Where’s the Cold Weather?

I prefer colder weather to warmer weather. I like to feel a bit of chill on my skin rather than a bit of warmth. This makes me that asshole who says “it’s great out today”, when the temperature is 5ºC (41ºF). (I also enjoy grey, cloudy days, but that’s a different matter entirely.) Anyway, thanks to a friend of mine I could take a look at some temperature maps of the contiguous United States.

High temperatures between 32º and 60ºF
High temperatures between 32º and 60ºF

The Pacific Northwest or the coast of the Mid-Atlantic and New England would be great along with the desert and the mountains. But, don’t deserts get hot? Because the whole point would be to not live somewhere too warm. So here’s a map of the number of days where I prefer to sit inside and crank the air conditioning.

Way too hot
Way too hot

Basically I should avoid the South, the deserts and the plains states of the Midwest. Chicago looks borderline uncomfortable. (And from experience, summers typically are.)

Credit for the piece goes to Christopher Ingraham.

Irish Coalition Government

As I alluded to yesterday, in addition to visualising Irish election results the Irish Times built a coalition builder.

The current coalition is far from a majority in the new Dáil
The current coalition is far from a majority in the new Dáil

The principle behind the visualisation is sound: how could a government be created? And so the user goes away and creates his or her fantasy government. From a design perspective, the piece is nice with bold, party-related colours and clear controls. The Irish Times also included a nice subtlety with independent TDs (members of the Dáil) as clicking the plus button does not add all ten, but one person at a time. That reflects the fact the independents are not a whole party but ten individuals.

But I personally keep returning to a single question: how realistic are these fantasies? I think an addition that would benefit the story-telling element of the piece would be a guided narrative. Start with the screenshot above, which presents the coalition from the previous Dáil. Clearly they are far from a majority. A guided narrative could explain the likelihood and possible priorities of a various number of plausible coalitions. It would also be able to exclude the more ridiculous pairings.

Credit for the piece goes to the Irish Times’ graphics department.

The Shape of the 32nd Dáil

Ireland calls its lower-house of parliament the Dáil and its prime minister taoiseach. When I visited Dublin, election season was in full swing and upon the first Friday of my return to Chicago, Ireland went to the polls to elect the 32nd Dáil. The vote resulted in a hung parliament, i.e. with no single party in control—there are more than two political parties. The Irish Times put together an interactive piece looking at the makeup of the new assembly. (There is also a coalition builder, but we will take a look at that separately.)

The Dáil by age
The Dáil by age

Credit for the piece goes to the Irish Times’ graphics department.

Tracking Super Tuesday

On Tuesday I tracked the results primarily with the New York Times and the Washington Post. I really enjoyed the Post’s coverage as they designed a homepage for the night’s results. The results were placed at the centre of the content, as you can see in the screenshot below. Below the map and table, content updated on the right with links to more static content on the left.

The results hub Tuesday night
The results hub Tuesday night

The map and table above naturally updated throughout the course of evening. I found their decision to move states from one table to the other when the race was declared a brilliant little decision. When reinforced with a small checkmark, the movement from the lower table to the final table at the top gave a real sense of progress—maybe momentum—to the victories of both Donald Trump and Hillary Clinton.

Final results table and map
Final results table and map

Overall, this was a very helpful site for me to follow the results streaming in Tuesday night.

Credit for the piece goes to the Washington Post graphics department.

Super Tuesday Time

Super Tuesday is the first test of an American presidential candidate’s ability to run—and win—a semi-national campaign. Unlike the one-off primaries or caucuses in places like Iowa or New Hampshire, for today, each candidate has had to prepare for votes in 11 states. And these states are as varied as Alabama to Texas to Massachusetts to Alaska. Consequently, Super Tuesday also means lots of delegates are at stake.

So before the results are announced, let’s look at Bloomberg Politic’s piece that is basically a delegate counter with explanations. (Because right now super-delegates are not at stake.) In the interactive graphic side, we have a counter for every pledged delegate.

The Republican landscape before the voting
The Republican landscape before the voting

I think in the big box up top, the only missing element is some visual measure of just how far each candidate remains from the magic number. In the Republican case, that is 1237 delegates. Below that, however, I really love the tiles that summarise the individual state results, both in delegates and vote share. (After all, some states are entirely proportional, some semi-proportional, and some none-at-all/winner-take-all.)

Credit for the piece goes to Alex Tribou and Jeremy Scott Diamond.

How Much Warmer Was 2015

When I was over in London and Dublin, most days were cool and grey. And a little bit rainy. Not very warm. (Though warmer than Chicago.) But, that is weather—highly variable on a daily basis. Climate is longer-term trends and averages. Years, again, can be highly variable—here’s looking at you kid/El Niño. But, even in that variability, 2015 was the warmest year on record. So the New York Times put together a nice interactive piece allowing the user to explorer data for available cities in terms of temperature and precipitation.

You can see the big chart is temperature with monthly, cumulative totals of precipitation. (I use Celsius, but you can easily toggle to Fahrenheit.) Above the chart is the total departure of the yearly average. Anyway, I took screenshots of Philadelphia and Chicago. Go to the New York Times to check out your local cities.

Philadelphia, PA
Philadelphia, PA
Chicago, IL
Chicago, IL

Credit for the piece goes to K.K. Rebecca Lai and Gregor Aisch.

Iowa Caucus Results by Demographic Types

Back to the Iowa Caucus results for a moment. A lot of the day-of forecasting for elections is done by entrance and exit polls. So in this piece from the Washington Post, we take a look at entrance poll results. This is basically a two-parter. The first is showing each candidate and the group they won and a number indicates by how much they won the demographic group.

Select the 30–44 age group
Select the 30–44 age group

If you click on any of the demographic groups in particular, you are brought to the part of the page with the actual full results for the demographic. The format is simple a basic heat map with table. Nothing fancy, but nothing fancy is required for that type of data. Interestingly, the colour denotes not the share, but the result. I am not sure I would have done that, but it is a minor quibble.

The 30–44 age group results
The 30–44 age group results

Credit for the piece goes to Lazaro Gamio and Scott Clement.

T-shirt Sizes

It’s Monday, folks. And for most of us that means going back to work. Which means dressing appropriately. And that’s about as far as I’ve got introducing this subject matter, because I wear a dress shirt and tie everyday. Not a t-shirt. But we’re talking t-shirts. Specifically their sizing.

Threadbase is a New York startup looking to do some cool things with data about t-shirts. But that requires having data with which to play. And they are starting to do just that. Their opening blog post has quite a few data visualisations.

Comparing actual sizes via a dot plot
Comparing actual sizes via a dot plot

The dot plot above charts the sizes by dimension for various brands and makes. I might quibble with the particular colours as the red and purple are a bit on the difficult side to distinguish. Symbols could be away around the issue. But the only real issue is that on my monitors the full image runs long and I lose the reference point of the actual dimensions in inches.

But the piece is worth the read for the cyclical changes in dimensions.

Mostly it’s just a pity that I’m not a jeans and t-shirt sort of guy.

Credit for the piece goes to Threadbase.

Urban Homicide

Today we look at a really nice piece from the Washington Post on urban homicide. It combines big, full-width images that use interactivity to promote exploration of data. But as you can see in the screenshot below, the designers took care to highlight a few key stories. Just in case the reader does not want to take the time to explore the data set.

The growth rate is an interactive piece
The growth rate is an interactive piece

But the piece uses scale to provide contrast throughout the article. Because in addition to the three or four big graphics, a similarly well-thought-out and well-designed approach was taken towards smaller, inline supplemental graphics. Here is an example about the homicide rate for New York.

New York's homicide rate as an inline graphic
New York’s homicide rate as an inline graphic

What I really enjoy about these small graphics is the attention paid to highlighting New York against the background averages provided for context. Note how the orange line for the city breaks the grey lines. It is a very nice detail.

Overall, this is a really strong piece marrying written content and data visualisation.

Credit for the piece goes to Denise Lu.

Selfiexploratory

New year, new selfies. Thankfully we have the Selfiecity to look at a sample of selfies, the goal to determine patterns and trends in the art of the selfie. Of course you also want to be able to look at the aforementioned selfies. For that they built the Selfiexploratory, an application that allows you to filter the set to see what you want. What I like is the return of data to show what the results of the filter look like against the whole set.

How my filters affect the results
How my filters affect the results

Credit for the piece goes to the Selfiecity team.