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Python BasicPython Tutorials

How to Make a Unique List in Python

Last updated: Jan 05, 2024 1:02 pm
By Meenakshi Agarwal
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6 Min Read
Unique List in Python
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In the world of Python, handling data is a big deal. We often work with lists, and sometimes, we need to make sure they only have unique items. In this detailed guide, we’ll explore different ways to make a unique list in Python. From using sets to more advanced stuff like functools.reduce(), we’re going to cover it all to help you become a pro at dealing with data uniquely.

Contents
1. Sets: Your Best Friend for Uniqueness2. List Comprehensions: Keeping It Simple and Unique3. The Dict.fromkeys() Trick: Uniqueness in a Different Way4. Using the Power of Collections.Counter5. The Power of functools reduce(): Uniqueness through IterationExtra InfoTime Complexity: Picking the Fastest RouteHandling Tricky Elements: Making it Work for AllKeeping Things in Order: Making Sure It Looks RightStaying Updated: Using the Latest and Greatest

5 Ways to Create a Unique List in Python

Watch out for 5 different methods you can easily adapt to either create or make an existing list unique.

1. Sets: Your Best Friend for Uniqueness

To create a unique list in Python, the magic word is “sets.” Python has this cool thing called a set, and it’s perfect for handling unique elements. Check this out:

# Example 1: Making a unique list using sets
original_list = [1, 2, 3, 2, 4, 5, 1]
unique_set = set(original_list)
unique_list = list(unique_set)

print(unique_list)  # Output: [1, 2, 3, 4, 5]

The set() trick does the job of removing duplicates and gives you a list without any duplicates.

2. List Comprehensions: Keeping It Simple and Unique

List comprehensions are like a cool shortcut in Python to create lists. We can use them to make a unique list easily:

# Example 2: Making a unique list with list comprehensions
original_list = [1, 2, 3, 2, 4, 5, 1]
unique_list = [x for x in original_list if original_list.count(x) == 1]

print(unique_list)  # Output: [3, 4, 5]

By using list comprehensions, we filter out duplicates and end up with a unique list.

3. The Dict.fromkeys() Trick: Uniqueness in a Different Way

Now, here’s a bit of a unique method using dict.fromkeys(). It’s not the usual, but it works surprisingly well to achieve our goal:

# Example 3: Making a unique list with dict.fromkeys()
original_list = [1, 2, 3, 2, 4, 5, 1]
unique_dict = dict.fromkeys(original_list)
unique_list = list(unique_dict.keys())

print(unique_list)  # Output: [1, 2, 3, 4, 5]

By playing with dictionaries and keys, we achieve the goal of having a unique list.

4. Using the Power of Collections.Counter

Python has this thing called Counter in the collections module, and it’s handy for counting stuff. Let’s explore this method with the help of the following example.

# Example 4: Making a unique list with collections.Counter
from collections import Counter

original_list = [1, 2, 3, 2, 4, 5, 1]
element_counts = Counter(original_list)
unique_list = [key for key, count in element_counts.items() if count == 1]

print(unique_list)  # Output: [3, 4, 5]

The Counter class helps us count things and, in turn, create a unique list.

5. The Power of functools reduce(): Uniqueness through Iteration

For those who enjoy a bit of a fancy touch with functional programming, we have functools.reduce(). It might look complex, but it’s a neat way to make a unique list:

# Example 5: Using functools.reduce()
from functools import reduce

original_list = [1, 2, 3, 2, 4, 5, 1]
unique_list = reduce(lambda acc, x: acc + [x] if x not in acc else acc, original_list, [])

print(unique_list)  # Output: [3, 4, 5]

This functional approach helps us build a unique list in a kind of fancy way.

Extra Info

Some additional info you may want to consider while deciding upon any of the above ways.

Time Complexity: Picking the Fastest Route

When you’re making a unique list in Python, it’s important to think about how long it will take. Using sets, list comprehensions, and the Counter approach is quick, making them good choices for different situations.

Handling Tricky Elements: Making it Work for All

For elements that aren’t easy to handle, like lists or dictionaries, sets, and dictionaries might not be the best. In those cases, we go for alternatives like list comprehensions or the functools.reduce() method.

Keeping Things in Order: Making Sure It Looks Right

Sometimes, the order of things matters. If it does, using list comprehensions or the functools.reduce() method is a good call. Sets and dictionaries don’t always keep things in the order you want.

Staying Updated: Using the Latest and Greatest

If you’re using Python 3.9 or newer, there’s this cool | operator for sets. It’s like a sneak peek into the future:

# Example 6: Using the | operator (Python 3.9+)
original_list1 = [1, 2, 3]
original_list2 = [3, 4, 5]
unique_list = list(set(original_list1) | set(original_list2))

print(unique_list)  # Output: [1, 2, 3, 4, 5]

Keep your Python up to date and use the newest features for cleaner and smarter code.

Conclusion

So there you have it! We’ve explored different ways to make a unique list in Python. Whether you like the simplicity of sets, the straightforwardness of list comprehensions, or the fancy touch of functional programming, there’s a way for you. Think about your data, how fast you want things to be, and whether the order matters. Choose the method that fits your unique needs, and let your lists stand out with their own special uniqueness.

Happy Coding,
Team TechBeamers

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Meenakshi Agarwal Avatar
By Meenakshi Agarwal
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Hi, I'm Meenakshi Agarwal. I have a Bachelor's degree in Computer Science and a Master's degree in Computer Applications. After spending over a decade in large MNCs, I gained extensive experience in programming, coding, software development, testing, and automation. Now, I share my knowledge through tutorials, quizzes, and interview questions on Python, Java, Selenium, SQL, and C# on my blog, TechBeamers.com.
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