PyData & Scientific Libraries Stack
11 talks from the 2025 edition.
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A11y Need Is Love (But Accessible Docs Help Too) ▶ Recording 📝 Transcript
Smera Goel
Accessible documentation benefits everyone, from developers to end users. Using the [PyData Sphinx Theme](https://pydata-sphinx-theme.readthedocs.io/en/stable/) as a case study, this talk dives into common...
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BayBE: A Bayesian Back End for Experimental Planning in the Low-To-No-Data Regime ▶ Recording 📝 Transcript
Martin Fitzner, Alexander Hopp, Adrian Šošić
From coffee machine settings to chemical reactions to website AB testing - iterative make-test-learn cycles are ubiquitous. The [Bayesian Back End](https://emdgroup.github.io/baybe/stable/) (BayBE) is an open-source...
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Extending Python with Rust, Mojo, Cuda and C and building packages ▶ Recording 📝 Transcript
Ruben Arts, Wolf Vollprecht
We all love Python - but we especially love it for its unique ability as a glue language. In this talk we will show a number of ways of extending Python: using Rust, C and Cython, C++, CUDA and Mojo! We will use the...
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High-performance dataframe-agnostic GLMs with glum ▶ Recording 📝 Transcript
Martin Stancsics
Generalized linear models (GLMs) are interpretable, relatively quick to train, and specifying them helps the modeler understand the main effects in the data. This makes them a popular choice today to complement other...
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How Narwhals is silently bringing pandas, Polars, DuckDB, PyArrow, and more together ▶ Recording 📝 Transcript
Marco Gorelli
If you were writing a data science tool in 2015, you'd have ensured it supported pandas and then called it a day. But it's not 2015 anymore, we've fast-forwarded to 2025. If you write a tool which only supports...
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Responsible AI with fmeval - an open source library to evaluate LLMs ▶ Recording 📝 Transcript
Mia Chang
The term "Responsible AI" has seen a threefold increase in search interest compared to 2020 across the globe. As developers, the questions like "How can we build large language model-enabled applications that are...
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Streamlining the Cosmos: Pythonic Workflow Management for Astronomical Analysis ▶ Recording 📝 Transcript
Raphael Hviding
Astronomical surveys are growing rapidly in complexity and scale, necessitating accurate, efficient, and reproducible reduction and analysis pipelines. In this talk we explore Pythonic workflow managers to streamline...
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The earth is no longer flat - introducing support for spherical geometries in Spherely and GeoPandas ▶ Recording 📝 Transcript
Joris Van den Bossche
The geometries in GeoPandas, using the Shapely library, are assumed to be in projected coordinates on a flat plane. While this approximation is often just fine, for global data this runs into its limitations. This...
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Topological data analysis: How to quantify "holes" in your data and why? ▶ Recording 📝 Transcript
Ondrej Draganov
Do you need to compare sets of points in a plane? Identify a potential cyclic event in high-dimensional time series data? Find the second or the third highest peak of a noisily sampled function? Topological data...
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Using Causal thinking to make Media Mix Modeling ▶ Recording 📝 Transcript
Carlos Trujillo
In today's data-driven landscape, understanding causal relationships is essential for effective marketing strategies. This talk will explore the link between Bayesian causal thinking and media mix modeling, utilizing...
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Zero Code Change Acceleration: familiar interfaces and high performance ▶ Recording 📝 Transcript
Tim Head
The PyData ecosystem is home to some of the best and most popular tools for doing data-science. Every data-scientist alive today has used pandas and scikit-learn and even Large Language Models know how to use them!...