⑤ / ⑤⓪ ✅ Fully Explained | Beginner Friendly | Easy Implementation | MSSQL - Pandas | 𝟓/𝟓𝟬 SQL50
IntuitionThe problem requires identifying tweets with content exceeding 15 characters. This can be achieved by checking the length of each tweet's content and f
# Intuition
<!-- Describe your first thoughts on how to solve this problem. -->
The problem requires identifying tweets with content exceeding 15 characters. This can be achieved by checking the length of each tweet's content and filtering accordingly.
# Approach
<!-- Describe your approach to solving the problem. -->
We utilize Pandas' built-in string methods to efficiently calculate the length of each tweet's content. Then, we filter the DataFrame to keep only the tweets with content length greater than 15 characters.


*Python Solution*
1. Use the str.len() method to calculate the length of each tweet's content.
2. Apply a boolean mask to filter tweets where content length is greater than 15.
3. Select only the 'tweet_id' column from the filtered DataFrame.

*SQL Solution*
1. Use the LEN() function to calculate the length of each tweet's content.
2. Use a WHERE clause to filter tweets where content length is greater than 15.
3. Select the 'tweet_id' column from the filtered results.


# Complexity
- Time complexity:
<!-- Add your time complexity here, e.g. $$O(n)$$ -->
O(N)
- Space complexity:
<!-- Add your space complexity here, e.g. $$O(n)$$ -->
O(N)
# Code
```pythondata []
import pandas as pd

def invalid_tweets(tweets: pd.DataFrame) -> pd.DataFrame:
    return tweets[(tweets['content'].str.len()) > 15][['tweet_id']]
    
```
['Python3', 'MS SQL Server', 'Pandas']