Python supports several built-in data types that you can use to store and manipulate different kinds of data. Here are some of the most common data types in Python:
Numeric Types:
int: Integer data type for whole numbers (e.g., -5, 0, 42).
float: Floating-point data type for decimal numbers with floating-point representation (e.g., 3.14, -0.5).
Text Type:
- str: String data type for sequences of characters, enclosed in single or double quotes (e.g., "Hello, World!").
Boolean Type:
- bool: Boolean data type representing True or False values.
Sequence Types:
list: An ordered collection of items, mutable (modifiable) using indexing and slicing.
tuple: An ordered collection of items, immutable (cannot be modified after creation).
range: Represents a sequence of numbers, often used for looping.
Mapping Type:
- dict: Dictionary data type for key-value pairs, where keys are unique and used to access corresponding values.
Set Types:
set: Unordered collection of unique items (no duplicates).
frozenset: Similar to a set, but immutable.
Binary Types:
bytes: Immutable sequence of bytes (often used to handle binary data).
bytearray: Mutable sequence of bytes.
None Type:
- NoneType: Represents the absence of a value (similar to null in other languages).
Python is dynamically typed, which means you don't need to declare the data type explicitly; the interpreter infers the data type based on the value assigned to a variable. For example:
x = 5 # int
name = "Alice" # str
pi = 3.14 # float
is_active = True # bool
You can use the type() function to determine the data type of a variable:
print(type(x)) # Output: <class 'int'>
print(type(name)) # Output: <class 'str'>
print(type(pi)) # Output: <class 'float'>
print(type(is_active)) # Output: <class 'bool'>
Understanding these data types is crucial for effective programming in Python, as it influences how you manipulate and process your data. Each data type has its own set of operations and methods that you can use to work with the data effectively.