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.
There are two things one is not supposed to discuss in mixed company, and let us face it, the internet is some rather mixed company. One of those things, politics, I frequently mention and bring up on this blog. The other, religion, I do not.
Until now. (I think.)
From the National Post comes this work on the size and distribution of the world’s religions.
Follow the money is almost always good advice. And in this case, the journalists over at ProPublica have done just that. They have visualised just where the campaign (and Super PAC) dollars are going using an interactive Sankey diagram.
And then for those interested in how this was made, ProPublica provides those details as well.
Via my colleague Lauren Beth.
Credit goes to Al Shaw, Kim Barker, and Justin Elliott.
The civil war in Syria rages on. The following graphic from the New York Times accompanies the article and uses a calendar-style timeline to look at the mounting death toll. The visualisation type appears more and more often for time-based data sets shaped around days; we all (usually) understand how calendars work and are shaped.
In this particular case, specific key dates and images are brought out of the timeline and featured on the left. These provide an additional context to the human side of the story that may otherwise be left in the dates and deaths on the right.
A problem with such a design is the length of the year, which might preclude users of small screens from being able to see the entire year in one screen-height. I am left to wonder about whether the user can make an adjustment to a horizontally-scrolling calendar and if in the future such arrangements may better take advantage of widescreen monitors.
From FlowingData comes a post to an interactive piece by Bloomberg that looks at the geographic distribution of different heritage—read heritage, neither race nor ethnicity—groups. (Its choice of groups, however, is slightly contentious as it omits several important ones, including African-Americans.)
I would say that a typical map like this would simply plot the percent of each county, state, or other sub-division for the selected heritage group. Much like below, as I chose the Irish.
Bloomberg’s piece is a bit more interesting than that because of the ability to compare two groups, to see where they overlap and where they diverge. In doing so, they created a divergent choropleth that can show the subtleties and nuances of settlement patterns.
Charles Booth was a 19th century social scientist living in Britain. He famously investigated poverty and mapped out which parts of London were teeming with vicious, lower-class criminals or well-to-do upper class folks. Today, one might use a simple choropleth style to paint whole swathes of London by postal districts or constituencies or some such. But, Booth went street-by-street and house-by-house colouring blocks of London’s residential areas until he arrived at a map far more complex—and thus ultimately more telling—of the intricacies of London’s social structure.
Oliver O’Brien has created a modern take on Booth’s approach to investigate the housing demographics of the UK, which ignores the large areas of the British countryside that are devoid of homes and thus focuses on the denser residential areas of the UK’s major cities.
Censuses seem to be a natural dataset for such work, but I wonder if in the future we will be able to apply such data visualisations to other geographically-tied data.
Over at the Guardian, people are playing with data about drug use. The data comes from the Global Drug Survey, and Ian Taylor and the Guardian worked together to create this interactive piece that lets you either browse drug use comparisons between Americans and Brits or compare two specific drugs between our two peoples. It looks like we al drink though…
Credit, again, goes to the Guardian and Ian Taylor.
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?