Biden’s English Ancestry

We all know Joe Biden as the Irish American president. And that’s no malarkey. But, go back far enough in your family tree and you may find some interesting ancestry and ethnic origins and that’s no different with Joe Biden. Keep in mind that our number of ancestors doubles every generation. You have four grandparents, and many of us met most of them. But you had eight great-grandparents. How many of those did you know? And you had 16 great-great-grandparents, you likely didn’t know any of them personally. It becomes pretty easy for an ethnic line to sneak into your ancestry.

And in Biden’s case it may well be English. Although sneaking in is probably a stretch, as this BBC article points out, because his patrilineal line, i.e. his father’s father’s father’s, &c., is likely English. Of course back in the day the Irish and the English mixing would have been unconscionable, at least as my grandmother would have described it. And so it’s easy to see how the exact origins of family lines are quietly forgotten. But that’s why we have genealogists.

The article eschews the traditional family tree graphic and instead uses only two charts. The first is a simple timeline of Biden’s direct ancestors.

Biden’s patrilineal timeline

No, it’s no family tree, but timelines are a critical tool used by genealogists because at its core, genealogy is all about time and place. And a timeline has got one of those two facets covered.

Timelines help visualise stories in chronological order. I cannot tell you the number of family trees I have seen where people who create trees casually simply copy and paste data without scrutiny. Children born well after the deaths of parents are common. Or children born to parents in their 50s or 60s—perhaps not strictly impossible, but certainly highly irregular. And so to see Biden’s ancestors plotted out chronologically is a common graphic for those who do any work in genealogy, which my regular readers know is my hobby.

That alone would make the article worth sharing. Because, I enjoyed that graphic. I probably would have created a separate line for the birthplace of each individual, but I quibble.

However, we have another graphic that’s not so great. And once again with the BBC I’m talking about axis lines.

American ethnic origins

Here we have a chart looking at US ancestry as claimed in the US censuses of 1980 and 2000. But we do not have any vertical lines making it easy for readers to accurately compare the lengths of the various bars. Twice lately I’ve posted about axis lines and the BBC. Third time’s the charm?

We can also look at using these not as bars, but as line charts as I did in this re-imagining to the right.

First, we no longer need two distinct colours, though you could argue the English line should be a highlight or call out colour given its role in the article. Instead each line receives a label at the right and only the English line crosses any other, but given their point-to-point slope, it’s not confusing like a line chart with all years between 1980 and 2000 could be.

Secondly, the slope here of the line reinforces the idea of falling population numbers. The bar chart also shows this, but through a leftward movement in bars. The bar option certainly works and there’s nothing wrong with it, but these lines offer a more intuitive concept of falling numbers.

I also added some clarification to the data definition. These lines represent the number of people who reported at least one ethnic ancestry—at the time US census respondents could enter upwards of two. For myself, as an example, I could have entered Irish and Carpatho-Rusyn. But my own small sliver of English ancestry would have been left off the list.

Ultimately, the declining numbers of responses along with some reporting on self-identification points to the disappearing concepts of “Irish American” or “English American” as many increasingly see themselves as simply White Americans. But that’s a story for another day.

In the meantime, we have Joe Biden, the Irish American president, with a small bit of English ancestry. Those interested in the genealogy, the article also includes some nice photos of baptismal records and marriage records. It’s an interesting read, though I’m hungry for more as it’s a very light duty pass.

Credit for the BBC pieces goes to the BBC graphics department.

Credit for my reimagination is mine.

Inflating Areas

One trend people have begun to follow lately is that of rising prices for consumer goods. If you have shopped recently for things, you may have noticed that you have been paying more than you were just a few weeks ago. We call this inflation. The Bureau of Labour Statistics (BLS) tracks this for a whole range of goods. We call the the consumer price index (CPI)

Prices can vary wildly for some goods, most notably food and energy. For those of my readers who drive, recall how quickly petrol/gasoline prices can change. Because of that volatility, the Bureau of Labour Statistics strips out food and energy prices and the inflation that excludes food and energy is what we call Core CPI.

Lately, we have been seeing an increase in prices and inflation is on the rise. To an extent, this is not surprising. The pandemic disrupted supply chains and wiped out supplies and stores of goods. But with many people working remotely, many now have pent up savings they want to spend. But with low supply and high demand, basic economics suggests rising prices. As supplies increase in the coming months, however, the rise in prices will begin to cool off. In other words, most economists are not yet concerned and expect this spike in inflation to be passing in nature. But not everyone agrees.

Last week, the Washington Post had an article examining the cause of inflation for a number of industries. To do so, it used some charts looking at prices over the past two years. This screenshot is from the used car section.

Going up…

I want to focus on the design of this graphic, though, not the content. The designers’ goal appears to be contrasting the inflation over the last year to that of the last two years. Easy peasy. Red represents one-year inflation and blue two-year.

Typically when you see a chart that look like this, an area or filled line chart, the coloured area reflects the total value of the thing being measured. You can also use the colour to make positive/negative values clearer. In this case, neither of those things are happening.

Because the blue, for example, starts at the beginning of the time series and at the bottom of the chart, it looks like an enormous amount of consistent blue growth. And when the line runs into May 2020, we begin to see what appears as a stacked area chart, with the blue area increasing at the expense of the red.

Another way of reading it could be that the 29.7% and 29.3% increases equal the shaded areas, but that’s also problematic. If the shaded area locked to the baseline like you’ll see in a moment, I could maybe see that working, but at this point it just leaves me confused.

Now you can use the area fill to make it clear when a line dips above or below the baseline, in this case 0%. And I took that approach when I reimagined the chart as seen below.

The earlier chart, reimagined

What we do here is we set the bottom of the area fill to the baseline. Consequently, where the chart is filled above 0 we have positive inflation, and where it falls below the 0 line we have negative inflation, or deflation.

We need to note here that the text in the original article talks about the monthly change in inflation, e.g. that used car prices have increased by 7.3% last month. That, however, is not what the chart looks at. Instead, the chart shows the change yearly, in other words, prices now vs last May. To an extent, the 29.7% increase is not terribly surprising given how terrible the recession was.

Ultimately, I don’t see the value in the filled blue and red areas of the chart because I am left more confused. Does the reader need to see how far back one year and two years are from May 2021? Don’t the date labels do that sufficiently well?

This is just a weird article that left me scratching my head at the graphics. But read the text, it’s super informative about the content. I just wish a bit more work went into the graphics. There are some nice illustrations beginning each section, but I kind of feel that more time was spent on the illustrations than the charts.

Credit for the piece goes to Abha Bhattarai and Alyssa Fowers.

Covid Update: 13 June

Last week I mentioned how the rate of decline in new cases had begun to fall significantly, largely due to two factors. The first is good, that we are reaching low levels of new cases overall, but the second is bad, that we see a large proportion of the population hesitant to receive their vaccines. (The vaccines have been proven safe, effective, and they’re free. If you haven’t received your shots yet, I highly encourage you to do so.)

This past week that trend for new cases largely continued. But another issue I was concerned about was a slight uptick, given that last Sunday’s daily new case data was higher than the previous Sunday’s. So as we look at the chart of new case curves, how are we doing?

New case curves for PA, NJ, DE, VA, & IL.

Good news. Those numbers are back on the decline and, in fact, the daily numbers from this Sunday are lower than those of even two weeks ago. We would have had a more muddled picture if the numbers were lower than last week, but still higher than two weeks ago. This leaves me more assured that the numbers are in fact still headed down and the few upticks are outliers and not a trend.

I also wanted to point out another data point this week. This coming week will mark the one-year anniversaries of the summer lows we saw in 2020. These were the points at which Covid-19 was at its lowest ebb after the initial spring wave and then the rise in cases beginning in late summer and early autumn. This most recent spring, despite the initial burst of reopening, our new case levels never fell to anywhere near the summer lows.

I will chart more of this likely next week as we hit all but one of those milestones. But as a teaser, today, 14 June was the lowest point for Delaware, which on that day had a seven-day average of 46 new cases per day. The average heading into today’s data release? 33. Or in other words, Delaware is averaging almost 25% fewer new cases now than it was at last year’s summer nadir.

But as we head into the week, you can see from the charts above that the numbers for all five states are quite low. Pennsylvania and Illinois lead, but are also some of the most populated states in the country. They sit at 403 and 336, respectively. New Jersey and Virginia, more middle-tier states in terms of population, are also fairly close with their new cases as their averages begin the week at 168 and 143, respectively. Delaware, as we noted above is sitting on 33.

So what about deaths? Last week I discussed a pattern of bottoming out, especially for Pennsylvania and Illinois. Unfortunately, I also noted how Pennsylvania had an aberrant large, one-day spike of deaths that influenced the seven-day average.

Death curves for PA, NJ, DE, VA, & IL.

This week you can clearly see that spike in Pennsylvania phasing out of the data set. That’s good, because it allows us to begin to evaluate the true state of Pennsylvania’s average. That average? 18, which is squarely in line with the average before the spike. In other words, Pennsylvania may have indeed bottomed out.

Illinois, however, has resumed a slight push downward, as the seven-day average yesterday just hit 16, down three from Saturday’s 19. I’ll want to see that trend persist throughout the week before saying that Illinois has resumed declining death rates, but it’s a good start to the week.

In New Jersey and Delaware we continue to see falling numbers of deaths. This time last week we saw a small cluster of deaths that brought Delaware up from 0.3 deaths per day to 2.3. But Delaware is now back down to 0.3, perhaps the lowest it reasonably expected to be. New Jersey had just managed to fall below 10 deaths per day, and it’s nearly halved that at it enters the week at 6.3.

Virginia, unfortunately, is the outlier. Deaths had slipped below 10 for over a week. And last week they fell as low as 7.7. But as of yesterday they have climbed back over 10. We need to watch this week to see if there is truly a rising number of deaths or if we are seeing the emergence of more of a bottom or floor in terms of deaths.

Finally we have vaccinations.

Full vaccination totals

Unfortunately, the City of Philadelphia’s website has been broken for over a week and they’re now only reporting updates twice a week anyway. In other words, the data for Pennsylvania isn’t great. Because while we can report the rest of the Commonwealth, the City of Philadelphia—excluding the suburban counties—on its own represents nearly 13% of Pennsylvania. That’s a huge chunk to be missing.

That leaves us with Illinois and Virginia.

The good news is that they are going up and that Illinois just hit 45% fully vaccinated. Virginia is now at 47%. The bad news is that it took a week for both states to climb up one percentage point. More evidence that vaccinations are slowing dramatically with millions left unvaccinated.

And we’re going to need them to get vaccinated. Consider the United Kingdom, another Western country doing well in its vaccination programme and that had decided to increasingly open up large swathes of its economy.

That is now on hold for another four weeks. The UK had planned to end its lockdown on 21 June, but that will now be extended into the end of July. And it’s all due to the Delta, formerly Indian, variant that has taken root in the UK. It’s more transmissible than the earlier UK variant, which the UK called the Kent variant.

The Delta variant has emerged in small numbers here in the US. But in order to prevent another surge that could threaten our healthcare systems, we need to get people vaccinated. It’s not inconceivable that the US may need to reinstate restrictions or full lockdowns if the Delta variant were to take root and swamp the US healthcare system.

And so I will end this post as I began it. If you haven’t started your vaccination process, I encourage you to do so. The vaccines have been proven safe and effective. And if you’re worried about cost, they’re free.

Credit for the piece is mine.

Back to the Office, Back to Basics

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.

Credit for the piece goes to Daniele Palumbo.

Covid Update: 7 Jun

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.

Credit for the piece is mine.

Oh the Degrees You’ll Earn

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.

Astronomy > Astrology

Credit for the piece goes to Jessica Hagy.

This Is Not My Populous State

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.

The Times Wore It Better

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..

Covid Update: 31 May

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.

Credit for the piece is mine.

Hamas’ Rocket Swarms

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.