Pandas10 Submission Kiran

[kiran160195]

No description provided.

[super30admin]

1. Correctness:

   • Problem1: The solution correctly groups by 'sell_date' and calculates both the number of unique products sold and a sorted comma-separated list of products. This appears to solve the problem correctly.
   • Problem2: The solution correctly groups by 'date_id' and 'make_name', then calculates unique counts for both 'lead_id' and 'partner_id'. The sorting at the end is a good touch.
   • Problem3: The solution correctly identifies actor-director pairs who have cooperated at least 3 times. The approach is correct but could be more efficient.

2. Time Complexity:

   • Problem1: O(n log n) due to the sorting operation on unique products.
   • Problem2: O(n) for grouping and counting, plus O(k log k) for sorting where k is the number of groups.
   • Problem3: O(n) for grouping and counting, plus O(m) for filtering where m is the number of groups.

3. Space Complexity:

   • All solutions have O(n) space complexity as they create new DataFrames from the input.

4. Code Quality:

   • Overall good structure and readability.
   • Variable names are descriptive.
   • Problem3 has a typo ('coorporated' instead of 'cooperated') and an unnecessary print statement.
   • The lambda function in Problem1 could be named for better clarity.

5. Efficiency:

   • Problem1: The sorting could be moved outside the aggregation for better readability.
   • Problem3: Could use groupby with size() directly in the filter condition to avoid creating an intermediate DataFrame.