Top-Streamed Track in Each Genre

Problem

A music service stores monthly stream counts per track; each track belongs to a genre.

**DataFrame: `tracks`**

| Column | Type |
|------------|---------|
| track_id | int |
| track_name | varchar |
| streams | int |
| genre_id | int |

`track_id` is unique; `genre_id` references `genres.genre_id`.

**DataFrame: `genres`**

| Column | Type |
|------------|---------|
| genre_id | int |
| genre_name | varchar |

`genre_id` is unique.

For each genre, return the track(s) with the **highest** stream count in that genre. If several tracks tie for the most streams in a genre, return all of them. Return three columns named `genre`, `track`, and `streams`, in any order.

Input data

Example rows — the live problem includes the full dataset.

Expected output

Your answer should return 3 rows with the columns genre, track, streams.

Starter code (Pandas (Python))

import pandas as pd

def top_track_per_genre(tracks, genres) -> pd.DataFrame:
    # Your code here
    return tracks

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