Sets in Python are unordered collections of unique elements. They are used to store multiple distinct items in a single variable, offering efficient methods for managing and comparing data.
What are sets in Python?
Sets are an unordered collection of unique elements. They used to store multiple items in a variable, making it easier to manage groups of data. Sets are mutable, which means we can add or remove items after creation. The items of a set must be immutable (like numbers, strings, or tuples).
Sets in Python
Assume you're organizing a guest list for a party. You start adding friends, but before you know it, you've accidentally written down the same friend's name twice! With a regular list, duplicates like this can happen easily. But with a set, Python ensures that each friend is invited only once, no matter how many times you add their name! This unique quality makes sets in Python a powerful tool for managing collections of data, where each item is distinct and order doesn’t matter.
This answer will cover how sets work, including creating sets, adding and removing elements, and performing various operations like union and intersection. Whether you're cleaning up data or simplifying data comparisons, sets are a useful addition to your Python toolkit. Let's move on to the next step!
Create a set in Python
To create a set, we have two options:
Curly braces
{}set()function
Curly braces can directly define a set with elements like my_set = {1, 2, 3, 4}. Similarly, the set() function allows us to create a set from other iterable types, such as lists or tuples, offering flexibility in initializing sets with various data structures.
# Using curly bracesmy_set = {1, 2, 3, 4}# Using the set() functionmy_set_from_function = set([1, 2, 3, 4])print(my_set) # Output: {1, 2, 3, 4}
Add and remove values from sets
Let's see each example of how we can add and remove elements from the sets below:
1. Add elements
To add values to sets in Python, the add() method is used. This method allows us to insert a single item into a set without adding duplicates. Since sets are unique by nature, any attempt to add a value already in the set will have no effect.
my_set = {1, 2, 3}my_set.add(4)print(my_set) # Output: {1, 2, 3, 4}
Try experimenting with all the codes. In the above example, consider adding a duplicate, like my_set.add(3), and run the code to see how it behaves with duplicate elements.
2. Remove elements
To remove elements from a set, we can use the remove() method, which raises an error if the item does not exist, or discard(), which quietly does nothing if the item is absent. This flexibility makes managing content in sets easy and safe.
my_set = {1, 2, 3, 4}# Using remove()my_set.remove(2)print(my_set) # Output: {1, 3, 4}# Using discard()my_set.discard(5) # Does not raise an error
3. Remove all elements
If we need to clear all the elements from a set, we can call the clear() method. This effectively empties the set, making it useful when we want to reuse the same variable without needing to create a new set.
my_set = {1, 2, 3}my_set.clear()print(my_set) # Output: set()
Iteration in sets
Iterating through a set in Python can be done using a simple for loop. Since sets do not maintain any particular order, the output may vary on different executions. This iteration allows us to access each unique element stored in the set without duplicates.
my_set = {1, 3, 3, 2}for item in my_set:print(item)# Output: 1 2 3 (order may vary)
Sort set
Sets are unordered, we can convert them into a list of ordered values using the sorted() function. This is helpful when you need to present the data in a specific sequence, allowing us to enjoy the benefits of sets while also displaying the data in an ordered manner.
my_set = {3, 1, 2}ordered_list = sorted(my_set)print(ordered_list) # Output: [1, 2, 3]
Remove duplicates
Sets in Python are ideal for removing duplicates from lists. By converting a list to a set, we automatically filter out any repeated elements, providing a clean list of unique items. This is particularly useful when we want to ensure that the data we’re working with is distinct.
my_list = [1, 2, 2, 3, 4, 4]unique_list = list(set(my_list))print(unique_list) # Output: [1, 2, 3, 4]
Python set operations
Sets in Python are used to perform common mathematical operations like union, intersection, difference, and symmetric difference. These operations help in comparing sets, finding commonalities, and excluding specific values. We can use methods like union(), intersection(), difference(), and symmetric_difference() to execute these operations.
Operation | Description | Method | Operator | Example |
Union | Combines elements of both sets, without duplicates. |
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Intersection | Returns common elements found in both sets. |
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Difference | Returns elements present in the first set but not in the second. |
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Symmetric Difference | Returns elements in either set but not in both. |
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Sets activity
Test all the sets operation by uncommenting the lines 4–6 below:
set_A = {3, 1, 2}set_B = {3, 4, 5}# Test all the sets methods by uncommenting# print(set_A.union(set_B))# print(set_A.intersection(set_B))# print(set_A.difference(set_B))# print(set_A.symmetric_difference(set_B))
Key Takeaways:
Definition and characteristics: Sets in Python are unordered collections of unique, immutable elements. They allow efficient storage and management of data without duplicates.
Creating sets: Sets can be created using curly braces
{}or theset()function, which enables flexibility in initializing sets from different iterables like lists or tuples.Adding and removing elements: Use the
add()method to insert elements into a set, andremove()ordiscard()to delete them. Theclear()method removes all elements from the set.Iterating and sorting: Iterate through sets using a
forloop, and usesorted()to convert the set into a sorted list.Removing duplicates: Convert lists to sets to automatically filter out duplicate elements, providing a clean list of unique items.
Set operations: Perform common mathematical operations like
union,intersection,difference, andsymmetric differenceusing set methods or operators for effective set comparisons and manipulations.
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