data visualisation – Page 41

First Florence, Now Michael

You may recall a few weeks ago there was a hurricane named Florence that slammed into the Carolina before stalling and dumping voluminous amounts of rain that inundated inland communities in addition to the damage by the storm surge in the coastal communities. At the time I wrote about a New York Times piece that explored housing density in coastal areas, specifically around the Florence impact area.

Well today the New York Times has a print graphic about something similar. It uses the same colours and styles, but swaps in a different data set and then uses a small multiple setup to include the Florida Panhandle. Of course the Florida Panhandle was just struck by Hurricane Michael, a Category 4 storm when it made landfall.

Of course that track for Michael also brought significant rainfall to the areas recovering from Florence for a double whammy

This one instead looks at median income per zip code to highlight the disparity between those living directly on the coast and those inland. In these two most recent landfall areas, the reader can clearly see that the zip codes along the coast have far greater incomes and, by proxy, wealth than those just a few zip codes further inland.

The problem is that rebuilding lives, communities, and infrastructure not only takes time, but also money. And with lower incomes, some of the hardest hit areas over the past several weeks could have a very difficult time recovering.

Regardless, the recoveries on the continental mainlands of the Carolinas and Florida will likely be far quicker and more comprehensive than they have been thus far for Puerto Rico.

The only downside with this graphic is the registration shift, which is why the graphic appears fuzzy as colours are ever so slightly offset whereas the single ink black text in the upper right looks clear and crisp.

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

Europe is More than the Big States

First, I want to start with a housekeeping note. Your author will be travelling for work and then a short autumn holiday. And so while I may be able to sneak a post or two in, I generally would not expect anything until next Friday, 12 October.

But let’s end this string of posts with a map. It is a choropleth, so in one sense there is nothing crazy going on here. The map comes from the Economist, which published an article on life expectancy throughout Europe and the big takeaway is that it is lower in the east than the west.

Apparently life is pretty good in northern Spain

The great part of the map, however, is that we get to see a more granular level of detail. Usually we just get a view of the European states, which presents them as an even tone of one shade or one colour. Here we can see the variety of life expectancy in the UK, France, and Belgium, and then still compare that to eastern Europe.

Of course creating a map like this demands data to drive it. Do data sets exist for the sub-national geographic units of EU or European states? Sometimes not. And in those cases, if you need a map, the European state choropleth is the choice you have to make. I just hope that we get to see more data sets like this with more granular data to present a more complex and patterned map.

Credit for the piece goes to the Economist Data Team.

Millennials Are the Worst

Happy Friday, everybody. We made it to week’s end. But wouldn’t you know it? Millennials are still terrible. Admittedly this piece is over a year old, but I could not remember ever seeing it before.

If you do not recall, last year there was a debate about the spending habits of millennials and why they are not out there buying homes and properties. The point was that we waste our money on experiences like expensive coffees and, most specifically, avocado toast. So amidst all this, the BBC decided to look at how many pieces of avocado toast would be needed to purchase an apartment in 10 global cities. Neither Philadelphia nor Chicago were on that list, but New York is.

Note they even have local prices for avocado toast to make the index more accurate.

Ultimately, I have never had avocado toast. But it sounds pretty good. But I find it a stretch to think the reason I do not own a home is because I am trying to eat 12,135 slices of avocado toast.

Credit for the piece goes to Piero Zagami.

Running Up the Debt

I was reading the paper this morning and stumbled across this graphic in a New York Times article that focused on the increasing importance of debt payments.

Those interest payment lines are headed in the wrong direction.

The story is incredibly important and goes to show why the tax cuts passed by the administration are fiscally reckless. But the graphic is really smart too. After all, it is designed to work in a single colour.

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

Kavanaugh’s Fading in Competitive House Seats

Another day, another allegation of sexual misconduct against Brett Kavanaugh. We are presently at two and are expecting a third tomorrow. But the question is, will these allegations sink his nomination? Probably not. But could that confirmation hurt Republicans in the mid-terms? Possibly.

The New York Times posted an article about how Kavanaugh’s support in battleground congressional districts is slipping. To be fair, the chart is simple, but it does its job. And usually that’s all we want a chart to do.

Just a few points can make all the difference…

Me the person interested in politics, however, will take this a bit further. If Kavanaugh’s support continues to fade—this survey was taken before these new allegations were public—will Republicans supporting the nomination face a backlash from their constituents?

Credit for the piece goes to Nate Cohn.

Our Lives Are a Mixed Bag

Last Thursday the Economist published an article looking at quality of life across the world. The data came from the Social Progress Imperative and examined quality of life, excluding economic performance. And as the article details, the results were mixed at best.

But, hey, the chart was really nice. We have a small multiple set looking at the overall index across all regions across the world and then the US, China, and India in particular.

Unfortunately the US is heading in the wrong direction…

I think this chart hits almost all the right notes. My only qualm would be the component indices being placed alongside the overall index. I wonder if breaking the whole thing out by component would work. As it is, it generally works well, I am just curious because there is the one issue of the United States where our well-being line falls beneath that of the overall index. But then again, the story is the overall index.

Credit for the piece goes to the Economist Data Team.

The Carolinas and Florence

As you all probably know, Hurricane Florence crashed into the Carolinas this past weekend. And while I was on holiday, I did see a few articles about the storm and its impact. This one from the New York Times captured my attention because of its use of—surprise, surprise—maps.

In particular, as the user scrolls through the experience, he or she sees the change in population density of the region from 1990 to 2010. Spoiler, a lot more people now live near the coast.

In terms of the graphic, however, I wonder if a simpler approach could have communicated that part of the story more clearly. Could the map have simply shown the change in density instead of visually transforming from one number to the next? Or maybe a summary map could have followed those transitions?

Credit for the piece goes to Stephen M. Strader and Stuart A. Thompson.

iPhone Screen Size

Your humble author has returned. And on my trip up to Boston I took plenty of photos with my Nexus 5X, a Google-designed smartphone. That is correct, this designer does not use an iPhone. But I am aware of the latest things coming out of Apple—after all this is being typed up on a Mac—and so the larger screen size caught my attention.

The Economist put together a piece looking at the screen sizes of the iPhone models over the years and then used that to project into the future the likely sizes of the phone’s display.

Now the article hints at what I would be particularly interested in: the screen sizes of comparable Android models. How have they changed over the years? I still cling to my smaller screen size mobile as I am not a fan of the phablet.

The chart itself is simple and well done, plotting the models without any fuss. But the most important part is the benchmark line of the iPad mini’s screen size. And the user can clearly see the forecast merger of the sizes.

Credit for the piece goes to the Economist Data Team.

Pie Charts

Today is my Friday, everyone, as I am going away on holiday for a little bit. (You can expect me back mid-next week.) So, enjoy this design tip from xkcd on my favourite form of data visualisation: the pie chart.

Credit for the piece goes to Randall Munroe.

Europe’s Far-right Parties

Yesterday we looked at the rise of the far-right in Sweden based on their electoral gains in this past weekend’s election. Today, the Economist has a piece detailing their strength throughout Europe and they claim that this type of nationalist party may have peaked.

The graphic fascinates me because it appears to be a twist on the box or tile map, which is often used to eliminate or reduce the discrepancies in geographic size so that countries, states, or whatevers, can be examined more easily and more equitably.

I am guessing that the ultimate sizes, which appear to be one to four units, are determined by population size. The biggest hitters of Germany, the UK, France, and Spain are all four squares or boxes whereas the smaller states like Malta are just one. (But again, hey, we can all see Malta this time.)

I think this kind of abstraction will grow on me over time. It is a clever solution to the age-old problem of how do we show important data in both Germany and Malta on a map when Malta is so geographically small it probably renders as only a few pixels.

On the other hand, I am not loving the line chart to the right. I understand what it is doing and why. And even conceptually it works well to show the peaks of the parties. However, there are just a few too many lines and we get into the spaghettification of the chart. I might have labelled a far fewer number and let most sit at some neutral grey. Or, space permitting, a series of small multiples could have been used.

Credit for the piece goes to the Economist Data Team.