Irma’s Impending Arrival

Your author is on holiday today and is actually writing today’s post on a Thursday night train to Boston. But by the time he returns late Sunday night—a Monday morning post is not guaranteed—Hurricane Irma will have likely made landfall somewhere along the Florida coast.

Thursday the Guardian published a nice article looking at the potential tracks for Irma. And while the specific routes will certainly be amended and updated over the weekend, the article is worth looking at prior to Irma’s arrival at Florida. As of my writing the track has shifted ever slightly westward and the current predicted path looks for Irma to land south and west of Miami. Ergo this screenshot is already a little outdated.

The three little wolves will huff and puff…
The three little wolves will huff and puff…

The remarkable thing about this graphic, which is just a cleaner version of the standard meteorological maps through more a more considered palette, is that there is not just one path of winds, but three. Following quickly on the heels of Irma are Katia and Jose, the latter the one taking the nearly same path as Irma while Katia spins towards Mexico.

But the graphic I really wanted to look at is the one ending the piece.

A very wide range of countries
A very wide range of countries

This looks at the countries in Irma’s path as of Thursday morning. What I do not understand is the vertical axis of the bars. What does the height represent? To simply show the rank of countries able to cope with natural disasters, a more straight-forward table could have been used. A dot plot would also make some sense, but again, it would require an understanding of the underlying metrics driving the chart.

The graphic is saved by the annotations, in particular the more/less vulnerable directional arrows. Because I do not understand why countries are grouped into the particular buckets, I find the coloured bins out of place.

I think the concept of showing the most vulnerable countries is terribly important, however, the graphic itself needed a little more thought to be a little more clear in presenting the concept.

Credit for the piece goes to the Guardian graphics department.

Rising Tides, Rising Disasters?

One more day of Harvey-related content. At least I hope. (Who knows? Maybe someone will design a fantastic retrospective graphic?) Today, however, we look at a piece from the Economist about the rising number of weather-related disasters, but thankfully falling numbers of deaths. The piece has all the full suite of graphics: choropleths, line charts, and bar charts (oh my!). But I want to look at the bar chart.

A timeline of disaster causes around the world
A timeline of disaster causes around the world

I cannot tell from this chart whether there has been any change in the individual elements, the meteorological, hydrological, or climatological disasters. And unfortunately stacked bar charts do not let us see that kind of detail. They only really allow us to see total magnitude and the changes in the element at the bottom of the stack, i.e. aligned with the baseline. So I took their chart and drew the shapes as lines and realigned everything to get this.

My take
My take

You can begin to see that meteorological might be overtaking hydrological, but it is too early to tell. And that right now, climatological causes are still far behind the other two.

Credit for the piece goes to the Economist Data Team.

Credit for mine goes to me.

Brexit’s Impact on Irish Shipping

Today’s post is, I think, the first time I’ve featured the Politico on my blog. Politico is, I confess, a regular part of my daily media diet. But I never thought of it as a great publication for data visualisation. Maybe that is changing?

Anyway, today’s post highlights an article on how the Irish shipping/logistics industry could be affected by Brexit. To do so, they looked at data sets including destinations, port volume, and travel times. Basically, the imposition of customs controls at the Irish border will mean increased travelling times, which are not so great for time-sensitive shipments.

This screenshot if of an animated .gif showing how pre-Brexit transit was conducted through the UK to English Channel ports and then on into the continent. Post-Brexit, to maintain freedom of movement, freight would have to transit the Irish Sea and then the English Channel before arriving on the continent. The piece continues with a few other charts.

Brexit strikes again
Brexit strikes again

My only question would be, is the animation necessary? From the scale of the graphic—it is rather large—we can see an abstracted shape of the European coastlines—that is to say it’s rather angular. I wonder if a tighter cropping on the route and then subdividing the space into three different ‘options’ would have been at least as equally effective.

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

Education and Eatery Preferences

Last week the Economist posted an intriguing article about the relationship between culinary choices/preferences and education and income. It began with an article by David Brooks in the Times, which I have not read, talking about how culture can create inequality as much as economics or government policy. The Economist then conducted a survey looking at the relationship between food preferences and both education and income. This is a screenshot of some of their results.

To be fair, I rarely eat sushi because I don't much care for it.
To be fair, I rarely eat sushi because I don’t much care for it.

Yes, correlation is not causation, but these are some fascinating findings that suggest we should perhaps explore the idea in more depth.

As to the graphics, we have nothing super sophisticated, just a matrix of small multiples. But that goes to the point of “simple” graphics sometimes can do wonders for a story.

Credit for the piece goes to the Economist graphics department.

Not Alone for Trivia

Well after the last two weeks of recording solo trivia performances, I decided that this week I would showcase a team effort.

A non-solo performance
A non-solo performance

And we finally placed, ending the performance tied for first place. But if you look closely you will see the final score has us at second. Why when we were tied with the same number of points? Because tiebreaker. And after I was selected to represent the team, I needed to respond, within three seconds, with the names of Tom Hanks films in a back-and-forth response.

I could name only Saving Private Ryan and Castaway. My competitor, she named three. They won.

Another Solo Pub Trivia Performance

This past Wednesday I once again ended up playing trivia at the pub solo. Once again, I decided over the final pint that I would attempt to visualise my performance.

One thing to keep in mind is that on Wednesday there were fewer teams competing—five instead of nine. And while I never placed higher than tied for third, this week’s bar charts show how I was incredibly competitive until the final music round.

Music and celebrity are clearly not my strong suits
Music and celebrity are clearly not my strong suits

Despite an abysmal performance at naming celebrities as they were as children, my near-perfect second round kept me only five points behind first place. And a perfect fourth round meant heading into that final round I climbed back to being only three points back. Thankfully I knew more of the songs this past week. And enough to not finish last. But, I was close enough that a perfect round would have been enough to still place first.

Super helpful that Lord of the Rings questions appeared a few times.

The Insurance Exchanges

There is a lot to unpack about last Thursday and Sunday. But before we dive into that, a little story from the New York Times that caught my eye from Friday.

Where there are no real options
Where there are no real options

The map shows the counties in the United States where there is one health insurer and no health insurer. Further on in the piece a small multiple gallery shows that progression from 2014 and highlights how the drastic changes are seen only in 2017 and 2018.

The problem is often not that people cannot buy insurance if no insurers are in the marketplace. The marketplace is for federally-subsidised coverage and insureres appear to be moving to offering policies outside the marketplace for non-subsidised customers.

The White House claims Obamacare is in a death spiral. It is not. But after seven years it could use a little maintenance.

Credit for the piece goes to Haeyoun Park and Audrey Carlsen.

Maps and Legends

First, great song by R.E.M.

Second, you may recall a post last week where I shared some work by FiveThirtyEight about life expectancy. In particular I liked the set of small multiples. However, the New York Times just took what I liked and upped it a slight notch.

Maybe he's caught in the legend…
Maybe he’s caught in the legend…

Every small multiple set needs a legend to explain just what the user is looking at. What the Times did is integrate that legend into the Alaska multiple. And it can do that because of Alaska’s position in the upper-left, or northwest, portion of the “map” as a non-contiguous part of the United States.

Clever.

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

Philly Falls from Fifth

Well it finally happened. While the Great Recession spared Philadelphia for several years, Phoenix has finally moved up into the rank of fifth-largest city in the United States.

There are some notable differences that this graphic captures. The big one is that Philly is relatively small at 135 square miles. Phoenix is half the size of Rhode Island. What the graphic does not capture, however, is that Philly is still growing, albeit more slowly than southern and western cities. Because also in the news is the fact that Chicago has shrunk and lost people. Personally I count as a -1 for Chicago and a +1 for Philly.

Comparing size and population
Comparing size and population

Credit for the piece goes to the Philly.com graphics department.

The Disappearing Urban Middle Class

Today we look at income in American cities and in particular the middle class disappearance. The Guardian published the graphics, but they originate with Metrocosm, LTDB at Brown, and IPUMS National Historical Geographic Information System. So what are we looking at? Well, the big one is a set of small multiples of cities and their income breakdowns as percentages of city census tracts. This screenshot is static, but the original is an animated .gif.

The flattening of the curve
The flattening of the curve

I have a few issues with the design of the graphic, the most important of which is the colour palette. If the goal is to focus on the decline of the middle class—and I admit that may be the point of the Guardian’s authors and not the original authors—why are the most visually striking colours at the top of the income distribution. Instead, you would want to draw attention to the middle of each chart, not the right. And if the idea was that the darker colours represent the higher income groups, well the positioning of each bar on the chart and the axis labelling does that already. After all, if anything, the story is that in a number of cities the middle class has shrunk while the lower income groups have grown. And you can barely see that with the lower income groups coloured yellow.

My other issues are more minor design things such as the city labelling. I kept reading the label as being below the bars, not above as it actually is.

And then I wonder if a different chart form would be more effective at showing the decline in the middle class. Perhaps a line chart plotting the beginning and end points for each cohort?

Then the piece gets into some three-dimensional maps that you can spin and rotate.

Just stop
Just stop

Yeah. Shall I count the ways? A more conventional choropleth would have served the purpose far more effectively. The dimensionality hides lower income tracts behind higher ones. The solution? Allow the user to rotate and spin the map? No, get rid of the dimensionality. It offers little to the understanding of the underlying data. Not to mention, are the areas of shadows shadows? Or are they another bin or cohort of income?

And then you have to read the piece to get a fuller understanding of my criticism.

But don’t worry, I can quote it.

Chicago was largely successful transitioning away from manufacturing to a service-based economy. This shift is evident in the bifurcated pattern present in 2015 – a heavy concentration of wealth in the business/financial district and marked decline in the surrounding area.

Those of you who read this blog from Chicago or who have lived in Chicago will pick up on it. The rest of you not so much. The concentration of wealth is not located in the business/financial district. Those dark red skyscrapers are not actual skyscrapers, they are census tracts located not in the financial district, but the areas of River North, Old Town, Gold Coast, &c. Thinking of the issue more logically, yes incomes are up in cities that are doing well. But how many of those very wealthy live on the same block as their office? Not many. Your higher income is going to be concentrated in residential or mixed-residential neighbourhoods near, but not in the business/financial district.

The data behind this work fascinates me. I just wish the final graphics had been designed with a bit more consideration for the data and the stories therein. And a little bit of proper understanding of the cities and their geography would help the text.

Credit for the piece goes to Metrocosm, LTDB at Brown University, and IPUMS National Historical Geographic Information System.