## Complexity Analysis (Time/Space)
Big O Notation Big O notation is used to analyze the efficiency of algorithms and represent their upper-bound time complexity. It helps us understand how the algorithm's performance scales with the input size. |
## Best, Average, and Worst Case Complexity
To determine the complexity of an algorithm, follow these steps: 1. Identify the major operations in the algorithm. 2. Analyze how many times each operation is executed concerning the input size. 3. Eliminate lower-order terms and constants to find the dominant term. Choose the appropriate complexity notation from the Big O table. |

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# DSA in Python Cheat Sheet (DRAFT) by aman-senpai

This is for coding interview.

This is a

**draft**cheat sheet. It is a work in progress and is not finished yet.