assignment2_kiran_submission

[kiran160195]

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[super30admin]

1. Correctness:

   • For problem1.py (article_views), the solution correctly identifies authors who viewed their own articles by comparing 'author_id' and 'viewer_id', drops duplicates, and returns the sorted result. This appears correct.
   • For problem2.py (invalid_tweets), the solution correctly identifies tweets with content length > 15 characters and returns their tweet_ids. This also appears correct.

2. Time Complexity:

   • For problem1.py: The operations are O(n) for comparison, O(n) for drop_duplicates, and O(n log n) for sorting. Overall O(n log n).
   • For problem2.py: The string length operation is O(n) where n is the number of tweets, making it O(n) overall.

3. Space Complexity:

   • For both problems, the space complexity is O(n) in the worst case as new DataFrames are created for intermediate results.

4. Code Quality:

   • The code is generally clean and readable.
   • Variable names are descriptive (condition, invalid_tweets_df).
   • Could improve by adding docstrings explaining the function purposes and return types.
   • In problem1.py, the intermediate variable 'condition' is reused which could be confusing - better to use distinct names for different transformations.

5. Efficiency:

   • Both solutions are efficient for their respective problems.
   • No major optimizations needed, though in problem1.py the sorting could be done earlier to potentially reduce memory usage.