Thanksgiving Side Dishes

American Thanksgiving meals often feature elaborate spreads of side dishes. And everyone has a favourite. A common theme around the holiday is for media outlets to conduct surveys to see which ones are most popular where. In today’s piece we have one such survey from pollster YouGov. In particular, I wanted to focus on a series of small multiples maps they used to illustrate the preferences.

Big splashes of colour do not necessarily make for a great map
Big splashes of colour do not necessarily make for a great map

I used to see this approach taken more often and by this I hope I do not see a foreshadow of its comeback. Here we have US states aggregated into distinct regions, e.g. the Northeast. One could get into an argument about how one defines what region. The Midwest is one often contested such region—I have one post on it dating back to at least 2014.

Instead, however, I want to focus on the distinction between states and regions. This small multiples graphic is a set of choropleth maps that use side dish preferences to colour the map. Simple enough. However, the white lines delineating states imply different fields to be coloured within the graphic. Consequently, it appears that each state within the region has the same preference at the same percentage.

The underlying data behind the maps, at least that which was released, indicates the data is not at the state level but instead at the regional level. In other words, there are no differences to be seen between, say, Pennsylvania and New Jersey. Consequently, a more appropriate map choice would have been one that omitted the state boundaries in favour of the larger outlines of the regions.

More radically, a set of bar charts would have done a better job. Consider that with the exception of fruit salad, in every map, only one region is different than the others. A bar chart would have shown the nuance separating the three regions that in almost all of these maps is lost when they all appear as one colour.

I appreciate what the designers were attempting to do, but here I would ask for seconds, as in chances.

Credit for the piece goes to the YouGov graphics team.

From Order to Chaos?

A few weeks ago we said farewell to John Bercow as Speaker of the House (UK). Whilst I covered the election for the new speaker, I missed the opportunity to post this piece from the BBC. It looked at Bercow’s time in office from a data perspective.

The piece did not look at him per se, but that era for the House of Commons. The graphic below was a look at what constituted debates in the chamber using words in speeches as a proxy. Shockingly, Brexit has consumed the House over the last few years.

At least climate change has also ticked upwards?
At least climate change has also ticked upwards?

I love the graphic, as it uses small multiples and fixes the axes for each row and column. It is clean, clear, and concise—just what a graphic should be.

And the rest of the piece makes smart use of graphical forms. Mostly. Smart line charts with background shading, some bar charts, and the only questionable one is where it uses emoji handclaps to represent instances of people clapping the chamber—not traditionally a thing that  happens.

Content wise it also nailed a few important things, chiefly Bercow’s penchant for big words. The piece did not, however, cover his amazing sense of sartorial style vis-a-vis neckties.

Overall a solid piece with which to begin the weekend.

Credit for the piece goes to Ed Lowther & Will Dahlgreen.

Auto Emissions Stuck in High Gear

The last two days we looked at densification in cities and how the physical size of cities grew in response to the development of transport technologies, most notably the automobile. Today we look at a New York Times article showing the growth of automobile emissions and the problem they pose for combating the greenhouse gas side of climate change.

The article is well worth a read. It shows just how problematic the auto-centric American culture is to the goal of combating climate change. The key paragraph for me occurs towards the end of the article:

Meaningfully lowering emissions from driving requires both technological and behavioral change, said Deb Niemeier, a professor of civil and environmental engineering at the University of Maryland. Fundamentally, you need to make vehicles pollute less, make people drive less, or both, she said.

Of course the key to that is probably in the range of both.

The star of the piece is the map showing the carbon dioxide emissions on the roads from passenger and freight traffic. Spoiler: not good.

From this I blame the Schuylkill, Rte 202, the Blue Route, I-95, and just all the highways
From this I blame the Schuylkill, Rte 202, the Blue Route, I-95, and just all the highways

Each MSA is outlined in black and is selectable. The designers chose well by setting the state borders in a light grey to differentiate them from when the MSA crosses state lines, as the Philadelphia one does, encompassing parts of Pennsylvania, New Jersey, Delaware, and Maryland. A slight opacity appears when the user mouses over the MSA. Additionally a little box remains up once the MSA is selected to show the region’s key datapoints: the aggregate increase and the per capita increase. Again, for Philly, not good. But it could be worse. Phoenix, which surpassed Philadelphia proper in population, has seen its total emissions grow 291%, its per capita growth at 86%. My only gripe is that I wish I could see the entire US map in one view.

The piece also includes some nice charts showing how automobile emissions compare to other sources. Yet another spoiler: not good.

I've got it: wind-powered cars with solar panels on the bonnet.
I’ve got it: wind-powered cars with solar panels on the bonnet.

Since 1990, automobile emissions have surpassed both industry emissions and more recently electrical generation emissions (think shuttered coal plants). Here what I would have really enjoyed is for the share of auto emissions to be treated like that share of total emissions. That is, the line chart does a great job showing how auto emissions have surpassed all other sources. But the stacked chart does not do as great a job. The user can sort of see how passenger vehicles have plateaued, but have yet to decline whereas lorries have increased in recent years. (I would suspect due to increased deliveries of online-ordered goods, but that is pure speculation.) But a line chart would show that a little bit more clearly.

Finally, we have a larger line chart that plots each city’s emissions. As with the map, the key thing here is the aggregate vs. per capita numbers. When one continues to scroll through, the lines all change.

Lots of people means lots of emissions.
Lots of people means lots of emissions.
There's driving in the Philadelphia area, but it's not as bad as it could be.
There’s driving in the Philadelphia area, but it’s not as bad as it could be.

Very quickly one can see how large cities like New York have large aggregate emissions because millions of people live there. But then at a per capita level, the less dense, more sprawl-y cities tend to shoot up the list as they are generally more car dependent.

Credit for the piece goes to Nadja Popovich and Denise Lu.

Different Paths to Density

Yesterday we looked at the expansion of city footprints by sprawl, in modern years largely thanks to the automobile. Today, I want to go back to another article I’ve been saving for a wee bit. This one comes from the Economist, though it dates only back to the beginning of October.

This article looks at the different ways a city can achieve density. Usually one things of soaring skyscrapers, but there are other paths. For those interested, the article is a short read and I won’t cover it here. But for the sake of the graphic below, there are three basic paths: coverage, height, and crowding. Or to put in other terms, how much of the city is covered by homes, how tall those homes go, and how many people fit into each home.

Reticulating splines
Reticulating splines

I really like this graphic. It does a great job of using small multiples to compare and contrast three cities that exemplify the different paths. Notably, it keeps each city footprint at the same scale, making it easier to see things such as why Hong Kong builds skyward. Because it has little land. (It is, after all, an island and the tip of a peninsula.)

One area where I wish the graphic had kept to the small multiples is its display of Minneapolis. There, the scale shifts (note the lines for 5 km below vs. Minneapolis’ 10 km). I think I understand why, because the sprawling city would not have fit within the confines of the graphic, but that would have also hammered home the point of sprawl.

I should also point out that the article begins with a graphic I chose not to screenshot, but that I also really enjoy. It uses small multiples to compare cities density over time, running population on the x-axis and people per hectare on the y-. It is not a perfect graphic (it uses I think unnecessary arrowheads at the end of the line), but scatter plots over time are, I think, an underused graphic to show how two variables (ideally related) have moved in tandem over time.

Overall, this is a strong piece from the Economist.

Credit for the piece goes to the Economist graphics department.

Urban Heat Islands

Yesterday was the first day of 32º+C (90º+F) in Philadelphia in October in 78 years. Gross. But it made me remember this piece last month from NPR that looked at the correlation between extreme urban heat islands and areas of urban poverty. In addition to the narrative—well worth the read—the piece makes use of choropleths for various US cities to explore said relationship.

My neighbourhood's not bad, but thankfully I live next to a park.
My neighbourhood’s not bad, but thankfully I live next to a park.

As graphics go, these are effective. I don’t love the pure gradient from minimum to maximum, however, my bigger point is about the use of the choropleth compared to perhaps a scatter plot. In these graphics that are trying to show a correlation between impoverished districts and extreme heat, I wonder if a more technical scatterplot showing correlation would be effective.

Another approach could be to map the actual strength of the correlation. What if the designers had created a metric or value to capture the average relationship between income and heat. In that case, each neighbourhood could be mapped as how far above or below that value they are. Because here, the user is forced to mentally transpose the one map atop the other, which is not easy.

For those of you from Chicago, that city is rated as weak or no correlation to the moderately correlated Philadelphia.

I lived near the lake for eight years, and that does a great deal for mitigating temperature extremes.
I lived near the lake for eight years, and that does a great deal for mitigating temperature extremes.

Granted, that kind of scatterplot probably requires more explanation, and the user cannot quickly find their local neighbourhood, but the graphics could show the correlation more clearly that way.

Finally, it goes almost without saying that I do not love the red/green colour palette. I would have preferred a more colour-blind friendly red/blue or green/purple. Ultimately though, a clearer top label would obviate the need for any colour differentiation at all. The same colour could be used for each metric since they never directly interact.

Overall this is a strong piece and speaks to an important topic. But the graphics could be a wee bit more effective with just a few tweaks.

Credit for the piece goes to Meg Anderson and Sean McMinn.

Brexit Crazyness Continues

The British Supreme Court ruled today that Boris Johnson unlawfully advised the Queen to prorogue Parliament. And because the advice was unlawful, the act was therefore unlawful. And because the act was unlawful, the effects of said act were unlawful. And because the effects were unlawful, said effects are null and void. So, you know, prorogation never happened.

So the Prime Minister has misled the Queen. He has failed to pass all but one bill in Parliament (it was a bill for the restoration of the Palace of Westminster totally unrelated to Brexit). He lost three seats, one via a by-election and two by defecting MPs. And then he purged 21 MPs from his party to completely obliterate his working majority. In any other year, this would be cause for the immediate resignation of the Prime Minister. Instead he is sticking around in New York to give a speech about, what else, Brexit, before flying back to London tonight (Eastern US time).

So what’s next? Who really knows. This has never before happened in the history of the United Kingdom. But one possible option is that the opposition parties may hold a no confidence vote. But there will be significant pressure against that, because, as my graphic shows, any election that would likely result, would mean Brexit happening with Parliament dissolved. And that would, ahem, defeat the entire purpose of preventing a No Deal Brexit. Consequently, a no confidence vote or general election is unlikely. (Unless, the opposition and Tory rebels can agree to a non-Jeremy Corbyn caretake prime minister, e.g. Ken Clarke or Margaret Beckett.)

Omnishambles. Even Iannucci couldn't have made this stuff up.
Omnishambles. Even Iannucci couldn’t have made this stuff up.

Regardless, get ready for a crazy day of Parliamentary procedure tomorrow.

Hong Kong Identity

One of the things I have been following closely the last few months has been the protests in Hong Kong. The city is one of China’s few Special Administrative Regions—basically the former British colony of Hong Kong and the former Portuguese colony of Macau, two cities bordering mainland China and separated by the Pearl River estuary.

Long story short, but since 1997 Hong Kong should enjoy 50 years of a legal system that is more aligned to that of its former status of a British colony than that of mainland China. But increasingly since Xi Jinping took power, he has been eroding those rights and the youth of Hong Kong have taken to the streets to protest, a right they enjoy but not the rest of mainland Chinese.

And so we have a survey looking at the identity by which those people living in Hong Kong choose to identify.

And it’s not Chinese.

Not a good trend for Beijing
Not a good trend for Beijing

From a news perspective, this poses problems for a Beijing-based Chinese government that is making pains to promote a greater Chinese identity throughout the world, least of all by pushing for a reunification with Taiwan by force if necessary. A generation of several million Hong Kongers and the way they raise their children, in addition to their friends and supporters abroad, weakens the authority of Beijing.

Hence the threat of a Tiananmen Square style crackdown on Hong Konger protestors.

Alas, the United States has been far more concerned with its trade dispute than it has been the democratic and human rights of several million people. At least, that is the impression given by the White House.

But, as to the design, I do not love the spaghettification of the line charts. Though I do appreciate that the Hong Kong identity has been separated by the maroon-coloured line. I wonder if labelling the lines in the small multiples is necessary given the decision to include the legend at the top of the chart.

The other tricky thing with this type of chart is that the data series is a population cohort. And yet the data is based on a time series. And so the cohorts vary over time. It might not be entirely clear to the audience that this (appears to be)/is a sample of people of an age at a particular date. How do those people change over the years? It’s hard to see that trend by separating out the data.

Overall, it’s a solid piece. And it’s important given the gravity of the protests in Hong Kong.

Credit for the piece goes to the Economist Data team.

Pub Trivia Scores

So today we have pub trivia scores.

It’s been a little while since I’ve posted from my data recording of my Wednesday night’s team trivia pub scores. For the very few of us who know what this means, here you go.

We're on a downward trend
We’re on a downward trend

Essentially, our ability to score points on music in the last round remains pretty bad. Hence the general downward trend.

Credit for this piece goes to me.

It’s Boris Time, Baby

Today Boris Johnson begins his premiership as the next prime minister of the United Kingdom. He might not be popular with the wide body of the British population, but he is quite popular with the Conservative base.

The Economist looked at how Boris polled on several traits, e.g. being more honest than most politicians, compared to his prime minister predecessors before they entered office. And despite being broadly unpopular outside the Tories, he still polls better than most of his predecessors.

Boris rates higher than many previous prime ministers before they came to power
Boris rates higher than many previous prime ministers before they came to power

Design wise, it’s a straight-forward use of small multiples and bar charts. I find the use of the light blue bar a nice device to highlight Boris’ position amongst his peers.

But now we see where Boris goes, most importantly on Brexit.

Credit for the piece goes to the Economist graphics department.

Tornado Alley Spread East

Last week the Philadelphia area experienced a mini tornado outbreak with three straight days of watches and warnings. Of course further west in the traditional Tornado Alley, far more storms of far greater intensity were wreaking havoc. But with tornado warnings going off every few minutes just outside the city of Philadelphia, it was hard to concentrate on storms in, say, Oklahoma.

But the New York Times did. And they put together a nice graphic showing the timeline of the outbreak using small multiples to show where the tornado reports were located on 12 consecutive days.

Who remembers the film Twister?
Who remembers the film Twister?

Of course the day of that publication, 29 May, would see another few dozen, even in and around Philadelphia. Consequently, the graphic could have been extended to a day 13. But that would have been rather unlucky.

From a design standpoint, the really nice element of this graphic is that it works so well in black and white. The graphic serves as a reminder that good graphics need not be super colourful and flashy to have impact.

Credit for the piece goes to Weiyi Cai and Jason Kao.