Finding the index of minimum value in a row in numpy array

I can’t seem to get my head around how to do this – I am new to Python and this kind of work with arrays. I have a large array, say:

array([[119., 323.,  42., 277., 401.],
       [122., 326.,  39., 278., 10.],
       [125., 329.,  36., 12., 407.],
       ...,
       [308., 314., 469., 188., 266.],
       [308., 314., 469., 188., 266.],
       [308., 314., 469., 188., 266.]])

I would like to find the column index of the minimum value in each row. For instance for the first 3 rows would give [2, 4, 3….]. I have experimented with .min() and np.where(), for instance:

np.where(array == array.min())

But I just can’t seem to get the answer I’m looking for. Any help would be much appreciated, thanks

Answer

Use numpy argmin():

np.argmin(a, axis=1)

where a is your numpy array.