How to create a vector in Python using NumPy (original) (raw)

Last Updated : 28 Oct, 2021

NumPy is a general-purpose array-processing package. It provides a high-performance multidimensional array object, and tools for working with these arrays. It is the fundamental package for scientific computing with Python. Numpy is basically used for creating array of n dimensions.

Vector are built from components, which are ordinary numbers. We can think of a vector as a list of numbers, and vector algebra as operations performed on the numbers in the list. In other words vector is the numpy 1-D array.

In order to create a vector, we use np.array method.

Syntax : np.array(list)
Argument : It take 1-D list it can be 1 row and n columns or n rows and 1 column
Return : It returns vector which is numpy.ndarray

Note: We can create vector with other method as well which return 1-D numpy array for example np.arange(10), np.zeros((4, 1)) gives 1-D array, but most appropriate way is using np.array with the 1-D list.

Creating a Vector
In this example we will create a horizontal vector and a vertical vector

Python3

import numpy as np

list1 = [ 1 , 2 , 3 ]

list2 = [[ 10 ],

`` [ 20 ],

`` [ 30 ]]

vector1 = np.array(list1)

vector2 = np.array(list2)

print ( "Horizontal Vector" )

print (vector1)

print ( "----------------" )

print ( "Vertical Vector" )

print (vector2)

Output :

Horizontal Vector [1 2 3]

Vertical Vector [[10] [20] [30]]

Basic Arithmetic operation:
In this example we will see do arithmetic operations which are element-wise between two vectors of equal length to result in a new vector with the same length

Python3

import numpy as np

list1 = [ 5 , 6 , 9 ]

list2 = [ 1 , 2 , 3 ]

vector1 = np.array(list1)

print ( "First Vector : " + str (vector1))

vector2 = np.array(list2)

print ( "Second Vector : " + str (vector2))

addition = vector1 + vector2

print ( "Vector Addition : " + str (addition))

subtraction = vector1 - vector2

print ( "Vector Subtraction : " + str (subtraction))

multiplication = vector1 * vector2

print ( "Vector Multiplication : " + str (multiplication))

division = vector1 / vector2

print ( "Vector Division : " + str (division))

Output :

First Vector: [5 6 9] Second Vector: [1 2 3] Vector Addition: [ 6 8 12] Vector Subtraction: [4 4 6] Vector Multiplication: [ 5 12 27] Vector Division: [5 3 3]

Vector Dot Product
In mathematics, the dot product or scalar product is an algebraic operation that takes two equal-length sequences of numbers and returns a single number.
For this we will use dot method.

Python3

import numpy as np

list1 = [ 5 , 6 , 9 ]

list2 = [ 1 , 2 , 3 ]

vector1 = np.array(list1)

print ( "First Vector : " + str (vector1))

vector2 = np.array(list2)

print ( "Second Vector : " + str (vector2))

dot_product = vector1.dot(vector2)

print ( "Dot Product : " + str (dot_product))

Output:

First Vector : [5 6 9] Second Vector : [1 2 3] Dot Product : 44

Vector-Scalar Multiplication
Multiplying a vector by a scalar is called scalar multiplication. To perform scalar multiplication, we need to multiply the scalar by each component of the vector.

Python3

import numpy as np

list1 = [ 1 , 2 , 3 ]

vector = np.array(list1)

print ( "Vector : " + str (vector))

scalar = 2

print ( "Scalar : " + str (scalar))

scalar_mul = vector * scalar

print ( "Scalar Multiplication : " + str (scalar_mul))

Output

Vector : [1 2 3] Scalar : 2 Scalar Multiplication : [2 4 6]