Sets

In Python, a set is an unordered collection of unique elements. It is a built-in data type that can be used to store and manipulate data in various ways.

To create a set in Python, you can use the set() function or use curly braces {} with comma-separated values inside. Here's an example:


As you can see, a set can contain any immutable data type such as integers, strings, and tuples. However, it cannot contain mutable objects such as lists and dictionaries.

Sets support various set operations such as union, intersection, difference, and symmetric difference. Here are some examples:


You can also perform set operations using methods, such as union(), intersection(), difference(), and symmetric_difference(). Additionally, you can use comparison operators such as ==, <, >, <=, and >= to compare two sets.

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Sets in Python are indeed a powerful data type for storing and manipulating unique elements. Here are a few additional points about sets:

1. Unique Elements: Sets automatically remove duplicate elements. If you try to add the same element multiple times, it will only be included once in the set. This property makes sets useful for tasks like finding unique values or removing duplicates from a list.
   
   
2. Set Operations: In addition to the operations mentioned earlier (union, intersection, difference, and symmetric difference), sets support other useful operations such as subset, superset, and disjoint. Here are some examples:
   
   
   Python:

   set1 = {1, 2, 3}set2 = {2, 3, 4}
   
   # Subset
   print(set1.issubset(set2))  # Output: False
   
   # Superset
   print(set1.issuperset(set2))  # Output: False
   
   # Disjoint
   print(set1.isdisjoint(set2))  # Output: False

   
   
3. Modifying a Set: Sets are mutable, meaning you can add and remove elements from a set. You can use the add() method to add a single element and the update() method to add multiple elements from another iterable. To remove elements, you can use the remove() method or discard() method. The difference is that remove() raises an error if the element doesn't exist, while discard() doesn't raise an error.
   
   
   Python:

   my_set = {1, 2, 3}my_set.add(4)
   print(my_set)  # Output: {1, 2, 3, 4}
   
   my_set.update([5, 6, 7])
   print(my_set)  # Output: {1, 2, 3, 4, 5, 6, 7}
   
   my_set.remove(2)
   print(my_set)  # Output: {1, 3, 4, 5, 6, 7}
   
   my_set.discard(10)  # No error raised if element doesn't exist

   
   
4. Set Comprehension: Similar to list comprehension, you can use set comprehension to create a set based on an iterable or with conditions. For example:
   
   
   Python:

   my_set = {x for x in range(1, 6)}print(my_set)  # Output: {1, 2, 3, 4, 5}
   
   even_set = {x for x in my_set if x % 2 == 0}
   print(even_set)  # Output: {2, 4}

Sets provide a convenient and efficient way to work with collections of unique elements and perform various set operations. They can be particularly useful when dealing with membership testing, finding unique values, or solving problems that require set-based operations.

myset = {"apple", "banana", "cherry"}

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Set​

Sets are used to store multiple items in a single variable.

Set is one of 4 built-in data types in Python used to store collections of data, the other 3 are , , and , all with different qualities and usage.

A set is a collection which is unordered, unchangeable*, and unindexed.

* Note: Set items are unchangeable, but you can remove items and add new items.
Sets are written with curly brackets.

Example

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Create a Set:
thisset = {"apple", "banana", "cherry"}
print(thisset)

my_set = {x for x in range(1, 8)}
print(my_set)

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