Learn Python With Us - Sets

Learn Python With Us - Sets

An unordered, unindexed, mutable with immutable datatypes.

Syed Jafer K's photo
Syed Jafer K
·Nov 19, 2022·

9 min read

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Table of contents

Series Link:
**Challenges: **


What is a set?

A set is a collection that is unordered, mutable with immutable data types, and unindexed. Since it doesn't maintain the order, we can't use the index.

Why Set is unordered?

So basically a set uses a hashtable as its underlying data structure. This explains the O(1) membership checking, since looking up an item in a hashtable is an O(1) operation, on average. Since the hashtable stores the key-value pair, it doesn't have a need to maintain the order or order of insertion. Now you know the reason for the unordered nature of the set.


A set data structure can be defined in two different methods,

  1. {} using curly brackets.

  2. set() method.

1. Using curly brackets

You can declare the set like below,

data = {'d1', 'd2', 'd3'}

But there is one thing to be noted, (i.e) if you want to declare an empty set we can't use this curly brackets {}.

Let's see why,

data = {'d1', 'd2'}


But If we are going to declare an empty set, probably we should not use curly bracket,

data = {}


2. Using set()

Using set() constructor, we can convert a list, tuple, set to a set.

List to Set :

data = set([1, 2, 3, 4])

set python

Dictionary to Set

data = set({1:1, 2:2, 3:3})

dictionary to set

Tuple to Set

data = set((1, 2, 3))

tuple to set

Data Types

Set is a mutable with the immutable data types. (i.e,) Set can comprise only strings, boolean, numbers, set, and tuple. It won't take a list, or dictionary as an element inside the set.

We already saw set is internally built on top of the Hash Table, and we can't generate a hash value for mutable data structures.

Let's see,

data = [1, 2, 3]

hash of immutable data

It will result in an error.

Set with basic built-in functions

Length - len()

To find the length of the set,

data = {'a', 'b', 'c'}

length of a set

Type of data structure - type()

data = {'a', 'b', 'c'}

data type of set

max() & min()

To find the maximum value and the minimum value of a set,

values = {1, 2, 3, 4, 5, 6}
print("Max of values is ", max(values))
print("Min of values is ", min(values))

maximum minimum value


If any of the values in the set is true (i.e,) Non-Zero , Non-Empty String, False values then it will return True, else False.

data = {0, 'makereading', False}
print(any(data)) # Will return True since it has 'makereading' non empty string.

data = {0, '', False}
print(any(data)) # Will return False since all the values are false.

python any


The all() function returns True if all items in an iterable are true, otherwise it returns False. If the iterable object is empty, the all() function also returns True.

data = {1, 2, 3}
print(all(data)) # True, since all the elements are having true value

data = {1, 2, 0}
print(all(data)) # False, since it has 0

python all

Accessing Elements of Set

Since the set is unordered, we can't access using the index values,

accessing set element

So the ways to access the set are,

  1. for loop

  2. in and not in

1. for loop

fruits = {"apple", "papaya", "banana", "orange"}
for element in fruits:

**output: **

python for

2. in and not in

fruits = {"apple", "papaya", "banana", "orange"}
print("apple" in fruits)
print("orange" not in fruits)

**output: **

python in notin

Adding elements to the set

There are two ways of adding element to the set.

  1. add() - Method to add an element to the set. It takes the immutable item as a parameter to add to the set.

  2. update() - Method to merge an existing set with the mutable and immutable data structures.


The add() method adds an element to the set. If the element already exists, the add() method does not add the element.

data = {1, 2, 3, 4, 5}

print('data', data)

python add


Update() method takes only a single argument. The single argument can be a set, list, tuples or a dictionary. It automatically converts into a set and adds to the set.

With Lists

data = {1, 2, 3, 4, 5}
data.update([11, 10, 12])

python set lists

With Dictionary

data = {1, 2, 3, 4, 5}
data.update({"a":"a", "b":"b", "c":"c"})

python set dict to set

With String

data = {1, 2, 3, 4, 5}

python set update

Removing Items from the Set

We have many methods to delete, remove the items from the set,

  1. remove()

  2. discard()

  3. pop()

  4. del

  5. clear

1. Remove

If the element is present then it will remove, else it will throw error.

**Example 1: **

data = {1, 'python', 'set', 100}

python remove

Example 2:

data = {1, 'python', 'set', 100}

python remove

2. discard()

discard() method is having the same functionality as the remove() method, but it will fail safe. (i.e) Even if the value is not there it wont throw an error.

**Example 1: **

data = {1, 'python', 'set', 100}

python discard

Example 2:

Even if the element 'kuku' is not present, it wont throw an error.

data = {1, 'python', 'set', 100}

python discard

3. pop()

pop() method in set will remove any random element in the set and returns the removed element. Set is unordered, we can specify the index value as list.pop()

fruits = {'apple', 'orange', 'banana'}
removed_element = fruits.pop()
print(removed_element, fruits)

python set pop

4. del

del will delete the object itself.

fruits = {'apple', 'orange', 'banana'}
del fruits

python set - del

5. Clear

Clear will empty the set,

fruits = {'apple', 'orange', 'banana'}

set removal - clear


We can sort the set, using sorted function, but the return type of the sorted is list.

fruits = {"apple", "orange", "lemon", "banana", "papaya"}

sorting python set


We can copy the set using the .copy() method,

fruits = {"apple", "orange", "lemon", "banana", "papaya"}
fruits_2 = fruits.copy()

print(fruits, fruits_2, id(fruits), id(fruits_2)

Copying python

Mathematical Functionalities

Sets are the fundamental property of mathematics. Now as a word of warning, sets, by themselves, seem pretty pointless. But it's only when we apply sets in different situations do they become the powerful building block of mathematics that they are.

Math can get amazingly complicated quite fast. Graph Theory, Abstract Algebra, Real Analysis, Complex Analysis, Linear Algebra, Number Theory, and the list goes on. But there is one thing that all of these share in common: Sets.

During our school days, we might have learned about union, intersection, difference, venn diagrams and more.

Using the python sets, we can achieve the above functionalities,

1. Union


Union of two sets will return all the items present in both sets (all items will be present only once). This can be done with either the | operator or the union() method.

📝 union() will return a new set. It's not inplace change.

set_a = {"apple", "banana", "orange"}
set_b = {"lemon", "jackfruit", "strawberry"}

union_val = set_a.union(set_b)


2. Intersection


The intersection of two sets will return only the common elements in both sets. The intersection can be done using the & operator and intersection() method.

fruits = {"apple", "orange", "banana" }
fav_fruits = {"apple", "jackfruit", "lemon"}

common_fruits = fruits & fav_fruits

common_fruits = fruits.intersection(fav_fruits)


intersection() will return a new set. It's not inplace change.

To have an inplace change, python provides intersection_update functionality, to update the first set.

fruits = {"apple", "orange", "banana" }
fav_fruits = {"apple", "jackfruit", "lemon"}



3. Difference


The difference operation will return the items that are present only in the first set i.e the set on which the method is called. This can be done with the help of the - operator or the difference() method.

fruits = {"apple", "orange", "banana" }
fav_fruits = {"apple", "jackfruit", "lemon"}

result = fruits.difference(fav_fruits)


difference() will return a new set. It's not inplace change.

To have an inplace change, python provides difference_update functionality, to update the first set.

fruits = {"apple", "orange", "banana" }
fav_fruits = {"apple", "jackfruit", "lemon"}



4. Symmetric Difference


The Symmetric difference operation returns the elements that are unique in both sets. This is the opposite of the intersection. This is performed using the ^ operator or by using the symmetric_difference() method.

fruits = {"apple", "orange", "banana" }
fav_fruits = {"apple", "jackfruit", "lemon"}

result = fruits.symmetric_difference(fav_fruits)


symmetric_difference() will return a new set. It's not in place change.

To have an in-place change, python provides symmetric_difference_update functionality, to update the first set.

fruits = {"apple", "orange", "banana" }
fav_fruits = {"apple", "jackfruit", "lemon"}


symmetric difference

5. Disjoint

disjoint set python

Two sets are called disjoint sets if they don't have any element in common, the intersection of sets is a null set.

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


disjoint set

6. subset and superset.

superset and subset

The issuperset() method returns True if a set has every elements of another set (passed as an argument). If not, it returns False. Set X is said to be the superset of set Y if all elements of Y are in X . Here, set B is a superset of set A and A is a subset of set B .

set_a = {1, 2, 3, 4, 5}
set_b = {2, 4, 5}

print(set_a.issuperset(set_b), set_b.issubset(set_a))

superset and subset python


**1: **Add a list of elements to a set, **clue: ** Use a constructor.
**2: **Return a new set of identical items from two sets, **clue: ** Use intersection.
**3: **Get Only unique items from two sets, **clue: ** Use union.
**4: **Update the first set with items that don’t exist in the second set, **clue: ** difference; in place
**5: **Remove items from the set at once, **clue: ** remove, pop, clear
**6: **Return a set of elements present in Set A or B, but not both, **clue: ** symmetric difference
**7: **Check if two sets have any elements in common. If yes, display the common elements, **clue: ** intersection
**8: **Update set1 by adding items from set2, except common items, **clue: ** difference
**9: **Remove items from set1 that are not common to both set1 and set2, **clue: ** intersection update


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