Python data structures#
Materials:#
Going over the fundmentals, we learned how to store numbers and sets of
characters as variables. Python also has built-in ways to store multiple
strings and numbers, namely lists, tuples, dictionaries, and
sets. These all allow you to groups of ints, floats, and strings in
different arrangements. Here, we created a list of 5 ints called
x.
x = [ 1, 2, 3, 4, 5 ] # integers 1 - 5
Here are brief descriptions of the four structures.
Lists: store data in a specific order
Dictionaries: store combinations of keys and values without any order
Tuples: store data in a specific order and cannot be altered
Sets: store unordered data
We will dive into these in more detail below, focusing primarily on lists and dictionaries.
Lists#
Lists are very common tools in Python. They allow us to store large amounts of data with an order. They come with very handy tools to reference different objects stored in them. We can also easily add items to them.
Initialize a list#
There are two ways of initializing an empty list: list() and [].
# these do the same thing
my_list = list()
your_list = []
To make a list with pre-populated with items, we can fill the brackets with comma-separated values.
number_list = [ 0.1, 0.2, 0.3, 0.4 ] # lists can hold numbers
string_list = [ 'cat', 'dog', 'rabbit' ] # can also hold strings
Referencing to items in a list#
Each item in a list has an index. If your list has 3 items, it has 3 indexes (or indicies, depending on who you ask).
In Python, indexes starts at 0. To reference the first item in
number_list, we use number_list[0].
number_list[0] # get the first item from number_list
0.1
We can reference the rest of the numbers in the list with indexes 1 through 3. Note that even though there are 4 items in the list, the index goes from 0 to 3.
We also can use the items in a list the same way we can use variables to do math or other operations.
print( number_list[1] - number_list[3] ) # 0.2 - 0.4
print( 'my favorite kind of animal is', string_list[2] ) # prints rabbit
-0.2
my favorite kind of animal is rabbit
If we try to reference an index that does not exist in a list, we get an error.
number_list[4]
IndexError: list index out of range
If we want to reference the last item in a list, we can do it two ways.
We can use the length of list and subtract 1. Alternatively, we can also
use [-1] as a shorthand for the last item.
print( number_list[ len(number_list) - 1 ] )
print( number_list[-1])
0.4
0.4
Appending to a list#
If we want to add an item to the end of string_list, we can use
string_list.append().
string_list.append('bear')
print(string_list)
['cat', 'dog', 'rabbit', 'bear']
Reassigning an item in a list#
We can also alter any item currently in a list.
number_list[0] = 2096
print(number_list)
[2096, 0.2, 0.3, 0.4]
Question 1: Lists#
Create a list of numbers. Add the first number in the list to the last number of the list. Append this value to the list.
Solution
num_list = [25, 50, 75, 100]
num_list.append( num_list[0] + num_list[-1] )
Dictionaries#
Like lists, dictionaries are powerful ways to store items. However, the two structures are quite different from each other. Instead of storing items in a specific order, like a list, dictionaries store them as keys and values.
For example, you might have a key giraffes
paired with the value 25, and the key kangaroos paired with the
value 32. We can do this with using brackets ({ }) and colons
(:) with the format of { KEY1: VALUE1, KEY2: VALUE2, ... }.
animals_dict = { 'giraffes': 25, 'kangaroos': 32 }
Notice that our keys are strings and our values here are ints. Keys and values can be any data types, though it tends to be best practice for keys to be strings.
We can also write this vertically, putting key-value pairs on their own lines for visual clarity. You will still need to separate entries with a comma, however.
animals_dict = {
'giraffes': 25,
'kangaroos': 32
}
Once we create a dictionary with keys and values, we can use the key to
return the corresponding value. We do this by using DICT[KEY]:
animals_dict['giraffes']
25
Similarly to lists, if we try to reference a key that is not present in the dictionary, we will get an error.
animals_dict['beaver']
KeyError: 'beaver'
However, dictionaries have a way around this. We can use the .get()
function to either return a value for a key or a default value that we
specify. We run it with DICT.get(KEY, DEFAULT_VALUE).
animals_dict.get('beaver', 0) # will return 0 because beaver is not a key in this dictionary
0
Making an empty dictionary is similar to making an empty list. We can
either use dict() or {}.
# these do the same thing
my_dict = dict()
your_dict = {}
Adding to a dictionary#
It is very simple to add a new item to a dictionary. Instead of using
the colon notation, we can simply run DICT[KEY] = VALUE.
animals_dict['moose'] = 43 # new key-value pair - moose: 43
print(animals_dict)
{'giraffes': 25, 'kangaroos': 32, 'moose': 43}
Give a key a new value#
Giving a key a new value works just like reassigning an item in a list. Note that this means that you cannot have two identical keys in the same dictionary.
animals_dict['giraffes'] = 85 # key giraffes assigned the value of 85
print(animals_dict)
{'giraffes': 85, 'kangaroos': 32, 'moose': 43}
Question 2: Dictionaries#
Assign the value of giraffes in animal_dict to a new key
rabbit in the same dictionary.
Solution
Assigning dictionary values of different keys can be tricky. Remember to have write key on the right side.
animal_dict['rabbit'] = animal_dict['giraffe']
Tuples#
Tuples are a lot like lists. They are ordered collections of items that can be referenced with number indexing. However, they are immutable, meaning that once you create one, you cannot change it by adding to it or editing items in it. They are a somewhat more efficient to use, so they are situationally useful.
You can create a new tuple with parentheses. Note that creating an empty tuple has little use, since it cannot be altered.
my_tuple = ( 0, 1, 2, 4, 8 )
Sets#
Sets are unordered collections of items. You can think about about them
like dictionaries that only consist of keys. Like tuples, they are more
situationally useful than lists or dictionaries. Like dictionaries, they
also use {} but they do not use colons.
my_set = set() # the only way to initialize an empty set
new_set = { 'lions', 'tigers', 'bears' } # without colons, NOT a dictionary
We can add items to a list using .add(). However, if the item is
already present in the set, only one copy will be kept in it. Therefore,
sets keep a unique group of items.
new_set.add('oh my') # oh my will now be a string in the set
print(new_set)
new_set.add('bears') # won't have two bears in the set
print(new_set)
{'oh my', 'tigers', 'lions', 'bears'}
{'oh my', 'tigers', 'lions', 'bears'}
Question 3: Structures#
For each of the following examples, should you use a list, dictionary, tuple, or set?
A group of employees and their IDs.
All 12 months in order.
Your favorite foods ranked.
All of the foods you have tried.
Solution
Dictionary: paired information works very well in dictionaries.
Tuple: Months are ordered, and you never need to change or add to the months of the year. (List would ok as well.)
List: You want an ordering to represent the rank, and you might change or add to the list.
Set: Order does not matter; you just need to keep all the foods in one place.
Bonus: Nested structures#
We can place data structures within other data structures as well. These new structures are referred to as nested data structures, and they are powerful.
We have lists containing lists, dictionaries containing dictionaries, dictionaries containing lists, and much more.
# list of lists
list1 = ['a', 'b', 'c']
list2 = ['d', 'e', 'f', 'f']
list3 = ['h', 'i', 'j']
large_list = [list1, list2, list3]
print(large_list)
# dictionary of dictionaries
sample1 = {
'co2': [10.2, 3.4, 10.1],
'n': 4,
'city': 'Waltham'
}
sample2 = {
'co2': [4.2, 2.3, 3.5, 23],
'a': 23,
'city': 'Watertown'
}
samples = {'s1': sample1, 's2':sample2}
print(samples)
[['a', 'b', 'c'], ['d', 'e', 'f', 'f'], ['h', 'i', 'j']]
{'s1': {'co2': [10.2, 3.4, 10.1], 'n': 4, 'city': 'Waltham'}, 's2': {'co2': [4.2, 2.3, 3.5, 23], 'a': 23, 'city': 'Watertown'}}
Indexing and referencing items in these nested structures can get quite complicated. It’s important to know the full nested structure when doing these references.
print(large_list[0][2])
print(samples['s1']['city'])
print(samples['s2']['co2'][0])
c
Waltham
4.2
Bonus Question 1: Nested structures pt. 1#
Create a list that contains an empty list, an empty dictionary, an empty tuple, and an empty set.
Then, add any new item to the nested list and the set, and add a key-item pair to the dictionary.
# your code here
Solution
nested_list = [ list(), dict(), tuple(), set()]
# or
nested_list = [ [], {}, (), set()] # can't make an empty set the same way
nested_list[0].append('a new item') # appending list
nested_list[3].add('another new item')
nested_list[1]['a new key'] = 'a new value'
Bonus Question 2: Nested structures pt. 2#
We want to store information regarding the ecological community in the local area.
In Rivertown, there are 12 species of frogs, 2 species of snakes, and 20 species of birds.
In Spring Valley, there are 4 species of frogs, 1 species of snake, 2 species of birds, and 13 species of rodents.
In Ice Town, there are 4 species of birds, 6 species of rodents, and 1 species of bear.
Store this information in one nested data structure.
# your code here
Solution
# nested dictionary: dictionary of dictionaries
ecosystem = {
'Rivertown': {'frogs':12, 'snakes':2, 'birds':20},
'Spring Valley': {'frogs':1, 'snakes': 1, 'birds': 2, 'rodents': 13},
'Ice Town': {'birds': 4, 'rodents':6, 'bear':1}
}