Here in Philadelphia, I think yesterday was the first day it had not rained in over a week. Not that everyday was a drenching storm, but at least showers passed through along with some downpours and definitely grey skies. But what about my old home, Chicago?
Well, FiveThirtyEight turned to a longer-term look and examined how over the century the amount of rainfall in the upper Midwest has been increasing. We are actually looking at the same places the Post looked at a few days ago. But instead of political maps, we have rainfall maps.
This one in particular is weird.
I get why they have the map, to show the geographic distribution of the rain gauges that collect the data. And those are site specific, not statewide. But did the designer have to choose area?
We know that area is a less than ideal way of allowing users to compare data points. And as I just noted, a choropleth, even at say the county level, is out of the question. But what about little squares? Or circles? Could colour have been used to encode the same data instead of size? And then we would likely have fewer overlapping triangles.
I suppose the argument is that the big triangles make a bigger visual impact. But they do so at the cost of comparable data points across the Midwest. Maybe the designer chose the area of triangles because there were too few gauges across the country. I am not sure, but for me the triangles are not quite on point.
That said, the graphics throughout the rest of the article are quite good, especially the opening scatterplots. They are not the sexiest of charts, but they clearly show a trends towards a wetter climate.
It’s Friday, everybody. We made it. So now go and hit the books this weekend and study up. Thanks to xkcd, we know a little bit more about areas of research. I just am wondering where design is. Or economics.
On Friday Albert Pujols joined the very elite club of baseball players who have managed 3000 hits in their career. Thankfully FiveThirtyEight covered it with a few graphics in an article that pointed out just how hard it is to do. Especially because, and I did not know this, Pujols did it in a not terribly common fashion. (Funny story, I had to explain this past weekend how Randy Johnson was a ridiculous pitcher, in the lots-of-strikeouts-and-also-exploded-a-bird way.)
The piece uses a ternary plot, which we can also just call a triangle chart because it is, you know, in the shape of an equilateral triangle, to look at three components of Pujols’ hit skill.
There are different types of hitters in baseball. The guys who crush home runs all the time, the guys who hit singles all the time, guys who walk a lot. (Technically a walk is not a hit, but they are still getting on base.) There are fancy metrics that can be used to tease out just how much power is in a person’s game, and when you compare that to the batting average and to their walk rate, you can see clusters of players.
These kind of charts can be difficult to read—what does it mean for a player in a certain area of the chart? But what the designer did real well here is label an example of the type of player. Ichiro, called out for being a singles machine, is notable because he just sort-of-retired last week. He also has something like another 1500 hits back in Japan. That guy can hit.
Credit for the piece goes to Neil Paine and Rachael Dottle.
Yesterday was Patriots’ Day, celebrated in Massachusetts and Maine—and in my research for this post, apparently now in Connecticut as of this year and Wisconsin of all places—with the date used as that of the famous Boston Marathon. Since I live in none of those states, I know it only because to my knowledge it is the only day we get morning baseball. As the Red Sox play in the morning with the Marathon runners passing through the neighbourhood mid-game-ish.
But yesterday was some wet weather along the East Coast and whilst the Red Sox game was postponed to May—no longer a morning game—the Marathon went on. One has to wonder, however, if those conditions affected the race—they almost certainly did—because this year’s winning times were the slowest in years. Thankfully FiveThirtyEight captured it in this graphic.
It makes nice use of colour to highlight the origin of the various runners and then highlights yesterday’s two winners: an American woman and a Japanese man. Those two nations have not won in a couple of years.
Overall a solid little piece that makes me sad I have to wait until 2019 for another chance at morning baseball.
Credit for the piece goes to the FiveThirtyEight graphics department.
Let’s start this week with a quick hit on popularity and politics. It ties in nicely with the fact that my local congressman, a Republican, announced on Sunday he would not be seeking re-election in a very competitive district.
This piece in particular comes from the Economist and in terms of form, it is fairly simple. A scatter plot tackling the popularity of groups of people and specific politicians divided by whether the respondent is Republican or Democratic.
The reason I really like this scatter plot are the inclusion of the keys at the four corners. The split between Republicans and Democrats is fairly obvious and nicely coloured. But the little keys really help to clear up any confusion about what is happening as groups of people fall closer to one corner or another. The keys were a small and subtle, but very important design decision.
But what does it all mean? Well, as the headline says, we both rate favourably nurses and working people. Less so Congress and Mitch McConnell.
Credit for the piece goes to the Economist’s graphics team.
Happy Friday, everyone. We made it through to week’s end. And you know what that means. It’s time for a drink. Thanks to one of my best mates for sharing this comic from Saturday Morning Breakfast Cereal.
He shared it with the comment: “I now understand your love of gin.”
Almost a month ago I wrote about how the Pennsylvania Supreme Court was considering a case involving the state’s heavily gerrymandered US congressional districts, which some have called among the worst in the nation. About a week later the Pennsylvania Supreme Court decided that the map is in fact so gerrymandered it violates the Pennsylvania Constitution. It ordered the Republican-controlled legislature to create a new, non-gerrymandered map that would have to be approved by the Democratic governor. I did not write up that then Pennsylvanian Republicans appealed to the US Supreme Court—no graphics for that story. That appeal was rejected by Justice Alito, but with only days to spare the state legislature then created this new map and sent in this new one on Friday.
The problem, according to the governor and outside analysts, is that the map is just as gerrymandered as the previous one. Consequently, yesterday the governor rejected the new map and so now the Pennsylvania Supreme Court, working with outside experts in political redistricting, will create a new congressional map for Pennsylvania. Hopefully before May when the state has its first primaries.
But just how do we know that the new map, despite looking different, was just as gerrymandered. Well, the Washington Post plotted the election margins for districts in 2016 using precinct data versus their proposed 2018 map overlaid atop those same precincts. What did they get? Almost identical results. The districts are no longer Goofy Kicking Donald Duck-esque, but they exhibit the same Republican bias of the previous map.
For the purposes of design, I probably would have dropped the “PA-” labels, as they are redundant since the whole plot examines Pennsylvania congressional districts. I think that, perhaps with a marker, and maybe a line of no-change would go a bit further in more clearly showing how the ultimately rejected map was nearly identical to its previous incarnation.
Credit for the map borders goes to the Pennsylvania state legislature, the version here to the Washington Post Wonkblog. All Wonkblog for the scatterplot.
Off of yesterday’s piece looking at the potential slowdown in British economic growth post-Brexit, I wanted to look at a piece from the Economist exploring the state of the UK’s current trade deals.
I understand what is going on, with the size of the bubbles relating to British exports and the colour to the depth of the free trade deal, i.e. how complex, thorough, and wide-ranging. But the grouping by quadrant?
With trade, geographical proximity is a factor. Things that come from farther cost more because fuel, labour time, &c. One of the advantages the UK currently has is the presence of a massive market on its doorstep with which it already has tariff- and customs-less trade—the European Union.
Consequently, could the graphic somehow incorporate the element of distance? The problem would be how to account for routes, modes of transport, time—how long does a lorry have to queue at the border, for example. Alas, I do not have a great answer.
Regardless of my concepts, this piece does show how the most valuable trade partners already enjoy the deepest and largest trade deals, all through the European Union. And so the UK will need to work to replicate those deals with all of these various countries.
Credit for the piece goes the Economist Data Team.
Baseball season begins next week. For different teams it starts different days, but for the Red Sox at least, pitchers and catchers report to Spring Training on Tuesday. But the Red Sox, along with many other teams throughout baseball, have holes in their roster. Why? Arguably because nearly 100 free agents remain unsigned.
I do not intend to go into the different theories as to why, but this has been a remarkably slow offseason. How do we know? Well using MLB Trade Rumours listing of the top-50 free agents this year, and the signings reported on Baseball Reference, we can look at the upper and middle, or maybe upper-middle, tiers of free agency.
Kind of messy to look at with all the player labels, but we can see here the projected contracts, in both length and total value, along with the contracts players signed, if they have. And for context we can see how those contracts compares to the Qualifying Offer (QO). What’s that? Complicated baseball stuff that is meant to ensure teams that lose stars or highly valuable players are compensated, especially since they might come from smaller market teams that cannot afford superstar prices. The QO is meant to help competitiveness in the sport. How does it do that? Let’s just say complicated baseball stuff. We should also point out that some players, most notably the Yankees’ Masahiro Tanaka, were expected to opt out of their contracts and try the free market. Tanaka did not, which is why his projection was so far off.
So is it true that free agency is or has moved slowly? Consider that approximately 100 free agents remain unsigned as of late Thursday night—please no big signings tomorrow morning—and that of the top 50, 22 of them remain unsigned. And if we take the QO as a proxy for the best players in the game, add in two players who were exempt because baseball stuff, we can say that 8 of the 11 best players remain unsigned. Though, in fairness to ownership, three of those players are reportedly sitting on multi-year offers in the nine-figure range.
But if players are unsigned, does that mean they are competing for lower value contracts? Possibly. If we use MLB Trade Rumours’ projected contracts, because in years past they have proven smart at these things, we can see that for the 28 who have signed, it’s a roughly even split in terms of the number of players who have signed for more or less than their projection. Sometimes however, non-monetary factors come into play. Two notable free agents, Todd Frazier and Addison Reed, both reportedly signed lesser value contracts to play closer to a specified geography, in Frazier’s case the Northeast and in Reed’s the Midwest.
But the telling part in that graphic is not necessarily the vertical movement, i.e. dollars, but the horizontal movement. (Though we should call out the cases of Carlos Santana and Tyler Chatwood, signed by the Phillies and Cubs respectively, who did far better than projected.) Consider that a team might not have a lot of money to spend and so might extend a contract over additional years, offering job security to a player. Or in a bidding war, the length of the contract might be what leads a player to pick one team over another. In those cases we would expect to see more left-to-right movement. So far we have only had one player, Lorenzo Cain, who signed for more years than expected. Most players who have signed for less have also signed for fewer years. Note the cluster of right-to-left, or shorter-than-expected, contracts in the lower tiers versus the small, vertical-only cluster in the same section for those signing greater than projected contracts.
Lastly, are these trends hitting any specific positional type of player? Well maybe. Ignoring the market for catchers because of how small the pool was—though the case of Jonathan Lucroy as the unsigned catcher is fascinating—we can see that the market has really been there for relief pitchers as there are few of the top-50 remaining on the market. Starting pitchers and outfields, while with quite a few still on the market, have generally done better than projected. But infielders lag behind with numerous players unsigned and those that have signed, most have signed for less than projected.
But at the same time, I would fully expect that once these higher level free agents come off the board—while one would think they would certainly be signed, who knows in such a weird offseason as this—the unsigned middle and lower tiers will quickly follow suit.
Of course none of this touches upon age. (Largely because lack of time on my part.) Though, in most cases, getting to free agency in and of itself makes a player older by definition the way baseball’s pre-arbitration and arbitration salary periods work. (Again, more baseball stuff but suffice it to say your first several years you play for peanuts and crackerjacks.)
Hopefully by this afternoon—Friday that is—some of these players will have signed. After all, baseball starts next week. If we are lucky this post will be outdated, at least in terms of the dataset, come Monday. Regardless, it has been a fascinating albeit boring baseball offseason.
Credit for the data goes to MLB Trade Rumours and Baseball Reference.
In the United Kingdom, the month of January has been less than stellar for the National Health Service, the NHS, as surgeries have been cancelled or delayed, patients left waiting in corridors, and a shortage of staff to cope with higher-than-usual demand.
But another problem is the shortage of hospital beds, which compounds problems elsewhere in hospitals and health services. The Guardian did a nice job last week of capturing the state of bed capacity in some hospitals. Overall, the piece uses line charts and scatter plots to tell the story, but this screenshot in particular is a lovely small multiples set that shows how even with surge capacity, the beds in orange, many hospitals are running at near 100% capacity.