Skip to main content
PYSPARK • LESSON 82

Multi-Column Group Counts

How do we group orders across multiple dimensions (country and status) to analyze fulfillment?

Intermediate2 Minutes390 XP
🤔 THE QUESTION

How do we group orders across multiple dimensions (country and status) to analyze fulfillment?

💡 WHAT IS IT?

Passing multiple column names into groupBy() to partition data into multi-dimensional buckets.

🎯 WHAT IS IT USED FOR?

Cross-dimensional fulfillment tracking, international order monitoring, and cohort breakdown.

💻 EXAMPLE
df.groupBy("country", "status").count().show()

🎯 Mission Objectives

Practice typing production-grade PySpark code for Multi-Column Group Counts.

  • Group across multiple dimensions
  • Compute multi-dimensional counts
  • Inspect fulfillment matrix