Completed Pandas4

[DhruvParashar246]

No description provided.

[super30admin]

The student's solution demonstrates a good understanding of pandas operations for solving the Nth highest salary problem. Here are the detailed observations:

1. Correctness:

• Both functions correctly handle the edge cases where N is invalid (too large or <=0) or when there aren't enough distinct salaries.
• The approach of dropping duplicates, sorting, and then using head/tail combination is correct for finding the Nth highest salary.
• The second_highest_salary function is a special case of the more general nth_highest_salary function.

2. Time Complexity:

• The operations (drop_duplicates, sort_values, head/tail) are all O(n log n) due to the sorting step, which is optimal for this problem.

3. Space Complexity:

• The solution creates intermediate DataFrames, but this is unavoidable for pandas operations. The space complexity is O(n) which is acceptable.

4. Code Quality:

• The code is well-structured and readable.
• Variable names are clear and appropriate.
• The functions follow a logical flow.
• One improvement could be to add docstrings explaining the functions' purposes and parameters.

5. Efficiency:

• The solution is already quite efficient for pandas operations.
• For very large datasets, using nlargest() might be slightly more efficient than sort_values().head(N).
• The second_highest_salary function could potentially be implemented by calling nth_highest_salary(employee, 2) for better code reuse.

6. Edge Cases:

• The solution handles edge cases well (empty DataFrame, N too large, N <=0).
• It correctly returns None in a DataFrame when appropriate.