## How to calculate dot product of two vectors in Python?

In mathematics, the **dot product** or also known as the **scalar product** is an algebraic operation that takes two equal-length sequences of numbers and returns a single number. Let us given two vectors **A** and **B, **and we have to find the dot product of two vectors.

Given that,

and,

Where,

i:the unit vector along the x directions

j:the unit vector along the y directions

k:the unit vector along the z directions

Then the dot product is calculated as:

**Example:**

Given two vectors A and B as,

## Dot Product of Two Vectors in Python

Python provides a very efficient method to calculate the dot product of two vectors. By using **numpy.dot()** method which is available in the NumPy module one can do so.

Syntax:numpy.dot(vector_a, vector_b, out = None)

Parameters:

vector_a:[array_like] if a is complex its complex conjugate is used for the calculation of the dot product.

vector_b:[array_like] if b is complex its complex conjugate is used for the calculation of the dot product.

out:[array, optional] output argument must be C-contiguous, and its dtype must be the dtype that would be returned for dot(a,b).

Return:Dot Product of vectors a and b. if vector_a and vector_b are 1D, then scalar is returned

**Example 1:**

- Python

`# Python Program illustrating` `# dot product of two vectors` `# Importing numpy module` `import` `numpy as np` `# Taking two scalar values` `a ` `=` `5` `b ` `=` `7` `# Calculating dot product using dot()` `print` `(np.dot(a, b))` |

**Output:**

35

**Example 2:**

- Python

`# Python Program illustrating` `# dot product of two vectors` `# Importing numpy module` `import` `numpy as np` `# Taking two 1D array` `a ` `=` `3` `+` `1j` `b ` `=` `7` `+` `6j` `# Calculating dot product using dot()` `print` `(np.dot(a, b))` |

**Output:**

(15+25j)

**Example 3:**

- Python

`# Python Program illustrating` `# dot product of two vectors` `# Importing numpy module` `import` `numpy as np` `# Taking two 2D array` `# For 2-D arrays it is the matrix product` `a ` `=` `[[` `2` `, ` `1` `], [` `0` `, ` `3` `]]` `b ` `=` `[[` `1` `, ` `1` `], [` `3` `, ` `2` `]]` `# Calculating dot product using dot()` `print` `(np.dot(a, b))` |

**Output:**

[[5 4] [9 6]]

**Example 4:**

- Python

`# Python Program illustrating` `# dot product of two vectors` `# Importing numpy module` `import` `numpy as np` `# Taking two 2D array` `# For 2-D arrays it is the matrix product` `a ` `=` `[[` `2` `, ` `1` `], [` `0` `, ` `3` `]]` `b ` `=` `[[` `1` `, ` `1` `], [` `3` `, ` `2` `]]` `# Calculating dot product using dot()` `# Note that here I have taken dot(b, a)` `# Instead of dot(a, b) and we are going to` `# get a different output for the same vector value` `print` `(np.dot(b, a))` |

**Output:**

[[2 4] [6 9]]