Alternatively known as the zombie food map. Sorry, but I couldn’t resist that one. Today we look at a piece from Bloomberg that maps brain drain across the country. What is brain drain? Basically it is the exodus of people with advanced degrees and education employed in science-y industries and fields. So this map shows us where the brains are moving from and where they are moving to.
Credit for the piece goes to Vincent Del Giudice and Wei Lu.
By just a hair under 20 percentage points, Italian voters—with a 70% turnout rate—voted down the reform package of soon-to-be-former Prime Minister Matteo Renzi. While the election was focused narrowly on a set of political reforms for Italian government, e.g. reducing the number of senators, the vote was unofficially seen by many as a test of the strength of anti-establishment populists in Europe. Note wins by such groups in Brexit and Donald Trump. In Europe this is a particularly important barometer reading because of 2017 elections in the Netherlands, France, and then Germany.
I had been looking for some online results trackers, in English, last night but found little. There was, however, this page from Bloomberg. The key thing for me is the link between the regions on the map and the section on the bar chart.
Credit for the piece goes to Bloomberg’s graphics department.
Today’s post is a choropleth map from the Washington Post examining diversity in the United States and how fast or slow diversity is expanding. Normally with two variables one goes instantly to the scatter plot. But here the Post explored the two variables geographically. And it holds up.
The colours are perhaps the only part holding me up on the piece’s design. Are blue and yellow the best two colours to represent level of diversity and growth? I lose some of the gradation in the yellows, especially between the big increases in diversity. Can I offer a better solution? No, and maybe there is not. But I would love the chance to explore different palette options.
As you well know, I am not a big fan of always plotting things on maps. I call them the silver bullet. However, in this instance, there are clear geographic patterns to the four different scenarios. Of course this soon after the election I would love adding a third variable: how the counties voted in the presidential election. Maybe next time.
Credit for the piece goes to Dan Keating and Laris Karklis.
In politics, it is really easy and often popular to bash the federal government. Especially when it comes to its penchant for collecting taxes to pay for things. And sometimes those things are in other states than your own. But do you know how much federal money goes back to your own state? Well now you can thank the Pew Charitable Trusts for putting together this piece that explores what percentage of state budgets is comprised of federal grant money.
While the piece also includes a donut chart—because why not?—my biggest gripe is with the choropleth and the choice of colour for the bins. If you look carefully at the legend, you will see how both the lowest and highest bins use a shade of blue. That means blue represents states that receive less than 25% of their budget from federal grants and also states that receive more than 40% of their budget from the same federal grants. But if your state is between 25% and 40%, your state suddenly turns a shade of green. It really makes no sense. I think the same colour, either blue or green, could be used for the entire spectrum. Or, if the designers really wanted a divergent scheme, they could have used the national average and used that as the breakpoint to show which states are above and which are below said average.
Credit for the piece goes to the Pew Charitable Trusts graphics department.
One of the things I like about Chicago’s WGN network is its weather blog. They often include infographic-like content to explain weather trends or stories. But as someone working in the same field of data visualisation and information design, I sometimes find myself truly confused. That happened with this piece last Friday.
The map in the upper-right in particular caught my attention and not in the good way. The overall piece discusses the heavy rainfall in the Chicago area on Thursday and the map looks at the percentage increase in extreme weather rainfall precipitation. All so far so good. But then I look at the map itself. I see blue and thing blue > water > rainfall. The darker/more the blue, the greater the increase. But, no—check out Hawaii. So blue means less rainfall. But also no, look at the Midwest and Southeast. So does green mean anything? Beyond being all positive growth, not that I can tell. As best I can tell, the colour means nothing in terms of rainfall data, but instead delineates the regions of the United States—noting of course they are not the standard US Census Bureau regions.
So here is my quick stab at trying to create a map that explains the percentage growth. I have included a version with and without state borders to help readers distinguish between states and regions.
And what is that at the bottom? A bar chart of course. After all, with only eight regions, is a map truly necessary especially when shown at such an aggregate level? You can make the argument that the extreme rainfall has, broadly speaking, benefitted the eastern half of the United States. But, personally speaking, I would prefer a map for a more granular set of data at the state or municipality level.
Credit for the piece goes to Jennifer Kohnke and Drew Narsutis.
Another day in Philadelphia, another post of Philly data visualisation work. Here we have a piece from 2015 that was updated earlier this spring. It looks at overdose rates in the Philadelphia region, including parts of New Jersey. It does include a map, because most pieces like this typically do. However, what I really find interesting about the piece is its use of small multiple line charts below to take a look at particular counties.
The piece overall is not bad, and the map is actually fairly useful in showing the differences between Jersey and Philadelphia (although why New Jersey is outlined in black and the Philly suburban counties are not I do not know). But I want to take a look at the small multiples of the piece, screenshot below.
You can see an interesting decision in the choice of stacked line charts. Typically one would compare death rates like for like and see whether a county is above, below, or comparable to the state, local, or national averages. But combining the three gives a misleading look at the specific counties and forces the user to mentally disentangle the graphic. I probably would have separated them into three separate lines. And even then, because of the focus on the counties, I would have shifted the colour focus to the specific counties and away from the black lines for the national average. The black is drawing more attention to the US line than to the county line.
So now it is two weeks since the Brexit vote. Yesterday, I looked at the results designs from the New York Times. Today I want to take a look at those of the BBC. Not surprisingly the two share in the use of choropleth maps; the choice makes a lot of sense. People vote within districts and those form the most granular unit of data available. But, whereas the New York Times led and really focused on one giant map, the BBC opted to use multiple, smaller maps. (They did choose a different page for their live results, but we are comparing post-result coverage.) For example, their piece leads in with a map of Leave’s results share.
There are a few key differences between this and the New York Times. First and foremost, this map is interactive. Mousing over various districts provides you the name, and by clicking you move into a zoomed-in view of the district. It displays the district name, the vote totals and share for the two camps, and then voter turnout. From a design standpoint, the problem with the zooming in is that the scales of the outlining stroke does not change.
A thin stroke at the national, zoomed-out view, translates to a thick, clunky, and awkward-looking outline at the local, zoomed-in view. And as the above screenshot highlights, many of the urban districts are small in comparison to the more rural districts. Unfortunately the map does not offer the functionality of zooming-in prior to selecting a district. So many of the districts in the more urban areas like London, Manchester, Birmingham, and Belfast are difficult to see and select. Thankfully, below the map the BBC offers a function to type in your district, post code, or Northern Irish constituency to help you find smaller districts.
Another design criticism I have with the piece is the colour palette. Broadly speaking, the piece uses blue and yellow. The two colours make sense in a few ways. Both are present on the European Union flag, with yellow stars on a blue field. (Importantly the twelve stars do not represent EU members like the US flag’s fifty stars represent the states.) Another, far looser interpretation could be the blue of the Conservatives and the yellow closer to the gold of the UK’s Liberal Democrats, the former broadly anti-EU and the latter pro-EU. Regardless of the rationale, the choice of yellow to display multiple levels of data is less than stellar (pun intended), as this Remain share map highlights.
Having multiple tints and shades of yellow makes the map difficult to read. The lowest value yellow is brighter than the next higher level, and so stands out more vividly on the map than those districts that had a higher share of Remain votes. Using yellow against blue does work, especially in the bar charts throughout the piece and seen in the aforementioned Islington screenshot. But, as a colour for wider, more intense use, yellow was not the wisest decision.
The BBC also included several other choropleth maps exploring the vote breakdown. In this instance of voter turnout, we have the same choropleth map, but a green colour indicating the total vote turnout.
The colour and its choice makes broad sense; green is what one gets when they mix yellow and blue, when you combine Remain and Leave. However, the map functionality of clicking to reveal results still shows the overall results.
At this point, we have moved on from the vote results themselves to the breakdown of the vote. I would have redesigned the mouse-click to display a results view that highlighted turnout over the results themselves. Certainly keeping the results is important, but the focus of this map is not the vote, but the turnout. The data display should be designed to keep that consistent.
One part of the piece where I quibble with the designer selection of chart type follows on from turnout: a comparison of turnout to the youth population.
Asking people to compare undistinguished districts on one map to those of another—note the white district lines have here disappeared—is difficult. My first thought: I would have instead opted for an interactive scatterplot. Comparing the turnout on one axis and youth on the other, the user would have an easier time identifying any correlations or clusters of data.
In contrast, the following map comparison would not work via a scatterplot. Here we compare June’s results to those of a vote in 1975. In the intervening years, the geography of the voting districts changed, and so a one-to-one comparison is impossible.
The broad scope, however, is clear. A resounding vote to stay part of the European Market or single market in 1975 evolved into a narrow but decisive vote to leave the European Union in 2016.
The piece then closes out with an interactive map of the total results and then, importantly, a long list of bar charts showing each district’s results. Unlike the map, however, the bar charts are a static graphic. And with a few hundred to view, it becomes difficult to isolate and compare two in particular. But the selection of the visualisation type makes a user’s comparison far more precise.
Overall, I would rate the piece a solid work, but with some clear areas of improvement. And who knows? Maybe there will be a second referendum. Or a new general election. And in that case, the BBC could improve upon the designs herein.
Credit for the piece goes to the BBC graphics department.
Well a little under two weeks later and here we are: Brexit. I wanted to take a moment in a slightly longer piece and comment on it. Not the results, because no, that I can leave to a pint at the pub. Instead I wanted to comment on this particular results content from the New York Times that I rather admire.
Overall the piece is not interactive; it features a static choropleth map with annotations and insets, particularly of greater London. On a side note, I would be remiss if I did not point out that similarly to the piece I wrote last week, this map omits a voting district: Gibraltar. Gibraltar, like Northern Ireland, borders the European Union directly via Spain. And despite voting overwhelmingly to remain in the EU, Gibraltar is omitted from these results.
In a large layout, the piece makes excellent use of annotation text to indicate the overview stories for the home nations of the United Kingdom: Scotland, Wales, and Northern Ireland. Northern Ireland, of course, will likely have to deal with the reintegration of border controls between the Republic of Ireland and Northern Ireland, a point the piece makes quite clear.
Additionally the map makes use of small elements to draw attention to data points, i.e. geographies, worth noting. London dominates the urban landscape, but other important cities like Belfast, Manchester, Birmingham are circled to show the strength of Leave/Remain. I would be curious to know the rationale behind including some areas, but omitting others, e.g. the strong Remain results in Cambridge or Brighton or the strong Leave results in Boston, require knowing just where cities are located in England.
From a design standpoint, the colours used in the map work really well together in contrast to other palette choices one could make. (We will take a look at that tomorrow.) Additionally, the shape of the United Kingdom allows for contextual elements, e.g. the regional result aggregates, to be placed much closer and nearer to the results. The space also allows for those annotations to be placed near their particular geographies.
But, what makes the piece stand out is when the user consumes it on smaller screens. On a more tablet-sized screen, we see a tweaked layout.
It makes use of the remaining wide-aspect dimensions to move the greater London results into a white space carved out by the peninsula of East Anglia. While the city and home nation labels remain, the regional annotations and results are gone from the graphic. Instead, they have been placed below the map, the main and most important part of the story.
Then for mobile phone or other narrow displays, the piece degrades even further.
City labels and circles are gone, with the exception of London. The greater London inset moves from alongside the map to now below the map, in the Channel so to speak. This layout allows for a narrow screen to better view the geographic results and then scroll down into the districts of London that require more space to be displayed. The annotations and stories remain below the graphic.
The design of the overall piece accounts nicely for at least three different screen sizes while keeping the story constant. All the truly changes is the layout of the graphic (and the loss of a few contextual labels at the smallest of sizes). Overall, it makes for a rich and compelling—and well designed—piece on the Brexit results.
Credit for the piece goes to Gregor Aisch, Adam Pearce, and Karl Russell.
This week I really wanted to hold off on commenting about Brexit graphics until things settled down—admittedly thinking Remain would win. Now that Thursday has arrived, I think we can all agree that settling down is not happening and the UK really is leaving the EU.
As an Irish American, I grew up with frequent commentary about the Troubles and the general situation in Ireland. So by dint of my heritage, I care about how Brexit impacts Northern Ireland. Unfortunately this graphic from the New York Times on Brexit sentiments entirely omitted Northern Ireland. (It is far from the first time graphics about the UK omit Northern Ireland.)
But, what irritates me in particular about this graphic at this historic time, is what the designers did choose to include. If you look to the north and west of Scotland, you will find the Outer Hebrides and Orkney Islands. From the legend it appears there are no results, accordingly the islands remain—pun intended—grey for, I presume, a classification of not applicable or something similar. (Although, that should also be clarified in the legend.) But, while we are given an inset of Greater London’s results, the entire home nation of Northern Ireland is omitted from the results. (I could then mention how Northern Ireland was not ignored when it came to the Euro 2016 Round of 16 participant results, but I do not understand football enough to comment intelligently.)
And since we mentioned Northern Ireland, we should also mention that Gibraltar is absent from the results map presented here. Gibraltar was once Spanish territory. However, Spain ceded it to the United Kingdom in 1713 as part of the Peace of Utrecht made to end the War of the Spanish Succession. Gibraltar voted overwhelmingly to Remain. And as with Scotland and Northern Ireland, it will (likely) be dragged out of the EU against its people’s wishes.
Credit for the piece goes to the New York Times graphics department.
Well the Democratic DC primaries were last Tuesday and Hillary Clinton won. So now we start looking ahead towards the July conventions and then the November elections. Consequently, if a day is an eternity in politics we have many lifespans to witness before November. But that does not mean we cannot start playing around with electoral college scenarios.
The Wall Street Journal has a nice scenario prediction page that leads with the 2012 results map, in both traditional map and cartogram form. You can play god and flip the various states to either red or blue. But from the interaction side the designers did something really interesting. Flipping a state requires you to click and hold the state. But the speed with which it then flips is not equal for all states. Instead, the length of hold time depends upon the state’s likelihood to be a flippable state, based on the state’s partisan voter index. For example, if you try and flip Kansas, you will have to wait awhile to see the state turn blue. But try and flip North Carolina and the flip is near instantaneous.
While the geographic component remains on the right, the left-hand column features either text, or as in this other screenshot, smaller charts that illustrate the points more specifically.
Taken all together, the piece does a really nice job of presenting users with a tool to make predictions of their own. The different sections with concepts and analysis guide the user to see what scenarios fall within the realm of reason. But, what takes the cake is that flipping interaction. Using a delay to represent the likelihood of a flip is brilliant.
Credit for the piece goes to Aaron Zitner, Randy Yeip, Julia Wolfe, Chris Canipe, Jessia Ma, and Renée Rigdon.