Python Data Types

Not all values are the same kind of thing. A name is text, a price is a number, and "is this user logged in?" is a yes-or-no answer. Python data types tell Python what kind of value it's working with, which decides what you can do with it. In this lesson, you'll get a friendly tour of every built-in type, learn how to check a value's type, and see which types can be changed after they're created.

What is a data type?

A data type is a category of values that share the same behavior. You can add two numbers, but you can't add a number to a word. You can make text uppercase, but you can't make a number uppercase. The type decides which actions make sense.

In Python, you never declare a type yourself. Python looks at the value and works it out, as you saw in Python variables.

city = "Toronto"   # Python knows this is text
year = 2026        # and this is a whole number
print(type(city))
print(type(year))

<class 'str'>
<class 'int'>

What are the built-in data types in Python?

Python's built-in types fall into a handful of groups. Here's the big picture before we look at each one briefly.

Simple types: text, numbers, booleans and None

These types hold a single value each.

Text: str

A string (str) is text inside quotes. Single or double quotes both work.

song = "Bohemian Rhapsody"
artist = 'Queen'
print(song, "by", artist)

Bohemian Rhapsody by Queen

Numbers: int, float and complex

An int (integer) is a whole number, positive or negative. A float is a number with a decimal point. A complex number has a real and an imaginary part, written with a j; you'll only need it for science and engineering math.

followers = 1500
temperature = -3.5
signal = 2 + 3j
print(type(followers), type(temperature), type(signal))

<class 'int'> <class 'float'> <class 'complex'>

Numbers get a full lesson of their own in Python numbers.

True or False: bool

A boolean (bool) has only two possible values: True and False. Booleans answer yes-or-no questions, and they power every decision your program makes.

is_open = True
has_stock = False
print(is_open, has_stock)

True False

More on these in Python booleans.

No value: None

None is a special value meaning "nothing here" or "not set yet". It's the only value of the type NoneType. Think of an empty "middle name" field on a form.

middle_name = None
print(middle_name)
print(type(middle_name))

None
<class 'NoneType'>

Collections: list, tuple, range, dict, set

Collections hold many values in one variable. Each kind has a different job:

playlist = ["Intro", "Sunrise", "Encore"]      # list: ordered, changeable
location = (51.5, -0.12)                        # tuple: ordered, fixed
countdown = range(5)                            # range: the numbers 0 to 4
menu = {"latte": 4.5, "muffin": 3.25}           # dict: key -> value
lucky_numbers = {7, 3, 7, 1}                    # set: duplicates removed

print(playlist)
print(location)
print(list(countdown))
print(menu["latte"])
print(lucky_numbers)

['Intro', 'Sunrise', 'Encore']
(51.5, -0.12)
[0, 1, 2, 3, 4]
4.5
{1, 3, 7}

• list: an ordered collection you can add to, remove from and change, like a streaming playlist.
• tuple: like a list, but fixed once created. Good for values that belong together, like map coordinates.
• range: a memory-friendly sequence of numbers, mostly used in loops.
• dict (dictionary): stores key-value pairs, so you look things up by name, like prices on a menu.
• set: unique items with no guaranteed order. Duplicates disappear automatically. A frozenset is a set that can't be changed.

Binary: bytes

bytes hold raw data as numbers from 0 to 255. You'll meet them when reading images, sending data over a network, or encoding text. A bytes value is written with a b before the quotes:

data = "café".encode()
print(data)
print(type(data))

b'caf\xc3\xa9'
<class 'bytes'>

As a beginner you can safely set bytes aside for now. (Python also has bytearray and memoryview for binary data, but they're rarely needed early on.)

How do you check the data type of a variable?

Use type() to ask "what type is this?" and isinstance() to ask "is this a certain type?" The second one returns True or False.

age = 30

print(type(age))
print(isinstance(age, int))
print(isinstance(age, str))
print(isinstance(age, (int, float)))   # is it either one?

<class 'int'>
True
False
True

What is the difference between mutable and immutable types?

A mutable value can be changed after it's created. An immutable value can't; to "change" it, you create a new value.

cart = ["apples", "bread"]
cart.append("milk")       # changes the same list
print(cart)

name = "sam"
name.upper()              # makes a NEW string, original untouched
print(name)

name = name.upper()       # store the new string
print(name)

['apples', 'bread', 'milk']
sam
SAM

Try to change a single letter of a string and Python refuses:

name = "sam"
name[0] = "S"

TypeError: 'str' object does not support item assignment

Real-world example: a user profile

name = "Jordan Lee"
age = 34
height_m = 1.78
is_premium = True
favorite_genres = ["jazz", "lo-fi", "indie"]
settings = {"theme": "dark", "autoplay": False}

print(name, "is", age, "and likes", favorite_genres[0])
print("Premium:", is_premium, "| Theme:", settings["theme"])

Jordan Lee is 34 and likes jazz
Premium: True | Theme: dark

How do you set a specific data type?

Each type has a constructor, a function with the same name as the type, that creates a value of that type. This is handy when you need to turn one type into another:

quantity = int("25")
price = float(7)
label = str(3.5)
letters = list("abc")
unique = set([1, 1, 2])
point = tuple([4, 5])
profile = dict(name="Ava", age=29)

print(quantity, price, label)
print(letters, unique, point)
print(profile)

25 7.0 3.5
['a', 'b', 'c'] {1, 2} (4, 5)
{'name': 'Ava', 'age': 29}

Converting between types has a few surprises, which you'll learn in Python type conversion.

Common mistakes with data types

1. Mixing text and numbers

print("Score: " + 10)

TypeError: can only concatenate str (not "int") to str

Convert the number first: "Score: " + str(10), or use a comma inside print().

2. Thinking a number in quotes is a number

print("5" + "3")

53

"5" is a string, so + joins the text instead of adding.

3. Comparing a type to a string

print(type(5) == "int")
print(type(5) == int)

False
True

Compare against the type itself (int), not the word "int". Better still, use isinstance().

4. Converting text that isn't a whole number

print(int("3.5"))

ValueError: invalid literal for int() with base 10: '3.5'

Practice exercise

title = "Running Shoes"
price = 89.99
stock = 12
on_sale = False
sizes = [8, 9, 10]

print(type(title))
print(type(price))
print(type(stock))
print(type(on_sale))
print(type(sizes))

<class 'str'>
<class 'float'>
<class 'int'>
<class 'bool'>
<class 'list'>

What's next?

You've met every built-in type. Now it's time to go deeper into the ones you'll use most, starting with Python numbers.