# numpy.sort() in Python

Last Updated : 29 Nov, 2018

numpy.sort() : This function returns a sorted copy of an array.

Parameters :

arr : Array to be sorted.
axis : Axis along which we need array to be started.
order : This argument specifies which fields to compare first.
kind : [â€˜quicksortâ€™{default}, â€˜mergesortâ€™, â€˜heapsortâ€™]Sorting algorithm.

Return :

`Sorted Array`

 `# importing libraries ` `import` `numpy as np ` ` `  `# sort along the first axis ` `a ``=` `np.array([[``12``, ``15``], [``10``, ``1``]]) ` `arr1 ``=` `np.sort(a, axis ``=` `0``)         ` `print` `(``"Along first axis : \n"``, arr1)         ` ` `  ` `  `# sort along the last axis ` `a ``=` `np.array([[``10``, ``15``], [``12``, ``1``]]) ` `arr2 ``=` `np.sort(a, axis ``=` `-``1``)         ` `print` `(``"\nAlong first axis : \n"``, arr2) ` ` `  ` `  `a ``=` `np.array([[``12``, ``15``], [``10``, ``1``]]) ` `arr1 ``=` `np.sort(a, axis ``=` `None``)         ` `print` `(``"\nAlong none axis : \n"``, arr1) `

Output :

```Along first axis :
[[10  1]
[12 15]]

Along first axis :
[[10 15]
[ 1 12]]

Along none axis :
[ 1 10 12 15]```

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