It's now incredibly easy to build calendar heatmaps! Thanks Joseph for your dayplot library! Documentation: josephbarbierdarnal.github.io/dayplot/tuto/a… If you like making charts with Python, come learn with us at matplotlib-journey.com!

New (small) release of dayplot 📅 It's now possible to specify the first day of the week (which is Sunday by default) thanks to Ali Shakiba! Learn more: josephbarbierdarnal.github.io/dayplot/ Github repo: github.com/JosephBARBIERD…

TLDR: I'm working on making pyfonts much faster 🏃‍♀️ pyfonts is a little python package I've created to make using fonts in Matplotlib easy and reproducible. It suffers from being too slow when using multiple fonts, but this will be resolved soon! Repo: lnkd.in/gRDMrgF7

chatgpt is finally starting to give some good answers about uv!

New major release of pyfonts! 😁 It’s now possible (and super easy) to use ALL fonts from Google Fonts with just a single line of code and apply them in matplotlib. Learn more: josephbarbierdarnal.github.io/pyfonts/ Github: github.com/JosephBARBIERD…

Why do most data science side projects have zero value? For many reasons: - Not reproducible - Not easy to browse - Lacking a clear narrative - Not visually appealing Just published a new blog post on how to do a data science project: barbierjoseph.com/blog/how-not-t…

Is there an equivalent to R CMD CHECK, but for python? ruff/uv do most of the work here, but I still feel like there's a lack of a single, very verbose tool for doing diagnostics in a python package.

I was looking to install a Pascal compiler earlier and found out that, apparently, some people take "cross-platform" very seriously. Now I’m wondering if I should try to make my statistics program run on my old GBA just to make it truly cross-platform.

New (small) release of pypalettes! 😁 - A create_cmap() function to easily create a colormap object - A show_cmap() function to preview the colors - Improved documentation - Minor bug fixes and internal code cleanup More info on the project repository: github.com/JosephBARBIERD…

New morethemes release! 🎨 4 new themes added (14 total now!) in morethemes, a Python package offering beautiful, ready-to-use styles for matplotlib. Feedback, stars, or suggestions welcome! Learn more: github.com/JosephBARBIERD…

New #tidytuesday chart! It's all about gas prices • Highlight the overall trend rather than precise values • Use a scale-free format • Keep the design minimalist Code: github.com/JosephBARBIERD…

I've started working on a minimalist PoC that converts Matplotlib plots into interactive graphics. There are a bazillion things to do before it's something robust and stable, but I'm confident it will go somewhere. Online demo: y-sunflower.github.io/plotjs/

New release of pyfonts, with a really cool new feature! You can now change the default font globally, instead of having to manually change all the text fonts. Thanks John Gardner who implemented this 😁 Feedback, stars, or suggestions welcome! Github: github.com/JosephBARBIERD…

It's been a year since I started freelancing! So I decided to write a little blog post about the upsides and downsides. It focuses mainly on: money, workload and working conditions. barbierjoseph.com/blog/lessons-a…

New release of morethemes 😁🎨 with 2 new themes for matplotlib! These themes (try to) be more color-blind friendly, as requested by some users. If you have any ideas for themes, please don't hesitate to reach out! Browse all themes: y-sunflower.github.io/morethemes/

New feature available in dayplot! 📅 You can now easily add captions (and customize them) to the calendar heatmaps. Now, I think it's time for me to spend more time finding better examples. Learn more about dayplot: github.com/y-sunflower/da…

Introducing ✨bumplot✨, a brand new Python package for creating bump charts! It's: - super easy to use - super easy to customize - super cool (obviously) - built on top of Matplotlib Learn more about bumplot: github.com/y-sunflower/bu…

🎉 Want to build better charts with #Python and Matplotlib ? Join me and Joseph for a brand new #dataviz workshop! We’ll spend 2 half-days together, alternating between impactful explanations and hands-on exercises. Only 15 spots available! matplotlib-journey.com/workshop