On Monday, Attorney General Jeff Sessions and the Justice Department released figures for violent crimes in 2016. The administration talked about the rise in violent crime. And yes, such crime did rise in 2016. But, what was not raised nearly as much is that we are also living in an era of historically low crime. FiveThirtyEight broke down the crime numbers through a series of charts and put them in their historical context.
The screenshot below looks just at murder rates. And again, nobody denies that the murder rate is up. But it still below the level it was in the 2000s, 1990s, and 1980s. One has to go back to the 1960s to find murder rates so low.
The point is really just to reiterate that context matters. If we were to look at the rise over the last year, yes an increase from 4.9 to 5.3 would look bad. But, really, we are still living in a far safer country than we were for most of the latter half of the 20th century. You just need to extend the endpoints of the chart to see it.
But to be honest, it never really went anywhere. As you know, your humble author visited Boston this past weekend and got to see two games of his Red Sox against Tampa Bay. Tampa, of course, is not the rivalry to which I am referring, but things were heated back in the days when Maddon managed Tampa.
No, I am of course talking about the Red Sox–Yankees rivalry. Two weeks ago FiveThirtyEight posted an article about the rivalry and how it has returned. Admittedly, they meant not from the perspective of bitter hatred for all things Yankees, but rather that the Yankees are attempting to be good again.
This chart from the article is nothing more than a line chart. But I just wanted to point out that the rivalry lives, though in my mind it never really went away.
Credit for the piece goes to the FiveThirtyEight graphics department.
One more day of Harvey-related content. At least I hope. (Who knows? Maybe someone will design a fantastic retrospective graphic?) Today, however, we look at a piece from the Economist about the rising number of weather-related disasters, but thankfully falling numbers of deaths. The piece has all the full suite of graphics: choropleths, line charts, and bar charts (oh my!). But I want to look at the bar chart.
I cannot tell from this chart whether there has been any change in the individual elements, the meteorological, hydrological, or climatological disasters. And unfortunately stacked bar charts do not let us see that kind of detail. They only really allow us to see total magnitude and the changes in the element at the bottom of the stack, i.e. aligned with the baseline. So I took their chart and drew the shapes as lines and realigned everything to get this.
You can begin to see that meteorological might be overtaking hydrological, but it is too early to tell. And that right now, climatological causes are still far behind the other two.
Credit for the piece goes to the Economist Data Team.
Initially I was not going to post this work, if only because other things came up and I do have to prioritise what I post on my site. It had nothing to do with the work’s quality, which I think is actually quite good. What am I talking about? Well today’s piece is from a Pro Public article about the impact of immigration on economic growth. And it turns out the two are linked. Why? Well, the overly simplistic explanation is that we will need immigrants to pick up the slack in the labour force that will otherwise begin shrinking in years to come.
But why take my word for it when you can take charts’ word for it. The piece does a great job of showing how changes in immigration numbers can help grow or shrink economic growth. And if you recall, President Trump has promised growth rates of 4%. But, and this is why I decided to post this, yesterday it was announced that Trump will support legislation intending to halve immigration to the United States over the next ten years. As my screenshot captured, a reduction in immigration will actually lead to lower economic growth and put us further away from the 4% rate.
In this piece from the Guardian, we have one of my favourite types of charts. But, the piece begins with a chart I wonder about. We have a timeline of countries creating universal healthcare coverage, according to the WHO definition—of which there are only 32 countries. But we then plot their 2016 population regardless of when the country established the system. It honestly took me a few minutes to figure out what the chart was trying to communicate.
However, we do get one of my favourite charts: the scatter plot over time. And in it we look at the correlation between spending on healthcare compared to life expectancy. And, as I revealed in the spoiler, for all the money we spend on healthcare—it is not leading to longer lives as it broadly does throughout the world. And care as you might want to blame Obamacare, the data makes clear this problem began in the 1980s.
And of course Obamacare is why the Guardian published this piece since this is the week of the Vote-a-rama that we expect to see Thursday night. The Republicans will basically be holding an open floor to vote on anything and everything that can get some measure of repeal and/or replace 50 votes. And to wrap the piece, the Guardian concludes with a simple line chart showing the number of uninsured out to 2026. To nobody’s surprise, all the plans put forward leave tens of millions uncovered.
It is a fantastic piece that is well worth the read, especially because it compares the systems used by a number of countries. (That is largely the text bit that we do not cover here at Coffeespoons.) I found the piece very informative.
Credit for the piece goes to the Guardian graphics department.
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.
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.
Well after the last two weeks of recording solo trivia performances, I decided that this week I would showcase a team effort.
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.
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.
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.
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.
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.
Wednesday night I had the dubious honour of playing the weekly pub trivia solo. Accordingly my team name was Hats Solo. (After I opted not to wear my fedora one night, another regular team called itself Where’s Your Hat?) I started strong, had a second wind, but still faded to a seventh place (of nine) finish. As I finished my G&T, I decided I would visualise the results. Here, two days later, are my results.
Credit for the highlights, mine. The lowlights, someone else.