Data structures in Python are essential for organizing and managing data efficiently. Python provides several built-in data structures, each serving different purposes. The most common data structures include lists, tuples, dictionaries, and sets.

Lists are versatile and can hold heterogeneous data types, such as integers, strings, and even other lists. They are defined using square brackets and allow for dynamic resizing, making them suitable for various applications ¹⁴.

Tuples are similar to lists but are immutable, meaning their contents cannot be changed after creation. They are defined using parentheses and are useful for storing fixed collections of items ⁴.

Dictionaries store data in key-value pairs, allowing for fast data retrieval based on unique keys. They are defined using curly braces and are particularly useful for associative arrays ⁴.

Sets are collections of unique elements and are useful for operations involving membership testing and eliminating duplicate entries. They are defined using curly braces or the set() function ⁵.

Understanding these data structures is crucial for effective programming in Python, as they help in organizing data and improving the efficiency of algorithms.