Calculate min of rows ignoring NaN values

Question

For example, I have this array and calculate mean of rows:

a = np.array([[1,2,3],[2,np.NaN,4]])

mins = np.min(a, axis = 1)

The problem is the output is: [1. nan]. How to ignore nan in a and get result [1 2]?

Answer 1

Another more concise and slightly faster alternative is to use the numpy.nanmin() function, which does exactly what you asked for.

Answer 2

You can use masked arrays

mins = list(np.min(np.ma.masked_array(a, np.isnan(a)), axis=1))