Jeroen Janssens
Head of Developer Relations
Jeroen Janssens, PhD, is Head of Developer Relations at Posit, PBC. His expertise lies in visualizing data, implementing machine learning models, and building solutions using Python, R, JavaScript, and Bash. He’s passionate about open source and sharing knowledge. He’s the author of Python Polars: The Definitive Guide (O’Reilly, 2025) and Data Science at the Command Line (O’Reilly, 2021). Jeroen holds a PhD in machine learning from Tilburg University and an MSc in artificial intelligence from Maastricht University. He lives with his wife and two kids in Rotterdam, the Netherlands.
Software by Jeroen Janssens#
Events attended by Jeroen Janssens#
Posts and resources by Jeroen Janssens#
Polars: The Blazing Fast Python Framework for Modern Clinical Trial Data Exploration
Polars: The Blazing Fast Python Framework for Modern Clinical Trial Data Exploration - Michael Chow, Jeroen Janssens
Abstract: Clinical trials generate complex and standards driven datasets that can slow down traditional data processing tools. This workshop introduces Polars, a cutting-edge Python DataFrame library engineered with a high-performance backend and the Apache Arrow columnar format for blazingly fast data manipulation. Attendees will learn how Polars lays the foundation for the pharmaverse-py, streamlining the data clinical workflow from database querying and complex data wrangling to the potential task of prepping data for regulatory Tables, Figures, and Listings (TFLs). Discover the ‘delightful’ Polars API and how its speed dramatically accelerates both exploratory and regid data tasks in pharmaceutical drug development. The workshop is led by Michael Chow, a Python developer at Posit who is a key contributor to open-source data tools, notably helping to launch the data presentation library Great Tables, and focusing on bringing efficient data analysis patterns to Python.
Resources mentioned in the workshop:
- Polars documentation: https://docs.pola.rs/
- Plotnine documentation: https://plotnine.org/
- pyreadstat: https://github.com/Roche/pyreadstat
- Examples of Great Tables and Pharma TFLs: https://github.com/machow/examples-great-tables-pharma
- UV Python package manager: https://docs.astral.sh/uv
Polyglot Data Science: Why and How to Combine R and Python (Jeroen Janssens) | posit::conf(2025)
Polyglot Data Science: Why and How to Combine R and Python
Speaker(s): Jeroen Janssens
Abstract:
Doing everything in one language is convenient but not always possible. For example, your Python app might need an algorithm only available as an R package. Or your R analysis might need to fit into a Python pipeline. What do you do? You take a polyglot approach! Many data scientists hesitate to explore beyond their main language, but combining R and Python can be powerful. In my talk, I’ll explain why polyglot data science is beneficial and address common concerns. Then, I’ll show you how to make it happen using tools like Quarto, Positron, Reticulate, and the Unix command line. By the end, you’ll gain a fresh perspective and practical ideas to start. posit::conf(2025) Subscribe to posit::conf updates: https://posit.co/about/subscription-management/
Untangling Nested JSON With Wes McKinney | PydyTuesday #3
Join Wes McKinney (principal architect at Posit) and Jeroen Janssens (developer relations engineer at Posit) as they dive into deeply nested JSON. Using Python, Positron, Polars, and Altair, they look at scraped GitHub data and create some sort of pulse signal for various GitHub repos.
As always, true to the “PydyTuesday Uncut” title, this video is completely unedited. Every typo, mistake, web search, and “aha!” moment is left in so you can see exactly how we approach a new dataset from scratch.
Things mentioned during the session and related resources:
- Posit Conf https://posit.co/conference/
- The Test Set https://thetestset.co
- Positron https://positron.posit.co
- Python for Data Analysis, 3E https://wesmckinney.com/book/
- Python Polars: The Definitive Guide https://polarsguide.com
- Code produced during the session https://github.com/jeroenjanssens/pydytuesday-uncut/blob/main/session-03/github.py
#polars #pydytuesday #datascience
Visualizing Gas Prices | PydyTuesday Uncut #2
Join Michael Chow (open source developer at Posit) and Jeroen Janssens (developer relations engineer at Posit) as they dive into this week’s #PydyTuesday dataset. This time, they visualize gas prices using the four P’s: Positron, Python, Polars, and Plotnine.
True to the “PydyTuesday Uncut” title, this video is completely unedited. Every typo, mistake, web search, and “aha!” moment is left in so you can see exactly how we approach a new dataset from scratch.
Things mentioned during the session and related resources:
- Weekly US Gas Prices https://github.com/rfordatascience/tidytuesday/blob/main/data/2025/2025-07-01/readme.md
- Code produced during the session https://github.com/jeroenjanssens/pydytuesday-uncut/
- Plotnine https://plotnine.org
- Positron https://positron.posit.co
#python #polars #tidytuesday #datascience
How marimo adds reactivity to your Quarto documents
Jeroen Janssens talks with Vincent Warmerdam about marimo and the Quarto plugin that was recently released.
Links:
- https://quarto.org
- https://marimo.io/
- https://docs.marimo.io/
- https://github.com/marimo-team/quarto-marimo
- https://github.com/koaning/wigglystuff
- https://anywidget.dev/
00:00 Introduction 01:19 Getting started with marimo 35:34 ScatterWidget 42:45 Data sources 53:24 Marimo plugin for Quarto
Jeroen Janssens - Package Your Python Code as a CLI | PyData London 25
Learn how to transform your Python code into a command-line tool. Jeroen Janssens, author of Data Science at the Command Line, guides you through the process of turning your scripts into reusable, executable tools, integrating them into your data workflows and harnessing the power of the Unix command line.
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details.
Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps
Exploring Web APIs | PydyTuesday Uncut #1
Join Michael Chow (open source developer at Posit) and Jeroen Janssens (developer relations engineer at Posit) as they dive into this week’s #PydyTuesday dataset about Web APIs. Tools include uv, Positron, Polars, Plotnine, Great Tables, and the Unix command line.
True to the “PydyTuesday Uncut” title, this video is completely unedited. Every typo, mistake, web search, and “aha!” moment is left in so you can see exactly how others approach a new dataset from scratch.
Things mentioned during the session and related resources:
- Code produced during the session: https://github.com/jeroenjanssens/pydytuesday-uncut/blob/main/2025-06-17/01-start.py
- PydyTuesday https://github.com/posit-dev/pydytuesday
- TidyTuesday https://github.com/rfordatascience/tidytuesday
- Getting Data from the TidyTuesday Repo with Python https://www.youtube.com/watch?v=ol2FrSL5gVU
- Positron IDE https://positron.posit.co
- Data Science at the Command Line https://jeroenjanssens.com/dsatcl/
- Python Polars: The Definitive Guide https://polarsguide.com
- Polars https://pola.rs
- Plotnine https://plotnine.org
- Great Tables https://posit-dev.github.io/great-tables/
- The Big Year https://www.imdb.com/title/tt1053810/
00:00 Introduction 02:46 Getting the data with uv 13:18 Positron IDE 17:42 Importing Polars 23:17 Plotting a bar chart with Plotnine 33:55 Inspecting duplicates 46:30 Handling missing values 58:56 Crafting a great table 1:38:48 Reflection
885: Python Polars: The Definitive Guide — with Jeroen Janssens and Thijs Nieuwdorp
#Python #Polars #Pandas
Jeroen Janssens and Thijs Nieuwdorp are data frame library Polars’ greatest advocates in this episode with @JonKrohnLearns where they discuss their book, Python Polars: The Definitive Guide, best practice for using Polars, why Pandas users are switching to Polars for data frame operations in Python, and how the library reduces memory usage and compute time up to 10x more than Pandas. Listen to the episode to be a part of an O’Reilly giveaway!
This episode is brought to you by: • Trainium2, the latest AI chip from AWS: https://aws.amazon.com/ai/machine-learning/trainium/ • Adverity, the conversational analytics platform: https://eu1.hubs.ly/H0jxK210 • Dell AI Factory with NVIDIA: https://www.dell.com/superdatascience
Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
In this episode you will learn:
• (00:00:00) Introduction
• (00:04:46) Why Jeroen and Thijs wrote Python Polars: The Definitive Guide
• (00:18:18) Best practices in Polars
• (00:25:08) Why Polars has so many users
• (00:32:37) The benefits of the Great Tables package
• (00:50:05) Jeroen and Thijs’ partnership with NVIDIA and Dell for Python Polars: The Definitive Guide
Additional materials: https://www.superdatascience.com/885
Polars Meetup #1 - Migrating a large codebase to Polars by Jeroen Janssens and Thijs Nieuwdorp
In this community talk, Jeroen Janssens and Thijs Nieuwdorp share their experiences and best practices for migrating a large pandas codebase to Polars at one of the largest utility companies in the Netherlands. By implementing Polars, they achieved a 98% cost reduction. Watch the video to learn how you can start migrating your own codebase.
Check our Meetup page to see when the next event is planned: www.meetup.com/polars-meetup/
#polars #dataframe #python #dataengineering #datascience
KEYNOTE: Dr. Jeroen Janssens - Embrace the Unix Command Line and Supercharge Your PyData Workflow
Discover why the Unix command line remains a powerful and relevant tool for data scientists, even in a Python-dominated landscape. This talk will demonstrate how embracing the command line and leveraging its many tools can significantly enhance your productivity, streamline data workflows, and complement your Python skills.
Jeroen Janssens, PhD, is a polyglot data science consultant and certified instructor. His expertise lies in visualizing data, implementing machine learning models, and building solutions using Python, R, JavaScript, and Bash. Jeroen is passionate about open source and sharing knowledge. He is the author of Data Science at the Command Line (O’Reilly, 2021) and is currently writing Python Polars: The Definitive Guide (O’Reilly, 2025). Every now and then he blogs at https://jeroenjanssens.com .
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details.
Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps
Data Science at the Command Line and Polars | Jeroen Janssens | Data Science Hangout
To join future data science hangouts, add it to your calendar here: https://pos.it/dsh - All are welcome! We’d love to see you!
We were recently joined by Jeroen Janssens, Senior Developer Relations Engineer at Posit, to chat about his career journey from machine learning to developer relations, the advantages of using the command line for data science, his books “Data Science at the Command Line” and “Python Polars”, and advice for aspiring DevRel professionals.
In this Hangout, we explore the benefits of working on the command line versus not. Jeroen explained that while the initial command line interface might seem stark, it offers a very different and powerful way to interact with your computer. The Unix command line is ubiquitous across various systems, from Raspberry Pis to supercomputers. Its strength lies in the ability to connect tools together through standard output and input, allowing for quick and iterative solutions by combining specialized tools. This fosters an interactive nature with a short feedback loop and provides closer interaction with the file system, making ad hoc data exploration efficient.
Resources mentioned in the video and zoom chat: Jeroen’s LinkedIn → https://www.linkedin.com/in/jeroenjanssens/ Data Science at the Command Line → https://jeroenjanssens.com/dsatcl/ Python Polars: The Definitive Guide → https://polarsguide.com/ Plotnine → https://plotnine.org/ Winner of the 2024 plotnine Plotting Contest → https://posit.co/blog/winner-of-the-2024-plotnine-plotting-contest/ Talk about plotnine → https://www.youtube.com/watch?v=xdD8r84sqYY R for Data Science → https://r4ds.had.co.nz/ Jeroen’s plotnine translation of R for Data Science → https://jeroenjanssens.com/plotnine/ froggeR package → https://azimuth-project.tech/froggeR/ Reticulate → https://rstudio.github.io/reticulate/ Install Windows Subsystem for Linux (WSL) → https://learn.microsoft.com/en-us/windows/wsl/install UTM for macOS (Virtualization) → https://mac.getutm.app fish shell → https://fishshell.com/ Quartodoc → https://github.com/machow/quartodoc Focusmate (Accountability Partner Tool) → https://www.focusmate.com/ Surface Area of Luck → https://modelthinkers.com/mental-model/surface-area-of-luck CRAN R Extensions Manual → https://cran.r-project.org/doc/manuals/r-release/R-exts.html
If you didn’t join live, one great thing you missed from the zoom chat was people sharing their varied experiences with the command line, with many admitting they primarily use it for basic navigation or only when necessary, and some sharing helpful tools and tips for those less familiar. Let us know below if you’d like to hear more about this topic!
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