Thanks for looking in to it.
TL;DR warning for a philosophical rant about learning data science:
As far as the data goes, it's great that it's fun but it's important that it's a data set I'm familiar with. I can look at that graph and tell you that around turn 50 is when I usually get my first wonders built and turn 230 looks like when I started building spaceports to explain the changes in the rate of increase. The point of data science is to be able to make sense of what you see when you aggregate data. All due respect to the people who work on the course content but sales data is nebulous. I have no way of explaining why some products outsell others and other such questions that facilitate understanding what numbers I see and why. Only from there can I possibly hope to learn new things by looking at the data and trying to understand numbers I can't explain. If the whole data set is producing numbers I can't explain, I can't even tell when I'm doing it wrong. I'm great with computer science but data science is a skill set where I still have a lot to learn. Obscure data is a barrier to understanding that I see a lot in teaching data science. I'd be willing to bet that for people who are good at this kind of thing, any data is fine to work with. When learning how to think about data science, I find it better to look at data I know. Sociologically, I'm not sure what data would be good for teaching most people but I can tell you anything you want to know about a game of Civ6 I played.
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