Regional Power Plays

One of the things we missed covering last week whilst I was on holiday? The dust up in the Gulf of Oman, located near the Strait of Hormuz, where two foreign ships were attacked by mines or other explosive devices. The United States blames Iran and, of course, Iran denies it. The thing is, an inordinate amount of oil flows through the Strait, connecting the petroleum-driven economies of the West to the instability in the Middle East. Thankfully we have a graphic from the Guardian to explain just what is going on there.

Not shown: the US, the EU, China, and Russia
Not shown: the US, the EU, China, and Russia

The above is a screenshot from the article, one of several graphics. There is a stacked bar chart showing the total volume of oil in transit, and the Strait’s share of it. Spoiler: it’s significant. We all know how I feel about stacked bars: not the biggest fan.

There are, of course, locator maps showing the locations of the attacked ships. We also have some photographs showing the damage inflicted upon the tankers, as well as some evidence of what the US claims is Iranian activities. (Side note: isn’t it great that when the US really wants the world to trust its intelligence agencies the White House has been doing nothing but trashing said intelligence agencies?)

The above, however, is a simple map showing the political fault line in the Middle East. It gets to the heart of the potential conflict here being not a US vs. Iran war, but a Saudi Arabia vs. Iran war. After all, relations between the Saudis and the Trumps have warmed significantly since the Obama administration. And not shown in the map is the role of Israel, which, again has seen a significant warming in relations between Trump and Netanyahu, and which has also been quietly supporting Saudi Arabia in its undeclared war against Iran, to date fought only with proxies, most notably in Yemen.

In other words, the Middle East is a complicated and complex tinder box, built next to a few nuclear reactors, all of which just happen to sit atop vast reserves of oil and natural gas. So the best thing to do? Clearly start exploding things.

Credit for the piece goes to the Guardian graphics department.

Tariffs Are a Tax

This piece from the New York Times isn’t really even a graphic. It’s a factette, or small fact. The article is about how tariffs are raising the price of certain goods, in this case a bicycle. Tariffs do not add money to the US Treasury, they are instead an additional price paid by US consumers on goods—not services—originating from outside the US.

Thankfully I can't ride a bike
Thankfully I can’t ride a bike

Sometimes a big chart is not as impactful as one big number. And here, in the context of this story, a graphic showing trade flows between the US and Mexico may have been useful. But the real gut punch is showing how the tariffs on Mexico, for this one particular bike, could cost the US consumer an additional $90. A tariff is just another word for a tax paid by the American consumer.

Credit for the piece goes to the New York Times graphics department.

The Rise of the Tropic(al Plant)s

Last week I had three different discussions with people about some of the impact of climate change upon the United States. However, what did not really come up in those conversations was the environmental changes set to befall the United States. And by environment, I explicitly mean how the flora of the US will change.

Why? Well, as warmer climates spread north, that means tropical and subtropical plants can follow warmer temperatures northward into lands previously too cold. And they could replace the species native to those lands, who evolved adaptations for their particular climate.

Thankfully, last week the New York Times published a piece that explored how those impacts could be felt. Hardiness zones are a concept designed to tell gardeners when and where to plant certain crops. And while the US Department of Agriculture has a detailed version useful to horticulturists, the National Oceanic and Atmospheric Administration produces a very similar version for the purpose of climate studies. And when you group those hardiness levels by the forecast lowest temperatures in an area, you get this.

More palm trees?
More palm trees?

There you have it, the forecast change to plant zones.

From a design standpoint, I like the idea of the colour shift here. However, where it breaks seems odd. Though it could be more influenced by the underlying classifications than I understand. The split occurs at 0ºF, which is well below freezing. I wonder if the freezing point, 32ºF could have been used instead. I also wonder if adding Celsius units above the same legend could be done to make the piece more accessible to a broader audience.

Otherwise, it’s a nice use of small multiples. And from the editorial design standpoint, I like how the article’s text above the graphic makes use of a six-column layout to add some dynamic contrast to what is essentially a three-column layout for the graphics.

They're living on a grid
They’re living on a grid

Credit for the piece goes to Nadja Popovich.

The Climate Impact of Your Food

Climate change is a thing. And facing it will require a lot of our societies. But the longer we choose not to act, the more the impact will be felt by later generations. Consequently, across the world, young students have been walking out of class to shine light on an issue on which they, as children, have little direct impact. Yet. But what about us? The ones who can vote and make lifestyle decisions?

The BBC had a piece where, after soliciting questions from their readership, they answered questions. One question being, what can individuals do to reduce their impact. And while clearly individuals need to do more than one thing, one facet can be examining one’s diet. The article included this graphic on the climate impact of various food types, vis-a-vis greenhouse gas emissions.

Is this saying I should drink more beer?
Is this saying I should drink more beer?

Essentially we are looking at a simplified box plot of greenhouse gas emissions per serving of food (and drink) type. The box plot looks at a range of values for a specific item. It usually shows the extremes at both ends; the range of a significant number of the data points, e.g. 80% of the set, or by decile, or by quartile; and then lastly the average, be it mean or median. Here we have only low impact, high impact, and average impact. Presumably the minimum, maximum, and then either mean or median.

And it works really well. Chocolate is a great example of how on average, chocolate isn’t terrible. But certain chocolates can have far worse ramifications than low-impact beef, or average-impact lamb and prawns. And beef is well known to be one of the most impactful types of food.

From a design standpoint, I don’t know if the colours necessarily help. The average beef impact, for example, is worse than the high-impact maximum of every other food listed. But the association of green=good and red=bad  here has little value because by that logic, the average=gold beef should be red as it sits above the high-impact everything else. A less editorial choice could be made of say a light grey or blue and then have the bright colour, maybe still orange, indicate where the average sits on that spectrum.

I do like the annotations on the chart. It highlights particular stories, like the aforementioned chocolate one, that the casual, i.e. skimming, reader may miss.

I could probably do without the little food illustrations. But the designer did a good job of making them all recognisable in such a small space—far from an easy task. And being so small, they don’t really distract or take away from the whole graphic.

Overall, this is a strong graphic.

Credit for the piece goes to the BBC graphics department.

Britain Bombing in Eurovision

Last weekend was not only the Game of Thrones finale, but also the Eurovision final. For the Americans not familiar with it, it’s a part music, part theatrics competition between all European countries and then sometimes guest countries like Australia or Israel. The winner is chosen by the total number of points their act receives. The UK, as one of the largest countries in Europe, is one of the few countries that is guaranteed a spot.

But that doesn’t mean the UK performs well. Last weekend, the UK bombed. The winner, the Netherlands, scored 498 points. The UK? 11. But the UK has been terrible for years now. And unlike in American baseball, it’s not because tanking gets you coveted draft picks for new talent. The BBC charted the placement of the British entries since its last win in 1997, the height of Cool Britannia.

Consistently bad over the last several years
Consistently bad over the last several years

Design wise, I wonder about the horizontal movement of places. A top-to-bottom movement might make more sense. The labelling here is also a bit too much. My eye immediately settles on the black text for the years, as their tight spacing creates a dark field that overpowers the otherwise nice light blue–dark blue contrast in the graphic. Maybe the beginning and end years could have been labelled with some key intervals, say every five years?

Similarly, the use of the ordinal number over the cardinal on the right hand side puts more emphasis on the labelling than the graphic itself. Here, however, the designers wisely chose a grey for the text so as not to overpower the graphic. But I wonder if the use of a cardinal number could have reduced the extra bits of text at the end and drive more focus to the graphic.

Overall, it’s a neat graphic. But I think a few small tweaks could improve the design. Unfortunately for the UK, they are more than just a few small tweaks away from winning Eurovision 2020.

Credit for the piece goes to the BBC graphics department.

Bad Endings

Turns out I was not the only one to look at plotting the ratings of the final series of Game of Thrones. The Economist looked at IMDB ratings, but just prior to the finale on Sunday. They, however, took it a step further and compared Game of Thrones to the final series of other well regarded shows.

All good things…
All good things…

From a design standpoint, I’m not a huge fan of breaking the y-axis at 6. While the data action is all happening at the high range of the scale, that is also the point. Each show is at the top of its class, which makes the precipitous falls of Game of Thrones, Dexter, and House of Cards all the more…wait for it…stark.

I do like the shading behind the line to indicate the final series. That certainly makes it easier to differentiate between the final episodes and those that came before.

But again, I’ll just say, I like how Game of Thrones ended.

Credit for the piece goes to the Economist graphics department.

Abortion by State

In case you did not hear, earlier this week Alabama banned all abortions. And for once, we do not have to add the usual caveat of “except in cases of rape or incest”. In Alabama, even in cases of rape and incest, women will not have the option of having an abortion.

And in Georgia, legislators are debating a bill that will not only strictly limit women’s rights to have an abortion, but will leave them, among other things, liable for criminal charges for travelling out of state to have an abortion.

Consequently, the New York Times created a piece that explores the different abortion bans on a state-by-state basis. It includes several nice graphics including what we increasingly at work called a box map. The map sits above the article and introduces the subject direct from the header that seven states have introduced significant legislation this year. The map highlights those seven states.

We've been calling these box maps. It's growing on me.
We’ve been calling these box maps. It’s growing on me.

The gem, however, is a timeline of sorts that shows when states ban abortion based on how long since a woman’s last period.

There are some crazy shifts leftward in this graphic…
There are some crazy shifts leftward in this graphic…

It does a nice job of segmenting the number of weeks into not trimesters and highlighting the first, which traditionally had been the lower limit for conservative states. It also uses a nice yellow overlay to indicate the traditional limits determined by the Roe v. Wade decision. I may have introduced a nice thin rule to even further segment the first trimester into the first six week period.

We also have a nice calendar-like small multiple series showing states that have introduced but not passed, passed but vetoed, passed, and pending legislation with the intention of completely banning abortion and also completely banning it after six weeks.

Far too many boxes on the right…
Far too many boxes on the right…

This does a nice job of using the coloured boxes to show the states have passed legislation. However, the grey coloured boxes seem a bit disingenuous in that they still represent a topically significant number: states that have introduced legislation. It almost seems as if the grey should be all 50 states, like in the box map, and that these states should be in some different colour. Because the eight or 15 in the 2019 column are a small percentage of all 50 states, but they could—and likely will—have an oversized impact on women’s rights in the year to come.

That said, it is a solid graphic overall. And taken together the piece overall does a nice job of showing just how restrictive these new pieces of legislation truly are. And how geographically limited in scope they are. Notably, some states people might not associate with seemingly draconian laws are found in surprising places: Pennsylvania, Illinois, Maryland, and New York. But that last point would be best illustrated by another box map.

Credit for the piece goes to K.K. Rebecca Lai.

Missing Planets

In science news, we turn to graphics about planets and things. Specifically we are talking about exoplanets, i.e. planets that exist outside our solar system. Keep in mind that we have only been able to detect exoplanets since the 1990s. Prior to then, how rare was our system with all our planets? It could have been very rare. Now we know, probably not so much.

But, in all of that discovery, we are missing entire types of planets. This article published by Forbes does a nice job explaining why. But one of the key types of planets that we have been unable to discover heretofore have been: intermediately distant, giant planets. Think the Jupiters and Saturns of our system. Prior to now we could detect massive Jupiter-like planets orbiting super near to their distant stars. Or, we could detect super massive planets orbiting very far away. The in-betweeners? Not so much.

There's still a pretty wide gap out there…
There’s still a pretty wide gap out there…

The above screenshot does a good job of showing where new detection methods have allowed scientists to begin to fill in the gaps. It shows how there is an enormous gap between what we have discovered and how they have been discovered. And the article does a nice job explaining how the science works in that only now with our longer periods of observation will help resolve certain issues.

From a design standpoint, this isn’t a super complicated graphic. It does rely upon a logarithmic scale, which isn’t common in non-scientific or academic papers. But this graphic comes from that environment, so it makes a lot of sense. The article is full of graphics from third-party sources, but I found this the most informative because of that very gap it highlights and how the new work (the stars) begin to fill it in.

Credit for the screenshotted piece goes to E. L. Rickman et al.

Bar Chart Bombshells

Tuesday night/Wednesday morning, the New York Times broke the story that they had some of President Trump’s tax return information. For decades now, US presidents and candidates for that office have released their tax returns for the public to inspect. Trump has refused, often claiming that they are under audit from the IRS and then adding, and falsely claiming, they cannot be released whilst under audit. Consequently, when the Times publishes an article at the secret world of Trump’s finances, it’s a big news thing.

Unfortunately, the Times only had access to what are essentially summary transcripts of the returns. And only for a period in the mid-1980s through mid-1990s. So we cannot get the granular data and make deeper insights. But what we did get was turned into this bold graphic in the middle of the article.

That's a whole lotta red. And not the good kind for a Republican.
That’s a whole lotta red. And not the good kind for a Republican.

Conceptually, there is not much to say. The bar charts are a solid choice to represent this kind of data. Red makes sense given the connotation of “being in the red”. And the annotations providing quotes from Trump about his finances for the years highlighted provide excellent context.

What the screenshot does not truly capture, however, is the massiveness of the chart in the context of the rest of the article. It’s big, bold, and red. That design choice instead of, say, making it a smaller sidebar-like graphic, goes a long way in hitting home the sheer magnitude of these business losses.

Sometimes it’s not always fancy and shiny charts that garner the most attention. Sometimes an old staple can do wonders.

Credit for the piece goes to Rich Harris and Andrew Rossback.

Trump-won Counties Are Winning

Yesterday we looked at how China and the European Union are planning their tariff/trade war retaliation to target Trump voters. Today let’s take a look at how those voters are doing as this article from Bloom does.

Lots of green, but some noticeably red counties in Florida.
Lots of green, but some noticeably red counties in Florida.

The article is not terribly complicated. We have four choropleth maps at the county level. Two of the maps isolate Trump-won counties and the other two are Clinton-won. For each candidate we have a GDP growth and an employment growth map.

In the Trump-won maps, the Clinton-won counties are white, and vice versa. Naturally, because the Democratic vote is greatest in the large cities, which, especially on the East Coast, are in tiny counties, you see a lot less colour in the Clinton maps.

Not a whole lot to see here…
Not a whole lot to see here…

Design wise, I should point out the obvious that green-to-red maps are not usually ideal. But the designers did a nice job of tweaking these specific colours so that when tested, these burnt oranges and green-blues do provide contrast.

Here they appear more of a yellow to grey
Here they appear more of a yellow to grey

But I am really curious to see this data plotted out in a scatter plot. Of course the big counties in the desert southwest are noticeable. But what about Philadelphia County? Cook County? Kings County? A scatter plot would make them equally tiny dots. Well, hopefully not tiny. But then when you compare GDP growth and employment growth and benchmark them against the US average, we might see some interesting patterns emerge that are otherwise masked behind the hugeness of western counties.

But lastly. And always. Where. Are .Alaska. And. Hawaii? (Of course the hugeness problem is of a different scale in Hawaii. Their county equivalents are larger than states combined.)

Credit for the piece goes to the Bloomberg graphics department.