3.3. Sequence Set¶

3.3.1. Rationale¶

Only unique values

Mutable - can add, remove, and modify items

Can store elements of any hashable types

3.3.2. Type Definition¶

Set is unordered data structure (each time order differs)

Do not record element position

Do not record order of insertion

Do not support getitem

Do not support slice

Defining only with set() - no short syntax

Comma after last element of a one element set is optional

Brackets are required

Listing 3.5. set type definition¶

data = set()

data = {1}
data = {1, 2, 3}
data = {1.1, 2.2, 3.3}
data = {True, False}
data = {'a', 'b', 'c'}
data = {'a', 1, 2.2, True, None}

Listing 3.6. set stores only unique values.¶

{1, 2, 1}                       # {1, 2}
{1, 2, 'a'}                     # {1, 2, 'a'}
{1, 2, (3, 4)}                  # {1, 2, (3, 4)}
{1, 2, [3, 4]}                  # TypeError: unhashable type: 'list'
{1, 2, {3, 4}}                  # TypeError: unhashable type: 'set'
{1, 2, frozenset({3, 4})}       # {1, 2, frozenset({3, 4})}

Listing 3.7. set compares by values, not types¶

{1}                             # {1}
{1.0}                           # {1.0}
{1, 1.0}                        # {1}
{1.0, 1}                        # {1.0}

3.3.3. Type Casting¶

set() converts argument to set

data = [1, 2, 3]
set(data)
# {1, 2, 3}

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

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

data = frozenset({1, 2, 3})
set(data)
# {1, 2, 3}

3.3.4. Deduplicate¶

Works with tuple, list, str

data = [1,2,3,1,1,2,4]

set(data)
# {1, 2, 3, 4}

Listing 3.8. Converting set deduplicate items¶

data = [
    'Twardowski',
    'Twardowski',
    'Watney',
    'Twardowski'
]

set(data)
# {'Twardowski', 'Watney'}

3.3.5. Add¶

data = {1, 2}

data.add(3)
# {1, 2, 3}

data.add(3)
# {1, 2, 3}

data.add(4)
# {1, 2, 3, 4}

data = {1, 2}
data.add([3, 4])
# TypeError: unhashable type: 'list'

data = {1, 2}
data.add((3, 4))
# {1, 2, (3, 4)}

data = {1, 2}
data.add({3, 4})
# TypeError: unhashable type: 'set'

data = {1, 2}
data.add(frozenset({3,4}))
# {frozenset({3, 4}), 1, 2}

3.3.6. Update¶

data = {1, 2}
# {1, 2}

data.update({3, 4})
# {1, 2, 3, 4}

data.update([5, 6])
# {1, 2, 3, 4, 5, 6}

data.update((7, 8))
# {1, 2, 3, 4, 5, 6, 7, 8}

3.3.7. Pop¶

Gets and remove items

data = {1, 2, 3}

value = data.pop()

print(data)
# {1, 2}

print(value)
# 3

3.3.8. Membership¶

3.3.8.1. Is Disjoint?¶

True - if there are no common elements in data and x

False - if any x element are in data

data = {1,2}

data.isdisjoint({1,2})     # False
data.isdisjoint({1,3})     # False
data.isdisjoint({3,4})     # True

3.3.8.2. Is Subset?¶

True - if x has all elements from data

False - if x don't have element from data

data = {1,2}

data.issubset({1})          # False
data.issubset({1,2})        # True
data.issubset({1,2,3})      # True
data.issubset({1,3,4})      # False

{1,2} < {3,4}               # False
{1,2} < {1,2}               # False
{1,2} < {1,2,3}             # True
{1,2,3} < {1,2}             # False

{1,2} <= {3,4}              # False
{1,2} <= {1,2}              # True
{1,2} <= {1,2,3}            # True
{1,2,3} <= {1,2}            # False

3.3.8.3. Is Superset?¶

True - if data has all elements from x

False - if data don't have element from x

data = {1,2}

data.issuperset({1})        # True
data.issuperset({1,2})      # True
data.issuperset({1,2,3})    # False
data.issuperset({1,3})      # False
data.issuperset({2,1})      # True

{1,2} > {1,2}               # False
{1,2} > {1,2,3}             # False
{1,2,3} > {1,2}             # True

{1,2} >= {1,2}              # True
{1,2} >= {1,2,3}            # False
{1,2,3} >= {1,2}            # True

3.3.9. Basic Operations¶

3.3.9.1. Union¶

returns sum of elements from data and x

data = {1,2}

data.union({1,2})           # {1, 2}
data.union({1,2,3})         # {1, 2, 3}
data.union({1,2,4})         # {1, 2, 4}
data.union({1,3}, {2,4})    # {1, 2, 3, 4}

{1,2} | {1,2}               # {1, 2}
{1,2,3} | {1,2}             # {1, 2, 3}
{1,2,3} | {1,2,4}           # {1, 2, 3, 4}
{1,2} | {1,3} | {2,4}       # {1, 2, 3, 4}

3.3.9.2. Difference¶

returns elements from data which are not in x

data = {1,2}

data.difference({1,2})          # set()
data.difference({1,2,3})        # set()
data.difference({1,4})          # {2}
data.difference({1,3}, {2,4})   # set()
data.difference({3,4})          # {1, 2}

{1,2} - {2,3}                   # {1}
{1,2} - {2,3} - {3}             # {1}
{1,2} - {1,2,3}                 # set()

3.3.9.3. Symmetric Difference¶

returns elements from data and x, but without common

data = {1,2}

data.symmetric_difference({1,2})           # set()
data.symmetric_difference({1,2,3})         # {3}
data.symmetric_difference({1,4})           # {2, 4}
data.symmetric_difference({1,3}, {2,4})    # TypeError: symmetric_difference() takes exactly one argument (2 given)
data.symmetric_difference({3,4})           # {1, 2, 3, 4}

{1,2} ^ {1,2}               # set()
{1,2} ^ {2,3}               # {1, 3}
{1,2} ^ {1,3}               # {2, 3}

3.3.9.4. Intersection¶

common element from in data and x

data = {1,2}

data.intersection({1,2})           # {1, 2}
data.intersection({1,2,3})         # {1, 2}
data.intersection({1,4})           # {1}
data.intersection({1,3}, {2,4})    # set()
data.intersection({1,3}, {1,4})    # {1}
data.intersection({3,4})           # set()

{1,2} & {2,3}                       # {2}
{1,2} & {2,3} & {2,4}               # {2}
{1,2} & {2,3} & {3}                 # set()

3.3.10. Cardinality¶

data = {1, 2, 3}

len(data)
# 3

3.3.11. Assignments¶

3.3.11.1. Sequence Set Create¶

Complexity level: easy
Lines of code to write: 3 lines
Estimated time of completion: 3 min
Solution: solution/sequence_set_create.py

English

Create set result with elements:
- 'a'
- 1
- 2.2
Print result
Print number of elements in result

Polish

Stwórz zbiór result z elementami:
- 'a'
- 1
- 2.2
Wypisz result
Wypisz liczbę elementów result

3.3.11.2. Sequence Set Many¶

Complexity level: easy
Lines of code to write: 9 lines
Estimated time of completion: 8 min
Solution: solution/sequence_set_many.py

English

Use data from "Input" section (see below)
Create set result representing first row
Values from second row add to set using .add()
From third row create set and add it to result using .update()
From fourth row create tuple and add it to result using .update()
From fifth row create list and add it to result using .update()
Print result
Compare result with "Output" section (see below)

Polish

Użyj danych z sekcji "Input" (patrz poniżej)
Stwórz zbiór result reprezentujący pierwszy wiersz
Wartości z drugiego wiersza dodawaj do result używając .add()
Na podstawie trzeciego wiersza stwórz set i dodaj go do result używając .update()
Na podstawie czwartego wiersza stwórz tuple i dodaj go do result używając .update()
Na podstawie piątego wiersza stwórz list i dodaj go do result używając .update()
Wypis result
Porównaj wyniki z sekcją "Output" (patrz poniżej)

Input

Table 3.2. Input data¶
Row	Sepal length	Sepal width	Petal length	Petal width
1	5.8	2.7	5.1	1.9
2	5.1	3.5	1.4	0.2
3	5.7	2.8	4.1	1.3
4	6.3	2.9	5.6	1.8
5	6.4	3.2	4.5	1.5

Output

result: set
# {0.2, 1.9, 2.7, 3.5, 1.4, 5.8, 5.1, 1.3, 2.8, 4.1, 5.7, 6.3, 5.6, 6.4, 1.5, 4.5, 3.2, 1.8, 2.9}

The whys and wherefores

Defining set
Basic set methods