# How to sort a Numpy Array | Python

• Last Updated : 11 May, 2020

In this article, we will learn how to sort a Numpy array. There are multiple ways in Numpy to sort an array, based on the requirement. Let’s try to understand them with the help of examples.

Example #1: Simply sort the given array based on axis using sort() method.

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 `# 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]

```

Example #2: Get the indices which can return sorted array using argsort() method

 `# Python code to demonstrate ``# working of  numpy.argsort``import` `numpy as np``  ` `# Numpy array created``a ``=` `np.array([``9``, ``3``, ``1``, ``7``, ``4``, ``3``, ``6``])``  ` `# unsorted array print``print``(``'Original array:\n'``, a)``  ` `# Sort array indices``b ``=` `np.argsort(a)``print``(``'Sorted indices of original array->'``, b)``  ` `# To get sorted array using sorted indices``# c is temp array created of same len as of b``c ``=` `np.zeros(``len``(b), dtype ``=` `int``)``for` `i ``in` `range``(``0``, ``len``(b)):``    ``c[i]``=` `a[b[i]]``print``(``'Sorted array->'``, c)`

Output:

```Original array:
[9 3 1 7 4 3 6]
Sorted indices of original array-> [2 1 5 4 6 3 0]
Sorted array-> [1 3 3 4 6 7 9]
```

Example #3: Get stable sort using a sequence of keys.

 `import` `numpy as np``  ` `# Numpy array created``# First column``a ``=` `np.array([``9``, ``3``, ``1``, ``3``, ``4``, ``3``, ``6``])``  ` `# Second column ``b ``=` `np.array([``4``, ``6``, ``9``, ``2``, ``1``, ``8``, ``7``]) ``print``(``'column a, column b'``)``for` `(i, j) ``in` `zip``(a, b):``    ``print``(i, ``' '``, j)``  ` `# Sort by a then by b``ind ``=` `np.lexsort((b, a)) ``print``(``'Sorted indices->'``, ind)`

Output:

```column a, column b
9   4
3   6
1   9
3   2
4   1
3   8
6   7
Sorted indices-> [2 3 1 5 4 6 0]

```

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