The Sun is about 400 times wider than the Moon. It’s also about 400 times farther away. Both objects appear almost exactly the same size in our sky — which is why, when they align, the Moon can cover the Sun nearly perfectly and reveal the corona, the Sun’s outer atmosphere, otherwise invisible from Earth.

No law of physics requires this. It’s a coincidence — and a temporary one. The Moon drifts away from Earth at about 38 millimeters per year, pulled outward by tidal forces. In roughly 600 million years, it will appear too small to fully cover the Sun. Total solar eclipses will become geometrically impossible. Complex animal life has existed on Earth for about 600 million years — meaning we’ve been here for essentially the entire window. That feels like luck worth paying attention to.

It’s also worth noting that this coincidence has been scientifically useful. In 1919, Arthur Eddington sailed to an island off the coast of Africa to photograph stars near the Sun during totality. Normally those stars are invisible, swamped by sunlight. The eclipse made the measurement possible. His photographs confirmed Einstein’s general relativity and turned a moderately well-known physicist into an international celebrity. The geometry of shadow has consequences.

The Visualization Problem

Any given location on Earth sees a total solar eclipse roughly once every 375 years. The 2024 eclipse over North America drew nearly 20 million travelers and generated an estimated $6 billion in economic activity. People care deeply about getting this right. And yet the maps available for planning have mostly been stuck in the same mode for decades: a corridor on a flat projection, maybe with a center line, maybe with a few city labels. In or out. That’s the whole story.

The problem is that “in or out” is not actually the question most people are asking. They’re asking: how much of the Sun will I see covered from where I’m standing, and at what time? That’s a continuous field, not a binary. And rendering it as a binary throws away most of the information.

Think of it like a topographic map that only shows whether terrain is above or below sea level. Technically accurate. Not very useful for planning a hike.

The Solar Eclipse Map

We built this because we didn’t want to miss another eclipse and couldn’t find anything that answered our actual questions. It opens in overview mode — all eclipses for a selectable date range on a globe, color-coded by type. The data runs from 1900 to 2100, from Fred Espenak’s Five Millennium Canon of Solar Eclipses. Click any band and the globe rotates to center on it.

Contours, Not Corridors

The key design decision was to render shadow coverage as contours rather than a single boundary. Like elevation lines on a topo map, the obscuration rings show exactly how the eclipse field varies across the landscape — 10%, 20%, 30%, all the way in to totality. The gradient from the outer edge to the center tells you far more than a corridor ever could.

There’s also a toggle between Path mode (static contour fills showing maximum coverage) and Shadow mode (live moving rings that update as you scrub through time). Path mode is for planning. Shadow mode shows the shadow as it actually moves — a fast-moving dark spot racing across the Earth at up to 1,770 km/h, surrounded by expanding penumbral rings.

Time as a Dimension

The time slider turns the eclipse from a static map into a queryable dataset. Scrub through it manually or hit play — 5 minutes of eclipse time per real second. The umbral shadow moves, the day/night terminator shifts, the Sun and Moon position markers track their actual computed positions. A 4-minute totality takes about 48 seconds to watch.

Point Query: Your Exact View

Most eclipse maps are broadcast visualizations — they show the whole picture and leave you to figure out your specific situation. The observer pin inverts that. Drop it anywhere on the map, and the tool becomes a point query: what is the exact sun coverage at these coordinates, right now, at this moment in the eclipse? Drag it somewhere else and the answer updates instantly.

The pin shows current coverage, peak coverage for that location over the full eclipse, and local time with automatic timezone lookup. The diagram in the top right renders the actual sun/moon geometry from that observer’s perspective — not an icon, a live computed view. If you’re asking “should I drive 40 miles north,” this answers it precisely.

Cities, Export, and Sharing

Toggle the cities layer and you get populated places along the center line, sized by population — useful for quickly finding where to go, or confirming you’re already there. The export options include a PNG screenshot and video recording in several formats (1920×1080 down to 1080×1080 square), which captures the actual computed shadow sequence frame by frame.

Every interaction — eclipse, time position, observer pin location, visible layers, map rotation, zoom — is encoded in the URL. Share the link and it opens to exactly that view.

What’s Next

The next few years are good ones if you’re willing to travel. August 12, 2026 — total eclipse over the Iberian Peninsula, Mallorca, North Africa. August 2, 2027 — the longest total eclipse of the 21st century, 6 minutes 23 seconds maximum, crossing the Sahara and Egypt. July 22, 2028 — Australia, up to 5 minutes 10 seconds across the Northern Territory and Queensland.

For North Americans who missed 2024: August 23, 2044 clips Montana and the Dakotas near sunset (90 seconds), then August 12, 2045 crosses California to Florida with up to 6 minutes in parts of Florida. The 2045 one is the one worth planning for.

The Moon is moving away from us at 38 millimeters a year. In 600 million years the geometry stops working. We’re in the window. Use it.

Plan your next eclipse

Full catalog 1900–2100. Shadow contours, live playback, observer pin, video export.

Open the Solar Eclipse Map

Subscribe now

We’re still experimenting with the format, but the general idea is to send a roundup once every other week, let’s say, on Wednesdays. It would spotlight the stuff we posted since the last send plus any other things we think you’d find interesting.

We believe it’s a good alternative to pushing every single article at you the minute it is posted, but just in case you disagree, we have a tiny little reader poll here:

Anyway, here’s what our team has cooked up in the last couple of weeks.

///

The Best Statistical Graphic Ever Created

There’s this legendary data visualization from 1869 that maps out Napoleon’s disastrous march into Russia — troop size, location, direction, temperature, time, and casualties all packed into one graphic. Edward Tufte basically crowned it the greatest statistical chart ever made.

We stumbled across an old gravure of Napoleon crossing the Neman River (or Nemunas as we call it here), which is right where the chart kicks off, and figured why not try rebuilding the whole thing with amCharts and a bit of help from Claude. Took about five hours. It’s a fun look at how a 150-year-old visualization still absolutely holds up.

///

Five Prompts to an Animated Globe

We took a spinning globe with flight paths, animated planes, and a live mileage counter from zero to done in five plain-English prompts. The trick was hooking up the amCharts MCP server so the AI could actually look stuff up in the docs instead of guessing — turns out an AI with a reference and an AI without one are basically different tools. Each prompt layered on more polish: city markers, dashed routes, altitude effects, fading labels, even a little plane shadow. Five sentences, one pretty slick globe.

///

Sankey Diagrams Weren’t Invented by Sankey

Sankey diagrams? Not actually invented by Sankey. Turns out a British Army lieutenant named Harness was drawing flow maps back in 1838 but anyone hardly noticed. Then Minard (the Napoleon chart guy) spent decades making gorgeous geographic flow maps. Sankey showed up last in 1898 with a steam engine diagram and somehow got his name slapped on the whole thing.

History lessons aside, the article concludes with practical advise on how this type of visualization is now readily buildable using a modern charting library.

///

Not All SVG Maps Are Created Equal

Most SVG maps floating around out there have the same problems — Mercator making everything near the poles look massive, Atlantic-centered views that awkwardly split the Pacific in half, and files bloated with thousands of coordinate points nobody needs.

Long story short, we built a free SVG Map Generator that lets you pick from 90+ projections, drag the map to center it however you want, and simplify the geometry down to a fraction of the file size without it looking janky.

///

In other news…

We gave VisitedPlaces.com a proper makeover. It’s one of our most popular tools, used by thousands to create their travel stories as static images, interactive embeds, or animated videos. The new version features a refined, intuitive user interface and a dramatically speedier video generator.

///

Subscribe now

Here’s something that bugs me about data visualization history: Sankey diagrams weren’t invented by Sankey. Captain Matthew Henry Phineas Riall Sankey — yes, that was his full name — created his famous steam engine efficiency diagram in 1898. It showed where energy was being lost in the system, with band widths proportional to the amount of energy flowing through each stage. People loved it, the name stuck, and here we are.

The person most people credit as the actual inventor is Charles Joseph Minard, the French civil engineer who was doing the same thing in the 1840s — fifty years before Sankey, on actual geographic maps. We talked about him before when we recreated his famous Napoleon’s 1812 retreat map — the one Edward Tufte called “the best statistical graphic ever drawn.”

But here’s the part that even most dataviz people don’t know: Minard wasn’t first either.

Enter Henry Drury Harness

In 1837, a British Army lieutenant named Henry Drury Harness was assigned to the Irish Railway Commission, tasked with figuring out where railways should be built across Ireland. To answer that question, he needed to map where people and goods were already moving — and he needed to show how much was moving, not just where.

So he invented something new: maps where the width of each line was drawn proportional to the volume of traffic it represented. Thick bands for busy routes, thin lines for quiet ones. The maps were published in the Commission’s report in 1838 — seven years before Minard’s first flow map, and sixty-one years before Sankey’s famous diagram.

Besides this remarkable piece of work, Harness also invented graduated circles for showing city populations, figured out how to show urban and rural populations on the same map, and pioneered choropleth shading for population density — all in the same atlas. Then, for nearly 120 years, almost nobody noticed. The cartographic historian Arthur Robinson called them “one of the more remarkable sets of maps ever made.” (his 1955 article in The Geographical Journal was the first serious academic treatment of Harness’s contribution.)

This is what’s sometimes called Stigler’s Law of Eponymy: scientific discoveries are almost never named after their actual discoverers. (Stigler himself attributed the law to the sociologist Robert Merton, making it a self-demonstrating theorem, which is maybe the most elegant thing in the history of science.) In this case the law applies with unusual force: three separate inventors, spread across sixty years, and the name went to the last one.

Anyway. Minard. Whether Minard knew of Harness’s work or arrived at the same idea independently isn’t known for certain. What is known is that he took it further than anyone: 51 flow maps over his career, each grounded to the geography it was about, so you could see the actual physical paths things took through the world.

His 1864 map of cotton imports into Europe, for example, traces flows from the American South, Egypt, and India into British and continental ports. His wine export maps show where French wine was shipped by sea — all the way to the Americas, Africa, and Australia. His migration maps show people moving between countries as bands, thicker where more people went. These weren’t just abstract Sankey charts — they were Sankey charts grounded to a map, so you could see the actual physical paths things took through the world.

And then, for about 150 years, this idea kind of sat there. You could make a regular Sankey chart in any charting library. You could put dots on a map. But actually combining the two — proportional flow bands that respect geography, follow real routes, animate, and work on a globe — that was surprisingly hard to pull off in an interactive, web-friendly way.

Until now.

amCharts Just Introduced Map Sankey

amCharts just released MapSankeySeries — a new chart series type for the amCharts 5: Maps library that does exactly what Minard was sketching by hand in the 1860s, but interactive, animated, and built into the same maps library you might already be using.

The core idea: you define a set of flows (origin, destination, value), and the library draws curved bands between those points on the map. Band width is proportional to the value, just like a regular Sankey. But because it’s on a map, the bands follow the actual geography — they pan and zoom with the map, they curve correctly in different projections, and if you’re using a globe, they wrap around it properly.

The Demos Are Where It Gets Fun

Provided you haven’t been taking a vacation from this world under some rock, you’ve no doubt heard about the Strait of Hormuz. Yes, that narrow sliver of water that acts as a bottleneck for the good chunk of the planet’s oil trade.

The oil flow demo is the one that really shows what waypoints can do. It maps crude oil exports out of the Persian Gulf — Saudi Arabia, Iraq, UAE, Kuwait, Iran, Qatar — all flowing out through the Strait of Hormuz and then splitting off to refineries in Asia and Europe. The flows route through actual maritime channels: through the Strait, across the Arabian Sea, through the Malacca Strait, up to East Asia, or west through the Suez Canal to Europe.

Interactive demo: Oil Export Flows with Waypoints »

The coffee one is a bit more fun for everyday context — it traces the global coffee supply chain from growing regions to consuming countries. Which is a nice way to think about your morning cup: it probably crossed at least two oceans to get to you.

Interactive demo: Coffee Sankey Map »

What Can You Actually Build With This?

Anytime you have data that’s about things moving between places, and the volume of that movement matters, this is the chart type you want. Some obvious ones:

• Trade flows — imports and exports between countries or regions

• Migration — where people are moving to and from

• Supply chains — where components are sourced and where products ship

• Energy grids — electricity generation and distribution across a region

• Flight routes — passenger volumes between hubs

• Financial flows — investment or remittance patterns between countries

The thing that makes it more useful than a regular Sankey is that your audience immediately understands the geography without having to think about it. If you’re visualizing shipping routes, the map tells half the story before anyone reads a label.

Getting Started

The basic setup is pretty minimal. You add a MapSankeySeries to an existing map chart and feed it nodes (the locations) and links (the flows between them). Locations can be specified as ISO country codes, latitude/longitude pairs, or a mix:

var sankeySeries = chart.series.push(
  am5map.MapSankeySeries.new(root, {
    sourceIdField: "from",
    targetIdField: "to",
    valueField: "value"
  })
);

sankeySeries.nodes.data.setAll([
  { id: "SA", title: "Saudi Arabia" },
  { id: "CN", title: "China" },
  // ...
]);

sankeySeries.links.data.setAll([
  { from: "SA", to: "CN", value: 1800 },
  // ...
]);

Waypoints are added per-link, as an array of lat/lon coordinates that the band should route through. The full documentation covers all the options — coloring modes, particle animation speed, node shapes, and so on.

Full docs »

Minard Would Have Loved This

The reason Minard’s Napoleon map is so celebrated isn’t just that it packs six variables into one chart. It’s that you feel the retreat. It’s not just informative — it’s affecting. The geography carries emotional weight that a table of numbers never could.

Minard got there first. His name just didn’t stick to it. But the idea was always right, and now it’s a lot easier to pull off.

Subscribe now

Before You Start: Set Up the amCharts MCP Server

If you’re using an AI coding assistant (Claude, Cursor, Windsurf, or any tool that supports MCP), the very first thing you should do is install the amCharts 5 MCP server. It gives your AI direct access to the full amCharts documentation, code examples, and class references — so it can look things up instead of guessing.

Install it globally:

npx @amcharts/amcharts5-mcp init

That’s it. One command. It registers the MCP server with your tool automatically.

For manual setup, configuration options, or more details:

• GitHub: amcharts/amcharts5-mcp

• npm: @amcharts/amcharts5-mcp

The Rule

Tell your AI this, and make it stick — put it in your system prompt, your CLAUDE.md, your project instructions, wherever your tool reads its guidelines from:

“For all amCharts-related code, use the MCP server as your single source of truth. Before using any setting, property, event, or method — look it up in the class reference via MCP. Do not guess. Do not rely on training data. If you’re unsure whether something exists, verify it before writing it.”

AI without a reference hallucinates. AI with a reference builds working charts. That’s the entire difference.

And if you’re using TypeScript (which you should — amCharts 5 ships full type definitions), always compile the generated code. The type checker will catch wrong setting names, missing properties, and bad method signatures that even the MCP lookup might miss.

What We’re Building

We’re going to build an animated globe, step by step, using nothing but natural language prompts. Each step builds on the previous one — starting from a simple rotating globe with city markers and ending with a polished animation featuring eased flight paths, pulsing plane icons, and city labels that fade in and out on cue.

At each step, you’ll see the exact prompt that was given to the AI, and the result as a live, interactive demo you can play with.

A note: if you try the same prompts, your results will differ. Working with AI is not an exact science — the output depends on the model, your setup, the conversation history, and sometimes, apparently, on weather conditions or the mood of your AI. That’s fine. The prompts are a starting point, not a recipe.

The Steps

Prompt #1

A rotating globe with cities and dashed connection lines:

Make a globe showing one famous city per continent, marked with circles. Connect them with dashed lines. The globe should auto-rotate, and let the user rotate it with mouse or touch.

Live demo »

Prompt #2

Add a plane that follows the lines, globe tracks the plane:

Add a plane icon that follows the lines between cities. The globe should rotate to keep the plane always at the center.

Live demo »

Prompt #3

Eased flight, scale pulse, city pauses, and rotation transition:

Fly the plane with easing — start and end each segment slower. The plane should start small, grow bigger mid-segment (as if gaining altitude), then shrink back when approaching the next city. Pause briefly when it reaches a city. Before takeoff, animate the rotation to face the new direction, then continue flying.

Live demo »

Prompt #4

City bullet animation and label fade on arrival/departure:

When the plane lands on a city, animate the city bullet bigger — make its fill transparent and show only the stroke (same color as the fill, 4px width). This way the plane won’t disappear into the city dot. Hide city labels by default — only fade them in when the plane is near the city, and fade them out when the plane leaves.

Live demo »

Prompt #5

Final touches — smooth labels, mileage counter, plane shadow:

Final touches: remove the background from city labels and make them bigger. Use a more interesting label animation. Reduce the dashed line gaps and stroke length. Add a large ‘Total miles: XXXX’ label in the top-left — the number should increase in real time as the plane flies, based on actual mileage. Show a shadow under the plane — the shadow distance should increase mid-segment (higher altitude) and decrease near cities.

Live demo »

Takeaways

Five prompts. Each one a plain English sentence describing what should happen next. The MCP server gave the AI access to real documentation — so instead of hallucinating API calls, it looked them up and got them right.

The key lesson: an AI with a reference is a different tool than an AI without one. The MCP server is free, takes one command to install, and turns vague guesses into working code. If you’re building with amCharts and AI, start there.

If we’d get 10 cents every time someone asked us for a such and such vector map, we’d be… uh, no idea what we’d be, but the point is there’s a strong demand for vector maps. And not just classic ones, like the one you remember from your classroom.

There are tens if not hundreds of map projections.

There are different versions of the same maps - both the world but also for individual countries.

There are Atlantic-centered maps, and the ones focused on the Pacific.

Flat maps or the globe.

Colored or monochrome. With or without graticule grid.

You get the drift.

That’s why we’ve built a new tool: SVG Map Generator.

It’s free, and super flexible. Just select a world, regional, or country map, the settings and grab a freshly minted SVG file. Free. No strings attached.

Whoa, give me all the nitty gritty detail

Fine, you asked for it. Treat the text below as a detailed round up of SVG Map Generator’s features. A sort of documentation. Here we go.

Choose the Right Projection

The good news is there are tons of projections that handle area much more honestly. Our SVG Map Generator offers 90+ projections, organized by type:

• Equal Earth - General-purpose world maps. Equal-area, visually appealing.

• Natural Earth - Thematic & editorial maps. Compromise: slight distortion, pleasant shape.

• Robinson - Wall maps, atlases. Compromise projection, National Geographic standard.

• Winkel Tripel - Reference maps. Minimizes overall distortion (area + shape + distance).

• Gall-Peters - Area-accurate comparisons. Strictly equal-area (shapes are stretched).

• Mollweide - Distribution maps. Equal-area, elliptical shape.

• Orthographic - Globe icons, perspective views. Shows Earth as seen from space.

You can switch between all of these instantly in the tool, preview the result, and export a clean SVG with the projection you actually want.

Pacific-Centered Maps

Here’s one that comes up a lot: what if you need a map centered on the Pacific instead of the Atlantic? If you’re working with Asia-Pacific data, the standard Atlantic-centered world map cuts the Pacific right in half, splitting Asia from the Americas.

In the tool, just drag the map to the position you want and hit export. The SVG comes out centered exactly as you see it. No post-processing, no coordinate hacking.

This works with any projection. Want a Pacific-centered Equal Earth? Robinson? Mollweide? Just rotate and export.

Simplification: Less Is More

Here’s another issue with most SVG maps you find online: they’re bloated. A typical “low-detail” world map SVG might have 11,000+ coordinate points. For dashboards, infographics, or thumbnails, that’s massive overkill. You’re shipping hundreds of kilobytes of path data that nobody can even see at normal display sizes.

Our tool has built-in TopoJSON simplification. Drag a slider, watch points disappear, and the map stays perfectly recognizable. Here’s the same world map at three levels:

That 90%-simplified map is 3x smaller than the original and still perfectly usable for dashboards, illustrations, or any context where you don’t need to zoom into individual coastlines. The tool supports both planar and spherical simplification, so you can pick whichever best preserves the shapes you care about.

• 137 KB: Original

• 85 KB: 50% simplified

• 45 KB: 90% simplified

Regional Maps: Only What You Need

Sometimes you don’t need the whole world. Maybe you’re building a European sales dashboard or a North American logistics tool. Loading a full world map and then zooming to your region is wasteful - you’re downloading paths for countries you’ll never show.

The tool includes 100+ map sources, with dedicated regional maps for every continent and sub-region:

Each map comes with proper country id attributes (ISO codes) and title tags, making it trivial to style individual countries with CSS or hook up interactions with JavaScript.

Globe Icons with Orthographic Projection

Need a small map icon or a globe thumbnail for your app? The orthographic projection shows the world as if viewed from space. It’s a natural, intuitive look that works great at small sizes.

In the tool, switch to orthographic projection, rotate the globe to show the region you want, and export. You get a clean, lightweight SVG globe:

These use a simplified continents map with no country borders, just clean landmass silhouettes. Pure SVG, no JavaScript, no dependencies. They scale to any size, look sharp on retina displays, and weigh just 15-17 KB each.

Animated SVG Globe

Here’s a fun one. You can take it a step further and create an animated spinning globe, entirely in SVG, no JavaScript needed. Generate multiple orthographic frames at different rotation angles, combine them with CSS animations, and you get a smoothly rotating globe:

This uses a heavily simplified world map (95% of points removed) to keep the file size manageable. Each frame is a separate group in the SVG, with CSS keyframes toggling their visibility. The result: a self-contained animated globe you can drop into any webpage, email, or presentation.

Maps as Icons

Sometimes you don’t need a detailed map at all, just a tiny recognizable shape. A favicon, a logo element, a loading indicator. For those cases, push simplification to the extreme and strip away country borders entirely, leaving just continent silhouettes.

Combine maximum simplification with the right projection, and you get map icons that are just a few kilobytes:

At 5-9 KB, these are smaller than most PNG icons, and they scale perfectly to any size. Use them as inline SVGs in your HTML or reference them as image files. Resolution-independent, crisp on any screen.

Country Maps

The tool doesn’t just do world maps. It includes individual maps for 100+ countries, each with internal subdivisions (states, provinces, departments). Perfect for country-specific dashboards, election maps, or regional analysis:

Each subdivision gets its own <path> element with an id attribute, so you can target them individually with CSS:

#JP-13 { fill: #ef4444; }  /* Highlight Tokyo */
#BR-SP { fill: #3b82f6; }  /* Highlight São Paulo */
#FR-75 { fill: #10b981; }  /* Highlight Paris */

The USA and Albers Projection

Remember my Alaska story? Here’s where it gets practical. The US spans a huge east-west distance, and Alaska and Hawaii are geographically far from the mainland. On a standard Mercator map, showing all three wastes a ton of space and makes Alaska look way bigger than it actually is (which is exactly why I lost my sense of scale in the first place).

That’s why the Albers USA projection exists. It’s a composite projection built specifically for the US: it uses a conic equal-area projection for the lower 48 states, then tucks Alaska (scaled down) and Hawaii (repositioned) into insets below. This is the standard projection used in government statistics, election maps, and pretty much any serious US data visualization.

Our tool includes Albers USA alongside all the standard options. Pick a USA map source and it shows up automatically in the projection dropdown. The exported SVG keeps the inset layout intact, ready for dashboards, infographics, or election night.

Color Customization & Paint Mode

The tool includes a paint mode that lets you color individual countries or regions right in the browser. Choose a color, click on a country, and the SVG export preserves your custom colors as CSS rules. Great for creating quick thematic maps without writing any code.

You can also tweak the global fill color, stroke color and width, background, and graticule styling. Everything updates live in the preview and gets baked into the exported SVG.

Clean, Semantic SVG Output

Unlike many SVG map tools that spit out opaque, tangled markup, our generator produces clean, readable SVG:

• Every country path has an id attribute (ISO country code) and a title

• Styles live in a <style> block, easy to override

• No inline transforms, no nested groups, no JavaScript

• Proper XML declaration and viewBox for correct scaling

• Works in any browser, any framework, any CMS

The SVG files are standalone. Drop them into your HTML, your React app, your Figma project, your PowerPoint. They just work.

Toggle & Hide Countries

Need to show only certain countries? The tool has a country list panel where you can hide or show individual countries with a click. When you export, hidden countries are simply excluded from the SVG. This is especially useful for:

• Creating maps of specific regions (e.g., EU member states only)

• Removing overseas territories you don’t need

• Building custom groupings (e.g., BRICS nations, NATO members)

Want Something Fancier? Pixel Maps

If you’re after a different aesthetic - maps made of dots, squares, hexagons, or diamonds - check out our Pixel Map Generator. Same idea (pick a projection, pick a map source, export), but instead of smooth vector paths, it renders the map as a grid of shapes.

Great for infographics, dashboards with a techy vibe, or anywhere you want a map that looks a bit more stylized. You can tweak the pixel size, gap, colors, and export as SVG, PNG, or even interactive HTML.

Need Interactivity? Use amCharts

SVG maps are great for static visuals, but if you need zooming, panning, tooltips, clickable regions, animated flight routes, or live data updates - you’ll want a proper charting library. That’s what amCharts is for. Check out the map demos gallery to see what’s possible - choropleth maps, bubble maps, drill-downs, animated planes flying along routes, and more. All with a few lines of code.

Passage du Niemen, the label at the bottom reads. It shows Napoleon at the very beginning of his infamous march toward Moscow -- the moment his army crosses the Neman (Nemunas) River.

That detail immediately reminded me of a famous data visualization.

If you’re into data visualization, you probably know Edward Tufte -- one of the most recognizable names in the field. In his book The Visual Display of Quantitative Information, he highlights a chart created in 1869 by Charles Joseph Minard and famously calls it “the best statistical graphic ever drawn.”

The chart visualizes French invasion of Russia and manages to encode six variables at once: the size of Napoleon’s army, geographic location, direction of movement, temperature, and time -- all in a single coherent two-dimensional graphic.

What’s interesting is where the famous visualization begins. Minard starts the march in Kowno -- today’s Kaunas -- right after Napoleon’s army crosses the Neman River. Exactly the moment depicted in the gravure I found. Seeing that image instantly connected the historical scene with Minard’s visualization in my mind.

I’ve wanted to recreate this remarkable chart using the library I built -- amCharts -- for a long time. What kept stopping me was the data and the time required to reconstruct it properly.

With modern AI tools (in this case, Claude), the process became much more manageable. I spent about five hours gathering the data, adjusting certain points, and refining the design. I’m not claiming the result is perfect, but it’s reasonably close -- and, in my opinion, it looks pretty good.

Take a look and play with it -- it’s interactive.

Interactive demo

Download the code