NumPy Sorting and Searching

Numpy provides a variety of functions for sorting and searching. There are various sorting algorithms like quicksort, merge sort and heapsort which is implemented using the numpy.sort() function.

The kind of the sorting algorithm to be used in the sort operation must be mentioned in the function call.

Let's discuss the sorting algorithm which is implemented in numpy.sort()

The syntax to use the numpy.sort() function is given below.

It accepts the following parameters.

Consider the following example.

Example

Output:

Sorting along the columns:
[[ 2  3 10]
 [ 4  5  6]
 [ 7  8  9]]
Sorting along the rows:
[[ 4  2  3]
 [ 7  5  6]
 [10  8  9]]
Sorting data ordered by name
[(b'John', 251) (b'Mukesh', 200)]

numpy.argsort() function

This function is used to perform an indirect sort on an input array that is, it returns an array of indices of data which is used to construct the array of sorted data.

Consider the following example.

Example

Output:

Original array:
 [90 29 89 12]
Printing indices of sorted data
 [3 1 2 0]
printing sorted array
12 29 89 90 

numpy.lexsort() function

This function is used to sort the array using the sequence of keys indirectly. This function performs similarly to the numpy.argsort() which returns the array of indices of sorted data.

Consider the following example.

Example

Output:

printing indices of sorted data
[0 3 1 4 2]
using the indices to sort the array
a 12
d 12
b 90
e 211
c 380

numpy.nonzero() function

This function is used to find the location of the non-zero elements from the array.

Consider the following example.

Example

Output:

printing original array [ 12  90 380  12 211]
printing location of the non-zero elements
(array([0, 1, 2, 3, 4]),)

numpy.where() function

This function is used to return the indices of all the elements which satisfies a particular condition.

Consider the following example.

Example

Output:

(array([1, 2, 4]),)
(array([0, 1, 1]), array([1, 0, 1]))