Learning about Python set is another important part when it comes to mastering python programming language. Here is all you need to know.
Python Set
Python Set: Operations on sets
with other sets
Python Set: Intersection
{1, 2, 3, 4, 5}.intersection({3, 4, 5, 6}) # {3, 4, 5}
{1, 2, 3, 4, 5} & {3, 4, 5, 6} # {3, 4, 5}
Python Set: Union
{1, 2, 3, 4, 5}.union({3, 4, 5, 6}) # {1, 2, 3, 4, 5, 6}
{1, 2, 3, 4, 5}  {3, 4, 5, 6} # {1, 2, 3, 4, 5, 6}
Python Set: Difference
{1, 2, 3, 4}.difference({2, 3, 5}) # {1, 4}
{1, 2, 3, 4}  {2, 3, 5} # {1, 4}
Symmetric difference with
{1, 2, 3, 4}.symmetric_difference({2, 3, 5}) # {1, 4, 5}
{1, 2, 3, 4} ^ {2, 3, 5} # {1, 4, 5}
Superset check
{1, 2}.issuperset({1, 2, 3}) # False
{1, 2} >= {1, 2, 3} # False
Subset check
{1, 2}.issubset({1, 2, 3}) # True
{1, 2} <= {1, 2, 3} # True
Disjoint check
{1, 2}.isdisjoint({3, 4}) # True
{1, 2}.isdisjoint({1, 4}) # False
with single elements
Existence check
2 in {1,2,3} # True
4 in {1,2,3} # False
4 not in {1,2,3} # True
Add and Remove s = {1,2,3}
s.add(4) # s == {1,2,3,4}
s.discard(3) # s == {1,2,4}
s.discard(5) # s == {1,2,4}
s.remove(2) # s == {1,4}
s.remove(2) # KeyError!
Set operations return new sets, but have the corresponding inplace versions:
method inplace operation inplace method union s = t update intersection s &= t intersection_update diﬀerence s = t diﬀerence_update
symmetric_diﬀerence s ^= t symmetric_diﬀerence_update
For example:
s = {1, 2}
s.update({3, 4}) # s == {1, 2, 3, 4}
Section 8.2: Get the unique elements of a list
Let’s say you’ve got a list of restaurants — maybe you read it from a file. You care about the unique restaurants in the list. The best way to get the unique elements from a list is to turn it into a set:
restaurants = ["McDonald's", "Burger King", "McDonald's", "Chicken Chicken"]
unique_restaurants = set(restaurants)
print(unique_restaurants)
prints {‘Chicken Chicken’, “McDonald’s”, ‘Burger King’}
Note that the set is not in the same order as the original list; that is because sets are unordered, just like dicts.
This can easily be transformed back into a List with Python’s built in list function, giving another list that is the same list as the original but without duplicates:
list(unique_restaurants)
[‘Chicken Chicken’, “McDonald’s”, ‘Burger King’]
It’s also common to see this as one line:
Removes all duplicates and returns another list list(set(restaurants))
Now any operations that could be performed on the original list can be done again.
Python Set: Set of Sets
{{1,2}, {3,4}}
leads to:
TypeError: unhashable type: 'set'
Instead, use frozenset:
{frozenset({1, 2}), frozenset({3, 4})}
Python Set: Set Operations using Methods and Builtins
We define two sets a and b
a = {1, 2, 2, 3, 4}
b = {3, 3, 4, 4, 5}
NOTE: {1} creates a set of one element, but {} creates an empty dict. The correct way to create an empty set is set().
Intersection
a.intersection(b) returns a new set with elements present in both a and b
a.intersection(b) {3, 4}
Union
a.union(b) returns a new set with elements present in either a and b
a.union(b) {1, 2, 3, 4, 5}
Diﬀerence
a.difference(b) returns a new set with elements present in a but not in b
a.difference(b) {1, 2}
b.difference(a){5}
Symmetric Diﬀerence
a.symmetric_difference(b) returns a new set with elements present in either a or b but not in both
a.symmetric_difference(b) {1, 2, 5}
b.symmetric_difference(a) {1, 2, 5}
NOTE: a.symmetric_difference(b) == b.symmetric_difference(a)
Subset and superset
c.issubset(a) tests whether each element of c is in a.
a.issuperset(c) tests whether each element of c is in a.
c = {1, 2}
c.issubset(a)
True
a.issuperset(c)
True
The latter operations have equivalent operators as shown below:
Method Operator
a.intersection(b) a & b

a.union(b)
a b
a.difference(b) a  b
a.symmetric_difference(b) a ^ b
a.issubset(b) a <= b
a.issuperset(b) a >= b
Disjoint sets
Sets a and d are disjoint if no element in a is also in d and vice versa.
d = {5, 6}
a.isdisjoint(b) # {2, 3, 4} are in both sets False
a.isdisjoint(d)
True
This is an equivalent check, but less efficient
len(a & d) == 0 True
This is even less efficient
a & d == set()
True
Testing membership
The builtin in keyword searches for occurances
1 in a
True
6 in a False
Length
The builtin len() function returns the number of elements in the set
len(a)
4
len(b)
3
Python Set: Sets versus multisets
Sets are unordered collections of distinct elements. But sometimes we want to work with unordered collections of elements that are not necessarily distinct and keep track of the elements’ multiplicities.
Consider this example:
setA = {'a','b','b','c'}
setA
set(['a', 'c', 'b'])
By saving the strings ‘a’, ‘b’, ‘b’, ‘c’ into a set data structure we’ve lost the information on the fact that ‘b’ occurs twice. Of course saving the elements to a list would retain this information
listA = ['a','b','b','c']
listA
['a', 'b', 'b', 'c']
but a list data structure introduces an extra unneeded ordering that will slow down our computations.
For implementing multisets Python provides the Counter class from the collections module (starting from version 2.7):
Python 2.x Version ≥ 2.7
from collections import Counter
counterA = Counter(['a','b','b','c'])
counterA
Counter({'b': 2, 'a': 1, 'c': 1})
Counter is a dictionary where where elements are stored as dictionary keys and their counts are stored as dictionary values. And as all dictionaries, it is an unordered collection.