Keeping with maps, they can be useful, but all too often people fall back upon them because it is a quick and easy way of displaying data for geographic entities. This graphic from the New York Times on ADHD is not terribly complex, but it uses a map effectively.
The article discusses how ADHD rates among states vary, but are still higher in the South. The map supports that argument. Consider how it would be different if every other state were darkened to a different shade of purple. There would be neither rhyme nor reason as to why the map was being used.
A subtle point worth noting is that only the states falling into the highest bin are labelled. Those are the states that best support the story. The remainder of the states are left unlabelled so as not to distract from the overall piece.
Today’s map comes from the Texas Tribune out of Austin, Texas. The map displays the location of disposal wells, i.e. the sites where the waste water from fracking and related drilling operations are dumped. Firstly, the map hints that the fracking industry is not spread equally across the state.
But secondly, the map does this through the use of hexagons that represent well density. So at a broad, state-wide view, the user sees almost a traditional choropleth. The difference is that these are not natural or political boundaries but rather data constructs designed to aggregate highly granular data points.
Even nicer, however, is that if you want to see where disposal wells are in your county or town, the map lets you do that too. Because as you zoom in ever closer, the individual wells appear within the hexagons that they colour. It’s a very solid piece of work.
The US imports a lot. But it does not export quite as much. The difference between those two figures is what is known as the balance of trade. Quartz looks at the US balance of trade not at an overall level, but between individual countries.
This is not one of my favourite pieces. For starters, while the overall figures are in the accompanying text, it would be useful to include total US imports and exports alongside the graphic as a point of reference.
Secondly, a long-standing issue I have is area comparisons. Sometimes they are needed and useful, a good example is a tree map. But in this piece, the circles do not add up to a recognisable whole. They also do not help when looking at individual countries and their historical trade values. A dotted outline of a circle shows the previous year’s trade. But more often than not, the trade level was so similar that the circles nearly overlap exactly.
The grouping and highlighting functionality hints at a useful application to explore US trade data, but the clumsiness of the circles renders that usefulness moot. .
First things first, the verb is to sequester. The noun is sequestration. 1 March is not when the sequester begins. It is when the sequestration begins.
Now that we have the preliminaries out of the way, much is made of high government spending relative to revenue. However, this conversation still misses the point that government spending has fallen significantly. The New York Times charted that recent fall in spending in this graphic. This contraction is the largest drop in over 50 years. Along with the bars indicating recessions, I perhaps would have indicated major US military conflicts given the emphasis the introduction places on those events.
The piece also looks at government employment, which has been atypically lower than pre-recessionary figures. Taken in sum, the two sets of data point to an extant condition of austerity that shall only be worsened by…c’mon everyone…that’s right, the sequestration.
The New York Times looks at who controlled the redistricting of US congressional seats because of the 2010 census. It then showed an example in North Carolina where Republican control led to the state being less competitive in the past for Democrats. In 2010, Democrats held 7/13 seats in North Carolina. But after the redistricting, in 2012 the Democrats held only 4/13. And all of this is done in a small, compact space. This is a very effective graphic.
Earlier this week, the Office of National Statistics in the United Kingdom released census results for England and Wales. (Northern Ireland and Scotland are reported separately.) England has more people than expected, most likely because of undercounting of immigrants, and Wales is now some three million and counting. There are fewer Christians than expected—and fewer Jedi than I expected—as the ranks of the non-religious grow. But from of course all of this comes a bevy of visualisations. These are but a few, but if anybody finds others worth nothing, please feel free to send them my way.
Straight from the source is a set of interactive mapping applications from ONS that compare 2001 data to 2011 data. As best it can, census districts are compared on a one-to-one basis, but with boundary changes that isn’t always possible. Clicking on district provides one with details about the responses for that area.
Perhaps the one thing missing from these—and it may well owe to the aforementioned boundary changes—is a map of changes to see which areas have been most impacted. Or a map of the results compared to the average to see where the average can be found and where the positive and negative extremes can be found.
An infographic from the Guardian looks at the overall dataset with quite a few maps and then circle-y things. While the large map is the white population in 2011, the remaining maps are before and after comparisons. Again, an interesting look would have been perhaps deviations from the average or of the actual change per district.
I appreciate the impact of the main story, the increasing diversity of England and, to a lesser extent, Wales. London in particular is now minority white. However, I am less keen on the circle-y things and that data could probably have been presented in a clearer, more direct fashion. I am not a fan of red, yellow, and green traffic light colours, but I also recognise that the Guardian is working within their brand on this.
Unfortunately this interactive map of Northern Ireland’s national identity does not quite work for me. I appreciate the toggle between the different response options, however, I find the responses themselves hard to compare. The colours remain the same, but the scales for the results change. For those identifying as Northern Irish, the top value is clearly less than those identifying as either British or Irish. But I would have liked to have seen the scales for British and Irish to closer match. I also find the black background distracting and overwhelming the colours. I wonder how the result would have worked if treated with the above aesthetic.
The BBC took a stab too with a section devoted to the results. Unlike the ONS visualisation above, however, the side-by-side comparison is forced to be smaller with the included text. And when one zooms into a particular district, the map degrades into crude polygons—a particular pet peeve of mine—that would be unrecognisable to someone familiar with the intimate geographic details of their home region. (Yes, simple shapes make the files smaller for overview maps, but when seen up-close, they lose their value by making ugly maps.) Also, the colours and bins in this particular view are not as informative as in the view above.
The BBC, however, did create a small graphic for an article that showed population changes in the districts, alas the colours did not work as well as one would hope.
That’s a lot for people to digest, but, overall I think the clearest visualisations go to the ONS. They lack the commentary that can be brought by journalism organisations, e.g. the BBC, but one needs a clear and powerful visualisation before one can start writing an analysis.
Credit for the ONS results goes to the ONS Data Visualisation Centre, for the Guardian infographic credit goes to Paul Scruton and Mark McCormick, for the Northern Ireland piece credit goes to John Burn-Murdoch, and credit for the BBC goes to the BBC.
Let’s face it, governments need money to function. If you want a large military, you have to fund it. If you want pension system, you have to fund it. If you want medical care for the old, the sick, and the poor, you have to fund it. If you want to give everyone unicorns made of rainbow beams, you have to fund it. And…well…nevermind.
The point is taxes. After an election that focused so heavily on them, we’re still debating them. But here are some facts about them from the New York Times. The designers, Mike Bostock, Matthew Ericson, and Robert Gebeloff used small multiples of line charts—and lots of them—to look at who pays taxes by income band and how they pay different types of taxes. I found particularly interesting the points made near the bottom of the piece about how the progressive tax system is increasingly less so.
But how do these taxes compare to spending? In a separate graphic for the same article, a stacked bar chart compares revenue to expenditure. With the exception of the balanced budget during President Clinton’s administration, we have been outspending our revenue since 1980. While statements to the effect of the US national budget needs to be managed like a US household budget are both overly simplistic and naive, there is a truth in a long-term mismatch between revenue and expenditure might cause problems. That is why many see the deficit and our debt as a medium-term problem facing the United States.
Credit for the first piece goes to Mike Bostock, Matthew Ericson, and Robert Gebeloff.
I make a lot of maps in my line of work. Often times, they are not particularly interesting. Mostly because they follow similar patterns to this. More stuff is bought and sold where there are more people. More stuff is bought and sold where more people have more money. Et cetera, et cetera.
Maps are sometimes very useful. But I have a saying when people ask for a map of some kind of data tied to geographies: Maps are not silver bullets. That is to say, just because you throw data about countries, states, or counties onto a map does not mean you are going to see anything worthwhile let alone new or unexpected.
The Boston Red Sox hired John Farrell this weekend to be their manager just one season after hiring Bobby Valentine for the role. There is a lot to be said about just who is to blame about the Red Sox’ awful season. But it was pretty awful. How awful? The Boston Globe shows us in this interactive piece.
It’s a series of small multiples of line charts. However, one of the big problems with the infographic is that the labels are entirely absent. As best I can tell the line is the number of games over .500, i.e. an even split between wins and losses. But, it could be more clearly called out if not in the legend or on the axes than in the title.
But over all it does put this past season into a sober perspective.
On Friday we received the monthly jobs report. And the furore that arose with it. Principally the anger stemmed from right-leaning commentators who believed that the non-partisan Bureau of Labor Statistics, a government agency tasked with collecting data on employment among other metrics, “cooked the books”/ “massaged the figures”/ flat-out lied to show a significant drop in the unemployment rate that could not be attributed to people who had stopped looking for work—a cause of some earlier drops over the last few years. As someone who works with data originally collected from national statistics offices across the world on a daily basis, those claims touched a nerve. But I shall leave that rant for another time.
Instead let’s look at the New York Times piece that quickly followed on the outrage of fools. We can look at and analyse the data in different ways—the origin of the phrase lies, damned lies, and statistics—and surely the Republican and Democratic parties would do just that. They did. This New York Times piece shows how that can be—and was—done. It involves points of reference and context.
First the facts:
Then how the Democrats spin them:
Finally how the Republicans spin them:
But the facts themselves do not lie. 114,000 non-farm jobs were added to payrolls. The unemployment rate fell to 7.8%, the lowest rate since January 2009.
Credit for the piece goes to Mike Bostock, Shan Carter, Amanda Cox and Kevin Quealy.