Pandas3: Problem Solutions_RN32MAY2025DS

[Feminto]

No description provided.

[super30admin]

The student has provided two methods to solve the problem, which demonstrates good problem-solving skills and understanding of different approaches. Here's a detailed evaluation:

1. Correctness: Both methods appear to correctly implement the logic to calculate bonuses based on the given conditions (odd employee_id and name not starting with 'M'). The second method is more concise and leverages pandas' vectorized operations.

2. Time Complexity:

   • Method 1: O(n) due to the loop through all employees
   • Method 2: O(n) as well, but likely faster in practice due to pandas' optimized vectorized operations

3. Space Complexity:

   • Method 1: O(n) for storing the result list
   • Method 2: O(1) additional space (modifies the DataFrame in place)

4. Code Quality:

   • Method 1 is straightforward but less idiomatic for pandas operations. The variable names are clear but the approach is less efficient.
   • Method 2 is more pandas-idiomatic and concise. The use of vectorized operations is a better practice for pandas.
   • Both methods could benefit from comments explaining the logic.

5. Efficiency:

   • Method 2 is clearly more efficient as it uses pandas' built-in operations.
   • Both methods correctly sort the output by employee_id as required.

Areas for improvement:

• Method 1 could be improved by using pandas' apply function instead of a manual loop.
• Adding docstrings to explain the function's purpose would improve readability.
• The variable names in Method 1 could be more descriptive (e.g., 'eid' could be 'employee_id').