Polars DataFrame blog pola.rs

A collection of articles on the usage / internal workings of Polars by the core team.

Efficient Cloud Data Processing with Polars – a DB Systel Case Study
pola.rs·82w
Joulen accelerates the transition to sustainable energy practices using Polars
pola.rs·85w
GPU acceleration with Polars and NVIDIA RAPIDS
pola.rs·86w
Transforming Music Data Management: How Polars Redefined CSV Processing at Vydia
pola.rs·87w
Polars has a new lightweight plotting backend
pola.rs·88w
Benchmarking energy usage and performance of Polars and pandas
pola.rs·90w
Complex Calculations vs. Polars Plugins - A Double River Case Study
pola.rs·91w
Hugging Face x Polars
pola.rs·92w
Polars in Aggregate: Improved I/O, Hugging Face support, and more
pola.rs·94w
Announcing Polars 1.0
pola.rs·97w
Processing hundreds of GBs of textual data on a daily basis at MDPI
pola.rs·98w
Polars in Aggregate: Faster CSV writer, dead expression elimination, and more
pola.rs·101w
G-Research tackles the biggest financial data challenges of tomorrow with Polars
pola.rs·108w
Updated PDS-H benchmark results
pola.rs·108w
Updated PDS-H benchmark results
pola.rs·108w
Accelerating Polars DataFrames
pola.rs·110w
Polars in Aggregate: New integrations, enhanced NumPy interop, and improved performance
pola.rs·111w
The power of predicate pushdown
pola.rs·112w
Check Technologies saves 25% of cloud expenses with Polars
pola.rs·114w
Polars in Aggregate: New string type, plotting, SQL and more
pola.rs·118w

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