Adding Guided Context to Maps

Maps are cool. They show the geographic distribution of data. And that is fantastic if there is a story in said distribution. But even if there is a story, sometimes given both the scale of the map and the amount of data encoded in the map, how could you possibly expect to find the story? Which little region of the map do you search to find the interesting nuggets?

On Sunday, the New York Times published an interesting solution to that very quandary. The context is an article looking at the anger and resentment felt by some towards government assistance via the social safety net, and yet how these very same people depend upon that safety net through programmes like Social Security, Medicare, Medicaid, &c. The map, a choropleth, examines several different metrics that comprise government assistance, e.g. Medicaid payments as a percentage of income.

Government benefits overview
Government benefits overview

One can easily toggle through the various metrics at the scale of the entire United States. This is a rather standard feature for such maps. However, in the upper-left corner, the designers placed a ‘guide’ that provides context and stories for each metric. But, not only does the guide provide text to support the map, but it zooms in on specific areas and regions that then support the text and best exemplify the point.

Here we see the map of the whole US for Medicaid, which appears to be scattered pockets of higher percentages. Interesting perhaps, but the user likely has few ideas as to what that visualisation actually means.

Medicaid's broad overview
Medicaid's broad overview

Compare that to the guide’s view of the map, which focuses on the large cities on the East Coast.

Medicaid's eastern core context
Medicaid's eastern core context

Providing context and guiding a reader/user through the stories contained in the map, or at least those deemed interesting by the designers and editors, is an interesting solution to the problem of finding the story in maps such as these. However, by moving away from a strict visualisation of the data, the New York Times and others that try similar avenues introduce human biases in the story-telling that may otherwise be unwanted or distracting.

Credit for the piece goes to Jeremy White, Robert Gebeloff, Ford Fessenden, Archie Tse and Alan McLean.

Circle Charts ca. 1937

Another image from my 1930s algebra book is on pie charts, or what was then called circle charts. And while the utility of such a chart form has not changed, especially in these examples, the circle chart of the 1930s had one particular good use for students. Constructing it.

Circle chart construction
Circle chart construction

Today a student plugs in numbers into a spreadsheet in Google Docs, Excel, or Open Office. He or she presses a button and the circle chart is done. Back in the 1930s, students needed to convert absolutes to percentages and then use protractors to draw the slices on pieces of paper. Fancy that, students having to do math to make a chart.

How to Use Good Data Visualisation in Your Private Life

Often we think of graphs, charts, and other forms of data visualisation as a means to exploring the economic growth of so and so, or visualising traffic patterns, of explaining the complexities of science, or the reporting of yesterday’s news. But, we can all use data visualisation in our own lives to help make better decisions.

While I normally opt not to post links to other data visualisation blogs—I figure most people are also already checking those out—Nathan Yau posted about why he wants to cut the cable, i.e. lose his cable television subscription. He has two separate charts that are simple but effective in driving home the point that he really ought to think about cutting cable out.

Cutting cable
Cutting cable

The article, while a bit longer than usual, is well worth the read. The charts with the explanation make for a compelling argument.

Comparing the (Display of) Results in Colorado

Mitt Romney lost badly last night. No way around that. But as I watched the results come in through various sources, I noticed two interesting design decisions that made me think; one from the Guardian (the British perspective), and the other from the New York Times.

Using only Colorado as an example, here is the map of county results by the Guardian.

Results map from the Guardian
Results map from the Guardian

Note how the map is presented in 3-D that therefore allows the use of height as another encoded variable, in this case the size of the lead. Now compare that to the map used by the New York Times.

Results map from the New York Times
Results map from the New York Times

Note how this map is flat. So much less cool, right? But try to compare the results in Denver County. When I look at the Times’ map, I see blue; Mitt Romney won. When I look at the Guardian’s map, I see…actually, I can’t. That label is in the way. And then even when I begin to interact with the map, Denver County is hidden by the height of Arapahoe County.

But what about the size of the lead? I cannot see that encoded in the New York Times map. No, one cannot. However, they added a toggle function to change the data displayed on the map—though the utility of that view can be left for another discussion.

And now to a minor point about comparing the totals.

Again, a look at the Guardian’s presentation.

Results table from the Guardian
Results table from the Guardian

And now the New York Times. Numbers are numbers and faces are faces. But look at the graphic element representing the percentage. With the Guardian, I can just barely discern that the size of the circles for Santorum and Romney are not the same. And the same goes for Gingrich and Paul. But when I look at the Times’ presentation, I see a simple bar chart that more clearly shows the relationships between the results.

Results table from the New York Times
Results table from the New York Times

So interesting design decisions lead to one view that I find far more successful in showing the data: the New York Times.

Replacing the Bay Bridge for the Long Term

Bridges are vital parts of infrastructure networks connecting two separate pieces of territory, but often they can be choke points. Damage to a bridge can result to isolation at worst and at best long, circuitous reroutes that add significant time to travel. In the San Francisco area authorities are building a new bridge to replace the current Bay Bridge. But as everyone knows, buildings and infrastructure in that area can be significantly damaged during earthquakes. And the area is waiting for the ‘Big One’ that shall come some day or another.

So how to build a new bridge for the long-term that will also survive a major earthquake? The New York Times explains it in an interactive piece accompanying an article. The interactive piece includes an animation with voiceover explaining the details of the design, with diagrams illustrating the components placed next to the video player. At the bottom, anchoring the piece (pun intended), is a photo-illustration of the new bridge’s design.

Diagram explaining the Bay Bridge replacement
Diagram explaining the Bay Bridge replacement

Credit for the piece goes to Mika Gröndahl and Xaquín G.V.

A Win for New Jersey

So apparently there was a game last night? I didn’t get the chance to watch it, I was busy updating this blog here. The changes ought to make it easier to be more social, since that’s the thing these days.

But, so about that game, apparently New Jersey won. Congratulations to the New Jersey Giants of East Rutherford, New Jersey. You have prevailed. The newspaper in the nearby city of New York had a graphic to explain the progress of the game, this being a cropping of the ending. Which is probably all anybody really needed to see anyway, right?

Second half drive chart
Second half drive chart

Picture Graphs ca. 1937

Among my legions of books are a few from my grandfather’s days when he was a student. After going through some photos yesterday, I realised that I had taken photos of his elementary school algebra text book. Among the first chapters was an entire section on graphing and chart types. I hope to go through these in more detail in some later posts, but here’s one for the stereotypes.

A picture graph
A picture graph

Punxsutawney Phil’s Day in the Sun

Groundhog Day. It’s Punxsutawney Phil’s day in the sun. Or not. Depends upon the year.

Anyway, the Philadelphia Inquirer did a small piece about the history of this famous little groundhog from remote northwestern Pennsylvania.

The Past Prognostications of Punxsutawney Phil (Alliterate that.)
The Past Prognostications of Punxsutawney Phil (Alliterate that.)

Credit for the piece goes to Cynthia Greer.

Housing Prices Fall Some More

Houses are meant to be lived in. Which is good to know if you’re a real estate investor because the housing market in the US is still not so good. According to an article in the New York Times, we’re back to 2003 levels (on average of course) for single-family homes.

Accompanying the article is an interactive chart that lets users view the full breadth of the survey while highlighting specific markets of interest and showing actual values along the length of the chart.

The Case-Shiller Index for Housing Prices
The Case-Shiller Index for Housing Prices

Credit for the piece goes to Kevin Quealy and Jeremy White.

Florida Primary

The Republican primaries…they’re still going on…on the long inevitable road to Romney’s coronation. Next up is Florida, always an interesting state to watch. There are a lot of people there with a whole host of interesting demographic slices. Perhaps one of the most interesting ones, at least to the media, is the Hispanic vote. Other things to look at in Florida include the burst housing bubble and rather high unemployment.

The New York Times published a graphic with a few maps and charts trying to paint the landscape of the Florida primary battle. These two selections below show which Republican primary candidates won which counties in 2008 as well as the size of the Hispanic population registered Republican.

Florida primary landscape
Florida primary landscape

Credit for the piece goes to Haeyoun Park.