Python’s in-built data types

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flowchart TD
    A[Python Built-in Data Types]

    A --> B(Numeric)
    B --> B1[int<br>float<br>complex]
    
    A --> C(Sequence Type)
    C --> C1[string<br>list<br>tuple]
    
    A --> D(Boolean)
    D --> D1[bool]

    A --> E(Mapping Type)
    E --> E1[dict]

• There are also other data types (e.g.set, binary, etc.) but these should suffice for most purposes.

Numeric Types

# integers: 
integer_variable = 1

# floats:
float_variable = 1.234

# complex numbers:
complex_variable = 1 + 2j

Sequence Types - String

# strings:
string_variable = 'Hello, this is some text and we call it a string'

• A string is a sequence of characters, created by enclosing them in quotes.
• Is there a “text” or “character” data type in Python?
  • Nope, you just have strings. A character is simply a string of length 1.

Sequence Types - List

# lists:
list_variable = [1, 2, 3, 4, 5]

• A list is a collection of items - simply put them in square brackets separated by commas.
• Lists can contain items of different types, including other lists.

Sequence Types - Tuple

# tuples:
tuple_variable = (1, 2, 3, 4, 5)

• A tuple is similar to a list, but it is immutable (cannot be changed).
• Tuples are created by enclosing items in parentheses.

Boolean Type

# booleans:
boolean_variable = True

• A boolean represents one of two values: True or False.
• Booleans are often used in conditional statements to control the flow of a program.

Lists

# A list of grocery items
groceries = ["apples", "bananas", "milk", "bread"]

print(groceries)

['apples', 'bananas', 'milk', 'bread']

groceries.append("eggs")   # add something
groceries.remove("milk")   # remove something
print(groceries)

['apples', 'bananas', 'bread', 'eggs']

# Accessing elements in a list
print("First item:", groceries[0])
print("Second item:", groceries[1])

First item: apples
Second item: bananas

Tuples

my_tuple = ("apples",4)

# Each grocery item with a quantity
groceries = [
    ("apples", 4),
    ("bananas", 6),
    ("milk", 1),
    ("bread", 2),
]

print("First tuple:", groceries[0])  

First tuple: ('apples', 4)

# Accessing elements in a tuple
print("First item:", groceries[0][0])
print("Quantity:", groceries[0][1])

First item: apples
Quantity: 4

But what if I forgot the sequence?

The if conditional

# Finding the quantity of bananas
item = groceries[0]
grocery_item = item[0]
if grocery_item == "bananas":
    print("Quantity of bananas:", item[1])
else:
    print("No bananas found")

No bananas found

# Finding the quantity of bananas
item = groceries[1]
grocery_item = item[0]
if grocery_item == "bananas":
    print("Quantity of bananas:", item[1])
else:
    print("No bananas found")

Quantity of bananas: 6

• What if bananas was the 963rd item in the list? This is not a smart strategy…

The for loop

# Finding the quantity of bananas
for item in groceries:
    grocery_item = item[0]
    if grocery_item == "bananas":
        print("Quantity of bananas:", item[1])

Quantity of bananas: 6

for item in groceries:
    print(item)
    print("Item done. Next one!")

('apples', 4)
Item done. Next one!
('bananas', 6)
Item done. Next one!
('milk', 1)
Item done. Next one!
('bread', 2)
Item done. Next one!

• Good to learn for loops, but looping is inefficient to find items in a large list.
• Wouldn’t it be nice to just look it up directly?

Mapping Type - Dictionary

# Dictionary: item → quantity
groceries = {
    "apples": 4,
    "bananas": 6,
    "milk": 1,
    "bread": 2
}

• A dictionary is a collection of key-value pairs. Here, a key is "apples" and the value is 4.
• Think of keys as “addresses” for the values they point to. So, keep them unique - otherwise you’ll overwrite it.
• Values can be of any type, including lists, tuples, or even other dictionaries.

# Access a value in a dictionary
print("Bananas:", groceries["bananas"])

Bananas: 6

Dictionary operations

groceries["eggs"] = 12      # add eggs
groceries["milk"] = 2       # update milk quantity
del groceries["bread"]      # remove bread

print(groceries)

{'apples': 4, 'bananas': 6, 'milk': 2, 'eggs': 12}

• Fast lookup, update, and deletion.

• Much more convenient than lists of tuples for this case.