Python Data Types with Examples

Look at this code:

name = "Sam"
age = 20
height = 5.8
is_student = True

We just created four different values and stored them in four variables. Here:

"Sam" is text.
20 is a whole number.
5.8 is a decimal number.
True is a true or false value (Boolean).

These are different data types.

What is a Data Type?

Definition: A data type tells Python what kind of data a value is, such as text, a decimal number, or a list.

In many programming languages, you must declare a variable's data type when you create it. For example, whether it stores text, an integer, or some other type.

But in Python, you don't have to.

Python automatically determines the data type from the value you assign.

Python Built-in Data Types

Python has 14 built-in data types . To make them easier to understand, they are grouped into categories based on what they do.

Category	Data Type	Description	Level
Text	`str`	Text / strings (e.g., `"Hello"`)	Core
Numeric	`int`	Whole numbers (e.g., `10`)	Core
	`float`	Decimal numbers (e.g., `3.14`)	Core
	`complex`	Complex numbers for advanced math	Advanced
Boolean	`bool`	True or False values	Core
Sequence	`list`	Ordered, changeable collection	Core
	`tuple`	Ordered, unchangeable collection	Core
	`range`	A sequence of numbers	Core
Mapping	`dict`	Key-value pairs	Core
Set	`set`	Unordered collection of unique values	Core
Set	`frozenset`	Unchangeable version of a set	Advanced
Binary	`bytes`	Sequence of bytes	Advanced
	`bytearray`	Changeable sequence of bytes	Advanced
	`memoryview`	Memory access for bytes	Advanced
None	`NoneType`	Represents the absence of a value	Core

Note: As you can see, there are a few advanced data types (complex, frozenset, bytes, bytearray, and memoryview). If you are a beginner, you do not need to worry about these right now, focus only on the "Core" types.

Do not try to memorize this table. You will learn each of these in detail as you build more Python programs.

Why Data Types Matter

Look at these two print statements:

The first outputs 30. The second outputs Hello World. The + operator adds numbers, but it joins text together.

Now, predict the output of this code:

print("10" + "20")

If you guessed 30, you made a common beginner mistake. The output is:

Why?

Because "10" and "20" are inside quotes, Python treats them as strings, not numbers. It joins them together instead of adding them.

This is why data types matter. The data type determines what operations Python performs on a value.

Checking Data Types

To check the data type of a Python variable, use the type() function.

Dynamic Typing

You may have heard that Python is a dynamically typed language. What does that mean?

In many programming languages, a variable is like a rigid box. if you create it to hold text, it can never hold numbers. Python is different.

Look at this code:

The same variable x is first used for an integer and then used for a string.

Why does this work? In Python, variables don't have fixed data types; only the values do. Think of a variable as a sticky note or name tag. First, Python sticks the x name tag on the integer 10. Then, it moves the x name tag to the string "Sam". Because the variable is just a label pointing to data, it can point to a new data type at any time. This behavior is called dynamic typing.