Python Pipeline Automates CSV Executive Reports With 45-Row Sales Analysis and Claude Opus 4.8
Updated
Updated · KDnuggets · Aug 5
Python Pipeline Automates CSV Executive Reports With 45-Row Sales Analysis and Claude Opus 4.8
1 articles · Updated · KDnuggets · Aug 5
Summary
A Python workflow turns a raw CSV into an executive report by cleaning data, calculating aggregates, generating charts and using Claude Opus 4.8 to draft insights from a summarized prompt.
In the 45-row sales example, the pipeline drops 3 pending or failed transactions, leaving 42 completed records so failed payments are not mistakenly counted as revenue.
Those cleaned figures produce $12,975 in gross sales, $4,875 in refunds and $8,100 in net revenue, with a 38% refund rate that the article frames as the key business signal.
Weekly and country cuts explain the pattern: the first three weeks are net positive, the last three net negative, Canada nets $0 after two refunded orders, and the median refund arrives 20 days after purchase.
The report argues AI should stay limited to narrative drafting because the model sees only clean aggregates, while humans still verify truth, sample-size limits and business context before using the output.