A Wetter Midwest

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.

Water water everywhere
Water water everywhere

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.

Credit for the piece goes to Ella Koeze.

Turning the Midwest Red

Continuing with election-y stuff, I want to share a fascinating map from the Washington Post. The article came out last week, and it is actually incredibly light in terms of data visualisation. By my count, there were only two maps. The article’s focus is on interviews with Trump voters in 2016 and how their opinions of the president have changed over the last year or so. If you want to read it, and you should as it is very well written, I will warn you that it is long. But, to the map.

I may have used an even lighter shade for 2012 counties…
I may have used an even lighter shade for 2012 counties…

What I loved about this map is how it flips the usual narrative a bit on its head. We talk about how much a candidate won a county in 2016, or even how much the vote shifted in 2016. And anecdotally we talk about “ancestral Democrats” flipping to Trump. But this map actually tries to chart that. It reveals the last time a county actually voted for a Republican presidential candidate—the darker the red, the further back in time one has to go.

Counties that vote Democratic are white, because why do we need them for this examination. Omitting them was a great design decision. Much of the country, as we know or can intuit, voted Republican in 2012 for Mitt Romney. But what about before then? You can see how the upper Midwest, along the Mississippi River, was a stronghold for Democrats with some counties going as far back as the 1980s or earlier. And then in 2016 they all flipped and that flipping was most significant there—of some additional interest to me are the counties in Maine, the Pacific Northwest, and along Lake Erie near Cleveland.

In short, this was just a brilliantly done map. And it sets the tone for the rest of the article, which is interviews with residents of those counties called out on the map.

Credit for the piece goes to Andrew Braford, Jake Crump, Jason Bernert and Matthew Callahan.

Pennsylvania Primary Night

Surprise, surprise. This morning we just take a quick little peak at some of the data visualisation from the Pennsylvania primary races yesterday. Nothing is terribly revolutionary, just well done from the Washington Post, Politico, and the New York Times.

But let’s start with my district, which was super exciting.

The only thing to write home about is how the Republican incumbent dropped out at the last moment and was replaced by this guy…
The only thing to write home about is how the Republican incumbent dropped out at the last moment and was replaced by this guy…

Moving on.

Each of the three I chose to highlight did a good job. The Post was very straightforward and presented each office with a toggle to separate the two parties. Usually, however, this was not terribly interesting because races like the Pennsylvania governor had one incumbent running unopposed.

Mango is represented by what colour?
Mango is represented by what colour?

But Politico was able to hand it differently and simply presented the Democratic race above the Republican and simply noted that the sitting governor ran unopposed. This differs from the Post, where it was not immediately clear that Tom Wolf, the governor, was running unopposed and had already won.

Clean and simple design. No non-sense here.
Clean and simple design. No non-sense here.

The Times handled it similarly and simultaneously displayed both parties, but kept Wolf’s race simple. The neat feature, however, was the display of select counties beneath the choropleth. This could be super helpful in the midterms in several months when key races will hinge upon particular counties.

The Republican primary for the PA governorship has been ugly
The Republican primary for the PA governorship has been ugly

But where the Times really shines is the race for Pennsylvania’s lieutenant governor. Fun fact, in Pennsylvania the governor and lieutenant governor do not run as a ticket and are voted for separately. This year’s Democratic incumbent, Mike Stack, does not get on with the governor and had a few little scandals to his name, prompting several Democrats to run against him. And the Times’ piece shows the two parties result, side-by-side.

Pennsylvania's oddest race this time 'round
Pennsylvania’s oddest race this time ’round

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

Credit for Politico’s piece goes to Politico’s graphics department.

Credit for the Times’ piece goes to Sarah Almukhtar, Wilson Andrews, Matthew Bloch, Jeremy Bowers, Tom Giratikanon, Jasmine C. Lee and Paul Murray, and Maggie Astor.

Kilauea Eruption

As a kid, volcanoes fascinated me. The idea that the molten core of the Earth can bubble its way up to and then erupt from the cold crusty surface of the planet still fascinates me. Of course, volcanoes can also have drastic impacts on people, both at the grand scale of impacting global climate to the smaller and more personal scale of someone’s home destroyed by a lava flow.

And unfortunately for residents of Hawai’i that personal destruction is unfolding across a development called Leilani Estates. The Washington Post has a nice piece detailing the geography of the area and showing how quickly things can change.

Earth is powerful
Earth is powerful

The article uses the photo above to illustrate the distance the lava flow travelled in only a few days. It also shows how precariously sited the homes are.

Only because I am so fascinated by these kinds of stories, I hope the Post continues to expand its content with pieces like this exploring the eruption and those of other volcanoes in the area.

Credit for the piece goes to Laris Karklis and Lauren Tierney.

Germany

Last week Angela Merkel, the German chancellor, visited President Trump in Washington. This post comes from the Economist and, while not specifically about that trip, describes Germany in a few different metrics. Back in the day it would be what I called a country-specific datagraphic. That is, it shows metrics not necessarily connected to each other, but all centred around a country. In theory, the framework can then be used to examine a number of different countries.

The thin red line…
The thin red line…

That sort of works here, except the choropleth is for the Alternative for Germany political party. That only real works as a metric in, you know, Germany.

Overall, I like the piece. The layout works well, but Germany is fortunate in that the geographic shape works here. Try it with Russia and good luck.

First let us dispense with the easy criticism: do we need the box map in the lower right corner to show where in the world Germany is? For Americans, almost certainly yes. But even if you cannot identify where Germany is, I am not certain its location in Europe is terribly important for the data being presented.

But the pie charts. I really wish they had not done that. Despite my well-known hatred of pie charts, they do work in a very few and specific instances. If you want to show a reader 1/4 of something, i.e. a simple fraction, a pie chart works. You could stretch and argue that is the case here: what is the migrant percentage in Bavaria? But the problem is that by having a pie party and throwing pie charts all over the map, the reader will want to compare Bavaria to the Rhineland-Palatinate.

Just try that.

Mentally you have to take out the little red slice from Bavaria and then transpose it to Rhineland-Palatinate. So which slice is larger? Good luck.

Instead, I would have left that little fact out as a separate chart. Basically you need space for 16 lines, presumably ranked, maybe coloured by their location in former East or West Germany, and then set in the graphic. Nudge Germany to the left, and eat up the same portion of Bavaria the box map, cover the Czech Republic, and you can probably fit it.

Or you could place both metrics on a scatter plot and see if there is any correlation. (To the designers’ credit, perhaps they did and found there is none. Although that in and of itself could be a story to tell.)

The point is that I still hate pie charts.

Credit for the piece goes to the Economist’s graphics department.

Southwest 1380

On Tuesday, Southwest Flight 1380 made an emergency landing here in Philadelphia after the Boeing 737-700’s port engine exploded. One passenger died, reportedly after being partially sucked out of the aircraft after the explosion broke a window. But the pilot managed to land the aircraft with only one engine and without any further deaths.

I wanted to take a look at some of the eventual graphics that would come out to visually explain the story. And as of Thursday, I have seen two: one from the Guardian and another from the New York Times.

The Guardian’s piece is the simpler of the two, but captures the key data. It locates the engine and the location of the window blown out by debris from the engine.

The Guardian's graphic
The Guardian’s graphic

The New York Times’ piece is a bit more complex (and accompanied elsewhere in the article by a route map). It shows the seat of the dead passenger and the approximate locations of other passengers who provided quotes detailing their experiences.

The Times' graphic
The Times’ graphic

So the first thing that struck me was the complexity of the graphic. The Times opted for a three-dimension model whereas the Guardian went with a flat, two-dimensional schematic of the aircraft. Notice, though, that the seating layout is different.

Four rows ahead of the circled window location are two seats, likely an exit row, in the Guardian’s graphic where in the Times’ piece they have a full three-seat configuration. If you check seating charts—seatguru.com was the first site that came up in the Google for me—you can see that neither configuration actually matches what the seating chart says should be the layout for a 737-700. Instead it, the Guardian’s more closely resembles the 737-800 model.

The 737-700 layout from SeatGuru.com
The 737-700 layout from SeatGuru.com
The 737-800 layout from SeatGuru.com
The 737-800 layout from SeatGuru.com

Nerding out on aircraft, I know. But, it is an interesting example of looking at the details in the piece. The Guardian’s piece is far closer to the layout, as least as provided by SeatGuru, and the New York Times’ is more representative of a generic narrow-body aircraft.

Personally, I prefer the Guardian in this case because of its improved accuracy at that level of detail. Though, the New York Times does offer some nice context with the passenger quotes. Unfortunately, the three-dimensional model ultimately provides just a flavour of the story, compared to the drier, but more accurate, schematic depiction of the Guardian.

Credit for the Guardian piece goes to the Guardian’s graphics department.

Credit for the New York Times piece goes to Anjali Singhvi, Sahil Chinoy, and Yuliya Parshina-Kottas.

Where Syria Struck with Chemical Weapons

Friday night the US, UK, and France struck targets in Syria that play a role in the chemical weapons programme of the Bashir al-Assad regime. This is despite “eliminating” his chemical weapons several years ago. And so not surprisingly the media this past weekend covered Syria and the airstrikes. This print piece from the New York Times, however, looked backwards at the history of the chemical attacks Syria has unleashed against its own people.

Note the timeline in the lower-right to provide context of when and how frequent the chemical attacks have been
Note the timeline in the lower-right to provide context of when and how frequent the chemical attacks have been

The map is straightforward and the timeline helpful. Though I would probably have added a point on the timeline highlighting the Ghouta attack of August 2013. That attack prompted the international community to pressure the Assad regime to, again, “eliminate” its chemical weapon stocks. Clearly it hid some sarin and chlorine gas has industrial uses, making it a classic dual-purpose object that is tricky to classify as a weapon. (Though using it against civilians is clearly a weaponised use of the element.)

On a side note, I wanted to point the editorial design here. The overall page is quite nice.

The whole article is well laid out
The whole article is well laid out

The map falls squarely within the middle of the article, with a nice gallery of photographs running along the top. It also features a devastating pull quote describing the Syrian government’s use of chemical weapons. The article fits almost entirely above not just the fold, but also another terrible line of text, in this case the title of another article: Officials Have Lost Count of How Many Thousands Have Died in Syria’s War.

Overall, this was a solid piece providing a backdrop and historical context for the news.

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

News Deserts

Yesterday we looked at the shrinking Denver Post. Today we have a graphic from a related story via Politico. The article explores the idea that President Trump performs better in what the article terms “news deserts”, those counties with a very low level of newspaper circulation. (The article explains the methodology in detail.) This piece we are looking at here shows how those counties performed against the circulation rate and their 2016 presidential election result.

How the news deserts performed
How the news deserts performed

Overall, the work is solid. But I probably would have done a few things differently. First, the orange overlay falls in the middle of one column of dots. Do those dots then fall inside or outside the categorisation of news desert?

Secondly, the dots. If this were perhaps a scatter plot comparing the variables of circulation rates and, perhaps, election vote results as a percent, dots would be perfect. Here, however, they create this slightly distracting pattern in the the main area of counties. When the dots are stacked neatly and apart from other columns, as they are more often on the right, the dots are fine. But in the packed space on the left, not as much.

As I was reading through the article I had a couple of questions. For example, couldn’t the lack of newspapers be reflective of the urban–rural split or the education split, both of which can be seen in the same election results. Thankfully the article does spend time going through those points as well. It is a bit lengthy of a read—with a few other perfectly fine graphics—but well worth it.

Credit for the graphics goes to Jeremy C.F. Lin.

Finding Yourself on the Pennsylvania Turnpike

I hope you all enjoyed your Easter holidays. Easter, wasn’t that two weekends ago you ask. Catholic/Protestant Easter, yes. This past weekend was Orthodox Easter. And since that is what my family celebrates, I was away on holiday this past weekend and only got back in town last night. But on the way out to the ancestral stomping grounds in western Pennsylvania, I realised that the Pennsylvania Turnpike Commission put a little bit of thought into the signage at their more modern service plazas.

The façade of the service plaza
The façade of the service plaza

The outside is basically what you expect, the symbol of the Pennsylvania Turnpike and the name of the plaza. But if you look closer, the name of the plaza, in this case the Lawn plaza outside of Lawn, Pennsylvania, is set not just on a blue sign, but a cropping of a blue map of the commonwealth.

This is where I was, where were you?
This is where I was, where were you?

The yellow lines represent the Pennsylvania Turnpike and, with right being east, the Northeast Extension. The red star represents your current location along the turnpike system. Is this going to tell you how many miles until your next exit? No. I had to go inside and find out how many miles to Bedford, PA on a larger display map. But, this provides a wonderful low-fidelity display. After all, I roughly know where I am headed on the turnpike, and I know whence I came. So I can see that I am a little under half-way to my destination.

Credit for the piece goes to the designers of the Pennsylvania Turnpike Commission.

Deaths in America

Yesterday was murders in London and New York. Today, we have a nice article from FiveThirtyEight about deaths more broadly in America. If you recall, my point yesterday was that not all graphics need to be full column width. And this article takes that approach—some graphics are full width whereas others are not.

This screenshot shows a nice line chart that, while the graphic sits in the full column, the actual chart is only about half the width of the graphic. I think the only thing that does not sit well with me is the alignment of the chart below the header. I probably would align the two as it creates an odd spacing to the left of the chart. But I applaud the restraint from making the line charts full width, as it would mask the vertical change in the data set.

The screenshot is of the graphic's full width, note the lines only go a little over half the width.
The screenshot is of the graphic’s full width, note the lines only go a little over half the width.

Meanwhile, the article’s maps all sit in the full column. But my favourite graphic of the whole set sits at the very end of the piece. It examines respiratory deaths in a tabular format. But it makes a fantastic use of sparklines to show the trend leading towards the final number in the row.

Loving the sparklines…
Loving the sparklines…

Credit for the piece goes to Ella Koeze and Anna Maria Barry-Jester.