Labour’s collapse in Copeland in particular is comically bad, but this Friday indulge me in a non-comedic post. Instead, Thursday night we had the results for the by-elections in Stoke and Copeland, two long-held Labour Party constituencies.
Generally speaking in a by-election, the government of the UK can expect to see its vote share decrease if not altogether lose seats. Consequently Labour, as the party of the opposition, should have been expected to hold its two seats and increase its vote share.
Well Labour did win in Stoke, but its majority shrank by half. That’s not so good. And then in Copeland, the bottom sort of fell out. The charts I put together using AP data show what in Copeland was an historic win for the Tories. I could get into the hows and the whys, but you’re best off to go read a British politics site for that. But…something something Corbyn.
Well, so about that whole Michael Flynn furore thing I wrote about yesterday…. Time to add another name to the list of people to be appointed—as I said, that post isn’t confirmed, merely appointed.
But today is Valentine’s Day. So for all you lovebirds out there, here are some graphics showing how rate of marriages has declined in the United States.
It does a real nice job of presenting the overall national view, but then breaking that down into a state-by-state comparison over time, the small multiples shown below.
My critique would be the labelling. Note how the state label appears above the chart, but how when stacked in a row, the label for the state below appears far closer to the chart above. The first few times I looked at this, I saw the label for the chart as being below. And I was therefore curious why Kansas was so different from the rest of the plains state. It just goes to show you how important spacing and layout can be on the page.
Well, we are one day away now. And I’ve been saving this piece from the New York Times for today. They call it simply 2016 in Charts, but parts of it look further back while other parts try to look ahead to new policies. But all of it is well done.
I chose the below set of bar charts depicting deaths by terrorism to show how well the designers paid attention to their content and its placement. Look how the scale for each chart matches up so that the total can fit neatly to the left, along with the totals for the United States, Canada, and the EU. What it goes to show you is best summarised by the author, whom I quote “those 63 [American] deaths, while tragic, are about the same as the number of Americans killed annually by lawn mowers.”
I propose a War on Lawn Mowers.
The rest of the piece goes on to talk about the economy—it’s doing well; healthcare—not perfect, but reasonably well; stock market—also well; proposed tax cuts—good for the already wealthy; proposed spending—bad for public debt; and other things.
The commonality is that the charts work really well for communicating the stories. And it does all through a simple, limited, and consistent palette.
Well, we have arrived at 2017. We all know the big political story in the executive branch. But we also saw elections in the legislative branch. But how different will the 115th Congress look from the 114th? The Wall Street Journal took a look at that in an article.
The article’s graphic does a nice job showing the two different compositions. But if we are truly interested in the growth, we could use a line chart to better showcase the data. So what did I do last night? I made that chart. But as I was playing with the data I saw some numbers that stood out for me. So I compared the proportion of minorities in the original graphic to their proportion of the US national population, per Census Bureau data.
The line charts, broken out into the House vs. the Senate and then into the two parties, do a really good job of showing how the growth is not equally distributed between the two parties. And the reverse of that is that it shows how one party has failed to diversify between the two congresses.
The 115th Congress might be more diverse than ever. But it has a long way to go.
Credit for the original piece goes to the Wall Street Journal graphics department.
Well today we elect the president of the United States. Wait! you say, did we not just do that a few weeks ago?
Not really, no.
In the run up to the election, I and others saw the possibility that this election could result in a gap between the national popular vote and the electoral college vote. And people think that unfair. Consequently I decided to start working on a series of graphics to help explain the system. But before I could finish, the Washington Post published this piece that I think does a strong job. So, I am going to point you there instead.
The United States is not a democracy, but a federal, democratic republic. Though that may smack of wordsmithery, it is an important distinction. We are a democratic republic in that we elect people to represent us, we do not directly vote on matters of government. And then that federal bit. The United States was formed by sovereign states, i.e. the colonies and other independent republics like Texas and (sort of) California. Others were territories belong to sovereign states that we acquired through negotiation, e.g. the Louisiana territory and Florida. In short, the United States is not a unitary state ruled by an all-powerful central government. The central government only has the authority granted to it by the states and territories entering the union.
States are intended to be equal, but the democratic republic bit means the people need to have their say. So the federal House of Representatives gets a set number of seats divided proportionally by population (as determined by the US Census) while the Senate represents all states equally with senators. The House is elected by the people every two years and thus is more in tune with national public sentiment. The Senate serves as the more deliberative body tempering perhaps overly reactionary House legislation. It also serves to represent the interests of the state governments. Initially, you did not even vote for senators. Those were chosen by your state governments, often the state legislature. (I will save that topic for another day.)
The electoral college of 538 members comes from each state’s House delegation and its two senators. And because this is a federal, i.e. state-led, republic, each state determines how to divvy up their votes. Most states do winner-take-all. Two, Maine and Nebraska, allocate them based on who wins the House districts and then an additional two (from the number of senators) to the overall state winner.
That very complicated system was designed to ensure that states with smaller populations are not summarily outvoted and overruled by the largest of states. This initially helped the smaller states in the Northeast like Maine, Rhode Island, Connecticut, and Delaware, but also the slave states like Georgia. In 2016, this means that the states of the Great Plains and Rocky Mountains receive overrepresentation at the expense of the larger states like California, Texas, New York, and even my Pennsylvania.
The graphics from the Washington Post do a great job of showing not just how states today are over- or under-represented, but how that has changed since 1960. That is an important date given the Voting Rights Act that attempted to break down systemic injustices against minorities, particular blacks, in elections.
Is the electoral college “fair”? If this was a unitary republic, no. I doubt anyone would or could argue that point. But the United States is not and was not meant to be a unitary republic. We are a collection of sovereign states that grant power to a federal government. So in that sense, the electoral college is a fair, albeit not perfect, system that seeks to reallocate electoral power from high population states to low population states.
A few weeks ago the Wall Street Journal published a graphic that I thought could use some work. I like line charts, and I think line charts with two or three lines that overlap can be legible. But when I see five in five colours in a small space…well not so much.
So I spent 45 minutes attempting to rework the graphic. Admittedly, I did not have source data, so I simply traced the lines as they appeared in the graphic. I kept the copy and dimensions and tried to work within those limitations. Clearly I am biased, but I think the work is now a little bit clearer. I also added for context the Great Recession, during which credit tightened, ergo more properties would have been likely purchased with cash. It’s all about the context.
And my take:
Credit for the original work goes to the Wall Street Journal graphics department.
But not likely. As this FiveThirtyEight piece explains, steroids are not likely the cause of the increased power exhibited this year by Major League Baseball. The article goes into a bit of detail, but this set of small multiples does a nice job comparing several other factors that could be at play.
What I like about the piece is how each line chart is centred on the year where the factor came into play. And then to the right and left are ten years before and after. Maybe a little bit more could have been done to highlight the differing years—I admit that I missed that at first—but the concept itself is solid.
Credit for the piece goes to the FiveThirtyEight graphics department.
Another day in Philadelphia, another post of Philly data visualisation work. Here we have a piece from 2015 that was updated earlier this spring. It looks at overdose rates in the Philadelphia region, including parts of New Jersey. It does include a map, because most pieces like this typically do. However, what I really find interesting about the piece is its use of small multiple line charts below to take a look at particular counties.
The piece overall is not bad, and the map is actually fairly useful in showing the differences between Jersey and Philadelphia (although why New Jersey is outlined in black and the Philly suburban counties are not I do not know). But I want to take a look at the small multiples of the piece, screenshot below.
You can see an interesting decision in the choice of stacked line charts. Typically one would compare death rates like for like and see whether a county is above, below, or comparable to the state, local, or national averages. But combining the three gives a misleading look at the specific counties and forces the user to mentally disentangle the graphic. I probably would have separated them into three separate lines. And even then, because of the focus on the counties, I would have shifted the colour focus to the specific counties and away from the black lines for the national average. The black is drawing more attention to the US line than to the county line.
And by this title I am not referencing McKinleys, K2s, or Everests. No, the BBC published this piece on the changing average heights of citizens of various countries. This was the graphic they used from the report’s author.
Personally speaking, I do not care for the graphic. It is unclear and puts undue emphasis on the 1914 figure by placing the illustration in the foreground as well as in the darkest colour. I took a thirty-minute stab at re-designing the graphic and have this to offer.
While I admit that it is far from the sexiest graphic, I think it does a better job of showing the growth than decline of national heights by each sex in each of these three select countries. Plus, we have the advantage of not needing to account for the flag emblems. Note how the black bars of Egypt disappear into the black illustration of the person.
Credit for the piece goes to the eLife graphics department.
Another Monday, another week, another post. But this week we will try to get by without any more Brexit coverage. So what better way to cure a hangover than with more booze? So let’s start with some fancy wine.
I meant to post this piece a little while back, but yeah that unmentionable thing occurred. Now we have the time to digest as we sip and not slam our beverage of choice—the Sun’s over the yardarm somewhere I figure. FiveThirtyEight took a look at expensive wines. It compares the pricing at various vintages for France, California, and other wine-producing regions. On the balance, a very smart piece with some great graphics.
But since I had to pick just one, since this isn’t a full-on critique, I opted for this set of small multiples. It compares the price vs. vintage for a number of California red wines. (One of which I had this weekend.)