Let’s start with a few examples first. Take your time to study these examples carefully.

Gryffindors = {"Harry", "Ron", "Hermine", "Neville", "Seamus", "Ginny", "Fred", "George"}## Set ConversionWeasleys = set(["Ron", "Ginny", "Fred"])# {'Ron', 'Fred', 'Ginny'}## Add ElementWeasleys.add("George")# {'Ron', 'Fred', 'Ginny', 'George'}## Remove ElementGryffindors.remove("Neville")# {'Ron', 'Hermine', 'George', 'Harry', 'Ginny', 'Seamus', 'Fred'}## Membership'Ginny' in Gryffindors# True## Sizelen(Weasleys)# 4## IntersectionWeasleys & Gryffindors# {'Fred', 'George', 'Ron', 'Ginny'}## UnionWeasleys | Gryffindors# {'Ron', 'Hermine', 'George', 'Harry', 'Ginny', 'Seamus', 'Fred'}## DifferenceGryffindors - Weasleys# {'Harry', 'Hermine', 'Seamus'}## Symmetric DifferenceGryffindors ^ {'Harry', 'Ginny', 'Malfoy'}# {'Ron', 'Fred', 'George', 'Malfoy', 'Hermine', 'Seamus'}## Set DisjointGryffindors.isdisjoint({'Malfoy', 'Grabbe', 'Goyle'})# True## SubsetWeasleys.issubset(Gryffindors)# True## SupersetGryffindors.issuperset(Weasleys)## Popprint(Gryffindors.pop())# 'Seamus'print(Gryffindors)# {'Ron', 'Fred', 'Hermine', 'Harry', 'Seamus', 'George'}

In the next few paragraphs, I give you detailed examples of the most important set operations (see docs).

Set Conversion

Sets are collections like tuples or lists. That’s why you can easily convert sets in lists or tuples. Here is how:

# convert list to set:s = set([1,2,3])print(s)# {1, 2, 3}# convert tuple to set:s = set((1,2,3))print(s)# {1, 2, 3}

Note that the Python interpreter uses the bracket notation to represent a set on your console.

Add an Element

Use the set function s.add(x) to add element x to the set s. Here is an example:

# Add Operators = set()s.add("Harry")s.add("Ron")s.add("Hermine")print(s)# {'Harry', 'Ron', 'Hermine'}

Remove an Element

Use the set function s.remove(x) to remove element x from set s. Note that because the set is duplicate-free, it is impossible that element x still exists in the set after calling remove(). In this way, the semantics are different than for Python lists where remove() only removes the first occurrence of the element in the list.

Here is an example:

# Remove Operators = set()s.add("Harry")s.add("Ron")s.add("Hermine")print(s)# {'Harry', 'Ron', 'Hermine'}s.remove("Ron")s.remove("Harry")print(s)# {'Hermine'}

Membership

The membership operator “x in s” checks whether set s contains element x. It returns True if this is the case. Here is an example:

# Membership Operators = {"Harry", "Ron", "Hermine"}x = "Ginny"print(x in s)# False

Number of Elements in a Set

Simply use the built-in len(s) function to get the number of elements in the set s.

Here is an example:

# Size Operators = {"Harry", "Ron", "Hermine"}print(len(s))# 3

Intersect Two Sets

The set intersection operator creates a new set which contains all elements that are in both sets s1 and s2 -- but not the ones that are only in one set. This means that the new set will never be larger than any of the sets s1 or s2.

There are two operators in Python to intersect two sets s1 and s2: the function s1.intersect(s2) or the operator s1 & s2.

Maybe you remember Venn diagrams from school? Here is an example of set intersection:

As you can see, the new set contains all elements that are in both sets s1 and s2.

Here is an example in code:

# Intersectiongood = {"Harry", "Ron", "Snape"}bad = {"Lord V", "Quirrell", "Snape"}print(good & bad)# {'Snape'}print(good.intersection(bad))# {'Snape'}

Union of Two Sets

The set union operator creates a new set which contains all elements that are in either set s1 or s2. This means that the new set will never be smaller than any of the sets s1 or s2.

There are two operators in Python to calculate the union of two sets s1 and s2: the function s1.union(s2) or the operator s1 | s2.

# Uniongood = {"Harry", "Ron", "Snape"}bad = {"Lord V", "Quirrell", "Snape"}print(good | bad)# {'Lord V', 'Quirrell', 'Snape', 'Harry', 'Ron'}print(good.union(bad))# {'Lord V', 'Quirrell', 'Snape', 'Harry', 'Ron'}

Difference of Two Sets

The set difference operator creates a new set which contains all elements that are in set s1 but not in s2. This means that the new set will never be larger than set s1.

There are two operators in Python to calculate the difference of two sets s1 and s2: the function s1.difference(s2) or the operator s1 - s2.

# Differencegood = {"Harry", "Ron", "Snape"}bad = {"Lord V", "Quirrell", "Snape"}print(good - bad)# {'Harry', 'Ron'}print(good.difference(bad))# {'Harry', 'Ron'}

Symmetric Difference of Two Sets

The symmetric set difference operator creates a new set which contains all elements that are in either set s1 or in s2 but not in the intersection of s1 and s2.

There are two operators in Python to calculate the difference of two sets s1 and s2: the function s1.difference(s2) or the operator s1 - s2.

# Symmetric Differencegood = {"Harry", "Ron", "Snape"}bad = {"Lord V", "Quirrell", "Snape"}print(good ^ bad)# {'Quirrell', 'Ron', 'Harry', 'Lord V'}print(good.symmetric_difference(bad))# {'Quirrell', 'Ron', 'Harry', 'Lord V'}print(bad.symmetric_difference(good))# {'Quirrell', 'Ron', 'Lord V', 'Harry'}

Set Disjoint

The set disjoint operation checks for two given sets s1 and s2 whether they have no elements in common.

# Set Disjoint Operationgood = {"Harry", "Ron", "Snape"}bad = {"Lord V", "Quirrell", "Snape"}print(good.isdisjoint(bad))# Falseprint(bad.isdisjoint(good))# Falsebad.remove("Snape")print(good.isdisjoint("Snape"))# True

As you can see, the good and the bad in Harry Potter are not disjoint because “Snape” is both - good AND bad. However, after removing “Snape” from the set of bad wizards (SPOILER ALERT), they become disjoint again.

Subset

The operation s1.issubset(s2) in Python checks whether all elements in set s1 are also elements in set s2. Of course, set s2 can have much more elements that are not in set s1.

# Set Subset OperationGryffindors = {"Seamus", "Fred", "George", "Harry", "Ginny", "Hermine"}Weasleys = {"Fred", "George", "Ginny"}print(Weasleys.issubset(Gryffindors))# Trueprint(Gryffindors.issubset(Weasleys))# False

While the set of all Weasleys is a subset of the set of all Gryffindors, the other way does not hold -- there are (still) Gryffindors that are not Weasleys (e.g. “Harry” and “Hermine”).

Superset

The operation s1.issuperset(s2) in Python is analogous to the previous operation issubset(). But in contrast to that, it checks whether all elements in set s2 are also elements in set s1. Of course, set s1 can have much more elements that are not in set s2.

# Set Superset OperationGryffindors = {"Seamus", "Fred", "George", "Harry", "Ginny", "Hermine"}Weasleys = {"Fred", "George", "Ginny"}print(Weasleys.issuperset(Gryffindors))# Falseprint(Gryffindors.issuperset(Weasleys))# True

Clearly, the set of all Weasleys is NOT a superset of the set of all Gryffindors (e.g. “Harry” is not a Weasley). However, the set of all Gryffindors is a superset of the set of all Weasleys.

Pop a Set Element

The s.pop() operation removes an arbitrary element x from the set s. It returns this element x. The pop() operation is often useful because you cannot easily access an arbitrary element of a set -- you cannot use indices on Python sets because sets are unordered.

Here is an example:

# Set Pop Operationteachers = {"Trelawney", "Snape", "Hagrid"}leaves_hogwarts = teachers.pop()print(teachers)# e.g. {'Snape', 'Hagrid'}

Remember when Professor Umbridge controlled each and every teacher in Hogwarts? She quickly found out that Professor Trelawney is not a suitable teacher, so she kicked her out from the set of all teachers. Essentially, she performed the pop() operation (although selecting an element from the set was less random).

The Ultimate Guide to Sets in Python

Course Structure

What Is A Set?

How to ​Create a Set?

[Overview] What ​Are the ​Most ​Important ​Set ​Operations in Python?

How Does ​Set ​Comprehension ​Work?

Python Sets vs Lists​

How to Create a Set?

[Overview] What Are the Most Important Set Operations in Python?

How Does Set Comprehension Work?

Python Sets vs Lists