A.Yazdiha - 1 year ago 106

Python Question

I am struggling to understand the mechanism behind a function around the topic of sorting in numpy.

`import numpy as np`

arr = [[8, 5, 9],

[3, 9.5, 5], [5.5, 4, 3.5], [6, 2, 1],

[6,1,2],[3,2,1],[8,5,3]]

res = sorted(arr, key=np.argmax)

This gives me the following result:

`print(res)`

[[5.5, 4, 3.5], [6, 2, 1], [6, 1, 2],

[3, 2, 1], [8, 5, 3], [3, 9.5, 5], [8, 5, 9]]

I am an R user and not very familiar with Python. I might have some clue about the role of the 'key' argument, but for this example specifically I ask for your help.

In a simple case if the

`key`

`sorted`

`argmax`

Thanks,

Recommended for you: Get network issues from **WhatsUp Gold**. **Not end users.**

Answer Source

The argmax function returns the indice of the biggest element. It is used as a key in the sort function.

If you print this:

```
print([np.argmax(x) for x in arr])
```

you get:

```
[2, 1, 0, 0, 0, 0, 0]
```

which explains the sorting. Last elements appear first in your result, first element appears last because it has the highest criteria, and second element appears just before.

Of course this is a "weak" sorting since the criteria often returns the same value and thus the result depends on the order of the initial list (edit: this is called a stable sorting, see interesting Bakuriu comment)

Recommended from our users: **Dynamic Network Monitoring from WhatsUp Gold from IPSwitch**. ** Free Download**