PySpark Null & Comparison Functions : Between(), isNull(), isin(), like(), rlike(), ilike()

In this PySpark tutorial, learn how to use powerful null-checking and comparison functions like between(), isNull(), isin(), like(), rlike(), and ilike() to filter and analyze your DataFrame data. We’ll walk through practical examples that show how to write clean, efficient PySpark queries for pattern matching, range checking, and handling NULL values in large datasets.

🔍 What You’ll Learn:

How to filter rows using between() for range conditions
Detect and handle NULL values with isNull()
Match multiple values using isin()
Use pattern matching with like(), rlike() (regex), and ilike() (case-insensitive)
Combine these functions in real-world PySpark DataFrame filters
Perfect for data engineers, analysts, and developers working with big data in PySpark.

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