Given a Kaggle dataset, write pandas queries to filter the DataFrame and answer questions about the data.
Asked in the Round 1 stage. Followed a LeetCode-style Python question in the same round.
Using the provided movies and movie_ratings tables, return English-language movies released from 2018 through 2020 whose rating count is at least 100, summarized by genre.
genre, movie_count, rated_movie_count, avg_rating, and high_rating_pctavg_rating descending, then genre ascending| Column | Type | Description |
|---|---|---|
| movie_idPK | INT | Unique movie identifier |
| title | VARCHAR(150) | Movie title |
| genre | VARCHAR(50) | Primary movie genre |
| language | VARCHAR(30) | Primary movie language |
| release_year | INT | Movie release year |
| Column | Type | Description |
|---|---|---|
| movie_idPK | INT | Referenced movie identifier |
| average_rating | DECIMAL(3,1) | Average user rating |
| rating_count | INT | Number of submitted ratings |