Sigmoid Social

Erik-JanI was annoyed that there is no "expand_grid()" function in :python: <a href="https://fosstodon.org/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#Python</a> as in :rstats: <a href="https://fosstodon.org/tags/RStats" class="mention hashtag" rel="nofollow noopener" target="_blank">#RStats</a> <a href="https://fosstodon.org/tags/tidyverse" class="mention hashtag" rel="nofollow noopener" target="_blank">#tidyverse</a> So I just published a small package on <a href="https://fosstodon.org/tags/PyPI" class="mention hashtag" rel="nofollow noopener" target="_blank">#PyPI</a> !Introducing polarsgrid <a href="https://pypi.org/project/polarsgrid/" rel="nofollow noopener" translate="no" target="_blank">https://pypi.org/project/polarsgrid/</a>Using the excellent <a href="https://fosstodon.org/tags/polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#polars</a> 🐻‍❄️ package, easily create a table with product of factors: from polarsgrid import expand_grid expand_grid(a=[1, 2, 3], b=["x", "y"])Yields all combinations of its inputs as a <a href="https://fosstodon.org/tags/DataFrame" class="mention hashtag" rel="nofollow noopener" target="_blank">#DataFrame</a>It can also produce a <a href="https://fosstodon.org/tags/LazyFrame" class="mention hashtag" rel="nofollow noopener" target="_blank">#LazyFrame</a> for streaming extra-big tables to disk

Jim GardnerDuring this week's Data Science team CPD session I realised that a bit of old R code I wrote could be streamlined, and the base R to Python Polars comparison continued.<a href="https://jimgar.github.io/posts/cpd-jul-2025/post.html#section-1" rel="nofollow noopener" translate="no" target="_blank">https://jimgar.github.io/posts/cpd-jul-2025/post.html#section-1</a><a href="https://hachyderm.io/tags/rStats" class="mention hashtag" rel="nofollow noopener" target="_blank">#rStats</a> <a href="https://hachyderm.io/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#Python</a> <a href="https://hachyderm.io/tags/Polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#Polars</a> <a href="https://hachyderm.io/tags/AoC2024" class="mention hashtag" rel="nofollow noopener" target="_blank">#AoC2024</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>

Jim GardnerNew blog post: Comparing Advent of Code 2024 day 1 part 1 solutions in base R and Python Polars.<a href="https://jimgar.github.io/posts/cpd-jul-2025/post.html" rel="nofollow noopener" translate="no" target="_blank">https://jimgar.github.io/posts/cpd-jul-2025/post.html</a>Did a bit of CPD with my team at work this week. We revisited the first problem from Advent of Code 2024. Last year I solved it using base R, so I decided to use Python Polars this time and compare the outputs.Along the way I got a tiny bit more familiar with using uv, and I finally had to learn what structs are in Polars! Turns out they're pretty simple to understand.<a href="https://hachyderm.io/tags/rStats" class="mention hashtag" rel="nofollow noopener" target="_blank">#rStats</a> <a href="https://hachyderm.io/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#Python</a> <a href="https://hachyderm.io/tags/Polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#Polars</a>

Edward :mastocol:Unas semanas bien pesadas, pero con cosas interesantes que he probado en el trabajo. - <a href="https://col.social/tags/polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#polars</a> : Definitivamente mi herramienta para dataframes por defecto, después de habituarse a las formas nativas esto es muy claro y eficiente. - Depurador de <a href="https://col.social/tags/zed" class="mention hashtag" rel="nofollow noopener" target="_blank">#zed</a>: Aunque no he podido lograr que funcione la forma de anexar un proceso en ejecución, el modo de lanzar proceso resulta muy directo, y la interfaz para explorar las variables y la consola de interacción integrada funcionan muy bien <a href="https://col.social/tags/python" class="mention hashtag" rel="nofollow noopener" target="_blank">#python</a> <a href="https://col.social/tags/mastodevs" class="mention hashtag" rel="nofollow noopener" target="_blank">#mastodevs</a>

Talk Python PodcastLatest episode with Christopher Trudeau and host <a href="https://fosstodon.org/@mkennedy" class="u-url mention" rel="nofollow noopener" target="_blank">@mkennedy</a> on <a href="https://fosstodon.org/tags/polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#polars</a> <a href="https://fosstodon.org/tags/python" class="mention hashtag" rel="nofollow noopener" target="_blank">#python</a> <a href="https://fosstodon.org/tags/datascience" class="mention hashtag" rel="nofollow noopener" target="_blank">#datascience</a> #510: 10 Polars Tools and Techniques To Level Up Your Data Science<a href="https://talkpython.fm/episodes/show/510/10-polars-tools-and-techniques-to-level-up-your-data-science" rel="nofollow noopener" translate="no" target="_blank">https://talkpython.fm/episodes/show/510/10-polars-tools-and-techniques-to-level-up-your-data-science</a>

PositGreat Tables is the <a href="https://fosstodon.org/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#Python</a> library for creating display-ready tables from your <a href="https://fosstodon.org/tags/Polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#Polars</a> DataFrames and more.In their three-part video series, Michael Chow and <a href="https://fosstodon.org/@rich_i" class="u-url mention" rel="nofollow noopener" target="_blank">@rich_i</a> show how to add structure, formatting, and styling to elevate your tables beyond the default.Explore the details: <a href="https://posit.co/blog/level-up-great-tables/" rel="nofollow noopener" translate="no" target="_blank">https://posit.co/blog/level-up-great-tables/</a>

Francois DionPicked up "Python Polars the definitive guide" by Jeroen Janssens and Thijs Nieuwdorp. The polar bear was already used on another O'Reilly book, but the Iberian lynx is cool.Never sure how tech books will pan out, but Jeroen's book data science at the command line was a good one, so I am hopeful.<a href="https://mastodon.online/tags/python" class="mention hashtag" rel="nofollow noopener" target="_blank">#python</a> <a href="https://mastodon.online/tags/polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#polars</a> <a href="https://mastodon.online/tags/dataframes" class="mention hashtag" rel="nofollow noopener" target="_blank">#dataframes</a> <a href="https://mastodon.online/tags/datascience" class="mention hashtag" rel="nofollow noopener" target="_blank">#datascience</a> <a href="https://mastodon.online/tags/DataEngineering" class="mention hashtag" rel="nofollow noopener" target="_blank">#DataEngineering</a> <a href="https://mastodon.online/tags/dataops" class="mention hashtag" rel="nofollow noopener" target="_blank">#dataops</a> <a href="https://mastodon.online/tags/book" class="mention hashtag" rel="nofollow noopener" target="_blank">#book</a> <a href="https://mastodon.online/tags/books" class="mention hashtag" rel="nofollow noopener" target="_blank">#books</a> <a href="https://mastodon.online/tags/computerscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#computerscience</a> <a href="https://mastodon.online/tags/analytics" class="mention hashtag" rel="nofollow noopener" target="_blank">#analytics</a>

Talk Python PodcastWe have a brand-new <a href="https://fosstodon.org/tags/python" class="mention hashtag" rel="nofollow noopener" target="_blank">#python</a> <a href="https://fosstodon.org/tags/datascience" class="mention hashtag" rel="nofollow noopener" target="_blank">#datascience</a> <a href="https://fosstodon.org/tags/polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#polars</a> course! Please give it a look.Polars for Power Users: Transform Your Data Analysis Game<a href="https://training.talkpython.fm/courses/polars-for-power-users" rel="nofollow noopener" translate="no" target="_blank">https://training.talkpython.fm/courses/polars-for-power-users</a>

Francois DionAnybody using the narwhals <a href="https://mastodon.online/tags/python" class="mention hashtag" rel="nofollow noopener" target="_blank">#python</a> package for <a href="https://mastodon.online/tags/dataframe" class="mention hashtag" rel="nofollow noopener" target="_blank">#dataframe</a> manipulations?Very comfortable with <a href="https://mastodon.online/tags/pandas" class="mention hashtag" rel="nofollow noopener" target="_blank">#pandas</a> and <a href="https://mastodon.online/tags/polars" class="mention hashtag" rel="nofollow noopener" target="_blank">#polars</a> syntax, but although <a href="https://mastodon.online/tags/narwhals" class="mention hashtag" rel="nofollow noopener" target="_blank">#narwhals</a> is supposed to be very close to polars, it is a subset and I find that there is a lot of basic stuff missing. Trying to figure out how to get the first part of a str.split.in pandas I just add .str[0] and in polars .list.get(0)with narwhals neither approaches are implemented. Any idea as what is supported in narwhals to do this? <a href="https://mastodon.online/tags/programming" class="mention hashtag" rel="nofollow noopener" target="_blank">#programming</a>

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>

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>

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>

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