What Is Tuple in Data Structure?


Scott Campbell

A tuple is a data structure in Python that is used to store an ordered sequence of elements. It is similar to a list, but unlike lists, tuples are immutable, meaning they cannot be modified once created. In this article, we will explore the concept of tuples and their usage in data structures.

Creating a Tuple

To create a tuple in Python, we enclose the elements within parentheses. Let’s take an example:

my_tuple = (1, 2, 3, 'a', 'b', 'c')

In the above example, we have created a tuple named my_tuple which contains integers and strings.

Accessing Elements in a Tuple

Similar to lists, we can access individual elements in a tuple using indexing. The index starts from 0 for the first element. Let’s see an example:


This will output 1, as it is the first element of the tuple.

Tuple Operations


We can concatenate two or more tuples using the ‘+’ operator. Let’s see an example:

tuple1 = (1, 2)
tuple2 = ('a', 'b')
concatenated_tuple = tuple1 + tuple2

The output of this code will be (1, 2, ‘a’, ‘b’), as it combines the elements of both tuples into one.


We can also extract a subset of elements from a tuple using slicing. Slicing allows us to specify a range of indices to extract. Let’s see an example:

my_tuple = (1, 2, 3, 4, 5)
sliced_tuple = my_tuple[1:4]

The output will be (2, 3, 4), as it extracts the elements from index 1 to index 3 (exclusive).

Advantages of Tuples

  • Tuples are immutable, so their values cannot be changed accidentally.
  • Tuples are faster than lists when it comes to accessing elements.
  • Tuples can be used as keys in dictionaries due to their immutability.


In this tutorial, we have learned about tuples in Python and their usage in data structures. We explored how to create tuples, access their elements using indexing, and perform operations such as concatenation and slicing.

We also discussed the advantages of using tuples. Tuples are an important concept in Python programming and understanding them will help you write more efficient code.

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