Two weeks ago I posted about an article from the BBC that used graphics about which I was less than thrilled. Inconsistent use of axis lines, centring the graphic were two of the things that irked me. Two weeks hence, I do want to draw some positive attention to another article in the BBC. This one discusses the, for many of us, impending return to the office. (I’ve also heard the phrase “return to work”, although a coworker of mine pointed out that’s not a great phrase because many of us never stopped working when we decamped for our flats and houses.)
The article discusses why some think the return to a five-day office week will occur within the next few years. There is some sound logic to the idea and for those like your author who are closely following the issue, I recommend the article.
But that’s not why we’re here, instead I wanted to focus on the one data visualisation graphic in the piece. It displays the amount of office space used in the city centres of six different UK cities outside London.
But what about Slough?
Here we have small multiples with the same fixed y-axis display. Axis lines are present and consistent and the baseline is distinct from the other lines. Solid improvement over what we discussed two weeks ago.
My only quibble? The colours here are not necessary. A single colour would work because each city’s graphic exists apart from the rest. The charts also all represent the same type of data, occupied office space. If the chart were doubling or tripling up cities somehow—though I wouldn’t want to see this as a stacked area chart—I would buy the need for colours to differentiate the cities. This, however, represents an opportunity to use a single, BBC-branded colour to define the experience whilst not negatively impacting the communication from the data visualisation standpoint.
Again, though, that’s a minor quibble. Of course, the BBC puts out copious amounts of content daily and I see only a fraction, but it is nice to see an improvement. Furthermore, at the end of the article I also spotted a graphic credit, which I don’t often see—and honestly cannot recall when I last saw period—from the BBC.
I wonder if moving forward the BBC intends to highlight the contributors to articles who are not solely the writers, i.e. the people creating the graphics? Of course, if we did that, we should also probably take a look at the copy editors who also play a role. Especially for an online article as opposed to say a print newspaper or magazine where space is money.
Technical difficulties yesterday. But I wanted to run the latest Covid numbers to start this week of posting, so we’re just going to use the Monday data, which is the lowest of the week since it captures the data reported by authorities on Sunday. That said, where are we?
Last week we began to see a slowdown in the rate of declining cases, though, crucially, cases were still in decline. The good news is that cases continue to decline. The seven-day averages for all five states are now well below 1,000 new cases per day, with Illinois dipping below 500. Only Pennsylvania remains above that level at 544 new cases per day.
New case curves for PA, NJ, DE, VA, & IL.
We are no longer seeing the numbers fall by hundreds per day, most notably in New Jersey, but we remain in a race to the bottom. Unfortunately, with significant numbers of the population refusing vaccination and the near certainty of this coronavirus becoming endemic, i.e. a persistent, circulating virus, we will never reach zero. The numbers at some point will bottom out and a slowing rate of decline could indicate nearing that point.
Death curves for PA, NJ, DE, VA, & IL.
Deaths have continued their even slower decline over the last week. New Jersey’s seven-day average fell into the high single digits for the first time since November. Virginia, which had flirted with single-digit days, has now reported a week-long run of about nine deaths per day. Delaware, due to its low population only reached double digits for most of February, but has seen a slight uptick to over two deaths per day.
The two most interesting states with regards to deaths are Illinois and Pennsylvania, for different reasons. Starting with Illinois, we are beginning to see a pattern of bottoming out. For most of the last week the seven-day average has hovered about 20 with day-to-day changes of one or two additional/fewer deaths per day. We will have to watch over the coming week whether the numbers can resume pushing downwards or if we continue to see this bottoming out.
Then we have Pennsylvania. Through the beginning of the weekend, we saw progress as the Commonwealth’s seven-day average dropped below 20 deaths per day for the first time since October. Two days ago the Department of Health reported an additional 185 deaths, but then yesterday the total number of deaths dropped by 174. I haven’t yet been able to piece together what happened, but it does make the sudden spike in the seven-day average—to 46 deaths per day—a wee bit suspect.
Finally we have vaccinations. And the news is there is no news. Over the last week we have seen almost zero growth in the number of fully vaccinated individuals in Pennsylvania (1.8 percentage points), Virginia (1.53 pts), and Illinois (2.41 pts).
Total full vaccinations in PA, VA, & IL.
If we look at where the cumulative rates remain stuck, however, we see numbers in the mid-40s, short of 2/3 the estimated herd immunity range. The flattening of the curve, indicating slowing rates of vaccination, have become increasingly pronounced. This is not the curve we want to see flattened. Ideally this slowdown would have occurred nearer the 70% range and we could have eased into the estimated herd immunity range.
That said, we are approaching 50% in these three states and numerous communities, though not all, within these states are now over 50% fully vaccinated. But the longer we have largely unvaccinated reservoirs available, the more likely it is we will see new variants emerge that could potentially evolve to be more transmissible or even more deadly.
And so for any of my readers who haven’t received their shots yet, I encourage you to please do so. They’re free, they’re effective, and they’re necessary for us to get back to some sense of normal.
This one from Indexed made me literally laugh out loud. Probably because I, like many of you, know all three types she describes. And after a week, we can probably all use a laugh before starting the weekend.
With the release of the 2020 US Census’ topline data, we can see which state populations increased and which few decreased. And in that we can sort, or resort, states by population. The Washington Post did this a few weeks ago with an interactive ranking chart in a nice online article. (I’d be curious what the print version was, alas I only receive the New York Times.)
The piece begins with a nice intro motion graphic that selects states and shows how their ranking among the other states (plus the District of Columbia, DC), has evolved since 1920.
Here we see the fall of Iowa in the rankings.
After scrolling down briefly, the reader enters a portion of the story displayed by keeping the hero graphic static whilst blurbs of texts scroll over the lines. As the blurbs move past, different states or sets of states become highlighted to draw attention to them.
I guess I’m picking on Iowa?
This works really well. When discussing the case of Iowa vis-a-vis the growth of California, Texas, and Florida, I don’t need to see the story of Nebraska. Especially as the end of the piece features this hero graphic as an interactive, explore-the-data piece of content. I don’t have a screenshot of that, because it’s really just the above two but with a dropdown selector and a legend.
As the user scrolls through the story, they move past the semi-motion graphic and into a text-driven narrative for each region of the United States. I’ve highlighted only the Northeast, where I was born, raised, and presently live. As an aside, I remember my family completing the 2000 Census around the kitchen table. The 2010 Census I filled out at a small desk not long after I moved into my second flat in Chicago. And this most recent one I completed whilst under quarantine here in Philadelphia.
The Northeast. Definitely not Iowa.
This section of the article uses static images with the region’s constituent states highlighted. Again, this works really well, because when looking at the Northeast, I’m still not interested in Nebraska. And also again, we have the interactive explorer at the end of the article.
Overall this is a really strong piece from the Post. I have some quibbles with the design, primarily I don’t understand the function of the connecting lines’ fades and curves. But I find neither too terribly distracting from the content of the graphic.
Credit for the piece goes to Harry Stevens and Nick Kirkpatrick.
Two weeks ago I posted about the death toll in the latest conflict between Israel and Hamas. As it happened, later that morning when I opened the door, there was this graphic sitting above the fold on the front page of the New York Times.
They added a map.
The piece sits prominently on the front page, but tones down the colour and detail on the map to let the graphical elements, the coloured boxes, shine and take their prominent position.
Here’s a detail photo I took in case the above is too small.
Maps make everything cooler.
Ultimately, the piece isn’t too complex and isn’t more than what I made. However, the map adds some important geographical context, showing just where the deaths were occurring.
The piece also highlights the deaths in the West Bank and those in Israel from civil unrest. That was data I didn’t have at the time.
redit for the piece goes to the New York Times graphics department..
Last week I wrote about how new cases had maybe flattened a wee bit in their rapid drop from peaks earlier this year. But the good news is that even in where new cases declines may have slowed down, they continue to decline.
New case curves for PA, NJ, DE, VA, & IL.
We can see the tails at the right ends are all back to declining shapes. Delaware is perhaps the most deceptive, because remember that there was the anomalous spike from late processing of earlier new cases.
I had noted that deaths had finally seen some data showing them dropping. That has held true to some degree.
Death curves for PA, NJ, DE, VA, & IL.
Indeed, the tails at the end of each state have shown slow declines. Delaware is even near 0 deaths per day. Illinois, however, is an exception with a small increase lately.
Finally, a brief look at vaccinations.
Full vaccination curves for PA, VA, & IL.
You can see that the rate of full vaccinations has begun to slow. All three states we cover are over 40%, though all are below 45%. Pennsylvania is difficult to evaluate, however, because for the last four days Philadelphia has not updated its numbers. And as the largest county by far in the state, it’s shifts can swing the overall state numbers.
Those of my readers who know me well know that I’ve long been a fan of Star Trek. And so we’ve made it to the weekend. And over at Indexed earlier this month, well, we have a great science fiction comparison.
Here in the states we have a bank holiday Monday, so Star Trek is just a great way to start a holiday weekend.
The needs of the many outweigh the needs of the few. Or the one.
Last week I wrote about the deaths in Gaza and Israel, where a ceasefire is holding at the time of writing. But I also included a graphic about the size of Hamas’ rocket arsenal. In a social media post I commented about how it appeared Hamas had also changed its tactics given Israel’s Iron Dome missile defence system.
Specifically, in the past Hamas launched rockets at a fairly even pace. However, with Iron Dome, Israel could—and did—defend about 90% of incoming fire. Consequently, Hamas tried to swarm Israel’s defences and some fire did leak through, killing over a dozen Israelis. I was looking for data on that, but couldn’t find what I wanted.
Clearly I didn’t look hard enough. This graphic appeared in the Wall Street Journal last week. It shows the cumulative number of rockets launched at Israel during this most recent surge in violence compared to the 2014 war between Israel and Hamas.
A very different profile for Hamas’ attack
In 2014, you can see even, incremental steps up in the total count of rockets. But from earlier this month, you can see much steeper increases on a daily basis with more time between those swarms.
From a design standpoint, it’s a really nice graphic. I will often say that good graphics don’t need to be crazy or flashy. This is neither. It relies on solid fundamentals and executes well. All the axis lines are labelled and the data series fall within the bounds of the x- and y-axis. The colours chosen contrast nicely.
Credit for the piece goes to the Wall Street Journal graphics department.
Two weeks ago I was reading an article in the BBC that fact checked some of President Biden’s claims about the economy. Now I noted the other day in a post about axis lines and their use in graphics. Axis lines help ground the user in making comparisons between bars, lines, or whatever, and the minimum/maximum/intervals of the data set.
I was reading the article and first came upon this graphic. It’s nothing crazy and shows job growth in the aggregate for the first three months of a presidential administration. A pretty neat comparison in the combination of the data. I like.
Pay attention to what you see here. There will be a quiz.
I don’t like the lack of grid lines for the axis, however. But, okay, none to be found.
I keep reading the article. And then a couple of paragraphs later I come upon this graphic. It looks at the monthly figures and uses a benchmark line, the red dotted one, to break out those after January 2021 when Biden took office.
Spot the differences.
But do you notice anything?
The lines for the y-axis are back!
The article had a third graphic that also included axis lines.
I don’t have a lot to say about these graphics in particular, but the most important thing is to try and be consistent. I understand the need to experiment with styles as a brand evolves. Swap out the colours, change the styles of the lines, try a new typeface. (Except for the blue, we are seeing different colours and typefaces here, but that’s not what I want to write about.)
First, I don’t know if these are necessarily style experiments. I suspect not, but let’s be charitable for the sake of argument. I would refrain from experimenting within a single article. In other words, use the lines or don’t, but be consistent within the article.
For the record, I think they should use the lines.
Another point I want to make is with the third graphic. You’ll note that, like I said above, it does use axis lines. But that’s not what I want to mention.
At least we have lines.
Instead I want to look at the labelling on the axes. Let’s start with the y-axis, the percentage change in GDP on the previous quarter. The top of the chart we have 30%. As I’ve said before, you can see in the Trump administration, the bar for the initial Covid-19 rebound rises above the 30% line. It’s not excessive, I can buy it if you’re selling it.
But let’s go down below the 0-line. Just prior to the rebound we had the crash. Similarly, this extends just below the -30% line. But here we have a big space and then a heavy black line below that -30% line. It looks like the bottom line should be -40%, but scanning over to the left and there is no label. So what’s going on?
First, that heavy black line, why does it appear the same as the baseline or zero-growth line? The axis lines, by comparison, are thin and grey. You use a heavier, darker line to signify the breaking point or division between, in this case, positive and negative growth. Theoretically, you don’t need the two different colours for positive and negative growth, because the direction of the bar above/below that black line encodes that value. By making the bottom line the same style as the baseline, you conflate the meaning of the two lines, especially since there is no labelling for the bottom line to tell you what the line means.
Second, the heaviness of the line draws visual attention to it and away from the baseline, especially since the bottom line has the white space above it from the -30% line. Consider here the necessity of this line. For the 30% line that sets the maximum value of the y-axis, we have the blue bar rising above the line and the administration labels sit nicely above that line. There is no reason the x-axis labels could not exist in a similar fashion below the -30% line. If anything, this is an inconsistency within the one chart, let alone the one graphic.
Third, is it -40%? I contend the line isn’t necessary and that if the blue bar pokes above the 30% line, the orange bar should poke below the -30% line. But, if the designer wants to use a line below the -30% line, it should be labelled.
Finally, look at the x-axis. This is more of a minor quibble, but while we’re here…. Look at the intervals of the years. 2012, 2014, 2016, every two years. Good, make sense. 2018. 20…21? Suddenly we jump from every two years to a three-year interval. I understand it to a point, after all, who doesn’t want to forget 2020. But in all seriousness, the chart ends at 2021 and you cannot divide that evenly. So what is a designer to do? If this chart had less space on the x-axis and the years were more compressed in terms of their spacing, I probably wouldn’t bring this up.
However, we have space here. If we kept to a two-year interval system, I would introduce the labels as 2012, but then contract them with an apostrophe after that point. For example, 2014 becomes ’14. By doing that, you should be able to fit the two-year intervals in the space as well as the ending year of the data set.
Overall, I have to say that this piece shocked me. The lack of attention to detail, the inconsistency, the clumsiness of the design and presentation. I would expect this from a lesser oganisation than the BBC, which for years had been doing solid, quality work.
The first chart is conceptually solid. If Biden spoke about job creation in the first three months of the administration vs. his predecessor, aggregate the data and show it that way. But the presentation throughout this piece does that story a disservice. I wish I knew what was going on.
Credit for the piece goes to the BBC graphics department.
As I prepared to reconnect and rejoin the world, I spent most of the weekend prior to full vaccination cleaning and clearing out my flat of things from the past 14 months. One thing I meant to do more with was printed pieces I saw in the New York Times. Interesting pages, front pages in particular, have been piling up and before recycling them all, I took some photos of the backlog. I’ll try to publish more of them in the coming weeks and months.
You may recall this time last month I wrote about a piece from the New York Times that examined the politicisation of vaccinations. I meant to get around to the print version, but didn’t, so let’s do it now.
Now in print…
I noted last time the use of ellipses for the title and the lack of value scales on the x-axis. Those did not change from the online version. But look at the y-axis.
For the print piece I noted how the labels were placed inside the chart. I wondered at the time—but didn’t write about—how perhaps that could have been a technical limitation for the web. But here we can see the labels still inside. It was a deliberate design decision.
Keeping with the labelling, I also pointed out Wyoming being outside the plot and it is here too, but I finally noted the lack of a label for zero on the first chart. Here the zero does appear, as I would have placed it. That does make me wonder if the lack of zero online was a technical/development issue.
Finally, something very subtle. At first, I didn’t catch this and it wasn’t until I opened the image above in Photoshop. The web version I noted the use of tints, or lighter shades, for two different blues and two different reds. When I looked at the print, I saw only one red and one blue. But they were in fact different, and it wasn’t until I had zoomed in on the photo I took when I could see the difference.
I’ve got the blues…
The dots do have two different blues. But it’s very subtle. Same with the red.
So all in all the piece is very similar to what we looked at last month, but there were a few interesting differences. I wonder if the designers had an opportunity to test the blues/reds prior to printing. And I wonder if the zero label was an issue for developers.
Credit for the piece goes to Lauren Leatherby and Guilbert Gates.
