List in Python

Lists are Python’s most flexible ordered collection object type. It can also be referred to as a sequence that is an ordered collection of objects that can host objects of any data type, such as Python Numbers, Python Strings and nested lists as well. Lists are one of the most used and versatile Python Data Types. In this module, we will learn all about lists in order to get started with them.
Following is the list of all topics that are going to be covered in this module.

Without any further ado, let’s get started.

 

Creating a Lists in python

A list can be created by putting the value inside the square bracket, and values are separated by commas.

List_name = [value1, value2, …, value n]

Unlike strings, lists can contain any sort of objects: numbers, strings, and even other lists. Python lists are:

  • Ordered collections of arbitrary objects
  • Accessed by offset
  • Arrays of object references
  • Of variable length, heterogeneous, and arbitrarily nestable
  • Of the category, mutable sequence
  • Data types in which elements are stored in the index basis with starting index as 0
  • Enclosed between square brackets ‘[]’

Example:

list1 = [1,2,3,4,5]
list2 = [“hello”, “intellipaat”]

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Creating Multi-dimensional Lists in Python

A list can hold other lists as well which can result in multi-dimensional lists, also called a List of Lists. Next, we will see how to create a python list of lists.

One-dimensional Lists in Python:

init_list = [0]*3
print(init_list)
Output:
[0, 0, 0]

 Two-dimensional Lists In Python:

two_dim_list = [ [0]*3 ] *3
print(two_dim_list)
Output: 
[[0, 0, 0], [0, 0, 0], [0, 0, 0]]

Three-dimensional Lists in Python:

two_dim_list = [[ [0]*3 ] *3]*3
print(two_dim_list)
Output: 
[[[0, 0, 0], [0, 0, 0], [0, 0, 0]],
[[0, 0, 0], [0, 0, 0], [0, 0, 0]],
[[0, 0, 0], [0, 0, 0], [0, 0, 0]]]
 

Python List Comprehension

Python List comprehension helps in constructing lists in a completely natural and easy way.

List = [1,2,3,4,5]
List1 = [ i for i in range(5)]
print(List1)
Output: 
[0, 1, 2, 3, 4]

Complicated Python List Comprehension Examples

Example 1:

print ([a+b for a in ‘mug’ for b in ‘lid’])
Output: 
[‘ml’, ‘mi’, ‘md’, ‘ul’, ‘ui’, ‘ud’, ‘gl’, ‘gi’, ‘gd’]

Example 2:

list_fruit = [“Apple”,”Mango”,”Banana”,”Avocado”]
first_letters = [ fruits[0] for fruits in list_fruit ]
print(first_letters)
Output: 
[‘A’, ‘M’, ‘B’, ‘A’]

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List Extension

Python allows lists to resize in many ways. We can do that just by adding two or more of them.
Example:

two_dim = [[0]*3 for i in range(3)]print(two_dim)
[[0, 0, 0], [0, 0, 0], [0, 0, 0]]
two_dim[0][2] = 1
print(two_dim)
Output: 
[[0, 0, 1], [0, 0, 0], [0, 0, 0]]
  • extend(): 

Alternately, we can do extension by using the extend() method. See the following example:

L1 = [‘a’, ‘b’]
L2 = [‘c’, ‘d’]
L1.extend(L2)
print(L1)
Output:
[‘a’, ‘b’, ‘c’, ‘d’]

Learn more about Lists from our blog on Python List Comprehension.

  • append(): 

Next, we can append a value to a list by calling the append() method. See the following example:

L1 = [‘a’, ‘b’]
L2 = [‘c’, ‘d’]
L1.extend(L2)
print(L1)
Output: 
[‘a’, ‘b’, ‘c’, ‘d’]
 

Accessing Lists in Python

Much similar to strings, we can use the index number to access items in lists as shown below.
Example:

list1 = [1,2,3,4,5]

Accessing a List Using Reverse Indexing

To access a list in reverse order, we have to use indexing from −1, −2…. Here, −1 represents the last item in the list.

print(list1[-1])
print(list1[-3])
Output:
5
3

Length of List

In python, there is a built-in method called, len() that helps you get the number of items in a list. It can also be used for arrays, tuples, dictionaries etc. The function takes a list as the argument and returns its length.

List1 = [“Intellipaat”, “Python”, “Tutorial”, 1, 2, 3]
print(“The number of items in this list is ”, len(List1))

The output will be 6

Linked list in Python

A linked list is an ordered collection of objects. The data elements in a linked list are connected to each other via links, and this makes them different from normal lists. They store elements in memory. Normal lists use contiguous memory block to store data references, whereas linked lists store the references as a part of their own elements

Python does not have linked lists in its standard library so it is implemented using the concept of nodes.

Each of the data elements are connected to other data elements using pointers. Linked lists contain a link element called first. Each link carries two fields, a data field and a link field called next, which links each element to the next element. The last link carries a null link, marking that it is the end of the linked list.

The types of linked lists are – 

  • Singly Linked List − Item navigation is forward only.
  • Doubly Linked List − Items can be navigated in both directions, forward and backward.
  • Circular Linked List − The last item has the link of the first element as next and the first element has the link to the last element as previous.

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List to String

A list can be converted to string using the join() method.

def ListToString(a):
s1 = “ ” 
return(s1.join(a))
a = [‘Intellipaat’,‘Python’,‘tutorial’] 
print(ListToString(a)

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Common List Operations in Python

Following is the list of some of the most common list operations in Python, along with their descriptions and examples.

 

Slicing Python Lists

Slicing operation is used to print a list up to a specific range. We can use slice operation by including the starting index and ending index of the range that we want to print separated by a colon as shown below:

list1[2:4]
output:
[3, 4]
list1[2:-1]
output:
[3, 4]
list1[:2]
output:
[1, 2]

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Iterating through Python Lists

Iterating is quite simple in lists. We can just use Python for loop to iterate, as shown below:

list1 = [1,2,3,4,5]
for element in list1:
print(element)

Output: 
1
2
3
4
5

List comprehension in Python

List comprehension has a shorter syntax to create a new list, based upon the values of a preexisting list.

Example: If you have a list of programming languages, and based on that, you have to create a new list, containing just the languages with the letter ‘a’ in their name. Without list comprehension, you would need to write a for statement with the condition inside, whereas, using list comprehension, all that can be done with just one line of code:

languages = [“python”, “java”, “c”, “javascript”, “kotlin”]
newlist = [x for x in languages if “a” in x]
print(newlist) 

The output will be [‘java’,’javascript’]

 

Update or Add Elements in a Python List

We can update a particular item or multiple items of a list by using the slice operation, and then add an element using the append () method as shown below.
Example:

list1[4] = ‘number’print(list1)list1[4:7] = [“Apple”,”Mango”,”Banana”]
print(list1)list1.insert(0,33)
print(list1)list1.insert(6,29)
print(list1)

Output:
[1, 2, 3, 4, ‘number’]
[1, 2, 3, 4, ‘Apple’, ‘Mango’, ‘Banana’]
[33, 1, 2, 3, 4, ‘Apple’, ‘Mango’, ‘Banana’]
[33, 1, 2, 3, 4, ‘Apple’, 29, ‘Mango’, ‘Banana’]
 

Remove elements from list in python

There are three ways of removing elements from lists. We can either use the del keyword to remove a particular element or we can use the remove () method, and the last way is using the pop () method, as shown in the following code block:

list1 = [1,2,3,4,5]
del list1[2]
list2 = [1,2,3,4,5]
list2.remove(4)
print(list2)
list3 = [1,2,3,4,5]
print(list3.pop(1))
print(list3)

Output:
[1, 2, 4, 5][1, 2, 3, 5]
2
[1, 3, 4, 5]
 

Remove duplicates from lists in python

Here’s an example of list where some items are repeating. Let us see how we can remove duplicates from list in python.

mylist = ["a", "b", "c", "d", "c"]
mylist = list(dict.fromkeys(mylist))


output: 
[“a”, “b”,”c”,”d”]
 

Reverse a list in python

lst = [10, 11, 12, 13, 14, 15]
lst.reverse()
print(lst)


output:
[15, 14, 13, 12, 11, 10]

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Sorting Lists in Python

Python list implements the sort() method for ordering (in both ascending and descending order) its elements in place.

list1.sort()

Sorting in ascending order:

list1 = [1,3,2,4,5,9,6]
list1.sort()
print(list1)


output:
[1, 2, 3, 4, 5, 6, 9]

Sorting in descending order:

list1 = [1,3,2,4,5,9,6]
list1.sort(reverse=True)
print(list1)
output:
[9, 6, 5, 4, 3, 2, 1]

 

Python List Functions and Methods

Let’s understand different types of Python functions for lists through the following table that contains a list of different functions with their respective descriptions.

Method Description
min(list_name) Returns the minimum value from a list in Python
max(list_name) Returns the largest value from a list in Python
len(list_name) Returns the number of elements in a list in Python
cmp(list1,list2) Compares two lists in Python
list.reverse() Reverses a list in Python
list.sort Sorts a list in Python
list(sequence) Converts the sequence of a list in Python
list.append(value) Adds a value into a list in Python
list.remove(value) Removes a value from a list in Python

With this, we come to the end of this module in Python Tutorial. Now, if you’re  interested to know why Python is the most preferred language for Data Science, you can go through this Python for Data Science blog
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