Arms Sales for Saudi Arabia and Head Removals for Journalists

Yeah, guess where I am going with that title…

If you have been living under a rock, Saudi Arabia barbarically murdered/assassinated a Washington Post journalist in the Saudi consulate in Istanbul, Turkey about three weeks ago. The journalist, Jamal Khashoggi, was a Saudi citizen and US resident living around Washington from where he reported on the new Saudi government under Mohammed bin Salman (MBS).

There is a lot to unpack in the story, but the key points are that Saudi Arabia has, for weeks, disputed the idea that his fingers were severed, then beheaded, body dismembered, and corpse disposed of within their consulate in Istanbul. Only yesterday did they begrudgingly admit that it was a “rogue” operation that involved some of the closest advisors/bodyguards to MBS. (We will look at that later.) How do we know all this? Basically, every time Saudi Arabia denies something, the Turks let leak evidence proving them wrong.

So while the story will continue to develop, what is the potential cost for Saudi Arabia? Well, according to President Trump, not arms sales. Although this morning Germany announced it was temporarily halting all exports to the Saudi kingdom. But the two of the largest providers of weapons to Saudi Arabia are the United States and the United Kingdom. And that is how we get to today’s chart. The question is what, if any, action will these two countries take against Saudi Arabia?

Will these line trend down anytime soon?
Will these line trend down anytime soon?

It’s a line chart from the Washington Post. There really isn’t much to say in its design. However, what I found interesting is the unit of measure. We might expect dollars, pounds, or euros, but instead we get TIV, or trend indicator values. It’s a unit devised by the data provider to allow a common measurement, presumably so that we can do just this: compare two different countries’ arms sales.

Credit for the piece goes to the Washington Post graphics department.

Running Up the Debt

I was reading the paper this morning and stumbled across this graphic in a New York Times article that focused on the increasing importance of debt payments.

Those interest payment lines are headed in the wrong direction.
Those interest payment lines are headed in the wrong direction.

The story is incredibly important and goes to show why the tax cuts passed by the administration are fiscally reckless. But the graphic is really smart too. After all, it is designed to work in a single colour.

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

Kavanaugh’s Fading in Competitive House Seats

Another day, another allegation of sexual misconduct against Brett Kavanaugh. We are presently at two and are expecting a third tomorrow. But the question is, will these allegations sink his nomination? Probably not. But could that confirmation hurt Republicans in the mid-terms? Possibly.

The New York Times posted an article about how Kavanaugh’s support in battleground congressional districts is slipping. To be fair, the chart is simple, but it does its job. And usually that’s all we want a chart to do.

Just a few points can make all the difference…
Just a few points can make all the difference…

Me the person interested in politics, however, will take this a bit further. If Kavanaugh’s support continues to fade—this survey was taken before these new allegations were public—will Republicans supporting the nomination face a backlash from their constituents?

Credit for the piece goes to Nate Cohn.

Our Lives Are a Mixed Bag

Last Thursday the Economist published an article looking at quality of life across the world. The data came from the Social Progress Imperative and examined quality of life, excluding economic performance. And as the article details, the results were mixed at best.

But, hey, the chart was really nice. We have a small multiple set looking at the overall index across all regions across the world and then the US, China, and India in particular.

Unfortunately the US is heading in the wrong direction…
Unfortunately the US is heading in the wrong direction…

I think this chart hits almost all the right notes. My only qualm would be the component indices being placed alongside the overall index. I wonder if breaking the whole thing out by component would work. As it is, it generally works well, I am just curious because there is the one issue of the United States where our well-being line falls beneath that of the overall index. But then again, the story is the overall index.

Credit for the piece goes to the Economist Data Team.

iPhone Screen Size

Your humble author has returned. And on my trip up to Boston I took plenty of photos with my Nexus 5X, a Google-designed smartphone. That is correct, this designer does not use an iPhone. But I am aware of the latest things coming out of Apple—after all this is being typed up on a Mac—and so the larger screen size caught my attention.

The Economist put together a piece looking at the screen sizes of the iPhone models over the years and then used that to project into the future the likely sizes of the phone’s display.

Bigger, and bigger, and bigger, and…
Bigger, and bigger, and bigger, and…

Now the article hints at what I would be particularly interested in: the screen sizes of comparable Android models. How have they changed over the years? I still cling to my smaller screen size mobile as I am not a fan of the phablet.

The chart itself is simple and well done, plotting the models without any fuss. But the most important part is the benchmark line of the iPad mini’s screen size. And the user can clearly see the forecast merger of the sizes.

Credit for the piece goes to the Economist Data Team.

Europe’s Far-right Parties

Yesterday we looked at the rise of the far-right in Sweden based on their electoral gains in this past weekend’s election. Today, the Economist has a piece detailing their strength throughout Europe and they claim that this type of nationalist party may have peaked.

The tile map, though
The tile map, though

The graphic fascinates me because it appears to be a twist on the box or tile map, which is often used to eliminate or reduce the discrepancies in geographic size so that countries, states, or whatevers, can be examined more easily and more equitably.

I am guessing that the ultimate sizes, which appear to be one to four units, are determined by population size. The biggest hitters of Germany, the UK, France, and Spain are all four squares or boxes whereas the smaller states like Malta are just one. (But again, hey, we can all see Malta this time.)

I think this kind of abstraction will grow on me over time. It is a clever solution to the age-old problem of how do we show important data in both Germany and Malta on a map when Malta is so geographically small it probably renders as only a few pixels.

On the other hand, I am not loving the line chart to the right. I understand what it is doing and why. And even conceptually it works well to show the peaks of the parties. However, there are just a few too many lines and we get into the spaghettification of the chart. I might have labelled a far fewer number and let most sit at some neutral grey. Or, space permitting, a series of small multiples could have been used.

Credit for the piece goes to the Economist Data Team.

Which of These Countries Does Not Belong

For those of you reading from the States, I hope you all enjoyed your holiday. And for my UK readers, I hope you all enjoyed your summer bank holiday last weekend. So now to the good and uplifting kind of news.

Something is clearly not right here.
Something is clearly not right here.

Indeed, a chart about deaths from firearms from the Economist. From a graphical standpoint, we all know how much I loathe stacked bar charts and this shows why. It is difficult for the user to isolate and compare the profiles of certain types of firearm violence against each other. Clearly there are countries where suicide by gun is more prevalent than murder, but most on this list are more murder happy.

And then the line chart that is cleverly spaced within the overall graphic, well, it falls apart. There are too many lines highlighted. Instead, I would have separated these out into a separate chart, made larger, so that the reader can more easily discern which series belongs to which country. Or I would have gone with a set of small multiples isolating those nine countries.

I am also unclear on why certain countries were highlighted in the line chart. Did they all need to be highlighted? Why, for example, is Trinidad & Tobago. It is not mentioned in the article, nor is it in the stacked bar chart.

But the biggest problem I have is with the data itself. But, every one of the countries on that list is among the developing countries or the least developed countries. Except one. And that, of course, is the United States.

Credit for the piece goes to the Economist Data Team.

The Rise of Online Dating

This past weekend I cited this article from the Economist that looked at the rise of online dating as a way of couples meeting. There was some debate about which channels of interaction/attraction still worked or were prevalent. And it turns out that, in general, the online world is the world today.

Meeting your partner in primary/secondary school has clearly gone out of fashion since the 40s.
Meeting your partner in primary/secondary school has clearly gone out of fashion since the 40s.

My problem with the graphic is that it is a bit too spaghettified for my liking. Too many lines, too many colours, and they are all overlapping. I probably would have tried a few different tricks. One, small multiples. The drawback to that method is that while it allows you to clearly analyse one particular series, you lose the overlap that might be of some interest to readers.

Second, maybe don’t highlight every single channel? Again, you could lose some audience interest, but it would allow the reader to more clearly see the online trend, especially in the heterosexual couple section of the data. You could accomplish this by either greying out uninteresting lines or removing them entirely, like that primary/secondary school series.

Third, I would try a bit more consistent labelling. Maybe increase the overall height of the graphic to give some more vertical space to try and label each series to the right or left of the graphic. You might need a line here or there to connect the series to its label, but that is already happening in this chart.

However, I do like how the designers kept the y-axis scale the same for both charts. It allows you to clearly see how much of an impact the online dating world has been for homosexual couples. My back-of-the-envelope calculations would say that is more than three times as successful than it is for heterosexual couples. But that insight would be lost if both charts were plotted on separate axis scales.

But lastly, note how the dataset only goes as far as 2010. I can only imagine how these charts would look if the data continued through 2018.

Credit for the piece goes to the Economist Data Team.

Most Liveable Cities Ranking

There is nothing super sophisticated in these charts, but I love them all the same. The Economist Intelligence Unit (EIU) published its rankings of the world’s most liveable cities and this year Vienna knocked off Melbourne for top spot. But what about the rest of the list?

Thankfully the Economist, a related company, put together a graphic highlighting important or noteworthy cities among the entire dataset. It is a wonderful tangle of light grey lines that have select cities highlighted in thicker strokes and brighter colours. Labelling each city would be too tricky at this scale.

I'm okay with the occasional rainbow spaghetti

I’m okay with the occasional rainbow spaghettiThat said about labelling each city, a few years back I worked on a similar top cities in a category datagraphic for Euromonitor International. We took a similar approach and coloured lines by region, but we presented the entire dataset and then complemented it by some additional charts to the side.

These were always fun pieces on which to work
These were always fun pieces on which to work

What is really nice about the Economist piece, however, is that they opted not to show the whole dataset. This could be a business decision, if people want to find where a particular city they could be persuaded to either outright subscribe or otherwise provide contact information in exchange for access to the data. Either way, the result is a piece that has space to provide textual context about why cities rose or fell over the years.

I think I like these types of pieces because there is so much to glean from getting lost in the chart. And this one from the Economist does not disappoint.

Credit for the liveability piece goes to the Economist Data Team.

Credit for the destinations piece goes to me.