Lists are one of the 4 data types in Python used to store collections of data. A short comparison of the containers is shown below:

Feature	List	Tuple	Dictionary	Set
Mutable (Can be modified in place)	Yes	No	Yes (keys are immutable)	Yes
Iterable (Can be use in for loop)	Yes	Yes	Yes	Yes
Ordered (Can access by index, slicing)	Yes	Yes	No	No
Duplicate Values	Allowed	Allowed	Not in keys	Not allowed

Lists

Getting values with indexes

>>> furniture = ['table', 'chair', 'rack', 'shelf']

>>> furniture[0]
# 'table'

>>> furniture[1]
# 'chair'

>>> furniture[2]
# 'rack'

>>> furniture[3]
# 'shelf'

Negative indexes

>>> furniture = ['table', 'chair', 'rack', 'shelf']

>>> furniture[-1]
# 'shelf'

>>> furniture[-3]
# 'chair'

>>> f'The {furniture[-1]} is bigger than the {furniture[-3]}'
# 'The shelf is bigger than the chair'

Getting sublists with Slices

>>> furniture = ['table', 'chair', 'rack', 'shelf']

>>> furniture[0:4]
# ['table', 'chair', 'rack', 'shelf']

>>> furniture[1:3]
# ['chair', 'rack']

>>> furniture[0:-1]
# ['table', 'chair', 'rack']

>>> furniture[:2]
# ['table', 'chair']

>>> furniture[1:]
# ['chair', 'rack', 'shelf']

>>> furniture[:]
# ['table', 'chair', 'rack', 'shelf']

Slicing the complete list will perform a copy:

>>> spam2 = spam[:]
# ['cat', 'bat', 'rat', 'elephant']

>>> spam.append('dog')
>>> spam
# ['cat', 'bat', 'rat', 'elephant', 'dog']

>>> spam2
# ['cat', 'bat', 'rat', 'elephant']

Getting a list length with len()

>>> furniture = ['table', 'chair', 'rack', 'shelf']
>>> len(furniture)
# 4

Changing values with indexes

>>> furniture = ['table', 'chair', 'rack', 'shelf']

>>> furniture[0] = 'desk'
>>> furniture
# ['desk', 'chair', 'rack', 'shelf']

>>> furniture[2] = furniture[1]
>>> furniture
# ['desk', 'chair', 'chair', 'shelf']

>>> furniture[-1] = 'bed'
>>> furniture
# ['desk', 'chair', 'chair', 'bed']

Concatenation and Replication

>>> [1, 2, 3] + ['A', 'B', 'C']
# [1, 2, 3, 'A', 'B', 'C']

>>> ['X', 'Y', 'Z'] * 3
# ['X', 'Y', 'Z', 'X', 'Y', 'Z', 'X', 'Y', 'Z']

>>> my_list = [1, 2, 3]
>>> my_list = my_list + ['A', 'B', 'C']
>>> my_list
# [1, 2, 3, 'A', 'B', 'C']

Using for loops with Lists

>>> furniture = ['table', 'chair', 'rack', 'shelf']

>>> for item in furniture:
...     print(item)
# table
# chair
# rack
# shelf

Getting the index in a loop with enumerate()

>>> furniture = ['table', 'chair', 'rack', 'shelf']

>>> for index, item in enumerate(furniture):
...     print('index', index, '- item:', item)
# index: 0 - item: table
# index: 1 - item: chair
# index: 2 - item: rack
# index: 3 - item: shelf

Loop in Multiple Lists with zip() (Optional)

>>> furniture = ['table', 'chair', 'rack', 'shelf']
>>> price = [100, 50, 80, 40]

>>> for item, amount in zip(furniture, price):
...     print(f'The {item} costs ${amount}')
# The table costs $100
# The chair costs $50
# The rack costs $80
# The shelf costs $40

The in and not in operators

>>> 'rack' in ['table', 'chair', 'rack', 'shelf']
# True

>>> 'bed' in ['table', 'chair', 'rack', 'shelf']
# False

>>> 'bed' not in furniture
# True

>>> 'rack' not in furniture
# False

The Multiple Assignment (Unpacking) Trick

The multiple assignment trick is a shortcut that lets you assign multiple variables with the values in a list in one line of code. So instead of doing this:

>>> furniture = ['table', 'chair', 'rack', 'shelf']
>>> table = furniture[0]
>>> chair = furniture[1]
>>> rack = furniture[2]
>>> shelf = furniture[3]

You could type this line of code:

>>> furniture = ['table', 'chair', 'rack', 'shelf']
>>> table, chair, rack, shelf = furniture

>>> table
# 'table'

>>> chair
# 'chair'

>>> rack
# 'rack'

>>> shelf
# 'shelf'

The multiple assignment trick can also be used to swap the values in two variables:

>>> a, b = 'table', 'chair'
>>> a, b = b, a
>>> print(a)
# chair

>>> print(b)
# table

The index() Method

The index method allows you to find the index of a value by passing its name:

>>> furniture = ['table', 'chair', 'rack', 'shelf']
>>> furniture.index('chair')
# 1

Adding Values

append()

append adds an element to the end of a list:

>>> furniture = ['table', 'chair', 'rack', 'shelf']
>>> furniture.append('bed')
>>> furniture
# ['table', 'chair', 'rack', 'shelf', 'bed']

insert()

insert adds an element to a list at a given position:

>>> furniture = ['table', 'chair', 'rack', 'shelf']
>>> furniture.insert(1, 'bed')
>>> furniture
# ['table', 'bed', 'chair', 'rack', 'shelf']

Removing Values

del

del removes an item using the index:

>>> furniture = ['table', 'chair', 'rack', 'shelf']
>>> del furniture[2]
>>> furniture
# ['table', 'chair', 'shelf']

>>> del furniture[2]
>>> furniture
# ['table', 'chair']

remove()

remove removes an item with using actual value of it:

>>> furniture = ['table', 'chair', 'rack', 'shelf']
>>> furniture.remove('chair')
>>> furniture
# ['table', 'rack', 'shelf']

If the value appears multiple times in the list, only the first instance of the value will be removed.

Sorting values with sort()

>>> numbers = [2, 5, 3.14, 1, -7]
>>> numbers.sort()
>>> numbers
# [-7, 1, 2, 3.14, 5]

furniture = ['table', 'chair', 'rack', 'shelf']
furniture.sort()
furniture
# ['chair', 'rack', 'shelf', 'table']

You can also pass True for the reverse keyword argument to have sort() sort the values in reverse order:

>>> furniture.sort(reverse=True)
>>> furniture
# ['table', 'shelf', 'rack', 'chair']

By default, string are sorted using ASCII order and if you need to sort the values in regular alphabetical order, pass str.lower for the key keyword argument in the sort() method call:

>>> letters = ['a', 'z', 'A', 'Z']
>>> letters.sort(key=str.lower)
>>> letters
# ['a', 'A', 'z', 'Z']

You can use the built-in function sorted to return a new list:

>>> furniture = ['table', 'chair', 'rack', 'shelf']
>>> sorted(furniture)
# ['chair', 'rack', 'shelf', 'table']

Numerical functions

There are a number of built-in functions that can be used on lists that allow you to quickly look through a list without writing your own loops:

>>> nums = [3, 41, 12, 9, 74, 15]
>>> print(max(nums))
>>> print(min(nums))
>>> print(sum(nums))
# 74
# 3
# 154

Comprehension (Like the set-builder notation)

List Comprehensions are a special kind of syntax that let us create lists out of other lists, and are incredibly useful when dealing with numbers and with one or two levels of nested for loops.

This is how we create a new list from an existing collection with a For Loop:

>>> names = ['Charles', 'Susan', 'Patrick', 'George']

>>> new_list = []
>>> for n in names:
...     new_list.append(n)
...
>>> new_list
# ['Charles', 'Susan', 'Patrick', 'George']

And this is how we do the same with a List Comprehension:

>>> names = ['Charles', 'Susan', 'Patrick', 'George']

>>> new_list = [n for n in names]
>>> new_list
# ['Charles', 'Susan', 'Patrick', 'George']

We can do the same with numbers:

>>> n = [(a, b) for a in range(1, 3) for b in range(1, 3)]
>>> n
# [(1, 1), (1, 2), (2, 1), (2, 2)]

Adding conditionals

If we want new_list to have only the names that start with C, with a for loop, we would do it like this:

>>> names = ['Charles', 'Susan', 'Patrick', 'George', 'Carol']

>>> new_list = []
>>> for n in names:
...     if n.startswith('C'):
...         new_list.append(n)
...
>>> print(new_list)
# ['Charles', 'Carol']

In a List Comprehension, we add the if statement at the end:

>>> new_list = [n for n in names if n.startswith('C')]
>>> print(new_list)
# ['Charles', 'Carol']

To use an if-else statement in a List Comprehension:

>>> nums = [1, 2, 3, 4, 5, 6]
>>> new_list = [num*2 if num % 2 == 0 else num for num in nums]
>>> print(new_list)
# [1, 4, 3, 8, 5, 12]

Note that most of the time method will modify list in place, while function will create a new list

Tuples

The Tuple data type

The key difference between tuples and lists is that, while tuples are immutable objects, lists are mutable. This means that tuples cannot be changed while the lists can be modified. Tuples are more memory efficient than the lists.

>>> furniture = ('table', 'chair', 'rack', 'shelf')

>>> furniture[0]
# 'table'

>>> furniture[1:3]
# ('chair', 'rack')

>>> len(furniture)
# 4

The main way that tuples are different from lists is that tuples, like strings, are immutable.

Converting between list() and tuple()

>>> tuple(['cat', 'dog', 5])
# ('cat', 'dog', 5)

>>> list(('cat', 'dog', 5))
# ['cat', 'dog', 5]

>>> list('hello')
# ['h', 'e', 'l', 'l', 'o']

Keywords

• containers (容器): Structures that hold or organize multiple values, such as lists, tuples, and strings.
• methods (方法): Functions that are associated with an object and can be called on that object.
• sequence (序列): An ordered collection of items, where each item can be accessed by its position (index).
• list (串列): A mutable sequence type in Python that can store a collection of items with different data types.
• tuple (元組): An immutable sequence type in Python that can store a collection of items with different data types.
• elements (元素): The individual items or values contained within a container like a list or tuple.
• index (索引): The numerical position of an element within a sequence, starting from 0.
• subscript operator (下標運算子): The square brackets ([]) used to access elements in a container by index.
• slicing (切片): A method to retrieve a subset of a sequence by specifying a start, stop, and optionally a step.
• mutable (可變的): Describes an object that can be changed after it is created, like a list.
• item assignment (元素賦值): The process of changing the value of an element within a mutable container using its index.
• iteration by item (逐項迭代): The process of going through each element in a container one at a time.
• list comprehension (串列生成式): A concise way to create lists by applying an expression to each item in a sequence.
• immutable (不可變的): Describes an object that cannot be changed after it is created, like a tuple or string.
• reference (參照): A variable in Python stores a reference, which is the memory address of an object. It points to where the object is stored rather than containing the object itself.
• modify in-place (原地修改): Changing the content of a mutable object without creating a new object.