Some median Python NaNsense

Some median Python NaNsense

Posted Jan 10, 2020 2:29 UTC (Fri) by gdt (subscriber, #6284)
In reply to: Some median Python NaNsense by cpitrat
Parent article: Some median Python NaNsense

None isn't that useful for processing large datasets where memory efficiency matters, as typically generated by scientific instruments. Thus SciPy's overloading of NaN. Putting that another way:

import array
a = array.array('d', [1.0, 2.0, 3.0, None])
TypeError: must be real number, not NoneType

Note that I am not arguing for overloading NaN -- I don't have a dog in this fight -- I'm just using my background as a statistics professional to explain why choices your tone suggests are unreasonable have been made by people acting reasonably.

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