Unlock the power of modern data processing! In this video, we guide you through the upgrade path from Pandas to Polars to Spark, showing you when and why to switch tools for big data workflows. Learn practical tips, performance benchmarks, and hands-on exercises to level up your data engineering skills. Additional affiliate resources: Polars Cookbook Learning Spark, 2nd ed. Download the 1 pager: #dataframe-upgrade-roadmap 0:00 — Intro: Why Pandas Struggles with Big Data 0:26 — The Upgrade Path: Pandas → Polars → Spark 0:47 — Metaphors Explained: Backpack, Truck, Moving Company 0:57 — When to Switch Tools 1:08 — Example 1: Reading CSV and Parquet Files 2:20 — Performance Benchmarks & Practice Exercise 3:50 — Example 2: Group By Aggregation 4:01 — Scaling Up: Local vs. Cluster Performance 4:54 — Example 3: Joining with Dimension Tables 5:05 — Spark Broadcasting & Practice Exercise 5:49 — Cheat Sheet: When to Use Each Tool 6:40 — Common Pitfalls & Optimization Tips 7:43 — Book Recommendations & Further Resources 8:11 — Outro: Next Steps and Call to Action