Python Is An Object-Oriented, High-Level, Dynamic Semantic Programming Language Where An Interpreter executes Code. 

Its high-level internal data structures and dynamic typing and binding make it very attractive for rapid application development.

Additionally, Python is popular with developers as a scripting language supported by various libraries.

Python’s simple syntax and easy learning have increased its readability and reduced the cost of producing programs. Python supports modules and packages, which simplify program modularity and code reuse.

The Python interpreter and a wide range of libraries that make this language an ideal choice for building various applications have made developers use Python to build multiple applications. In this article, we will discuss what a List is in Python.

First, I need to see what precisely the list is? Since a Python list is a collection of multiple elements, including duplicates, it is sometimes necessary to make a list unique. In this section, there are different ways to duplicate items from a Python list delete.

What is a list in Python?

Lists in Python store values separated by commas and enclosed in brackets. The list is the most critical data type in the Python programming language. The most important advantage of the list is that the elements inside it do not have to be of the same data type, and it is possible to use negative values ​​to access their values.

Additionally, all string operations, such as truncation and concatenation, apply to list data types. We can also create a nested list, which is a list that contains another list.

How to remove duplicates from a list in Python?

In Python, there are several methods to remove duplicate items from the list, and we will look at some of these methods below.

1. Native method

To remove duplicates from a list in Python, number the list elements, store the first value found in a temporary index and ignore the other values. The algorithm for doing this is as follows:

• Use a For clause to traverse the list.
• Add weights ​​to the list if the elements do not already exist in a temporary list.
• Assign the provisional list to the main index.
• Now we write the following piece of code for the algorithm we presented:

sam_list = [11, 13, 15, 16, 13, 15, 16, 11]

print (“The list is: ” + str(sam_list))

# Remove duplicate elements from the list

result = []

for I in sam_list:

if I am not in the result:

result.append(i)

# Print the list after removing duplicate values

print (“The list after removing duplicates : ” + str(result))

Output:

 The list is: [11, 13, 15, 16, 13, 15, 16, 11]

 The list after removing duplicates: [11, 13, 15, 16]

2. Use the powerful features of Python

Instead of using a for loop as the primary mechanism for removing duplicates from a list, we can use Python‘s native capabilities and only one code line.

Example:

# Remove duplicates from list using list comprehension

# Initial directory

sam_list = [11, 13, 15, 16, 13, 15, 16, 11]

print (“The list is: ” + str(sam_list))

Remove duplicate elements from the list #  

result=[]

[result.append(x) for x in sam_list if x not in result] 

# printing list after removal 

print (“The list after removing duplicates: ” + str(result))

Output:

The list is: [11, 13, 15, 16, 13, 15, 16, 11]

List after removing duplicate elements: [11, 13, 15, 16]

3. Using the set function

Python is the most common way to remove duplicate elements from a list. The above method works based on the hypothesis that repetition is not allowed in the set data structure. However, when using this method, the order of the elements is lost.

# Remove duplicate elements from the list using the Set method

# Initialize the list 

sam_list = [11, 15, 13, 16, 13, 15, 16, 11] 

print (“The list is: ” + str(sam_list)) 

# Remove duplicate elements from the list 

sam_list = list(set(sam_list)) 

# Print deleted elements 

# Print the list after removing the elements

print (“The list after removing duplicates: ” + str(sam_list))

Output:

The list is: [11, 15, 13, 16, 13, 15, 16, 11]

The list after removing duplicates: [16, 11, 13, 15]

4. Use the enumerate function

In the above method, we find distinct elements and store them in a temporary list. When we use the enumerate() function, the program checks the features it has already seen and does not add duplicate elements to the quick list. The enumerate function takes an iteration parameter as an argument and returns it as an enumerator (index, stuff) object, incrementing one value for each element iterated.

# Remove duplicate elements using enumerate() 

# Initialize the list  

sam_list = [11, 15, 13, 16, 13, 15, 16, 11] 

print (“The list is: ” + str(sam_list)) 

# Remove duplicate elements from the list 

result = [i for n, i in enumerate(sam_list) if i not in sam_list[:n]] 

# List after removing duplicate elements 

print (“The list after removing duplicates: ” + str(result))

Output:

The list is: [11, 13, 15, 16, 13, 15, 16, 11]

The list after removing duplicates: [11, 13, 15, 16]

5. Remove duplicate elements using collections.OrderedDict.fromkeys

The fastest way to remove duplicate elements from a Python list is the OrderedDict.fromkeys function. The above function first removes duplicate elements from the list before returning the return value of the dictionary. The above function has a good ability to work with strings.

# removing duplicates from list using collections.OrderedDict.fromkeys() 

from collections import OrderedDict 

# initializing list 

sam_list = [11, 15, 13, 16, 13, 15, 16, 11] 

print (“The list is: ” + str(sam_list)) 

# to remove duplicates from list 

result = list(OrderedDict.fromkeys(sam_list)) 

# printing list after removal 

print (“The list after removing duplicates: ” + str(result))

Output:

The list is: [11, 15, 13, 16, 13, 15, 16, 11]

The list after removing duplicates: [11, 15, 13, 16]

last word

Collections, built-in functions, and iterative methods can remove duplicate items from a list. If the list elements are not hashable, always use an iterative mechanism to extract the unique features. If the order of the components is not essential, we can remove the duplicates using the Set method and the Numpy unique() function. Also, we can use Pandas functions, OrderedDict, reduce() operation, Set + sort method, and iterative approaches to maintain the order of elements.