👑 Python wants R’s dataviz crown

👋 Hi!

I’ve been working in dataviz for quite a while now, and one thing has always amazed me:

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R > Python for dataviz 😳

There are far more Python users worldwide. Yet when it comes to visualization, R still leads the way.

Why?
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Partly because ggplot2 changed everything. Its syntax is so powerful and flexible. And partly because the community keeps pushing it further. Every week you see jaw-dropping charts made with ggplot2 and a new extension.
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With matplotlib? Not so much.

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It’s not Matplotlib’s fault

Matplotlib is the backbone of Python dataviz. It’s extremely powerful: you can build anything with it.
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Don’t believe me? Check out my list of the best Python charts. They’re just as good as the R ones. Just fewer in number.
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But:
- its syntax is tricky,
- the docs can be overwhelming, and
- it doesn’t come with the same ecosystem of extensions that R enjoys.

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The jungle of extensions

R has a package for everything:

• Need a beeswarm? ggbeeswarm.
• A Sankey diagram? ggsankey.
• A streamgraph? ggstream.
• Text that follows a curve? geomtextpath.

The list is endless.
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That’s why I built a curated selection on the R Graph Gallery to help people navigate it.

In Python, you don’t risk getting lost in a jungle.
Because the jungle simply doesn’t exist.

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Closing the gap

But things are changing.
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Two years ago, I hired Joseph Barbier. He helped me with the graph galleries for a while, and is now consulting on his own!
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He knows matplotlib inside out and has been releasing new Python packages that make dataviz easier and more beautiful.

This week, he dropped bumplot, a library for bump charts. What used to take dozens of lines of code now fits in just a few.

And that’s not all: Joseph has also built packages for custom fonts, selecting an awesome color palette, and even experiments to make matplotlib interactive.
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We also teach dataviz with Python together in a project called Matplotlib Journey! ☺️

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The outlook

Python is still behind R in dataviz.
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But with Posit investing in Python support (Shiny, Quarto, Pydi-tuesday), and with developers like Joseph pushing the ecosystem forward, the gap is narrowing.

The future of dataviz in Python looks genuinely exciting.

See you next week, it's getting late here!
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Yan
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PS: Huge thanks to the 68 people who joined Productive R Workflow last week! The price has gone up, but it’s still half off for students, groups, and folks in low-income countries.
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