Done Pandas10

[kaaviyavarrshini]

No description provided.

[super30admin]

The student's solution demonstrates a good understanding of pandas operations for grouping and aggregating data. Here's a detailed evaluation:

1. Correctness:

• Problem1: The solution correctly groups products by sell date, counts unique products, and joins them in sorted order. Both pandas and non-pandas solutions are correct.
• Problem2: Correctly calculates unique leads and partners per date and make_name.
• Problem3: Correctly identifies actor-director pairs who collaborated at least 3 times.

2. Time Complexity:

• Problem1: O(n log n) due to sorting products for each date.
• Problem2: O(n) for grouping operations.
• Problem3: O(n) for grouping and counting.

3. Space Complexity:

• All solutions have O(n) space complexity as they store intermediate results.

4. Code Quality:

• Good use of pandas operations and method chaining.
• Consistent formatting and style.
• Could improve by adding docstrings explaining each function's purpose.
• The commented-out non-pandas solution in Problem1 could be removed or moved to a separate file.

5. Efficiency:

• Problem1: The pandas solution is more efficient than the commented non-pandas version.
• Problem3: Could potentially use count() instead of size() for clarity since we're counting occurrences.

Areas for improvement:

• Add docstrings to explain function purposes and return types.
• Consider removing commented code or moving it to a separate file.
• The type ignore comment in Problem3 suggests potential type issues that could be properly addressed.