This week on the PolicyViz Podcast: Yours Truly

Oh, the pleasure of reaching a milestone in your career. This is one of those days for me as Jon Schwabish has finally relented and had me as a guest on the PolicyViz podcast, after years of me pestering him (tuns out he wanted money).

Seriously, it is an honour to be on the podcast. I listen to it and find it not only useful to know who's who and who's doing what, but engaging too. The live format is less guarded than the blog posts or tweetstorms that we share and it can be revealing of people's strongly held views (and language tics).

I admire greatly what Jon is doing to connect the dataviz community. In person, he's a natural networker and it's very much thanks to his generosity at Visualized in 2014 that I first got to meet many people in the field. I'm glad he's doing the same thing online with the PolicyViz podcast.

So don't miss this episode, especially if you find the French accent sexy. We spoke a lot about my work at the World Bank Group and with my clients, helping people change their ways. How do you convince people to replace their beloved graphs? To give up on their four paragraphs of text on a slide? Foolproof solutions to these age-old problems and more in just 26 minutes. As a bonus, you'll get to know how I got in the field.

Remake: CNBC Holiday Shopping Graph

My friends Ann K. Emery and Jon Schwabish have been discussing a graph published by CNBC about Holiday budgets. Ann reported that her husband was confused by the original graph:

Jon chimed in with his own remake:

Here is the image of his remake.

 
 

Ann's pet peeve is clustered columns and mine is stacked bar charts. On Jon's remake, I can't quite see what's going on with everyone's Holiday shopping, except perhaps that Millenials stuck to their budget more than other generations.

Upon closer look, it seems that the point of the data is to compare how fiscally responsible each generation is in regards to its Holiday budget. Hence, it should be easy, looking at the graph, to see which generation overspends, which sticks to its budget, and which doesn't even have a budget.

Here is my remake.

 
 

The organization of the data is close to the original: I grouped the generations under their spending habits. This way we can immediately see which generation spends more (Generation X), which sticks to its budget (Millenial), which spends less (X again) and who doesn't have a budget (Baby boomer). Unlike Ann's husband, I don't find it difficult (or necessary) to see which data adds to 100%. It seems more interesting to answer the questions "Which generation over/underspends?" Given that the generations follow the same general trend, grouping by generation would yield graphs difficult to differentiate.

My general approach to data visualization is that content matters. It should influence the choice of graph, the order of the data, the colors, the analytical angle. Here are a few explanations for my design choices:

  1. Obviously, I replaced the columns with horizontal bars, giving space to the titles and labels. In my training, I often joke that people would solve 50% of their data visualization issues with horizontal bar charts, but perhaps it's not a joke.
  2. I stuck to the original size because that was the rule of the game and a useful constraint. I saved some space because with the integration of text and data, I no longer needed a separate legend like the original chart did.
  3. I relabeled the "Total" row. When it comes to people, it seems more intuitive and appropriate to talk about "Everyone". I also differentiated it visually. This is another of my pet peeves: calculated data that is shown the same way as the source data.
  4. I stuck to the client colors (except for a lighter grey) but I tried to apply them in a slightly more intuitive sense: yellow for overspending, green for sticking to budget and grey for no budget (neutral in this context of comparing to budget). Blue seemed neutral and indeed I'm not sure if it's that good to spend less than budgeted on gifts.
  5. I changed the order of the charts so that the one on top is about overspending, then the one about sticking to budget, then underspending and finally, no budget. It seems a more intuitive sequence (more-stuck-less-none) than the original (stuck-more-less-none) with the "on-budget" chart in between the more and less ones. The order of the generations also follows that of a population pyramid with the older people on top.

I don't quite hope to get Ann's husband approval given that it keeps the same groupings, but perhaps with better design, the messages will become clearer and he'll understand the data better.


BREAKING: I won the competition! I would like to thank the judge and all those who have supported me on this long journey.

Accès refusé: le métro de Montréal

Inspiré par le projet «Access Denied» du Guardian, j'ai voulu voir de quoi le métro de Montréal a l'air pour ceux qui se déplacent en chaise roulante et ont donc besoin d'un accès par ascenseur. La STM marque ces stations d'un icône, mais celui-ci se perd dans le design et il n'est pas facile de voir la réalité des gens en chaise roulante. J'ai donc changé les couleurs de la carte officielle afin de faire ressortir celle que voient ces gens et qui est invisible aux autres.

Il y a donc seulement deux lignes de métro sur quatre qui leur soient accessibles, la bleue ne servant que de raccourci d'est en ouest. Techniquement, la ligne verte est accessible entre Lionel-Groulx et Berri-UQÀM, mais elle ne fait que dédoubler l'accès par la ligne orange. Des douze stations avec ascenseurs, trois sont à Laval. Un projet pour la prochaine administration?

Note: Une première version de cette carte n'incluait pas le passage sur la ligne bleue entre les stations Snowdon et Jean-Talon. Merci à Robert Couillard pour l'observation.

Interview: Stephanie Evergreen wants to build a 30-foot dataviz out of clay

I got to cross an item off the bucket list when offered the opportunity to work with another data visualization professional. Luck stroke when a client invited me to work on a project with Stephanie Evergreen. And it was all that I was hoping: inspiring, professional, dynamic. 

Just look at what she's done: she's written one of the books in my library, she delivers workshops around the world, blogs profusely, is cooking up a dataviz academy, and more. She's been on the PolicyViz podcast of course. But now is when she really achieves fame by agreeing to answer a few questions for this blog. 

1. Of the last 50 tweets in your home timeline, which is your favorite and why?

My friend Chris Lysy posted a cartoon and short blog about the drama I recently had in which some pure statisticians got angry over the way guests on my site worded their regression results. It’s adding humor to something that became a little stressful and I always appreciate that.

2. What’s the one thing you would improve on the Minard map? 

A “Translate This” button, because I don’t know French.

3. Who needs data visualization most and doesn’t know it?

The guy sitting next to me in first class. I tweeted a pic of one of these situations:

4. If you were to organize a conference on data visualization, how would you call it and why?

I’d call it the “Free Kittens Conference” and make it such that everyone sends the one person they know who really needs to learn more about data visualization but is reluctant to change. Do you think the guy in first class will come to a Free Kittens Conference? Maybe it needs to be called Free Martinis.

5. What else would you do if you were not remotely in this field?

Nature guide. I have a knack for identifying flora and fauna. I can barely remember my mother’s birthday but I can detail how to distinguish a vulture from a hawk from an eagle when they fly overhead (hint: it's in the wing tips).

6. How would you introduce yourself to Edward Tufte?

Hard pass on this question, Francis.

7. Who has less than 300 followers on Twitter and should have much more? 

Deven Wisner.  He’s been blogging on dataviz lately and he’s got solid info to share. 

 

 

 


8. (From Andy Kirk) What’s the one data visualisation passion project that you’ve never had the time, opportunity or capability to undertake but would dearly love to do so one day?

After launching the Data Viz Academy and the Chart Chooser Cards, I’ve gotten to realize many of my dreams. But I’ve always wanted to work with a client who would let me build a 30 foot data visualization out of clay, showcasing some great results, for display in their lobby. 


9. What question should I ask my next guest? 

What’s the freshest good data visualization idea you’ve heard lately?

Tapestry 2017: Connecting the Dots

Data visualization is not an easy job. This can get lost in the quibbles about whether bar charts are boring and pie charts are useless, as we risk thinking that our role is limited to finding which encoding is perceived most precisely by the human eye. In fact, it is to give humans access to something written in a machine language: data.

The richness of a conference like Tapestry is a reminder of the multifaceted job of information designers. This year, the thread that ran through the conference seemed to be the multiple connections that we need to establish to hope succeed at our task.

The data visualization community is a motley crew and Catherine d’Ignazio made the most of it as she trained art students to play with data and illustrate it with animated GIFs. The result was engaging, amusing even. How else would responses to a survey became a spectacular, months-long exhibit in a public hall?

This happened because the data had a purpose — in this case, public transit. In fact, it seems a sine qua non if we want our content to connect with our audience. Finding something important to say about schools and discrimination in Florida is what got the Tampa Bay Times a Pulitzer price for Failure Factories, the project shown by Nathaniel Lash.

An important topic is not enough to guarantee a connection. How matters. Our tool is data visualization and our audience is humans — certain ways will connect the two better than others. Michelle Borkin brought the valuable perspective from academia as she explored what visual elements are most easily recalled in a visualization. Again, the findings were about connection: people would recall a title that was more story than description, and human recognizable objects such as animals and silhouettes. Who would have remembered anything from Cole Nussbaumer’s “typical business presentation” if she hadn’t translated it later into a story about vocal and insightful dissatisfied customers? The fact that her satire was a reflection of the real world reminds us that understanding a story might be intuitive, but knowing how to tell one is learnt.

Jewel Loree opened up about her stumbles in sharing her enthusiasm for data about a local radio station. Fellow fans of the station weren't thrilled by the mere existence of the data and its superficial findings. She had to dig deeper until a story about the connection between the artists, the DJs and the audience emerged. 

The conference started and ended by challenging us to connect with ourselves. Self-awareness is a rhetorical tool and not the least. Still, it remains elusive. Are we even aware of our own biases and emotions, asked Lena Groeger and Neil Halloran? Are we ready to face them? The question of biases seems especially relevant to a field where many of us are working alone or in very small teams where diversity is either impossible or very difficult, but no less important. Exposing ourselves to different perspectives, through reading, listening and experiencing, is merely a start.

On the day of my return from Tapestry, I witnessed a grown man, a professional hockey player, cry in front of thousands and millions on television because he was reminded of a past connection to a city where he lived in for years. Connection is what moves us and, as we attempt to move people, we’ll have to learn to connect: to our subjects, to our audiences and to ourselves.


Much like the meal at a dinner with friends, talks are central to a conference, but they remain an excuse to meet people. For a lone freelancer, these opportunities to get together with peers are a fountain of youth, to use a metaphor local to our host city. Sinuous career paths caught in the attraction of a passion, infectious enthusiasm, and similar interest in mundane details are all things that remind me of my connection to a community. For these reasons, I can’t stress enough how important it was to meet again with some and to get to know others. With the certainty of overlooking some, let me say another hello to Andy Kirk, my partner in crime for the poster, Cole Nussbaumer Knaflic, Jon Schwabish (and his mom), Neil Halloran (and his dad), Andy Cotgreave, RJ Andrews, Domonique Meeks, Ben Jones, Chad Skelton, Catherine Madden, Enrico Bertini, Robert Kosara, Jewel Loree, Lena Groeger, Alberto Cairo, Chris Mast, Naomi Robbins, Jeffrey Osborn, Jeffrey Shaffer and my rideshare team: Chrys Wu, Blake Esselstyn and Lori Navarro. I came to see you. Thanks to the organizers for inviting me.

Also: My thoughts about Tapestry 2014.