00:00:00

Description

Editorial

Frequent Actor-Director Collaboration Pairs

EASY10 pts

You are given an ActorDirector event table that stores one row per recorded collaboration between an actor and a director.

Columns:

actor_id: actor identifier
director_id: director identifier
timestamp: unique event timestamp for that collaboration row

Task:

Find every distinct pair (actor_id, director_id) that collaborated at least three times.
Return each qualifying pair exactly once.
Output row order does not matter.

Supported submission environments:

SQL (SQLite 3.27.2)
Pandas (Python)

Example

Input

ActorDirector:
| actor_id | director_id | timestamp |
|----------|-------------|-----------|
| 1        | 1           | 0         |
| 1        | 1           | 1         |
| 1        | 1           | 2         |
| 1        | 2           | 3         |
| 1        | 2           | 4         |
| 2        | 1           | 5         |
| 2        | 1           | 6         |

Output

[
  {"actor_id":1,"director_id":1}
]

Explanation

Pair (1, 1) appears three times, so it qualifies. Pairs (1, 2) and (2, 1) appear only twice.

Example

Input

ActorDirector:
| actor_id | director_id | timestamp |
|----------|-------------|-----------|
| 4        | 7           | 11        |
| 4        | 7           | 12        |
| 4        | 7           | 13        |
| 4        | 7           | 14        |
| 4        | 8           | 21        |
| 4        | 8           | 22        |
| 4        | 8           | 23        |
| 9        | 1           | 24        |

Output

[
  {"actor_id":4,"director_id":7},
  {"actor_id":4,"director_id":8}
]

Explanation

Pair (4, 7) appears 4 times and pair (4, 8) appears 3 times. Pair (9, 1) appears once.

Example

Input

ActorDirector:
| actor_id | director_id | timestamp |
|----------|-------------|-----------|
| 10       | 20          | 100       |
| 10       | 20          | 101       |
| 10       | 21          | 102       |
| 11       | 20          | 103       |
| 11       | 20          | 104       |
| 12       | 22          | 105       |

Output

[]

Explanation

No pair reaches three collaborations, so the output is empty.

Accepted0/0·0% Acceptance

Constraints

1 <= number of rows in ActorDirector <= 10,000
1 <= actor_id <= 1,000,000,000
1 <= director_id <= 1,000,000,000
1 <= timestamp <= 1,000,000,000
timestamp is unique per row
A pair qualifies only when its frequency is >= 3
Return each qualifying pair once with columns actor_id, director_id
Use SQLite 3.27.2 semantics for SQL submissions
For Pandas submissions, return a DataFrame with columns actor_id and director_id

Code

Visualizer

Solutions

14px

Test Cases3

Results

Submissions

actordirector =

[{"actor_id":1,"director_id":1,"timestamp":1},{"actor_id":1,"director_id":1,"timestamp":2},{"actor_id":1,"director_id":1,"timestamp":3},{"actor_id":1,"director_id":2,"timestamp":4},{"actor_id":1,"director_id":2,"timestamp":5},{"actor_id":2,"director_id":1,"timestamp":6},{"actor_id":2,"director_id":1,"timestamp":7}]

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101

00:00:00

Description

Editorial

Frequent Actor-Director Collaboration Pairs

EASY10 pts

You are given an ActorDirector event table that stores one row per recorded collaboration between an actor and a director.

Columns:

actor_id: actor identifier
director_id: director identifier
timestamp: unique event timestamp for that collaboration row

Task:

Find every distinct pair (actor_id, director_id) that collaborated at least three times.
Return each qualifying pair exactly once.
Output row order does not matter.

Supported submission environments:

SQL (SQLite 3.27.2)
Pandas (Python)

Example

Input

ActorDirector:
| actor_id | director_id | timestamp |
|----------|-------------|-----------|
| 1        | 1           | 0         |
| 1        | 1           | 1         |
| 1        | 1           | 2         |
| 1        | 2           | 3         |
| 1        | 2           | 4         |
| 2        | 1           | 5         |
| 2        | 1           | 6         |

Output

[
  {"actor_id":1,"director_id":1}
]

Explanation

Pair (1, 1) appears three times, so it qualifies. Pairs (1, 2) and (2, 1) appear only twice.

Example

Input

ActorDirector:
| actor_id | director_id | timestamp |
|----------|-------------|-----------|
| 4        | 7           | 11        |
| 4        | 7           | 12        |
| 4        | 7           | 13        |
| 4        | 7           | 14        |
| 4        | 8           | 21        |
| 4        | 8           | 22        |
| 4        | 8           | 23        |
| 9        | 1           | 24        |

Output

[
  {"actor_id":4,"director_id":7},
  {"actor_id":4,"director_id":8}
]

Explanation

Pair (4, 7) appears 4 times and pair (4, 8) appears 3 times. Pair (9, 1) appears once.

Example

Input

ActorDirector:
| actor_id | director_id | timestamp |
|----------|-------------|-----------|
| 10       | 20          | 100       |
| 10       | 20          | 101       |
| 10       | 21          | 102       |
| 11       | 20          | 103       |
| 11       | 20          | 104       |
| 12       | 22          | 105       |

Output

[]

Explanation

No pair reaches three collaborations, so the output is empty.

Accepted0/0·0% Acceptance

Constraints

1 <= number of rows in ActorDirector <= 10,000
1 <= actor_id <= 1,000,000,000
1 <= director_id <= 1,000,000,000
1 <= timestamp <= 1,000,000,000
timestamp is unique per row
A pair qualifies only when its frequency is >= 3
Return each qualifying pair once with columns actor_id, director_id
Use SQLite 3.27.2 semantics for SQL submissions
For Pandas submissions, return a DataFrame with columns actor_id and director_id

Code

Visualizer

Solutions

14px

Test Cases3

Results

Submissions

actordirector =

Frequent Actor-Director Collaboration Pairs

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Frequent Actor-Director Collaboration Pairs

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