In Python, a Set is an unordered collection of unique items. Sets are based on the mathematical concept of sets and are primarily used for membership testing and eliminating duplicate entries from a dataset.
Unordered: Sets do not record element position or order of insertion. Therefore, you cannot access items using an index (e.g., my_set[0] will raise an error).
Unique Elements: Sets automatically filter out duplicate values. Each element must be unique.
Unchangeable (Immutable) Items: While the set itself is mutable (you can add or remove items), the individual items within the set must be of an immutable type (like strings, integers, or tuples).
Unindexed: Since sets are unordered, the items do not have a defined index.
Duplicate Removal: Quickly turn a list with duplicates into a collection of unique values.
Mathematical Operations: Easily perform operations like Union, Intersection, and Difference.
Membership Testing: Checking if an item exists in a set is significantly faster than in a list (O(1) average time complexity vs O(n)).
Sets are created using curly braces {} or the set() constructor.
Note: To create an empty set, you must use set(), because {} creates an empty dictionary.
# Creating sets fruits = {"apple", "banana", "cherry", "apple"} # "apple" is duplicated print(fruits) # Output: {'banana', 'apple', 'cherry'} (Order may vary) # Creating an empty set empty_set = set()
| Method | Description | Example |
| add() | Adds a single element. | my_set.add("orange") |
| update() | Adds multiple elements (from a list, tuple, etc.). | my_set.update(["kiwi", "mango"]) |
| remove() | Removes a specific item; raises error if not found. | my_set.remove("banana") |
| discard() | Removes a specific item; does NOT raise error if missing. | my_set.discard("banana") |
| pop() | Removes a random item (since sets are unordered). | my_set.pop() |
This is where sets truly shine for data analysis.
set_a = {1, 2, 3, 4}
set_b = {3, 4, 5, 6}
# Union: Items in either set
print(set_a | set_b) # {1, 2, 3, 4, 5, 6}
# Intersection: Items in both sets
print(set_a & set_b) # {3, 4}
# Difference: Items in set_a but NOT in set_b
print(set_a - set_b) # {1, 2}
# Symmetric Difference: Items in either set, but NOT both
print(set_a ^ set_b) # {1, 2, 5, 6}
# Membership Testing print("apple" in fruits) # True # Subset and Superset set_x = {1, 2} set_y = {1, 2, 3} print(set_x.issubset(set_y)) # True print(set_y.issuperset(set_x)) # True
If you need a set that is entirely immutable (cannot be changed after creation), Python provides the frozenset() type. These can be used as keys in a dictionary.
fs = frozenset(["red", "green", "blue"]) # fs.add("yellow") # This would raise an AttributeError
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