How do I calculate Big O notation?

What is Big O notation and why is it important?

Big O notation is a mathematical concept used to describe the performance or complexity of an algorithm. It helps us understand how the runtime or space requirements grow as the input size increases.

How do I calculate the Big O notation for a simple loop?

For a simple loop that runs 'n' times, the Big O notation is O(n). This means the time complexity grows linearly with the input size.

What about nested loops?

For nested loops, you multiply the complexities. For example, if you have two nested loops each running 'n' times, the Big O notation would be O(n^2).

Can you give me an example of a function and its Big O notation?

Sure! Consider a function that checks all pairs in an array:

for i in range(n): 
    for j in range(n): 
        print(i, j) 

This has a time complexity of O(n^2) because of the nested loops.