Data Types in Python

Welcome back! Now that you have a good grasp of variables in Python, it’s time to delve into the different types of data you can work with. Python is known for its simplicity and readability, and part of that comes from its flexible and dynamic data types. Understanding data types is essential because it helps you know what kind of operations you can perform on different types of data. Let’s explore the various data types in Python.

Basic Data Types

1. Integers

Integers are whole numbers without a fractional component. They can be positive, negative, or zero.

x = 10
y = -5
z = 0

print(type(x))  # Output: <class 'int'>

2. Floats

Floats (floating-point numbers) are numbers with a decimal point.

a = 10.5
b = -3.14
c = 0.0

print(type(a))  # Output: <class 'float'>

3. Strings

Strings are sequences of characters enclosed in single quotes (') or double quotes (").

name = "Alice"
greeting = 'Hello, World!'

print(type(name))  # Output: <class 'str'>

4. Booleans

Booleans represent one of two values: True or False.

is_student = True
is_teacher = False

print(type(is_student))  # Output: <class 'bool'>

Advanced Data Types

1. Lists

Lists are ordered collections of items (which can be of different data types) enclosed in square brackets ([]).

numbers = [1, 2, 3, 4, 5]
mixed_list = [1, "two", 3.0, True]

print(type(numbers))  # Output: <class 'list'>

You can access list elements by their index, starting from 0.

print(numbers[0])  # Output: 1
print(mixed_list[1])  # Output: two

2. Tuples

Tuples are similar to lists, but they are immutable, meaning their elements cannot be changed after they are created. Tuples are enclosed in parentheses (()).

coordinates = (10, 20)
empty_tuple = ()

print(type(coordinates))  # Output: <class 'tuple'>

3. Dictionaries

Dictionaries are collections of key-value pairs enclosed in curly braces ({}). Each key is unique, and it maps to a value.

student = {
    "name": "Alice",
    "age": 20,
    "is_student": True
}

print(type(student))  # Output: <class 'dict'>

You can access dictionary values by their keys.

print(student["name"])  # Output: Alice
print(student["age"])   # Output: 20

4. Sets

Sets are unordered collections of unique items enclosed in curly braces ({}).

unique_numbers = {1, 2, 3, 4, 5, 5, 5}

print(unique_numbers)  # Output: {1, 2, 3, 4, 5}
print(type(unique_numbers))  # Output: <class 'set'>

Type Conversion

Sometimes, you may need to convert one data type to another. Python provides built-in functions for type conversion.

1. int()

Converts a value to an integer.

x = "10"
y = int(x)

print(type(y))  # Output: <class 'int'>

2. float()

Converts a value to a float.

x = "10.5"
y = float(x)

print(type(y))  # Output: <class 'float'>

3. str()

Converts a value to a string.

x = 10
y = str(x)

print(type(y))  # Output: <class 'str'>

4. bool()

Converts a value to a boolean.

x = 0
y = bool(x)

print(type(y))  # Output: <class 'bool'>
print(y)        # Output: False

Example: Using Different Data Types

Let’s create a simple program that uses various data types to store and manipulate information about a book.

# Book information
title = "The Catcher in the Rye"
author = "J.D. Salinger"
year_published = 1951
price = 10.99
is_ebook = False
tags = ["classic", "novel", "literature"]
ratings = (5, 4, 4, 5, 5)
metadata = {
    "pages": 214,
    "publisher": "Little, Brown and Company",
    "language": "English"
}

# Print book information
print("Title:", title)
print("Author:", author)
print("Year Published:", year_published)
print("Price: $", price)
print("Is eBook:", is_ebook)
print("Tags:", tags)
print("Ratings:", ratings)
print("Metadata:", metadata)

In this program, we use strings, integers, floats, booleans, lists, tuples, and dictionaries to store information about a book. We then print out the information.

Conclusion

Understanding data types is crucial for writing effective Python programs. Each data type has its own set of operations and uses, and knowing when and how to use them will make you a more proficient programmer. We’ve covered the basic and advanced data types in Python, as well as type conversion. With this knowledge, you’re well on your way to mastering Python.

In the next tutorial, we’ll explore how to use operators and expressions in Python to perform various operations on these data types. Stay tuned, and happy coding!