Completed Pandas3

[sangeeths29]

No description provided.

[super30admin]

1. Correctness:

   • Problem 1 (Calculate Special Bonus): All three approaches correctly implement the logic to calculate the bonus based on the given conditions. The solutions handle both conditions (odd employee ID and name not starting with 'M') correctly.
   • Problem 2 (Fix Names in a Table): Both approaches correctly capitalize the first letter and make the rest lowercase. The sorting by user_id is also correctly implemented.
   • Problem 3 (Patients with a Condition): Both approaches correctly identify patients with conditions starting with 'DIAB1'. The regex approach is particularly efficient.

2. Time Complexity:

   • Problem 1: Approach 1 and 3 are O(n) where n is the number of employees. Approach 2 is also O(n) but uses a less efficient loop.
   • Problem 2: Both approaches are O(n) where n is the number of users.
   • Problem 3: Approach 1 is O(n*m) where n is the number of patients and m is the number of conditions per patient. Approach 2 is O(n) due to the efficient regex search.

3. Space Complexity:

   • Problem 1: Approach 1 and 3 use O(1) additional space (modifying in place). Approach 2 creates a new DataFrame, so O(n).
   • Problem 2: Both approaches modify in place, so O(1).
   • Problem 3: Approach 1 creates a new list and DataFrame, so O(n). Approach 2 filters in place, so O(1).

4. Code Quality:

   • The code is generally well-structured and readable.
   • All approaches are correctly implemented, but some approaches are more efficient than others.
   • The student shows good understanding of pandas operations and multiple ways to solve each problem.
   • Comments could be improved to explain each approach's trade-offs.

5. Efficiency:

   • Problem 1: Approach 1 and 3 are more efficient than Approach 2. The student should prefer vectorized operations.
   • Problem 2: Both approaches are efficient, but Approach 2 using capitalize() is cleaner.
   • Problem 3: Approach 2 using regex is more efficient and concise.

Areas for Improvement:

• Remove commented-out approaches in the final submission to keep the code clean.
• Add comments explaining why certain approaches are better than others.
• For Problem 3, Approach 1 could be optimized by using pandas string operations instead of manual loops.