Average Listening Sessions per Listener

PandasEasyJunior level~10 min

Problem

You are given a DataFrame `plays` loaded from `plays.csv` with the columns `listener_id`, `session_ref`, `play_day` and `track_genre`. There is no single-column key; each row is one track play inside a listening session.

For the 30-day window ending **2024-09-30 inclusive** (from 2024-09-01 to 2024-09-30), return the average number of distinct sessions per distinct listener, rounded to 2 decimal places. If there are no rows in the window the answer should be 0.00. Name the single output column `avg_sessions_per_listener`.

Example `plays`:

```text
listener_id session_ref play_day track_genre
1 100 2024-09-01 jazz
1 100 2024-09-01 jazz
1 101 2024-09-02 rock
2 200 2024-09-10 pop
```

Expected result is `1.5`: there are 3 distinct sessions (100, 101, 200) across 2 distinct listeners, so 3 / 2 = 1.5.

Input data

Example rows — the live problem includes the full dataset.

plays

listener_id	session_ref	play_day	track_genre
1	100	2024-09-01	jazz
1	100	2024-09-01	jazz
1	101	2024-09-02	rock
2	200	2024-09-10	pop

Expected output

Your answer should return 1 row with the columns avg_sessions_per_listener.

Starter code (Pandas (Python))

import pandas as pd

def avg_sessions(plays) -> pd.DataFrame:
    # Your code here
    return plays

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