The Python tutorials are written as Jupyter notebooks and run directly in Google Colab—a hosted notebook environment that requires no setup. Click the Run in Google Colab button.

Colab link - Open colab

Tuples in Python

Welcome! This notebook will teach you about the tuples in the Python Programming Language. By the end of this lab, you'll know the basics tuple operations in Python, including indexing, slicing and sorting.

About the Dataset

Imagine you received album recommendations from your friends and compiled all of the recommandations into a table, with specific information about each album.

The table has one row for each movie and several columns:

- **artist** - Name of the artist

- **album** - Name of the album

- **released_year** - Year the album was released

- **length_min_sec** - Length of the album (hours,minutes,seconds)

- **genre** - Genre of the album

- **music_recording_sales_millions** - Music recording sales (millions in USD)

- **claimed_sales_millions** - Album's claimed sales (millions in USD)

- **date_released** - Date on which the album was released

- **soundtrack** - Indicates if the album is the movie soundtrack (Y) or (N)

- **rating_of_friends** - Indicates the rating from your friends from 1 to 10

The dataset can be seen below:

Artist	Album	Released	Length	Genre	Music recording sales (millions)	Claimed sales (millions)	Released	Soundtrack	Rating (friends)
Michael Jackson	Thriller	1982	00:42:19	Pop, rock, R&B	46	65	30-Nov-82		10.0
AC/DC	Back in Black	1980	00:42:11	Hard rock	26.1	50	25-Jul-80		8.5
Pink Floyd	The Dark Side of the Moon	1973	00:42:49	Progressive rock	24.2	45	01-Mar-73		9.5
Whitney Houston	The Bodyguard	1992	00:57:44	Soundtrack/R&B, soul, pop	26.1	50	25-Jul-80	Y	7.0
Meat Loaf	Bat Out of Hell	1977	00:46:33	Hard rock, progressive rock	20.6	43	21-Oct-77		7.0
Eagles	Their Greatest Hits (1971-1975)	1976	00:43:08	Rock, soft rock, folk rock	32.2	42	17-Feb-76		9.5
Bee Gees	Saturday Night Fever	1977	1:15:54	Disco	20.6	40	15-Nov-77	Y	9.0
Fleetwood Mac	Rumours	1977	00:40:01	Soft rock	27.9	40	04-Feb-77		9.5

Tuples

In Python, there are different data types: string, integer and float. These data types can all be contained in a tuple as follows:

Now, let us create your first tuple with string, integer and float.

 
# Create your first tuple

tuple1 = ("disco",10,1.2 )
tuple1

The type of variable is a **tuple**.

 
# Print the type of the tuple you created

type(tuple1)

Indexing

Each element of a tuple can be accessed via an index. The following table represents the relationship between the index and the items in the tuple. Each element can be obtained by the name of the tuple followed by a square bracket with the index number:

We can print out each value in the tuple:

 
# Print the variable on each index

print(tuple1[0])
print(tuple1[1])
print(tuple1[2])

We can print out the **type** of each value in the tuple:

 
# Print the type of value on each index

print(type(tuple1[0]))
print(type(tuple1[1]))
print(type(tuple1[2]))

We can also use negative indexing. We use the same table above with corresponding negative values:

We can obtain the last element as follows (this time we will not use the print statement to display the values):

 
# Use negative index to get the value of the last element

tuple1[-1]

We can display the next two elements as follows:

 
# Use negative index to get the value of the second last element

tuple1[-2]

# Use negative index to get the value of the third last element

tuple1[-3]

Concatenate Tuples

We can concatenate or combine tuples by using the **+** sign:

 
# Concatenate two tuples

tuple2 = tuple1 + ("hard rock", 10)
tuple2

We can slice tuples obtaining multiple values as demonstrated by the figure below:

Slicing

We can slice tuples, obtaining new tuples with the corresponding elements:

 
# Slice from index 0 to index 2

tuple2[0:3]

We can obtain the last two elements of the tuple:

 
# Slice from index 3 to index 4

tuple2[3:5]

We can obtain the length of a tuple using the length command:

 
# Get the length of tuple

len(tuple2)

This figure shows the number of elements:

Sorting

Consider the following tuple:

 
# A sample tuple

Ratings = (0, 9, 6, 5, 10, 8, 9, 6, 2)

We can sort the values in a tuple and save it to a new tuple:

 
# Sort the tuple

RatingsSorted = sorted(Ratings)
RatingsSorted

Nested Tuple

A tuple can contain another tuple as well as other more complex data types. This process is called 'nesting'. Consider the following tuple with several elements:

 
# Create a nest tuple

NestedT =(1, 2, ("pop", "rock") ,(3,4),("disco",(1,2)))

Each element in the tuple including other tuples can be obtained via an index as shown in the figure:

 
# Print element on each index

print("Element 0 of Tuple: ", NestedT[0])
print("Element 1 of Tuple: ", NestedT[1])
print("Element 2 of Tuple: ", NestedT[2])
print("Element 3 of Tuple: ", NestedT[3])
print("Element 4 of Tuple: ", NestedT[4])

We can use the second index to access other tuples as demonstrated in the figure:

We can access the nested tuples :

 
# Print element on each index, including nest indexes

print("Element 2, 0 of Tuple: ",   NestedT[2][0])
print("Element 2, 1 of Tuple: ",   NestedT[2][1])
print("Element 3, 0 of Tuple: ",   NestedT[3][0])
print("Element 3, 1 of Tuple: ",   NestedT[3][1])
print("Element 4, 0 of Tuple: ",   NestedT[4][0])
print("Element 4, 1 of Tuple: ",   NestedT[4][1])

We can access strings in the second nested tuples using a third index:

 
# Print the first element in the second nested tuples

NestedT[2][1][0]

# Print the second element in the second nested tuples

NestedT[2][1][1]

We can use a tree to visualise the process. Each new index corresponds to a deeper level in the tree:

Similarly, we can access elements nested deeper in the tree with a fourth index:

 
# Print the first element in the second nested tuples

NestedT[4][1][0]

# Print the second element in the second nested tuples

NestedT[4][1][1]

The following figure shows the relationship of the tree and the element NestedT[4][1][1]:

Python Collections - Tuples in Python