There was a lot of news this past weekend. So we’ll start with the important stuff first. An infographic about the big baseball trade between my Boston Red Sox and the Los Angeles Dodgers. The advantage of a story breaking over the weekend is time to get something together for Monday.
Today’s post features a Sankey diagram from the New York Times that looks at how the Obama administration has been failing to help homeowners with mortgage problems. Less than 25% of applicants have seen successful modifications of their home loans. The diagram here clearly shows the process and the failures that have led to so many Americans not receiving the help they sought.
Credit for the piece goes to Alicia Parlapiano.
A little while ago the World Bank, generally a rich-country club that doles out loans to the developing world, published an infographic looking at mobile phones and their presence in the developing world.
The piece supplemented a report and is rather large. It actually exists as two separate images. The cropping below focuses just on how people in the developing world use mobile phones. Overall the piece is a bit weak in terms of data visualisation types and some of it is a bit confusing, but the story is clearly worth telling. And fortunately there are more hits than misses.
If you haven’t heard, we share a border with Mexico. And we patrol it. And the Washington Post published a graphic looking at the patrolling of the US–Mexican border.
Credit for the piece goes to Anup Kaphle and Bill Webster.
Oil, sweet oil. We Americans love the stuff. Like too much of anything, though, that can lead to some problems. This post isn’t about that. But rather it’s about a New York Times graphic on how even though we are learning to check our sweet tooth, we are importing more oil from the Middle East relative to other oil exporters, like Mexico.
Today’s post comes via a co-worker of mine and is from the Pew Research Center’s Forum on Religion and Public Life. The infographic is of the long-running image type, but in this case is neatly sliced into digestible morsels of tasty infographic-ness. Below is a cropping of the longer piece. It looks at how Muslim populations in different countries feel about the importance of their religion in their daily life.
So the Olympics are over. But before they began, I and some co-workers made a prediction about how the United Kingdom and their Team GB would perform. We predicted 65 medals. How did the United Kingdom fare? They won 65 medals. This is a follow-up infographic about what made the United Kingdom a winner at the 2012 Summer Games. It’s a bit larger than the first version, but this one also includes new data and revisits some of the earlier themes.
Another important (and correct) prediction was that China would slip and not reach 100 medals. This should happen after experiencing the host nation bump. While we did not create a number for China, they scored only 87 medals. Another correct prediction.
All in all a very successful series. (Created for my employer Euromonitor International, as the usual disclaimer goes.)
The New York Times has been conducting surveys or polls of voters and likely voters in swing states, i.e. the states where the 2012 election will be decided. The nice thing about the piece is that it allows the user to select different sets of demographics through which one can view the questions asked. Furthermore, the user can mouse over the individual bar of a response and see the whole set.
The Olympics bring out the best. Well, at least in athletics. In terms of infographics, not always so much. This piece from CNN is a fairly unorganised mess with lots of individual datapoints. It’s a shame to see this at CNN when so many other news outlets are doing quality graphic work for the Olympics.
Over the weekend, the New York Times looked at how the Obama campaign has been spending its cash.
I appreciate the value in these sort of block charts, but, I wonder if a bar chart would not have been more clear for the comparison. I like the block charts when the designer is rearranging the data in different ways. For example, if the data set also included when the cash was spent, the blocks could be re-ordered into a day by day or month by month analysis.
