The Olympics are coming, the Olympics are coming. (As if you didn’t know.) In a rare moment of seeing my work outside of my company’s paywall, I can post a few infographics I have created for the 2012 Summer Games in London. The series looks at a few different non-Olympic variables like GDP per capita and mean BMI and sees whether they impact total medal counts in the Olympics.
This first datagraphic (to use my company’s internal language) looks at what makes a winner and will the UK be one this summer. The main chart in the piece compares GDP per capita performance to total medal count in each Olympic year from 1988 to 2008. And yes, we are predicting the UK to win a total of 65 medals this summer.
In the interest of full disclosure, I work as the senior graphic designer for Euromonitor International. This series was not intended to be used as part of marketing/promotional piece (I probably need to include the link to download that document here), but instead I designed them all as client-only content. But since others decided to use my work as marketing material, I am fortunately allowed to share it with all of you via my blog. So yeah, that’s pretty cool. Enjoy.
The Slovakian government has published the results from its 2011 census. The census looked at many things, including nationality and language. This should allow the government in Bratislava to better fund and support the ethnic minorities in Slovakia.
Of course, some of my ancestors were one of the small ethnic minorities in Slovakia. Ergo, I have a personal interest in the data. The result is a quick infographic about the Carpatho-Rusyns of Slovakia. Click on the cropping below to learn more, meaning, see a bigger and fuller version.
Credit for the work goes to me. For the data, the statistics office of Slovakia.
Last week Mitt Romney’s campaign released a series of infographic adverts. They were Venn Diagrams with messages attacking President Obama by highlighting what the Romney campaign called gaps between what the president has said he would do and what he has in fact done.
The problem with these is that they are all wrong. Do not misunderstand me, the Romney campaign certainly has valid points in these statements. And to use an infographic to communicate their points is a valid approach. But whoever designed these adverts clearly did not know how a Venn Diagram works.
Here is a brief refresher course for those interested.
Unfortunately, the Romney campaign’s message is being lost in a failed medium. It’s like watching a clown give a doctoral thesis in rocket science. He sure might be making a good point. But it’s a clown. People laugh at clowns. People won’t take the clown seriously. The Romney campaign is making good points, but that message is being lost because the campaign cannot master one of the simplest types of charts.
Credit for the originals go to the Romney campaign. The bit on How Venn Diagrams Work is mine.
The National Post’s business section, branded separately as the Financial Post, posted a comment about a proposed bridge that would span the Detroit River and add a third major crossing to the Detroit–Windsor area. The comment used a graphic to explain one of the key points of the story, that early 21st century traffic projections haven proven to be very much incorrect. Unfortunately, it took me a little bit of time to realise that in the graphic.
So without access to the raw data provided by United Research Services I have made a quick attempt to improve the graphic within the confines of Coffee Spoons’ main column space, i.e. 600 pixels. The original locator map is quite useful and therefore not included in my effort.
My main issues with the charts are the separation of the estimates from the actuals and the spacing between the estimates. I would have preferred to have seen, as in my example, how the actuals for 2010 fell far short of the 2004 projections. Ideally, I would have liked to have seen the original estimates for the intervening years between 2010, ’20, and ’30, however that data was not provided in the comment if it is even available from the original source. Consequently, unlike the original, I have kept the spacing of the actual data in the estimates with the intervening gaps.
The subtle effect of this increased spacing is to reduce the visual speed, if one will, of the projected growth. Over the original and narrower space the rate of increase appears fairly dramatic. However when given the correct spacing the ‘time’ to reach the projections lengthens and thus the rate ‘slows down’.
Credit for the original piece goes to Richard Johnson. The reinterpretation and any errors therein are entirely my own.
I generally refrain from posting links to my professional work. Normally because I’d have to be the first to criticise it and tear it apart. But also because a lot of it is confidential and behind the paywall—it’s like the Iron Curtain meets the Great Wall but really a lot less interesting.
Yet from time to time, through the work and deeds of others, things escape and make it into the wild. Then things are fair game. This is one of those times and one of those pieces. The image links to the third-party page.
On Sunday the New York Times featured a small graphic highlighting the disparity in growth rates across the G-20 if broken into the ‘core’ G-8 and then what one might call the emerging markets of the G-11.
The charts are small yet compelling in telling the story of how the two different groups are performing. However, I was left wanting to better understand the comparisons between the sizes and growth of the various countries. The areas of circles are difficult to compare and aggregates mask interesting outliers. So, using what I imagine to be the same data from the IMF, I took a quick try at the data to create my own infographic.
Indeed, interesting stories began to appear as I plotted the data. Russia is a member of the G-8, but perhaps has more in common with the G-11. After all, Russia’s growth was nearly 500%. Similarly interesting were Canada and Australia. The former, a G-8 country, was the only G-8 country besides Russia to have greater than 100% growth. And Australia, certainly not an emerging market in most senses, experienced nearly 300% growth. Whereas the emerging markets of Mexico and South Korea lag behind the rest of the G-11.
Then, when plotting the sizes of the economies, China was no surprise as the second-largest economy. However, that Brazil has managed to already surpass the G-8 economies of Italy, Russia, and Canada was a bit shocking. And Brazil looks nearly ready to surpass the UK, but for its apparent recent downturn. Also interesting to note are the Financial Crisis dips in GDP across most countries. Some countries, like China, unsurprisingly did not suffer greatly. However, that Japan and South Africa kept on a steady pace of growth was unexpected.
All of that would have been missed but for a slightly deeper dive into the IMF data. And a few hours of my time.
Last month I visualised my tea consumption data. But the other dataset that I record along with the tea is that of alcohol: when, where, and what I consume. The following is the result of four months of data, but you have to click for the full-scale view.
But the song relates to this post because earlier this week the print design blog For Print Only featured my annual Christmas card. I typically design and print a card to mail (as in a physical copy through the postal service, none of that e-card non-sense) to my friends and family. This past year I took to infographics to explore the realm of Santa and his North Pole dictatorship.
Last weekend I visited Ganister, Pennsylvania to see family, meet some old family friends, do some research, and generally just get out of Chicago. After I arrived, I realised I wasted an opportunity to tell the story of the drive out. So, I made a mental note to record some data on the long drive back. This infographic is the result.
Given the absence of a post yesterday, I took some time to do a small catch-up piece for you all. Those who know me offline are well aware that I document many things about my life including when I happen to drink tea. (And that’s often.) Finding myself with some unexpected time, I looked through the data that I have amassed since 1 January through to 28 March. While I aim to do more with this dataset someday, for now consider this a start. And now a self-surveillance infographic. On drinking tea.
It is interesting to note that I have in fact had tea every single day so far this year.