numpy.dot() in Python (original) (raw)

Last Updated : 19 Dec, 2025

numpy.dot() is used to compute the dot product of two arrays.

For 1D arrays, it returns the scalar dot product.
For 2D arrays, it performs matrix multiplication.
For arrays with N dimensions, it performs a sum-product over the last axis of the first array and the second-to-last axis of the second array.

**Example: This example shows how numpy.dot() calculates the dot product of two 1D arrays.

Python `

import numpy as np

a = np.array([2, 3]) b = np.array([4, 5]) print(np.dot(a, b))

**Explanation: np.dot(a, b) -> 2*4 + 3*5 = 8 + 15 = 23.

Syntax

numpy.dot(a, b, out=None)

**Parameters:

**Example 1: This example demonstrates the dot product of two complex numbers using numpy.dot().

Python `

import numpy as np

a = 2 + 3j b = 4 + 5j print(np.dot(a, b))

**Explanation: **np.dot(a, b) multiplies using complex arithmetic -> 2*(4+5j) + 3j*(4+5j) -> -7 + 22j.

**Example 2: This example shows matrix multiplication using numpy.dot() on two 2D arrays.

Python `

import numpy as np

a = np.array([[1, 4], [5, 6]])

b = np.array([[2, 4], [5, 2]])

print(np.dot(a, b))

**Explanation: np.dot(a, b) performs matrix multiplication

**Example 3: This example uses numpy.dot() with a 2D array and a 1D array to produce a vector.

Python `

import numpy as np

a = np.array([[3, 5], [1, 2], [4, 1]])

b = np.array([2, 3])

print(np.dot(a, b))

**Explanation: Each row of a is dotted with vector b