# xorbits.numpy.ndarray.sort#

ndarray.sort(axis=- 1, kind=None, order=None)#

Sort an array in-place. Refer to numpy.sort for full documentation.

Parameters
• axis (int, optional) – Axis along which to sort. Default is -1, which means sort along the last axis.

• kind ({'quicksort', 'mergesort', 'heapsort', 'stable'}, optional) –

Sorting algorithm. The default is ‘quicksort’. Note that both ‘stable’ and ‘mergesort’ use timsort under the covers and, in general, the actual implementation will vary with datatype. The ‘mergesort’ option is retained for backwards compatibility.

Changed in version 1.15.0(numpy): The ‘stable’ option was added.

• order (str or list of str, optional) – When a is an array with fields defined, this argument specifies which fields to compare first, second, etc. A single field can be specified as a string, and not all fields need be specified, but unspecified fields will still be used, in the order in which they come up in the dtype, to break ties.

`numpy.sort`

Return a sorted copy of an array.

`numpy.argsort`

Indirect sort.

`numpy.lexsort`

Indirect stable sort on multiple keys.

`numpy.searchsorted`

Find elements in sorted array.

`numpy.partition`

Partial sort.

Notes

See numpy.sort for notes on the different sorting algorithms.

Examples

```>>> a = np.array([[1,4], [3,1]])
>>> a.sort(axis=1)
>>> a
array([[1, 4],
[1, 3]])
>>> a.sort(axis=0)
>>> a
array([[1, 3],
[1, 4]])
```

Use the order keyword to specify a field to use when sorting a structured array:

```>>> a = np.array([('a', 2), ('c', 1)], dtype=[('x', 'S1'), ('y', int)])
>>> a.sort(order='y')
>>> a
array([(b'c', 1), (b'a', 2)],
dtype=[('x', 'S1'), ('y', '<i8')])
```

This docstring was copied from numpy.ndarray.