Data Types II

9. Data Types II#

We’ve already encountered several data types. Now, let’s take a closer look and discuss additional important types. Let’s begin with a quick review.

It’s crucial to understand that variables in Python don’t contain the data/values directly. They are simply names linked to the memory location where the value is stored.

This explains why the following happens:

a = [5]
b = a
b.append(4)
print(a)

9.1. Review of Data Types We’ve Worked With#

9.1.1. Numbers#

We’ve frequently used integers and floats (floating-point numbers):

type(6)  # => int
type(6.0)  # => float

We haven’t discussed complex numbers yet, but for completeness:

type(2j + 3)  # => complex

9.1.2. Strings#

type("abcdefg")
type('abcdefg')
type("""abcdefg""")  # e.g., in function "docstrings"

9.1.3. Lists & Tuples#

We’ve already seen lists and tuples, which seem similar at first glance:

my_list = ["abc", "ABC", 5, 0.315]
my_tuple = ("abc", "ABC", 5, 0.315)

print(my_list[-1])
print(my_tuple[-1])

However, their behavior differs significantly!

  • Lists (list) are mutable and come with many methods/functions:

my_list = ["abc"]

my_list.append("something else")
my_list.insert(1, "xyz")
my_list[2] = "XYZ"
print(my_list)  # => ['abc', 'xyz', 'XYZ']

9.1.4. Boolean and None#

We’ve seen these types without discussing them as separate data types:

  • Boolean (bool): Can only be True or False.

  • NoneType (None): Represents the absence of a value or object.

9.2. Sets and Dictionaries#

Python includes two additional widely used data types: sets and dictionaries.

9.2.1. Sets#

my_set = {"yes", "no", "maybe"}

At first glance, sets may resemble tuples or lists. However, consider this:

my_set[0]  # => TypeError: 'set' object is not subscriptable

Sets are not sequences! Elements have no indices. Other operations (e.g., membership tests) still work:

"maybe" in my_set  # => True

Even a for-loop works:

for s in my_set:
    print(f"Well, {s}...")

The differences between sets and lists align with their usage in everyday language or mathematics. For instance:

animals = {"cat", "dog", "elephant", "lion", "dog"}
print(animals)  # => {'cat', 'dog', 'elephant', 'lion'}

9.2.1.1. Combining Sets#

When combining sets, duplicates are automatically removed. Operations include:

  • Union (A ∪ B):

animal_set1 = {"cat", "dog", "elephant", "lion"}
animal_set2 = {"parrot", "cat", "dog", "goldfish", "cow"}

all_animals = animal_set1.union(animal_set2)
print(all_animals)

  • Intersection (A ∩ B):

most_popular = animal_set1.intersection(animal_set2)
print(f"Named twice: {most_popular}")

Mini Quiz: What animals are output here?
a) {‚parrot‘, ‚goldfish‘, ‚cow‘}
b) {‚cat‘, ‚dog‘}
c) {‚elephant‘, ‚lion‘}
d) {}

  • Symmetric Difference:

named_once = animal_set1.symmetric_difference(animal_set2)
print(f"Named once: {named_once}")

9.2.2. Dictionaries#

Dictionaries allow data to be stored as key-value pairs:

my_dict = {"Hallo": "hello",
           "Tschüss": "bye",
           "Danke": "thanks"}

print(my_dict["Danke"])  # => thanks

Keys must be unique:

my_dict = {"Hallo": "hello",
           "Hallo": "hi"}
print(my_dict["Hallo"])  # => 'hi'

9.2.2.1. Modifying Dictionaries#

Dictionaries are mutable. Entries can be added, removed, or modified:

my_dict["password"] = "prettyfl0wer"
my_dict["hair color"] = "blond"
print(my_dict)

Check for a specific key:

print("password" in my_dict)  # => True

Retrieve all keys, values, or key-value pairs:

print(my_dict.keys())
print(my_dict.values())
print(my_dict.items())

9.2.3. Nested Dictionaries#

Dictionaries can also contain other dictionaries, enabling more complex data structures:

hogwarts = {
    "Dumbeldore": {"surname": "Albus", "function": "headmaster"},
    "Lockhart": {"surname": "Gilderoy", "function": "teacher"},
    "Granger": {"surname": "Hermione", "function": "pupil"}
}

print(hogwarts["Granger"]["surname"])  # => Hermione

9.3. Copying Objects: =, copy(), deepcopy()#

9.3.1. Shallow Copy (copy())#

A shallow copy only duplicates the top-level structure:

hogwarts = {"Dumbeldore": {"surname": "Albus", "function": "headmaster"}}
hogwarts_copy = hogwarts.copy()
hogwarts_copy["Dumbeldore"]["function"] = "former headmaster"

print(hogwarts["Dumbeldore"]["function"])  # => former headmaster

9.3.2. Deep Copy (deepcopy())#

For nested objects, use deepcopy():

import copy

hogwarts = {"Dumbeldore": {"surname": "Albus", "function": "headmaster"}}
hogwarts_copy = copy.deepcopy(hogwarts)
hogwarts_copy["Dumbeldore"]["function"] = "former headmaster"

print(hogwarts["Dumbeldore"]["function"])  # => headmaster

my_list1 = [[1, 2, 3], 12, 15]
my_list2 = copy.deepcopy(my_list1)

my_list2[0][0] = 54321
print(my_list1[0])  # => [1, 2, 3]
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