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@DataPolars

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422

Dataframes powered by a multithreaded, vectorized query engine, written in Rust.

Amsterdam
Joined July 2022
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@vanstriendaniel
Daniel van Strien
5 days
Is the web getting more educational? @DataPolars can stream (some would say blazingly fast) from @huggingface Hub. I analysed 736GB from finepdfs-edu without downloading locally. 50M rows spanning 2013-2025. Answer: Yes. High-quality educational content is up ~22%. ~14 min
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@DataPolars
polars data
5 days
"We adopted Polars to meet strict technical requirements, but the result went beyond simple optimization. The 30x performance improvement gave us the unexpected opportunity to do more." Read about how Rabobank successfully deployed Polars in a critical enterprise production
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@premium
Premium
4 months
Enjoy the best experience on X.
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@DataPolars
polars data
7 days
We've just released 1.36.0 with a couple of big features. Here are the highlights: Highlights: 🧩 Extension Types: Allows for custom data types within the Polars ecosystem. You can see an example in the image below. πŸ›Ÿ Float16 Support: First-class support for model parameters
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@DataPolars
polars data
13 days
It’s been a year since the last Polars in Aggregate. Since then, we've shipped 37 releases, merged over 2,300 PRs, and built two new engines. Here is what you need to know: ☁️ Polars Cloud is Live: Write code once, run it anywhere. Whether processing hundreds of rows locally or
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@RitchieVink
Ritchie Vink
15 days
The pre-release of Polars 1.36 is out. Please give it a try so that we can ensure a stable final release with minimal regressions. It lands a lot of goodies: - Extension types - Lazy pivots - Streaming group_by_dynamic - Float16 support - Nested .over()/ window expressions
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github.com
πŸ† Highlights Add Extension types (#25322) ✨ Enhancements Add SQL support for ROW_NUMBER, RANK, and DENSE_RANK functions (#25409) Add SQL support for named WINDOW references (#25400) Add BIT_NOT ...
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@Wayfair
Wayfair.com
21 days
Our favorite piping hot hosting hack (literally) ♨️
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@lhoestq
Quentin Lhoest πŸ€—
16 days
Just merged: 100x Faster scans with @DataPolars of large scale datasets on @huggingface ⚑ fineweb-2 (8,257 files) 379 API calls -> 19 API calls finepdfs-edu (429 files) 139 API calls -> 1 API call Looking forward to the release ! See PR #25521 on github
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@idro___
beaver quant
1 month
Started to use polars, this is good and addictive
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@DataPolars
polars data
20 days
Citizens cut query times from 80 to 8 minutes by adopting Polars, but the transformation went beyond speed. It provided, what they called, a "grammar of business logic." Teams moved from intricate nested loops to readable, composable expressions, drastically improving
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pola.rs
DataFrames for the new era
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@DataPolars
polars data
28 days
We recently shipped some performance upgrades and long-awaited features. Here are the highlights from releases 1.35.0-1.35.2: πŸ† Decimal Type Now Stable The Decimal data type is now production-ready. If you're working with financial data or anything requiring exact numeric
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@roborockglobal
Roborock
1 day
From Dec 8 to Dec 21, Save Up to 50% on Roborock Vacuums Built for Effortless Cleaning.
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@emilsnotes
Emil
28 days
πŸ”₯ @Accel (early investors in Facebook, Dropbox, Slack, and Flipkart) just dropped their 2025 top 100 Europe AI startups, and I’m excited to see @kapa_ai make an appearance. We have Silicon Valley roots, but we’re full-speed-ahead in Copenhagen making sure the entire world has
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@DataPolars
polars data
2 months
At the recent Polars meetup, Oliver & Daniel discussed how they migrated a pandas + SQL to Polars using Dataframely: - 22x speedup - 3x lower memory - 50% code reduction - Native dataframe validation with minimal overhead using Dataframely Watch:
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@DataPolars
polars data
2 months
Swiss insurer @diemobiliar refactored their risk model to Polars, achieving 5-10x speedups and enabling actuaries to run millions of simulation years on laptops. Previously unfeasible with pandas due to memory and single-core limitations. https://t.co/aeCF6m26wW
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pola.rs
DataFrames for the new era
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@DataPolars
polars data
3 months
We raised €18M in Series A led by @Accel to build fast data processing at any scale. All on Polars. https://t.co/Qy13YezymD
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pola.rs
DataFrames for the new era
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@TechCrunch
TechCrunch
3 months
Polars, the Amsterdam-based company behind the popular open source project by the same name, has raised an €18 million Series A led by Accel.
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techcrunch.com
Polars, the Amsterdam-based company behind the popular open source project by the same name, has raised an €18 million Series A led by Accel.
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@DataPolars
polars data
3 months
The recordings of our third meetup are now available on Youtube! Watch the session of Gijs Burghoorn, core developer @ Polars, here: https://t.co/ViFIwduDLf. In his talk he discussed how and why we optimize our Parquet reader.
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@DataPolars
polars data
3 months
Polars Cloud client 0.3.0 is released. You can now spawn >100k queries to a single cluster and we load balance them gracefully. Additionally, the query planning now is posted as a worker task and can be cancelled by the user. https://t.co/IZZ3gxrldC
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github.com
πŸ’₯ Breaking changes Remove partitioned_by execution ✨ Enhancements Plan query on worker nodes Implement partition sink file path callback Add shuffle write data to observatory 🐞 Bug fixes Harde...
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@DataPolars
polars data
3 months
Today we launch Polars Cloud and the Public Beta of our Distributed Engine. Read the post to get started! https://t.co/MR9Br3QMC5
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pola.rs
DataFrames for the new era
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@DataPolars
polars data
4 months
It is almost time for the 3rd official Polars meetup! The next meetup will take place on the 17th of September in Munich, Germany. There will be a talk by the Polars team and a community talk. RSVP here:
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meetup.com
On September 17, 2025, we organize our third meetup! This time we will be in **Munich** for an **in-person event.** The sessions will be recorded and shared afterwards. We
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