Calculate min of rows ignoring NaN values

user3654650

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]?

lejlot

You can use masked arrays

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

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edited at2020-10-21

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