#treemapify

For the #30DayChartChallenge day 4: Big or Small, I made an #rstats treemap with the 📦 #treemapify, in the same Byrne's Euclid style as for day 1. It shows that a Small number of programs each attract a Big number of students, and a Big amount of programs each attract a Small number of students.

A collection of squares, each area represents the number of new full-time students in a bachelor or associate degree program at dutch universities of applied sciences in 2024. The 17 largest (red) squares attract 51% of the students. The 224 other  (blue) squares attract49% of the students.
2025-04-04

Día 4 | Comparaciones – Grande o Pequeño | #30DayChartChallenge. La visualización fue creada usando R basado en los paquetes: #ggplot2, #dplyr, #treemapify. Fuente: Sistema de Educación Superior - UNAH – 2023.

One language to rule them all, One language to find them, One language to bring them all and in the #AI bind them. 🤭 #dataviz 🌍📊 made & posted via #rstats, #bskyr, #treemapify 🚀

A treemap showing the top 10 languages used in ~ 2k posts with the #AI hashtag yesterday
Each rectangle represents a language, with size proportional to the number of posts.
The visualization highlights the global diversity of discussions about AI.
Aditya Dahiyaadityadahiya
2024-04-17

@ShinyConf How are packages linked to @Posit's {shiny}. For linked packages, the most popular imports are & . Most common suggestions are , @rmarkdown and .
Data: , @tracykteal & @jonthegeek
Code🔗tinyurl.com/tidy-shny
Tools:

Treemap of {shiny} linked packages' reverse dependencies. Most popular parent packages shown, for 4 different types of linkages.

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Server: https://mastodon.social
Version: 2025.04
Repository: https://github.com/cyevgeniy/lmst