexy job in the next 10 years would be statisticians. Obviously, I whole-heartedly agree. Heck, I'd go a step further and say they're sexy now - mentally and physically.

However, if you went on to read the rest of Varian's interview, you'd know that by statisticians, he actually meant it as a general title for someone who is able to extract information from large datasets and then present something of use to non-data experts.
Continue Reading
Visual Representation of Tabular Information – How to Fix the Uncommunicative Table

April 21, 2009 to Design, Network Visualization • Nathan Yau • Share on Twitter

This is a guest post by Martin Krzywinski who develops Circos, a GPL-licensed (free) visualization tool that can help you show relationships in data. This article is based on a longer writeup which you can find here.

Suppose that you are reading an article and the text refers you to a table on the next page. Before you turn the page, what are your expectations of the table? Chances are, you would like it to communicate trends and patterns. Chances are, too, that it will fail and simply deliver numerical minutiae. You are left hunting around the numbers for a while, only to return to the text in hopes that the table's data trends will be communicated elsewhere.
Continue Reading
Data Visualization is Only Part of the Answer to Big Data

March 20, 2009 to Design, Exploratory Data Analysis • Nathan Yau • Share on Twitter

How can we now cope with a large amount of data and still do a thorough job of analysis so that we don't miss the Nobel Prize?

— Bill Cleveland, Getting Past the Pie Chart, SEED Magazine, 2.18.2009

For the past year, I've been slowly drifting off my statistical roots - more interested in design and aesthetics than in whether or not a particular graphic works or the more numeric tools at my disposal. I've always had more fun experimenting on a bunch different things rather than really knuckling down on a particular problem. This works for a lot of things - like online musings - but you miss a lot of the important technical points in the process, so I've been (slowly) working my way back to the analytical side of the river.
Continue Reading
Flow Chart Shows You What Chart to Use

January 15, 2009 to Design • Nathan Yau • Share on Twitter

~~Amit Agarwal, of Digital Inspiration, posts this~~ Andrew Abela creates this flow chart that helps you decide, well, what type of chart to use. Start in the middle with what you want to show - comparison, relationship, distribution, or composition - and then work your way out to the number of variables. Pretty timely for our brand new Visualize This project.

[via Digital Inspiration]
One Death is a Tragedy; a Million is a Statistic

January 9, 2009 to Design • Nathan Yau • Share on Twitter

Photograph by *Your Guide

I posted a comic from xkcd last week that implied graphs and data lead to a decline in love. I didn't really think much of it, but Jim commented that an episode from This American Life (episode 88: Numbers), was very much related to the topic of personal data and what we often miss out on as a result. The lead-in to the show reads:

Numbers lie. Numbers cover over complicated feelings and ambiguous situations. In this week's show, stories of people trying to use numbers to describe things that should not be quantified.

This reminded me of Joseph Stalin's well known quote, "One death is a tragedy; a million is a statistic." It's a horrible thing to say, but when it comes to data visualization and analysis, it's true a lot of the time. We have a huge dataset and we have to extract information from it. In the process though, we forget that every one of those numbers has real non-numeric value to it. There are emotions and feelings. Life is complex. Data represents life, and therein lies the purpose and meaning of FlowingData.
Continue Reading
Steve Jobs on Design

October 31, 2008 to Design, Quotes • Nathan Yau • Share on Twitter

Most people make the mistake of thinking design is what it looks like… People think it's this veneer -- that the designers are handed this box and told, 'Make it look good!' That's not what we think design is. It's not just what it looks like and feels like. Design is how it works.

— Steve Jobs, The New York Times, 2003

I post this not because I like Apple products, but because it's true (and because I like Apple products). I'm no designer, but as a statistician, I have tremendous respect for those who are. Have a nice weekend all.

[via swissmiss]
Great Data Visualization Tells a Great Story

October 10, 2008 to Design • Nathan Yau • Share on Twitter

Think of all the popular data visualization pieces out there - the ones that you always hear in lectures, read about in blogs, and the ones that popped into your head as you were reading this sentence. What do they all have in common? They probably all told a great story. Maybe the story was to convince us of something, compel us to action, enlighten us with new information, or force us to question our own preconceptions. Whatever it is, truly great data visualization reaches us at a very human level and that is why we remember them.

Let's face it. Data can be boring if you don't know what you're looking for or don't know that there's something to look for in the first place. It's just a mix of numbers and words that mean nothing other than their raw value. The great thing about statistics and data visualization though is that they provide us with the tools to learn that the data are much more than a bucket of numbers. There are stories in that bucket. There's meaning, truth, and beauty. Sometimes the stories will be simple and other times complex. Some will belong in a textbook; others will come in novel form. It's up to the statistician, computer scientist, designer, or analyst to make that decision.
Continue Reading