corpus.blog
41554 blogs · [ { "id": "01a0bded-d374-7231-aa93-c169fd792034", "title": "Profile your Polars queries", "url": "https://pola.rs/posts/profile-local-queries/", "published_at": "2026-09-17T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccdf0ae51e", "title": "Pre-release of Polars 2.0", "url": "https://pola.rs/posts/announcing-polars-2/", "published_at": "2026-09-02T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccdf461fa2", "title": "A new streaming backend for the Polars GPU engine", "url": "https://pola.rs/posts/gpu-streaming-backend/", "published_at": "2026-08-28T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccdfd006a8", "title": "Announcing Polars 1.44", "url": "https://pola.rs/posts/polars-1-44/", "published_at": "2026-08-26T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce04735af", "title": "How BMLL Processes 1.5 TB of Market Data in Under 4 Minutes", "url": "https://pola.rs/posts/case-bmll/", "published_at": "2026-08-25T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce0b2d90e", "title": "Migration strategies for going from pandas to Polars", "url": "https://pola.rs/posts/pandas-to-polars-migration-strategies/", "published_at": "2026-08-06T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce0dcc052", "title": "Announcing Polars Cloud 0.10.0", "url": "https://pola.rs/posts/polars-cloud-0-10/", "published_at": "2026-08-04T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce0eaa30e", "title": "Prototype on a laptop, scale to 16 billion rows: one Polars query", "url": "https://pola.rs/posts/market-data-to-plotly-enterprise-dashboard/", "published_at": "2026-07-28T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce0eecbde", "title": "Announcing Polars 1.43", "url": "https://pola.rs/posts/polars-1-43/", "published_at": "2026-07-23T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce1a7bea0", "title": "Benchmarking single node vs distributed", "url": "https://pola.rs/posts/single-node-vs-distributed/", "published_at": "2026-07-14T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce1e4d1a7", "title": "Polars in Aggregate: Distributed On-Prem, a Spark Benchmark, and a Smarter Optimizer", "url": "https://pola.rs/posts/polars-in-aggregate-jul26/", "published_at": "2026-07-07T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce23e0557", "title": "Announcing Polars Cloud 0.9.0", "url": "https://pola.rs/posts/polars-cloud-0-9/", "published_at": "2026-07-02T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce2a99d70", "title": "Announcing Polars 1.42", "url": "https://pola.rs/posts/polars-1-42/", "published_at": "2026-06-29T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce2f502c5", "title": "Fluent, not native: agents translating pandas to Polars", "url": "https://pola.rs/posts/llm-polars-patterns/", "published_at": "2026-06-25T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce3d4787b", "title": "Benchmarking Polars and Spark", "url": "https://pola.rs/posts/polars-pyspark-benchmarks/", "published_at": "2026-06-16T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce4c81424", "title": "Launching Polars Distributed on Kubernetes", "url": "https://pola.rs/posts/polars-distributed-available-on-kubernetes/", "published_at": "2026-06-03T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce4c9ccda", "title": "Announcing Polars 1.41", "url": "https://pola.rs/posts/polars-1-41/", "published_at": "2026-05-26T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce537009a", "title": "Handling Schema Issues in Polars", "url": "https://pola.rs/posts/schema-evolution/", "published_at": "2026-04-30T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce5ee186f", "title": "Polars in Aggregate: Streaming Expands, Lakehouse I/O, and Cloud Profiling", "url": "https://pola.rs/posts/polars-in-aggregate-apr26/", "published_at": "2026-04-16T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce655231e", "title": "Streaming sort-merge joins in Polars", "url": "https://pola.rs/posts/streaming-joins/", "published_at": "2026-04-09T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce6daf9b9", "title": "Introducing the Query Profiler and Optimizing Cluster Configuration", "url": "https://pola.rs/posts/query-profiler-instance-optimization/", "published_at": "2026-03-26T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce77611c2", "title": "Orchestrating Polars Cloud Queries with Apache Airflow", "url": "https://pola.rs/posts/airflow-orchestration/", "published_at": "2026-02-17T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce7b4fc68", "title": "Understanding the New Categorical", "url": "https://pola.rs/posts/categoricals-refactor/", "published_at": "2026-01-29T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce7d9042d", "title": "How Rabobank leverages window functions to drastically improve performance", "url": "https://pola.rs/posts/case-rabobank/", "published_at": "2025-12-10T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce8a36a52", "title": "Polars in Aggregate: Polars Cloud, Streaming engine, and New Data Types", "url": "https://pola.rs/posts/polars-in-aggregate-dec25/", "published_at": "2025-12-03T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce8e1331d", "title": "Supercharging Analytics with Polars: A Case Study in Analyst Empowerment", "url": "https://pola.rs/posts/case-citizens/", "published_at": "2025-11-26T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce99520dd", "title": "Polars helps coping with black swan events at La Mobilière", "url": "https://pola.rs/posts/case-mobiliere/", "published_at": "2025-10-09T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce99cebfb", "title": "Polars raises €18M Series A to build fast, ergonomic data processing at any scale", "url": "https://pola.rs/posts/series_a/", "published_at": "2025-09-29T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cce9c3e4e7", "title": "Polars at Decathlon: Ready to Play?", "url": "https://pola.rs/posts/case-decathlon/", "published_at": "2025-09-15T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cceaadb515", "title": "Launch of Polars Cloud and Distributed Polars", "url": "https://pola.rs/posts/polars-cloud-launch/", "published_at": "2025-09-03T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cceb896e1d", "title": "Polars Meetup #2: Polars at Scale", "url": "https://pola.rs/posts/talk-polars-meetup-2-at-scale/", "published_at": "2025-07-31T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cceba641b7", "title": "Introducing UVM for larger than VRAM data on the Polars GPU engine", "url": "https://pola.rs/posts/uvm-larger-than-ram-gpu/", "published_at": "2025-06-26T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccec38cabe", "title": "Updated PDS-H benchmark results (May 2025)", "url": "https://pola.rs/posts/benchmarks/", "published_at": "2025-06-01T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccec4dfea4", "title": "METRO.digital Optimized Their KPI Creation Process Across 19 Countries with Polars", "url": "https://pola.rs/posts/case-metro-digital/", "published_at": "2025-04-24T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccec8dd746", "title": "Polars Meetup #1: New Streaming Engine", "url": "https://pola.rs/posts/talk-polars-meetup-1-streaming-engine/", "published_at": "2025-04-09T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccec919c6c", "title": "Polars Cloud; the distributed Cloud Architecture to run Polars anywhere", "url": "https://pola.rs/posts/polars-cloud-what-we-are-building/", "published_at": "2025-02-10T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cced172141", "title": "Exploring calendar-aware date operations in Polars", "url": "https://pola.rs/posts/exploring-calendar-aware-date-operations-in-polars/", "published_at": "2024-12-23T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cced27c6ba", "title": "Breaking the rules with expression expansion", "url": "https://pola.rs/posts/breaking-the-rules-with-expression-expansion/", "published_at": "2024-12-05T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cced37b91a", "title": "Polars in Aggregate: Faster I/O, inequality joins, and much more", "url": "https://pola.rs/posts/polars-in-aggregate-dec24/", "published_at": "2024-12-04T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cced37cbdb", "title": "Understanding Polars data types", "url": "https://pola.rs/posts/understanding-polars-data-types/", "published_at": "2024-11-26T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cced7a2bae", "title": "PyData NYC 2024: Polars GPU Acceleration", "url": "https://pola.rs/posts/talk-pydata-nyc-2024/", "published_at": "2024-11-25T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cced906bf0", "title": "PyData Amsterdam 2024: Polars 1.0 and Beyond", "url": "https://pola.rs/posts/talk-pydata-amsterdam-2024/", "published_at": "2024-10-22T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccedb8bb61", "title": "Efficient Cloud Data Processing with Polars – a DB Systel Case Study", "url": "https://pola.rs/posts/case-db-systel/", "published_at": "2024-10-17T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccede5794a", "title": "Joulen accelerates the transition to sustainable energy practices using Polars", "url": "https://pola.rs/posts/case-joulen/", "published_at": "2024-09-25T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccee4caa08", "title": "GPU acceleration with Polars and NVIDIA RAPIDS", "url": "https://pola.rs/posts/gpu-engine-release/", "published_at": "2024-09-17T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13cceefc9b23", "title": "Transforming Music Data Management: How Polars Redefined CSV Processing at Vydia", "url": "https://pola.rs/posts/case-vydia/", "published_at": "2024-09-13T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccef052ee6", "title": "Polars has a new lightweight plotting backend", "url": "https://pola.rs/posts/lightweight_plotting/", "published_at": "2024-09-04T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccef27157e", "title": "Benchmarking energy usage and performance of Polars and pandas", "url": "https://pola.rs/posts/benchmark-energy-performance/", "published_at": "2024-08-22T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccef76c8d6", "title": "Complex Calculations vs. Polars Plugins - A Double River Case Study", "url": "https://pola.rs/posts/case-double-river/", "published_at": "2024-08-14T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccf06f2ed1", "title": "Hugging Face x Polars", "url": "https://pola.rs/posts/polars-hugging-face/", "published_at": "2024-08-09T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccf11f0a52", "title": "Polars in Aggregate: Improved I/O, Hugging Face support, and more", "url": "https://pola.rs/posts/polars-in-aggregate-juli24/", "published_at": "2024-07-25T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccf1ece25e", "title": "Announcing Polars 1.0", "url": "https://pola.rs/posts/announcing-polars-1/", "published_at": "2024-07-01T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccf287e34b", "title": "Processing hundreds of GBs of textual data on a daily basis at MDPI", "url": "https://pola.rs/posts/case-mdpi/", "published_at": "2024-06-27T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccf2e1bc76", "title": "Polars in Aggregate: Faster CSV writer, dead expression elimination, and more", "url": "https://pola.rs/posts/polars-in-aggregate-jun24/", "published_at": "2024-06-05T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccf32e50f6", "title": "PyCon Lithuania 2024: Keynote on Polars", "url": "https://pola.rs/posts/talk-pycon-lithuania-2024/", "published_at": "2024-05-02T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccf33273f1", "title": "G-Research tackles the biggest financial data challenges of tomorrow with Polars", "url": "https://pola.rs/posts/case-gresearch/", "published_at": "2024-04-18T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccf3562498", "title": "Updated PDS-H benchmark results", "url": "https://pola.rs/posts/benchmarks-2024/", "published_at": "2024-04-16T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccf35ed811", "title": "Accelerating Polars DataFrames", "url": "https://pola.rs/posts/polars-on-gpu/", "published_at": "2024-04-04T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccf3c3632b", "title": "Polars in Aggregate: New integrations, enhanced NumPy interop, and improved performance", "url": "https://pola.rs/posts/polars-in-aggregate-mar24/", "published_at": "2024-03-28T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccf3cdf733", "title": "The power of predicate pushdown", "url": "https://pola.rs/posts/predicate-pushdown-query-optimizer/", "published_at": "2024-03-19T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccf42d70cc", "title": "Check Technologies saves 25% of cloud expenses with Polars", "url": "https://pola.rs/posts/case-check-technology/", "published_at": "2024-03-06T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccf4717bc0", "title": "Polars in Aggregate: New string type, plotting, SQL and more", "url": "https://pola.rs/posts/polars-in-aggregate-feb24/", "published_at": "2024-02-07T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccf54e7be0", "title": "Why we have rewritten the string data type", "url": "https://pola.rs/posts/polars-string-type/", "published_at": "2024-01-30T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccf5f2ec9d", "title": "A bird's eye view of Polars", "url": "https://pola.rs/posts/polars_birds_eye_view/", "published_at": "2024-01-19T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccf6903d9f", "title": "Global DevSlam 2023: Polars, a Lightning-Fast DataFrame Library", "url": "https://pola.rs/posts/talk-global-devslam-2023/", "published_at": "2024-01-09T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccf756b36c", "title": "Polars in Aggregate: Going from 0.19.0 to 0.20.2", "url": "https://pola.rs/posts/polars_in_aggregrate-0.20", "published_at": "2024-01-04T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccf84fc717", "title": "PyData Eindhoven 2023: Keynote on Polars Plugins", "url": "https://pola.rs/posts/talk-pydata-plugins-keynote-2023/", "published_at": "2023-12-21T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccf8ce2620", "title": "PyData NYC 2023: Polars; DataFrames in the Multi-Core Era", "url": "https://pola.rs/posts/talk-pydata-nyc-2023/", "published_at": "2023-11-29T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccf8dbe072", "title": "PyData Amsterdam 2023: Polars and a Peek into the Expression Engine", "url": "https://pola.rs/posts/talk-pydata-amsterdam-2023/", "published_at": "2023-11-22T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccf9affe5f", "title": "Polars 0.19 upgrade guide", "url": "https://pola.rs/posts/polars-0-19-upgrade-guide/", "published_at": "2023-08-31T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccfa93e54c", "title": "Company announcement", "url": "https://pola.rs/posts/company-announcement/", "published_at": "2023-08-03T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccfb7ad490", "title": "EuroPython 2023: What Polars Does for You", "url": "https://pola.rs/posts/talk-europython-2023/", "published_at": "2023-07-20T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccfbe20c29", "title": "PyCon Lithuania 2023: Polars; Done the Fast, Now the Scale", "url": "https://pola.rs/posts/talk-pycon-lithuania-2023/", "published_at": "2023-06-17T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccfcb2ce1c", "title": "PDS-H Benchmark", "url": "https://pola.rs/posts/benchmarks-2023/", "published_at": "2023-01-01T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccfd184e56", "title": "PyData Global 2021: Introduction to Polars", "url": "https://pola.rs/posts/pydata-global-2021/", "published_at": "2022-01-22T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccfd658c5e", "title": "The Expressions API in Polars is Amazing", "url": "https://pola.rs/posts/the-expressions-api-in-polars-is-amazing/", "published_at": "2021-11-21T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccfe2d4ac1", "title": "Bristech: Polars DataFrame library built on Apache Arrow", "url": "https://pola.rs/posts/talk-bristech-bytesize-conference/", "published_at": "2021-09-16T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccfe8bd80b", "title": "Xomnia Data & Drinks: Polars, the Fastest DataFrame Library You Never Heard Of", "url": "https://pola.rs/posts/talk-xomnia-data-drinks-2021/", "published_at": "2021-03-22T00:00:00+00:00" }, { "id": "01a07df4-9498-71fb-b9ba-13ccff5e5f7e", "title": "I wrote one of the fastest DataFrame libraries", "url": "https://pola.rs/posts/i-wrote-one-of-the-fastest-dataframe-libraries/", "published_at": "2021-02-28T00:00:00+00:00" } ] posts Claim your blog
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Polars Blog

pola.rs

2026

Profile your Polars queriesoriginal ↗
17 Sept 2026
Pre-release of Polars 2.0original ↗
2 Sept 2026
A new streaming backend for the Polars GPU engineoriginal ↗
28 Aug 2026
Announcing Polars 1.44original ↗
26 Aug 2026
How BMLL Processes 1.5 TB of Market Data in Under 4 Minutesoriginal ↗
25 Aug 2026
Migration strategies for going from pandas to Polarsoriginal ↗
6 Aug 2026
Announcing Polars Cloud 0.10.0original ↗
4 Aug 2026
Prototype on a laptop, scale to 16 billion rows: one Polars queryoriginal ↗
28 Jul 2026
Announcing Polars 1.43original ↗
23 Jul 2026
Benchmarking single node vs distributedoriginal ↗
14 Jul 2026
Polars in Aggregate: Distributed On-Prem, a Spark Benchmark, and a Smarter Optimizeroriginal ↗
7 Jul 2026
Announcing Polars Cloud 0.9.0original ↗
2 Jul 2026
Announcing Polars 1.42original ↗
29 Jun 2026
Fluent, not native: agents translating pandas to Polarsoriginal ↗
25 Jun 2026
Benchmarking Polars and Sparkoriginal ↗
16 Jun 2026
Launching Polars Distributed on Kubernetesoriginal ↗
3 Jun 2026
Announcing Polars 1.41original ↗
26 May 2026
Handling Schema Issues in Polarsoriginal ↗
30 Apr 2026
Polars in Aggregate: Streaming Expands, Lakehouse I/O, and Cloud Profilingoriginal ↗
16 Apr 2026
Streaming sort-merge joins in Polarsoriginal ↗
9 Apr 2026
Introducing the Query Profiler and Optimizing Cluster Configurationoriginal ↗
26 Mar 2026
Orchestrating Polars Cloud Queries with Apache Airfloworiginal ↗
17 Feb 2026
Understanding the New Categoricaloriginal ↗
29 Jan 2026

2025

How Rabobank leverages window functions to drastically improve performanceoriginal ↗
10 Dec 2025
Polars in Aggregate: Polars Cloud, Streaming engine, and New Data Typesoriginal ↗
3 Dec 2025
Supercharging Analytics with Polars: A Case Study in Analyst Empowermentoriginal ↗
26 Nov 2025
Polars helps coping with black swan events at La Mobilièreoriginal ↗
9 Oct 2025
Polars raises €18M Series A to build fast, ergonomic data processing at any scaleoriginal ↗
29 Sept 2025
Polars at Decathlon: Ready to Play?original ↗
15 Sept 2025
Launch of Polars Cloud and Distributed Polarsoriginal ↗
3 Sept 2025
Polars Meetup #2: Polars at Scaleoriginal ↗
31 Jul 2025
Introducing UVM for larger than VRAM data on the Polars GPU engineoriginal ↗
26 Jun 2025
Updated PDS-H benchmark results (May 2025)original ↗
1 Jun 2025
METRO.digital Optimized Their KPI Creation Process Across 19 Countries with Polarsoriginal ↗
24 Apr 2025
Polars Meetup #1: New Streaming Engineoriginal ↗
9 Apr 2025
Polars Cloud; the distributed Cloud Architecture to run Polars anywhereoriginal ↗
10 Feb 2025

2024

Exploring calendar-aware date operations in Polarsoriginal ↗
23 Dec 2024
Breaking the rules with expression expansionoriginal ↗
5 Dec 2024
Polars in Aggregate: Faster I/O, inequality joins, and much moreoriginal ↗
4 Dec 2024
Understanding Polars data typesoriginal ↗
26 Nov 2024
PyData NYC 2024: Polars GPU Accelerationoriginal ↗
25 Nov 2024
PyData Amsterdam 2024: Polars 1.0 and Beyondoriginal ↗
22 Oct 2024
Efficient Cloud Data Processing with Polars – a DB Systel Case Studyoriginal ↗
17 Oct 2024
Joulen accelerates the transition to sustainable energy practices using Polarsoriginal ↗
25 Sept 2024
GPU acceleration with Polars and NVIDIA RAPIDSoriginal ↗
17 Sept 2024
Transforming Music Data Management: How Polars Redefined CSV Processing at Vydiaoriginal ↗
13 Sept 2024
Polars has a new lightweight plotting backendoriginal ↗
4 Sept 2024
Benchmarking energy usage and performance of Polars and pandasoriginal ↗
22 Aug 2024
Complex Calculations vs. Polars Plugins - A Double River Case Studyoriginal ↗
14 Aug 2024
Hugging Face x Polarsoriginal ↗
9 Aug 2024
Polars in Aggregate: Improved I/O, Hugging Face support, and moreoriginal ↗
25 Jul 2024
Announcing Polars 1.0original ↗
1 Jul 2024
Processing hundreds of GBs of textual data on a daily basis at MDPIoriginal ↗
27 Jun 2024
Polars in Aggregate: Faster CSV writer, dead expression elimination, and moreoriginal ↗
5 Jun 2024
PyCon Lithuania 2024: Keynote on Polarsoriginal ↗
2 May 2024
G-Research tackles the biggest financial data challenges of tomorrow with Polarsoriginal ↗
18 Apr 2024
Updated PDS-H benchmark resultsoriginal ↗
16 Apr 2024
Accelerating Polars DataFramesoriginal ↗
4 Apr 2024
Polars in Aggregate: New integrations, enhanced NumPy interop, and improved performanceoriginal ↗
28 Mar 2024
The power of predicate pushdownoriginal ↗
19 Mar 2024
Check Technologies saves 25% of cloud expenses with Polarsoriginal ↗
6 Mar 2024
Polars in Aggregate: New string type, plotting, SQL and moreoriginal ↗
7 Feb 2024
Why we have rewritten the string data typeoriginal ↗
30 Jan 2024
A bird's eye view of Polarsoriginal ↗
19 Jan 2024
Global DevSlam 2023: Polars, a Lightning-Fast DataFrame Libraryoriginal ↗
9 Jan 2024
Polars in Aggregate: Going from 0.19.0 to 0.20.2original ↗
4 Jan 2024

2023

PyData Eindhoven 2023: Keynote on Polars Pluginsoriginal ↗
21 Dec 2023
PyData NYC 2023: Polars; DataFrames in the Multi-Core Eraoriginal ↗
29 Nov 2023
PyData Amsterdam 2023: Polars and a Peek into the Expression Engineoriginal ↗
22 Nov 2023
Polars 0.19 upgrade guideoriginal ↗
31 Aug 2023
Company announcementoriginal ↗
3 Aug 2023
EuroPython 2023: What Polars Does for Youoriginal ↗
20 Jul 2023
PyCon Lithuania 2023: Polars; Done the Fast, Now the Scaleoriginal ↗
17 Jun 2023
PDS-H Benchmarkoriginal ↗
1 Jan 2023

2022

PyData Global 2021: Introduction to Polarsoriginal ↗
22 Jan 2022

2021

The Expressions API in Polars is Amazingoriginal ↗
21 Nov 2021
Bristech: Polars DataFrame library built on Apache Arroworiginal ↗
16 Sept 2021
Xomnia Data & Drinks: Polars, the Fastest DataFrame Library You Never Heard Oforiginal ↗
22 Mar 2021
I wrote one of the fastest DataFrame librariesoriginal ↗
28 Feb 2021