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ndarray.sort() ⚬｜Documentation｜1st｜20251021141213-00-⌔

numpy.ndarray.sort — NumPy v2.0 Manual#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: 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.

See also:

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')])

Printed 2026-06-28.

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