Given the absence of a post yesterday, I took some time to do a small catch-up piece for you all. Those who know me offline are well aware that I document many things about my life including when I happen to drink tea. (And that’s often.) Finding myself with some unexpected time, I looked through the data that I have amassed since 1 January through to 28 March. While I aim to do more with this dataset someday, for now consider this a start. And now a self-surveillance infographic. On drinking tea.
It is interesting to note that I have in fact had tea every single day so far this year.
Earlier this month I posted about how the New York Times looked at the polarisation of the US Senate. Now the National Journal has another, similar visualisation attempting to explain the political gridlock that was picked up by the Atlantic.
For those wondering, the National Journal ranks senators on their conservativeness–liberalness by their votes and that is the plotted data.
Credit for the piece goes to the National Journal.
Public Policy Polling had a survey in February where they polled respondents on whether they had favourable or unfavourable attitudes towards states, or if they were not sure. As a Pennsylvania transplant to Illinois, I can say that Pennsylvania came out a bit better than Illinois. But how about your state?
This piece in the Globe and Mail of Toronto looks at smartphone usage by operating system through a comparison of Canada to both the United States and Japan.
While I understand the need for aesthetic distinction from having an entire page of bar charts, these ring or donut charts are a touch misleading. Because of the space between rings, the radius of each circle from the central Android icon is significantly increased. This of course proportionally scales up the length of each segment within the rings. In short, it becomes difficult to compare segments of each ring to the corresponding segments on the other rings without looking at the datapoint. And if you need to look at the datapoint, one could argue that the infographic has failed from the standpoint of communication of the data.
Beneath is the original (with the legend edited to fit into my cropping) with two very simple (and hasty) reproductions of the data as straight pie charts placed next to each other and then as clusters of bar charts grouped beneath each other. I leave it to you the audience to decide which is easiest to decode.
Credit for the Globe and Mail piece goes to Carrie Cockburn.
So apparently last night actors, directors, and others associated with the production of films won little statues. (And then probably celebrated with fancy foods and wines.) Yes, last night was the Academy Awards. But who is this Academy that decides upon the best films and performances?
As it turns out, the demographics of the Academy do not quite mirror those of the broader country. Just over a week ago, the Los Angeles Times looked at the Academy and visualised its membership, discovering the details of which was itself a journalistic feat.
After a broad overview with pie charts and such, each branch was mapped as a choropleth to the Los Angeles area. Those members from outside the LA metropolitan area were given small squares to represent their cities.
As someone not at all familiar with Los Angeles and its neighbourhoods, perhaps where the members of the various branches of the Academy live is actually somewhat interesting. However, I fail to understand the value in that. More useful is the idea of breaking out a socio-economic demographic and mapping that data. And if that had been the case here we almost have a set of small multiples. These are just a bit big.
Overall, a solid body of work.
Credit for the visualisation piece goes to Doug Smith, Robert Burns, Khang Nguyen, and Anthony Pesce.
Yo, Philly, apparently Pew did a survey on what Philadelphians think about Philadelphia. And what better way to talk about a survey than through an infographic. So thanks to the Inquirer, that is what we have.
The interesting bit is that while there is a black-and-white, presumably print version, the website broke the whole graphic into its components and made them larger for web viewing. But, if you look at this example from the segment on immigration and diversity, they ought to have left colour alone. The two segments Bad Thing and No Difference use the same colour when they clearly do not mean the same thing. The black-and-white version keeps those two as separate greys.
Presidents’ Day is actually Washington’s Birthday. That makes sense when you consider how Washington is still a much beloved president. And according to a recent survey, the most favoured president.
What is worth nothing is that most Americans know little of the 19th century presidents, save the big names like Lincoln, Grant, and (Teddy) Roosevelt. Not until the other Roosevelt (FDR) do we start seeing a decline in “Not Sure” responses. But, by far, Washington and Lincoln are the most favoured presidents.
The questions for all of us on this holiday are who’s your favourite? And how does he stack up? (Get it? Eh, chart humour.)
The previous two entries have been about visualisations of the administration’s budget proposal for 2013. Today’s will be (probably) the last in such a theme. Perhaps some wonder if not the bubbles and circles of the Times’ visualisation, what?
Some might answer bar charts. Because we all love bar charts. But, as in this example from the Philadelphia Inquirer, sometimes we are left wanting more.
The graphic captures the size of the budget by general spending and revenue areas, but misses the story on how each has changed on account of this new era of austerity. What colour was in the previous examples, here instead we see it used to group the different categories of spending. From an aesthetic standpoint, the depth in the third dimension is distracting and the space between the two stacked bars (and the line separating them) does not aid in comparison.
In brief review, of the three visualisations presented over the past three days, I have to say that the Washington Post’s tree maps are the most useful from a design perspective, but sadly lacks in the granularity we see—regardless of the clarity or lack thereof in presentation—in the piece from the New York Times.
The main visualisation shows spending by department compared against revenue, the difference between being the grey box of deficit. Of note is that this piece also contains the revenue, and not just the spending, unlike the New York Times version. You can also see that the level of granularity is different; the Post looks only at department-level data while the Times delves into specific programmes. Critically, the arrangement of the budget components in this graphic makes it easier to attempt comparisons of area and thus weigh Education against Defence.
If you click a particular department, you swap out the revenue side of the budget equation with the details of previous spending in that area, broken down into presidential administrations that are coloured by party. The same holds true for revenue, clicking on those reveals the amount of revenue taken in by administration. Of some note is the deficit, which shows how we did briefly have a budget surplus back in the 1990s and how that compares to the deficits of today.
All in all, while the level of detail is not present in the Post’s visualisation, I find that the comparison at the departmental level stands strongly in the favour of the Post. The Post also benefits from presenting the other side of the budget story, revenue. Unfortunately, if you care to dig any deeper into any particular part of the budget, say weapons procurement or education grants, you cannot in the Post. That leaves space for a nicely designed, detailed, clear, and informative piece should someone or some organisation be so inclined to build it.
Credit for the piece goes to Wilson Andrews, Dan Keating and Karen Yourish.
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.
The article, while a bit longer than usual, is well worth the read. The charts with the explanation make for a compelling argument.