Steven D'Aprano writes: > As usual though, NANs are unintuitive: > > >>> d = {float('nan'): 1} > >>> d[float('nan')] = 2 > >>> d > {nan: 1, nan: 2} > > > I suspect that's a feature, not a bug. I don't see how it can be so. Aren't all of those entries garbage? To compute a histogram of results for computations on a series of cases would you not have to test each result for NaN-hood, then hash on a proxy such as the string "Nan"?
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