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young man yells at the cloudIf anyone is looking at using <a href="https://mastodon.social/tags/polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#polars</a> for dataframes in <a href="https://mastodon.social/tags/rust" class="mention hashtag" rel="nofollow noopener" target="_blank">#rust</a> , having done it myself for a few months at work, here are my thoughts:1. It works and it's fast. I'd use it again. 2. The /rust-specific/ documentation is really barebones. However, the python docs are good, so you can read those and the translation isn't too bad. However, this is definitely the largest pain point.If anyone has any questions about using the crate, feel free to ask and I'll answer if I can!

Michael Sumnerwow, <a href="https://rstats.me/tags/polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#polars</a> is good - just read-from-url filter/select/unique super straightforward<a href="https://rstats.me/tags/python" class="mention hashtag" rel="nofollow noopener" target="_blank">#python</a>

narkodeI am transforming a project from <a href="https://nerdculture.de/tags/pandas" class="mention hashtag" rel="nofollow noopener" target="_blank">#pandas</a> to <a href="https://nerdculture.de/tags/polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#polars</a> and I already like it! I don't want to talk bad about <a href="https://nerdculture.de/tags/pandas" class="mention hashtag" rel="nofollow noopener" target="_blank">#pandas</a>, it did a lot for the data science community. But, beside of being blazingly fast, the syntax of <a href="https://nerdculture.de/tags/polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#polars</a> is much more logic and consistent!

Towards Data ScienceStruggling with slow GIS processing? Tony Albanese's article demonstrates a lightning-fast method for generating transects using <a href="https://hachyderm.io/tags/Geopandas" class="mention hashtag" rel="nofollow noopener" target="_blank">#Geopandas</a> and <a href="https://hachyderm.io/tags/Polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#Polars</a>, reducing processing time from days to seconds. <a href="https://towardsdatascience.com/harnessing-polars-and-geopandas-to-generate-millions-of-transects-in-seconds-d37b176a0b57/" rel="nofollow noopener" translate="no" target="_blank">https://towardsdatascience.com/harnessing-polars-and-geopandas-to-generate-millions-of-transects-in-seconds-d37b176a0b57/</a>

HabrPolars для обработки JSON и ParquetПривет, Хабр! Сегодня рассмотрим тему обработки временных рядов с помощью Polars. Начну с того, что в Pandas для агрегации временных рядов принято использовать метод resample() . Он удобен и привычен, но имеет свои ограничения по производительности и гибкости. Polars, в свою очередь, имеет метод groupby_dynamic() , который позволяет группировать данные по динамическим временным интервалам.<a href="https://habr.com/ru/companies/otus/articles/892812/" rel="nofollow noopener" translate="no" target="_blank">https://habr.com/ru/companies/otus/articles/892812/</a><a href="https://zhub.link/tags/polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#polars</a> <a href="https://zhub.link/tags/%D0%B2%D1%80%D0%B5%D0%BC%D0%B5%D0%BD%D0%BD%D1%8B%D0%B5_%D1%80%D1%8F%D0%B4%D1%8B" class="mention hashtag" rel="nofollow noopener" target="_blank">#временные_ряды</a> <a href="https://zhub.link/tags/%D0%BE%D0%B1%D1%80%D0%B0%D0%B1%D0%BE%D1%82%D0%BA%D0%B0_%D0%B2%D1%80%D0%B5%D0%BC%D0%B5%D0%BD%D0%BD%D1%8B%D1%85_%D1%80%D1%8F%D0%B4%D0%BE%D0%B2" class="mention hashtag" rel="nofollow noopener" target="_blank">#обработка_временных_рядов</a> <a href="https://zhub.link/tags/%D0%B0%D0%BD%D0%B0%D0%BB%D0%B8%D1%82%D0%B8%D0%BA%D0%B0" class="mention hashtag" rel="nofollow noopener" target="_blank">#аналитика</a>

PyCharm BlogPolars vs. pandas – Python のデータフレームライブラリを徹底比較 <a href="https://techhub.social/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#Python</a> <a href="https://techhub.social/tags/Pycharm" class="mention hashtag" rel="nofollow noopener" target="_blank">#Pycharm</a> <a href="https://techhub.social/tags/Datascience" class="mention hashtag" rel="nofollow noopener" target="_blank">#Datascience</a> <a href="https://techhub.social/tags/Pandas" class="mention hashtag" rel="nofollow noopener" target="_blank">#Pandas</a> <a href="https://techhub.social/tags/Polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#Polars</a><a href="https://blog.jetbrains.com/pycharm/2025/02/polars-vs-pandas" rel="nofollow noopener" translate="no" target="_blank">https://blog.jetbrains.com/pycharm/2025/02/polars-vs-pandas</a>

CuducosDo I know any <a href="https://tech.lgbt/tags/Polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#Polars</a> contributor or maintainer? I would love to help with that bug/exploration, but I am not sure where to start!<a href="https://github.com/pola-rs/polars/issues/21851" rel="nofollow noopener" translate="no" target="_blank">https://github.com/pola-rs/polars/issues/21851</a> <a href="https://tech.lgbt/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#Python</a> <a href="https://tech.lgbt/tags/Rust" class="mention hashtag" rel="nofollow noopener" target="_blank">#Rust</a>

EuroSciPyWorking on core array computing libraries that power <a href="https://fosstodon.org/tags/scientificPython" class="mention hashtag" rel="nofollow noopener" target="_blank">#scientificPython</a>? <a href="https://fosstodon.org/tags/EuroSciPy2025" class="mention hashtag" rel="nofollow noopener" target="_blank">#EuroSciPy2025</a> wants your proposals on optimized array operations, vectorization techniques, and numerical foundations. Submit your groundbreaking work!<a href="https://pretalx.com/euroscipy-2025/cfp" rel="nofollow noopener" translate="no" target="_blank">https://pretalx.com/euroscipy-2025/cfp</a><a href="https://fosstodon.org/tags/ScientificComputing" class="mention hashtag" rel="nofollow noopener" target="_blank">#ScientificComputing</a> <a href="https://fosstodon.org/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#Python</a> <a href="https://fosstodon.org/tags/EuroSciPy" class="mention hashtag" rel="nofollow noopener" target="_blank">#EuroSciPy</a> <a href="https://fosstodon.org/tags/numpy" class="mention hashtag" rel="nofollow noopener" target="_blank">#numpy</a> <a href="https://fosstodon.org/tags/scipy" class="mention hashtag" rel="nofollow noopener" target="_blank">#scipy</a> <a href="https://fosstodon.org/tags/pandas" class="mention hashtag" rel="nofollow noopener" target="_blank">#pandas</a> <a href="https://fosstodon.org/tags/polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#polars</a>

Data SciencePolars is a lightning fast DataFrame library/in-memory query engine with parallel execution and cache efficiency. And now you can use is with the tidyverse syntax: <a href="https://www.tidypolars.etiennebacher.com/" rel="nofollow noopener" translate="no" target="_blank">https://www.tidypolars.etiennebacher.com/</a> <a href="https://genomic.social/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#rstats</a> <a href="https://genomic.social/tags/polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#polars</a> <a href="https://genomic.social/tags/optimisation" class="mention hashtag" rel="nofollow noopener" target="_blank">#optimisation</a>

Mainmatter🌊  Kisters provides real-time flood warnings—but traffic spikes made scaling costly. We helped them build a Rust-based system using Polars to process data efficiently across servers, edge, and browsers (WASM)—keeping performance high and costs low.Read more ➡️ <a href="https://mainmatter.com/cases/kisters/?utm_source=linkedin" rel="nofollow noopener" translate="no" target="_blank">https://mainmatter.com/cases/kisters/?utm_source=linkedin</a> <a href="https://fosstodon.org/tags/rustlang" class="mention hashtag" rel="nofollow noopener" target="_blank">#rustlang</a> <a href="https://fosstodon.org/tags/WASM" class="mention hashtag" rel="nofollow noopener" target="_blank">#WASM</a> <a href="https://fosstodon.org/tags/edgecomputing" class="mention hashtag" rel="nofollow noopener" target="_blank">#edgecomputing</a> <a href="https://fosstodon.org/tags/cloudoptimization" class="mention hashtag" rel="nofollow noopener" target="_blank">#cloudoptimization</a> <a href="https://fosstodon.org/tags/polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#polars</a>

WolfAt last night’s <a href="https://hachyderm.io/@mug" class="u-url mention" rel="nofollow noopener" target="_blank">@mug</a> meeting we looked at a lot of different solutions to <a href="https://hachyderm.io/tags/adventofcode" class="mention hashtag" rel="nofollow noopener" target="_blank">#adventofcode</a> day 1 in many different languages. Two that were very interesting to me were <a href="https://hachyderm.io/tags/Zig" class="mention hashtag" rel="nofollow noopener" target="_blank">#Zig</a> and <a href="https://hachyderm.io/tags/haskell" class="mention hashtag" rel="nofollow noopener" target="_blank">#haskell</a>. The way these two languages worked was really quite fascinating. After seeing real code in these two languages, I can tell they are not for me; but they were interesting and illuminating nonetheless. There was a solution entirely in <a href="https://hachyderm.io/tags/SQL" class="mention hashtag" rel="nofollow noopener" target="_blank">#SQL</a>. Another in <a href="https://hachyderm.io/tags/vim9script" class="mention hashtag" rel="nofollow noopener" target="_blank">#vim9script</a>. Another in <a href="https://hachyderm.io/tags/swiftlang" class="mention hashtag" rel="nofollow noopener" target="_blank">#swiftlang</a> <a href="https://hachyderm.io/tags/swift" class="mention hashtag" rel="nofollow noopener" target="_blank">#swift</a> (I don’t think that one’s in the repo yet). I wrote several implementations myself. The one I felt most proud of is <a href="https://hachyderm.io/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#Python</a> with the core written in <a href="https://hachyderm.io/tags/rustlang" class="mention hashtag" rel="nofollow noopener" target="_blank">#rustlang</a> <a href="https://hachyderm.io/tags/rust" class="mention hashtag" rel="nofollow noopener" target="_blank">#rust</a> tied together with <a href="https://hachyderm.io/tags/PyO3" class="mention hashtag" rel="nofollow noopener" target="_blank">#PyO3</a>. The one I felt was maybe the best tool for the job was entirely based on <a href="https://hachyderm.io/tags/pandas" class="mention hashtag" rel="nofollow noopener" target="_blank">#pandas</a>. As I said in a previous post, I tried to solve it in <a href="https://hachyderm.io/tags/polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#polars</a>, but the API exposed by Polars at least as far as I could tell, made it no better than simple lists in Python. I need to get deeper knowledge here. The repo lives here: <a href="https://github.com/MichiganUnixUserGroup/MUG-2025-03-11-Advent-of-Code" rel="nofollow noopener" translate="no" target="_blank">https://github.com/MichiganUnixUserGroup/MUG-2025-03-11-Advent-of-Code</a>.

Eric R. ScottThere are now so many "backends" for {dplyr}—duckdb with {duckplyr}, polars with {tidypolars}, various database engines with {dbplyr}, {data.table} with {dtplyr}. Is there a blog post or flow chart somewhere with pros and cons of each? Like, comparisons of memory requirements, speed, and how likely they are to "just work"?<a href="https://fosstodon.org/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#rstats</a> <a href="https://fosstodon.org/tags/duckdb" class="mention hashtag" rel="nofollow noopener" target="_blank">#duckdb</a> <a href="https://fosstodon.org/tags/dplyr" class="mention hashtag" rel="nofollow noopener" target="_blank">#dplyr</a> <a href="https://fosstodon.org/tags/tidyverse" class="mention hashtag" rel="nofollow noopener" target="_blank">#tidyverse</a> <a href="https://fosstodon.org/tags/polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#polars</a>

N-gated Hacker NewsAh, nothing screams "cutting-edge innovation" like using <a href="https://mastodon.social/tags/Parquet" class="mention hashtag" rel="nofollow noopener" target="_blank">#Parquet</a> and <a href="https://mastodon.social/tags/Polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#Polars</a> for text embeddings. 🤣 Because, clearly, what the AI world needed was some spreadsheet nostalgia. And don't forget, everyone desperately needed to know how to embed 32,254 Magic the Gathering cards. 🧙‍♂️💾 Truly groundbreaking stuff! <a href="https://minimaxir.com/2025/02/embeddings-parquet/" rel="nofollow noopener" translate="no" target="_blank">https://minimaxir.com/2025/02/embeddings-parquet/</a> <a href="https://mastodon.social/tags/cuttingedgeinnovation" class="mention hashtag" rel="nofollow noopener" target="_blank">#cuttingedgeinnovation</a> <a href="https://mastodon.social/tags/textembeddings" class="mention hashtag" rel="nofollow noopener" target="_blank">#textembeddings</a> <a href="https://mastodon.social/tags/MagicTheGathering" class="mention hashtag" rel="nofollow noopener" target="_blank">#MagicTheGathering</a> <a href="https://mastodon.social/tags/AIhumor" class="mention hashtag" rel="nofollow noopener" target="_blank">#AIhumor</a> <a href="https://mastodon.social/tags/HackerNews" class="mention hashtag" rel="nofollow noopener" target="_blank">#HackerNews</a> <a href="https://mastodon.social/tags/ngated" class="mention hashtag" rel="nofollow noopener" target="_blank">#ngated</a>

Hacker NewsThe Best Way to Use Text Embeddings Portably Is with Parquet and Polars — <a href="https://minimaxir.com/2025/02/embeddings-parquet/" rel="nofollow noopener" translate="no" target="_blank">https://minimaxir.com/2025/02/embeddings-parquet/</a> <a href="https://mastodon.social/tags/HackerNews" class="mention hashtag" rel="nofollow noopener" target="_blank">#HackerNews</a> <a href="https://mastodon.social/tags/TextEmbeddings" class="mention hashtag" rel="nofollow noopener" target="_blank">#TextEmbeddings</a> <a href="https://mastodon.social/tags/Parquet" class="mention hashtag" rel="nofollow noopener" target="_blank">#Parquet</a> <a href="https://mastodon.social/tags/Polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#Polars</a> <a href="https://mastodon.social/tags/DataScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#DataScience</a> <a href="https://mastodon.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#MachineLearning</a>

benrutterWas noodling around with Gleam a while back, needed a dataframe library and set up a half-baked interface for polars.I can't beleive how easy the js ffi made it! Language FFI is such a hidden superpower, more of this please from bew languages! 😍<a href="https://mastodon.green/tags/programming" class="mention hashtag" rel="nofollow noopener" target="_blank">#programming</a> <a href="https://mastodon.green/tags/gleam" class="mention hashtag" rel="nofollow noopener" target="_blank">#gleam</a> <a href="https://mastodon.green/tags/polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#polars</a>

Alexandre B A Villares 🐍"Plotando estatísticas básicas com <a href="https://ciberlandia.pt/tags/Polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#Polars</a> e <a href="https://ciberlandia.pt/tags/Matplotlib" class="mention hashtag" rel="nofollow noopener" target="_blank">#Matplotlib</a> - <a href="https://ciberlandia.pt/tags/NLP" class="mention hashtag" rel="nofollow noopener" target="_blank">#NLP</a> 04 " <a href="https://bolha.us/@dunossauro" class="u-url mention" rel="nofollow noopener" target="_blank">@dunossauro</a> <a href="https://ciberlandia.pt/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#Python</a><a href="https://www.youtube.com/watch?v=4HpSFIekqDw" rel="nofollow noopener" translate="no" target="_blank">https://www.youtube.com/watch?v=4HpSFIekqDw</a> Hoje eu aprendi uma ideia ótima do Dunossauro que é imaginar que o ax do fig, ax do matplotlib (axis/eixo) é como uma haste onde penduramos as coisas! Como é fundamental o trabalho dele pra nossa comunidade.Update: inicialmente achei que era uma tradução corrente mas ele me explicou que não.

Jim GardnerDoes anyone have advice for unit testing a Polars Python expression? Say I have:def my_func(a, b): return (pl.col(a) / pl.col(b))How do you unit test? We want to compare the result of this function to an expectation. At the moment we’re wrapping the result in str(), which gives us a stringified version of the expression. Then we assert that it is equal to the stringified expression that we would expect.It works, just feels a little bit fragile. Unfortunately you can’t compare expressions directly with the equality operator ==. And polars.testing doesn’t have asserts for it either.(We are of course also going to have integration tests, where the expression actually gets used on a df fixture)<a href="https://bird.makeup/users/jeroenhjanssens" class="u-url mention" rel="nofollow noopener" target="_blank">@jeroenhjanssens</a> <a href="https://hachyderm.io/tags/Polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#Polars</a> <a href="https://hachyderm.io/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#Python</a> <a href="https://hachyderm.io/tags/PyData" class="mention hashtag" rel="nofollow noopener" target="_blank">#PyData</a>

Isa BernardiniUne auteure de <a href="https://mastodon.social/tags/polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#polars</a> à suivre assurément. J’en ai lu plusieurs d’elle, dont « Block 46 ». Voici son « dernier » sorti. Je ne gagne absolument rien à faire sa pub, je suis juste une personne qui aime ce qu’elle <a href="https://mastodon.social/tags/%C3%A9crit" class="mention hashtag" rel="nofollow noopener" target="_blank">#écrit</a> et représente. Une bien belle personne.

Claudine Layre<a href="https://maisonjuliengracq.fr/evenement/affaire-classee-noir-sur-loire/" rel="nofollow noopener" translate="no" target="_blank">https://maisonjuliengracq.fr/evenement/affaire-classee-noir-sur-loire/</a> <a href="https://mastodon.social/tags/culture" class="mention hashtag" rel="nofollow noopener" target="_blank">#culture</a> <a href="https://mastodon.social/tags/litt%C3%A9rature" class="mention hashtag" rel="nofollow noopener" target="_blank">#littérature</a> <a href="https://mastodon.social/tags/polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#polars</a>

Markus SuhrJust caught up with the recent Delta Lake webinar, > Revolutionizing Delta Lake workflows on AWS Lambda with Polars, DuckDB, Daft & RustSome interesting hints there regarding lightweight processing of big-ish data. Easy to relate to any other framework instead of Lambda, e.g. <a href="https://gruene.social/tags/ApacheAirflow" class="mention hashtag" rel="nofollow noopener" target="_blank">#ApacheAirflow</a> tasks<a href="https://youtu.be/BR9oFD0QMAs" rel="nofollow noopener" translate="no" target="_blank">https://youtu.be/BR9oFD0QMAs</a><a href="https://gruene.social/tags/dataengineering" class="mention hashtag" rel="nofollow noopener" target="_blank">#dataengineering</a> <a href="https://gruene.social/tags/datascience" class="mention hashtag" rel="nofollow noopener" target="_blank">#datascience</a> <a href="https://gruene.social/tags/duckdb" class="mention hashtag" rel="nofollow noopener" target="_blank">#duckdb</a> <a href="https://gruene.social/tags/daft" class="mention hashtag" rel="nofollow noopener" target="_blank">#daft</a> <a href="https://gruene.social/tags/polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#polars</a> <a href="https://gruene.social/tags/pandas" class="mention hashtag" rel="nofollow noopener" target="_blank">#pandas</a> <a href="https://gruene.social/tags/python" class="mention hashtag" rel="nofollow noopener" target="_blank">#python</a> <a href="https://gruene.social/tags/spark" class="mention hashtag" rel="nofollow noopener" target="_blank">#spark</a> <a href="https://gruene.social/tags/deltalake" class="mention hashtag" rel="nofollow noopener" target="_blank">#deltalake</a> <a href="https://gruene.social/tags/databricks" class="mention hashtag" rel="nofollow noopener" target="_blank">#databricks</a> <a href="https://gruene.social/tags/airflow" class="mention hashtag" rel="nofollow noopener" target="_blank">#airflow</a> <a href="https://gruene.social/tags/bigdata" class="mention hashtag" rel="nofollow noopener" target="_blank">#bigdata</a> <a href="https://gruene.social/tags/smalldata" class="mention hashtag" rel="nofollow noopener" target="_blank">#smalldata</a>

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