Borrows per Patron in 2023

Problem

You are given two DataFrames. `patrons` (from `patrons.csv`) has the columns `patron_id` (the key), `signup_day` and `favorite_genre`. `loans` (from `loans.csv`) has the columns `loan_id` (the key), `loan_day`, `book_id`, `patron_id` and `clerk_id`; `patron_id` is the patron who borrowed the book.

For every patron, return their `patron_id`, their `signup_day`, and the number of books they borrowed during the year **2023**. Patrons who borrowed nothing in 2023 should still appear with a count of 0. Name the count column `loans_in_2023`.

Example `patrons`:

```text
patron_id signup_day favorite_genre
1 2022-01-10 fantasy
2 2023-03-05 history
```

Example `loans`:

```text
loan_id loan_day book_id patron_id clerk_id
100 2023-02-01 9 1 50
101 2022-12-30 8 1 50
```

Expected result:

```text
patron_id signup_day loans_in_2023
1 2022-01-10 1
2 2023-03-05 0
```

Patron 1 has one loan dated in 2023 (the 2022 loan does not count); patron 2 has none, so 0.

Input data

Example rows — the live problem includes the full dataset.

Expected output

Your answer should return 2 rows with the columns patron_id, signup_day, loans_in_2023.

Starter code (Pandas (Python))

import pandas as pd

def loans_per_patron(patrons, loans) -> pd.DataFrame:
    # Your code here
    return patrons

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