Coding questions · Boston Consulting Group

Merge and Concatenate Inconsistent Order Files with Pandas

This question evaluates proficiency with pandas-based data manipulation, including schema alignment, column renaming, type casting, and vertical concatenation when merging CSV files.

orders_2023

+----------+-------------+--------+
| order_id | customer_id | amount |
+----------+-------------+--------+
| 101      | C001        | 120.5  |
| 102      | C002        |  75.0  |
| 103      | C003        | 140.0  |
+----------+-------------+--------+

orders_2024

+----------+-------------+--------+
| orderid  | customer_id | amount |
+----------+-------------+--------+
| 201      | C001        | 110.0  |
| 202      | C004        |  95.0  |
| 203      | C005        | 180.0  |
+----------+-------------+--------+

Scenario

BCG CodeSignal notebook – merging annual order files with schema inconsistencies

Question

Using Python (pandas), load orders_2023.csv and orders_2024.csv, rename columns so both have ['order_id','customer_id','amount'], cast amount to float, then vertically concatenate them into one DataFrame called orders_all.

Hints

read_csv ➜ rename ➜ astype ➜ concat; watch the typo in orderid.