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Stacked bar chart showing percentage of female tortoises compared to male, between 2010 and 2023 for three different locations. The first two locations are a reasonable even split, but the third location (plateau) has a consistently low female percentage always below 6%.

Stacked bar chart showing percentage of female tortoises compared to male, between 2010 and 2023 for three different locations. The first two locations are a reasonable even split, but the third location (plateau) has a consistently low female percentage always below 6%.

A simple stacked bar chart for #TidyTuesday this week, looking at disparities in the number of male and female tortoises 🐒

Made with Plotnine in #Python πŸ“Š

Code: github.com/nrennie/tidy...

#DataViz #PydyTuesday #Plotnine

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Scatter plot of countries in a 2D UMAP embedding based on five data metrics. 
Each point represents a country-year combination. The x-axis (umap1) roughly aligns with income level, 
with high-income countries on the right. The y-axis (umap2) roughly aligns with time, with more recent years toward the bottom. 
Point shape and fill encode income category, point size encodes population, and point colour represents year in a yellow-to-red gradient. 
Clusters indicate countries with similar metric profiles. China (large cyan point) and India (large orange point) are clearly separated, 
with India moving toward the high-income region and China moving upward over time. Mixed-income clusters from earlier years appear in the upper-left region.

Scatter plot of countries in a 2D UMAP embedding based on five data metrics. Each point represents a country-year combination. The x-axis (umap1) roughly aligns with income level, with high-income countries on the right. The y-axis (umap2) roughly aligns with time, with more recent years toward the bottom. Point shape and fill encode income category, point size encodes population, and point colour represents year in a yellow-to-red gradient. Clusters indicate countries with similar metric profiles. China (large cyan point) and India (large orange point) are clearly separated, with India moving toward the high-income region and China moving upward over time. Mixed-income clusters from earlier years appear in the upper-left region.

Statistical Performance Indicators
#TidyTuesday
UMAP of the five scores, by year (circumference), income (circle) and population (radius).
#Marimo notebook: fluents.xyz/c/2025-11-25/
#Pandas #Plotnine

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🎨🐍 Plotnine Free Workshop!
Master data visualization in Python with the grammar of graphics. Perfect for all levels! πŸ’»βœ¨
πŸ“… 8 Oct | πŸ“ PyCon Africa, Johannesburg | πŸŽ‰ FREE
🎟️ Register for FREE: za.pycon.org/tickets
#PyConAfrica #Plotnine #Python #DataScience

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Distribution of titled chess players based on their nationality.

Distribution of titled chess players based on their nationality.

Countries with maximum number of titled chess players.

Notebook: dviz.manishdatt.com/r/2594

#TidyTuesday #PydyTuesday #dataviz #Plotnine

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Join our FREE workshops on 8 October for PyCon Africa’s Beginners Day! No experience needed. Connect with the Python community: za.pycon.org/beginners-day

Share and help us open doors!

#Python #PyCon #DjangoGirls #HumbleData #PyGame #Apify #Plotnine

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Join our FREE workshops on 8 October for PyCon Africa’s Beginners Day! No experience needed. Connect with the Python community: za.pycon.org/beginners-day

Share and help us open doors!

#Python #PyCon #DjangoGirls #HumbleData #PyGame #Apify #Plotnine

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Join our FREE workshops on 8 October for PyCon Africa’s Beginners Day! No experience needed. Connect with the Python community: za.pycon.org/beginners-day

Share and help us open doors!

#Python #PyCon #DjangoGirls #HumbleData #PyGame #Apify #Plotnine

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πŸŽ‰ Exciting updates to the Plotnine website are now live! | Jeroen Janssens πŸŽ‰ Exciting updates to the Plotnine website are now live! We've completely transformed the user experience with: ✨ A sleek new homepage design that better showcases what Plotnine can do πŸ–ΌοΈ An enh...

@jeroenjanssens.com So cool to see your LinkedIn post today about the #plotnine website update. Glad the library is getting some loving!

www.linkedin.com/posts/jeroen...

posit.co/blog/three-m...

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Warm recommendations for #plotnine for #python visualisation: it's feels a bit like emacs in that it takes time to grok its mental model, certainly if, like me you have no previous experience with its ancestor ggplot. But in the end it just does the job.

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I was going to sit down and learn the {plotnine} python library today, but turns out there's nothing really to learnβ€”it's literally {ggplot2} code wrapped in parentheses. If you know {ggplot2} in R, turns out you also know how to make plots on Python!

#Rstats #plotnine #Python

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We played with penguins data for this week's #TidyTuesday. I accepted @jonthegeek.com's challenge to recreate an existing plot. I recreated @allisonhorst.bsky.social's plot in #python using #plotnine. Can you guess which is the original?

Code here: github.com/kylieainslie...

#pydytuesday

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Screenshot of first slide of "Practical Techniques for Polished Visuals with Plotnine" presentation

Screenshot of first slide of "Practical Techniques for Polished Visuals with Plotnine" presentation

The recording of my PyData Global talk about Plotnine in #Python is available! 🐍

Give it a watch if you're interested in:

πŸ“Š customising plotnine plots
πŸ“ˆ combining with matplotlib
✍️ adding custom annotations

(or if you're an #RStats user wondering about Plotnine vs #ggplot2)

#DataViz #Plotnine

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This week's #tidytuesday was all about palm trees 🌴 and my #pydytuesday mission was using #plotnine πŸš€

I made my first few plots using matplotlib and seaborn, but plotnine is waaaay more intuitive as a longtime #rstats user transitioning to #python.

🌴 heights and fruit color vary by palm subfamily!

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A presentation slide titled "Practical Techniques for Polished Visuals with Plotnine" by Nicola Rennie for PyData Global 2024. It features a hexagon design on the left and Nicola’s contact details on the bottom right, including social media and website links.

A presentation slide titled "Practical Techniques for Polished Visuals with Plotnine" by Nicola Rennie for PyData Global 2024. It features a hexagon design on the left and Nicola’s contact details on the bottom right, including social media and website links.

PyData Global starts today! This evening I'll be talking about customising charts with Plotnine, and building better data visualisations πŸ“Š

πŸ“… Tue 3 Dec 2024
⏰ 18:30 UTC (13:30 EST)

#PyData #Plotnine #Python #DataViz

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Area plot of different types of coal production with custom annotations instead of a legend

Area plot of different types of coal production with custom annotations instead of a legend

I'm excited to be at PyData Global in December! I'll be talking about

πŸ“Š customising plotnine plots
πŸ“ˆ combining with matplotlib functions
✍️ adding annotations with HighlightText

I'll be using this chart πŸ‘‡ as an example!

Link: https://buff.ly/3Z9R9k6

#DataViz #Plotnine #Python #PyData #ggplot2

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πŸ“ "Plotnine plot contest"

πŸ‘€ Isabel Zimmerman (@isabelizimm.bsky.social)

πŸ”— isabelizimm.me/posts/2024-06-24_cheese-...

#pyladies #python #plotnine #data

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I'm absolutely thrilled to be one of the runners up in the 2024 Plotnine Contest! πŸ“Š

You can view my annotated area chart and blog post about it's creation here: nrennie.rbind.io/blog/plotnin...

Winners announcement: posit.co/blog/winner-...

#DataViz #Python #plotnine

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a rank chart showing how the ranking of different Women's football clubs in the FA Women's Super league have changed. Chelsea Women are highlighted.

a rank chart showing how the ranking of different Women's football clubs in the FA Women's Super league have changed. Chelsea Women are highlighted.

A quick chart looking at the rankings of different clubs in the FA Wome's Super League for #TidyTuesday this week!

πŸ“Š chart made using `plotnine` in Python
✍️ coloured and bold text added with `highlight-text`

Code: github.com/nrennie/tidy...

#Python #DataViz #DSLC #plotnine

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Area plot of coal production with coloured annotation

Area plot of coal production with coloured annotation

🚨 New blog post! 🚨

I've written a blog post showing you how to make annotated area charts using plotnine in Python (with a little bit of help from highlight-text and matplotlib) πŸ“Š

(possibly of interest to #RStats users who use #ggplot2!)s a subtitle! πŸ“Š

Link πŸ‘‡πŸ‘‡πŸ‘‡

#Python #plotnine #DataViz

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We’re exploring the beauty of #plotnine with @tanya_shapiro πŸ‘©πŸ»β€πŸŽ¨ at the second event of our joined @pyladies and @RLadiesGlobal πŸ’œ

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Doing talks to final year BA and MA students re writing empirical dissertations. I have 7 points - parts of the data analysis process. I'll talk about 7 tools. @Overleaf, @SurveyMonkey, @rstudio /@ProjectJupyter, #ggplot2 /#plotnine, @github, #markdown and @Twitter. Comments? Thx

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