The np.sort() function is used to sort the array along a specified axis.
Numpy.sort (a, axis=- 1, kind=None, order=None)
- Purpose: This function is used for sorting the array.
- Parameters:
- arr:a:array_like array to be sorted.
- axis: None or int,optional Axis on which we perform the arithmetic mean if specified. otherwise, the arr will be flattened.
- kind: {‘quicksort’, ‘mergesort’, ‘heapsort’, ‘stable’}, optional Kind of sorting algorithm that should be used on the array if required.
- order: str or list of str, optional which fields should be compared first.
- Returns:
- sorted array:ndarray_ Returns array of same type and shape as a
# Import Packages
import numpy as np
Numpy Sort Function
The numpy.sort() function takes in the array as one of the required arguments and returns a copy of the sorted array. Let’s take an example to understand this.
1. Sort 1-D array
Let’s see, how to sort a 1-D numpy array.
Example 1: Sort a 1-D numpy array with default parameters.
# Create a 1-D array
a = np.array([3,6,5,2,1])
# Apply sort method on the above array
sort_a = np.sort(a)
# Print the sorted array
print(sort_a)
[1 2 3 5 6]
The above array is sorted in ascending order. because you have not mentioned any parameters.
2. Sort on 2-D array
Let’s see, sort of a 2-D numpy array using default parameters.
Example 1: Sort a 2-D numpy array with default parameters.
# Create a 2-D array
a = np.array([[2,5,4],[7,4,9]])
# Apply sort method on the above array
sort_a = np.sort(a)
# print sorted array
print(sort_a)
[[2 4 5]
[4 7 9]]
The array is sorted in ascending order along axis 0 as axis 0 is the default parameter.
Example 2: Sort a 2-D numpy array with axis = 0
# Create a 2-D array
a = np.array([[2,5,4,0],[7,4,9,1]])
# Apply sort method on the above array
sort_a = np.sort(a, kind = 'quicksort', axis = 0)
# print sorted array
print(sort_a)
[[2 4 4 0]
[7 5 9 1]]
array = [[2,5,4,0],[7,4,9,1]]
sub array1 = [2,5,4,0] sub array2 = [7,4,9,1]
- The sort() method in this example compares the sub array1 1st column value with sub array2 1st column value.
- Which among the compared values are small that will be sorted first.
- The same repeats with all column values in sub arrays.
Example 3: Sort a 2-D numpy array with axis = 1
# Create a 2-D array
a = np.array([[2,5,4,0],[7,4,9,1]])
# Apply sort method on the above array
sort_a = np.sort(a, kind = 'quicksort', axis = 1)
# print sorted array
print(sort_a)
[[0 2 4 5]
[1 4 7 9]]
Here, The sort() method is performed on entire sub array1 and sorts the values in that sub array1 in ascending order.
The same applies to sub array2
3.Test your knowledge
Q1: Can you perform a sort operation on 1-D array when axis=1?
Ans: No, you cannot perform a sort operation on 1-D array when axis=1. It returns a error.
