Basic data types

In Python, data types define the kind of information you can store and work with. Different tasks require different types of data, such as text, numbers, or simple yes-or-no values.

This lesson introduces Python’s most common basic data types and their uses.

Common data types

1. Strings str

A string is a sequence of characters used to represent text. Strings are created by enclosing text in either single ' or double " quotes.

Examples:

name = "Alice"  
greeting = 'Hello, world!'  

Usage: Strings are ideal for handling any text-based data, such as names, messages, or sentences.

2. Integers int

An integer is a whole number—positive, negative, or zero—without a decimal point. Python automatically recognizes integers when you assign them.

Examples:

age = 25  
score = -10  

Usage: Integers are used for counts, ages, IDs, or any data that does not require fractions or decimals.

3. Floats float

A float is a number that includes a decimal point. These are useful for representing values that require precision, such as measurements or financial data.

Examples:

price = 19.99  
pi = 3.14159  

Usage: Floats are used for weights, temperatures, prices, or any calculations that involve non-integer values.

4. Booleans bool

A Boolean represents one of two possible values: True or False. Booleans are commonly used in decision-making and control flow.

Examples:

is_student = True  
is_admin = False  

Usage: Booleans are used to check conditions, control program flow, and represent simple yes-or-no states, like whether a user is logged in or a switch is turned on.

Example code

Here’s how these data types look and function in Python:

# String
name = "Alice"  
print(name)  # Output: Alice  

# Integer
age = 30  
print(age)  # Output: 30  

# Float
height = 5.9  
print(height)  # Output: 5.9  

# Boolean
is_member = True  
print(is_member)  # Output: True  

Checking a data type

Python provides the type() function to check the data type of a value. This is especially helpful when debugging or working with dynamic data.

print(type(name))      # Output:   
print(type(age))       # Output:   
print(type(height))    # Output:   
print(type(is_member)) # Output:   

Summary of data types

Type	Example	Description	Common Uses
String	"Alice"	Text-based data, enclosed in quotes	Names, messages, or sentences
Integer	25, -10	Whole numbers, positive or negative	Counts, ages, or IDs
Float	19.99, 3.14159	Numbers with a decimal point	Measurements, prices, or scientific data
Boolean	True, False	Logical values representing yes/no conditions	Conditions, control flow, or flags

Why are data types important?

Data types help Python understand how to store and manipulate your information. For example:

• Text needs different operations than numbers (e.g., concatenation vs. addition).
• Floats enable precision in calculations that integers can’t handle.
• Booleans simplify decision-making in your programs.

Conclusion

Understanding these basic data types is essential to writing effective Python code. By choosing the right data type for your needs, you make your programs more efficient and easier to maintain.

Start experimenting with strings, integers, floats, and booleans to see how they work in practice!