Python list vs array – when to use смотреть онлайн

Download this blogpost from https://codegive.com
in python, both lists and arrays are used to store collections of elements. however, they have different characteristics and use cases. understanding when to use a python list or a numpy array is important for efficient and effective programming. this tutorial will explain the differences between lists and arrays and provide code examples to illustrate their use cases.
a python list is a built-in data structure that can hold elements of different data types. lists are versatile and easy to work with, making them suitable for various tasks. here are some key characteristics of python lists:
dynamic sizing: lists can grow or shrink in size dynamically. you can append or remove elements without specifying the size beforehand.
mixed data types: lists can contain elements of different data types, such as integers, strings, or even other lists.
slower for numerical operations: lists are not optimized for numerical operations like arithmetic or matrix operations. performing mathematical operations on lists can be slower compared to arrays.
standard library: lists are part of python's standard library, so you don't need to import any external modules to use them.
numpy is a powerful library for numerical and scientific computing in python. numpy arrays, also known as ndarrays, are the primary data structure for numerical operations. here are some key characteristics of numpy arrays:
fixed size: numpy arrays have a fixed size when created. you need to specify the shape and data type when creating an array.
homogeneous data types: numpy arrays store elements of the same data type, which allows for efficient numerical operations.
fast numerical operations: numpy provides optimized functions for numerical operations like addition, multiplication, and matrix operations. these operations are significantly faster than equivalent operations on lists.
requires numpy: you need to import the numpy library (import numpy as np) to work with numpy arrays.
use lists when:
use numpy arrays ...