Pandas10 Submitted

[PranathiDeepak]

No description provided.

[super30admin]

1. Problem1.py:

   • Correctness: The solution correctly groups products by sell_date, counts unique products, and lists them in sorted order. This appears to solve the problem correctly.
   • Time Complexity: O(n log n) due to the sorting operation on products.
   • Space Complexity: O(n) as it stores all unique products.
   • Code Quality: The code is clean and readable. Using lambda for joining sorted products is a good approach.
   • Efficiency: The solution is efficient, though the sorting could be avoided if order wasn't required.

2. Problem2.py:

   • Correctness: The solution correctly calculates unique leads and partners per date and make_name. This appears correct.
   • Time Complexity: O(n) for the groupby operation.
   • Space Complexity: O(n) for storing the grouped data.
   • Code Quality: The code is concise and clear. The renaming of columns is done neatly.
   • Efficiency: The solution is efficient. No obvious optimizations needed.

3. Problem3.py:

   • Correctness: The solution correctly finds actor-director pairs who collaborated at least 3 times. This appears correct.
   • Time Complexity: O(n) for the groupby operation.
   • Space Complexity: O(n) for storing the grouped data.
   • Code Quality: The code is well-structured. The filtering and column selection are done clearly.
   • Efficiency: The solution is efficient. No obvious optimizations needed.

General Observations:

• All solutions follow pandas best practices and are well-structured.
• Variable naming is appropriate and consistent.
• The solutions handle the grouping and aggregation tasks efficiently.
• No major edge cases seem to be missed in these problems.