Numpy.prod() in Python

Last Updated : 5 Jun, 2026

numpy.prod() is used to calculate the product of array elements. It can multiply all elements of an array or multiply elements along a specific axis in multi-dimensional arrays. It is commonly used in numerical computing when we need the multiplication result of multiple values stored in a NumPy array.

Example: This example multiplies all elements of a NumPy array using np.prod().

Python 
import numpy as np
arr = [1, 2, 3, 4]
res = np.prod(arr)
print(res)

Output
24

Explanation: np.prod(arr) multiplies all elements of arr: 1 × 2 × 3 × 4 = 24.

Syntax

numpy.prod(a, axis=None, dtype=None, out=None, keepdims=False)

Parameters:

  • a: Input array whose elements are multiplied.
  • axis: Axis along which the product is calculated. By default, product of all elements is returned.
  • dtype: Data type of the returned result.
  • out: Alternative output array to store the result.
  • keepdims: If True, reduced axes are kept as dimensions with size 1.

Examples

Example 1: This example finds the product of all elements in a 1D array using np.prod().

Python 
import numpy as np
arr = np.array([2, 3, 4])
res = np.prod(arr)
print(res)

Output
24

Explanation: np.prod(arr) multiplies all array elements: 2 × 3 × 4 = 24.

Example 2: This example calculates the product of elements row-wise in a 2D array using axis=1.

Python 
import numpy as np
arr = np.array([[1, 2], [3, 4]])
res = np.prod(arr, axis=1)
print(res)

Output
[ 2 12]

Explanation: axis=1 calculates the product across each row:

  • First row: 1 × 2 = 2
  • Second row: 3 × 4 = 12

Example 3: This example shows the result when np.prod() is applied to an empty array.

Python 
import numpy as np
arr = []
res = np.prod(arr)
print(res)

Output
1.0

Explanation: For an empty array, np.prod() returns 1.0, which is the neutral value for multiplication.

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