Python Data Types

A comprehensive guide to the built-in data types in Python, categorized by their behavior and characteristics.

🔢

Numeric Types

Used to represent numbers. Python automatically handles memory allocation for large numbers.

int: Whole numbers, positive or negative, without decimals. x = 42
float: Numbers containing one or more decimals, or exponential notation. y = 3.14
complex: Written with a "j" as the imaginary part. z = 3 + 5j

🧵

Ordered collections of items where elements can be accessed via indexing.

str: Textual data enclosed in single or double quotes. Immutable. name = "Alice"
list: Ordered, mutable collections that allow duplicate members. items = [1, "apple", 3.4]
tuple: Ordered, immutable collections that allow duplicate members. point = (10, 20)

🗺️

Unordered collections of key-value pairs. Keys must be unique and immutable.

dict: Stores data as associated pairs for fast lookups. Mutable. user = {"id": 1, "role": "admin"}

🧺

Collections of unique, unordered items. Ideal for membership testing and eliminating duplicates.

set: Unordered, mutable collection of unique items. unique_ids = {1, 2, 3}
frozenset: Immutable version of a set; cannot be modified after creation. fs = frozenset([1, 2])

⚖️

Represents logical values used primarily in conditional statements and expressions.

bool: Can only hold one of two values: True or False. Evaluates logical conditions.