Tuesday, November 19, 2019

'How Charts Lie': a few edits to the first print edition

If you read the first print edition of How Charts Lie you may notice a few printing and layout errors. These should have been corrected in the e-book and the audiobook already. If you detect anything that looks strange other than these, please let me know.

Here they are:

On page 24 the transparency effects that should emphasize or hide parts of the charts disappeared between the galleys and the final printing. Here's how that graphic should look like:

On page 45 the line corresponding to the United States didn't show when printed. Here's the real graphic:

There's a minor issue with the gradient on the second bar of the chart on page 142: it doesn't fade to white for some reason. It should look like this:

A chart on page 116 is slightly misplaced.

On page 44, where it says “people became richer or poorer” or “people in those countries contaminated more or less,” I think I'll add “on average” just in case, as these are per capita numbers. On page 92 there's a needless “is” in a sentence that should read “Unless a crime is premeditated...” And at the bottom of page 128 there's an “as” missing before “Assange”.

The last label on the Y-scale of the chart on page 172 should read “600” instead of “490”. Like this:

Monday, November 18, 2019


C-SPAN2's BookTV recorded a public How Charts Lie lecture I gave at Northeastern University a few weeks ago. They broadcasted it this past Sunday afternoon and they've just made it available online, too. Here it is.

The slides are also available as a PDF, in case you find the talk useful and want to steal some ideas for your own classes or talks.

Friday, November 15, 2019

Visualization stuff I've seen recently

I guess I should launch a newsletter soon, as I'm seeing plenty of interesting visualizations and visualization-related articles lately—more than usual,—and it's difficult to keep up. Here are a few:

• I'll be on C-Span 2's BookTV on Sunday at 3:30PM EST to talk about How Charts Lie. The program will be available online right after, I believe.

• Kaiser Fung redesigns a chart that was discussed recently in social media.

Betsy Mason explains why scientists should get better at visualization. Her article is a good introduction to some elementary principles. She even has a section about why rainbow color schemes are evil.

Jon Peltier writes about maps (maps!) in Excel.

Nathan Yau talks about a Javascript library that lets you design XKCD-like visualizations.

• Randall Munroe, the creator of XKCD, is in the DataStories podcast, and has many thoughts about science communication.

• Cole Nussbaumer's Storytelling With Data website has a new look.

• There's a new episode of EagerEyesTV, Robert Kosara's video series; it explains data formats.

• Matteo Moretti explains how visualizations can be embedded into larger “informative experiences” through a couple of projects he designed.

Monday, November 11, 2019

Beautiful visualizations that reveal ugly truths: a neofascist party gets 15% of the vote in Spain

El País's coverage of yesterday's general election in Spain was exemplary, and that includes their graphics. El País made significant changes to their data and visualization desks recently, and it shows. They have a detailed map of the country and before the complete results were available they experimented with forecasts and real-time counting.

The bad news of the day was that a neofascist party, Vox, got 15% of the vote. More than 3.6 million people supported it. That should worry anyone who cares about the future of liberal democracy. I miss boring times.

Friday, November 8, 2019

Data and the junk in our lives

Spotting data visualizations and infographics in movies is a little pastime of mine. The latest case appears in the trailer of the upcoming Pixar movie, 'Soul'. A character is sitting in front of a large dashboard chockablock with data visualizations. The narrator says “don't waste your time with all the junk of life,” and the character tosses the screens away. Maybe the message of the movie is that Jazz is preferable to data? Why not both? I'm intrigued. Watch the trailer here; it looks beautiful.

Wednesday, November 6, 2019

A King and a Princess walk into a lecture about charts...

Yesterday I gave a talk about How Charts Lie in Barcelona. It was part of an event celebrating the 10th anniversary of the Princess of Girona Foundation, which supports young Spanish artists, scientists, and entrepreneurs. The King, the Queen, and their two daughters, Leonor and Sofia, attended the opening ceremony on the first day.

Several parallel talks and workshops took place the day after. When I was setting up in the auditorium I was assigned, Alfredo Martínez, the chief of protocol of the Spanish Royal Household, showed up, introduced himself, and casually said—this is not verbatim—“hey, did anybody tell you that the King is coming to your lecture?” Nobody had. “No pressure,” I thought.

The King brought Princess Leonor; they sat in the front row for most of the session. I got encouraged by two facts I observed: first, the King repeatedly whispered in his daughter's ear and pointed at the screen to further explain to her some of the graphics; second—and most importantly—the Princess, who is now 14, didn't fall asleep at any point. Success!

My dear friend Xaquín G.V. took some photos with his cell phone. Here they are:

Thursday, October 31, 2019

If the data is imperfect why isn't the visual representation of that data imperfect as well?

Animated GIF by Jared Wilber
RoughJS is a Javascript library that generates charts that look hand-drawn. Nadieh Bremer used it in her Why Do Cats & Dogs ...?, and I just saw a tweet about it by Javor Jordacevic. It reminded me of Mona Chalabi's charts, Elijah Meeks's Semiotic, and this paper about sketchy rendering.

Given my interest in methods of depicting uncertainty, I've often wondered why this type of rough, fuzzy style isn't explored more often. I have the hunch that graphics based on conventional geometric shapes with sharp boundaries such as dots, bubbles, lines, or bars may sometimes give readers a misleading impression of complete precision, when the truth is that most point estimates we represent in our visualizations are surrounded by clouds of uncertainty. Perhaps charts that look imperfect may suggest that the data they're based on isn't perfect either.

Wednesday, October 30, 2019

Visualizing personal notes on the history of Western Philosophy

Deniz Cem Önduygu, one of the founders of the Turkish studio Fevkalade, is both a designer and an amateur philosopher who has read extensively on the history of the field.

Deniz's portfolio contains a wide variety of intriguing projects, but the one that got my attention the most is a visualization of his personal notes on the history of Western Philosophy; it's a work-in-progress that he updates regularly (I hope that in the future he'll consider a color scheme different than red-green.)

I got drawn to this experimental interactive graphic because I'm also interested in philosophy—particularly epistemology, ethics, and the philosophy of mind—and the diagram reminded me of the visual notes I learned to draw when I was in High School: dense, hand-drawn network diagrams that work as personal mnemonic devices and that connect ideas, concepts, and direct quotes from books. Mine aren't interactive, though:

Monday, October 28, 2019

Student infographics and data visualizations

Our Interactive Media program's website is updating its student projects section soon; there's plenty of great work in it already, but we'll soon add many more infographics and data visualizations. The section currently looks like this (notice data visualization as one area of specialization on the upper-right corner):

Today I'm presenting to students and faculty at Mount Holyoke College, and one of my goals is to remind everyone that designing information graphics isn't magic; anyone can learn. I'll do that by mentioning our students' weblogs, and by including examples of their work in my slide deck; these graphics will soon be added to our program's website. Some of these students will graduate soon, so contact me if you're looking into hiring someone.

Deb Pang Davis came to the University of Miami with a background in editorial design and photography, but no experience whatsoever in data visualization; one month and a half into my introduction to infographics class she was able to design pieces like these, which were longlisted in this year's Information is Beautiful Awards:

Alyssa Fowers has a background in statistics and also a keen eye for design; her piece about her long-distance relationship also ended up in the Information is Beautiful Awards longlist:

Besides static infographics, interactive data visualization (d3.js and the like,) and mapping, we also teach 3D design; here's work by María del Carmen Aguilar and Yutong Han:

Sunday, October 27, 2019

Adding another funny map to my collection

Who knows whether I'll be able to add an updated foreword or epilogue to future editions of How Charts Lie in years to come, but I feel that there'll be plenty of material I can use because of the 2020 presidential election in the United States and the turmoil in many countries I know well—Spain, Argentina, Brazil, etc. In the meantime, I'll use this blog to collect deceptive, misleading, or funny graphics.

Saturday Night Live has just released the following clip with Alec Baldwin playing Trump during one of his rallies; the map he shows at the beginning is pretty funny:

Friday, October 25, 2019

Updated public talk and a great panel discussion

On Wednesday I delivered my updated public talk at Columbia University, and yesterday I did the same at the Urban Institute, where I shared a roundtable with Alli Torban, Amanda Makulec, Jon Schwabish, and Lázaro Gamio. Urban recorded the event, I made the slides available (feel free to use them in any way you want,) and Jon has shared some extra materials.

The talk was connected to How Charts Lie, but it went beyond it to get to matters I've been tentatively exploring for a year or so, such as attention, mindfulness, and the psychology of how we form and maintain beliefs. Anyway, I recommend that you jump to 59:00 in the video below and watch the panel first; it was a great conversation with fantastic questions from the public:

Thursday, October 24, 2019

Who doesn't love a good explanation graphic?

My friend and colleague Hiram Henríquez is both a lecturer at our School of Communication and an infographics designer with decades of experience at publications such as The Miami Herald and National Geographic magazine. He's recently posted a gallery of his most recent freelancing work, and there's much to like in it. For instance, this infographic about deep injection wells he made for the Everglades Foundation:

Or this piece about hurricane Irma's aftermath:

For years I've been trying to persuade Hiram to write a book about how to design visual, illustration-driven explanations. He's a master of the craft and also a good teacher, so I think he's the right person to do it. I hope that book will happen one day!

Tuesday, October 22, 2019

Musings on the modes of visualization design

When I finished writing How Charts Lie months ago I immediately began working on a new book; I'm co-writing with a friend and colleague. I always carry a notebook to scribble ideas, write reminders to myself, or just sketch things out, and the other day it occurred to me that it might be possible to envision the main modes of visualization design as a ternary chart:

I'm not sure about these terms or whether the diagram makes sense at all. These purposes a designer may have in mind aren't mutually exclusive, so they can't be defined as the opposite ends of a spectrum. Maybe a visualization can be conceptualized not by locating it as dot moving over those three axes, but by envisioning it as a triangle of varying size and shape. For instance, a visualization in which the designer emphasizes explanatory and emotional aspects—that's what I mean by “experiential”—would be described like this (this doesn't solve the challenge of the false opposites, though):

The corners of the diagram might also correspond to goals we seek: exploratory visualization favors efficiency to enable discovery; explanatory visualization needs to be understandable; experiential visualization elicits curiosity joy, worry, or outrage, which may lead to action:

None of this is very original. For instance, these days I'm re-reading Donald A. Norman's classic The Design of Everyday Things, and in its first pages there's this quote: “The major areas of design relevant to this book are industrial design, interaction design, and experience design. None of the fields is well defined, but the focus of the efforts does vary, with industrial designers emphasizing form and material, interactive designers emphasizing understandability and usability, and experience designers emphasizing the emotional impact.”

Also, Andy Kirk's Data Visualisation: A Handbook for Data Driven DesignI recently received its excellent second edition—lists three modes of experience when engaging with a visualization: explanatory, exhibitory, exploratory. Don't miss it:

Monday, October 21, 2019

The Gates Foundation's inequality report is a visualization feast

The Gates Foundation's 2019 Goalkeepers Report is titled Examining Inequality, and it exemplifies how to combine different languages within a single narrative piece. My favorite visuals in the report are the conceptual hand-drawn diagrams; these ones reveal the factors that may hinder a person's progress, such as gender, geography, etc.:

The report also contains orthodox visualizations. The designers at Graphicacy used scrollytelling in the middle section to zoom from a world map down to a specific region in Chad, and then to an individual girl: “Each time we zoom, we see yet another layer of disadvantage. These disadvantages don’t need to pile up on top of one another to make life hard—but when they do, as for the marginalized girl in Chad, the effect is brutal.”

There are several interactive scatter plots in this section. Notice that the Y-axis is often flipped in them: 0% on top and 100% at the bottom. There's a reason for this, as 0% means “better”—no child mortality—and 100% means “worse”, and therefore it's at the bottom. Pay attention also to the carefully written annotations:

The report can be downloaded in multiple languages as a PDF; I recommend that you take a look at it, as it contains many more graphics:

All data behind these figures is available here.

Thursday, October 17, 2019

Politico visualizes 'The Dis-United States of Cannabis'

The Dis-United States of Cannabis by Politico's Taylor Miller Thomas and Beatrice Jin is an example of how to categorize complex data, and of how to use equal-size square maps in a news story (one suggestion, though: I wish the charts had better color contrast; the shades of green are way too similar to each other):

Legislation about cannabis possession and use is so varied in the United States that the designers had to subdivide the country into several categories, and then show where marijuana is illegal, has been decriminalized, or has become legal either for medical or personal purposes. This is an example of one of the sections of the story:

There's a sources and methodology section at the end of the piece. This is great. Sometimes news publications separate their stories from the footnotes, sources, or explanations of the methods used to gather or analyze data. I think that integrating it all works better:

Tuesday, October 15, 2019

A dubious chart that confuses bias with trustworthiness

How Charts Lie is out today in the United States (see a few early corrections here,) and I guess that there's no better way to celebrate it than discussing a dubious chart, the one on the right. According to reporter Dana Liebelson it's being used in libraries to educate kids about which news organizations to avoid—those on the far left and far right columns.

There's so much wrong with this chart that it's difficult to decide what to begin with. I guess I'd first point out that having an ideological bias isn't bad per se, as the source of the chart, AllSides, implies in its motto (“don't be fooled by media bias and fake news”.) Lacking a clear ideological bias doesn't automatically make you more trustworthy.

On the contrary, you can have a clear ideological slant and still be trustworthy because your reporting and verification methods are solid, and because you strive to be honest and fair. Think of the New Yorker or Mother Jones magazines, for instance. On the right, Fox News online is pretty decent, National Review is a mixed bag, but it still has good columnists, and I fondly remember The Weekly Standard, which was clearly neoconservative while holding itself to strong professional standards, particularly when Stephen Hayes was in charge (Steve has just launched a new media venture recently, by the way; it's called The Dispatch.)

But the main reason this chart is so deceptive is that it compares things that aren't comparable. Come on, Breitbart or The Federalist rags at the same level of “bias” as Vox? The Washington Examiner at the same level as NPR? Those aren't equal. Neither in terms of trustworthiness, nor in terms of ideological bias. And The Hill (The Hill!) isn't a “centrist” publication. I could go on and on, and I'm sure you will have your own pet peeves.

UPDATE: Laura Ana Maria Bostan suggests this scatter plot as an alternative:

Monday, October 14, 2019

In The Washington Post and The Economist

How Charts Lie will be released tomorrow in the United States, and there has been some buzz around it in the past few days. This week's The Economist includes a review by Alex Selby-Boothroyd,—it's on page 87 of the print magazine,—and The Washington Post has just published this interview written by Christopher Ingraham.

I love the title that The Economist chose: ‘Axes of evil: Lies, damn lies and charts,’ and also the fact that the review ends with the following note:

“Mr Cairo has sent a copy to the White House.”

(I did!)

You can find other recent interviews in Storytelling With Data (Cole has also written a review,) BIBrainz, Present Beyond Measure, and Data Viz Today. Época, the Brazilian magazine I used to work for years ago, has also published a review.

If you want to get a sense of the cone and content of the book, read its first 20+ pages for free.

Thursday, October 10, 2019

Sometimes it's the simpler visualizations that matter the most

The New York Times has just published a nice piece about automobile COemissions in the U.S. It opens with a beautiful map where you can search for any metro area. Here's the Miami metro area:

It may be because I've seen a lot of visualizations in the past decades but, even if I liked the map a lot, I didn't find it that impressive or insightful. It's a bit like a population map, after all, although I'll admit it helps bring attention to the story.

I was more interested in the variation of emissions and their sources. Fortunately, Nadja Popovich and Denise Lu, the authors, also cover that in the graphs that follow the map. There's a lot of attention to detail in the design of these. Notice the annotations and the careful use of color:

Wednesday, October 9, 2019

Decisions in visualization should be based on reasons

The New York Times's David Leonhardt has a column titled The Rich Really Do Pay Lower Taxes Than You, meaning a lower effective tax rate. The column is based on a recent book, and it contains a graph that reminded me of something I wrote a while ago about line charts not being appropriate just for time-series data.

The graph displays the flattening of tax rates in the past seven decades. In the 1950s households in the lower income groups paid an effective rate of ~20%, while the richest were hit by a total tax bill of ~70%.

Today the picture is quite different: the line is almost flat, and the top 400 households pay ~23% while the lowest decile of households pays a higher rate of (I think) ~27%.

Responses to Leonhardt's social media postings about the article have been intense: people on the left claim that the flattening of the tax rate curve is unjust (Leonhardt agrees,) while conservatives say that the current tax rate distribution is fair, as everyone should pay more or less the same percentage of their income as taxes. In How Charts Lie I wrote that charts are rarely the last word in discussions about relevant issues, but they can certainly inform them. This chart is a great example of that.

A few words about the design of the graph itself: RJ Andrews, author of Info We Trust, sent me some intriguing suggestions. He worries about the evenly spaced tick marks on the X-axis of the graph. RJ proposes to subdivide the graph into three sections to separate the top 1% and the top 400 households from the other 99%. Here's a quick sketch he drew:

I liked the original NYT graphic, and it didn't bother me much that the X-axis tick marks are evenly spaced even if the last three tick marks don't correspond to income deciles. But I also like RJ's idea. Stuart Thompson reminded me that they tried an alternative design for a similar type of graph in a previous article—and I also like it!

I see good reasons to justify different design solutions in a case like this, so I'm torn. Perhaps this is a good topic for a class discussion or even for a little research experiment: does it matter more to be geometrically accurate? Or is it better to preserve continuity and maybe increase clarity, as the NYT did, by showing all data into a single chart that magnifies the upper echelons of the income distribution? Or could it be that none of this matters, and that all these design alternatives are equally effective and persuasive? Are we facing a distinction without a difference?

Tuesday, October 8, 2019

Read the first 20+ pages of 'How Charts Lie' for free

How Charts Lie will be available in the United States exactly one week from now—and a bit later in the UK. Here are the links to pre-order it through different bookstores and receive it exactly on the release date, October 15:

IndieBound (independent bookstores.)



My publisher, W.W. Norton, has agreed to make the book's introduction publicly available and free to download. If you want to read the first 20+ pages of the book in advance, download them from Google Drive or Dropbox.

I hope you'll enjoy them!