Moving on, we’ll discuss lambda functions and how they can be used with map, filter, and reduce functions to perform complex operations on data structures. We’ll also learn about frozen sets and how to check if a set is a superset of another. Next, we’ll look at some set operations such as checking for existence, intersection, union, difference, and symmetric difference. We’ll also have a look how to get the length of each data structure and iterate over them to perform various operations. We’ll take a closer look at the key differences and we’ll also explore lambda, map, filter and reduce functions.įirst, we’ll go over how to create these data structures and how to add, edit, and delete items in them. While these data structures may seem similar at first glance, they each have their unique properties and use cases. Some examples of these are lists, sets, tuples, and dictionaries. Ideal for mappings or storing data in a way that makes it easily retrievable by its name or identifier.Python has different ways to store a group of information, which are called data structures. Use Cases: When you need to associate keys with values, like looking up values by some identifier.

Values can be of any type and can be changed.

Keys must be unique and immutable (e.g., strings, numbers, or tuples).

Key-value pairs allow direct access to values by keys.

Syntax: Created with curly braces with key-value pairs separated by colons. They are mutable and do not allow duplicate elements. Mrcoder 👉 Set: The Unique Element Collectorĭefinition: Sets are unordered collections of unique elements. Use Cases: When you need an ordered collection of items that should not change through the course of the program.

Cannot be modified after creation (immutable).Reversing Elements list1 = Ĭounting Elements list1 = ĭefinition: Tuples are similar to lists but are immutable, meaning once a tuple is created, its elements cannot be changed. Use Cases: When you need an ordered collection of items that may need to be modified, or when you want to store a sequence of items. Elements can be added, removed, or changed.Index-based: You can access elements by their position in the list.They are mutable, meaning their elements can be changed after the list is created. Let us know more about Lists, Tuples, Sets and Dictionaries in following topics: 👉 List: The Versatile Collectionĭefinition: Lists are ordered collections of items that can be of different types. Dictionary: Collection of key-value pairs.Dictionary: Unique keys, values can be duplicated.Dictionary: As of Python 3.7+, insertion order is preserved.Dictionary: Mutable keys are immutable, but values can change.Set: Mutable, but elements must be immutable.The article was originally published at mrcoder701 blog Key Difference Between List, Tuple, Set, and Dictionary in Python 👉 Mutability: So, buckle up as we delve into the nuances of these structures, complete with examples to illuminate your path through Python’s data jungle. Each serves a unique purpose, and understanding their differences is crucial for any aspiring Pythonista.

At the heart of Python’s simplicity lies its core data structures: lists, tuples, sets, and dictionaries. Python, the ever-popular programming language, is beloved for its simplicity and readability, making it a go-to for beginners and seasoned developers alike.

Are dictionaries mutable