Merge and Concatenate Inconsistent Order Files with Pandas

orders_2023

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

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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.