MaskedArray.transpose(*axes)

numpy.ma.std(self, axis=None, dtype=None, out=None, ddof=0) = Compute the standard deviation along the specified axis. Returns

MaskedArray.prod(axis=None, dtype=None, out=None)

numpy.ma.compress_rowcols(x, axis=None)

numpy.ma.zeros(shape, dtype=float, order='C') = Return a new array of given shape and type, filled with zeros.

numpy.ma.argmin(a, axis=None, fill_value=None)

MaskedArray.resize(newshape, refcheck=True, order=False)

numpy.ma.innerproduct(a, b)

MaskedArray.recordmask Return the mask of the records. A record is masked when all the fields are masked

MaskedArray.data Return the current data, as a view of the original underlying data.