Last week the Economist published a fascinating read that uses one of the fundamental information design pieces there is. The piece talks about the history of organising within the field of chemistry and the most well-known…elements in it: the elements. I am, of course, referring to the Periodic Table.
The piece starts actually in revolutionary France, a history I did not know, and walks through how that led into the eventual development of Mendeleev’s table. It then briefly runs through the history of the concept of the atom and how that evolved to define the refined table we see today. (And in so doing it includes a nice graphic showing the shell model of the atom’s electron orbits.)
I often work in data visualisation—surprising exactly nobody given this blog—and one thing I often say is that while graphics are for showing and storytelling, tables are for organising. The Periodic Table organised information known about atoms both known and unknown, creating holes for future chemists to place their discoveries. It is the chemistry we all know and love—or perhaps hate—today. It is a classic piece of information design.
And the reason why I bring it up? The Economist pointed out that last week it turned 150 years old.
Credit for the piece goes to the Economist graphics department.
We made it to the end of the week, everybody. And that’s saying something.
Part of my jobs over the last several years has been to work with context experts and help them tell their stories. Sometimes I have to do it through charts and graphics. When that happens, I often need data files to help me create the final piece. I cannot tell you how many times this has happened.
This piece from the BBC is a few years old, but it provides some interesting nuggets about North Korea. Unsurprisingly it appeared on my radar because of the coverage of the Trump–Kim summit in Vietnam. The article says it is nine charts that tell you all you need to know about North Korea. Now, I do not think that is quite true, but it does contain the following graphic—I hesitate to call it a chart—that illustrates one of my favourite details.
The two figures illustrate the average height of a person from North Korea and then South Korea. What do you see? That the North Korean is shorter. This is despite the fact that the populations were the same just a few decades ago. The impact of years of malnutrition, undernourishment, and general lack of well-being have manifested themselves in the physical reduction of size of human beings compared to their nearly identical population to the south.
Thankfully the rest of the piece contains data on things like GDP, birth rates, and life expectancy. So there are some things in there that one should know about North Korea. As much as I find the story of height interesting, I struggle to think it is one of the nine things you should really know about the state.
Credit for the piece goes to Mark Bryson, Gerry Fletcher, and Prina Shah.
Today’s piece is a nice little graphic from the Economist about the oil and natural gas industry in the United States. We have a bar chart that does a great job showing just how precipitous the decline in Chinese purchases of oil and liquid natural gas has been. Why the drop off? That would be the trade war.
The second graphic, on the right, is far more interesting. The data comes from BP, so the proverbial grain of salt, but it compares expected GDP and demand for energy by source from a baseline model of pre-Trumpian trade war policies to a future of “less globalisation”. Shockingly (sarcasm), the world is worse off when global trade is hindered.
You all know where I stand on stacked bar charts. They are better than pie charts, but still not my favourite. If I really want to dig in and look at the change to, say, coal demand, I cannot. I have to mentally remove that yellow-y bit from the bottom of the bar and reposition to the 0 baseline. Or, I could simply have coal as a separate bar next to the other energy sources.
Credit for the piece goes to the Economist Data Team.
So today’s piece is not a revolutionary piece of information design, but it is fascinating. For two or so years now, we have all heard about the Robert Mueller investigation into potential contacts between the Trump campaign, early administration, and the administration of Russian president Vladimir Putin.
To be clear, thus far, this has been an incredibly productive special counsel.
34: the number of indictments
6: guilty pleas from associates of the Trump campaign
But what happens when the whole thing is done, especially since prevailing Justice Department rules state sitting presidents cannot be indicted? Well to answer that, we have this piece from the Washington Post.
Ultimately it is nothing more than a flow chart broken into pieces, separated by a textual narrative explaining the process. Now, I’m not certain how critical to the design each headshot is—especially Barr’s that looks especially frowny faced. However, the context in the above screenshot is crucial. The public does not necessarily have the right to the findings of the report if individuals in the report are not charged.
This means that design wise, we are looking at snippets of a larger chart interspersed with text. I would be interested to see the entire thing stitched together, but the textual breaks make a lot of sense. Overall, much like the sports pieces we looked at recently, this does a nice job of weaving textual story together with information design or data-driven content.
Credit for the piece goes to Dan Keating and Aaron Steckelberg.
As many of you know, genealogy and family history is a topic that interests me greatly. This past weekend I spent quite a bit of time trying to sort through a puzzle—though I am not yet finished. It centred on identifying the correct lineages of a family living in a remote part of western Pennsylvania. The problem is the surname was prevalent if not common—something to be expected if just one family unit has 13 kids—and that the first names given to the children were often the same across family units. Combine that with some less than extensive records, at least those available online, and you are left with a mess. The biggest hiccup was the commonality of the names, however. It’s easier to track a Quinton Smith than a John Smith.
Taking a break from that for a bit yesterday, I was reminded of this piece from the Economist about two weeks ago. It looked at the individualism of the United States and how that might track with names. The article is a fascinating read on how the commonness or lack thereof for Danish names can be used as a proxy to measure the individualism of migrants to the United States in the 19th century. It then compares that to those who remained behind and the commonness of their names.
The scatter plot above is what the piece uses to introduce the reader to the narrative. And it is what it is, a solid scatter plot with a line of best fit for a select group of rich countries. But further on in the piece, the designers opted for some interesting dot plots and bar charts to showcase the dataset.
Now I do have some issues with the methodology. Would this hold up for Irish, English, German, or Italian immigrants in the 19th century? What about non-European immigrants? Nonetheless it is a fascinating idea.
Credit for the piece goes to the Economist Data Team.
On Tuesday the San Diego Padres signed Manny Machado to a guaranteed contract worth $300 million over the next ten years—though he can opt out after five years. Machado was one of two big free agents on the market, the other being Bryce Harper. One question out there is whether or not these big contracts will be worth it for the signing teams. This piece yesterday from the New York Times tries to look at those contracts and how the players performed during them.
Like the piece we looked at Tuesday, this takes a narrative approach instead of a data exploratory approach—the screenshot above is halfway through the read. Unlike the Post piece, this one does not allow users to explore the data. Unlabelled dots do not reveal the player and there is no way to know who they are.
Overall it is a very strong piece that shows how large and long contracts are risky for baseball teams. The next big question is where, for how long, and how much will Bryce Harper sign?
Credit for the piece goes to Joe Ward and Jeremy Bowers.
Yesterday the New York Times published a fascinating piece looking at the data on how often President Trump has gone after the Special Counsel’s investigation. (Spoiler: over 1100 times.) It makes use of a number of curvy line charts showing the peaks of mentions of topics and people, e.g. Jeff Sessions. But my favourite element was this timeline.
It’s nothing crazy or fancy, but simple small multiples of a calendar format. The date and the month are not particular important, but rather the frequency of the appearances of the red dots. And often they appear, especially last summer.
Credit for the piece goes to Larry Buchanan and Karen Yourish.
Back in 2012 the New York Times ran what is a classic data visualisation piece on Mariano Rivera. It tracked the number of saves the legendary Yankees closer had over his career and showed just how ridiculous that number was—and how quickly he had attained it. Last week, the Washington Post ran a piece that did something very similar about LeBron James, a future basketball legend, and Michael Jordan, definitely a basketball legend.
The key part of the piece is the line chart tracking points scored, screenshot above. It takes the same approach as the Rivera piece, but instead tracks scored points. Unlike the Rivera piece, which was more “dashboard” like in its appearance and function, allowing users to explore a dataset, this is more narratively constructed. The user scrolls through and reads the story the authors want you to read. Thankfully, for those who might be more interested in exploring the dataset, the interactivity remains intact as the user scrolls down the article.
While the main thrust of the piece is the line chart, it does offer a few other bar and line charts to put James’ career into perspective relative to the changing nature of NBA games. The line chart breaking down the composition of James’ scoring on a yearly basis is particularly fascinating.
But, don’t ask me about how he fits into the history of basketball or how he truly compares to Michael Jordan. Basketball isn’t my sport. But this is a great piece overall.
Credit for the piece goes to Armand Emamdjomeh and Ben Golliver.
Last summer NASA’s Martian exploration rover Opportunity went dark as its solar panels, needed to power the golf-cart sized explorer, were covered in dust from a planet-wide dust storm. Everyone hoped that over the following months the light Martian winds and dust devils would wipe clean the dust from the solar panels and the rover could recharge its batteries, turn on its heaters, and resume contact with Earth. It hasn’t. Consequently, on Wednesday NASA called Opportunity’s mission complete. And thanks to xkcd we have a proper little farewell.