What Are the Simplest Data Structure in Python?


Angela Bailey

Python provides a wide range of data structures that can be used to store and manipulate data efficiently. In this article, we will explore some of the simplest data structures in Python and understand their basic functionalities.


The simplest and most commonly used data structure in Python is a list. A list is an ordered collection of items, where each item can be of any type. It allows us to store multiple values in a single variable.

To create a list, we use square brackets [] and separate the items with commas. For example:

my_list = [1, 2, 3, 'apple', 'banana', 'cherry']

We can access individual elements in the list using their index. The indexing starts from 0 for the first element. For example:

print(my_list[0])  # Output: 1
print(my_list[3])  # Output: 'apple'

Lists are mutable, which means we can modify them by assigning new values to specific indexes or using various built-in methods like append(), remove(), and sort(). We can also use slicing to extract specific portions of a list.


A tuple is similar to a list but is immutable, meaning its elements cannot be changed once defined. Tuples are created using parentheses () instead of square brackets [].

my_tuple = (1, 2, 'apple', 'banana')

We can access tuple elements using indexing just like lists.

print(my_tuple[0])  # Output: 1
print(my_tuple[2])  # Output: 'apple'

Since tuples are immutable, we cannot modify them directly. However, we can perform operations like concatenation and slicing to create new tuples.


A set is an unordered collection of unique elements. It is defined using curly braces {} or the set() function.

my_set = {1, 2, 'apple', 'banana'}

Unlike lists and tuples, sets do not support indexing or slicing because they are unordered. However, they provide various methods to perform common set operations like union(), intersection(), and difference(). Sets are useful when dealing with distinct elements or eliminating duplicates from a list.


A dictionary is a collection of key-value pairs. Each value in a dictionary is associated with a unique key. Dictionaries are defined using curly braces {} and colons : to separate keys and values.

my_dict = {'name': 'John', 'age': 25, 'city': 'New York'}

We can access values in a dictionary using their keys instead of indexes.

print(my_dict['name'])  # Output: 'John'
print(my_dict['age'])   # Output: 25

Dictionaries are mutable, meaning we can add new key-value pairs, modify existing values, or delete items using built-in methods like update(), pop(), and del(). They are widely used for mapping one value to another efficiently.

In Conclusion

In this article, we explored some of the simplest data structures in Python – lists, tuples, sets, and dictionaries. Each data structure has its own characteristics and use cases.

Lists are ordered and mutable, tuples are ordered but immutable, sets are unordered and unique, and dictionaries are unordered but provide key-value mapping. Understanding these data structures is crucial for efficient data manipulation in Python.

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