Jupiter’s New Moons

Yesterday, space nerds were alerted to the news that 12 new moons have been discovered in orbit of Jupiter. These are much smaller than Jupiter’s moon Ganymede, which is the largest moon in the Solar System and is larger than even Mercury. The point is that there are almost certainly no Ganymede-esque moons orbiting Jupiter that remain undiscovered.

But despite their small size, these moons do have some interesting features, as the article I read in the Guardian pointed out. The most interesting is the orbit of the moons. In general, Jovian moons orbit either prograde, i.e. with the orbit of Jupiter, or retrograde, i.e. against the orbit of Jupiter. The two inner moons discovered are prograde and nine of the other 12 are in an outer orbit of retrograde moons. But Valetudo, the 12th, which orbits in the retrograde group, actually orbits in a prograde fashion. The graphic below from the Carnegie Science Institute does a pretty good job of showing this.

Consider this your collision warning
Consider this your collision warning

Ultimately this means that at some point in the future, Valetudo will slam head-on collision style with another Jovian moon. And reportedly that will be so intense we will be able to see it from Earth. Bangin’. Catch is that it will not likely happen anytime soon.

As for the graphic above, I am of two minds. I generally like the use of colour. The bright green contrasts starkly against the red—though it should be pointed out it would fail a red-green colour blindness test. And then the interesting, but admittedly less interesting prograde and previously discovered Galilean moons are in more muted blues and purples, which puts them further into the background. It works nicely as a complete package.

But should it be on a deep blue background? Lots of space visualisations use black backgrounds, including my work and the work of others. But sometimes work that uses a white or otherwise light background could more clearly show things like orbits. It is difficult to say with certainty because of the lack of a light background for comparison’s sake.

The other thing that gets to me is the viewing angle of the orbits. Clearly we are looking neither dead-on nor from high above. And that makes it a bit more difficult to compare orbits. Of course these might not all be on the same plane because orbits are in three-dimensional space. But if the orbits were all shown from above, it would certainly aid with problems of foreshortening.

All in all, though, I shan’t complain because we have more moons in the Solar System. And who knows how many more smaller moons both Jupiter and Saturn have.

Credit for the piece goes to Roberto Molar Candanosa.

Penalty Shoot Outs

Well, football is not coming home. But the World Cup continues. And should we get another final match tied at the end of extra time, that means penalty shoot outs. Thankfully, the Economist did a nice job detailing the success rates on goal by placement of the ball.

Coin flips
Coin flips

The only thing I am unsure about is whether the dots represent the actual placement or just positioning within the aggregate zone. The colours work well together and the graphic of the goal is not overpowering.

Credit for the piece goes to the Economist Data Team.

The Semifinalists

Today is the semifinal match between England and Croatia. I could have posted this yesterday, but the US Supreme Court selection seemed more important. But today’s post is a simple scatter plot from FiveThirtyEight. It is part of a broader article comparing the four semifinalists of the World Cup. (Spoiler alert, France won its match.)

No drama today, please
No drama today, please

In terms of design, we can contrast this to yesterday’s dot plot about Kavanaugh. There the highlighted dot was orange with a black outline. Here, same deal. But yesterday, the other justices were shown with black dots and an empty dot for retiring Justice Kennedy. Here all the other countries in the World Cup are orange dots.

I wonder, given the orangeness of the other countries, maybe a solid black dot would have worked a little better for the four semifinalists. Or to keep the orange with black outline dots, maybe a lighter orange or grey dots for the other World Cup teams. (I think black would probably be too strong in this case.)

Overall, it shows that today’s match between England and Croatia will be tough. And should England advance, a match against France will be even tougher.

Credit for the piece goes to Bobby Gardiner.

Kavanaugh the Conservative

Last night President Trump nominated Merrick Garland to fill the seat left by Anthony Kennedy. Just kidding. But he is up for a vote in the Senate. Also just kidding.

No, instead, President Trump nominated a very conservative judge for the Supreme Court, Brett Kavanaugh. How conservative? Well, FiveThirtyEight explained in a piece that plotted the judge against his probably peers on the bench, based upon one measure of judicial ideology. And it turns out, spoiler, Kavanaugh sits just to the left of Clarence Thomas. And he sits pretty well to the right.

To the right, to the right, to the right goes the Court
To the right, to the right, to the right goes the Court

The graphic itself is an evolution of a piece from last Friday that looked at what were thought to be the four main candidates on Trump’s shortlist.

A definite lean to the right
A definite lean to the right

The final piece, with only Kavanaugh plotted, removes the other potential candidates. And it functions well, using the brighter orange to draw attention from the black dots of the sitting bench and the open dot of the vacant seat. My slight issue is with the predecessor graphic that shows the four candidates.

I probably would have just left off Barrett as she did not have a score. While I have no doubt that she would score to the right based upon all the reading I have done over the past several days, it feels a bit odd to place her on the graphic at all. Instead, I probably would have used an asterisk or a footnote to say that she did not have a score and thus was not placed.

Credit for the piece goes to Oliver Roeder and Amelia Thomson-DeVeaux.

Still a Loyalist

As most of you know, I am what would have been called a loyalist. That is, I disagree with the premise of the American Revolution. People often mistake that as saying I think Americans should be British. No, although I personally would not mind that. Instead, America would likely have been a lot more like Canada and it would have obtained its independence peacefully through an organic, evolutionary process leading to, likely, some kind of parliamentary democracy.

Every year, somebody digs up articles people have written about why the Revolution was a bad idea. I have seen a lot of them. But I had not seen this Washington Post article that looked at constitutional monarchies. It was published during the whole royal baby buzz back in 2013. It examines why constitutional monarchies are not so bad, and might even be better than presidential republics.

God save the Queen
God save the Queen

The above graphic is far from great. The same goes for the other graphic in the article. I probably would have added more emphasis on the constitutional monarchies as they get overwhelmed by the number of non-constitutional monarchies s in the scatter plot. That could be through a brighter blue or keeping the pink and setting the rest to a light grey. I perhaps would have added a trend line.

Credit for the piece goes to Dylan Matthews.

Going Over (But Actually Under)

Late last week I was explaining to someone in the pub why the World Cup matches are played beyond their 90 minute booking. For those among you that do not know, basically the referees add up all the stoppage time, i.e. when play stops for things like injuries or people dilly dallying, and then tack that on to the end of the match.

But it turns out that after I explained this, FiveThirtyEight published an article exploring just how accurate this stoppage time was compared to the amount of stopped time. Spoiler: not very.

In design terms, the big takeaway was the dataset of recorded minutes of actual play in all the matches theretofore. It captured everything but the activity totals where they broke down stoppage time into categories, e.g. injuries, video review, free kicks, &c. (How those broke out across an average game are a later graphic.)

Through 27 June
Through 27 June

The setup is straightforward: a table organises the data for every match. The little spark chart in the centre of the table is a nice touch that shows how much of the 90 minutes the ball was actually in play. The right side of the table might be a bit too crowded, and I probably would have given a bit more space particularly between the expected and actual stoppage times. On the whole, however, the table does its job in organising the data very well.

Now I just wonder how this would apply to a baseball or American football broadcast…

Credit for the piece goes to David Bunnell.

The London Job Exodus

Brexit is bad for Britain. Here is some proof from an article by Bloomberg that looks at where London-based banking jobs are headed post-Brexit. Spoiler alert, not elsewhere in Britain. The article purports to be more of a tracker in that they will add on data about jobs moving places when news breaks. But I cannot verify that part of the piece.

What I can verify is a sankey diagram. Underused, but still one of my favourite visualisation forms. This one explores where companies’ London-based banking jobs are moving. Right now, it clearly says Frankfurt, Germany is winning.

Look at all those job…
Look at all those job…

As sankeys go, this one is pretty straightforward. Aesthetically I wonder about the colour choice. I get the blues and that the banks are coloured by their ultimate destination. But why the gradient?

But conceptually the big question would be what about London? I probably would have kept London in the destination set. While many jobs are likely to leave Britain, some will in fact stay, and those lines will need to go somewhere in this graphic.

The piece also makes nice use of some small multiple maps and tables. All in all, this is a really solid piece. It tells a great—well, not great as in good news—story and does it primarily through visuals.

Credit for the piece goes to Gavin Finch, Hayley Warren and Tim Coulter.

The Evolution of the S&P 500

I found myself doing a bit of summer cleaning yesterday and I stumbled upon a few graphics of interest. This one comes from a September 2016 Wall Street Journal article about the changes in the S&P 500, a composite index of American stocks, some of the 500 largest.

In terms of the page design, if it were not for that giant 1/6 page advert in the lower right corner, this graphic could potentially dominate the visual page.  The bulk of it sits above the page’s fold and the only other competing element is a headshot to the upper-right. Regardless, it was clearly enough to grab my attention as I was going through some papers.

The overall page
The overall page

As for the graphic itself, I probably would have some done things differently.

Trees?
Trees?

To start, are these actual tree maps? Or are they things attempting to look like tree maps? It is difficult to tell. In an actual tree map, the rectangles are not just arranged by convenience, as they appear to be here. Instead, they are in descending—or perhaps occasionally ascending—area, within groupings.

The groupings would have been particularly powerful here.  Imagine instead of disparate blue boxes for industrials and utilities in the latter two years that they were combined into a single box. In 2001, that box may have been larger than the orange financials. Then by 2016, you would have seen those boxes switch places—in both years well behind the green boxes of 2001 debuts. If instead the goal was to show the percentages, as it might be given each percentage is labelled, a straight bar chart would have sufficed.

I am not always a fan of the circle for sizes along the bottom. But the bigger problem I have here is the alignment of the labelling and the pseudo-tree maps. One of my first questions was “how big are these years?”. However, that was one of the last points displayed, and it is separated from the tree maps from the listing of the largest company in the index from that year. I would have kept the total market cap closer to the trees, and perhaps used the whole length of line beneath the trees and instead pushed the table labels somewhere between the rather large gap from 1976 and 2001.

Credit for the piece goes to the Wall Street Journal graphics department.

For Whom to Root

The World Cup continues. Well for a few teams. Some have already been eliminated from the Round of 16. But for those Americans rooting for Team America, well, if you have not yet figured it out, you got knocked out well before the World Cup even started by…Panama. And so you are stuck in the question of who’s next? Thankfully FiveThirtyEight, in addition to their fantastic live probabilities that we looked at the other day, put together a little quiz to help you find your new team.

You answer seven questions and you are told your new allegiance. Questions like this:

How would you answer?
How would you answer?

Naturally I took the quiz and discovered that in addition to England, I am cheering for…

Goal? Make that skål!
Goal? Make that skål!

Yep. Fantastic since I was just there in December and happened to love Stockholm. But what I love about this piece is how it uses data to create the newfound bond I have with Sweden. Often times you take a quiz and are given an answer without any sense of why the answer was correct. Here, FiveThirtyEight plots the seven different variables used to create your newfound personality and then shows you how you scored.

Right in the middle there
Right in the middle there

It’s Friday, it’s the World Cup. Have a great weekend. And in addition to England on Sunday, I’ll now be cheering for Sweden against Germany on Saturday.

Credit for the piece goes to Michael Caley, Rachael Dottle, Geoff Foster, Gus Wezerek, Daniel Levitt, Emily Scherer, and Jorge Lawerta.

World Cup Match Probabilities

The World Cup has had some impressive matches and some stunners. (And the two are not mutually exclusive.) But if you are like me and have to work during most of the broadcasts, how can you follow along? Well thankfully FiveThirtyEight put together a nice statistical model that provides the probability of a team winning—or drawing—in real time.

Looking pretty good for Portugal this morning…
Looking pretty good for Portugal this morning…

The design is fairly simple: a small table with the score and probability followed by a chart drawn as the match goes on. (Clearly I took this image at the half.)

I included a snippet of the table below to show the other work the FiveThirtyEight team put out there. You can explore the standings, the screenshot above, as well as the matches and then the brackets later in the competition.

The table makes nice use of the heat map approach to show is likely to make easy of the different stages of the competition. Like I said the other day, they are high on Brazil, because Brazil. But a little lower on Germany. But never count Germany out.

Shouldn't Iran be in the top slot?
Shouldn’t Iran be in the top slot?

The only unclear thing to me in the table? The sorting mechanism. In Group B, at least whilst the Portugal match is ongoing, should probably have Iran at the top. After all, as of writing, it is the only team in the group to have won a match. The only thing I can guess is that it has to do with an overall likelihood to advance to the next round. I highly doubt that Iran will defeat either Spain or Portugal. But as with many knockout-style championships, anything can happen in a single match sample size.

Credit for the piece goes to Jay Boice, Rachael Dottle,Andrei Scheinkman, Gus Wezerek, and Julia Wolfe.