Dynamic Column Transformations

How can we dynamically trim all string columns in a DataFrame using list comprehension without hardcoding column names?

Advanced⏱ 3 Minutes⭐ 840 XP

🤔 THE QUESTION

How can we dynamically trim all string columns in a DataFrame using list comprehension without hardcoding column names?

💡 WHAT IS IT?

Iterating through df.dtypes enables programmatic generation of transformation expressions for specific data types.

🎯 WHAT IS IT USED FOR?

Sanitizing enterprise datasets with dozens of string columns during automated ingestion pipelines.

💻 EXAMPLE

string_cols = [c for c, t in df.dtypes if t == "string"]
df_clean = df.select([trim(col(c)).alias(c) if c in string_cols else col(c) for c in df.columns])

🎯 Mission Objectives

Practice typing production-grade PySpark code for Dynamic Column Transformations.

✓ df.dtypes iteration
✓ Programmatic expression generation
✓ Batch column sanitization

🚀 Start Mission

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