Enthought has asked me to look into the "missing data" problem and how NumPy could treat it better. I've considered the different ideas of adding dtype variants with a special signal value and masked arrays, and concluded that adding masks to the core ndarray appears is the best way to deal with the problem in general.
I've written a NEP that proposes a particular design, viewable here: https://github.com/m-paradox/numpy/blob/cmaskedarray/doc/neps/c-masked-array.rst There are some questions at the bottom of the NEP which definitely need discussion to find the best design choices. Please read, and let me know of all the errors and gaps you find in the document. Thanks, Mark
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