Hurricane Sandy caused a lot of devastation, especially along the Jersey Shore. I covered some of theinfographics coming out of the storm last year when I happened to be home in Pennsylvania for the storm. But as the region begins to rebuild, many property owners are likely to face hardships in brining their constructions up to the newer FEMA codes. Last week the New York Times looked at some of those new regulations—along with damage and flood zones—for the northern section of the Jersey Shore.
It’s Oscar time. And not in the it’s time for grouchy, can-living commentary. It’s as in movie award time.
How are films promoted? Often through trailers and teasers. But how are those made? Well, the New York Times dissected trailers for five of the nine films up for best film. The piece looks at where the films are cut and spliced to create a 120-second-long overview without ruining the plot. And as it turns out, different types of trailers have different systems for cutting up those films.
Argo's Trailer
The piece is made even better through the annotations associated with different segments of the different films. This paired with the introductory text makes the diagram of the film trailers intelligible to the reader. And then of course you can click on the still and see the actual trailer. A solid piece, all around.
Credit for the piece goes to Shan Carter, Amanda Cox, and Mike Bostock.
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
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.
This time last year I used some data published by Public Policy Polling upon presidential popularity (alliterative, right?) to create a graphic looking at said popularity. So here it is again for Presidents Day. Next time I’ll try to remember the holiday is coming a bit further in advance and work on something newer.
Presidential popularity
A minor point, someone asked why the bar runs past 100 for some presidents yet stops before 100 for others. The data was rounded and some things didn’t add to 100. I saw no need to manipulate the numbers for aesthetic purposes.
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 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.
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
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
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.
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 teamSelecting a team highlights its dataSorting 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.
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
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
However, this sort of user-created data allows for more nuanced, locally-specific data visualisations.
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.
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 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
Credit for the piece goes to Tom Giratikanon, Matthew Ericson, Xaquin G.V., Archie Tse, and Jeremy White.
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.)
