List and Membership Operators

There are three videos as a part of this page. Be sure to check them out along with the additional helpful reminders!

Lists!

Data structures are containers that organize and group data types together in different ways. A list is one of the most common and basic data structures in Python.

You saw here that you can create a list with square brackets. Lists can contain any mix and match of the data types you have seen so far.

list_of_random_things = [1, 3.4, 'a string', True]

This is a list of 4 elements. All ordered containers (like lists) are indexed in python using a starting index of 0. Therefore, to pull the first value from the above list, we can write:

>>> list_of_random_things[0]
1

It might seem like you can pull the last element with the following code, but this actually won't work:

>>> list_of_random_things[len(list_of_random_things)] 
---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-34-f88b03e5c60e> in <module>()
----> 1 lst[len(lst)]

IndexError: list index out of range

However, you can retrieve the last element by reducing the index by 1. Therefore, you can do the following:

>>> list_of_random_things[len(list_of_random_things) - 1] 
True

Alternatively, you can index from the end of a list by using negative values, where -1 is the last element, -2 is the second to last element and so on.

>>> list_of_random_things[-1] 
True
>>> list_of_random_things[-2] 
a string

Slice and Dice with Lists

You saw that we can pull more than one value from a list at a time by using slicing . When using slicing, it is important to remember that the lower index is inclusive and the upper index is exclusive .

Therefore, this:

>>> list_of_random_things = [1, 3.4, 'a string', True]
>>> list_of_random_things[1:2]
[3.4]

will only return 3.4 in a list. Notice this is still different than just indexing a single element, because you get a list back with this indexing. The colon tells us to go from the starting value on the left of the colon up to, but not including, the element on the right.

If you know that you want to start at the beginning, of the list you can also leave out this value.

>>> list_of_random_things[:2]
[1, 3.4]

or to return all of the elements to the end of the list, we can leave off a final element.

>>> list_of_random_things[1:]
[3.4, 'a string', True]

This type of indexing works exactly the same on strings, where the returned value will be a string.

Are you in OR not in ?

You saw that we can also use in and not in to return a bool of whether an element exists within our list, or if one string is a substring of another.

>>> 'this' in 'this is a string'
True
>>> 'in' in 'this is a string'
True
>>> 'isa' in 'this is a string'
False
>>> 5 not in [1, 2, 3, 4, 6]
True
>>> 5 in [1, 2, 3, 4, 6]
False

Mutability and Order

Mutability is about whether or not we can change an object once it has been created. If an object (like a list or string) can be changed (like a list can), then it is called mutable . However, if an object cannot be changed without creating a completely new object (like strings), then the object is considered immutable .

>>> my_lst = [1, 2, 3, 4, 5]
>>> my_lst[0] = 'one'
>>> print(my_lst)
['one', 2, 3, 4, 5]

As shown above, you are able to replace 1 with 'one' in the above list. This is because lists are mutable .

However, the following does not work:

>>> greeting = "Hello there"
>>> greeting[0] = 'M'

This is because strings are immutable . This means to change this string, you will need to create a completely new string.

There are two things to keep in mind for each of the data types you are using:

1. Are they mutable ?
2. Are they ordered ?

** Order** is about whether the position of an element in the object can be used to access the element. ** Both strings and lists are ordered.** We can use the order to access parts of a list and string.

However, you will see some data types in the next sections that will be unordered. For each of the upcoming data structures you see, it is useful to understand how you index, are they mutable, and are they ordered. Knowing this about the data structure is really useful!

Additionally, you will see how these each have different methods, so why you would use one data structure vs. another is largely dependent on these properties, and what you can easily do with it!