Pandas Should Go Extinct
The author argues that the Python library Pandas is becoming obsolete for data workloads in the 100GB range, suggesting that modern tools like Polars and DuckDB are more efficient. The piece critiques the industry's tendency to jump to complex distributed systems prematurely.
Why it matters
Challenges standard data engineering practices and advocates for more efficient, single-machine computing solutions.
pandas , python , data , polars , duckdb , analytics This post covers material from a talk I gave at Latency Conference . If you want to just:
You read that correctly, Pandas should go extinct. Not the cute fluffy things used for international diplomacy , but the Python DataFrame library.
Why? Because Pandas’ inefficiencies force you to adopt distributed querying systems before your workloads justify the added complexity. I posit that most workloads will never justify those systems, they are just well marketed “silver bullets”.
To understand what I’m talking about we first must understand the typical adoption pathway for Pandas.
Get smarter about the news
Sign up free for a feed built around what you actually care about, Dive Deeper research on any story, and the full text of every article.
Create free accountAlready have an account? Sign in