"Anders J. Munch" <[email protected]> writes:
> So far I received exactly the answer I was expecting. 0 examples of
> NaN!=NaN being beneficial.
> I wasn't asking for help, I was making a point. Whether that will
> lead to improvement of Python, well, I'm not too optimistic, but I
> feel the point was worth making regardless.
Well, I just spotted this thread. An easy example is, well, pretty much
any case where SQL NULL would be useful. Say I have lists of borrowers,
the amount owed, and the amount they paid so far.
nan = float("nan")
borrowers = ["Alice", "Bob", "Clem", "Dan"]
amount_owed = [100.0, nan, 200.0, 300.0]
amount_paid = [100.0, nan, nan, 200.0]
who_paid_off = [b for (b, ao, ap) in
zip(borrowers, amount_owed, amount_paid)
if ao == ap]
I want to just get Alice from that list, not Bob. I don't know how much
Bow owes or how much he's paid, so I certainly don't know that he's paid
off his loan.
Cheers,
Johann
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