00:00:00

Description

Editorial

February Hashtag Momentum Leaderboard

MEDIUM20 pts

A social analytics team needs a monthly leaderboard of the strongest hashtag momentum in short-form posts.

Table: Tweets

user_id: author identifier
tweet_id: unique post identifier
tweet_date: posting date (YYYY-MM-DD)
tweet: post text

Task: Produce the top 3 hashtags for February 2024.

Processing rules:

Consider only rows where tweet_date is in February 2024.
Extract a hashtag token from tweet text using pattern #[A-Za-z0-9_]+.
Count how many February tweets mention each hashtag token.
Return at most 3 rows sorted by:
- hashtag_count DESC
- hashtag DESC (for tie-breaking)

Output requirements:

Return exactly these columns: hashtag, hashtag_count

Notes:

Rows without a valid hashtag token are ignored.
Comparison is case-sensitive, so #Data and #data are different hashtags.

Supported submission environments:

SQL (SQLite 3.27.2)
Pandas (Python)

Example

Input

Tweets:
| user_id | tweet_id | tweet_date  | tweet                               |
|---------|----------|-------------|-------------------------------------|
| 135     | 13       | 2024-02-01  | Enjoying a great start #HappyDay    |
| 136     | 14       | 2024-02-03  | Another bright morning #HappyDay    |
| 137     | 15       | 2024-02-04  | Deep work session #WorkLife         |
| 138     | 16       | 2024-02-04  | Exploring new tools #TechLife       |
| 139     | 17       | 2024-02-05  | Grateful for progress #HappyDay     |
| 140     | 18       | 2024-02-07  | Building with curiosity #TechLife   |
| 141     | 19       | 2024-02-09  | A quiet walk helps #Nature          |

Output

[
  {"hashtag":"#HappyDay","hashtag_count":3},
  {"hashtag":"#TechLife","hashtag_count":2},
  {"hashtag":"#WorkLife","hashtag_count":1}
]

Explanation

The top three hashtags in February are ranked by mention frequency, then hashtag text descending for ties.

Example

Input

Tweets:
| user_id | tweet_id | tweet_date  | tweet                  |
|---------|----------|-------------|------------------------|
| 10      | 101      | 2024-02-10  | Fast ship #Alpha       |
| 10      | 102      | 2024-02-11  | Fast ship #Alpha       |
| 11      | 103      | 2024-02-10  | Feature push #Zeta     |
| 11      | 104      | 2024-02-12  | Feature push #Zeta     |
| 12      | 105      | 2024-02-12  | Ops sync #Beta         |

Output

[
  {"hashtag":"#Zeta","hashtag_count":2},
  {"hashtag":"#Alpha","hashtag_count":2},
  {"hashtag":"#Beta","hashtag_count":1}
]

Explanation

#Zeta and #Alpha tie on count. Descending hashtag order places #Zeta first.

Example

Input

Tweets:
| user_id | tweet_id | tweet_date  | tweet                        |
|---------|----------|-------------|------------------------------|
| 21      | 201      | 2024-02-28  | Release train #ShipIt        |
| 21      | 202      | 2024-02-29  | Leap day celebration #ShipIt |
| 22      | 203      | 2024-02-29  | Tracking quality #Stable     |
| 23      | 204      | 2024-02-14  | No marker in this row        |
| 24      | 205      | 2024-01-31  | Jan data should not count #ShipIt |

Output

[
  {"hashtag":"#ShipIt","hashtag_count":2},
  {"hashtag":"#Stable","hashtag_count":1}
]

Explanation

February 29 is included in 2024. January rows and rows without a valid hashtag token are ignored.

Accepted0/0·0% Acceptance

Constraints

1 <= number of rows in Tweets <= 300000
tweet_id values are unique
1 <= user_id, tweet_id <= 2 * 10^9
tweet_date is a valid ISO date string
tweet is a text payload that may or may not contain a hashtag token
A valid hashtag token matches #[A-Za-z0-9_]+
Only February 2024 rows are considered
Output columns must be exactly: hashtag, hashtag_count
Sort by hashtag_count DESC, hashtag DESC
Return at most 3 rows
Use SQLite 3.27.2 semantics for SQL submissions
For Pandas submissions, return a DataFrame with columns [hashtag, hashtag_count]

Code

Visualizer

Solutions

14px

Test Cases3

Results

Submissions

Tweets =

[{"user_id":135,"tweet_id":13,"tweet_date":"2024-02-01","tweet":"Enjoying a great start to the day #HappyDay"},{"user_id":136,"tweet_id":14,"tweet_date":"2024-02-03","tweet":"Another bright morning #HappyDay"},{"user_id":137,"tweet_id":15,"tweet_date":"2024-02-04","tweet":"Deep work session #WorkLife"},{"user_id":138,"tweet_id":16,"tweet_date":"2024-02-04","tweet":"Exploring new tools #TechLife"},{"user_id":139,"tweet_id":17,"tweet_date":"2024-02-05","tweet":"Grateful for progress #HappyDay"},{"user_id":140,"tweet_id":18,"tweet_date":"2024-02-07","tweet":"Building with curiosity #TechLife"},{"user_id":141,"tweet_id":19,"tweet_date":"2024-02-09","tweet":"A quiet walk helps #Nature"}]

Loading problem...

101

00:00:00

Description

Editorial

February Hashtag Momentum Leaderboard

MEDIUM20 pts

A social analytics team needs a monthly leaderboard of the strongest hashtag momentum in short-form posts.

Table: Tweets

user_id: author identifier
tweet_id: unique post identifier
tweet_date: posting date (YYYY-MM-DD)
tweet: post text

Task: Produce the top 3 hashtags for February 2024.

Processing rules:

Consider only rows where tweet_date is in February 2024.
Extract a hashtag token from tweet text using pattern #[A-Za-z0-9_]+.
Count how many February tweets mention each hashtag token.
Return at most 3 rows sorted by:
- hashtag_count DESC
- hashtag DESC (for tie-breaking)

Output requirements:

Return exactly these columns: hashtag, hashtag_count

Notes:

Rows without a valid hashtag token are ignored.
Comparison is case-sensitive, so #Data and #data are different hashtags.

Supported submission environments:

SQL (SQLite 3.27.2)
Pandas (Python)

Example

Input

Tweets:
| user_id | tweet_id | tweet_date  | tweet                               |
|---------|----------|-------------|-------------------------------------|
| 135     | 13       | 2024-02-01  | Enjoying a great start #HappyDay    |
| 136     | 14       | 2024-02-03  | Another bright morning #HappyDay    |
| 137     | 15       | 2024-02-04  | Deep work session #WorkLife         |
| 138     | 16       | 2024-02-04  | Exploring new tools #TechLife       |
| 139     | 17       | 2024-02-05  | Grateful for progress #HappyDay     |
| 140     | 18       | 2024-02-07  | Building with curiosity #TechLife   |
| 141     | 19       | 2024-02-09  | A quiet walk helps #Nature          |

Output

[
  {"hashtag":"#HappyDay","hashtag_count":3},
  {"hashtag":"#TechLife","hashtag_count":2},
  {"hashtag":"#WorkLife","hashtag_count":1}
]

Explanation

The top three hashtags in February are ranked by mention frequency, then hashtag text descending for ties.

Example

Input

Tweets:
| user_id | tweet_id | tweet_date  | tweet                  |
|---------|----------|-------------|------------------------|
| 10      | 101      | 2024-02-10  | Fast ship #Alpha       |
| 10      | 102      | 2024-02-11  | Fast ship #Alpha       |
| 11      | 103      | 2024-02-10  | Feature push #Zeta     |
| 11      | 104      | 2024-02-12  | Feature push #Zeta     |
| 12      | 105      | 2024-02-12  | Ops sync #Beta         |

Output

[
  {"hashtag":"#Zeta","hashtag_count":2},
  {"hashtag":"#Alpha","hashtag_count":2},
  {"hashtag":"#Beta","hashtag_count":1}
]

Explanation

#Zeta and #Alpha tie on count. Descending hashtag order places #Zeta first.

Example

Input

Tweets:
| user_id | tweet_id | tweet_date  | tweet                        |
|---------|----------|-------------|------------------------------|
| 21      | 201      | 2024-02-28  | Release train #ShipIt        |
| 21      | 202      | 2024-02-29  | Leap day celebration #ShipIt |
| 22      | 203      | 2024-02-29  | Tracking quality #Stable     |
| 23      | 204      | 2024-02-14  | No marker in this row        |
| 24      | 205      | 2024-01-31  | Jan data should not count #ShipIt |

Output

[
  {"hashtag":"#ShipIt","hashtag_count":2},
  {"hashtag":"#Stable","hashtag_count":1}
]

Explanation

February 29 is included in 2024. January rows and rows without a valid hashtag token are ignored.

Accepted0/0·0% Acceptance

Constraints

1 <= number of rows in Tweets <= 300000
tweet_id values are unique
1 <= user_id, tweet_id <= 2 * 10^9
tweet_date is a valid ISO date string
tweet is a text payload that may or may not contain a hashtag token
A valid hashtag token matches #[A-Za-z0-9_]+
Only February 2024 rows are considered
Output columns must be exactly: hashtag, hashtag_count
Sort by hashtag_count DESC, hashtag DESC
Return at most 3 rows
Use SQLite 3.27.2 semantics for SQL submissions
For Pandas submissions, return a DataFrame with columns [hashtag, hashtag_count]

Code

Visualizer

Solutions

14px

Test Cases3

Results

Submissions

Tweets =

February Hashtag Momentum Leaderboard

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February Hashtag Momentum Leaderboard

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