Bus Transit in Philadelphia

I have lived in Philadelphia for almost ten months now and that time can be split into two different residences. For the first, I took the El to and from Centre City. For the second, I walk to and from work. I look for living spaces near transit lines. In Chicago I took the El for eight years to get home. But to get to work, I often used the 143 express bus. Personally, I prefer trains and subways to busses—faster, dedicated right-of-way, Amtrak even has WiFi. But, busses are an integral part of a dense city’s transit network. You can cram dozens of people into one vehicle and remove several cars from the road. Here in Philadelphia, however, as the Inquirer reports, bus ridership is down over the last two years at the same time as ride-hailing apps are growing in usage.

For those interested in urban planning and transit, the article is well worth the read. But let’s look at one of the graphics for the article.

Lots of red in Centre City
Lots of red in Centre City

The map uses narrow lines for bus routes and the designer wisely chose to alternate between only two shades of a colour: high and low values of either growth (green) or decline (red). But, and this is where it might be tricky given the map, I would probably dropdown all the greys in the map to be more of an even colour. And I would ditch the heavy black lines representing borders. They draw more attention and grab the eye first, well before the movement to the green and red lines.

And the piece did a good job with the Uber time wait map comparison as well. It uses the same colour pattern and map, small multiple style, and then you can see quite clearly the loss of the entire dark purple data bin. It is a simple, but very effective graphic. My favourite kind.

Still haven't used Uber yet. Unless you count the times I'm being put into one by a friend…
Still haven’t used Uber yet. Unless you count the times I’m being put into one by a friend…

Anyway, from the data side, I would be really curious to see the breakout for trolleys versus busses—yes, folks, Philly still has several trolley lines. If only because, by looking at the map, those routes seem to be in the green and growing category. So as I complain to everyone here in Philly, Philly, build more subways (and trolleys). But, as the article shows, don’t forget about the bus network either.

Credit for the piece goes to the Inquirer graphics department.

Stabby Stabby Sexy Sexy Stabby Stabby

Happy Friday, all.

This past Sunday Series Seven of Game of Thrones began. And, no spoilers here, but it basically served as an episode to set the table for this series and its plot lines. But this piece from the Washington Post does a good job of summarising the deaths in the show over the previous six series. That does have some spoilers, but I chose my screenshot from minor characters in Series One. So I should not be ruining it for too many people.

MInor deaths and story locations, no spoilers for those of you who want to start watching the show
MInor deaths and story locations, no spoilers for those of you who want to start watching the show

Credit for the piece goes to Shelly Tan.

Traffic Accidents in Philadelphia

I’m working on a set of stories and in the course of that research I came across this article from Philly.com exploring traffic accident in Philadelphia.

Lots of red there…
Lots of red there…

The big draw for the piece is the heat map for Philadelphia. Of course at this scale the map is pretty much meaningless. Consequently you need to zoom in for any significant insights. This view is of the downtown part of the city and the western neighbourhoods.

A more granular view
A more granular view

 

As you can see there are obvious stretches of red. As a new resident of the city, I can tell you that you can connect the dots along a few key routes: I-76, I-676, and I-95. That and a few arterial streets.

Now while I do not love the colour palette, the form of the visualisation works. The same cannot be said for other parts of the piece. Yes, there are too many factettes. But…pie charts.

 

This is the bad kind of pie
This is the bad kind of pie

From a design standpoint, first is the layout. The legend needs to be closer to the actual chart. Two, well, we all know my dislike of pie charts, in particular those with lots of data points, which this piece has. But that gets me to point three. Note that there are so many pieces the pie chart loops round its palette and begins recycling colours. Automotives and unicycles are the same blue. Yep, unicycles. (Also bi- and tricycles, but c’mon, I just want to picture some an accident with a unicycle.)

If you are going to have so many data points in the pie chart, they should be encoded in different colours. Of course, with so many data points, it would be difficult to find so many distinguishable but also not garish colours. But when you get to that point, you might also be at the point where a pie chart is a bad form for the visualisation. If I had the time this morning I would create a quick bar chart to show how it would perform better, but I do not. Trust me, though, it would.

Credit for the piece goes to Michele Tranquilli.

Trump’s Polling

My battery is about to die this morning and I don’t have my charger so this is going to be a shorter piece than usual. But I wanted to look back on the 100 Day polling that the New York Times posted. It does paint an interesting picture of somebody so polarising that Trump is probably safe despite being one of the least favourably viewed presidents in modern times. Why? Because his supporters are so fervently loyal.

Not only is Trump low, he's low historically
Not only is Trump low, he’s low historically

But that piece is almost a month old now. And so I wanted to point out something that FiveThirtyEight is doing—a running tracker of Trump’s polling. I am sure I will return to it in the future, after all we have over three and a half years to go until the next four year presidential term begins.

Trump is pretty low…
Trump is pretty low…

Credit for the piece goes to Karen Yourish and Paul Murray for the Times and Aaron Bycoffe, Dhrumil Mehta, and Nate Silver for FiveThirtyEight.

The World’s Fighter Jets

As you know, I am a sucker for military-related things. So here we have a piece from the Wall Street Journal on the leading fighter jets of the world. If you have a bone to pick on which jets were included, please take that up with them and not me.

Of course, speed isn't everything…
Of course, speed isn’t everything…

The screenshot is from the end of an animation where they depict the maximum range and the relative speed of each aircraft against each other.

Credit for the piece goes to Andrew Barnett, Jason French, and Robert Wall.

The Disappearing Urban Middle Class

Today we look at income in American cities and in particular the middle class disappearance. The Guardian published the graphics, but they originate with Metrocosm, LTDB at Brown, and IPUMS National Historical Geographic Information System. So what are we looking at? Well, the big one is a set of small multiples of cities and their income breakdowns as percentages of city census tracts. This screenshot is static, but the original is an animated .gif.

The flattening of the curve
The flattening of the curve

I have a few issues with the design of the graphic, the most important of which is the colour palette. If the goal is to focus on the decline of the middle class—and I admit that may be the point of the Guardian’s authors and not the original authors—why are the most visually striking colours at the top of the income distribution. Instead, you would want to draw attention to the middle of each chart, not the right. And if the idea was that the darker colours represent the higher income groups, well the positioning of each bar on the chart and the axis labelling does that already. After all, if anything, the story is that in a number of cities the middle class has shrunk while the lower income groups have grown. And you can barely see that with the lower income groups coloured yellow.

My other issues are more minor design things such as the city labelling. I kept reading the label as being below the bars, not above as it actually is.

And then I wonder if a different chart form would be more effective at showing the decline in the middle class. Perhaps a line chart plotting the beginning and end points for each cohort?

Then the piece gets into some three-dimensional maps that you can spin and rotate.

Just stop
Just stop

Yeah. Shall I count the ways? A more conventional choropleth would have served the purpose far more effectively. The dimensionality hides lower income tracts behind higher ones. The solution? Allow the user to rotate and spin the map? No, get rid of the dimensionality. It offers little to the understanding of the underlying data. Not to mention, are the areas of shadows shadows? Or are they another bin or cohort of income?

And then you have to read the piece to get a fuller understanding of my criticism.

But don’t worry, I can quote it.

Chicago was largely successful transitioning away from manufacturing to a service-based economy. This shift is evident in the bifurcated pattern present in 2015 – a heavy concentration of wealth in the business/financial district and marked decline in the surrounding area.

Those of you who read this blog from Chicago or who have lived in Chicago will pick up on it. The rest of you not so much. The concentration of wealth is not located in the business/financial district. Those dark red skyscrapers are not actual skyscrapers, they are census tracts located not in the financial district, but the areas of River North, Old Town, Gold Coast, &c. Thinking of the issue more logically, yes incomes are up in cities that are doing well. But how many of those very wealthy live on the same block as their office? Not many. Your higher income is going to be concentrated in residential or mixed-residential neighbourhoods near, but not in the business/financial district.

The data behind this work fascinates me. I just wish the final graphics had been designed with a bit more consideration for the data and the stories therein. And a little bit of proper understanding of the cities and their geography would help the text.

Credit for the piece goes to Metrocosm, LTDB at Brown University, and IPUMS National Historical Geographic Information System.

Georgia 6th Special Election

Wow do we have a lot to talk about this week. Probably bleeding into next week to be honest. But, last night was the special election for the Georgia 6th.

For those of you not following politics, the congressman representing it was Tom Price; he is now the Secretary of Health and Human Services. Consequently, Georgia needed to elect a fill-in for the Atlanta-suburbs district. That election was between 18 candidates last night. The race could have been won outright, but it would have required a vote total over 50%.

That did not happen—and realistically with 18 people running was not likely. But, Democrats hoped they could get their candidate in at 50+%.

The live results from early in the evening
The live results from early in the evening

This screenshot is from a nice piece by the New York Times. As you all know by now, I am not a huge fan of choropleth maps. They distort geographic area and population. But, I like the arrangement of these small multiples. It does a nice job of comparing the results for the five major candidates. I particularly like the addition of the 2016 presidential election result. With the cratering poll approvals of Donald Trump, could some of the paler red precincts flip in June?

The results from later in the evening
The results from later in the evening

The above screenshot comes from BuzzFeed, whose coverage I followed via live streaming last night. They used a cartogrammic approach, assuming that cartogrammic is actually a word. The colours could use a bit more sophistication—the best example being the Democratic–Republican margin map where the blues are darker than the reds and have a hopefully unintended greater visual weight.

Credit for the piece

Get Ready Folks

Well have we got an interesting week this week. Friday begins Trump Time. So hold onto your Twitter accounts, folks. But before we get there, I wanted to do a short week of some data-driven graphics that take a look at the state of things.

Instead of what I had intended for today, let us take a look at a new post from the Wall Street Journal that examines GDP, inflation, industrial production, and the unemployment rate in advanced economies. At its most basic level, the graphics show how many of the 39 advanced economies have a value within a one-percentage point range. The size of the dots indicates how many countries fall within the bin.

A look at advanced economies' GDPs
A look at advanced economies’ GDPs

What keeps getting me, however, is the colour. Nowhere does the piece explain what the colour represents. Does it represent anything? I think it might only be used to show the ranges in the values, not the number of countries sharing said values. And if that is the case, it is a poor design decision.

My eye goes to the colour first before it goes to the dot density let alone the size of the dots. Like a Magic Eye, when I stare at the piece long enough, I begin to see the overall trend for each metric. But blink and the colours reassert their visual dominance.

I wonder what would happen if the graphic settled on a single colour? My instinct says that the patterns would become far clearer, because colour change would no longer be a visual pattern needing interpretation—even though it needs no interpretation from a data standpoint. By limiting the number of visual patterns, the piece would make the data stand out more clearly and make for clearer communication.

If an editor screams something like “It needz more colourz!!1!”, I would reserve four separate colours and then use one and only one for each of the four metrics.

That all said, what the piece does really well is explain segments of the data. In the above screenshot, you can clearly see and get the overall GDP story. But then from there you read down and get explanations or callouts of the overall to provide more context and information. The designer greys out the remainder of the dots and allows the colour to emphasise those countries in focus. A lightly transparent overlay allows for the background dots to remain faintly visible while the text can clearly be read.

All in all, I am not sure where I fall on this particular piece. It does some things well, others not so much. But either way, the piece does paint an interesting portrait of populism’s potential causes.

Credit for the piece goes to Andrew Van Dam.

The Federal Funds Rate

In my new role as data visualisation manager at the Philadelphia Federal Reserve, I am learning a lot about what the Fed does and how it does it. Needless to say, this piece from Bloomberg interested me as it displayed how the federal funds rate has changed over time.

How this potential hike cycle would compare to the two previous
How this potential hike cycle would compare to the two previous

What I really enjoy is how they colour-coded the two previous hiking cycles as well as what I think everyone presumes will be a new one. And those colours then move on down the piece into the dot plots. The dot plots show various potential factors in the decision-making process, and just how far off the current hiking cycle is from the two previous.

Credit for the piece goes to Chloe Whiteaker, Jeremy Scott Diamond, and Jeanna Smialek.

Populism Marches on in Europe

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.

The datasets in the map and bar chart are linked, a nice touch
The datasets in the map and bar chart are linked, a nice touch

Credit for the piece goes to Bloomberg’s graphics department.