Data Structures

Data Structures in Python

Python offers several built-in data structures that are essential for organizing and manipulating data efficiently. Here’s a brief overview of the main data structures in Python:

Lists

Lists are ordered, mutable sequences of elements. They are created using square brackets and can contain items of different data types.

Example:

fruits = ['apple', 'banana', 'cherry']

Dictionaries

Dictionaries are unordered collections of key-value pairs. They are created using curly braces and allow fast lookups based on unique keys.

Example:

person = {'name': 'John', 'age': 30, 'city': 'New York'}

Sets

Sets are unordered collections of unique elements. They are created using curly braces or the set() function and are useful for removing duplicates and performing set operations.

Example:

unique_numbers = {1, 2, 3, 4, 5}

Tuples

Tuples are ordered, immutable sequences of elements. They are created using parentheses and are often used for grouping related data.

Example:

coordinates = (10, 20)

Each of these data structures has its own strengths and use cases, allowing Python developers to choose the most appropriate one for their specific needs.