PySpark Column Operations Explained | select, withColumn, rename, cast, drop (Day 7)
Welcome to Day 7 of the PySpark for Data Engineering series.
In this video, we learn column operations in PySpark — one of the most important skills for real-world ETL pipelines. You’ll learn how to select columns, create new columns using withColumn, rename columns, drop columns, and change column data types using cast.
These operations form the foundation of most Data Engineering transformations.
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🎯 What you’ll learn in this video:
✔ How to select specific columns in PySpark
✔ How to create new columns using withColumn
✔ How to rename columns using withColumnRenamed
✔ How to drop columns
✔ How to change column data types using cast
✔ Chaining multiple transformations together
✔ How PySpark transformations work internally
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👥 Who should watch this?
• Data Engineers
• PySpark beginners
• ETL developers
• Big Data engineers
• Interview preparation candidates
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📅 Series Roadmap:
▶ Day 8 – Joins in PySpark (Inner, Left, Right, Full)
▶ Aggregations
▶ Filtering
▶ Window functions
▶ Real-world ETL pipelines
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🧠 Why column operations matter:
Most real-world data transformations involve modifying columns. These operations are essential for building ETL pipelines and preparing data for analytics.
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