Summary  
This chapter covers defining and manipulating set data structures in Python, including union, intersection, difference, symmetric difference, subset/superset checks, and using sets to remove duplicate elements.

General domain of usage  
Data science

## Breaking Down the Python Code

### Defining Sets
A **set** is defined using curly brackets `{}` or the `set()` function. Sets **do not allow duplicate values** and do not maintain any specific order.

# Define two sets
set_a = {1, 2, 3, 4, 5}
set_b = set([4, 5, 6, 7, 8])

print("Set A:", set_a)
print("Set B:", set_b)

Even if we define a set with duplicate values, Python **automatically removes** the duplicates.

### Union of Sets
Combines elements from **both sets**. **No duplicates** are included.


set_a = {1, 2, 3, 4, 5}
set_b = {4, 5, 6, 7, 8}

union_set = set_a.union(set_b)
print("Union:", union_set)

### Intersection of Sets

Returns only the elements **common to both sets**.


set_a = {1, 2, 3, 4, 5}
set_b = {4, 5, 6, 7, 8}

intersection_set = set_a.intersection(set_b)
print("Intersection:", intersection_set)

### Difference of Sets
Finds elements in `set_a` that are **NOT** in `set_b`.


set_a = {1, 2, 3, 4, 5}
set_b = {4, 5, 6, 7, 8}

difference_set = set_a.difference(set_b)
print("Difference (A - B):", difference_set)

### Symmetric Difference
Finds elements that are in **either set**, but **NOT in both**.


set_a = {1, 2, 3, 4, 5}
set_b = {4, 5, 6, 7, 8}

symmetric_difference_set = set_a.symmetric_difference(set_b)
print("Symmetric Difference:", symmetric_difference_set)

### Subset and Superset Relationships
- `issubset()` checks if **all elements of one set exist in another**;
- `issuperset()` checks if **one set fully contains another**.


set_a = {1, 2, 3, 4, 5}
set_b = {4, 5, 6, 7, 8}

print("Is A a subset of B?", set_a.issubset(set_b))
print("Is A a superset of {3, 4}?", set_a.issuperset({3, 4}))

### Removing Duplicates Using Sets
A common **real-world use case** for sets is removing duplicates from a list.


data = [1, 2, 2, 3, 4, 4, 5]
unique_data = set(data)
print("Unique values:", unique_data)

Since sets **do not allow duplicates**, converting a list into a set automatically removes repeated values.

This course distills the essentials of Python's math module, focusing on trigonometric functions, logarithmic operations, and mathematical constants. Learners will gain hands-on experience using Python to perform these standard mathematical computations, ideal for beginners seeking practical skills with the math module.

Implementing Sets in Python

Breaking Down the Python Code

Defining Sets

Union of Sets

Intersection of Sets

Difference of Sets

Symmetric Difference

Subset and Superset Relationships

Removing Duplicates Using Sets