Axis Lines in Charts

The British election campaign is wrapping up as it heads towards the general election on Thursday. I haven’t covered it much here, but this piece from the BBC has been at the back of my mind. And not so much for the content, but strictly the design.

In terms of content, the article stems from a question asked in a debate about income levels and where they fall relative to the rest of the population. A man rejected a Labour party proposal for an increase in taxes on those earning more than £80,000 per annum, saying that as someone who earned more than that amount he was “not even in the top 5%, not even the top 50”.

The BBC looked at the data and found that actually the man was certainly within the top 50% and likely in the top 5%, as they earn more than £75,300 per annum. Here in the States, many Americans cannot place their incomes within the actual spreads of income. The income gap here is severe and growing.  But, I want to look at the charts the BBC made to illustrate its points.

The most important is this line chart, which shows the income level and how it fits among the percentages of the population.

Are things lining up? It's tough to say.
Are things lining up? It’s tough to say.

I am often in favour of minimal axis lines and labelling. Too many labels and explicit data points begin to subtract from the visual representation or comparison of the data. If you need to be able to reference a specific data point for a specific point on the curve, you need a table, not a chart.

However, there is utility in having some guideposts as to what income levels fit into what ranges. And so I am left to wonder, why not add some axis lines. Here I took the original graphic file and drew some grey lines.

Better…
Better…

Of course, I prefer the dotted or dashed line approach. The difference in line style provides some additional contrast to the plotted series. And in this case, where the series is a thin but coloured line, the interruptions in the solidity of the axis lines makes it easier to distinguish them from the data.

Better still.
Better still.

But the article also has another chart, a bar chart, that looks at average weekly incomes across different regions of the United Kingdom. (Not surprisingly, London has the highest average.) Like the line chart, this bar chart does not use any axis labels. But what makes this one even more difficult is that the solid black line that we can use in the line charts above to plot out the maximum for 180,000 is not there. Instead we simply have a string of numbers at the bottom for which we need to guess where they fall.

Here we don't even a solid line to take us out to 700.
Here we don’t even a solid line to take us out to 700.

If we assume that the 700 value is at the centre of the text, we can draw some dotted grey lines atop the existing graphic. And now quite clearly we can get a better sense of which regions fall in which ranges of income.

We could have also tried the solid line approach.
We could have also tried the solid line approach.

But we still have this mess of black digits at the bottom of the graphic. And after 50, the numbers begin to run into each other. It is implied that we are looking at increments of 50, but a little more spacing would have helped. Or, we could simply keep the values at the hundreds and, if necessary, not label the lines at the 50s. Like so.

Much easier to read
Much easier to read

The last bit I would redo in the bar chart is the order of the regions. Unless there is some particular reason for ordering these regions as they are—you could partly argue they are from north to south, but then Scotland would be at the top of the list—they appear an arbitrary lot. I would have sorted them maybe from greatest to least or vice versa. But that bit was outside my ability to do this morning.

So in short, while you don’t want to overcrowd a chart with axis lines and labelling, you still need a few to make it easier for the user to make those visual comparisons.

Credit for the original pieces goes to the BBC graphics department.

Food Flows Connect Counties

For my American audience, this week is Thanksgiving. That day when we give thanks for Native Americans giving European settlers their land for small pox ridden blankets. And trinkets. Don’t forget the trinkets. But we largely forget about the history and focus on three things: family, food, and American football. Not necessarily in that order.

But this week I am largely going to want to focus on the food.

Today we can look at a graphic coming from a team of researchers at the University of Illinois who examined the flows of food across the United States, down to the county level. It helped produce this map that shows the linkages between counties.

Oh look at that Mississippi River trail
Oh look at that Mississippi River trail

To be sure, the piece uses some line charts and other maps to showcase the links, but the star is really this map. But aside from its lack of Alaska and Hawaii, I think it suffers from one key design choice: leaving the county borders black.

The black lines, while thin, compete with the faint blue lines that show the numerically small links between counties. Larger trade flows, such as those within California, are clearly depicted with thicker strokes that contrast with the background political boundaries of the counties. But the light blue lines recede into the background beneath the borders.

I wonder if a map of solid, light grey fills and white county borders would have helped showcase the blue lines and thus trade flows a little bit better. After all, the problem is especially  noticeable in the eastern half of the United States where we have much geographically smaller counties.

Hat tip to friend and former colleague Michael Schaefer for sharing the article in question.

Credit for the piece goes to Megan Konar et al.

From Order to Chaos?

A few weeks ago we said farewell to John Bercow as Speaker of the House (UK). Whilst I covered the election for the new speaker, I missed the opportunity to post this piece from the BBC. It looked at Bercow’s time in office from a data perspective.

The piece did not look at him per se, but that era for the House of Commons. The graphic below was a look at what constituted debates in the chamber using words in speeches as a proxy. Shockingly, Brexit has consumed the House over the last few years.

At least climate change has also ticked upwards?
At least climate change has also ticked upwards?

I love the graphic, as it uses small multiples and fixes the axes for each row and column. It is clean, clear, and concise—just what a graphic should be.

And the rest of the piece makes smart use of graphical forms. Mostly. Smart line charts with background shading, some bar charts, and the only questionable one is where it uses emoji handclaps to represent instances of people clapping the chamber—not traditionally a thing that  happens.

Content wise it also nailed a few important things, chiefly Bercow’s penchant for big words. The piece did not, however, cover his amazing sense of sartorial style vis-a-vis neckties.

Overall a solid piece with which to begin the weekend.

Credit for the piece goes to Ed Lowther & Will Dahlgreen.

Casual Fails?

In a recent Washington Post piece, I came across a graphic style that I am not sure I can embrace. The article looked at the political trifecta at state levels, i.e. single political party control over the government (executive, lower legislative chamber, and upper legislative chamber). As a side note, I do like how they excluded Nebraska because of its unicameral legislature. It’s also theoretically non-partisan (though everybody knows who belongs to which party, so you could argue it’s as partisan as any other legislature).

At the outset, the piece uses a really nice stacked bar chart. It shows how control over the levers of state government have ebbed and flowed.

You can pretty easily spot the recent political eras by the big shifts in power.
You can pretty easily spot the recent political eras by the big shifts in power.

It also uses little black lines with almost cartoonish arrowheads to point to particular years. The annotations are themselves important to the context—pointing out the various swing years. But from an aesthetic standpoint, I have to wonder if the casualness of the marks detracts from the seriousness of the content.

Sometimes the whimsical works. Pie charts about pizza pies or pie toppings can be whimsical. A graphic about political control over government is a different subject matter. Bloomberg used to tackle annotations with a subtler and more serious, but still rounded curve type of approach. Notably, however, Bloomberg at that time went for an against the grain, design forward, stoic business serious second approach.

Then we get to a choropleth map. It shows the current state of control for each state.

X marks the spot?

X marks the spot?However, here the indicator for recent party switches is a set of x’s. These have the same casual approach as the arrows above. But in this case, a careful examination of the x’s indicates they are not unique, like a person drawing a curve with a pen tool. Instead these come from a pre-determined set as the x’s share the exact same shape, stroke lengths and directions.

In years past we probably would have seen the indicator represented by an outline of the state border or a pattern cross-hatching. After all, with the purple being lighter than the blue, the x’s appear more clearly against purple states than blue. I have to admit I did not see New Jersey at first.

Of course, in an ideal world, a box map would probably be clearer still. But the curious part is that the very next map does a great job of focusing the user’s attention on the datapoint that matters: states set for potential changes next November.

Pennsylvania is among the states…
Pennsylvania is among the states…

Here the states of little interest are greyed out. The designers use colour to display the current status of the potential trifecta states. And so I am left curious why the designers did not choose to take a similar approach with the remaining graphics in the piece.

Overall, I should say the piece is strong. The graphics generally work very well. My quibbles are with the aesthetic stylings, which seem out of place for a straight news article. Something like this could work for an opinion piece or for a different subject matter. But for politics it just struck a loud dissonant chord when I first read the piece.

Credit for the piece goes to Kate Rabinowitz and Ashlyn Still.

The Shifting Suburbs

Last we looked at the revenge of the flyover states, the idea that smaller cities in swing states are trending Republican and defeating the growing Democratic majority in big cities. This week I want to take a look at something a few weeks back, a piece from CityLab about the elections in Virginia, Kentucky, and Mississippi.

There’s nothing radical in this piece. Instead, it’s some solid uses of line charts and bar charts (though I still don’t generally love them stacked). The big flashy graphic was this, a map of Virginia’s state legislative districts, but mapped not by party but by population density.

Democrats now control a majority of these seats.
Democrats now control a majority of these seats.

It classified districts by how how urban, suburban, or rural (or parts thereof) each district was. Of course the premise of the article is that the suburbs are becoming increasingly Democratic and rural areas increasingly Republican.

But it all goes to show that 2020 is going to be a very polarised year.

Credit for the piece goes to David Montgomery.

I Have an App for That Too

Well, everyone, we made it to Friday. So let’s all reflect on how many things we did on our mobile phones this week. xkcd did. And it’s fairly accurate. Though personally, I would only add that I did not quite use my mobile for a TV remote. Unless you count Chromecasting. In that case I did that too.

What about boarding passes?
What about boarding passes?

If I have to offer a critique, it’s that it makes smart use of a stacked bar chart. I normally do not care for them, but it works well if you are only stacking two different series in opposition to each other.

Credit for the piece goes to Randall Munroe.

How Worldly Is the World Series?

The World Series began Tuesday night. But, as many people reading this blog will know, baseball is not exactly a global sport. But is it really? CityLab looked at the origin of Major League Baseball players and it turns out that almost 30% of the players today are from outside the United States. They have a number of charts and graphics that explore the places of birth of ball players. But one of the things I learned is just how many players hail from the Dominican Republic—since 2000, 12% of all players.

There are quite a few players from countries around the Caribbean.
There are quite a few players from countries around the Caribbean.

The choropleth here is an interesting choice. It’s a default choice, so I understand it. But when so many countries that are being highlighted are small islands in the Caribbean, a geographically accurate map might not be the ideal choice. Really, this map highlights from just how few countries MLB ball players originate.

Fortunately the other graphics work really well. We get bar charts about which cities provide MLB rosters. But the one I really enjoy is where they account for the overall size of cities and see which cities, for every 100,000 people, provide the most ballplayers.

One of the other things I want to pick on, however, is the inclusion of Puerto Rico. In the dataset, the designers included it as a foreign country. When, you know, it’s part of the United States.

Credit for the piece goes to David H. Montgomery.

Canadian Election Results

Yesterday Canada went to the polls for the 43rd time. Their prime minister, Justin Trudeau, has had a bad run of it the last year or so. He’s had some frivolous scandals with wearing questionable fashion choices to some more serious scandals about how he chose to colour his face in his youth to arguably the most serious scandal where an investigation concluded improperly attempted to influence a criminal investigation for political gain. (Sound familiar, American readers?) Consequently, there was some chatter about whether he would lose to the Conservatives.

But nope, Trudeau held on.

So this morning I charted some of the results. It was a bad night for Trudeau, but not nearly as bad as it could have been. He remains in power, albeit head of a minority government.

That's a steep drop in seats, but it could have been worse
That’s a steep drop in seats, but it could have been worse

Credit for the piece goes to me.

Prorogation of Parliament

If you’re among my British/European audience, you are probably well aware Boris Johnson has prorogued, or suspended, Parliament. He and cabinet ministers stated it was a normal, average-length prorogation to prepare for a Queen’s Speech. (The Queen’s Speech is the formal opening of a new session of Parliament that sets out a new legislative agenda and formally closes/kills any unpassed legislation from the old session.) Except that in documents revealed in a Scottish court case, we now know that the real reason was to shut down Parliament to prevent it from interfering in Boris’ plans for a No Deal Brexit. And just this morning the Scottish High Court did indeed rule that the prorogation is illegal. The case now moves to the UK Supreme Court.

But I want to focus on the other claim, that this is a prorogation of average length. Thankfully instead of having to do a week’s hard slog of data, the House of Lords Library posted the data for me. At least since 1900, and that works well enough for me. And so here we go.

Back to the 1930s?
Back to the 1930s?

So yeah, this is not an average prorogument. If you look at only proroguments that do not precede a general election—you need time for the campaigning and then hosting the actual election in those cases—this is the longest prorogument since 1930. (Also, a Parliament does not necessarily need to be prorogued before it is dissolved before an election. And that happened quite often in the 1960s, 70s, and 80s.)

And as I point out in the graphic, Parliament was prorogued during the depths of World War II to start new legislative sessions. But in those cases, Parliament opened the very next day, during a time of national crisis. One could certainly make the argument that Brexit is a national crisis. So wherefore the extraordinarily long prorogument? Well, quite simply, Brexit.

Credit for the piece goes to me.

Greenland, the 51st State?

If you haven’t heard, President Trump wants to buy Greenland from Denmark. So is Greenland going to beat Puerto Rico to joining the Union as the 51st state?

No.

Not even close.

It would be the smallest state in terms of population, but also one of the smallest US territories. But in terms of area, Greenland dwarfs every state but Alaska. Though it still beats Alaska by almost 50% of its land area.

It's like a super-charged Seward's Folly
It’s like a super-charged Seward’s Folly

I had hoped to include some more economic data, but that will have to wait for a different post. Acquiring the population data was actually the most difficult—the US Census Bureau does not actually have easy to access data on the populations of US territories not called Puerto Rico.

This piece is mine.