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.
Fear not, this graphic makes about as much sense as the title. The concept is actually a worthwhile exploration of the variation in caffeine across cups of coffee from different cafes and coffee shops. But, this visualisation fails at showing it.
Coffee Pie Charts
Remember, pie charts show the piece amongst the whole. What is the whole in this case? A cup of coffee? No, the data labels indicate milligrams per fluid ounce. It appears as if 60mg./fl. oz. is the whole. A bit arbitrary that. So what happens if you lose the trite pie as a cup of coffee device and simply chart the values. Oh wait, that’s not very hard to do. (I also threw in what I believe to be the benchmark for an average cup of brewed coffee, though I could be wrong.)
Coffee Bar Chart
Much clearer. More concise (I used less than the original’s dimensions).
Credit for the original piece goes to Dan Gentile.
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.
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.
Today’s graphic looks at the backlog of aircraft delivery, i.e. the manufacturing of civilian aircraft. Why? Because Boeing is attempting to increase production of its 787 Dreamliner. And this weekend I arrived in Chicago from Warsaw via a 787.
This is a really nice piece from Thomson Reuters that looks at the manufacturing lines for both Boeing and Airbus and how many planes have yet to be delivered. The annotations really help to explain some of the stories behind some of the aircraft and their delayed deliveries.
Aircraft manufacturing backlog
Credit for the piece goes to Simon Scarr and Christian Inton.
After two weeks out of the country, I come back and find early this morning (thanks, jet lag) an interactive article published by the New York Times on income mobility. What does that mean? From a medium side, a long narrative interspersed with charts and graphics with which the user can interact to uncover specific data about specific elements in the dataset. From a content side, income mobility means the movement of an individual from one group of money earned to another, e.g. a poor person becoming a millionaire. The piece is fantastic and you should take the time to go read and interact with it.
A map shows the broad context of the data to be looked at in the story
For some time now I have harped on about the need to annotate and contextualise datasets. Too often, large datasets paralyse people; their eyes glaze over and they simply gaze at a graphic without seeing the data, the story, the information. Little notes and blurbs of text can help people synthesise what they see with what they read with what they know to gain better understanding. But in this piece, by combining a lengthy article—very well written although that is not the focus of this post—with powerful interactive maps and graphics, the New York Times has created a powerful piece that states and then proves the point of the article. And while doing all of that, by making the datasets explorable, the Times also allows you to find your own stories.
A story-like piece lets you choose an area and an income to see how the article's topic plays out
Lastly, in the credits section at the end you will see this piece required the input of eight individuals (though I know not in what particular capacities). Clearly, for the Times this is not about to become a regular type of infographic/datavis/journalism piece. But when will skill sets be democratised or dispersed enough that smaller teams can create similar scale projects? That will be interesting to see. However, the Times certainly leads the States if not the world in some of the best information design pieces and undoubtedly this will push other publishers of similar content in this direction.
Ultimately people want to know who's best and who's worse and where they fall and this chart does that at the end of the piece
Credit for the piece goes to Mike Bostock, Shan Carter, Amanda Cox, Matthew Ericson, Josh Keller, Alicia Parlapiano, Kevin Quealy, and Josh Williams.
If all is going according to plan, I should be somewhere in the Carpathian Mountains at this point, specifically in the Presov region of Slovakia. So as a reminder of just what that means, here is a (recycled) piece I created this time last year about the Carpatho-Rusyns (sometimes known as Ruthenians) living in Slovakia. Click the image to go to the full infographic.
Cropping of the Rusyns of Slovakia
Credit goes to me for the piece, but to the statistics office of Slovakia for the data.
Hong Kong—and to a similar extent Macau—is part of China, but at times not so much. Because of the long history of British control through their colony, the people of Hong Kong, Hongkongers, are accustomed to a more liberal, democratic, and perhaps Western lifestyle than those of mainland China. Since the British handover, a local university has been asking the inevitable question of “Are you Hongkonger or Chinese?”. This interactive piece from the South China Morning Post looks at how that answer has evolved over nearly 20 years.
Hongkonger identity
The piece presents a broad overview on the right with the specific survey results displayed larger on the left. Broadly speaking, the piece is successful. In particular, the decision to highlight the particular survey on the right brings that into focus without losing the context of the historical results. And providing a timeline beneath the larger stacked bar chart on the left offers a second means of choosing a survey of interest.
Yet I think the piece lacks two, perhaps three, elements that would improve the piece. First, sometimes I like to see the numbers for data visualisations. Adding a hover or mouseover state would help with that. Second, while the chart on the left includes a 50% line, I wonder if that would not also be helpful in the historical display on the right. Thirdly, and perhaps not too important for those not terribly interested in the data, the overall piece states the sample size for all surveys being within a range. People wanting more data on the survey responses might be interested in seeing the sample size per survey.
Credit for the piece goes to Simon Scarr and Joe Lo.
Last week I looked at a piece from the Washington Post about the possible impact of the Supreme Court rulings on gay marriage in the United States. But with the rulings yesterday, we step back and look at globally how the progression of gay rights has taken steps forward or backward.
The National Post looked at the reversal of bans of gay marriage as well as polling from several countries to look at changing opinions and perspectives across the world. Fascinating/horrifying are some of the stories about specific countries in the map.
Gay acceptance
My only real criticism is that the colour-coding of regions seems a bit jarring. I wonder if grouping countries by region would not have allowed the same data to be presented in a bit quieter tone.
