# How to sort a Numpy Array | Python

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.

 `# 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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