How to create a vector in Python using NumPy
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)
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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))
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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]
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