Matplotlib@matplotlib
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@matplotlib
Python library for creating static, animated, & interactive visualizations. Chat w/ us @ https://t.co/QDNR5Khj9w Sponsored by @NumFocus
IEEE VIS @ieeevis🎉 Just 2 weeks until #IEEEVIS2026! Curious what’s coming to VIS this year? 👀 Get a sneak peek at the research being presented, from fresh ideas to new visualization techniques! 🎬 Check out the paper previews and get ready for Boston! #DataVisualization
Simone Conradi @S_ConradiI’ve never been able to draw, until I learned to turn math ideas into code and explore visualizing things. More than 20 years ago I started with @WolframResearch Mathematica, now ~1000 #Python scripts: from complex analysis to statistical mechanics to fractals. #builtWithMarimo
polars data @DataPolarsWe just released Polars 2.0. It removed many of our legacy decisions makes the streaming engine our default and promotes SQL to a first class citizen within Polars. It comes with initial out-of-core (spill to disk) support, a new Map data type and a lot of performance improvements. In fact, we think Polars is now one of the fastest analytical SQL engines on a single node. See benchmarks in the post:
Simone Conradi @S_ConradiA classic Monte Carlo simulation, it takes me right back to my student days. 16 cars of equal length park at random along a street 20 cars long. #builtWithMarimo #python #numpy #matplotlib Thanks Claude Code for drawing nice cars in matplotlib 😀
GitHub Projects Community @GithubProjects
am i suzu or am i selene? @theothersuzu@vikhyatk now they can get the joy of catplotlib :D
vik @vikhyatkkids these days will never know the feeling of making matplotlib charts by hand
NumFOCUS @NumFOCUSMDAnalysis just landed a Research Software Maintenance Fund grant — enough to hire a dedicated Research Software Engineer. That’s what sustained backing does: it turns “someone squeezes this in” into “someone’s job is to make sure this works.” Support like Max the Stack keeps that momentum going.
Michael Pyrcz🌻 @GeostatsGuyI refuse! I will not teach #MachineLearning without first covering frequentist and Bayesian #Probability! Today in my machine learning class, we covered probability. During our discussion of Bayesian probability, we worked through the Sivia Bayesian coin demo. Then I opened my interactive @matplotlib #Python dashboard and formulated our prior and likelihood directly in the computer! Probability first. Machine learning second. 😉
Luis Pedro Coelho @luispedrocoelhoSyxel: images in your terminal, via SIXEL Includes a matplotlib backend, so draws into your terminal It's pure Python too pip install syxel Early alpha, feedback welcome: