Chained Multi-Branch Conditional Classification

How do we construct multi-tier customer spend segmentation rules with chained when/otherwise logic?

Intermediate⏱ 2 Minutes⭐ 310 XP

🤔 THE QUESTION

How do we construct multi-tier customer spend segmentation rules with chained when/otherwise logic?

💡 WHAT IS IT?

Chaining multiple when() statements sequentially to implement complex CASE-WHEN logic in PySpark.

🎯 WHAT IS IT USED FOR?

Multi-tier loyalty programs, pricing bracket allocations, and credit risk tiering.

💻 EXAMPLE

from pyspark.sql.functions import col, when

df = df.withColumn(
    "customer_segment",
    when(col("spend") > 10000, "High Value")
    .when(col("spend") >= 2500, "Mid Tier")
    .otherwise("Standard")
)

🎯 Mission Objectives

Practice typing production-grade PySpark code for Chained Multi-Branch Conditional Classification.

✓ Chain multiple when() conditions
✓ Implement multi-bracket logic
✓ Assign customer segment labels

🚀 Start Mission

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