In Python, a data type is a classification that specifies which type of value a variable can hold. It defines the operations that can be performed on the data and the way the data is stored in memory. Python is a dynamically-typed language, which means that the data type of a variable is interpreted at runtime based on the type of value it holds.

Here are some common data types in Python:

1. Numeric Types:

   • int: Integer type, e.g., 1, -5, 100.
   • float: Floating-point type, e.g., 3.14, -0.5, 2.0.

2. Sequence Types:

   • str: String type, e.g., "hello", 'world'.
   • list: List type, e.g., [1, 2, 3], ['apple', 'banana'].

3. Boolean Type:

   • bool: Boolean type, either True or False.

4. Set Types:

   • set: Unordered collection of unique elements, e.g., {1, 2, 3}.

5. Mapping Type:

   • dict: Dictionary type, e.g., {'key': 'value', 'name': 'John'}.

6. None Type:

   • NoneType: Represents the absence of a value or a null value.

7. Other Types:

   • complex: Complex number type, e.g., 2 + 3j.
   • bytes: Immutable sequence of bytes, e.g., b'hello'.

Python is designed to be flexible with types, and variables can change their types dynamically during execution. For example, a variable initially assigned an integer value can later be assigned a string or any other type of value.

x = 5         # x is of type int
x = "hello"   # x is now of type str

Understanding and using appropriate data types is crucial for writing efficient and bug-free Python code.

Thank you.