Completed Pandas4

[sangeeths29]

No description provided.

[super30admin]

The student's solution demonstrates a good understanding of pandas operations to solve the Nth highest salary problem. Here are the key observations:

1. Correctness: The solution correctly handles the problem requirements. It drops duplicate salaries, checks for edge cases (N being too large or too small), and returns the correct Nth highest salary. The approach is sound.

2. Time Complexity: The solution involves sorting (O(n log n)), dropping duplicates (O(n)), and head/tail operations (O(n)). The overall time complexity is O(n log n) due to sorting, which is reasonable for this problem.

3. Space Complexity: The solution creates a new DataFrame for duplicates, so space complexity is O(n), which is acceptable.

4. Code Quality: The code is generally well-structured and readable. However, there are some areas for improvement:

   • The variable name 'df' is not very descriptive. A better name like 'unique_salaries' would improve readability.
   • The comments are helpful but could be more detailed about the logic flow.
   • The solution could be made more modular by separating the edge case handling into a separate function.

5. Efficiency: The solution is efficient for typical cases. One potential optimization would be to use the nlargest method instead of sort+head+tail, which might be more efficient for large datasets.

Edge cases handled well:

• Duplicate salaries
• N larger than number of unique salaries
• N <= 0
• Empty DataFrame

Potential improvements:

• Add input validation (e.g., check if employee is a valid DataFrame)
• Consider using nlargest for better performance
• More descriptive variable names
• More detailed comments explaining the pandas operations