Python supports a wide range of data types that classify what variables and objects can hold. Understanding these types is crucial for effective programming.
1. Numeric Types
- Integers (
int): Whole numbers without decimals (e.g., -3, 0, 204) - Floating Point Numbers (
float): Numbers with decimal points (e.g., -3.14, 0.0, 2.718) - Complex Numbers (
complex): Numbers with real and imaginary parts (e.g., 3 + 5j)
2. Sequence Types
- Strings (
str): A sequence of Unicode characters that are immutable - Lists (
list): Ordered collections of items that can be of mixed types and are mutable - Tuples (
tuple): Similar to lists but immutable once created
3. Mapping Type
- Dictionaries (
dict): Collections of key-value pairs that are mutable
4. Set Types
- Sets (
set): Unordered collections of unique elements useful for mathematical operations - Frozen Sets (
frozenset): Immutable versions of sets
5. Boolean Type (bool)
Represents two values: True or False, typically resulting from comparisons or conditions.
6. None Type (NoneType)
A special type representing the absence of a value or a null value denoted by the keyword None.
Key Takeaway
Python’s dynamic type system means you don’t have to declare the type of a variable when you create one. The interpreter automatically detects the data type based on the assigned value.