The **np.roll()** function is defined under Numpy, imported as import NumPy as np. We can create multidimensional arrays and derive other mathematical statistics with the help of NumPy, which is a library in Python.

**np.roll**

The **np.roll()** is a mathematical function used for rolling array elements along a specified axis, i.e., elements of an input array is being shifted. For example, if the item is being rolled first to the last position, it is rolled back to the first position.

**Syntax**

numpy.roll(array, shift, axis=None)

**Parameters**

**array:**It is an Input array whose elements are to be rolled.**shift:**It is of int and tuple datatype. It depicts No. of times we need to shift array elements. If it is of**tuple**type, then the axis must be a tuple of the same size, and the corresponding number shifts each of the given axes. If an**int**data type is used, then the same value is used for all given axes for rolling in the input array.**axis:**It depicts the Plane, along which we wish to roll array or shift its elements.

**Return Value**

It returns an array rolled with the same size as of **input array.**

**Examples**

**Write a program to show the working of the Numpy.roll() function.**

import numpy as np # creating a sample array with arange and reshape function array = np.arange(12).reshape(3, 4) print("Original array : \n", array) # Rolling array; Shifting one place print("\nRolling with 1 shift : \n", np.roll(array, 1)) # Rolling array; Shifting four places print("\nRolling with 4 shift : \n", np.roll(array, 4)) # Rolling array; Shifting five places with 1th axis print("\nRolling with 5 shift with 1 axis : \n", np.roll(array, 2, axis=1))

**Output**

Original array : [[ 0 1 2 3] [ 4 5 6 7] [ 8 9 10 11]] Rolling with 1 shift : [[11 0 1 2] [ 3 4 5 6] [ 7 8 9 10]] Rolling with 4 shift : [[ 8 9 10 11] [ 0 1 2 3] [ 4 5 6 7]] Rolling with 5 shift with 1 axis : [[ 2 3 0 1] [ 6 7 4 5] [10 11 8 9]]

**Explanation**

In the above program, An array is created with an arange function and reshape function.

Arange function created an array with 12 elements starting from 0 to 11, and the reshape function made a matrix with 3 rows and 4 columns.

1st function is used for shifting all its elements by 1 time.

2nd function is used for shifting all its elements by 4 times.

3rd function is used for shifting all its elements by 5 times w.r.t 0 axis.

**Conclusion**

**Numpy**.**roll**(array, shift, axis = None) function **Roll** array elements along the specified axis. What happens is that elements of the input array are being shifted.

If an element is being rolled first to last-position, it is rolled back to the first position.

That’s it for np.roll() function.