Yesterday we looked at Billy Penn’s graphics about the cooler stations and I mentioned a few ways the graphic could be improved. So last night I created a graphic where I explored the limited scope of the data, but also showing how low the temperatures were, relative to the air temperature outside, using weather data from the National Weather Service, admittedly from Philadelphia International Airport, not quite Centre City, which I would expect to be warmer due to the urban heat bubble effect.
I opted to exclude the Patco Line since the original dataset did not include it either. However a section of it does run through Centre City and could be relevant.
Credit for the piece goes to me, though the data is all from Billy Penn and the National Weather Service.
Those of you living on the East Coast, specifically the Mid-Atlantic, know that presently the weather is quite warm outside. As in levels of dangerous heat and humidity. Personally, your author has not left his flat in a few days now because it is so bad.
Alas, not everyone has access to air conditioning in his or her abode. Consequently, they need to look to public spaces with air conditioning. Usually that means libraries or public buildings. But here in Philadelphia, have people considered the subway?
Billy Penn investigated the temperatures in Philadelphia’s subsurface stations along the Broad Street and Market–Frankford Lines—Philadelphia’s third and oft-forgot line, the Patco, was untested. What they found is that temperatures in the stations were significantly below the temperatures above ground. The Market–Frankford stations, for example, were less than 100ºF.
Of course that misses the 2nd Street station in Old City, but otherwise picks up all the Market–Frankford stations situated underground.
Then there is the Broad Street Line.
Here, I do have a question about why the line wasn’t investigated from north to south. It ran only as far north as Girard, stopping well short of north Philadelphia neighbourhoods, and then as far south as Snyder, missing both Oregon and Pattison (sorry, corporately branded AT&T) stations. The robustness of the dataset is a bit worrying.
The colours here too mean nothing. Instead blue is used for the blue-coloured Market–Frankford line and orange for the orange-coloured Broad Street line. (The Patco line would have been red.) Here was a missed opportunity to encode temperature data along the route.
Finally, if the sidewalk temperatures were measured at each station, I would want to see that data alongside and perhaps run some comparisons.
This is an interesting story, but some more exploration and visualisation of the data could have taken it to the next level.
Happy Friday, all. We made it to the end of the week. Though if you are like me, i.e. living on the East Coast, welcome to Hell. As in so hot and humid.
So last month President Trump visited the United Kingdom on a state visit. He drew attention to himself not just because of his rhetoric, but also for his fashion choices. Consequently, the Washington Post published a piece about those fashion choices from the perspective of a professional tailor.
The overall piece is well worth a read if you find presidential fashion fascinating. But how does it qualify for Coffeespoons? A .gif that shows how Trump would look in a properly tailored suit.
Since this is a screenshot, you miss the full impact. The piece is an animation of an existing photo and how that then morphs into this for comparison’s sake.
I really enjoy the animated .gif when it works for data visualisation and story-telling.
Back in April the famed Notre Dame cathedral in Paris caught fire and its roof and spire spectacularly collapsed. At the time I looked at a few different pieces, including two from the New York Times, that explored the spread of the fire. Several months later the Times has just published a look into how the firefighters saved the cathedral from collapse.
The graphics are the same amazing illustrated models from before. Now with routes taken by firefighters and coloured areas indicating key equipment used in the fight to preserve what could be saved. But the real gem in the article are a series of graphics from the firefighters themselves.
Naturally the annotations are all in French. But this French firefighter and sketch artist detailed the progress of the battle during and in the days after the fire. It makes me wish I could read French to understand the five selected sketches the Times chose to use. And I love this line from the Times.
For all the high-tech gear available to big-city fire departments, investigators still see value in old-school tools.
If you are interested in the story of how the cathedral was saved, read the lengthy article. If you just want to see some really amazing and yet wholly practical sketches, scroll through the article until you get to these gems.
Credit for the overall piece goes to Elian Peltier, James Glanz, Mika Gröndahl, Weiyi Cai, Adam Nossiter, and Liz Alderman.
This is a graphic from the Guardian that sort of mystified me at first. The article it supports details how the rising rents across England are hurting the rural youth so much so they elect to stay in their small towns instead of moving to the big city.
The first thing I noticed is that there really is no description of the data. We have a chart looking at something from 1997 and comparing it to 2018. The title is more of a sentence describing the first pair of bars. And from that title we can infer that these bars are income changes for the specified move, e.g. Sunderland to York, for the specified year. But a casual reader might not pick up on that casual description.
Then we have the issue of the bars themselves. What sort of range are we looking at? What is the min? The max? That too is implied by the data presented in the bars. Well, technically not the bars, but in the numbers at the end of each bar. I will spare you the usual rant about numbers in graphics defeating the purpose of graphics and organisation vs. visual relationship. Instead, the numbers here are essential because we can use them to suss out the scale of the grey bars. After looking at a few bars, we can tell that the white lines separating the grey boxes are most likely 10% increments. And from that we can gather the minimum is about -40% and the maximum 100%. But instead of making the reader work to figure this out, would not some min/max labels at the bottom of the chart be far clearer?
And then there is the issue of the grey boxes/bars themselves. Why are they there in the first place? If the dataset were more about an unmet value, say reservoirs in towns were only at x% of capacity, the grey bars could relate the overall capacity and the coloured bars the actual values. But here, income is not a capacity or similar type of value. It could expand well beyond the 100% or decline beyond the -40%. These bars imply the values are trapped within these ranges. I would instead drop the grey bars entirely and let the coloured bars exist on their own.
Overall this is a confusing graphic for a fascinating article. I wish the graphic had been a little bit clearer.
Credit for the piece goes to the Guardian’s graphics department.
Hurricane/tropical storm Barry has been dumping rain along the Gulf Coast for a few days now. But prior to this weekend, the biggest concern had been for the city of New Orleans, which sits besides the swollen Mississippi River. The river was running already high at 17 feet above normal, and with storm surges and tropical rain levels forecast, planners were concerned not with the integrity of the city’s levee system, rebuilt in the aftermath of Hurricane Katrina, but simply whether they would be tall enough.
So far, they have been.
The Washington Post tracked Barry’s course with the usual graphics showing forecast rainfall amounts and projected tracks. However, the real stunner for me was this cross section illustration of New Orleans that shows just how much of the central city sits below sea level. The cross section sits above a map of the city that shows elevation above/below sea level as well as key flood prevention infrastructure, i.e. levees and pumping stations.
The unmentioned elephant remains however. The National Oceanic and Atmosphere Administration’s extreme climate change impact forecast says the water around New Orleans might rise by nearly 13 feet by 2100. Clearly, that is still well below the 20 feet levees of today. But what if there were to be a 17 feet high Mississippi River atop the additional 13 feet? 30 feet would flood the city.
Credit for the piece goes to John Muyskens, Armand Emamdjomeh, Aaron Steckelberg, Lauren Tierney, and Laris Karklis.
The United Kingdom is known for having a large number of accents in a—compared to the United States—relatively small space. But then you add in Ireland and you have an entirely new level of linguistic diversity. Josh Katz, who several years ago made waves for his work on the differences in the States, completed some work for the New York Times on those differences between the UK and Ireland.
Why do I bring it up? Well, your author is going on holiday again, this time back to London. I will be maybe taking some day trips to places outside the capital and maybe I will confirm some of these findings. But if you want, you can take the quiz and see where you fall compared to Katz’s findings.
And it does pretty well. It identified me as being clearly not from the British Isles.
But depending upon how you answer a particular question, the article will show you how your answer compares. Let’s take my answer for scone. In that, I am more Irish.
Ebola, which killed 11,000 people in West Africa in 2014 (whichIcoveredinacoupleofdifferentposts), is back and this time ravaging the Congo region, specifically the Democratic Republic of the Congo (DRC). The BBC published an article looking at the outbreak, which at 1,400 deaths is still far short of the West Africa outbreak, but is still very significant.
The piece uses a small multiples of choropleths for western Congo. The map is effective, using white as the background for the no case districts. However, I wonder, would be more telling if it were cases per month? That would allow the user to see to where the outbreak is spreading as well as getting a sense of if the outbreak is accelerating or decelerating.
The rest of the article features four other graphics. One is a line chart that also looks at cumulative cases and deaths. And again, that makes it more difficult to see if the outbreak is slowing or speeding up. Another is how the virus works and then two are about dealing with the virus in terms of suits and the containment camps. But those are graphics the BBC has previously produced, one of which is in the above links.
Credit for the piece goes to the BBC graphics department.
Long before I worked as a designer, I was a busboy. After that I was a dishwasher. After that I was a barista. Then I became a designer. This graphic from Indexed resonated with me, because, yeah, at a more basic level, don’t fuck with your servers.
This isn’t really a graphic so much as it is an x-ray photograph. But I also can’t get it out of my head. We all know that mobile phones has changed the way we live. But now we have evidence that our use of them is changing us physically. Young people are growing horns or spikes at the back of their skull. Don’t believe, photo:
The article in the Washington Post from which I screen captured the image is well worth a read. But I advise you to not do it on a mobile phone.