Added Pandas2 Q1–Q2 solutions

[arushi2106]

No description provided.

[super30admin]

The student has provided solutions for two different problems using pandas. Let's evaluate each one separately.

1. Article_Views:

• Correctness: The solution correctly identifies authors who viewed their own articles by comparing author_id and viewer_id, then returns unique IDs sorted in ascending order. This appears correct.
• Time Complexity: O(n) for filtering + O(m) for unique (where m is filtered rows) + O(k log k) for sorting (where k is unique IDs). This is efficient.
• Space Complexity: O(k) for storing unique IDs, which is optimal.
• Code Quality: The code is clean and readable. One minor improvement could be to chain operations for better readability.
• Efficiency: The solution is already efficient. No major optimizations needed.

2. Invalid_Tweets:

• Correctness: The solution correctly filters tweets with content length > 15 characters and returns their tweet_ids. This appears correct.
• Time Complexity: O(n) for filtering, which is optimal.
• Space Complexity: O(m) where m is the filtered rows, which is necessary.
• Code Quality: The code is simple and effective. The variable name 'tweets' is reused which could be confusing - better to use a new variable name for the filtered result.
• Efficiency: The solution is already efficient. The str.len() operation is the right approach.

General strengths:

• Both solutions use pandas effectively
• Proper type hints are included
• Solutions are concise yet readable
• Correct use of DataFrame operations

Areas for improvement:

• Could add docstrings to explain the functions
• In Article_Views, could chain operations like:
  return (views[views['author_id'] == views['viewer_id']]['author_id']
.unique()
.to_frame('id')
.sort_values('id'))
• In Invalid_Tweets, could use a different variable name for the filtered result