Agent Resolution Rate

Problem

A help desk tracks its support agents and the outcome of every ticket they handle.

You are given two DataFrames.

`agents` — one row per agent:

| Column | Type |
|----------|----------|
| agent_id | int |
| hired_at | datetime |

`agent_id` is unique. Each row records when an agent was hired.

`tickets` — one row per ticket:

| Column | Type |
|-----------|----------|
| agent_id | int |
| opened_at | datetime |
| outcome | text |

`(agent_id, opened_at)` is unique. `outcome` is either `'resolved'` or `'escalated'`.

An agent's **resolution rate** is the number of `'resolved'` tickets divided by the total number of tickets that agent handled. An agent who handled no tickets has a resolution rate of `0`. Round the rate to two decimal places.

Return a DataFrame with `agent_id` and `resolution_rate` for every agent, in any order.

Input data

Example rows — the live problem includes the full dataset.

Expected output

Your answer should return 4 rows with the columns agent_id, resolution_rate.

Starter code (Pandas (Python))

import pandas as pd

def agent_resolution_rate(agents: pd.DataFrame, tickets: pd.DataFrame) -> pd.DataFrame:
    # Your code here
    return agents

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