To be honest, some of these ideas have a fairly saturated market. If you write another python tricks & tips book or another data science starter examples book, it might sell some copies and make some money. But it probably won't contribute a lot unless you have some extremely good and new ideas and can execute them consistently.

Medium-complexity books are much more interesting but also harder to write.

"in pictures" books are also great; I feel we don't have enough of them. But they are also not very simple, because if you can't use animation, some phenomena are kind of hard to convey. If you can pull that off for graph theory or statistics, awesome!

Perhaps you should take one hard example from each domain and think about how you would write it.

I.e. How would you explain a gibbs sampler in pictures?