Python supports various data types that allow you to work with different kinds of values in your programs. Here's an overview of the different data types in Python:

• Integers:

Integers are whole numbers, both positive and negative, without decimal points.

Example:

-5, 0, 42

• Floats:

Floats represent real numbers with decimal points. They can also be in scientific notation.

Example:

-3.14, 0.0, 1.25e5

• Strings:

Strings are sequences of characters enclosed within single ('') or double ("") quotes. They are used to represent text.

Example:

"Hello, World!", 'Python', "123"

• Booleans:

Booleans represent truth values: True or False. They are often used for logical comparisons and branching.

Example:

True

• Lists:

Lists are ordered collections of items, which can be of different data types. They are mutable, meaning you can change their contents after creation.

Example:

[1, 2, 'apple', True]

• Tuples:

Tuples are similar to lists but are immutable, meaning their contents cannot be changed after creation. They are often used when you want to group related values together.

Example:

(3.14, 'pie')

• Dictionaries:

Dictionaries store key-value pairs, allowing you to associate values with unique keys. They are unordered and mutable.

Example:

{'name': 'Alice', 'age': 25}

• Sets:

Sets are unordered collections of unique elements. They are useful for operations like finding intersections and differences between collections.

Example:

{1, 2, 3}

Understanding and utilizing these different data types is essential for effective Python programming. They enable you to manipulate and process various types of data in your applications.