data types

In Python, data types define the type of values that can be assigned to variables or used as function arguments. Here are some commonly used data types in Python:

1. Numeric Types:
   • int: Represents integers, e.g., x = 10.
   • float: Represents floating-point numbers, e.g., y = 3.14.
   • complex: Represents complex numbers, e.g., z = 2 + 3j.
2. Text Type:
   • str: Represents strings of characters, e.g., name = "John".
3. Boolean Type:
   • bool: Represents boolean values, either True or False. Used for logical operations and control flow.
4. Sequence Types:
   • list: Represents an ordered collection of items, enclosed in square brackets, e.g., numbers = [1, 2, 3].
   • tuple: Represents an ordered, immutable collection of items, enclosed in parentheses, e.g., point = (x, y).
5. Mapping Type:
   • dict: Represents key-value pairs enclosed in curly braces, e.g., person = {"name": "John", "age": 25}.
6. Set Types:
   • set: Represents an unordered collection of unique items, enclosed in curly braces, e.g., fruits = {"apple", "banana", "orange"}.
   • frozenset: Represents an immutable set, similar to set but cannot be modified once created.
7. None Type:
   • None: Represents the absence of a value or a null value, used to indicate no value or uninitialized variables.

These are some of the fundamental data types in Python. Each data type has specific properties, methods, and behaviors associated with it, enabling various operations and manipulations. It’s important to understand these data types as they form the building blocks for working with data and solving problems in Python.