Analyze Loan Payments Using Pandas for Key Insights

Q: How do I practice SQL interview questions?

PracHub provides an interactive SQL console where you can write and test queries against real database schemas. Get instant feedback and compare your solution with the expected output.

Q: What difficulty level is this coding question?

This is a Medium difficulty Data Manipulation (SQL/Python) question, commonly asked during Technical Screen rounds at Affirm.

Q: What role is this question designed for?

This question is commonly asked for Data Scientist candidates at Affirm during technical interviews.

Question

loan_payments

+------------+------------+-------------+-----------+---------+
| loan_id    | payment_id | payment_date | amount    | status  |
+------------+------------+-------------+-----------+---------+
| L1         | P1         | 2023-01-15   | 250.00    | success |
| L1         | P2         | 2023-02-15   | 250.00    | success |
| L1         | P3         | 2023-03-15   | 250.00    | success |
| L1         | P4         | 2023-04-15   | 250.00    | success |
| L2         | P5         | 2023-01-20   | 500.00    | failed  |
+------------+------------+-------------+-----------+---------+

##### Scenario

Credit Risk – Analyze loan-payment data with pandas

##### Question

Using pandas, load the loan_payments table below and compute:
(a) total amount paid per loan_id,
(b) payment success rate per loan_id, and
(c) a flag indicating whether the loan has been fully repaid ($1,000 principal). Return the resulting DataFrame.

##### Hints

Use groupby, agg, and boolean logic.

PracHub · Accepted Answer

This question evaluates data manipulation and aggregation skills using pandas, focusing on computing per-loan payment totals, payment success rates, and a repayment-status flag. It is commonly asked to assess applied data wrangling and numeric summarization abilities in the Data Manipulation (SQL/Python) domain, testing practical application rather than purely conceptual understanding.

Quick Overview

Quick Overview