Jeroen Janssens is Head of Developer Relations at Posit, author of Python Polars: The Definitive Guide and Data Science at the Command Line. He works across Python, R, JavaScript, and data tooling, and lives in Rotterdam, the Netherlands.
20 articles from this blog
A cheatsheet for Plotnine, a Python data visualization package based on the grammar of graphics.
Jeroen Janssens announces his new role as Head of Developer Relations at Posit and his plan to establish a DevRel Guild.
An animated exploration of UMAP, a state-of-the-art dimensionality reduction algorithm, applied to the classic MNIST dataset of handwritten digits.
A tutorial on using Plotnine, a Python data visualization library based on the grammar of graphics, comparing it to ggplot2 and using Polars.
Announcement of an upcoming O'Reilly book titled 'Python Polars: The Definitive Guide', a comprehensive guide to the Polars DataFrame library.
A blog post reviving an interactive stem-and-leaf plot playground built with D3 and CoffeeScript, demonstrating data visualization techniques.
Archive of a cohort-based online course teaching developers and researchers how to use the command line for automation and data science tasks.
A developer automates iTerm key mapping creation for tmux using a Python script to generate JSON configurations, improving terminal workflow.
Author announces closing his data science training company after seven years and shares his new role as a Senior Machine Learning Engineer.
A technical tutorial on using R and the rvest package to scrape data from multiple web pages, including handling pagination.
A guide with practical heuristics for converting ggplot2 (R) visualization code to plotnine (Python) code, including syntax and style differences.
A tutorial on using Plotnine, a Python data visualization library based on the grammar of graphics, translated from the ggplot2 R tutorial.
A Python script called csv2vw converts CSV data into Vowpal Wabbit's input format for machine learning, with examples for label handling.
Interview with data scientist Jeroen Janssens about his background, work on data science at the command line, and his Data Science Toolbox project.
Exploring the IBash Notebook, a Bash kernel for Jupyter, and its potential as a data science environment with inline image support.
A guide to using the Unix command-line for efficient data science workflows, including data processing, exploration, and modeling.
Introduces Stochastic Outlier Selection (SOS), an unsupervised machine learning algorithm for detecting outliers based on affinity between data points.
A guide to seven essential command-line tools (jq, csvkit, Rio, etc.) for data scientists to obtain, scrub, explore, and model data.
Explains how Bayesian A/B testing improves online headline optimization, overcoming challenges of traditional frequentist methods for faster, more accurate results.
A guide to creating custom shell functions for quickly navigating filesystems using symbolic links and tab completion.
