Pandas5: Problem Solutions_RN32MAY2025DS

[Feminto]

No description provided.

[super30admin]

The student has provided two solutions to the problem, which demonstrates good problem-solving skills and the ability to approach a problem from different angles. Here's a detailed evaluation:

1. Correctness:

• Both methods appear to solve the problem correctly by finding employees with the highest salary in each department.
• Method 1 uses a manual approach with dictionaries and loops, while Method 2 leverages pandas' built-in functions for merging and grouping.
• Method 2 is more concise and likely more efficient due to pandas' optimized operations.

2. Time Complexity:

• Method 1: O(n*m) where n is the number of employees and m is the number of departments due to nested loops.
• Method 2: O(n log n) for the groupby operation, which is more efficient than Method 1.

3. Space Complexity:

• Method 1: Creates multiple intermediate data structures (dictionaries, lists) leading to higher space complexity.
• Method 2: Uses pandas operations that are more memory-efficient with fewer intermediate structures.

4. Code Quality:

• Method 1 has more verbose code with manual iterations and could benefit from more descriptive variable names.
• Method 2 is cleaner and more idiomatic pandas code, following best practices for data manipulation.
• Both methods could benefit from docstrings explaining their purpose and parameters.

5. Efficiency:

• Method 2 is clearly more efficient and should be preferred.
• Method 1 could be optimized by using pandas operations instead of manual loops.
• The print statements in Method 1 should be removed or replaced with proper logging for production code.

Areas for Improvement:

• Add docstrings to explain the function's purpose and parameters.
• Remove debug print statements or replace with proper logging.
• Consider adding input validation for edge cases (empty DataFrames, missing columns).
• Method 1 could be simplified using pandas' groupby functionality.