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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 among developers as a scripting language with extensive libraries.

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

The Python interpreter and a wide range of libraries that make the language an ideal choice for building applications have led developers to use Python to create 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, we discuss several ways to duplicate items in a Python list.

What is a list in Python?

Lists in Python store values separated by commas and enclosed in brackets. The list is the most fundamental data type in Python. The most important advantage of the list is that its elements do not have to be of the same data type, and negative indices can be used to access elements.

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 a 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 to remove duplicates from a list, we can leverage Python’s built-in capabilities in a single 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 relies on the assumption that repetition is not allowed in the set data structure. However, with this method, the element order 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 method above, we identify 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 iterable as an argument and returns an enumerator (index, item) object, incrementing the index for each element.

# 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 duplicates from the list, then returns the dictionary value. The above function is well-suited to working with strings.

# removing duplicates from a 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 a 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. We can also use Pandas functions, the OrderedDict class, the reduce() function, the set + sort method, and iterative approaches to maintain element order.

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