A few approaches got lucky in the rapid inflationary period of the personal computer revolution (C), and the advent of the Web (Javascript), and became deeply entrenched in industry, while superior alternatives that had been known for decades missed the boat. Industry languages still haven't caught up to where Lisp, Prolog, Smalltalk, and APL were in the 1970's, but they are clearly (if slowly) trending in that direction.
APL and derivatives are still used extensively in finance, a highly competitive field, to say the least. That's where you find the jobs.
That's just the whole "popularity means it must be good" argument, which I disagree with.
Why? I believe if you started teaching someone APL who'd never programmed before you'd never hear "this code is too dense!".
Math tends to be written for subject matter experts. If I'm reading a paper about graphics, I know that θ is "theta" and likely means "angle in radians". If I'm not a subject matter expert, it means nothing. Of course they can write at the top "let θ = light incident angle in radians", but I still need to hold that definition in my head while I'm trying to understand the rest of it. If I simultaneously need to remember ⍵ and ε and Δ, well, I can do that if I've seen those symbols used in similar ways previously, but it's certainly going to increase the amount of things I need to hold in my head if it's something novel. And now I have to memorize what those things mean, and I suck at memorizing personally.
In contrast, most mainstream programming languages you'd just write "angle_rads" or some variant. It's a little longer, but I don't need to remember nearly as much because it's just plain english formatted in a way that at least resembles sentences I might read. I just think APL is too unfamiliar for it to be easy to learn, and so the only people that are going to learn it are those that are very intellectually curious. That's a good thing, but if you're talking popularity? Well, I think we've seen it, and it's not just path dependence.