Numpy Array advantage over a Nested List

2023-01-20 13:26:41 人气: 20

In this article, we will learn about the advantages of a Numpy array with a Nested List in Python. The Numpy array definitely has advantages over a Nested. Let’s see the reasons − The array in Numpy executes faster than a Nested List. A Nested...

In this article, we will learn about the advantages of a Numpy array with a Nested List in Python. The Numpy array definitely has advantages over a Nested. Let’s see the reasons −

The array in Numpy executes faster than a Nested List.
A Nested List consumes more memory than a Nested List.

Numpy Array

NumPy is an N-dimensional array type called ndarray. It describes the collection of items of the same type. Items in the collection can be accessed using a zero-based index.

Every item in an ndarray takes the same size of block in the memory. Each element in ndarray is an object of data-type object

Create a Numpy Array

Example

The basic Numpy Array is created using an array() function in NumPy:

import numpy as np # Create a Numpy Array arr = np.array([5, 10, 15, 20, 25]) print("Array = ",arr)

Output

Array = [ 5 10 15 20 25]

Create a Matrix with Numpy

Output

In this example, we will create a matrix using the numpy library −

import numpy as np # Create a Numpy Matrix 2x3 a = np.array([[5, 10, 15], [20, 25, 30]]) # Display the array with more than one dimension print("Array = ",a)

Output

Array =
[[ 5 10 15]
[20 25 30]]

Nested Lists

A nested list as the name suggests is a list of lists. They can be used to create a matrix as well.

Create a Matrix with Nested Lists

With Nested Lists, you can easily create a matrix in Python. In a Nested List.

Every element of the nested list i.e., a matrix has rows and columns.
Number of elements in the nested lists = The number of rows of the matrix.
Length of the lists inside the nested list = number of columns.

Example

Let us see an example −

# create a matrix 3x3 mat = [[5, 10, 15], [50, 100, 150], [100, 150, 200]] # number of rows rows = len(mat) print("Number of rows = ", rows) # number of columns = length of sublist cols = len(mat[0]) print("Number of columns = ", cols) # Display the matrix (nested list) print("\nMatrix = ") for i in range(0, rows): print(mat[i])

Output

Number of rows =  3
Number of columns =  3

Matrix = 
[5, 10, 15]
[50, 100, 150]
[100, 150, 200]

The above example displays nested list −

Numpy Array advantage over a Nested List

Numpy Array

Create a Numpy Array

Example

Output

Create a Matrix with Numpy

Output

Output

Nested Lists

Create a Matrix with Nested Lists

Example

Output

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