Complex Data Types in Python

So far each variable has held a single value: a name, an age, a price. But data rarely comes one piece at a time. A shopping list is many items. A point on a map is latitude and longitude together. A user profile is a name, an email, and a city under one object. Making a separate variable for every value quickly becomes unworkable.

For cases like these Python has complex types: they hold many values at once under a single name. There are four of them, and they differ in how they organize the data inside.

What are complex data types?

Unlike simple data types (numbers, strings, boolean values) that store a single value, complex types can contain multiple values of various types under one name. They are similar to containers or collections where you can organize and store related data.

Python offers four main complex data types:

1. Lists (list) — ordered, mutable collections of elements
2. Tuples (tuple) — ordered, immutable collections of elements
3. Sets (set) — unordered collections of unique elements
4. Dictionaries (dict) — collections of key-value pairs

Let's look at a brief example of each type:

Python 3.13
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# List (ordered, mutable)
fruits = ["apple", "banana", "cherry"]

# Tuple (ordered, immutable)
coordinates = (10.5, 20.7, 30.9)

# Set (unordered, unique elements only)
unique_numbers = {1, 2, 3, 4, 5}

# Dictionary (key-value pairs)
person = {"name": "Alex", "age": 30, "city": "New York"}

Comparison of complex data types

Key differences between the main complex data types:

When to use different data types?

The choice of an appropriate data type depends on the task:

• List (list) — when the order of elements is important and the collection may change

  Python 3.13
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  # Daily to-do list
  todo_list = ["Buy groceries", "Walk the dog", "Write code"]

• Tuple (tuple) — when data should not change and order is important

  Python 3.13
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  # Point coordinates in 3D space
  point_3d = (10.5, 8.3, 9.1)

• Set (set) — when you only need unique elements and order doesn't matter

  Python 3.13
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  # Unique user names
  unique_users = {"alice", "bob", "charlie"}

• Dictionary (dict) — when data is organized as key-value pairs

  Python 3.13
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  # User information
  user = {"username": "alex123", "email": "alex@example.com", "active": True}

Converting between types

Python makes it easy to convert data from one complex type to another:

Python 3.13
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# Create a list
my_list = [1, 2, 3, 3, 4, 5]

# Convert list to tuple
my_tuple = tuple(my_list)  # (1, 2, 3, 3, 4, 5)

# Convert list to set (duplicates will be removed)
my_set = set(my_list)  # {1, 2, 3, 4, 5}

# Create a dictionary from a list of pairs
pairs = [("a", 1), ("b", 2), ("c", 3)]
my_dict = dict(pairs)  # {"a": 1, "b": 2, "c": 3}

Understanding Check

Let's check how well you've understood the basic complex data types:

Which data type is best suited for storing unique elements when order doesn't matter?

In the following lessons we'll explore each of these types in detail. Let's start with lists, the most flexible and frequently used complex data type.