Home Vacancies in Kensington and Chelsea

I added Chelsea to make doubly certain for my Philadelphia audience that you did not think I was referring to Philly’s Kensington. Why? Because today’s piece comes from the Guardian and refers to the neighbourhood where the Grenfell Tower caught fire and the inferno killed dozens of people.

A north–south divide
A north–south divide

This is not the most complex piece, but I really like the annotations and notes on the choropleth. They add a great amount of detail and context to a graphic that I imagine many places would be okay leave as is. I can see why the colour palette differs for the two maps, but I wonder if it could have been made to work as a unified palette.

Credit for the piece goes to the Guardian graphics department.

Shifting Temperatures

This past weekend, I came upon a neat little graphic in the New York Times supporting an article about the impact of climate change on temperatures. The article basically lays out the argument that summers are getting hotter. And as a cold-weather person, that is dreadful news.

Can we not shift a wee bit the other way please?
Can we not shift a wee bit the other way please?

But the good news is the graphic was well done. It uses the outline of the baseline data as a constant juxtaposition against the date interval examined. And the colour breaks remain in place to show that compared to what we consider “normal”, we are seeing a shift to the higher end of the spectrum.

Credit for the piece goes to the New York Times 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.

London in Small Multiple Form

You all know that I love small multiples. And we have been seeing them more often as representations of the United States. But today we look at a small multiple map of London. The piece comes from the Economist and looks at the declining numbers of pubs in London. With the exception of the borough of Hackney, boroughs all across London are seeing declines, though the outer boroughs have seen the largest declines.

Mini London
Mini London

The only thing that does not work for me is the bubble in each tile that represents the number of pubs. That gets lost easily among the blue backgrounds. Additionally, the number itself might suffice.

Credit for the piece goes to the Economist graphics department.

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.

Trump’s Polling

My battery is about to die this morning and I don’t have my charger so this is going to be a shorter piece than usual. But I wanted to look back on the 100 Day polling that the New York Times posted. It does paint an interesting picture of somebody so polarising that Trump is probably safe despite being one of the least favourably viewed presidents in modern times. Why? Because his supporters are so fervently loyal.

Not only is Trump low, he's low historically
Not only is Trump low, he’s low historically

But that piece is almost a month old now. And so I wanted to point out something that FiveThirtyEight is doing—a running tracker of Trump’s polling. I am sure I will return to it in the future, after all we have over three and a half years to go until the next four year presidential term begins.

Trump is pretty low…
Trump is pretty low…

Credit for the piece goes to Karen Yourish and Paul Murray for the Times and Aaron Bycoffe, Dhrumil Mehta, and Nate Silver for FiveThirtyEight.

Life Expectancy in the US and All Its States

Happy Monday, all.

If this week’s news cycle cooperates, I am going to try and catch up on some things I have seen over the last several weeks that got bumped because of, well, Trump usually. Today we start with a piece on life expectancy from FiveThirtyEight.

The piece begins with a standard choropleth to identify, at county levels, pockets of higher mortality. But what I really like is this small multiples map of the United States. It shows the changes in life expectancy for all 50 states. And the use of colour quickly shows, for those states drastically different than the national average, are they above or below said average.

Look at all the little boxes
Look at all the little boxes

Credit for the piece goes to the FiveThirtyEight 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.

O’Reilly’s Out

Of all the things I expected to cover this week, this was not one of them.

This is Fox New’s firing of Bill O’Reilly, their lead personality and heaviest hitter for the last 21 years, for accusations of sexual harassment both externally and internally. But up until yesterday afternoon, just how important was O’Reilly to Fox News? Well, as you might guess somebody covered just that question. The New York Times addressed the question in this online piece and uses a nice graphic to buttress their argument.

What goes up must eventually fall down
What goes up must eventually fall down

I like the use of the longer time horizon across the top of the graphic. But most important in it is the inclusion of the trend line. It helps the reader find the story amid the noise in the weekly numbers. The big decline towards the end of December looks important until one realises that it probably owes the drop to the Christmas holidays.

Then the bottom piece does something intriguing; it shows both the actuals and percentages side-by-side. Typically people love stacked bar charts—by this point you probably all know my personal reluctance to use them—and that would be that. But here the designer also opts to show the share as a separate data point beside the stacked bar charts.

I think the only thing missing from the piece is a bit more context. Is O’Reilly still the heaviest weight in the lineup? The top chart could have perhaps used some additional context of other shows over the last few months. For example, how does O’Reilly compare to Hannity?

Regardless, this piece does a fantastic job of showing the until-yesterday increasing importance of O’Reilly to Fox News and then Fox News’ importance to 21st Century Fox.

Credit for the piece goes to Karl Russell.