Does using tensors for storage yield some benefit over the 'panels' metaphor that Python Pandas affords? It seems like the real power of tensors is in the calculus that can be run over them, rather than just them by themselves.

If I want to store lists of numbers, arrays and (linked) lists are basically equivalent. It's when I want to calculate cross- and dot-products that vectors prove especially useful.

The discussions I've seen recently in data science about tensors seems to only be about the storage aspect. And, I suppose, if your libraries _don't_ provide such a storage mechanism, then yes, you'll benefit from adding that capability. But I keep waiting for more from the ML community about leveraging differential geometry full-on. I assume it's out there somewhere, in some shops, but I've not found a lot of discussion about it.