💡 Life-pro-tip: enable inline type hints 🏷️ Your editor will display inferred types for variables you haven't annotated 🕵️ Debugging those red squiggly lines will become much easier

✨🐼 Pandas 3.0 will have `pd.col` syntax 💡 You can use it for clean chaining in `assign` and `loc` 🚀 It's happening, the PR just got merged!

✨ New @pola.rs feature - you can now chain `name` expressions! 🌊🦄 As of Narwhals 2.0 (yes, we've released 2.0 🚀), this feature is available there as well! Little example below with our friend @duckdb.org

💡 "There's nothing for permanent than a temporary fix" Case in point, this pandas comment which was added [checks git log] ... 12 years ago 🙈

"If the U.S. can't get its greenhouse emissions under control, they need to face real consequences" said the rest of the world.

💡 Today in open source: a 17-year-old NumPy commit promising that a new feature will be coming soon Any day now..

😍 @posit.co have done it again 🧙 gt-extras offers even more functionality for their table renditions of @pola.rs and pandas dataframes! 🌊🦄 Using Narwhals for some dataframe logic

💡 Solution: use Narwhals for universal dataframe support 🌊🦄

✨ New Formulaic release (1.2), featuring native support for @pola.rs ! 🌊🦄 Powered by Narwhals

🎢 When the Q&A goes off-script 🤣 🇯🇵 Japanese math rock, 🅿️ porpoises and unfortunate aliases, and 🎤 Taylor Swift: 🥈All of these unexpectedly came up in this fun session, which is currently the 2nd most viewed of the conference 🙏 Thanks @pydatalondon.bsky.social for inviting me!

🥳 The next version of @mlflow.org will support @pola.rs ! 😩 Slightly disappointingly, they do so by converting to pandas 🌊🦄 Could Narwhals help make MLFlow gain native support for Polars? Link to the discussion below 👇

🙀 It's scary to merge a 2,000+ line PR! 😇 But, this one was so thorough that we just had to ship it 🏆 Thanks to an incredible effort by Ryan Whitten, Narwhals supports Ibis! 💡You can now use Narwhals with all of Ibis' backends, plus some extra, whilst keeping @pola.rs expressive API!

✨ @pola.rs now supports `list.filter` 🪄 The `list` namespace is now even more turbocharged ⚡ 👇 Full release notes for 1.30

✨ PySpark 4.0 is out 🌊🦄 And it's already supported by Narwhals, including PySpark connect (thanks Francesco Bruzzesi!)

✨ Narwhals now supports `fill_null` with forwards and backwards strategies 🎬 Here's a demo of a fill-forward function which supports PySpark, @pola.rs , @duckdb.org , pandas, cuDF, and more! 🎁 Bonus: curious about what this looks like as DuckDB SQL? We got you covered 😎

✨ Narwhals now supports PySpark 🎇 If you have a dataframe-agnostic function, you can pass in `pyspark.sql.DataFrame` 📈 Here's a demo, made with @marimo.io 🎁 BONUS feature: combine with SQLFrame, to generate SQL from @pola.rs syntax 🪄

🛠️ NVIDIA's cuDF library now runs the Narwhals test suite as part of its CI process 🙀

✨ New Polars feature: `is_business_day` 🌴 Use this to determine which dates fall on holidays, blazingly fast 🇩🇪 Using Germany as an example because I was just there to give a talk at @pyconde.bsky.social - thanks for having me and for putting on such a fun event!

🎈✨ Feeling pumped for this new @pola.rs feature! It's not a perf improvement, and it's not a new expression It's...working auto-complete in Jupyter / IPython / Marimo! 🙀😱 🙏 Credit to @krassowski.bsky.social for debugging and Alex Beedie for submitting a fix! 🧑‍🏫 This is gonna be great for teaching

📚 List normalisation: Polars vs DuckDB syntax 🐻‍❄️ Polars: divide the column by its list sum. Expressive as always 🎨 🦆 DuckDB: `a / list_sum(a)` would error...but you can write a list comprehension 😱🙀

✨✨ 2 big Narwhalified releases this week! 🎯 For time series enthusiasts, Darts now supports @pola.rs / PyArrow / cuDF / Modin via Narwhals 🎨 For visualisation enthusiasts, same story for @bokeh.org 🦄🌊 Underwater unicorn magic

We are excited to be here on @bsky.app and excited to announce the release of Bokeh version 3.7! Some great new features like windowed auto-ranging, support for more DataFame types, and new UI components—read all about it on our latest blog post discourse.bokeh.org/t/bokeh-3-7-...

🐻‍❄️ @pola.rs is my favourite dataframe library (surprise surprise) 🦆 @duckdb.org belongs alongside it in the modern data stack, learn both and you're in for a treat 📝 My latest blog post teaches the DuckDB equivalent of common dataframe operations, based on learnings from Narwhals development

✨ Streamlit merge PR to support Polars for cache hashing

🐻‍❄️ Under-appreciated @pola.rs feature: seamless expression composability 🎢 In Polars, `shift` and `rolling_mean` can be chained 💡 In SQL, you need a common table subexpression, because LAG isn't a scalar (i.e. elementwise) function

🎙️ Pleased to present at @pyconde.bsky.social this year! 🎯 This will be my first talk focused entirely on Narwhals and how it's bringing open source data tools together

🙀 Bokeh merged a pull request to use Narwhals for Polars / PyArrow support! 3️⃣.7️⃣ This will be available in their 3.7 release, probably later this month 🎢 Exciting times for Python dataframe visualisation!

✨New Narwhals release (1.24) 🏷️ Selectors and `nw.all` expressions are now supported across the API 💖🦆 Many improvements to the PySpark and @duckdb.org backends 😍 The more we work on Narwhals, the more we appreciate how expressive the @pola.rs API is

✨ New Polars release (1.20)! 🔎 Series.index_of and Expr.index_of added 🧵 New str.normalize method 🎢 Performance improvements for rolling functions (on my time series feature engineering benchmark it's a 2x improvement!) Full release notes: github.com/pola-rs/pola...

✨New Narwhals cover image 🧑‍🍳Can you guess what's cooking?

✨ New Pyodide release (0.27)! 🤗 With support for 🐻‍❄️Polars and 🌊🦄Narwhals! 💡 So let's take it for a spin and write some dataframe-agnostic code!

✨ New temporal feature in the next Polars release! ⏲️ dt.replace lets you replace components of Date / Datetime columns ⚡🦀 It's an expressified vectorised rustified version of the Python standard library datetime.replace

🦀 10 minutes to live-coding in Rust from LunarVim 🥐 French pastries and Geoguessr meta 🔁 "Le Verlan", and my revenge on the French for having invented it 🎥 My @pydataparis.bsky.social video is now online!

🌊🦄 Narwhals featured in Tryolabs's top 10 new AI/ML/Data tools 2024 list! 🥳 Even more pleasing is that 2 of the other packages featured (Marimo and Rio) use Narwhals under-the-hood 🛠️ Given that Narwhals is a tool for tool-builders, this fills us with joy!

Tuesday Tip! 💡 marimo renders dataframes as interactive tables — search over rows, sort and filter by columns, and page through millions of rows. Works out of the box with @pola.rs and other dataframes thanks to Narwhals by @marcogorelli.bsky.social!

Significant life goal reached 🚀 - had my first PR merged into an open source project. Revel in the docstring awesomeness. (small steps!) github.com/narwhals-dev... Thanks to @pydata.bsky.global and the Narwhals team for organising the session.

🗣️ "Instead of relying on the Pandas API, we are using Narwhals [...]. This means faster, more efficient handling of tabular data and serious performance gains for data apps at scale." 😍 Love this from @plotly.com Plotly v6 isn't out yet but you can try it with `pip install -U --pre plotly`

🔮 Looks like the next release of Nixtla's HierarchicalForecast will support @pola.rs ! 🌊 🦄 With Narwhals under the hood 🧑‍🏫 If you'd like to contribute to Narwhals, we're hosting mentored sprints at PyData Global and PyLadiesCon with plenty of issues for all levels

✨ Plotly 6.0 𝐩𝐫𝐞𝐫𝐞𝐥𝐞𝐚𝐬𝐞 is out! 🌊 🦄 With Narwhals as required dependency (🙀) 🐻‍❄️ For non-pandas inputs things often get 2-3x faster 🐼 For pandas, things should stay backwards-compatible 💡 To try it out: pip install -U --pre plotly 👉 Release notes: github.com/plotly/plotl...

✨ New Vegafusion release (2.0)! 🦀 Modernized Rust core ➡️ Arrow PyCapsule Interface 🌊🦄 Narwhals for agnostic Dataframe support 👉 Full release notes vegafusion.io/posts/2024/2...

😨 I nearly introduced a bug in Altair 🛑 BUT WAIT 🏷 Static typing saved the day 💂‍♀️ The saviour was TypeGuard, which was introduced in Python 3.10 🔥 So there you go, "typing doesn't prevent bugs" people - you're wrong 🔥

𝐓𝐡𝐞 𝐏𝐨𝐥𝐚𝐫𝐬 𝐯𝐬 𝐩𝐚𝐧𝐝𝐚𝐬 𝐝𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐜𝐞 𝐧𝐨𝐛𝐨𝐝𝐲 𝐢𝐬 𝐭𝐚𝐥𝐤𝐢𝐧𝐠 𝐚𝐛𝐨𝐮𝐭 💡 I don't always write blog posts 🐖 But when I do, I complain about piggy-backing 🎢 This was a fun one to write, and I was surprised to see it land on HackerNews news.ycombinator.com/item?id=4215... 👉 labs.quansight.org/blog/datafra...

🎢 Rolling mean: Polars vs DuckDB syntax 🐻 In Polars this is fairly concise - if you know `rolling_mean` it's a one-liner 🦆 DuckDB SQL is more verbose, but some clients and teams prefer maintaining SQL solutions so it's good to have this under your belt

❌ Never write a long regular expression... 💚 ...unless you absolutely have to 👉 In which case, verbose mode is your friend docs.python.org/3/library/re...

✨ Py-Shiny 1.2.0 is out! 🦄🌊 This releases includes Narwhals as a required dependency 💡 Polars users can pass Polars DataFrames directly to `@render.data_frame` without it converting to pandas 🕊️ The impact on pandas users is minimal, as Narwhals is lightweight and with zero dependencies

Just joined Bluesky, feeling pumped