The Hon Andrew Leigh MP
Assistant Minister for Productivity, Competition, Charities and Treasury
The Best Charts Ever Drawn
2026 APS Data Awards,
Canberra
Wednesday, 18 March 2026
1. Seeing Clearly
I acknowledge the Ngunnawal people, the Traditional Custodians of the land on which we meet tonight, and pay my respects to their Elders past and present; I also thank the Data Awards team for bringing us together, and Chief Statistician David Gruen, head of the Data Profession.
It’s a pleasure to be among people who know that data is where opinions go to face consequences.
These awards celebrate excellence across the full data enterprise – building systems, linking information, analysing patterns, and strengthening capability.
Each step matters.
Because data, on its own, doesn’t change anything.
Data lives in spreadsheets, dashboards, and occasionally in PowerPoint decks dense enough to qualify as insulation.
What changes things is understanding.
Most humans find spreadsheets confronting. They look like the Matrix – except without Keanu Reeves to explain what’s going on.
The brain evolved to spot patterns.
A good visualisation speaks that language. It reveals structure. It makes the complex graspable.
It allows people to see clearly.
And once you see something clearly, you can’t unsee it.
Tonight, I want to show you some visualisations that do exactly that.
And the first may be the most famous statistical graphic ever drawn.
2. Minard’s Napoleon Graphic
This chart shows Napoleon’s invasion of Russia in 1812. It was created by Charles Joseph Minard, a French civil engineer.
The band represents his army. Its width shows the number of soldiers.
At the start, it’s thick and confident – about 422,000 men crossing into Russia.
As the army advances, the band narrows. Gradually at first. Then relentlessly.
By the time Napoleon reaches Moscow, only 100,000 remain.
Then comes the retreat.
And the band collapses. It thins to a fragile thread.
By the time the survivors stagger home, just 10,000 are left.
Minard adds temperature along the bottom. As the army retreats, the mercury falls to minus 30 degrees Celsius – which, from a military planning perspective, is suboptimal.
What makes this visualisation extraordinary is its honesty. It doesn’t explain the disaster. It lets you watch it happen.
Minard drew this in 1869, when he was 88 years old.
Which is reassuring for anyone who feels their best work may still be ahead of them.
3. John Snow’s Cholera Map
John Snow was a London physician, and one of the founders of modern epidemiology.
In 1854, cholera swept through Soho. The dominant theory held that disease spread through ‘bad air.’ This had the advantage of sounding scientific while requiring very little plumbing reform.
Snow had a different hypothesis. He suspected the source was contaminated water.
So he gathered data, and mapped the deaths.
Each black bar marks a cholera fatality. And they cluster, unmistakably, around a single location: the Broad Street water pump.
The pattern speaks instantly. The pump sits at the centre of the outbreak.
Snow persuaded local officials to remove the pump handle.
Cases fell.
This map helped establish one of the central ideas of public health: that careful observation, combined with clear visualisation, can reveal causes that speculation alone cannot.
4. Florence Nightingale and Visualising Mortality
Florence Nightingale was a nurse, a reformer, and one of the first people to realise that saving lives sometimes begins with better charts.
She rose to prominence during the Crimean War, where British soldiers faced an unexpected enemy: their own hospitals.
This chart shows causes of death by month. Blue represents disease. Red represents wounds.
In the early period, the blue wedges dominate. Disease killed far more soldiers than combat. Infection proved more lethal than the opposing army.
Then, in early 1855, the blue wedges suddenly shrink.
This marks the introduction of basic sanitary reforms. Revolutionary ideas, such as washing hands.
The result was immediate. Death rates collapsed.
Nightingale understood that senior officials might skim a report, but they couldn’t ignore a picture like this.
She helped pioneer the use of data visualisation to drive reform.
And in doing so, she demonstrated a powerful truth: in war, charts can save lives.
5. History of Pandemics
Produced by Nicholas LePan, Nick Routley and Harrison Schell at Visual Capitalist, this chart shows pandemics across human history, with each circle representing a disease and its death toll.
The Black Death dominates the centre – about 200 million deaths in the 14th century. In visualisation terms, it’s the chart’s headline act.
But other circles carry enormous weight too.
Smallpox, which persisted for centuries, killed an estimated 56 million people. The Spanish flu of 1918 killed between 40 and 50 million in just a few years – remarkable efficiency, deeply unfortunate timing. The Plague of Justinian, more than a thousand years earlier, killed an estimated 30 to 50 million. HIV/AIDS, unfolding more slowly, has taken between 25 and 35 million lives.
What makes this chart powerful is comparison.
Numbers like 10 million or 50 million remain abstract. They pass through the brain without leaving much trace.
But here, scale becomes visible.
You see immediately which pandemics reshaped entire societies.
Visualisation gives numbers weight.
And once numbers have weight, they stay with you.
6. What Word Frequencies Reveal
This chart was created by Julia Silge, a data scientist and one of the leading figures in text analysis. Her work focuses on using statistical methods to understand language – turning books and documents into something you can analyse.
It compares the most frequent meaningful words in two novels: Pride and Prejudice and The War of the Worlds.
Common filler words – ‘the’, ‘and’, ‘of’ – have been removed. What remains are the words that carry substance.
On the left, Pride and Prejudice. The dominant words are names: ‘Elizabeth’, ‘Darcy’, ‘Bennet.’ This is a novel built around people, relationships, and social interaction. Even the frequent appearance of ‘said’ reminds us that much of the action unfolds through conversation.
On the right, The War of the Worlds. The vocabulary shifts. ‘Martians.’ ‘Black.’ ‘Night.’ ‘Road.’ This is a world of movement, threat, and atmosphere. Far fewer drawing-room conversations. Considerably more existential dread.
What makes this visualisation effective is its simplicity.
It shows that different texts leave distinct statistical fingerprints.
You don’t need to read the books to sense their character.
The words tell the story.
Which suggests that if someone applied this method to government, they could identify each department purely from its favourite acronym.
7. Cat Proximity
We’ve now gone through five images without any cats, so it’s time to remedy that.
This chart comes from XKCD, a webcomic created by Randall Munroe, a former NASA roboticist.
Munroe has a gift for using the visual language of data – axes, curves, labels – to capture everyday truths with scientific precision.
And on that note, I’ll let the chart speak for itself.
8. Lakes and Oceans
That previous chart showed XKCD at its lightest.
This one shows its depth.
Randall Munroe maps the vertical structure of lakes and oceans, drawn to scale.
The shoreline sits at the top. Then the seabed drops away. And keeps dropping. Past one kilometre. Past two. Past five.
Eventually, you reach the Mariana Trench, nearly 11,000 metres down.
Munroe adds reference points along the way: the depth where sunlight fades, the operating limits of submarines, and the deepest points reached by human divers.
Most of human activity occupies a very thin layer near the surface.
Below that lies a vast vertical world that we rarely think about.
What makes this chart effective is its restraint.
No decoration. No exaggeration. Just depth, rendered honestly.
It recalibrates your sense of scale.
And it explains why, when something falls into the ocean, the recommended retrieval strategy is often: accept the loss and move on.
9. When Are Sports Fans Safe to Leave the Game?
This chart comes from FiveThirtyEight, a data journalism organisation founded by Nate Silver, which specialises in using statistics to explain real-world decisions.
It shows the probability that the leading baseball team goes on to win, depending on how far ahead they are, and how late in the game it is.
Each curve represents a different inning. Early in the game, even a large lead leaves room for reversal. But as time runs out, the same lead becomes far more decisive.
The highlighted line shows the sixth inning. At that point, a four-run lead gives the leading team more than a 95 percent chance of winning.
That’s the moment when fans face a decision: stay loyal, or beat the traffic.
What makes this chart effective is that it combines two variables – margin and time – and turns them into a clear decision rule.
It answers a question people actually have.
And I look forward to seeing someone in this room produce the equivalent chart for union, league, and AFL.
10. The Most Common PINs
This chart was created by Nick Berry of Information is Beautiful, using data from 3.4 million PINs exposed in real-world data breaches.
Each square represents one of the 10,000 possible four-digit PINs. Lighter colours show the most common choices.
One number dominates: 1234.
It accounts for a remarkable share of users. Followed by 0000, 1111, and 7777.
The chart also reveals patterns.
The bright diagonal shows repeated pairs – 1212, 3434, 5656.
The horizontal band shows birth years – 1980, 1990, 2000.
What makes this visualisation effective is that it exposes structure where randomness should live.
A secure PIN should look evenly distributed.
Instead, human choices cluster around what’s memorable.
It turns out that when asked to be unpredictable, humans display remarkable consistency.
11. Who Spends Time Alone
The previous chart showed how people choose PINs.
This one shows how people spend their time.
It comes from the Financial Times, based on analysis of the American Time Use Survey.
Each panel shows a different age group. The red line is men. The blue line is women. The vertical axis shows the share of free time spent alone.
Twenty years ago, young people spent the smallest share of their free time alone. Youth came with a built-in social life. Older women spent the most time alone.
That pattern has flipped.
Young men aged 18 to 24 now spend the largest share of their free time alone of any group.
The line rises steadily, and ends at the top.
What makes this chart so effective is its restraint.
A massive social change, conveyed with nothing more than two lines changing places.
12. How People Use ChatGPT
Here’s another one from David McCandless of Information is Beautiful. It shows what people use ChatGPT for.
Each rectangle represents a category. The size reflects its share of total use.
The largest block is ‘specific information,’ followed by editing text, tutoring, and practical advice.
Coding appears, but occupies a modest share. Mathematical analysis smaller still.
This visualisation is called a treemap.
It works far better than a pie chart would here. A pie chart with this many categories would resemble a pizza dropped on the floor. Technically intact, but hard to work with.
This treemap solves that problem.
It uses area efficiently. Large categories stand out immediately. Smaller categories remain visible without clutter.
And it reveals something subtle.
People use AI less for computation than for communication.
Less as a calculator.
More as a collaborator.
13. The Changing Population of the World
This chart comes from Visual Capitalist, using United Nations population projections.
Each coloured band is a country. The width shows its population. The bands run from today through to the end of the century.
India stays firmly in first place.
China, long accustomed to the top tier, slides downward.
Meanwhile, Nigeria climbs rapidly, overtaking countries that currently sit well ahead of it.
What makes this visualisation work is the flowing design. This is called an alluvial chart. It lets you track each country over time, watching them overtake one another.
A table would tell you the rankings.
This shows you the overtaking manoeuvres.
It has the unexpected drama of a motorway, where one lane keeps moving while another mysteriously slows to a crawl.
Except here, the vehicles contain hundreds of millions of people.
14. Renaissance Artists and Ninja Turtles
One more from XKCD, aka Randall Munroe.
It compares the notoriety of Leonardo, Michelangelo, Donatello, and Raphael.
Brown represents recognition as Renaissance artists.
Green represents recognition as Ninja Turtles.
I’ll let the data speak for itself.
15. Who Gets the Lines
The final two charts both relate to movies.
This one comes from an analysis by Hanah Andersen and Matt Daniels for Polygraph, examining screenplay dialogue in Disney films.
Each bar represents a film. Blue shows male dialogue. Red shows female dialogue.
Some results are striking.
In The Jungle Book, 98 percent of the dialogue goes to male characters.
Aladdin, Toy Story, and The Lion King follow a similar pattern.
And even The Little Mermaid – a film named after a female protagonist – still gives most of the lines to male characters.
More recent films begin to shift. Frozen moves closer to balance. Into the Woods tips into female majority.
What makes this visualisation effective is its simplicity.
Each film becomes a single, unmistakable comparison.
It measures something audiences feel, but rarely quantify.
Who drives the conversation.
16. Critics, Audiences, and the Occasional Misfire
Our final chart, another one from Information is Beautiful, compares critics’ ratings with audience ratings.
Each circle represents a film. The horizontal position shows the gap between critics and audiences.
Some films unite everyone.
Gravity sits close to the centre – critics admired it, audiences agreed, and nobody left the cinema demanding a refund for excessive orbital mechanics.
Cloudy with a Chance of Meatballs lands nearby. A film about weather made of hamburgers achieved something rare: consensus.
Other films divide opinion.
The Last Jedi stands well to the right. Critics praised its ambition. Audiences conducted a more spirited discussion.
The Witch sits there too. Critics admired its atmosphere and restraint. Some viewers spent much of the film waiting for something to explode.
What makes this visualisation effective is how quickly it shows agreement and disagreement.
Consensus forms a cluster.
Controversy drifts outward.
And large budgets, represented by larger circles, raise the stakes when things don’t land as planned.
17. Closing: Seeing Clearly
We’ve covered wars, pandemics, novels, cats, PINs, population shifts, and Disney screenplays.
Some of these visualisations helped save lives.
Some helped shape policy.
Some helped people understand their world in new ways.
And some simply captured everyday truths with elegance.
They all share a common purpose.
They help us see.
Data, on its own, speaks in dulcet tones.
Great visualisation makes it sing.
It reveals patterns.
It brings structure into focus.
It allows insight to travel from the analyst’s screen into the audience’s mind.
Charles Minard showed the human cost of a military campaign.
John Snow revealed the source of an epidemic.
Florence Nightingale turned mortality into reform.
Julia Silge showed that language carries measurable patterns.
And XKCD showed that even the most rigorous charts benefit from a sense of humour.
The finalists and winners tonight carry that same tradition forward.
Because every dataset holds insight.
And every clear visualisation brings that insight within reach.
Ends