Working with data scientists, in practice, these identifiers are usually "arr1", "arr2", &c. I'd rather have method chaining. Often the intermediates are not meaningful.
I agree with you in general, people (especially data scientists) are bad at naming things.
It's probably the core skill of good programmers though, so it should be taught more. I don't think anyone sets out to use misleading names, but it's easy for name and code to diverge, and it's crippling to readability.
However, often when refactoring/updating such data scientist code (or even understanding), I need to break apart the long method chains, and this is much, much more annoying than dealing with crummy names.
At least I can print the values associated with the names, which is not easily possible in the really long method chain.
It's probably the core skill of good programmers though, so it should be taught more. I don't think anyone sets out to use misleading names, but it's easy for name and code to diverge, and it's crippling to readability.
However, often when refactoring/updating such data scientist code (or even understanding), I need to break apart the long method chains, and this is much, much more annoying than dealing with crummy names.
At least I can print the values associated with the names, which is not easily possible in the really long method chain.