Python Data Types – A Beginner’s Guide

In our previous discussion, we explored variables—how they store different types of values in Python. Now, let's dive into data types, which define the kind of data stored in a variable. Unlike languages such as Java, C, or C++, where you must explicitly declare a variable’s type, Python handles data types dynamically. This means you can directly assign a value to a variable without specifying its type. What Are Data Types? A data type not only defines the type of data stored in a variable but also determines the amount of memory allocated for that variable. Common Data Types in Python Python provides several built-in data types: Integer (int) – Whole numbers, both positive and negative. num1 = 23 num2 = -232 Floating-point (float) – Numbers with decimals. num3 = 23.232 num4 = -23.232 String (str) – Text enclosed in single or double quotes. name = "Brian" blood_group = 'B' Character (char) – Python doesn’t have a separate char type like C or Java. Instead, a single-character string (e.g., 'A', 'B') is still a string. Boolean (bool) – Represents True or False, often used in conditions. is_greater = 10 > 3 # True is_adult = age >= 18 # True Complex Numbers (complex) Python has a built-in complex type, which is not commonly found in some languages. num = 3 + 4j # Complex number print(type(num)) # Output: Checking Data Types and Memory Usage Python provides the type() function to check the type of any variable: print(type(232)) # Output: print(type(23.232)) # Output: print(type("Brian")) # Output: print(type(True)) # Output: To check the memory size of a variable, use sys.getsizeof(): import sys print(sys.getsizeof(232)) # Output: Memory size of int print(sys.getsizeof(23.232)) # Output: Memory size of float print(sys.getsizeof("Brian")) # Output: Memory size of string Memory Usage of Data Types Different data types occupy different amounts of memory in Python. Key Observations: Integers (int) – Generally take 28 bytes, but the size can increase with larger numbers. Floating-point numbers (float) – Usually 24 bytes, independent of the value. Strings (str) – Memory depends on the length of the string. Each character takes extra space. Boolean (bool) – Takes 28 bytes, same as an integer. Note: Unlike C or Java, where int and float have fixed sizes (e.g., 4 bytes, 8 bytes), Python’s data types are dynamically sized. The actual memory usage can vary depending on the system and Python implementation. Key Takeaways: ✔ Data types define both the type and memory usage of variables. ✔ Strings generally require more memory than integers or booleans. ✔ Use type() to check the data type and sys.getsizeof() to check memory allocation. ✔ Python dynamically assigns types without explicit declarations. This flexibility makes Python beginner-friendly while keeping it powerful for complex applications.

Feb 27, 2025 - 16:51

In our previous discussion, we explored variables—how they store different types of values in Python. Now, let's dive into data types, which define the kind of data stored in a variable.

Unlike languages such as Java, C, or C++, where you must explicitly declare a variable’s type, Python handles data types dynamically. This means you can directly assign a value to a variable without specifying its type.

What Are Data Types?

A data type not only defines the type of data stored in a variable but also determines the amount of memory allocated for that variable.

Common Data Types in Python

Python provides several built-in data types:

Integer (int) – Whole numbers, both positive and negative.

num1 = 23  
num2 = -232

*Floating-point (float) *– Numbers with decimals.

num3 = 23.232  
num4 = -23.232

String (str) – Text enclosed in single or double quotes.

name = "Brian"  
blood_group = 'B'

Character (char) – Python doesn’t have a separate char type like C or Java. Instead, a single-character string (e.g., 'A', 'B') is still a string.

Boolean (bool) – Represents True or False, often used in conditions.

is_greater = 10 > 3  # True  
is_adult = age >= 18  # True

Complex Numbers (complex)

Python has a built-in complex type, which is not commonly found in some languages.

num = 3 + 4j  # Complex number
print(type(num))  # Output:

Checking Data Types and Memory Usage

Python provides the** type()** function to check the type of any variable:

print(type(232))       # Output:   
print(type(23.232))    # Output:   
print(type("Brian"))   # Output:   
print(type(True))      # Output:

To check the memory size of a variable, use sys.getsizeof():


import sys  
print(sys.getsizeof(232))       # Output: Memory size of int  
print(sys.getsizeof(23.232))    # Output: Memory size of float  
print(sys.getsizeof("Brian"))   # Output: Memory size of string

Memory Usage of Data Types

Different data types occupy different amounts of memory in Python.

Key Observations:

Integers (int) – Generally take 28 bytes, but the size can increase with larger numbers.
Floating-point numbers (float) – Usually 24 bytes, independent of the value.
Strings (str) – Memory depends on the length of the string. Each character takes extra space.
*Boolean (bool) *– Takes 28 bytes, same as an integer.

Note: Unlike C or Java, where int and float have fixed sizes (e.g., 4 bytes, 8 bytes), Python’s data types are dynamically sized. The actual memory usage can vary depending on the system and Python implementation.

Key Takeaways:

✔ Data types define both the type and memory usage of variables.
✔ Strings generally require more memory than integers or booleans.
✔ Use type() to check the data type and sys.getsizeof() to check memory allocation.
✔ Python dynamically assigns types without explicit declarations.

This flexibility makes Python beginner-friendly while keeping it powerful for complex applications.