Numpy Array advantage over a Nested List

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


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)


Array = [ 5 10 15 20 25]

Create a Matrix with Numpy


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)


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.


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])


Number of rows =  3
Number of columns =  3

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

The above example displays nested list −