Python Data Types

Understanding Python Data Types

Python has several built-in data types that help us store and manipulate different kinds of data. Let's explore each one in detail:

1. Numbers

Python has several numeric types:

# Integers (whole numbers)
age = 25
year = 2024

# Floats (decimal numbers)
price = 19.99
pi = 3.14159

# Complex numbers
complex_num = 3 + 4j

In this complex number, 3 is the real part and 4j is the imaginary part. The imaginary part is multiplied by j or the square root of -1. In other words,

complex_num = 3 + 4*((-1) ** 0.5)

2. Strings

Strings are sequences of characters:

# String creation
name = "Alice"
message = 'Hello, World!'

# String operations
greeting = "Hello"
name = "Alice"
full_message = greeting + " " + name  # Concatenation

# String methods
upper_text = "hello".upper()  # HELLO
lower_text = "WORLD".lower()  # world
length = len("Python")        # 6

3. Lists

Lists are ordered, mutable sequences:

# Creating lists
numbers = [1, 2, 3, 4, 5]
fruits = ["apple", "banana", "orange"]

# List operations
numbers.append(6)       # Add item
fruits.remove("apple")  # Remove item
first_fruit = fruits[0] # Access item
fruits[1] = "grape"     # Modify item

# List methods
numbers.sort()         # Sort list
fruits.reverse()       # Reverse list

4. Tuples

Tuples are ordered, immutable sequences:

# Creating tuples
coordinates = (10, 20)
rgb = (255, 128, 0)

# Tuple operations
x = coordinates[0]     # Access item
length = len(rgb)      # Get length

# Common use cases
def get_coordinates():
    return (5, 10)     # Return multiple values

5. Dictionaries

Dictionaries store key-value pairs:

# Creating dictionaries
person = {
    "name": "John",
    "age": 30,
    "city": "New York"
}

# Dictionary operations
name = person["name"]          # Access value
person["email"] = "john@example.com"  # Add item
del person["age"]             # Remove item

# Dictionary methods
keys = person.keys()          # Get all keys
values = person.values()      # Get all values

6. Sets

Sets are unordered, mutable sequences of unique items:

# Creating sets
inhabitants = {
    "Human",
    "Cat",
    "Dog"
}

# Set operations
inhabitants.add(Antlion)  # Add item
inhabitants.update([Spider, Pig, Hamster]) # Add multiple items
inhabitants.discard["Human"] # Remove item
inhabitants2024 = frozenset(inhabitants) # Freeze set; Make immutable

7. Booleans

Booleans represent True or False values:

# Boolean values
is_active = True
is_finished = False

# Boolean operations
result = True and False  # False
result = True or False   # True
result = not True       # False

# Comparison operators
is_adult = age >= 18
is_valid = name != ""

Conclusion

Understanding these data types is crucial for Python programming. Each type has its own specific use cases and methods. Booleans are often used in conditional statements to make decisions in code.