I'd probably use genfromtxt:
>>> from numpy import genfromtxt
>>> genfromtxt("missing1.dat", delimiter=",")
array([[ 1., 2., 3., 4., 5.],
[ 6., nan, nan, 7., 8.],
[ nan, nan, 9., 10., 11.]])
and then do whatever with the nans (change them to something, use a mask instead, etc.) Some of this could be done inline:
>>> genfromtxt("missing1.dat", delimiter=",", filling_values=99)
array([[ 1., 2., 3., 4., 5.],
[ 6., 99., 99., 7., 8.],
[ 99., 99., 9., 10., 11.]])
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