Distribution of Tickets Closed per Shift

PandasHardSenior level~10 min

Problem

You are given two DataFrames. `shift` has columns `agent_id` and `shift_day`; the pair is unique, and each row means an agent worked a shift on that day. `closure` has columns `agent_id`, `closed_on`, and `ticket_no`; each row records one support ticket an agent closed on a day. An agent can close several tickets on the same day, and may close tickets only on a day they actually worked a shift.

For every shift, count how many tickets the agent closed during it. Then build a histogram: for each possible number of tickets closed, report how many shifts had exactly that count.

Return `tickets_closed` (the count value, starting from 0) and `shift_count` (how many shifts closed that many tickets). Include every integer from 0 up to the maximum number of tickets closed in any single shift, even if `shift_count` is 0. Order by `tickets_closed`.

**Example**

```text
If the per-shift ticket counts are {0, 1, 1, 2}, the result is:
tickets_closed=0 -> 1 shift, tickets_closed=1 -> 2 shifts, tickets_closed=2 -> 1 shift.
```

Input data

Example rows — the live problem includes the full dataset.

shift

agent_id	shift_day
1	2023-01-01
1	2023-01-02
2	2023-01-01
2	2023-01-02

closure

agent_id	closed_on	ticket_no
1	2023-01-01	500
2	2023-01-01	501
2	2023-01-01	502

Expected output

Your answer should return 3 rows with the columns tickets_closed, shift_count.

Starter code (Pandas (Python))

import pandas as pd

def distribution_of_tickets_closed_per_shift(shift, closure) -> pd.DataFrame:
    # Your code here
    return shift

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