Skip to main content

Set Methods in Python

 

Learning Sections          show

Set Methods in Python

A set is an unordered collection of unique elements. Python provides several built-in methods for manipulating sets:

1. add()

Adds an element to the set if it is not already present.


# Define a set
fruits = {'apple', 'banana', 'cherry'}

# Add an element to the set
fruits.add('orange')
print(fruits)  # Output: {'banana', 'cherry', 'orange', 'apple'}

2. remove()

Removes the specified element from the set. Raises a KeyError if the element is not present.


# Remove an element from the set
fruits.remove('banana')
print(fruits)  # Output: {'apple', 'cherry', 'orange'}

3. discard()

Removes the specified element from the set if it is present. Does not raise an error if the element is not present.


# Discard an element from the set
fruits.discard('grape')
print(fruits)  # Output: {'apple', 'cherry', 'orange'}

4. pop()

Removes and returns an arbitrary element from the set. Raises a KeyError if the set is empty.


# Remove an arbitrary element from the set
removed_item = fruits.pop()
print(removed_item)  # Output: apple
print(fruits)  # Output: {'cherry', 'orange'}

5. clear()

Removes all elements from the set.


# Clear the set
fruits.clear()
print(fruits)  # Output: set()

6. union()

Returns a new set containing all elements from the original set and the specified set(s).


# Define another set
more_fruits = {'banana', 'grape'}

# Perform union operation
combined_fruits = fruits.union(more_fruits)
print(combined_fruits)  # Output: {'banana', 'grape', 'cherry', 'orange'}

7. intersection()

Returns a new set containing only the elements that are present in both sets.


# Perform intersection operation
common_fruits = fruits.intersection(more_fruits)
print(common_fruits)  # Output: {'banana'}

8. difference()

Returns a new set containing the elements that are present in the original set but not in the specified set(s).


# Perform difference operation
unique_fruits = fruits.difference(more_fruits)
print(unique_fruits)  # Output: {'cherry', 'orange'}

9. symmetric_difference()

Returns a new set containing the elements that are present in either set, but not both.


# Perform symmetric difference operation
symmetric_diff = fruits.symmetric_difference(more_fruits)
print(symmetric_diff)  # Output: {'cherry', 'orange', 'grape'}

10. isdisjoint()

Returns True if two sets have no elements in common.


# Check if sets are disjoint
disjoint = fruits.isdisjoint(more_fruits)
print(disjoint)  # Output: False

11. issubset()

Returns True if all elements of one set are present in another set.


# Check if a set is a subset
subset = fruits.issubset(combined_fruits)
print(subset)  # Output: True

12. issuperset()

Returns True if all elements of one set are present in another set.


# Check if a set is a superset
superset = combined_fruits.issuperset(fruits)
print(superset)  # Output: True
Labels:

Popular posts from this blog

Generators in Python

  Learning Sections          show Generators in Python Generators are a special type of iterator in Python that allow you to iterate over a sequence of items without storing them all in memory at once. They are useful for generating large sequences of data on-the-fly, or for processing data in a memory-efficient manner. Creating Generators In Python, generators are created using generator functions or generator expressions: # Generator function def my_generator ( n ): for i in range ( n ): yield i # Generator expression my_generator = ( i for i in range ( 10 )) A generator function uses the yield keyword to yield values one at a time, while a generator expression creates an anonymous generator. Iterating Over Generators You can iterate over the values produced by a generator using a for loop: for value in my_generator ( 5 ): print ( value ) This w...
Read more

Inheritance in Python

  Learning Sections          show Inheritance in Python Inheritance is a fundamental concept in object-oriented programming (OOP) that allows a class to inherit attributes and methods from another class. The class that inherits is called the child class or subclass, and the class being inherited from is called the parent class or superclass. Basic Inheritance In Python, a child class inherits from a parent class by specifying the parent class in parentheses after the child class name. Example: class Animal : def __init__ ( self , name ): self . name = name def speak ( self ): raise NotImplementedError ( "Subclass must implement this method" ) class Dog ( Animal ): def speak ( self ): return "Woof!" class Cat ( Animal ): def speak ( self ): return "Meow!" # Create instances of Dog and Cat dog = Dog ( "Buddy" ) cat = Cat ( "Whiskers" ...
Read more

If else Conditional Statements in Python

  Learning Sections     show If-Else Conditional Statements Conditional statements allow you to execute different blocks of code based on certain conditions. The most common conditional statement is the if statement. It can be used alone, or combined with elif (else if) and else statements to handle multiple conditions. If Statement The if statement evaluates a condition, and if the condition is true, the block of code indented under the if statement is executed. # If statement example x = 10 if x >> 0 : print ( "x is positive" ) If-Else Statement The if-else statement adds an additional block of code that runs if the condition is false. # If-else statement example x = -10 if x >> 0 : print ( "x is positive" ) else : print ( "x is non-positive" ) If-Elif-Else Statement The if-elif-else statement allows you to check multiple conditions. The fir...
Read more