# [SOLVED] how do I properly use the result of argmin to slice out an array of the minimums?

## Issue

I’m looking to slice out the minimum value along the first axis of an array.
For example, in the code below, I want to print out `np.array([13, 0, 12, 3])`.
However, the slicing isn’t behaving as I would think it does.
(I do need the argmin array later and don’t want to just use `np.min(g, axis=1)`)

``````import numpy as np
g = np.array([[13, 23, 14], [12, 23, 0], [39, 12, 92], [19, 4, 3]])
min_ = np.argmin(g, axis=1)
print(g[:, min_])

``````

What is happening here?
Why is my result from the code

``````[[13 14 23 14]
[12  0 23  0]
[39 92 12 92]
[19  3  4  3]]
``````

Other details:
Python 3.10.2
Numpy 1.22.1

## Solution

If you want use `np.argmin`, you can try this:

For more explanation : from `min_` you have `array([0, 2, 1, 2]) ` but for accessing to array you need `((0, 1, 2, 3), (0, 2, 1, 2))` for this reason you can use `range`.

``````min_ = np.argmin(g, axis=1)
g[range(len(min_)), min_] # like as np.min(g ,axis=1)
``````

Output:

``````array([13,  0, 12,  3])
``````