pandas 10 complete

[nagaraja993]

No description provided.

[super30admin]

The student's solutions demonstrate a good understanding of pandas operations and grouping/aggregation techniques. Here's a detailed evaluation for each problem:

Problem1.py:

1. Correctness: The solution correctly groups by sell_date and calculates both the number of unique products sold and a sorted comma-separated list of products. The commented-out alternative shows good problem-solving exploration.
2. Time Complexity: O(n log n) due to the sorting operation in the lambda function.
3. Space Complexity: O(n) for storing the grouped data.
4. Code Quality: Well-structured and readable. The use of named aggregations is a good practice.
5. Efficiency: The solution is efficient, though the sorting could be avoided if order wasn't a requirement.

Problem2.py:

1. Correctness: Correctly calculates unique leads and partners per date and make_name.
2. Time Complexity: O(n) for the grouping and counting operations.
3. Space Complexity: O(n) for storing the grouped data.
4. Code Quality: Clean and concise. The commented alternative shows awareness of different approaches.
5. Efficiency: Optimal solution for the requirements.

Problem3.py:

1. Correctness: Correctly identifies actor-director pairs with at least 3 cooperations.
2. Time Complexity: O(n) for the grouping and counting operations.
3. Space Complexity: O(n) for storing the grouped data.
4. Code Quality: Good, though could be slightly more readable by using named aggregation like the other solutions.
5. Efficiency: The solution is efficient, though the intermediate 'coop' column could be avoided by using filter().

General strengths:

• Consistent use of pandas best practices
• Good handling of grouping and aggregation
• Clean code formatting
• Shows exploration of alternative approaches (commented code)

Areas for improvement:

• Problem3.py could benefit from named aggregations like the other solutions
• The lambda in Problem1.py could be replaced with a predefined function for better readability
• Some docstrings explaining the functions would be helpful