Python Data Types and Type Conversion Explained (With Examples)

Introduction

Python is a versatile programming language used for web development, data science, automation, and more. One of the fundamental concepts in Python (and programming in general) is data types. Understanding data types and how to convert between them (type conversion) is essential for writing efficient and error-free code.

In this blog, we’ll explore:
✅ Different Python data types (integers, floats, strings, booleans, None)
✅ How to check data types using the type() function
✅ Type conversion (type casting) between different data types
✅ Practical examples with Python IDLE

1. What Are Data Types in Python?

Data types define the kind of value a variable can hold. Python has several built-in data types:

A. Integer (int)

Represents whole numbers (positive or negative).

num = 28  
print(type(num))  # Output: <class 'int'> 

B. Float (float)

Represents decimal numbers.

price = 5.9  
print(type(price))  # Output: <class 'float'>  

C. String (str)

Represents text (enclosed in single or double quotes).

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

D. Boolean (bool)

Represents True or False.

is_active = True  
print(type(is_active))  # Output: <class 'bool'>

E. NoneType (None)

Represents the absence of a value.

data = None  
print(type(data))  # Output: <class 'NoneType'> 

2. Type Conversion (Type Casting) in Python

Sometimes, we need to convert one data type into another. Python allows this using built-in functions like int(), float(), str(), and bool().

A. Converting int to float and Vice Versa

# int to float  
num = 28  
float_num = float(num)  
print(float_num)  # Output: 28.0  

# float to int (truncates decimal part)  
price = 34.9  
int_price = int(price)  
print(int_price)  # Output: 34 

B. Converting Between int/float and str

# int to string  
age = 25  
str_age = str(age)  
print(str_age)  # Output: "25"  

# string to int (only works if string is a valid number)  
num_str = "50"  
int_num = int(num_str)  
print(int_num)  # Output: 50  

# Invalid conversion (Error)  
invalid_str = "hello"  
# int_num = int(invalid_str)  # ❌ Raises ValueError  

C. Boolean Conversions

• True → 1, False → 0
• Non-zero numbers → True, 0 or None → False
• Non-empty strings → True, Empty strings → False

# bool to int  
print(int(True))   # Output: 1  
print(int(False))  # Output: 0  

# int to bool  
print(bool(1))    # Output: True  
print(bool(0))    # Output: False  

# string to bool  
print(bool("hello"))  # Output: True  
print(bool(""))       # Output: False 

3. Common Errors in Type Conversion

• ValueError – When converting invalid strings to numbers.# int(“hello”) → Error
• TypeError – When converting incompatible types.# int(None) → Error

4. Practical Use Cases

• User Input Handling (Converting string inputs to numbers)
• Data Processing (Ensuring correct data types in calculations)
• Boolean Checks (Validating conditions)

Conclusion

Understanding Python data types and type conversion is crucial for writing efficient code. Whether you’re working with numbers, strings, or booleans, knowing how to convert between them helps prevent errors and improves flexibility.

🔹 Want to see these concepts in action? Watch the full video tutorial above!

🚀 Ready to learn more? Check out our next Python tutorial on variables and operators!

📌 Key Takeaways

✔ Python has int, float, str, bool, and None as primary data types.
✔ Use type() to check a variable’s data type.
✔ Type conversion (int(), float(), str(), bool()) helps in data manipulation.
✔ Be cautious of ValueError and TypeError during conversions.

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