Flatten Nested List Columns with df.explode() in Pandas

Question

Given an order table where `product_ids` contains a list of items `[101, 102, 103]`, unnest the list so that each product appears on its own row with duplicate order details.

Accepted Answer

Optimal Solution:
import pandas as pd

# explode unrolls lists into rows, replicating all other column data
exploded_df = df.explode('product_ids').reset_index(drop=True)

Technical Explanation:
`.explode('column')` takes elements of an iterable column and creates a separate row for each item while replicating the remaining columns.

order_id	product_ids
1	101,102
2	103

order_id	product_ids
1	101
1	102
2	103