A Deeper Look at Python’s Data Types

In Python, every single piece of information is an “object,” and every object belongs to a specific data type. The data type defines what properties the object has, what actions you can take with it, and how it behaves when you combine it with other values.

Let us explore Python’s built-in data types in detail using our interactive console!

Numeric

Numeric Types: `int`, `float`, `complex`

Python has three built-in numeric types to represent different kinds of numbers:

int (Integer): Represents whole numbers, both positive and negative, without any decimal points (for example: 100, -5). Python integers have unlimited size, meaning they can be as large as your computer’s memory can handle!
float (Floating-Point): Represents numbers with a decimal point. They are used for fractional or real numbers (for example: 3.14159, -0.5).
complex (Complex Number): Represents numbers with a real and an imaginary part, written in the mathematical form a + bj.

Let us see these numbers in action in the interactive editor below:

Example

Output:

Integer Value: 101, Type: <class 'int'>
Float Value: 3.14159, Type: <class 'float'>
Complex Value: (2-3j), Type: <class 'complex'>

Strings

Text Sequence Type: `str`

The string data type is used to store text (sequences of letters, numbers, and symbols).

str (String): An immutable sequence of characters. You can create strings using single quotes ('...'), double quotes ("..."), or triple quotes ("""...""" or '''...''') for text that spans multiple lines.

What does “Immutable” mean? It means once a string is created, it is locked and cannot be changed. Any action that appears to edit a string (like joining two strings together) actually creates a brand new string behind the scenes.

Run the interactive example below to see single-line and multi-line strings:

Example

Output:

Value: Hello, World!, Type: <class 'str'>
Once upon a time,
there was a brilliant developer
writing Python code.

Sequences

Sequence Types: `list`, `tuple`, `range`

Sequences represent ordered collections of items. Python has three fundamental sequence types:

list: A flexible, ordered sequence of items that you can change (mutable) at any time. You create lists by wrapping comma-separated items inside square brackets [].
tuple: An ordered sequence of items that is locked and cannot be changed (immutable) after it is created. You define tuples using parentheses ().
range: A sequence of numbers generated in order, typically used for repeating a task a specific number of times in for loops.

Let us compare lists, tuples, and ranges in our interactive console:

Example

Output:

List: [1, 'apple', True, 3.5], Type: <class 'list'>
Tuple: (1, 'apple', True, 3.5), Type: <class 'tuple'>
Range: range(0, 5), List form: [0, 1, 2, 3, 4], Type: <class 'range'>

Dictionaries

Mapping Type: `dict`

A dictionary is a fast, organized way to store data using key-value pairs.

dict (Dictionary): A mutable collection of associations, where each unique “key” maps to a specific “value”. You define dictionaries using curly braces {} and separate keys from values with a colon.

Let us see how a user profile is structured as a dictionary:

Example

Output:

Sets

Set Types: `set`, `frozenset`

Sets are unordered collections of unique items. They cannot contain any duplicate values.

set: A mutable collection of unique elements. It is incredibly useful for finding unique items, removing duplicates, and performing mathematical operations like unions and intersections.
frozenset: An immutable, frozen version of a set. Once created, you cannot add or remove any elements.

Let us see how sets handle duplicate entries automatically:

Example

Output:

Original List with duplicates: [1, 2, 2, 3, 4, 3, 5, 1]
Set with unique items only: {1, 2, 3, 4, 5}
Type: <class 'set'>
Frozenset: frozenset({1, 2, 3}), Type: <class 'frozenset'>

To create an empty set, you must use set(). If you write {}, Python will assume you are creating an empty dictionary!

Booleans

Boolean Type: `bool`

The boolean data type represents logical truth.

bool (Boolean): Can only ever hold one of two values: True or False. Booleans form the absolute foundation of all decision-making and flow control in programming.

Under the hood, Python treats True as the number 1 and False as the number 0.

Let us see how boolean expressions work in practice:

Example

Output:

Learning variable: True, Type: <class 'bool'>
Is 10 greater than 5? True
Type of comparison result: <class 'bool'>

None Type

The None Type: `NoneType`

This special data type consists of a single value: None. It is used to represent the absence of a value or a null value.

NoneType: The data type of the None object. If a function does not explicitly return a value, it returns None by default. It is often used as a placeholder for variables that you plan to assign values to later.

Let us see this interactive example:

Example

Output:

Winner value: None
Type of winner variable: <class 'NoneType'>

A Deeper Look at Python’s Data Types

Numeric

Numeric Types: int, float, complex

Example

Output:

Strings

Text Sequence Type: str

Example

Output:

Sequences

Sequence Types: list, tuple, range

Example

Output:

Dictionaries

Mapping Type: dict

Example

Output:

Sets

Set Types: set, frozenset

Example

Output:

Booleans

Boolean Type: bool

Example

Output:

None Type

The None Type: NoneType

Example

Output:

Numeric Types: `int`, `float`, `complex`

Text Sequence Type: `str`

Sequence Types: `list`, `tuple`, `range`

Mapping Type: `dict`

Set Types: `set`, `frozenset`

Boolean Type: `bool`

The None Type: `NoneType`