Plan Price on a Given Date

Problem

You are given a DataFrame `pricechanges` loaded from `pricechanges.csv` with the columns `plan_id`, `new_price` and `effective_on`. There is no single-column key (a plan can change price many times); each row records that `plan_id`'s price became `new_price` on `effective_on`.

Every plan starts at a base price of **20** before its first recorded change. Return the price of each plan **as of 2024-07-01** (the most recent change on or before that date, or 20 if there is none). Return `plan_id` and a column named `price`.

Example `pricechanges`:

```text
plan_id new_price effective_on
1 35 2024-05-01
1 40 2024-08-01
2 25 2024-06-15
3 50 2024-09-01
```

Expected result:

```text
plan_id price
1 35
2 25
3 20
```

Plan 1's latest change on or before 2024-07-01 set the price to 35 (the 2024-08-01 change is in the future). Plan 3's only change is after the date, so it keeps the base price of 20.

Input data

Example rows — the live problem includes the full dataset.

Expected output

Your answer should return 3 rows with the columns plan_id, price.

Starter code (Pandas (Python))

import pandas as pd

def price_as_of_date(pricechanges) -> pd.DataFrame:
    # Your code here
    return pricechanges

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