numpy: what is the logic of the argmin() and argmax() functions?

Question

I can not understand the output of argmax and argmin when use with the axis parameter. For example:

>>> a = np.array([[1,2         


        

Answer 1

The axis in the argmax function argument, refers to the axis along which the array will be sliced.

In another word, np.argmin(a,axis=0) is effectively the same as np.apply_along_axis(np.argmin, 0, a), that is to find out the minimum location for these sliced vectors along the axis=0.

Therefore in your example, np.argmin(a, axis=0) is [0, 0, 2, 2] which corresponding to values of [1, 2, 3, 4] on respective columns