Long-term Unemployment

Two weeks ago Bloomberg published a really great example of annotating what some would find a complex infographic.

On occasion I hear concerns that charting two variables on a scatter plot is confusing. Further confusing people is to then plot the data over time, connected by a line. The approach is really no different than what I hear called “combo” charts. Those take two separate variables and plot them in the same space but use one axis to represent the two different variables—often without respect to scales and implicit meanings in the positioning of the two data series.

I find separating those two series onto separate axes and connecting them over time far clearer. And that’s just what the designers at Bloomberg did. But to allay any concerns about confusion—or so I assume—a series of annotations were made, guided by the buttons in the upper-right. These explain succinctly the view presented to the reader in the highlighted section of the overall graphic.

Normal patterns from 2001 to 2007 are highlighted here
Normal patterns from 2001 to 2007 are highlighted here

Overall a strong piece of data visualisation and analysis tied into effort.

Credit for the piece goes to Peter Coy, Evan Applegate, and Jennifer Daniel.

The Battle of Hoth, an Imperial Disaster

Military history can offer us numerous examples of graphics, maps, and illustrations to explain significant battles. Today’s graphics from Wired are no exception. Wired explores the future’s past—not today—by looking at the Battle of Hoth from Star Wars and arguing that the battle was a tactical victory but strategic blunder.

The Imperial Ground Assault on Rebel Lines
The Imperial Ground Assault on Rebel Lines

The author reasons his argument well. But apparently the argument caused quite the controversy and so for you very interested folks, the argument continued onto a subsequent post (alas, sans graphics).

Credit for the article goes to Spencer Ackerman. Credits for the illustrations go to Simon Lutrin, Ross Patton, and Dennis Crothers.

Influenza

The Washington Post has an interactive infographic piece out about the spread of the flu. The big draw is of course the map—people like maps and they are easy to navigate. However, this time the map actually can serve a useful purpose because a virus spreads through the contact of people and communities. And when illustrated over time, the user can see a general spread from the deep south to the Mid-Atlantic than the west before becoming a national problem.

The geographic distribution of the flu
The geographic distribution of the flu

But a really sharp component that I enjoy is the index of flu cases from the four most recent flu seasons. While half the years displayed have seen a gradual increase in the number of hospitalisations, the 2012–13 season became quite troublesome quite quickly. It has even surpassed the 2009–10 levels that were affected by the H1N1 pandemic.

An indexed look at the rampancy of influenza outbreaks
An indexed look at the rampancy of influenza outbreaks

Lastly, not shown here, is an illustration of just what the flu is—a virus—and how it spreads and where anti-viral drugs work.

Credit for the piece goes to Darla Cameron, Dan Keating and Alberto Cuadra.

NFL Teams by the Numbers

While the Superbowl was two weekends ago, I have been sitting on this post for a little while. Probably because I really just don’t understand the sport. But over at the Guardian, the interactive team put together an interactive infographic that looked at payroll spending for each team by position and by overall position, i.e. offence vs. defence.

Admittedly I found the position part not as interesting, probably because of my aforementioned lack of understanding of the game. But the small-multiples-based exploration of the offence vs. defence numbers was quite interesting. It allows the user to highlight their preferred team and then sort the view by offence, defence, or special teams.

The overview shows the breakdown of spending by team
The overview shows the breakdown of spending by team
Selecting a team highlights its data
Selecting a team highlights its data
Sorting the data by one of the four metrics atop the table, in this case offence
Sorting the data by one of the four metrics atop the table, in this case offence

Credit for the piece goes to the Guardian US interactive team and Harry J. Enten.

Blizzard Snowfall

If you do not live on the East Coast, you may be unaware that there was some minor snowfall in New England over this past weekend. The Weather Channel went ahead and named the storm Nemo. (I’m going to lay off the suspect and fishy jokes.) I wanted to revisit the storm because of two graphics that both mapped snowfall totals.

The first is from the New York Times. As one would expect, a quality graphic with clear colour ranges to show the impact across the wider New England area, western New York and New Jersey.

The New York Times snowfall totals
The New York Times snowfall totals

But from the local radio station WNYC came an interesting map of users’ observations. Because it’s a local radio station, the difference between the two versions is that the breadth of data is not as far-reaching as the Times’ data from the National Weather Service.

The limits of WNYC user-reporting
The limits of WNYC user-reporting

However, this sort of user-created data allows for more nuanced, locally-specific data visualisations.

User-reported snowfall in the near New York area
User-reported snowfall in the near New York area

Of course, this creates issues with the accuracy of the data. And in the case of this map, whether the amount given was a snapshot of the snowfall at the time the snow was falling or the final tally.

Credit for the pieces go to the New York Times, and to Steven Melendez, Louise Ma and John Keefe for the WNYC piece.

Forecasting Snowfall

So that fishy little storm the Weather Channel called Nemo—you may have heard of it—put a little snow across New England. Last week the New York Times published an interactive infographic that looked at when and where the snow would be falling, from New Jersey to New York to Maine.

The storm at or near its worst
The storm at or near its worst

The times are cut into six-hour blocks and show in the upper left where the snow would be falling by rate per six-hours. To the right of the map is a series of bar charts that show the snowfall pattern in more or less of a wave. Beneath all of it are a comparison of when, over the last several decades, the largest snowstorms hit Boston and New York (and how much snow each city received). A comparison of the map before to the end of the storm, except for parts of Maine.

The forecast for after the worst had passed
The forecast for after the worst had passed

Credit for the piece goes to Tom Giratikanon, Matthew Ericson, Xaquin G.V., Archie Tse, and Jeremy White.

Whence the Popes Came

For the first time in centuries, a sitting pope is to resign. Typically most popes have served until their death. The question for many will now be who will be the next pope. Will it be a cardinal from Latin America? From Africa?

I looked at the origins of the all the popes since Peter. (Although the earliest few centuries are sketchy at best with not a whole lot of data.) As it turns out, there have already been probably three popes from Africa. Granted, they all lived during the Roman Empire, but still…that has to count for something…right?…No?…okay. Fine. Well in that case, you have plenty of Italians, in particular Romans to serve. (At least historically speaking.)

Whence the Popes Came
Whence the Popes Came

Wawa vs. Sheetz…Wawa of Course…Was There Any Doubt?

Once when I worked at the Jersey shore as a kid a woman purchased her books and then asked me the location of the nearest ATM. I replied “Wawa”. She looked at me as if what I said was gobbledy-gook. She asked again. I replied “Wawa” again but with probably a look of confusion upon my face. It turned out she was from California and she thought I was mentally ill. I did not understand how anyone did not or could not know about the awesomeness of Wawa.

But for all of my upbringing in the Philadelphia suburbs/South Jersey loyalty to Wawa, I must confess to an unfortunate divide in Pennsylvania between we civilised folks near Philly and, well, the rest of the state. We in the Philadelphia metropolitan area are loyal to Wawa. The rest of the state swears allegiance to Sheetz. But how stark is this geographic loyalty? The New York Times mapped store locations with Wawa in blue and Sheetz in red to accompany an article about the “tribal loyalties” to the two chains.

The geographic footprint of Wawa (blue) vs. that of Sheetz (red)
The geographic footprint of Wawa (blue) vs. that of Sheetz (red)

For those more curious about this author’s loyalties, the author of the article, Trip Gabriel, included photos by Mark Makela of one of my local Wawas (the one near Malvern at 202 and 29 for my hometown readers) as the main image for the article along with photos of interiors in West Chester. And of course the Wawas where I grew up:

My Wawas
My Wawas

 

 

All Your Drone Base Are Belong to Us

John Brennan’s confirmation for heading up the CIA begins today. He’s been pretty instrumental in strengthening the United States’ counter-terrorism programme, especially the use of drones to eliminate terrorists.

For those drones, the Washington Post mapped out the known bases in Africa and the Middle East from which we operate our drones.

Map of drone bases
Map of drone bases