line chart – Coffee Spoons

The Red Sox May Finally Have a Second Baseman

Last week was baseball’s opening day. And so on the socials I released my predictions for the season and then a look at the revolving door that has been the Red Sox and second base since 2017.

Back in 2017 we were in the 11th year of Dustin Pedroia being the Sox’ star second baseman. That summer, Manny Machado slid spikes up into second and ruined Pedroia’s knee. Pedroia had surgery and missed Opening Day 2018 then struggled to return. He played 105 games in 2017 then only three in 2018 and then six in 2019. And thus began the instability. Here’s a list of the Opening Day second baseman since 2017.

2018 Eduardo Nuñez
2019 Eduardo Nuñez
2020 José Peraza
2021 Kiké Hernández
2022 Trevor Story
2023 Christian Arroyo
2024 Enmanuel Valdez
2025 Kristian Campbell

And, again, by comparison…

2007 Dustin Pedroia
2008 Dustin Pedroia
2009 Dustin Pedroia
2010 Dustin Pedroia
2011 Dustin Pedroia
2012 Dustin Pedroia
2013 Dustin Pedroia
2014 Dustin Pedroia
2015 Dustin Pedroia
2016 Dustin Pedroia
2017 Dustin Pedroia

But not only is it a lack of stability, it is a lack of production. Wins Above Replacement (WAR) is a statistic that attempts to capture a player’s value relative to an “average” player or substitute. A below replacement level person is less than 0 WAR. A substitute is 0–2, a regular everyday players is 2–5, an All Star is 5–8, and an elite MVP level performance is 8+ WAR. And, spoiler, the Sox have not had a 5+ WAR second baseman since Pedroia’s final full season in 2016.

Suffice it to say, the Sox have long had a need for a long-term second baseman. The graphics I created were meant to be two Instagram images in the same post, and so the the axis labels and lines stretch across the artboards.

The graphic shows pretty clearly the turmoil at the keystone. The two outliers are Kiké Hernández in 2021 and Trevor Story in 2022. The latter is easily explained. Story was signed to be the backup plan in case shortstop Xander Bogaerts left after 2022. (Back in 2013 I made a graphic after a similar revolving door of shortstops in the eight years after the Red Sox traded Nomar Garciaparra. Then the question was, would a young rookie named Xander Bogaerts be the replacement for the beloved Nomah. Xander played 10 years for the Sox.)

Kiké, however, is a bit trickier to explain. WAR weights value by position. A second baseman is worth more than a leftfielder. But shortstops and centrefielders are worth more than second baseman. And Kiké played a lot more shortstop and centre than he did second base, which likely explains his 4.9 WAR that season.

And so now in 2025 we had yet another guy starting at second. His name? Kristian Campbell. I saw him a few times last year as he rocketed from A to AAA, the lowest to highest levels of minor league player development below the major league. I thought he looked good and so did the professionals, because he’s a consensus top-10 prospect in the sport.

Going into Monday’s matchup between Boston and Baltimore, Campbell is hitting 6 for 14 with one homer and two doubles, an on-base percentage of .500 and an OPS (on-base plus slugging, which weights extra base hits more heavily than singles) of 1.286. Spoiler: that’s very good.

Boston beat writers are reporting the Sox and Campbell’s agent are in talks for a long-term extension.

It looks like the Sox may have found their new long-term second baseman.

Credit for the piece is mine.

Imports, Tariffs, and Taxes, Oh My!

Apologies, all, for the lengthy delay in posting. I decided to take some time away from work-related things for a few months around the holidays and try to enjoy, well, the holidays. Moving forward, I intend to at least start posting about once per week. After all, the state of information design these days provides me a lot of potential critiques.

Let us start with the news du jour , the application of tariffs on China and the delayed imposition on both Canada and Mexico. Firstly, let us be very clear what a tariff is. A tariff is a tax paid by importers or consumers on goods sourced from outside the country. In this case, we are talking about Canadian, Mexican, and Chinese imports and the United States slapping tariffs on goods from those countries. Foreign governments do not pay money to the United States, neither Canada, nor Mexico, nor China will pay money to the United States.

You will.

You should expect your shopping costs to increase, whether that is on the price of gasoline (imported from Canada), fast fashion apparel (from China), or avocados (from Mexico). On the more durable goods side, homes are built with Canadian lumber and your automobiles with parts sourced from across North America—the reason why we negotiated NAFTA back in the 1990s.

Now that we have established what tariffs are, why is the Trump administration imposing them? Ostensibly because border security and fentanyl. What those two issues have to do with trade policy and economics…I have no idea. But a few news outlets created graphics showing US imports from our top-five trading partners.

First I saw this graphic from the New York Times. It is a variation of a streamgraph and it needs some work.

A streamgraph type chart from the *New York Times*

To start, at any point along the timeline, can you roughly get a sense of what the value for any country is? No. Because there is no y-axis to provide a sense of scale. Perhaps these are the top import sources and these are their share of the total imports? Read the fine print and…no. These are the countries with a minimum of 2% share in 2024, which is approximately 75% of US imports.

This graphic fails at clearly communicating the share of imports. You need to somehow extrapolate from the y-height in 2024 given the three direct labels for Canada, Mexico, and China what the values are at any other point in time or for any other country.

Nevertheless, the chart does a few things nicely. It does highlight the three countries of importance to the story, using colours instead of greys. That focuses your attention on the story, whilst leaving other countries of importance still available for your review. Secondly, the nature of this chart ranks the greatest share as opposed to a straight stacked area chart.

Overall, for me the chart fails on a number of fronts. You could argue it looks pretty, though.

The aforementioned stacked area charts—also not a favourite of mine for this sort of comparison—forces the designer to choose a starting country in this case and then stack other countries atop it.

What this chart does really well, especially well compared to the previous New York Times example is provide content for all countries across all time periods by the inclusion of the y-axis. Like the Times graphic it focuses attention on Canada, Mexico, and China with colour and uses grey to de-emphasise the other countries. You can see here how the Times’ decision to exclude all countries below 2% can skew the visual impact of the chart, though here all countries below Japan (everything but the top-five) are grouped as other.

Personally, the inclusion of the specific data labels for Canada, Mexico, and China distract from the visualisation and are redundant. The y-axis provides the necessary framework to visually estimate the share. If the reader needs a value to the precision level of tenths, a table may be a better option.

I could not find one of the charts I thought I had bookmarked and so in an image search I found a chart from one of my former employers on the same topic (though it uses value instead of share) and it is worth a quick critique.

A stacked area chart from Euromonitor International

Towards the end of my time there, I was creating templates for more wide-screen content. My fear from an information design and data visualisation standpoint, however, was the increased stretch in simple, low data-intensity graphics. This chart incorporates just 42 data points and yet it stretches across 1200 pixels on my screen with a height of 500.

Compare that to the previous BBC graphic, which is also 1200 pixels, but has a greater height of 825 pixels. Those two dimensions give ratios of 2.4 for Euromonitor International and 1.455 for the BBC. Neither is the naturally aesthetically pleasing golden ratio of 1.618, but at least the BBC version is close to Tufte’s recommended 1.5–1.6. The idea behind this is that the greater the ratio, the softer the slope of the line. This can make it more difficult to compare lines. A steeper slope can emphasise changes over time, especially in a line chart. You can roughly compare this by looking at the last few years of the longer time span in the BBC graphic to the entirety of this graphic. You can more easily see the change in the y-axis because you have more pixels in which to show the change.

Finally we get to another New York Times graphic. This one, however, is a more traditional line chart.

And for my money, this is the best. The data is presented most clearly and the chart is the most legible and digestible. The colours clearly focus your attention on Canada, Mexico, and China. The use of lines instead of stacked area allow the top importer to “rise” to the top. You can track the rapid rise of Chinese imports from the late 1990s through to the first Trump administration and the imposition of tariffs in 2018—note the significant drop in the line. In fact you can see the impact in Mexico becoming the United States’ top trading partner in recent years.

Over the years, if I had a dollar for every time I was told someone wanted a graphic made “sexier” or with more “sizzle” or made “flashier”, I would have…a bigger bank account. The issue is that “cooler” graphics do not always lead to clearer graphics. Graphics that communicate the data better. And the guiding principle of information design and data visualisation should be to make your graphics clear rather than cool.

Credit for the New York Times streamgraph goes to Karl Russell.

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

Credit for the Euromonitor International graphic goes to Justinas Liuima.

Credit for the New York Times line chart goes to the New York Times.

Fear the Floodwaters

This past weekend saw some flooding along the East Coast due to the Moon pulling on Earth’s water. In Boston that meant downtown flooding, including Long Wharf. The Boston Globe’s article about the flooding dwelt with more impact, causes, and long-term forecasts—none of which really warranted data visualisation or information graphics. Nonetheless, the article included a long time series examining the change in Boston’s sea level relative to the mean.

For me, the graphic works really well. The data strips out the seasonal fluctuations and presents the reader with a clear view of rising sea levels in Boston. If the noisiness of the red line distracts the reader—one wonders if an annual average could have been used—the blue trend line makes it clear.

And that blue trend line has a nice graphic trick to help itself. Note the designer added a thin white stroke on the outside of the line, providing visual separation from the red line below.

My only real critique with the graphic is the baseline and the axis lines. The chart uses solid black lines for the axes, with grey lines running horizontally depicting the deviation from the mean sea level. But the black lines draw the attention of the eye and thus diminish the importance of the 0 inch line, which actually serves as the baseline of the chart.

If I quickly edit the screenshot in Photoshop, you can see how shifting the emphasis subtly changes the chart’s message.

Overall, however, the graphic works really well.

Credit for the piece goes to John Hancock.

Labelling Line Charts

Today I have a little post about something I noticed over the weekend: labelling line charts.

It begins with a BBC article I read about the ongoing return to office mandates some companies have been rolling out over the last few years. When I look for work these days, one important factor is the office work situation and so seeing an article about the tension in that issue, I had to read it.

The article includes this graphic of Office of National Statistics (ONS) data and BBC analysis.

Overall, the chart does a few things I like, most notably including the demarcation for the methodology change. The red–green here also works. Additionally the thesis expressed by the title, “Hybrid has overtaken WFH”, clearly evidences itself by the green line crossing the blue. (I would quibble and perhaps change the hybrid line to red as it is visually more impactful.)

I also like on the y-axis how we do not have a line connecting all the intervals. Such lines are often unnecessary and can often add visual clutter, see yesterday’s post for something similar. I quibble here with dropping the % symbol for the zero-line. Since the rest of the graphic uses it, I would have put the baseline as 0%. And that baseline is indeed represented by a darker, black line instead of the grey used for the other intervals.

Then we get to the labels on the right of the graphic. Firstly, I do not subscribe to the view charts and graphs need to label individual datapoints. If the designer created the chart correctly, the graph should be legible. Furthermore, charts show relationships, if one needs a specific value, I would opt for a table or a factette instead. These are not the most egregious labels, mind you, but here they label the datapoint, but not the line. Instead, for the line the reader needs to go back to the chart’s data definition and retrieve the information associated with the colour.

Now compare that to a chart representing Major League Baseball’s playoff odds from Fangraphs.

Here too we have mostly good things going on, but I want to highlight the labelling at the right. This chart also includes the precise value, which is fine, but here we also have the actual label for the lines. The user does not need to leave the experience of the chart to find the relevant information, although a secondary/redundant display or legend can be found at the bottom of the chart.

If you can take the time to label the end value, you may as well label the series.

Credit for the BBC graphic goes to the BBC’s graphics department.

Credit for the Fangraphs piece goes to Fangraphs’ design team.

To X or Not to X

As it happens, the Latino culture largely remains x’ed out on using the term Latinx, according to a new survey from Pew Research.

The issue of supplanting Latino/Latina with Latinx as a gender neutral replacement—or as a complementary alternative—emerged in the general discourse in that oh-so-fun year of 2020 when everything went well.

One common argument I have heard is the inherent gender within the Spanish language. Broadly you use -o for singular masculine endings and -a for singular feminine forms and -os for plural masculine and mixed gender forms and -as for plural feminine forms.

Perhaps my biggest issue is that -x does not linguistically make sense. X is typically pronounced like a j or sometimes an s. Consider how Mexicans pronounce Mexico, May-hie-co. Latinx becomes La-teen-h, an almost silent ending that does not fit, at least to my ears. Pero, hablo solo un pocito Español. Aprendí a hablar por cuatro años en la escuela, dos años de niño, y trabaja en una cocina del restaurante. Thus Latinx, pronounced Lat-in-ecks, always seemed, daresay, a gringo solution to a problem that earlier polling of Latino communities did not indicate was a problem. With the potential exception of the young, but even then not terribly so.

Four years later, however, and not much has changed according to Pew. Their graphic shows as much.

Significantly more people are aware of Latinx as a term. Fewer people use the term, though not significantly. Although a shift from four to three percent can be seen as significant given its low adoption. Moreover, as a second graphic shows, more people who are aware of the term think it should not be used.

The article continues with a discussion of a new new alternative, Latine, which to my ears makes more sense. But is largely yet unheard of in the community—20%—and of those who have heard it, almost nobody uses it.

As far as the graphics go, I am not a huge fan.

For the first, we have two lines showing the movement between two datapoints. At the most basic level, the use of a line chart makes sense to depict two series moving between two points in time. But without any axis labelling one can only trust the lines begin and end at the correct position. Furthermore people need to read the specific labels to get a sense of the line charts’ magnitude. More of a tell, don’t show approach. If the chart had even a simple 0% line and 50% line, one need not label all four datapoints to convey the scale of the graphic.

Ultimately, though, does a chart with four datapoints even need to be graphed? Some would argue in most instances a dataset with fewer than five or six numbers need not be visualised; a table should suffice. Broadly I agree. This chart does show a particularly striking trend of increasing awareness of the term, but largely static to declining usage.

The second graphic, however, falls more squarely into that argument’s camp of “Why bother?” It shows simply two numbers. Numbers placed atop purple rectangles. Without any axis labelling, we presume these bars represent columns encoding the percent—at least the lines in the first chart were clearer to their meaning. Then we still have the issue of telling and not showing. Perhaps labelling to the left from 0% to 75% or 80% would help. Then you need not even add additional “ink” with the four digits sitting atop the bars and sparkling for unnecessary reader attention.

This falls into a broader trends I have witnessed over the last few years in the information design and data visualisation field of labelling individual datapoints within a chart. It is a trend with which I strongly disagree, but perhaps is best left for another post another day. Suffice it to say, if knowing the precise measurement is important, a chart is not the best form. For that use case I would opt for a table, best used to organise and find specific datapoints.

Overall, Pew shows that within the Latino community, very few use the term Latinx. Consequently, perhaps this entire post is, to use a Spanish-language expression, a tempest in a teapot.

Credit for the piece goes to Pew Research.

Electric Throat Share

For the last few weeks I have been working on my portfolio site as I update things. (Note to self, do not wait another 15 years before embarking upon such an update.)

At the University of the Arts (requiescat in pace), I took an information design class wherein I spent a semester learning about the electricity generation market in the Philadelphia region. This became a key part of my portfolio when I applied for 99 jobs at the beginning of the Great Recession, had 3 interviews, and only 1 job offer.

That job offer lead me to Chicago and Euromonitor International where one of the first projects I worked on was a datagraphic about throat share, i.e. what drinks products/brands people in different countries drank. Essentially, I took what I learned about visualising the share of electricity generation in Pennsylvania to the share of drinks consumption across the world. Thus a career was born. Fast forward 15 years and I wanted to see how that electricity generation had changed. And I can do that because I used a public source in the US Energy Information Administration.

Anecdotally, Pennsylvanians know fracking for natural gas has been a boon to the former coal and steel parts of the Commonwealth, which really is a lifeline. But overall, Pennsylvania has long been known as a nuclear power state. More on that from a personal standpoint in a later post. Back in the uphill both ways to university day, I did not look at the United States overall. But now I can.

Largely this fits with the narratives I know. Coal has plummeted both in the Commonwealth and more broadly as natural gas has largely taken its place. No, that’s not great from a climate change perspective, but natural gas is definitely better than coal.

Renewables, nationally speaking, are now about 20% or 1/5th our net electricity generation. But in Pennsylvania, whilst this Monday morning might be a bright and blue sky day great for solar power, the nights are getting longer and we get a lot of clouds. We do have some hydroelectric dams—it helps to be a partially mountainous state. And, yes, we do have the wind farms along the Allegheny Ridge, one of the windiest spots along the East Coast, but for context one of the two nuclear reactors near to which I grew up is equal to almost the entire wind power electricity generation in the entire Commonwealth.

But for all the supposed growth in renewables, we just are not seeing it in Pennsylvania, at least not at a scale to supplant fossil fuels. And unfortunately, it is not as if demand is falling. And that might be why we are seeing quiet talks about reactivating some of Pennsylvania’s shuttered nuclear reactors. If you could bump that nuclear share of electric throat back up to 40% or even 50%, you could cut down that natural gas usage significantly.

Credit for the piece is mine.

I Want a Pitcher Not a Back o’ Head Hitter

We’re about to go into the sportsball realm, readers. Baseball, specifically.

Tuesday night, Atlanta Braves batter Whit Merrifield was hit in the back of the head by a 95 mph fastball. Luckily, modern ballplayers wear helmets. But at that velocity, one does not have the most reaction time in the world a number of other batters have been hit in the face. And generally, that’s not good. Merrifield went off in post-game interviews about the lack of accountability on the pitchers’ side. From my perspective as an armchair ballplayer, back in my day, when I walked up hill through the snow both ways to get to my one-room schoolhouse, if you hit a batter, our pitcher was hitting one of yours.

I have noticed in ballgames, however, I see hit-by-pitch (HBP) more often—and I score most ballgames I attend, so I have records. But I also know a handful attended per year makes for a very small sample size. Nonetheless, I know I have talked to other baseball friends and brought up that I think pitchers throw with less command, i.e. throwing strikes, than they used to, because I see more HBP in the box scores. And when I go to minor league ballgames, which I do fairly often, HBP seems on the rise there, which means in future years those same pitchers will likely be in the majors.

So yesterday morning, I finally took a look at the data and, lo and behold, indeed, since my childhood, the numbers of HBPs has increased.

There is one noticeable sharp dip and that is the 2020 COVID-shortened season. Ignore that one. And then a smaller dip in the mid-90s represents the 114-game and 144-game seasons, compared to the standard 162 per year. Nonetheless, the increase is undeniable.

There is a general dip in the curve, which occurs in the late 200s and early 2010s, with its nadir in 2012. Without doing more research, that was probably the peak of pitchers, who could command—throw strikes—and control—put their strikes where they want in the strike zone—their pitches at the sacrifice of velocity.

2014 saw the rise of the dominant Royals bullpen, which changed the course of modern baseball. Stack your bullpen with a number of power arms who throw 100 mph and just challenge batters to hit the speedball. Problem is, not everyone who can throw 100 knows where that speedball is going. And that leads to more batters being hit.

Merrifield is correct in his assessment that until pitchers and teams face consequences for hitting batters, we are not likely to see a decrease in HBPs. Or at least not until velocity is de-emphasised for some other reason. What if there were a rule a pitcher who hits a batter from the shoulder up is immediately ejected? What if a long-term injury for a batter is tied to a long-term roster removal for the pitcher? If, say, the batter hit in the head is out for a month with a concussion, the same pitcher is on the restricted list for a month?

Have I worked through any of these ideas in depth? Nope. Just spitballing here on ye olde blog. But as my chart shows, it does not look like this potentially life-changing problem in the game is going away anytime soon.

Credit for the piece is mine.

Just Keep Grinding it Out

There are certain journalism outlets that I read that consistently do a good job with information design or at least are known for it. Now I try to keep my media diet fairly large and ideologically broad, but in that there are also still some outlets that feature quality design than others. The New York Times, the Washington Post, and the Economist are usually probably top of my list, but you will also see the Wall Street Journal, Philadelphia Inquirer, Boston Globe, the Guardian, and the BBC. I also read more niche outlets for some of my interests, e.g. the Athletic for Red Sox and baseball. But these often don’t feature information design. Politico is one that I read for my political news fix. And when I was reading it whilst on holiday, I was surprised to find an article about the employment market with a really nice line chart.

The article examines the changing labour market where, for over a year now, bargaining power largely resided with employees. If employees wanted raises, benefits, perks, whatever, they could often leave their current employer if their requests weren’t met because another employer, desperate for staff, would likely meet their asks. However, as the economy cools, we would expect the labour market to tighten making few openings available. That begins to reduce the bargaining power of employees as now employers can say “take it or leave it”, knowing that the offers they make to staff aren’t likely to be met by other employers who don’t have open positions or aren’t otherwise hiring.

Four graphics punctuate the article, detailing just that changeover. The full article is worth a read, but I wanted to take a look at one graphic that I think best captures the design decisions made.

That looks like an inflection point to me.

My screenshot above doesn’t capture the interactivity, but we will return to that in a moment. We see three data series: job openings, quits, and layoffs and discharges. The designer represented each with a primary colour, making clear distinctions between the three, and since all three are represented by thousands of units, they can be plotted together. That allows one to make easy comparisons across the three series at particular moments in time, e.g. the Covid recession. My only real quibble is with that recession bar. I probably would have used a neutral colour like a light grey instead of red, because the red appears visually linked to layoffs and discharges when they really are not.

Normally when we see an interactive line chart, we have a small legend above, sometimes below, the graphic. Here, however, the labelling for the lines sit directly next to the line. This makes the display clearer for the reader who scans the data series and I’ve seen the approach often in print, but rarely for interactive work.

And when the reader mouses over the work, the highlight does a few nice things.

We can first see that the line with which the user is engaged becomes the focus: the remaining two lines recede into the background as they are greyed out. We also get a simple, but well designed text label above the cursor. Note how that behind the text there is a thin white stroke that creates visual separation between the letters and the data line. And that cursor is a small grey circle surrounding the data point, allowing you to see said data point.

Take it all together and you have a very clear and very effective interactive line chart. It’s a job well done.

When I see good work from unexpected places it’s important to call it out and highlight it because it means some design director somewhere cares enough to try and improve their publication’s quality of communication. And in an era when many outlets suffer from disinvestment and cost-cutting staff reductions that leave fewer designers, editors, and photographers on staff it is easy to imagine design quality decreasing.

So credit for this piece goes to Eleanor Mueller.

Facebook’s for the Old Folks

We start this work week with something that the young people use, but in a different way than older people do, including elder millennials like myself: social media. Of course, as an elder millennial, I remember Facebook when it was The Facebook when it expanded access to Penn State, which I attended for a single year.

Pew Research conducted a study of teenagers that revealed they use social media more than ever before, but that they use new (sort of) platforms more than the venerable paragon of the past: Facebook.

The Economist’s Data Team looked at the data and created this graphic showing the trends.

We see stacked bar charts on the left and then a line chart on the right. The left-hand chart shows the frequency with which teenagers use various social media platforms. What I don’t understand is how someone uses a social media application “almost constantly”. But that’s probably why I’m an elder millennial.

Get off my lawn, you whippersnappers.

On the right we see the percentage of teenagers who have used an application at least once. The biggest winners? Applications primarily featuring image over text. The losers? Those that use words.

Now longtime readers know that I am not terribly fond of stacked bar charts, especially because they make comparisons between, in this case, social media platforms very difficult. And I feel like we have a story in the occasional use responses, but it’s tough teasing it out from this graphic.

On the right, well, this is one I enjoy. You can tell just how much the social media environment has evolved in the last 7–8 years because TikTok did not exist and YouTube was not thought of as a social media platform.

I wonder if different colours were truly needed for the line chart. The lines do not really overlap and there is sufficient separation that each line can be read cleanly. If the designers wanted to highlight the fall of Facebook or another story line, they could have used accent colours.

But overall a solid graphic.

Now to check my feeds.

Credit for the piece goes to the Economist’s Data Team.

Warming Towards Women Leaders

We are going to start this week off with a nice small multiple graphic that explores the reducing resistance to women in positions of leadership in Arab countries. The graphic comes from a BBC article published last week.

These kinds of graphics allow a reader to quickly compare the trajectory of a thing between a start and an endpoint. The drawback is it can obscure any curious or interesting trends in the midpoints. For example, with Libya, is its flat trajectory always been flat? You could imagine a steep fall off but then rapid climb back up. That would be a story worth telling, but a story obscured by this type of graphic.

I do think the graphic could use a few tweaks to help improve the data clarity. The biggest change? I would work to improve the vertical scale, i.e. stretch each chart taller. Since we care about the drop in opposition to women leaders, let’s emphasise that part of the graphic. There could be space constraints for the graphic, but that said, it looks like some of the spacing between chart header and chart could be reduced. And I think for most of the charts except for the first, the year range could be added as a data definition to the graphic and removed from each chart. Similar to how every row only once uses the vertical axis labels.

Another way this could be done is by reducing the horizontal width of each chart in an attempt to squeeze the nine from three rows down to two. That would mean two additional chart positions per row. Tight fit? Probably, but there is also some extraneous space to the right and left of each chart and a large gap between the charts themselves. This all appears to be due to those aforementioned x-axis labels. An additional benefit to reducing the horizontal dimensions of each chart is it increases the vertical depth of the chart as each line’s slope, its rise over run, sees its horizontal distance shrink.

Overall this is a really smart graphic that works well, but with a few extra tweaks could take it to the next level.

Credit for the piece goes to the BBC graphics department.