Python Data Types

Welcome to The Coding College, your ultimate resource for mastering Python programming! In this tutorial, we’ll dive deep into Python Data Types, a crucial topic for any programmer. Understanding data types allows you to manage and manipulate data effectively in your code.

What are Data Types in Python?

Data types define the type of data a variable can hold. Python provides a wide variety of data types, making it one of the most versatile programming languages.

Key Points:

  1. Python is dynamically typed: You don’t need to declare a variable’s type explicitly.
  2. Python automatically assigns the type based on the value assigned.
x = 10        # Integer  
y = 3.14      # Float  
z = "Python"  # String

Built-in Data Types in Python

Python categorizes its data types into the following groups:

1. Text Type

  • String (str): Represents text data.
text = "Hello, Python!"  
print(type(text))  # Output: <class 'str'>

2. Numeric Types

  • Integer (int): Whole numbers.
  • Float (float): Decimal numbers.
  • Complex (complex): Complex numbers with real and imaginary parts.
x = 10          # int  
y = 3.14        # float  
z = 2 + 3j      # complex  

print(type(x))  # Output: <class 'int'>  
print(type(y))  # Output: <class 'float'>  
print(type(z))  # Output: <class 'complex'>

3. Sequence Types

  • List (list): Ordered, mutable, and allows duplicate elements.
  • Tuple (tuple): Ordered, immutable, and allows duplicate elements.
  • Range (range): Represents an immutable sequence of numbers.
my_list = [1, 2, 3]  
my_tuple = (4, 5, 6)  
my_range = range(10)  

print(type(my_list))  # Output: <class 'list'>  
print(type(my_tuple)) # Output: <class 'tuple'>  
print(type(my_range)) # Output: <class 'range'>

4. Mapping Type

  • Dictionary (dict): Key-value pairs, unordered, and mutable.
my_dict = {"name": "Alice", "age": 25}  
print(type(my_dict))  # Output: <class 'dict'>

5. Set Types

  • Set (set): Unordered and contains unique elements.
  • Frozen Set (frozenset): Immutable version of a set.
my_set = {1, 2, 3}  
my_frozenset = frozenset([4, 5, 6])  

print(type(my_set))       # Output: <class 'set'>  
print(type(my_frozenset)) # Output: <class 'frozenset'>

6. Boolean Type

  • Boolean (bool): Represents True or False.
is_valid = True  
print(type(is_valid))  # Output: <class 'bool'>

7. Binary Types

  • Bytes (bytes): Immutable sequence of bytes.
  • Bytearray (bytearray): Mutable sequence of bytes.
  • Memoryview (memoryview): Views of byte data.
my_bytes = b"Hello"  
my_bytearray = bytearray(5)  
my_memoryview = memoryview(b"Hello")  

print(type(my_bytes))      # Output: <class 'bytes'>  
print(type(my_bytearray))  # Output: <class 'bytearray'>  
print(type(my_memoryview)) # Output: <class 'memoryview'>

Example: Working with Multiple Data Types

Here’s an example of using various data types in a single program:

# Declare variables of different types  
name = "Alice"         # String  
age = 25               # Integer  
height = 5.5           # Float  
is_student = True      # Boolean  
grades = [85, 90, 95]  # List  

# Print data types  
print(f"{name} is {age} years old.")  
print(f"Height: {height}")  
print(f"Is student: {is_student}")  
print(f"Grades: {grades}")

Check Data Type of a Variable

Use the type() function to check the data type of any variable:

x = 10  
print(type(x))  # Output: <class 'int'>

Python’s Dynamic Typing

In Python, variables can change their type dynamically:

x = 10         # x is an integer  
x = "Python"   # Now x is a string  
print(type(x)) # Output: <class 'str'>

Type Casting in Python

Convert one data type to another using type casting functions like int(), float(), str(), etc.

# Type casting  
x = "10"         # String  
y = int(x)       # Convert to integer  
print(type(y))   # Output: <class 'int'>

Learn Python at The Coding College

At The Coding College, we’re dedicated to helping you understand Python’s fundamentals and beyond. With detailed guides and practical examples, you’ll:

  • Master Python Data Types
  • Learn Best Practices for Data Management
  • Build Real-World Projects

Conclusion

Understanding Python’s data types is key to writing efficient and error-free code. By practicing and experimenting with these data types, you’ll gain confidence and versatility in Python programming.

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