choropleth – Page 4 – Coffee Spoons

Sunday Covid-19 Data

Another day, more cases of coronavirus and Covid-19. So let’s take a look at Sunday’s data as there were some interesting things going on.

First, let’s dispense with Virginia. The state is enhancing its reporting structure, and so they admit the data is likely an underestimate of the present situation in Virginia. So here’s Virginia, nothing really changed.

Moving on, we have Pennsylvania. Here we are beginning to truly see the disparity between the cities in the southeast and southwest, namely Philadelphia and Pittsburgh, and the T that describes what sometimes is used to describe Pennsyltucky. (Though it also includes cities like Harrisburg, the state capital.) The point is that the T of Pennsylvania has yet to suffer greatly from the outbreak. Of course, it’s also the part of the state least equipped to deal with a pandemic.

New Jersey is just bad. One can make the argument that South Jersey is hanging on. (Though I will touch on that later with an idea for today’s afterwork work.) Bergen County in the northeast is likely to surpass 10,000 cases on its own today. And that will put it above most states.

Delaware is tough because it sits as a small state next to several much larger ones. But, the numbers seem to indicate the outbreak is still worsening. Though in terms of geographic spread, there’s little to say other than that New Castle County, home to Wilmington, in the north is the heart of the state’s outbreak.

Illinois is a fascinating state, because of how dissimilar it is compared to Pennsylvania, a state which has a similar number of people.

The map shows that geographic spread still has a little way to go before reaching every county in the state. But the outbreak has been there longer than in Pennsylvania. And most of the darker purples are concentrated in the northeast, in Chicago and its collar counties. Compare that to Pennsylvania above where you will see dark purple scattered across the cities of its eastern third, e.g. Allentown and Scranton, and in the western parts near Pittsburgh. This too could be worth exploring in depth in the future.

Lastly I want to get to the cases curves charts. Here we look at the daily new cases in each state.

The curves, flattening or otherwise, of the five states.

And unfortunately Sunday’s numbers will impact the Virginia curve, but it overall looks as if the state is worsening. I would argue that Illinois, which appears to be bending towards a steadying condition is likely in a weird weekly pattern where it appears to stabilise on weekends and then resumes reported infections come Monday. Pennsylvania might well be flattening its curve. I would want to see a few more days’ worth of data before stating that more definitively. Let’s give it to Wednesday or Thursday.

And then in New Jersey we have a fascinating trend. The curve of increasing number of cases has clearly broken. But it also is not shrinking. Instead, it seems to be more of a plateau. And in that case, the outbreak in New Jersey is not getting worse, but it’s also not getting any better. At least not numerically. However, the goal of flattening the curve is to create a slower, more steady increase in case numbers to help hospitals cope with surge volumes. So good news?

Credit for the pieces is mine.

Wednesday’s Corona Update

As I said yesterday, since people are finding these updates helpful on the social media, I am going to repost the previous evening’s graphics I make on the Coronavirus Covid-19 outbreak here on Coffeespoons as well. So while today is Thursday, these are the numbers states provided yesterday, so it’s more of a Wednesday update.

But here I can start with the flatter curves graphic. The New Jersey numbers in particular look good—I mean they’re still bad. Of course we are just a few big breaches of quarantine and lapses in social distancing from reversing that progress.

State-wise, Pennsylvania continues to worsen. However, a close look at the slope of the line in the previous chart indicates that the steepness of the growth may be lessening. Deaths passed 300 and cases are now firmly entrenched on both sides of the state with the rural, less densely populated areas in the Ridge and Valley portion of the state seemingly hit not as hard.

Despite the potential flattening, New Jersey is just in a rough spot. The final bastions of low case numbers in South Jersey are slowly filling up as Cape May County passed the 100-case threshold.

Delaware continues to accelerate and is now past 1000 cases.

Virginia continues to see cases spreading in the eastern, more populous portions of the state. And at 75 deaths, it’s nearing the 100-death threshold.

Illinois is seeing deaths occur away from Chicago, in the St. Louis suburban counties and in and around Springfield and Champaign and Bloomington areas.

Credit for the piece goes to me.

Tuesday’s Data on Covid-19

Here are the Tuesday figures for Pennsylvania, New Jersey, Delaware, Virginia, and Illinois. At the end is an updated version of the flattening curves chart as well. Given the value of these graphics that people have been texting, emailing, and DMing me on social media, I might consider making these a regular staple here on my blog as well. I would probably slowly write about other graphics covering the outbreak as well.

Any feedback is welcome on how to make the graphics more useful to you, the public.

Pennsylvania has finally reached the point where the virus has infected at least one person in every county. Now, if we shift our attention a wee bit to the deaths, we can see those are still largely confined to the eastern third of the state.

New Jersey continues to suffer greatly. But a sharp increase in new cases could be a blip, or it could mean the curve isn’t flattening. We need more data to see a longer trend. Regardless, over 3000 more people were reported infected and over 200 more died.

Delaware worsened significantly. As a small state, it has a lower captive population. But it is rapidly approaching 1000 cases. In fact, I would not be surprised if that is the headline from Wednesday.

Virginia also saw a significant uptick in cases. And most counties and independent cities in eastern Virginia now report cases. But the rural, mountainous counties in the west and southwest are not uniformly infected. At least not yet.

Illinois saw some geographic spread, but again, compared to a state like Pennsylvania, the worst in Illinois is disproportionately concentrated in the Chicago metropolitan area.

Lastly, the curves are not flattening in all the states but maybe New Jersey. But as I noted above, the higher daily cases there might be a blip.

Credit for the pieces goes to me.

Where’s My Corona? Another Round, Please

This past weekend I continued looking at the spread of COVID-19 across the United States. But in addition to my usual maps of Pennsylvania, New Jersey, Delaware, Virginia, and Illinois, I also looked at the number of cases across the United States adjusted for population. I then looked at the five aforementioned states in terms of new cases to see if the curve is flattening. Finally, I looked at the number of hospital beds per 1000 people vs the number of cases per 1000 people.

The latter in particular I wanted to be an examination of hospitalisation rates vs ICU beds, which are a small fraction of total hospital beds. But as I could not find that data, I made do with overall cases and overall beds.

So first let’s look at the cases across the U.S. What you can see is that whilst New York and New Jersey do have some of the worst of the impact, Washington is still not great and Louisiana and Michigan are also suffering.

And then when we look at the states by their cases per 1000 people and their hospital beds per 1000 people, we see that the states often claimed to be overwhelmed, New York, New Jersey, and Washington are all well over the blue line, which indicates an equal number of beds and cases per 1000 people, or near it. Because it is important to remember that not all beds are the type needed for COVID-19 victims, who often require the more fully kitted out ICU beds. Additionally, not all cases are severe enough to warrant hospitalisation.

Cases per 1k people vs hospital beds per 1k people

Then from the broader national view, we can look at the states of interest. Here, those of you who have been following my social media posts, you can see fewer dark purples in these maps. That’s because I have adopted a new palette that has sacrificed granularity at the lower end of the scale and added it at the top, a particular need in New Jersey and the Philadelphia and Chicago metro areas. And finally we look at the daily new cases to see if that curve is flattening.

Pennsylvania now has almost every county infected. But unlike Illinois, which has a similar infection rate but more unaffected counties, Pennsylvania has fewer cases in its big city, Philadelphia, and has more cases in the smaller cities and towns.

New Jersey is just a disaster. Deaths are now reported in every county—so I can probably remove those orange outlines. The only potential good news is that new cases for the second day in a row were fewer than the day before. It could be a blip. But it could also be a signal that the peak of infection has or is nearing. That said, hospitalisations and deaths are lagging indicators and could take two weeks to follow the positive test results. So in the best case scenario that this is a peak, New Jersey is far from out of the woods.

Delaware is the smallest state I look at—and one of the smallest in the union overall—but its cases are worryingly increasing rapidly, although like every state I examine in detail it had fewer new cases Sunday than Saturday.

Virginia is in a better spot overall than the other four states. You can see that in the national map above. And most of Virginia’s cases are concentrated in the DC and Richmond areas as well as the cities along the peninsulas jutting into the Chesapeake.

Illinois is, as noted above, similar to Pennsylvania in terms of infections. In terms of deaths, however, it is doubling Pennsylvania’s numbers. And most of its cases are located in and around Chicago. Big chunks of downstate Illinois are unaffected or lightly affected compared to the Commonwealth.

Finally, as I noted in New Jersey, could these lower numbers Sunday than Saturday be meaningful? Possibly. But in all five states? Highly unlikely. Regardless, we can look at the number of daily new cases and see if that curve of infection is flattening. We should wait several days before beginning to make that assessment. But one can hope.

All of this is to say that things are bad and likely will continue to get worse. But I will keep looking at the data daily and presenting it to the public to keep them informed.

Credit for this piece is mine.

Another Friday, Another Corona with Lime Update

Today is yet another Friday in the pandemic. And so I wanted to just upload a few of the graphics I have been making for family, friends, and coworkers and posting on the Instagram and the Facebook. I did this two weeks ago as well, and if you compare those maps to these, you will see quite a stark difference. But on to today’s maps.

As a brief reminder, I am specifically looking at Pennsylvania, New Jersey, and Delaware—the tri-state region for my non-Philly followers—as well as Virginia and Illinois by the request of friends and former colleagues who live in those states. And then at the end I’ve been putting the tri-state region together to provide a fuller regional context.

Lastly, for today only, the Bureau of Labour Statistics published its jobs report about the number of job losses in March across the US. And…it wasn’t pretty.

Plus, the added bonus of the Bureau of Labour Statistics’ monthly jobs report. And spoiler, things aren’t so great out there.

Conditions in the national job market. Not great!

Credit for the work is mine.

The Spread of COVID-19 in Select States

By now we have probably all seen the maps of state coverage of the COVID-19 outbreak. But state level maps only tell part of the story. Not all outbreaks are widespread within states. And so after some requests from family, friends, and colleagues, I’ve been attempting to compile county-level data from the state health departments where those family, friends, and colleagues live. Not surprisingly, most of these states are the Philadelphia and Chicago metro areas, but also Virginia.

These are all images I have posted to Instagram. But the content tells a familiar story. The outbreaks in this early stage are all concentrated in and around the larger, interconnected cities. In Pennsylvania, that means clusters around the large cities of Philadelphia, Pittsburgh, and Harrisburg. In New Jersey they stretch along the Northeast Corridor between New York and Trenton (and along into Philadelphia) and then down into Delaware’s New Castle County, home to the city of Wilmington. And then in Virginia, we see small clusters in Northern Virginia in the DC metro area and also around Richmond and the Williamsburg area. Finally in Illinois we have a big cluster in and around Chicago, but also Springfield and the St. Louis area, whose eastern suburbs include Illinois communities like East St. Louis.

I have also been taking a more detailed look at the spread in Pennsylvania, because I live there. And I want to see the rapidity with which the outbreak is growing in each county. And for that I moved from a choropleth to a small multiple matrix of line charts, all with the same fixed scale. And, well, it doesn’t look good for southeastern Pennsylvania.

Then last night I also compared the total number of cases in Pennsylvania, New Jersey, Delaware, and Virginia. Most interestingly, Pennsylvania and New Jersey’s outbreaks began just a day apart (at least so far as we know given the limited amount of testing in early March). And those two states have taken dramatically different directions. New Jersey has seen a steep curve doubling less than every two days whereas Pennsylvania has been a bit more gradual, doubling a little less than every three.

For those of you who want to continue following along, I will be looking at potential options this coming weekend whilst still recording the data for future graphics.

Credit for the pieces is mine.

The Spread of COVID-19 in Pennsylvania

Over the last several days, along with most of the country, I’ve taken an interest in the spread of the novel coronavirus named COVID-19. Though, to be fair, it’s actually been in the news since early January, though early news reports like this from the Times, simply called it a mysterious new virus. At the time I thought little of it, because the news out of China was that it did not appear it could spread amongst humans. How did that idea…wait for it…pan out?

Anyway, over the last couple of days I’ve been making some maps for Instagram because people tend to look at a national map and see every nearly state infected when, in reality, there are pockets and clusters within those states. So I started looking at Pennsylvania. And initially, the cluster was along the Delaware River, namely Pennsylvania as well as its upper reaches near the Lehigh Valley and in the far northeast of the state.

But the spread has grown, and fairly quickly, with Montgomery County, a Philadelphia suburb, a hotspot. Consequently, the Pennsylvania governor has shut down all schools across the state and ordered non-essential shops, restaurants, and bars in the counties surrounding Philadelphia—as well as the county containing Pittsburgh—closed.

So 11 days in, here’s where we stand. (To be fair, I looked at including the early numbers out of today, but nothing has really changed, so I’ll wait until the evening figures are released before I update this again.)

Credit is mine. Data is the Pennsylvania Department of Health.

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

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.

Casual Fails?

In a recent Washington Post piece, I came across a graphic style that I am not sure I can embrace. The article looked at the political trifecta at state levels, i.e. single political party control over the government (executive, lower legislative chamber, and upper legislative chamber). As a side note, I do like how they excluded Nebraska because of its unicameral legislature. It’s also theoretically non-partisan (though everybody knows who belongs to which party, so you could argue it’s as partisan as any other legislature).

At the outset, the piece uses a really nice stacked bar chart. It shows how control over the levers of state government have ebbed and flowed.

You can pretty easily spot the recent political eras by the big shifts in power.

It also uses little black lines with almost cartoonish arrowheads to point to particular years. The annotations are themselves important to the context—pointing out the various swing years. But from an aesthetic standpoint, I have to wonder if the casualness of the marks detracts from the seriousness of the content.

Sometimes the whimsical works. Pie charts about pizza pies or pie toppings can be whimsical. A graphic about political control over government is a different subject matter. Bloomberg used to tackle annotations with a subtler and more serious, but still rounded curve type of approach. Notably, however, Bloomberg at that time went for an against the grain, design forward, stoic business serious second approach.

Then we get to a choropleth map. It shows the current state of control for each state.

X marks the spot?However, here the indicator for recent party switches is a set of x’s. These have the same casual approach as the arrows above. But in this case, a careful examination of the x’s indicates they are not unique, like a person drawing a curve with a pen tool. Instead these come from a pre-determined set as the x’s share the exact same shape, stroke lengths and directions.

In years past we probably would have seen the indicator represented by an outline of the state border or a pattern cross-hatching. After all, with the purple being lighter than the blue, the x’s appear more clearly against purple states than blue. I have to admit I did not see New Jersey at first.

Of course, in an ideal world, a box map would probably be clearer still. But the curious part is that the very next map does a great job of focusing the user’s attention on the datapoint that matters: states set for potential changes next November.

Here the states of little interest are greyed out. The designers use colour to display the current status of the potential trifecta states. And so I am left curious why the designers did not choose to take a similar approach with the remaining graphics in the piece.

Overall, I should say the piece is strong. The graphics generally work very well. My quibbles are with the aesthetic stylings, which seem out of place for a straight news article. Something like this could work for an opinion piece or for a different subject matter. But for politics it just struck a loud dissonant chord when I first read the piece.

Credit for the piece goes to Kate Rabinowitz and Ashlyn Still.

The Shifting Suburbs

Last we looked at the revenge of the flyover states, the idea that smaller cities in swing states are trending Republican and defeating the growing Democratic majority in big cities. This week I want to take a look at something a few weeks back, a piece from CityLab about the elections in Virginia, Kentucky, and Mississippi.

There’s nothing radical in this piece. Instead, it’s some solid uses of line charts and bar charts (though I still don’t generally love them stacked). The big flashy graphic was this, a map of Virginia’s state legislative districts, but mapped not by party but by population density.

Democrats now control a majority of these seats.

It classified districts by how how urban, suburban, or rural (or parts thereof) each district was. Of course the premise of the article is that the suburbs are becoming increasingly Democratic and rural areas increasingly Republican.

But it all goes to show that 2020 is going to be a very polarised year.

Credit for the piece goes to David Montgomery.