Data Structures in Python

Python has several built-in data structures that are used to store and organize data. Here is a short description of the most commonly used data structures in Python:

Mutable Data structures

Lists

Lists are a collection of items in a specific order. They are defined using square brackets [ ] and can store items of different data types. They are mutable, which means you can add, remove or change items in a list after it is created. Lists have built-in methods like append(), insert(), remove() etc to manipulate them.

Sets

Sets are a collection of unique items, meaning it does not allow duplicate items. They are defined using curly braces {} or set() constructor. Sets are mutable and have useful methods like add() , remove() , intersection() , union() etc.

Dictionaries are collections of key-value pairs. They are defined using curly braces {}. The keys in a dictionary are unique and are used to access the corresponding values. Dictionaries are mutable, which means you can add, remove or change key-value pairs after it is created. They have various methods like keys() , values() , items() , get() etc.

Immutable Data structure

Tuples

Tuples are similar to lists, but they are immutable, which means you cannot add, remove or change items in a tuple after it is created. They are defined using parentheses () and can also store items of different data types.

These are some of the basic data structures in Python and can be very powerful when used in combination with other built-in functions and control structures of Python.