Today is primary day and everyone will be looking to the California results. Although probably not quite me, because Eastern vs. Pacific time means even I will likely be asleep tonight. But before we get to tonight, we have a nice primer from last Friday’s New York Times. It examines the California House of Representatives races that we should be following.
53 districts are a lot to follow in one night…
Like most election-related pieces, it starts with a map. But it uses some scrolling and progressive data disclosure. The map above, after a bit of scrolling, finally reveals the districts worth following and their 2016 vote margins.
Out of all 53, these are the districts the Times says to watch
From there the article moves onto a bit of an exploration of those few districts. You should read the full article—it’s a short read—for the full context on the California votes today. But it does make some nice of bar and line charts to plot the differences in presidential race vs. congressional race margins and the slow Democratic shift.
Credit for the piece goes to Jasmine C. Lee and Karen Yourish.
We are inching ever closer to the US midterm elections in November. In less than a week the largest state, California, will go to the polls to elect their candidates for their districts. So late last week whilst your author was on holiday, the Economist released its forecast model for the results. They will update it everyday so who knows what wild swings we might see between now and the election.
I will strike out against the common knowledge that this is a wave election year and Democrats will sweep swaths through Republican districts in an enormous electoral victory. Because while Democrats will likely win more overall votes across the country, the country’s congressional districts are structurally designed to favour Republicans as a result of gerrymandering after the 2010 Census redistricting. The Economist’s modelling handles this fairly well, I think, as it prescribes only a modest majority and gives that likelihood as only at 2-in-3. (This is as of 30 May.)
But how is it designed?
The big splashy piece is an interactive map of districts.
The overall state of the US in the 30 May run of the model
It does a good job of connecting individual districts to the dots below the map showing the distribution of said seats into safe, solid, likely, leaning, and tossup states. However, the interactivity is limited in an odd way. The dropdown in the upper-right allows the user to select any district they want and then the district is highlighted on the map as well as the distribution plot below. Similarly, the user can select one of the dots below the map to isolate a particular district and it will display upon the map. But the map itself does not function as a navigation element.
Selecting the newly drawn Pennsylvania 6th
I am unsure why that selection function does not extend to the map because clearly the dropdown and the distribution plot are both affecting the objects on the map. Redeeming the map, however, are the district lines. Instead of simply plopping dots onto a US state-level map, the states are instead subdivided into their respective congressional districts.
But if we are going so far as to display individual districts, I wonder if a cartogram would have been a better fit. Of course it is perfectly plausible that one was indeed tried, but it did not work. The cartogram would also have the disadvantage of, in this case, not exhibiting geographically fidelity and thus being unrecognisable and therefore being unhelpful to users.
Now the piece also makes good use of factettes and right-left divisions of information panels to show the quick hit numbers, i.e. how many seats each party is forecast to win in total. But the map, for our purposes, is the big centrepiece.
Overall, this is solid and you better bet that I will be referencing it again and again as we move closer to the midterms.
Credit for the piece goes to the Economist Data Team.
Yesterday was murders in London and New York. Today, we have a nice article from FiveThirtyEight about deaths more broadly in America. If you recall, my point yesterday was that not all graphics need to be full column width. And this article takes that approach—some graphics are full width whereas others are not.
This screenshot shows a nice line chart that, while the graphic sits in the full column, the actual chart is only about half the width of the graphic. I think the only thing that does not sit well with me is the alignment of the chart below the header. I probably would align the two as it creates an odd spacing to the left of the chart. But I applaud the restraint from making the line charts full width, as it would mask the vertical change in the data set.
The screenshot is of the graphic’s full width, note the lines only go a little over half the width.
Meanwhile, the article’s maps all sit in the full column. But my favourite graphic of the whole set sits at the very end of the piece. It examines respiratory deaths in a tabular format. But it makes a fantastic use of sparklines to show the trend leading towards the final number in the row.
Loving the sparklines…
Credit for the piece goes to Ella Koeze and Anna Maria Barry-Jester.
I know I’ve looked at the Times a few times this week, but before we get too far into the next week, I did want to show what they printed on Saturday.
It is not too often we get treated to data on the front page or even the section pages. But last Saturday we got just that in the Business Section. Two very large and prominent charts looked at federal government borrowing and the federal deficit. Both are set to grow in the future, largely due to the recently enacted tax cuts.
That’s about half the page on those two charts.
The great thing about the graphic is just how in-the-face it puts the data. Do two charts with 14 data points (28 total) need to occupy half the page? No. But there is something about the brashness of the piece that I just love.
And then it continues and the rest of the article points, at more normal sizes, to treasury bill yields and car loan rates. The inside is what you would expect and does it well in single colour.
In news that surprises absolutely nobody, Russia “re-elected” Vladimir Putin as president for another six-year term. The Economist recently looked at what they termed the Puteens, a generation of Russians born starting in 1999 who have no memory of a Russia pre-Vladimir Putin.
This piece features a set of interactive dot plots that capture survey results on a number of topics that are segmented by age. It attempts to capture the perspective of Puteens on a range of issues from their media diet to foreign policy outlook to civil rights.
The ideas of youth…
The design is largely effective. The Puteen generation sticks out clearly as the bright red to the cool greys. And more importantly, when the dots would overlap they move vertically away from the line so users can clearly see all the dots. And on hover, all the dots of the same age cohort’s interest are highlighted. I think one area of improvement would have been to apply that same logic to the legend to allow the user to scroll through the whole dataset without always having to interact with the chart. But that is a minor bit on an otherwise really nice piece.
Credit for the piece goes to the Economist’s graphics department.
I don’t know if you heard, but the Winter Olympics just concluded. I’m admittedly not a huge fan of the Winter Olympics, but that doesn’t mean I didn’t keep my eye on some of the stories coming out of the coverage. One that I liked was this piece from FiveThirtyEight.
US performance was lagging at this point
It was about halfway through the Olympics and the US was not doing terribly well. The chart does a great job of showing how various countries were performing, or over- or under-performing, their expected total medal winnings. It did this through a filled bar chart with a bar-specific benchmark line. It was a nice combination of a couple of different techniques to incorporate not just the usual above or below the trend, but also the actual amounts.
Earlier this month I wrote-up a piece from the Economist that looked at 2018 GDP growth globally. I admitted then—and still do now—that it was an oddly sentimental piece given the frequency with which I made graphics just like that in my designer days of youth and yore. Today, we have the redux, a piece from the New York Times. Again, nothing fancy here. As you will see, we are talking about a choropleth map and bar charts in small multiple format. But why am I highlighting it? Front page news.
Choropleth on the front page? More please.
I just like seeing this kind of simple, but effective data visualisation work on the front page of a leading newspaper.
Lots of green on that map
I personally would have used a slightly different palette to give a bit more hint to the few negative growth countries in the world—here’s lookin’ at you, Venezuela—but overall it works. And the break points in the bin seem a bit arbitrary unless they were chosen to specifically highlight the called-out countries.
Then on the inside we get another small but effective graphic.
Page 4
It doesn’t consume the whole page, but sits quietly but importantly at the top of the article.
The world’s leading economies, on their own
There the small multiples show the year-on-year change—nothing fancy—for the world’s leading economies. A one-colour print, it works well. But, I particularly enjoy the bit with China. Look at how the extreme growth before the Great Recession is handled, just breaking out of the container. Because it isn’t important to read growth as 13.27% (or whatever it was), just that it was extremely high. You could almost say, off the charts.
Overall, it was just a fun read for a Sunday morning.
Credit for the piece goes to Karl Russell and the New York Times graphics department.
The last two weeks we twice looked at gerrymandering as it in particular impacted Pennsylvania, notorious for its extreme gerrymandered districts. And now that the state will have to redraw districts to be less partisan, will Pennsylvania usher in a series of court orders from other state supreme courts, or even the federal Supreme Court, to create less partisan maps?
To that specific question, we do not know. But as we get ever closer to the 2020 Census that will lead to new maps in 2021, you can bet we will discuss gerrymandering as a country. Maybe to jumpstart that dialogue, we have a fantastic work by FiveThirtyEight, the Gerrymandering Project.
Since we focus on the data visualisation side of things, I want to draw your attention to the Atlas of Redistricting. This interactive piece features a map of House districts, by default the current map plan. The user can then toggle between different scenarios to see how those scenarios would adjust the Congressional map.
The setup today
If, like me, you live in an area with lots of people in a small space, you might need to see Pennsylvania or New Jersey in detail. And by clicking on the state you can quickly see how the scenarios redraw districts and the probabilities of parties winning those seats. And at the bottom of the map is the set of all House seats colour-coded by the same chance of winning.
But what I really love about this piece is the separate article that goes into the different scenarios and walks the user through them, how they work, how they don’t work, and how difficult they would be to implement. It’s not exactly a quick read, but well worth it, especially with the map open in a separate tab/window.
Overall, a solid set of work from FiveThirtyEight diving deep into gerrymandering.
Credit for the piece goes to Aaron Bycoffe, Ella Koeze, David Wasserman and Julia Wolfe.
The Winter Olympics are creeping ever closer and so this piece from the New York Times caught my eye. It examines the impact of climate change on host cities for the Winter Olympics. Startlingly, a handful of cities from the past almost century are no longer reliable enough, i.e. cold and snow-covered, to host winter games.
This screenshot is of a bar chart that looks at temperatures, because snow and ice obviously require freezing temperatures. The reliability is colour-coded and at first I was not a fan—it seemed unnecessary to me.
At first I did not care for the colours in the bars
But then further down the piece, those same colours are used to reference reliability on a polar projection map.
But then this map changed my mind
That was a subtle, but well appreciated design choice. My initial aversion to the graphic and piece was changed by the end of it. That is always great when designers can pull that off.
Credit for the piece goes to Kendra Pierre-Louis and Nadja Popovich
