Brexit’s Impact on Irish Shipping

Today’s post is, I think, the first time I’ve featured the Politico on my blog. Politico is, I confess, a regular part of my daily media diet. But I never thought of it as a great publication for data visualisation. Maybe that is changing?

Anyway, today’s post highlights an article on how the Irish shipping/logistics industry could be affected by Brexit. To do so, they looked at data sets including destinations, port volume, and travel times. Basically, the imposition of customs controls at the Irish border will mean increased travelling times, which are not so great for time-sensitive shipments.

This screenshot if of an animated .gif showing how pre-Brexit transit was conducted through the UK to English Channel ports and then on into the continent. Post-Brexit, to maintain freedom of movement, freight would have to transit the Irish Sea and then the English Channel before arriving on the continent. The piece continues with a few other charts.

Brexit strikes again
Brexit strikes again

My only question would be, is the animation necessary? From the scale of the graphic—it is rather large—we can see an abstracted shape of the European coastlines—that is to say it’s rather angular. I wonder if a tighter cropping on the route and then subdividing the space into three different ‘options’ would have been at least as equally effective.

Credit for the piece goes to Politico’s graphics department.

Bus Transit in Philadelphia

I have lived in Philadelphia for almost ten months now and that time can be split into two different residences. For the first, I took the El to and from Centre City. For the second, I walk to and from work. I look for living spaces near transit lines. In Chicago I took the El for eight years to get home. But to get to work, I often used the 143 express bus. Personally, I prefer trains and subways to busses—faster, dedicated right-of-way, Amtrak even has WiFi. But, busses are an integral part of a dense city’s transit network. You can cram dozens of people into one vehicle and remove several cars from the road. Here in Philadelphia, however, as the Inquirer reports, bus ridership is down over the last two years at the same time as ride-hailing apps are growing in usage.

For those interested in urban planning and transit, the article is well worth the read. But let’s look at one of the graphics for the article.

Lots of red in Centre City
Lots of red in Centre City

The map uses narrow lines for bus routes and the designer wisely chose to alternate between only two shades of a colour: high and low values of either growth (green) or decline (red). But, and this is where it might be tricky given the map, I would probably dropdown all the greys in the map to be more of an even colour. And I would ditch the heavy black lines representing borders. They draw more attention and grab the eye first, well before the movement to the green and red lines.

And the piece did a good job with the Uber time wait map comparison as well. It uses the same colour pattern and map, small multiple style, and then you can see quite clearly the loss of the entire dark purple data bin. It is a simple, but very effective graphic. My favourite kind.

Still haven't used Uber yet. Unless you count the times I'm being put into one by a friend…
Still haven’t used Uber yet. Unless you count the times I’m being put into one by a friend…

Anyway, from the data side, I would be really curious to see the breakout for trolleys versus busses—yes, folks, Philly still has several trolley lines. If only because, by looking at the map, those routes seem to be in the green and growing category. So as I complain to everyone here in Philly, Philly, build more subways (and trolleys). But, as the article shows, don’t forget about the bus network either.

Credit for the piece goes to the Inquirer graphics department.

Education and Eatery Preferences

Last week the Economist posted an intriguing article about the relationship between culinary choices/preferences and education and income. It began with an article by David Brooks in the Times, which I have not read, talking about how culture can create inequality as much as economics or government policy. The Economist then conducted a survey looking at the relationship between food preferences and both education and income. This is a screenshot of some of their results.

To be fair, I rarely eat sushi because I don't much care for it.
To be fair, I rarely eat sushi because I don’t much care for it.

Yes, correlation is not causation, but these are some fascinating findings that suggest we should perhaps explore the idea in more depth.

As to the graphics, we have nothing super sophisticated, just a matrix of small multiples. But that goes to the point of “simple” graphics sometimes can do wonders for a story.

Credit for the piece goes to the Economist graphics department.

Stabby Stabby Sexy Sexy Stabby Stabby

Happy Friday, all.

This past Sunday Series Seven of Game of Thrones began. And, no spoilers here, but it basically served as an episode to set the table for this series and its plot lines. But this piece from the Washington Post does a good job of summarising the deaths in the show over the previous six series. That does have some spoilers, but I chose my screenshot from minor characters in Series One. So I should not be ruining it for too many people.

MInor deaths and story locations, no spoilers for those of you who want to start watching the show
MInor deaths and story locations, no spoilers for those of you who want to start watching the show

Credit for the piece goes to Shelly Tan.

London in Small Multiple Form

You all know that I love small multiples. And we have been seeing them more often as representations of the United States. But today we look at a small multiple map of London. The piece comes from the Economist and looks at the declining numbers of pubs in London. With the exception of the borough of Hackney, boroughs all across London are seeing declines, though the outer boroughs have seen the largest declines.

Mini London
Mini London

The only thing that does not work for me is the bubble in each tile that represents the number of pubs. That gets lost easily among the blue backgrounds. Additionally, the number itself might suffice.

Credit for the piece goes to the Economist graphics department.

Home Run Distance

Apologies for the lack of posts recently. Allow me to blame work, travel, and sickness. But let’s get back on track this week—for me now a short one—with this post from FiveThirtyEight about the distances travelled by home runs.

The piece uses data up to the All Star break, and looks at how far the home runs would have travelled. Of course, the data set is fairly recent in terms of tracking just how far home runs went. That is, there’s nothing for Ted Williams or Babe Ruth. But this screenshot from the article is Seattle slugger Nelson Cruz.

Cruz has left the yard. And also downtown Seattle
Cruz has left the yard. And also downtown Seattle

Personally, I would have loved to have seen one for David Ortiz.

Credit for the piece goes to Neil Paine.

Not Alone for Trivia

Well after the last two weeks of recording solo trivia performances, I decided that this week I would showcase a team effort.

A non-solo performance
A non-solo performance

And we finally placed, ending the performance tied for first place. But if you look closely you will see the final score has us at second. Why when we were tied with the same number of points? Because tiebreaker. And after I was selected to represent the team, I needed to respond, within three seconds, with the names of Tom Hanks films in a back-and-forth response.

I could name only Saving Private Ryan and Castaway. My competitor, she named three. They won.

Another Solo Pub Trivia Performance

This past Wednesday I once again ended up playing trivia at the pub solo. Once again, I decided over the final pint that I would attempt to visualise my performance.

One thing to keep in mind is that on Wednesday there were fewer teams competing—five instead of nine. And while I never placed higher than tied for third, this week’s bar charts show how I was incredibly competitive until the final music round.

Music and celebrity are clearly not my strong suits
Music and celebrity are clearly not my strong suits

Despite an abysmal performance at naming celebrities as they were as children, my near-perfect second round kept me only five points behind first place. And a perfect fourth round meant heading into that final round I climbed back to being only three points back. Thankfully I knew more of the songs this past week. And enough to not finish last. But, I was close enough that a perfect round would have been enough to still place first.

Super helpful that Lord of the Rings questions appeared a few times.

Clear the Cache

Some of the aforementioned work that has been keeping me busy is the design of a new part of a website. And one of the most common things I hear when I ask why something is not displaying as I intended is “Have you cleared the cache?”. And that is why this Friday’s piece from xkcd is super relevant to me.

I could have used this table earlier this week
I could have used this table earlier this week

Credit for the piece goes to Randall Munroe.

The Donald and The Donald Subreddit

I don’t use Reddit. But things begin to made sense for me in this article from the Economist as it explained the origins behind Trump’s weird tweet of himself beating up a CNN-headed wrestler.

Unfortunately I don't understand how Reddit works well enough to make full sense of these
Unfortunately I don’t understand how Reddit works well enough to make full sense of these

I think the thing perhaps lacking from the graphic is a line that tracks Trump’s approval or popularity. The article mentions that explicitly and it would be interesting to see that track over time. Although I certainly understand how stacking so many line charts above each other could become difficult to compare.

And my final critique are the Election Day outliers. They are above the y-axis maximum. But I wonder if there couldn’t have been a way of handling the outlier-ness of the datapoints while remaining true to the chart scales.

Credit for the piece goes to the Economist graphics department.