Pandas vs Polars in 2025: Who Wins the Data Speed Race?

⚔️ Pandas is mature, flexible, battle-tested.
🚀 Polars is fast, lean, and written in Rust.

Tested on 10-core CPU, here’s what I found:
🔥 Benchmarks (avg. of 3 runs)

• Group by date (76M rows):
• Pandas 28s ⏱ | Polars 4.7s ⚡
• Log filtering (10GB gz):
• Pandas 95s 🐌 | Polars 18s 🏎
• Multi-key group:
• Pandas 6.3s | Polars 0.9s
• Sorting (10M rows):
• Pandas 14s | Polars 3.8s
• Rolling mean:
• Pandas 1.1s | Polars 0.22s

Why Polars flies
✅ True multi-threading
✅ Lazy evaluation
✅ Arrow memory layout
✅ No GIL bottleneck

So, which to pick?
🧪 Pandas for quick experiments & ecosystem glue
💼 Polars for production speed & large datasets

💡 Learn both. Use what fits. Don’t force pandas to do a polar bear’s job.
https://blog.devgenius.io/polars-vs-pandas-2025-which-library-runs-your-data-faster-bd08211e4684