Daily Distinct Gym Visitors

PandasEasyJunior level~10 min

Problem

You are given a DataFrame `checkins` loaded from `checkins.csv` with the columns `member_id`, `visit_id`, `visit_day` and `zone`. There is no single-column key: a member can pass through the turnstile many times in one day, and each row is one entry.

A member is *active* on a day if they have at least one check-in that day. For each day in the 30-day window ending **2024-05-31 inclusive** (from 2024-05-02 to 2024-05-31), return the day and the number of distinct active members. Name the columns `day` and `active_members`, and only include days that actually have at least one check-in.

Example `checkins`:

```text
member_id visit_id visit_day zone
1 10 2024-05-02 weights
1 11 2024-05-02 cardio
2 12 2024-05-02 pool
3 13 2024-05-31 weights
```

Expected result:

```text
day active_members
2024-05-02 2
2024-05-31 1
```

On 2024-05-02 members 1 and 2 were active (member 1's two check-ins count once). On 2024-05-31 only member 3 was active.

Input data

Example rows — the live problem includes the full dataset.

checkins

member_id	visit_id	visit_day	zone
1	10	2024-05-02	weights
1	11	2024-05-02	cardio
2	12	2024-05-02	pool
3	13	2024-05-31	weights

Expected output

Your answer should return 2 rows with the columns day, active_members.

Starter code (Pandas (Python))

import pandas as pd

def daily_active_members(checkins) -> pd.DataFrame:
    # Your code here
    return checkins

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