Topic List :

A set is a collection of unique data. That is, elements of a set cannot be duplicate. For example,
Suppose we want to store information about student IDs. Since student IDs cannot be duplicate, we can use a set.

## Create a Set in Python

In Python, we create sets by placing all the elements inside curly braces {}, separated by comma.

A set can have any number of items and they may be of different types (integer, float, tuple, string etc.). But a set cannot have mutable elements like lists, sets or dictionaries as its elements.

Let's see an example,

```
# create a set of integer type
student_id = {112, 114, 116, 118, 115}
print('Student ID:', student_id)
# create a set of string type
vowel_letters = {'a', 'e', 'i', 'o', 'u'}
print('Vowel Letters:', vowel_letters)
# create a set of mixed data types
mixed_set = {'Hello', 101, -2, 'Bye'}
print('Set of mixed data types:', mixed_set)
```

**Output**

```
Student ID: {112, 114, 115, 116, 118}
Vowel Letters: {'u', 'a', 'e', 'i', 'o'}
Set of mixed data types: {'Hello', 'Bye', 101, -2}
```

In the above example, we have created different types of sets by placing all the elements inside the curly braces {}.

**Note:** When you run this code, you might get output in a different order. This is because the set has no particular order.

## Create an Empty Set in Python

Creating an empty set is a bit tricky. Empty curly braces {} will make an empty dictionary in Python.

To make a set without any elements, we use the set() function without any argument. For example,

```
# create an empty set
empty_set = set()
# create an empty dictionary
empty_dictionary = { }
# check data type of empty_set
print('Data type of empty_set:', type(empty_set))
# check data type of dictionary_set
print('Data type of empty_dictionary', type(empty_dictionary))
```

**Output**

```
Data type of empty_set: <class 'set'>
Data type of empty_dictionary <class 'dict'>
```

Here,

empty_set - an empty set created using set()

empty_dictionary - an empty dictionary created using {}

Finally we have used the type() function to know which class empty_set and empty_dictionary belong to.

## Duplicate Items in a Set

Let's see what will happen if we try to include duplicate items in a set.

```
numbers = {2, 4, 6, 6, 2, 8}
print(numbers) # {8, 2, 4, 6}
```

Here, we can see there are no duplicate items in the set as a set cannot contain duplicates.

## Add and Update Set Items in Python

Sets are mutable. However, since they are unordered, indexing has no meaning.

We cannot access or change an element of a set using indexing or slicing. Set data type does not support it.

### Add Items to a Set in Python

In Python, we use the add() method to add an item to a set. For example,

```
numbers = {21, 34, 54, 12}
print('Initial Set:',numbers)
# using add() method
numbers.add(32)
print('Updated Set:', numbers)
```

**Output**

```
Initial Set: {34, 12, 21, 54}
Updated Set: {32, 34, 12, 21, 54}
```

In the above example, we have created a set named numbers. Notice the line,

`numbers.add(32)`

Here, add() adds **32** to our set.

## Update Python Set

The update() method is used to update the set with items other collection types (lists, tuples, sets, etc). For example,

```
companies = {'Lacoste', 'Ralph Lauren'}
tech_companies = ['apple', 'google', 'apple']
companies.update(tech_companies)
print(companies)
# Output: {'google', 'apple', 'Lacoste', 'Ralph Lauren'}
```

Here, all the unique elements of tech_companies are added to the companies set.

## Remove an Element from a Set

We use the discard() method to remove the specified element from a set. For example,

```
languages = {'Swift', 'Java', 'Python'}
print('Initial Set:',languages)
# remove 'Java' from a set
removedValue = languages.discard('Java')
print('Set after remove():', languages)
```

**Output**

```
Initial Set: {'Python', 'Swift', 'Java'}
Set after remove(): {'Python', 'Swift'}
```

Here, we have used the discard() method to remove 'Java' from the languages set.

## Built-in Functions with Set

Built-in functions like all(), any(), enumerate(), len(), max(), min(), sorted(), sum() etc. are commonly used with sets to perform different tasks.

## Function

**all()**

Returns True if all elements of the set are true (or if the set is empty).

```
# all values true
l = [1, 3, 4, 5]
print(all(l))
# all values false
l = [0, False]
print(all(l))
# one false value
l = [1, 3, 4, 0]
print(all(l))
# one true value
l = [0, False, 5]
print(all(l))
# empty iterable
l = []
print(all(l))
```

**any()**

Returns True if any element of the set is true. If the set is empty, returns False.

```
# True since 1,3 and 4 (at least one) is true
l = [1, 3, 4, 0]
print(any(l))
# False since both are False
l = [0, False]
print(any(l))
# True since 5 is true
l = [0, False, 5]
print(any(l))
# False since iterable is empty
l = []
print(any(l))
```

**enumerate()**

Returns an enumerate object. It contains the index and value for all the items of the set as a pair.

```
grocery = ['bread', 'milk', 'butter']
enumerateGrocery = enumerate(grocery)
print(type(enumerateGrocery))
# converting to list
print(list(enumerateGrocery))
# changing the default
counterenumerate
Grocery = enumerate(grocery, 10)
print(list(enumerateGrocery))
```

**len()**

Returns the length (the number of items) in the

```
testList = []
print(testList, 'length is', len(testList))
testList = [1, 2, 3]
print(testList, 'length is', len(testList))
testTuple = (1, 2, 3)
print(testTuple, 'length is', len(testTuple))
testRange = range(1, 10)
print('Length of', testRange, 'is', len(testRange))
```

**set.max()**

Returns the largest item in the set.

```
number = [3, 2, 8, 5, 10, 6]
largest_number = max(number);
print("The largest number is:", largest_number)
```

**min()**

Returns the smallest item in the set.

```
number = [3, 2, 8, 5, 10, 6]
smallest_number = min(number);
print("The smallest number is:", smallest_number)
```

**sorted()**

Returns a new sorted list from elements in the set(does not sort the set itself).

```
# vowels list
py_list = ['e', 'a', 'u', 'o', 'i']
print(sorted(py_list))
# string
py_string = 'Python'
print(sorted(py_string))
# vowels tuple
py_tuple = ('e', 'a', 'u', 'o', 'i')
print(sorted(py_tuple))
```

**sum()**

Returns the sum of all elements in the set.

```
numbers = [2.5, 3, 4, -5]
# start parameter is not provided
numbers_sum = sum(numbers)
print(numbers_sum)
# start = 10numbers_sum = sum(numbers, 10)
print(numbers_sum)
```

## Iterate Over a Set in Python

```
ruits = {"Apple", "Peach", "Mango"}
# for loop to access each fruits
for fruit in fruits:
print(fruit)
```

**Output**

```
Mango
Peach
Apple
```

## Python Set Operations

Python Set provides different built-in methods to perform mathematical set operations like union, intersection, subtraction, and symmetric difference.

## Union of Two Sets

The union of two sets **A** and **B** include all the elements of set **A** and **B**.

We use the | operator or the union() method to perform the set union operation. For example,

```
# first set
A = {1, 3, 5}
# second set
B = {0, 2, 4}
# perform union operation using |
print('Union using |:', A | B)
# perform union operation using union()
print('Union using union():', A.union(B))
```

**Output**

```
Union using |: {0, 1, 2, 3, 4, 5}
Union using union(): {0, 1, 2, 3, 4, 5}
```

**Note**: A|B and union() is equivalent to A â‹ƒ B set operation.

## Set Intersection

The intersection of two sets **A** and **B** include the common elements between set **A** and **B**.

In Python, we use the & operator or the intersection() method to perform the set intersection operation. For example,

```
# first set
A = {1, 3, 5}
# second set
B = {1, 2, 3}
# perform intersection operation using &
```

```
print('Intersection using &:', A & B)
# perform intersection operation using intersection()
```

`print('Intersection using intersection():', A.intersection(B)) `

**Output**

```
Intersection using &: {1, 3}
Intersection using intersection(): {1, 3}
```

**Note**: A&B and intersection() is equivalent to A â‹‚ B set operation.

## Difference between Two Sets

The difference between two sets **A** and **B** include elements of set **A** that are not present on set **B**.

We use the - operator or the difference() method to perform the difference between two sets. For example,

```
# first set
A = {2, 3, 5}
# second set
B = {1, 2, 6}
# perform difference operation using &
```

```
print('Difference using &:', A - B)
# perform difference operation using difference()
```

`print('Difference using difference():', A.difference(B)) `

**Output**

```
Difference using &: {3, 5}
Difference using difference(): {3, 5}
```

**Note**: A - B and A.difference(B) is equivalent to A - B set operation.

## Set Symmetric Difference

The symmetric difference between two sets **A** and **B** includes all elements of **A** and **B** without the common elements.

In Python, we use the ^ operator or the symmetric_difference() method to perform symmetric difference between two sets. For example,

```
# first set
A = {2, 3, 5}
# second set
B = {1, 2, 6}
# perform difference operation using &
print('using ^:', A ^ B)
# using symmetric_difference()
print('using symmetric_difference():',
A.symmetric_difference(B))
```

**Output**

```
using ^: {1, 3, 5, 6}
using symmetric_difference(): {1, 3, 5, 6}
```

## Check if two sets are equal

We can use the == operator to check whether two sets are equal or not. For example,

```
# first set
A = {1, 3, 5}
# second set
B = {3, 5, 1}
# perform difference operation using &
if A == B:
print('Set A and Set B are equal')
else:
print('Set A and Set B are not equal')
```

**Output**

`Set A and Set B are equal`

In the above example, A and B have the same elements, so the condition

`if A == B`

evaluates to True. Hence, the statement print('Set A and Set B are equal') inside the if is executed.

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