 One of the things I used to do a lot, especially in grad school, is make cool maps. The same tools that I was learning to visualize data from astronomy sources, big catalogs of stars for example, are perfect for visualizing other kinds of data, and this became a hobby for me that I published almost every week for a couple of years on my blog. So I just now remade a really cool map, one of my favorites that I made in grad school, which is called Airports of the World. This is the latitude and longitude location of like 50,000 airports. What I love about this map is not only does it reproduce the geography of our world, there's runways and helipads and airstrips on all seven continents. But this is a large data set that's made publicly available, so what's so wonderful about dealing with data like this? Usually you're dealing with government data, this is made available by ourairports.com. It's as simple as downloading this data, in my case, sticking it into Python and out comes a really awesome graph, or in this case, a map. What's so enchanting about this is that first you look at it and you say, this is simply a population density map. There's a famous XKCD comic where people are making all kinds of like neat data visualizations that just turn out to be population density maps. Of course in America, this is something that's very famously done to distort geography and politics and population density, but what I love about this map is we're not exactly probing population density directly, but it's modulated by something to do with wealth and infrastructure and history. Highly colonialist mindset history. For example, there is a really sharp discontinuity in the amount of data along the U.S. Mexican border. This has a lot to do with wealth inequality. It may have also to do with incomplete data, so there's a whole story there just in that border that's being drawn simply by the density of airstrips. I love all the little dots that are out in the oceans. Of course, a lot of these are military bases or landing sites for military planes or historical landing strips from war. There's a place to land almost everywhere on the planet. A cool follow-up project would be like a hybrid of the United States of Starbucks map that I made. What's the furthest you can get from an airstrip or a landing site? That's a cool idea. Somebody should do that. Another good example of history being laid out on this map is there's this little faint line in Northern Canada. This is actually the dew line or the distant early warning line, a line of radar stations that were put up in the Arctic to warn the Americans about possible Russian incursions in the Cold War. Most of them are abandoned or are not functional. Some of them are still military outposts, I think. It's an interesting like historical relic that is just seen as this line. Of course, you'll notice problems in the data as well. For example, there is a little cross of data points, a little cluster that I noticed off the coast of Nigeria or the Cameroon sort of area. This took me a minute to figure out, but it turns out these are just data entry problems. I didn't do too deep of a dive, but this cross lines up to, within about a degree of the origin of zero latitude and zero longitude. This is just an artifact in the data. One thing that I consistently like about data visualizations and maps like this is they have a lot of different scales you can view the map. You can step back and look at the whole earth and admire the aesthetic beauty of how the continents are traced out in these faint dots and lines and clusters. Of course, there's tremendous detail where the data is most complete, which is the U.S. There's lots of little clusters. And I love a graph that encourages people to zoom in. I don't know the geography of Eastern Europe very well, for example. But if you zoom in, there's lots of structure. There are lots of clumps. There are lots of lines. There are borders. There are holes, which again, tell these stories of war and population and people. When you make a static visualization like this, it's really effective. When it has these layers of interpretability, where people will be drawn to zooming in where they live to tell their own story, to take their own screenshot of where they live in Europe or in Australia or in Africa and make the story about them. So there you go. A simple graph I made yesterday, which is part of a complex story of our civilization. You can check out the code on GitHub, the original post on my blog, ifweassume.com. And usually I talk about astronomy on this channel. But if you like this discussion of data visualization, graphs, tools and techniques, have a lot of content and expertise in data visualization. And so, if you're interested in these kinds of videos, let me know and I'll make more. And as is YouTube tradition, make sure you like and subscribe and all those important things so that I know you're enjoying what I'm doing. Okay.