Python Data Types

Python, a versatile and powerful programming language, offers several built-in data types to store and manipulate different kinds of information. Understanding these data types is crucial for effective Python programming.

Basic Data Types

Numbers

Python supports various numeric types:

• Integers (int): Whole numbers without decimal points.
• Floating-point numbers (float): Numbers with decimal points.
• Complex numbers: Numbers with real and imaginary parts.

Example:

integer_num = 42
float_num = 3.14
complex_num = 2 + 3j
    

Strings (str)

Strings are sequences of characters, enclosed in single or double quotes. They are immutable, meaning their content cannot be changed after creation.

Example:

greeting = "Hello, World!"
name = 'Alice'
multiline_string = """This is a
multiline string."""
    

Sequence Types

Lists

Lists are ordered, mutable sequences that can contain elements of different data types. They are defined using square brackets.

Example:

fruits = ['apple', 'banana', 'cherry']
mixed_list = [1, 'two', 3.0, [4, 5]]
    

For more information on lists, check out the Python Lists guide.

Tuples

Tuples are ordered, immutable sequences. They are similar to lists but cannot be modified after creation. Tuples are defined using parentheses.

Example:

coordinates = (10, 20)
rgb_color = (255, 0, 128)
    

Learn more about tuples in the Python Tuples guide.

Mapping Type

Dictionaries

Dictionaries are unordered collections of key-value pairs. They are mutable and defined using curly braces.

Example:

person = {
    'name': 'John',
    'age': 30,
    'city': 'New York'
}
    

Explore dictionaries further in the Python Dictionaries guide.

Set Types

Sets are unordered collections of unique elements. They are mutable and defined using curly braces or the set() function.

Example:

fruits_set = {'apple', 'banana', 'cherry'}
numbers_set = set([1, 2, 3, 3, 4])  # Duplicates are automatically removed
    

For more details on sets, refer to the Python Sets guide.

Boolean Type

The Boolean type represents truth values: True or False. Booleans are often used in conditional statements and logical operations.

Example:

is_raining = True
is_sunny = False
    

Type Conversion

Python allows conversion between different data types using built-in functions:

• int(): Converts to integer
• float(): Converts to float
• str(): Converts to string
• list(): Converts to list
• tuple(): Converts to tuple
• dict(): Converts to dictionary

For more information on type conversion, check out the Python Type Conversion guide.

Conclusion

Understanding Python's data types is fundamental to writing efficient and effective code. Each data type has its own characteristics and use cases. As you progress in your Python journey, you'll become more familiar with when and how to use each type.

Remember to choose the appropriate data type for your specific needs, considering factors like mutability, ordering, and performance. Practice working with different data types to solidify your understanding and improve your Python programming skills.