How to Aggregate Provincial Data with Python Pivot Tables vs SQL

1. Introduction

A community member asked how to aggregate 5,000 nationwide records by province, calculating the number of entries, total amount, average, and proportion, and wondered whether Python or SQL would be more convenient.

2. Implementation

One suggestion was to use an Excel pivot table, which can quickly produce the required statistics. The community later solved the problem themselves with Excel.

Another contributor shared a Python approach: using pandas.pivot_table with the aggfunc parameter accepting a list (e.g., sum, mean) or a dictionary to apply different aggregations to multiple columns. This one‑line solution replicates the Excel pivot functionality directly in Python.

3. Summary

The discussion demonstrated how a simple Excel pivot table can address the aggregation need, and how the same result can be achieved programmatically with a concise pandas pivot_table call in Python, offering flexibility for further data processing.