Lists in Python#

Goals of this lecture#

The primary goal of today’s lecture is to give you a basic familiarity with lists in Python. This includes:

  • A high-level understanding of what a list is and how it fits into the broader ecosystem of Python collections.

  • How do you create a list?

  • Indexing into lists.

  • Looping through lists.

  • List comprehension.

  • Checking if an item is in a list.

What a list?#

A list is a mutable collection of ordered items, which can have various types.

Let’s break this down:

  • Mutable: a list object can be changed.

  • Collection: i.e., a list can contain multiple items (unlike, say, an int).

  • Ordered: these items have a particular order, i.e., it’s a sequence. (We’ll later discuss objects like dictionaries that don’t have order.)

  • Various types: i.e., a list can have objects belonging to different types, such as an int, a str, and even another list!

How do you create a list?#

A list is created with square brackets, i.e., [].

### This is an empty list
my_first_list = []
print(my_first_list)
print(type(my_first_list))

[]
<class 'list'>

You can put objects into the list by separating them with commas.

## This list has an int and several strings.
assorted_objects = ["apple", 1, "class", "library"]
assorted_objects

['apple', 1, 'class', 'library']

Check-in#

Use the square brackets operator to create a list called sample_list. Put exactly three items in this list (they can be of any type you prefer).

### Your code here

Check-in#

Now, double-check your work by using len to calculate the length of sample_list. Does it return the value 3? If not, there are either too few or too many items.

### Your code here

Indexing into a list#

Indexing means returning the item at a particular position in a list.

You can index into a list using square brackets.

assorted_objects[0]

'apple'

assorted_objects[1]

1

assorted_objects[2]

'class'

Check-in#

Try indexing into assorted_objects with the number 4. What happens? Why?

### Your code here

Counting backward#

The index [-1] retrieves the final item on a list. Thus, you can use this syntax to “count backwards” from the end of a list.

print(assorted_objects)

['apple', 1, 'class', 'library']

### Last object
assorted_objects[-1]

'library'

### Second-to-last object
assorted_objects[-2]

'class'

Slicing#

Just as we can slice into a str (i.e., retrieve multiple characters between a span of indices), we can do the same for a list.

my_long_list = ["this", "is", "a", "set", "of", "words", "I", "made", "up"]
my_long_list[0:4]

['this', 'is', 'a', 'set']

my_long_list[4:8]

['of', 'words', 'I', 'made']

Interim summary: indexing#

  • Python indexing starts at zero.

  • The final element of a sequence can be retrieved with [-1].

  • Multiple adjacent elements can be retrieved with [start:stop].

    • This will include the element at start, but not the one at stop.

Check-in#

Consider my_long_list below. How would you return the sub-list ["words", "I", "made", "up"]?

my_long_list = ["this", "is", "a", "set", "of", "words", "I", "made", "up"]
### Your code here

Looping through a list#

We’ve already discussed loops, so this will serve as a brief review/reminder.

There are two main ways of looping through a list:

  • for loop.

  • while loop.

for loops#

A for loop will iterate through each item in a sequence, such as list.

core_courses = ['CSS 1', 'CSS 2', 'CSS 100']
for course in core_courses:
    print(course)

CSS 1
CSS 2
CSS 100

while loops#

A while loop will continue running as long as some condition is met.

A common formulation is to use an index to loop through the elements of a list, which runs into the index reaches the len of the list.

i = 0
while i < len(core_courses):
    print(core_courses[i])
    i += 1 ## Make sure to increase index!

CSS 1
CSS 2
CSS 100

enumerate#

The enumerate function allows you to iterate through a list, as in a for loop, but it also tracks an index.

for index, item in enumerate(core_courses):
    print(index)
    print(item)

0
CSS 1
1
CSS 2
2
CSS 100

List “comprehensions”#

In Python, a list comprehension is a shorter, more efficient way to loop through a list (and possibly apply some function to each element of a list).

Examples:

  • Multiply each number in a list by 2.

  • Make each str in a list lowercase.

A list comprehension will return another list, which has been modified in some way.

### The simplest list comprehension simply returns every element in a list
original_list = ["This", "is", "CSS", "1"]
new_list = [i for i in original_list]
new_list

['This', 'is', 'CSS', '1']

Check-in (conceptual)#

What do you notice about the syntax of a list comprehension? Does it remind you of any other technique we’ve discussed?

Modifying elements of a list#

You can also use a list comprehension to modify elements of a list.

In the code below, the list comprehension returns the elements of the original 1ist, but converts them all to uppercase.

### Make everything upper-case.
original_list = ["This", "is", "CSS", "1"]
new_list = [i.upper() for i in original_list]
new_list

['THIS', 'IS', 'CSS', '1']

Using conditions#

You can also conditionally modify (or conditionally return) elements of a list using a list comprehension.

### List of foods
foods = ["pasta", "pizza", "sushi", "curry", "rice"]
### Return only foods with letter "i"
foods_with_i = [food for food in foods if "i" in food]
foods_with_i

['pizza', 'sushi', 'rice']

Check-in#

The list below contains both int and str objects. Use a list comprehension to multiply each int by 2, and ignore the str objects.

### List of objects
assorted_list = [1, 5, "bottle", 10, "bag"]
### Your code here

Check-in#

The list below contains both int and str objects. Now, use a list comprehension to turn each str into an upper-case string, and ignore the int objects.

### List of objects
assorted_list = [1, 5, "bottle", 10, "bag"]
### Your code here

Checking membership#

The in operator can be used to check if a given item occurs in a particular list. It returns a boolean answer (i.e., True or False).

Note that this can be used with strings as well.

"CSS 1" in core_courses

True

"COGS 14B" in core_courses

False

Check-in#

Consider my_long_list below. How would you check whether the str "words" appears in that list?

my_long_list = ["this", "is", "a", "set", "of", "words", "I", "made", "up"]
### Your code here

Conclusion#

This was a brief introduction to list objects. The lab this week will contain many more examples and practice problems; additionally, next week we’ll talk about some more complex operations, such as combining lists, appending items to a list, and more.