NumPy mod() Function

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The NumPy mod() function is used to return the element-wise remainder of division. It performs modulo operation on each pair of elements from the input arrays.

It calculates the remainder after dividing each element in the first array by the corresponding element in the second array (or by a scalar). This function handles broadcasting for arrays of different shapes.

Syntax

Following is the syntax of the NumPy mod() function −

numpy.mod(x1, x2, /, out=None, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])

Parameters

This function accepts the following parameters −

• x1: The dividend input array. It is the array whose elements will be divided by the elements of x2.
• x2: The divisor input array. Like x1, it should have the same shape as x1, or be broadcastable to a common shape.
• out (optional): A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned.
• where (optional): This condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Otherwise, it will retain its original value.
• casting (optional): Controls what kind of data casting may occur. Defaults to 'same_kind'.
• order (optional): Controls the memory layout order of the result. 'C' means C-order, 'F' means Fortran-order, 'A' means 'F' if inputs are all F, 'C' otherwise, 'K' means match the layout of the inputs as closely as possible.
• dtype (optional): The type of the returned array and of the accumulator in which the division is performed. The dtype of x1 and x2 is used by default unless dtype is specified.
• subok (optional): If True, then sub-classes will be passed-through, otherwise the returned array will be forced to be a base-class array.

Return Value

This function returns the element-wise remainder of the division of x1 by x2. If out is provided, it returns a reference to out.

Example: Basic Usage of mod() Function

In the following example, we create two 1-dimensional arrays and use the mod() function to perform element-wise modulo operation −

import numpy as np

# Creating two 1-dimensional arrays
arr1 = np.array([5, 9, 11, 14])
arr2 = np.array([3, 4, 5, 6])

# Performing element-wise modulo
result = np.mod(arr1, arr2)
print(result)

Following is the output obtained −

[2 1 1 2] 

Example: Modulo with Broadcasting

In this example, we demonstrate the use of broadcasting with the mod() function. We create a 2-dimensional array and calculate the remainder when it is divided by a 1-dimensional array −

import numpy as np

# Creating a 2-dimensional array
arr1 = np.array([[5, 9, 11], [14, 21, 29]])

# Creating a 1-dimensional array
arr2 = np.array([3, 4, 5])

# Performing element-wise modulo with broadcasting
result = np.mod(arr1, arr2)
print(result)

This will produce the following result −

[[2 1 1]
 [2 1 4]]

Example: Modulo with Scalar

In this example, we raise all elements of an array and calculate their modulo with a scalar value −

import numpy as np

# Creating a 1-dimensional array
arr = np.array([5, 9, 11, 14])

# Performing modulo with a scalar value 3
result = np.mod(arr, 3)
print(result)

Following is the output of the above code −

[2 0 2 2]

Example: Modulo with Negative Values

In this example, we calculate the modulo of negative numbers −

import numpy as np

# Creating a 1-dimensional array with negative values
arr = np.array([-5, -9, -11, -14])

# Performing modulo with a scalar value 3
result = np.mod(arr, 3)
print(result)

The output obtained is as shown below −

[ 1 0 1 1]