Today we look at a piece that focuses on my native (and favourite) state: the Commonwealth of Pennsylvania. (Along with Virginia, Massachusetts, and Kentucky, we self-identify as a commonwealth and not a state.) FiveThirtyEight examines how Pennsylvania and its shifting political preferences might just be the key (get it? keystone) to the election for both candidates. The crux of the article can be seen in the map, but the whole piece is worth the read. If only because it mentions Pennsyltucky by name.
My apologies to you for the blog being down the last week and a half. This is what happens when I get 33,000 spam comments in the span of 24 hours: the blog crashes. Rest assured, I have lots of things to post.
But for today, we are picking up after a yuuugge night for Donald Trump so let’s get on with the data visualisations. Trump decisively won Connecticut, Delaware, Maryland, Pennsylvania, and Rhode Island with a majority of votes in every state. As he made sure to point out, winning 50–60% in a three-way race is quite difficult to do. Simply put, Cruz and Kasich got destroyed.
Why is that? Well a few days ago—can you tell I meant to post this then?—David Wasserman over at FiveThirtyEight posted an insightful article about the various counties thus far contested and how, when divided into quadrants based on socioeconomics and conservativeness, Trump has won three out of four quadrants. The whole article is worth the read.
Flags are cool. And I will openly admit I may have designed several of my own over the years. So thanks to my good friend for pointing me in the direction of this project from ferdio that breaks down flags across the world. If you are at all curious about how many flags use particular colours, shapes, sizes, you need not go any further.
Yesterday I took a look at the Alaskan Airlines and Virgin America merger. Part of the disappointment on the internets centres around the service and experience delivered by Virgin. I mean who doesn’t like mood lighting, right? Well the Economist took a look at international airlines by both price and service. And if we use Virgin Atlantic as the best proxy for Virgin America, you can see why people prefer it over American carriers.
As I mentioned earlier this week, I visited London for work for a week and then took some rollover holiday time to stay around London and then visit Dublin. But now I am back. And this week that has meant all the jet lag. And while everybody experiences jet lag and recovers from it differently, I wanted to take a look at my experience. The data and such is below. But the basic point, it is about four days before I return to normal.
What is missing, unfortunately, is the Chicago-to-London data. Because anecdotally, that was far, far worse than the return flight.
It’s Monday, folks. And for most of us that means going back to work. Which means dressing appropriately. And that’s about as far as I’ve got introducing this subject matter, because I wear a dress shirt and tie everyday. Not a t-shirt. But we’re talking t-shirts. Specifically their sizing.
Threadbase is a New York startup looking to do some cool things with data about t-shirts. But that requires having data with which to play. And they are starting to do just that. Their opening blog post has quite a few data visualisations.
The dot plot above charts the sizes by dimension for various brands and makes. I might quibble with the particular colours as the red and purple are a bit on the difficult side to distinguish. Symbols could be away around the issue. But the only real issue is that on my monitors the full image runs long and I lose the reference point of the actual dimensions in inches.
But the piece is worth the read for the cyclical changes in dimensions.
Mostly it’s just a pity that I’m not a jeans and t-shirt sort of guy.
Sorry for not writing the last few weeks, but I was on a much needed holiday. But I’m back now. And first things first, one of my good mates got engaged whilst I was back in Philadelphia. And so in honour of that we have today’s piece.
As the graphic might hint, it’s about marriage. The piece dates from September of last year—2015 and I think I will have to get used to that for a few weeks—and looks at the demographics of marriage mostly in the United States. The chart above in particular looks at men that are married at every age by year, i.e. how many men aged 30 were married in 1960 versus 2013.
The news this morning carried the latest polling data out of Iowa for the Republicans. And in that state, Ted Cruz now polls above Donald Trump. And so I wanted to share this post from the Economist last week that looks at how Trump rises every time he says something ridiculous. Could it just be that we should expect even more ridiculous this week?
Credit for the piece goes to the Economist’s Data Team.
We go from one crisis to another, as we go back to Syria. This piece from Bloomberg is very nicely designed and is almost entirely in black and white. We often think that because computer, everything needs to be in a rainbow of shiny, shiny colours. But here we have places where the designers smartly used patterns and smart labelling to avoid the need for colour.
Credit for the piece goes to Cindy Hoffman, Dave Merrill, Chris Nosenzo, Mira Rojanasakul, and Blacki Migliozzi.
So yesterday we reimagined a less-than-stellar BBC chart. Today, we look at a good chart from the BBC about climate change, timed to coincide with the start of the Paris climate talks. This comes from an article with six charts related to climate change, but it is the best in my mind.
Nothing but nice design here with the use of colour to highlight the top ten hottest and coldest years over the last 225+ years. But it really comes alive when animated and tells the story how those coldest years occurred at the beginning of the set and the hottest are among the most recent years.
Credit for the piece goes to Emily Maguire, Tom Nurse, Steven Connor, and Punit Shah.