2008/5/20 Vasileios Gkinis <[EMAIL PROTECTED]>: > I have a question concerning nan in NumPy. > Lets say i have an array of sample measurements > a = array((2,4,nan)) > in NumPy calculating the mean of the elements in array a looks like: > >>>> a = array((2,4,nan)) >>>> a > array([ 2., 4., NaN]) >>>> mean(a) > nan > > What if i simply dont want nan to propagate and get something that would > look like: > >>>> a = array((2,4,nan)) >>>> a > array([ 2., 4., NaN]) >>>> mean(a) > 3.
For more elaborate handling of missing data, look into "masked arrays", in numpy.ma. They are designed to deal with exactly this sort of thing. Anne _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
