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Code Keys/PySpark Academy/Module 25/Lesson 196
PYSPARK • LESSON 196

Multi-Level Regional KPI Aggregation

How do we aggregate enriched sales by region and category to compute transaction count, unique products, and sales totals?

Production⏱ 3 Minutes⭐ 1750 XP
🤔 THE QUESTION

How do we aggregate enriched sales by region and category to compute transaction count, unique products, and sales totals?

💡 WHAT IS IT?

Multi-dimensional dimensional aggregation computing transaction volume, unique SKU counts, total sales, and averages.

🎯 WHAT IS IT USED FOR?

Executive sales scorecards, regional merchandise performance, and quarterly business reviews.

💻 EXAMPLE
from pyspark.sql.functions import avg, col, count, countDistinct, round, sum

regional_kpis = enriched_sales.groupBy("region", "category") \
    .agg(
        count("transaction_id").alias("total_txns"),
        countDistinct("product_name").alias("unique_products_sold"),
        round(sum("revenue"), 2).alias("total_revenue"),
        round(avg("revenue"), 2).alias("avg_txn_value")
    )

🎯 Mission Objectives

Practice typing production-grade PySpark code for Multi-Level Regional KPI Aggregation.

  • ✓ Group by geographic region and product category
  • ✓ Aggregate transaction count and distinct product cardinality
  • ✓ Compute rounded revenue totals and averages
🚀 Start Mission
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