We have all heard talk about cutting cable, i.e. unsubscribing from cable television. But the question is what is replacing it if anything? Fortunately, this really nice graphic produced by Quartz shows the market over the course of the last five years.
Cutting the cable
It is a really nice use of small multiples and the power of not overlapping size and growth charts, or combo-charts, just because you can. Different metrics deserve different charts. The important part is placement, and that’s where a good designer can make sure to place relevant data near its partner.
We already got to Mars. At the end of a week of maps and map-related things. Here’s a map of Mars. Well, sort of. It’s more of a map of Mars as explored by Curiosity. (Remember that guy?)
It’s an interactive piece from the New York Times that charts out just where the rover has driven and photographs of the stops along the way. There’s also a nice little chart that shows just how much of the trip has consisted of driving.
A day in the life…on Mars…
Credit for the piece goes to Jonathan Corum and Jeremy White.
This map comes from the Washington Post and it uses the American Community Survey to explore languages spoken by Americans at home other than English.
Who speaks what?
I got stuck (in a good way) on the seemingly random counties of German speakers. After I poked around a bit, I found one where almost 50% of the county speaks German. After some quick investigation, it turns out that Holmes County, Ohio is a centre for the Amish population. The Amish, of course, will often speak German or Pennsylvania Dutch, thus accounting for the abnormally high percentage of German speakers.
Credit for the piece goes to Dan Keating and Darla Cameron.
Today’s graphic comes from Thomson Reuters. It charts the success of 3D movies that have been released and how long those movies stayed in the theatres.
3D movie success
Credit for the piece goes to S. Scarr, G. Cabrera, and K. Pong.
Today’s post is a small interactive from the Wall Street Journal that allows the user to explore consumer spending not by category of spending, but rather the type of store in which they are spending, e.g. grocery retailers. Consumer spending is a fairly important measure of the US economy since so much of our economy depends upon it (I want to say roughly two-thirds, but I cannot recall exactly).
Comparing retail spending by type of store
This piece has a few interesting things going for it. Firstly is the ability to compare and contrast three different retail channels (My screenshot compares only two). An unlimited amount would have been far too many, but three is a manageable number, especially in the various charting components used.
The tree map is interesting. I like the idea of using them, but I am not sure this is the best application. First, a tree map is fantastic for showing hierarchy. If, for example, there were sub-channels of the big retailing types, they could be nested within, well, squares or rectangles. But here the size and growth could have been compared perhaps more easily in a scatter plot. Secondly, I cannot determine the order for which the channels have been arranged. Clearly it is not by size, because the small ones are near the top. Nor is it reverse, because there are smaller ones where there should be larger ones.
Then the bar chart. An interesting idea, to be sure, of aggregating the sales per channel to see their total value. But if the goal is to compare them, would not a line chart looking at both separately not in aggregate show size and relative gains/declines against the other?
Driving can be dangerous. But perhaps most so in the developing world. The Pulitzer Center created this interactive map to allow users to explore just how dangerous driving can be.
A look at road deaths in Kenya
Little windows provide details on countries the user rolls over. This data looks at deaths per 100,000 people, killer/victims, and lastly a rating of law enforcement across several different issues. The map also includes links to stories on the website as well as an information panel that related small bits of information about selected countries.
Credit for the piece goes to Tom Hundley and Dan McCarey.
Major League Baseball is set to suspend Alex Rodriguez this morning—if the news reports are true. That will all but end the season for Rodriguez, though he could well play through his appeal so you never really know. But what does this mean for the Yankees and their offense?
The New York Times put together an interactive scatter plot charting the annual salary against the number of hits (roughly a measure of offensive production throughout the year) with benchmark lines for the league average of both. First, the user can see the team averages.
Comparing baseball teams salaries vs. offensive production
At the team-level, one can see that, roughly speaking, the more money a team pays to hitters, the more productive the team. Production it should be noted, does not necessarily equal wins. Look at the Angels, who have some of the most hits, but are in fourth place (out of five) and in a difficult place to make the playoffs.
Quick comparison of the Red Sox's hitters to the Yankees' hitters
But then the user can switch to the top-10 paid hitters on each team. (Four presets are offered beneath the piece, but click on a player from any team and his compatriots will appear.) You can see how the Yankees are hitting poorly in comparison to the Red Sox. (The only reason the Yankees are not truly awful is because their pitching has not been horrible.)
So if Rodriguez is suspended for this year and next, maybe they can use his salary for next year to buy a one-year free agent that isn’t at the bottom right of the this chart.
Credit for the piece goes to Mike Bostock and Joe Ward.
Happy Friday, everyone. Today’s post comes via colleagues of mine in London, who shared with me the Guardian’s selection of 16 useless infographics. They are shit infographics. Well, at least one is. Check them out and you’ll understand.
Using maps to explain maps…
Credit for the selection goes to Mona Chalabi. Credit for each infographic belongs to the infographic’s respective designer.
A map? Again? I know. But trust me, this one is interesting. For those of you who do not know, Boston’s Thomas Menino is not running for reelection this year. By the time he leaves office, he will have been the mayor of Boston for over twenty years and so this year is the first open election in a long, long time.
So what’s better than graphics for election-related data? Graphics with a medieval/Renaissance/fiefdom aesthetic, that’s what. With a little bit of fun, the Boston Globe mapped out the local areas of strength for the 12 candidates for mayor. The residence of each is denoted by a castle keep while areas of strength, location of donors, and key voting areas are signified in different colours. And the map’s background? Well, you can see for yourself.
Boston mayoral candidate map
Credit for the piece goes to Alvin Chang, Andrew Ryan, Javier Zarracina, and Matt Carroll.
I don’t often write about maps, especially of the choropleth kind. In many cases I choose not to because so many of the maps are one-dimensional: how fast is x growing across the world; which is predominant across the world, y or z? So I was pleasantly surprised by the Economist yesterday when they published this interactive map on the scourges of hepatitis and HIV.
Hepatitis vs HIV
Quickly put, the map is a success. It shows a clear geographic pattern; the developed/Western world along with the Middle East and Asia have a larger problem in hepatitis than HIV whereas Africa and Latin America are dealing moreso with HIV. (Admittedly, the fact that 117 out of 187 countries are dealing more with hepatitis is lost because so many of the countries are small in area.) But, the really nice bit about the map is not just the colour by virus, but the tint by comparative ratio. The darker the colour, the stronger the one virus over the other.
Lastly, from a data perspective, I just wonder if the ratios could not be adjusted for population, or deaths as a percentage of the national population? I would be curious to see if that would yield interesting results.
Credit for the piece goes to C.H., R.L.W., J.S., and D.H.
