5. Data Structures (Part 2) - MantsSk/CA_PTUA14 GitHub Wiki

Dictionary

A very powerful data structure which is going to be used a lot. Dictionary hold key: value pairs, with which we can access it's attributes. Dictionaries are:

  1. mutable ✔️ (can be changed)
  2. dynamic ✔️ (can grow and shrink in size)
  3. nested ✔️ (can contain other dictionaries or other complex structures)

A dictionary is a collection which is ordered, changeable and do not allow duplicates.

Main difference between python list and dictionary is that values in dictionaries are accessed by keys.

Creating a dictionary and adding values to it is as simple as:

my_dictionary = {}
my_dictionary["name"] = "Tom"
print(my_dictionary["name"])

my_dictionary = {"name": "Tom"}
print(my_dictionary["name"])

Access dictionary values

my_dictionary = {"name": "Tom", "surname": "Edison"}
print(f"name: {my_dictionary['name']}")
print(f"surname: {my_dictionary['surname']}")

If the value is non existent we shall get a KeyError as such key does not exist:

my_dictionary = {"name": "Tom", "surname": "Edison"}
print(f"favourite car: {my_dictionary['car']}")
# KeyError: 'car'

Dictionaries may use any immutable type as it's key (so no list as for example) and any type as its values:

Changing values in dictionary

my_dictionary = {"name": "Tom", "surname": "Edison"}
my_dictionary["name"] = "Charles"
print(f"name: {my_dictionary["name"]}")

Droping key from dictionary

my_dictionary = {"name": "Tom", "surname": "Edison"}
del my_dictionary ["name"]
print(my_dictionary)

More complex, nested structures

As with the lists, we have seen that lists can contain other lists, it so happens that the dictionary can have a value of another diciotnary and we can built a complex hierarchies like that:

user_info = {
	"name": "Albert",
	"surname": "Einstein",
	"occupation": {
		"role": "Professor",
		"workplace": "University of Berlin"
	},
        "languages": ["German", "Latin", "Italian", "English", "French"]
}

Let's say we wanted to print all the languages one by one, we could do something like this:

user_info = {
	"name": "Albert",
	"surname": "Einstein",
	"occupation": {
		"role": "Professor",
		"workplace": "University of Berlin"
	},
        "languages": ["German", "Latin", "Italian", "English", "French"]
}

for language in user_info["languages"]:
    print(language)

The possibilities are almost endless, we can go deeper and deeper.

.items()

There will be many of situations, that we will want to iterate through dictionary. We will be using in-built .items() method for dictionaries.

d = {'a': 10, 'b': 20, 'c': 30}
print(list(d.items()))

.keys()

This method returns dictionary keys:

d = {'a': 10, 'b': 20, 'c': 30}
list(d.keys())

.values()

This method returns dictionary values:

d = {'a': 10, 'b': 20, 'c': 30}
list(d.values())

.pop

This method pops the key value pair based on key and returns its value:

d = {'a': 10, 'b': 20, 'c': 30}
result = d.pop('a')
print(result)
print(d)

.update(obj)

If obj is a dictionary, my_dictionary.update(obj) merges the entries from obj into dictionary my_dictionary. If the key is not present in a dictionary my_dictionary, the key-value pair from obj is added to my_dictionary, otherwise, the corresponding value in my_dictionary for that key is updated with the value from obj.

Examples:

dict_one = {'a': 10, 'b': 20, 'c': 30}
dict_two = {'b': 200, 'd': 400}
dict_one .update(dict_two )
print(dict_one )

dict_one = {'a': 10, 'b': 20, 'c': 30}
dict_one .update([('b', 200), ('d', 400)])
print(dict_one )

dict_one = {'a': 10, 'b': 20, 'c': 30}
dict_one .update(b=200, d=400)
print(dict_one )

Iterating through dictionary

Example:

d = {'a': 10, 'b': 20, 'c': 30}
for key, value in d.items():
    print(key, value)

Converting two lists into a dictionary

Note that lists must be of the same size here:

test_keys = ["Albert", "Tom", "Stephen"]
test_values = [1, 4, 5]
my_dictionary= dict(zip(test_keys, test_values))
print(my_dictionary)

Sets

Sets are used to store multiple items in a single variable. A set is a collection which is unordered, unchangeable, and unindexed.

Note: Set items are unchangeable, but you can remove items and add new items.

Notation:

my_set = {1, 2, 3}

Another important property is that in sets we can't store duplicates values:

my_set = {1, 2, 3, 1}
print(my_set)
# {1, 2, 3}

For example, getting unique values from python list:

numbers_list = [1, 2, 3, 4, 5, 5, 5, 6]
numbers_set = set(numbers_list)
print(numbers_set)

🧠Exercises

  1. Write python program that asks user to enter name, surname, age. Put these values into a dictionary and print it.

  2. Try creating nested dict structure which would use all data types and structures you already know.

  3. Create a program, that would take sentences from the input and create a dictionary where they keys represents word and values the frequency those words appeared in those sentence. It doesn't matter if the word is upper case or lower case, it sounds like the same word.

Example: Enter a sentence: Hello hello its me, I was wondering about those all years we had been together. You and I.

Output: {'hello': 2, 'its': 1, 'me': 1, 'i': 2, 'was': 1, 'wondering': 1, 'about': 1, 'those': 1, 'all': 1, 'years': 1, 'we': 1, 'had': 1, 'been': 1, 'together': 1, 'you': 1, 'and': 1}

🌐 Extra reading: