#treemapify
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nrennie.bsky.social
Recently made a cover image for BlueSky using treemaps of colors from Bob Ross paintings (columns = seasons, rows = episodes)!

🖼️ #TidyTuesday data
📷 Image processing with {imager}
🎨 Color extraction with {eyedroppeR}
📈 Analysis in #RStats
📊 Plots with {treemapify}

#DataViz #Rtistry #ggplot2
a 31x13 grid of treemaps, where each treemap shows 5 colours used in Bob Ross paintings
February 3, 2025 at 10:34 AM
nrennie.bsky.social
A quick treemap for this week's #TidyTuesday data about APIs! 🌳

📊 Built with {treemapify} package in #RStats
🎨 Colours (sort of) based on brands
✍️ Coloured text and icons with {ggtext}

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

#DataViz #ggplot2
Treemap showing number of APIs provided by different companies. Amazon, Google, and Microsoft dominate.
June 18, 2025 at 3:15 PM
klauswiese.bsky.social
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.
April 4, 2025 at 5:09 PM
klauswiese.bsky.social
Día 1 | Comparaciones – Part-to-Whole | #30DayChartChallenge. Distribución del área construida en Centroamérica según ESA WorldCover, donde el tamaño refleja los km² de suelo urbanizado por país. El gráfico fue creada usando R con los paquetes #ggplot2, #treemapify, #scales y #showtext.
April 1, 2026 at 2:22 AM
ansgarw.bsky.social
Wer sich für die technischen Hintergründe des Charts interessiert: Es wurde mit R #rstats und den {ggplot2}- und {treemapify}-Packages sowie einem kleinen Einsatz von {grid}, um das zu kleine Label der CSU zu platzieren, erstellt.
February 8, 2025 at 6:17 PM
klauswiese.bsky.social
#Día3 | Comparación– Mosaico | #30DayChartChallenge. Focos de calor detectados para los paises de América Central. Un gráfico con valores absolutos y otro con valores relativos. Creada usando R con #ggplot2, #treemapify, #dplyr, #scales, #readr y #stringr.
April 3, 2026 at 3:43 PM
jenrichmondphd.bsky.social
The vast majority of books in the Gutenberg Project are in English.

I made this plot using the `treemapify` package. Treemap plots are useful when one category is overrepresented in your data.

#rstats #TidyTuesday

Checking out my plotting process jenrichmond.github.io/posts/2025-0...
treemap plot illustrating the number of books in the gutenberg database by language, the vast majority of books are in English, followed by French, Finnish, and German.
June 4, 2025 at 12:26 AM
hrbrmstr.dev
Well, the one way I know the week has not been *all* bad is that this has been at the top of the Quarto project doc I've been hacking on all week. Gotta take solace in the little things even more — now.
library(tidyverse) library(hrbrthemes) library(waffle) library(ggbeeswarm) library(treemapify) library(ggstream) library(extrafont)
January 24, 2025 at 12:48 PM
martinejansen.bsky.social
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.
April 12, 2025 at 6:39 PM
jessimoore.bsky.social
#TidyTuesday - Week 6 - CDC Datasets. I looked at the categories of datasets that have been archived and visualised the counts using {treemapify}.

code: github.com/jessjep/tidy...

#rstats #dataviz #ggplot2
A visualisation titled "CDC Datasets backed up during Trump Administration". Shows a group of rectangles, which are sized, grouped, and colored according to the number of datasets in each category. The largest is in red and labelled "National Notifiable Disease Surveillance System (NDSS): 293". This is followed by "National Center for Health Statistics: 199", "National Institute for Occupational Safety and Health: 108", "Vaccinations: 78", "Public Health Surveillance: 68", and "500 Cities & Places: 57". As the number of datasets becomes smaller, the color changes in a sunset gradient from red to yellow to blue.
February 11, 2025 at 5:50 AM
jenrichmondphd.bsky.social
Day 24 WHO Friday

Another new geom for the Day 24 WHO prompt; this is a treemap and I made it using the treemapify package.

Find the #rstats code and read about my #30DayChartChallenge plotting process jenrichmond.github.io/charts/2025-...
April 25, 2025 at 7:27 AM
leomrtns.bsky.social
I was gonna suggest treemap (wilkox.org/treemapify/), I see that you're on it. Much better than piecharts IMHO
Draw Treemaps in ggplot2
Provides ggplot2 geoms for drawing treemaps.
wilkox.org
June 16, 2025 at 5:22 PM
nrennie.bsky.social
We're looking at Fiscal Sponsors for #TidyTuesday this week! 📊

🌳 Treemap made with {treemapify}
🗺️ Colours from {rcartocolor}
✒️ Styling with {ggplot2}

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

#RStats #DataViz #R4DS #ggplot2
a treemap showing the prevalence of different types of Fiscal sponsorship models, with Model C taking up the most space. Caption reads A fiscal sponsorship is an arrangement between a not-for-profit with 501(c)(3) tax-exempt status and another party without tax-exempt status. The *Fiscal Sponsorship: 6 Ways to Do It Right* books describes six models for fiscal sponsorships - Model A, the sponsor takes the project in-house; Model B, the independent contractor projec; Model C, a preapproved grant relationship; Model D, group exemption; Model E, the supporting organisation; Model F — technical assistance. Model L, Single Member LLC also exists. Model C is the most common approach. Some fiscal sponsors are represented multiple times in this graphic as they provide different types of relationships.
March 12, 2024 at 12:47 PM
hrbrmstr.mastodon.social.ap.brid.gy
Well, the one way I know the week has not been *all* bad is that this has been at the top of the Quarto project doc I've been hacking on all week. Gotta take solace in the little things even more — now.
library(tidyverse) library(hrbrthemes) library(waffle) library(ggbeeswarm) library(treemapify) library(ggstream) library(extrafont)
January 24, 2025 at 12:54 PM
robertskeril.czesky.online
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.
December 18, 2024 at 5:44 PM
cranupdates.bsky.social
Updates on CRAN: allelematch (2.6.0), fcmfd (0.1.2), geoperu (0.0.1), ggfittext (0.10.4), mclust (6.1.3), QRAGadget (0.4), Sequential (4.6.1), treemapify (2.6.1), tsissm (1.0.3)
July 5, 2026 at 11:01 AM
cranberriesfeed.bsky.social
CRAN updates: fcmfd ggfittext mclust QRAGadget Sequential treemapify tsissm #rstats
July 5, 2026 at 7:02 AM
cranberriesfeed.bsky.social
CRAN updates: DR.SC manymome treemapify #rstats
December 14, 2025 at 12:02 PM
cranberriesfeed.bsky.social
New CRAN package ggtreebar with initial version 0.1.0
#rstats
https://cran.r-project.org/package=ggtreebar
CRAN: Package ggtreebar
Provides 'ggplot2' geoms analogous to 'geom_col()' and 'geom_bar()' that allow for treemaps using 'treemapify' nested within each bar segment. Also provides geometries for subgroup bordering and text annotation.
cran.r-project.org
May 16, 2025 at 10:02 AM
cranupdates.bsky.social
Updates on CRAN: BH (1.90.0-1), boiwsa (1.1.4), DR.SC (3.7), germinationmetrics (0.1.9), hdf5lib (2.0.0.3), manymome (0.3.2), mlr3tuning (1.5.1), PGRdup (0.2.4.0), ProFAST (1.7), SDModels (2.0.2), sortable (0.6.0), treemapify (2.6.0)
December 14, 2025 at 1:29 PM
energtx.bsky.social
treemapify + ggplot2 = gorgeous treemaps.

Size = electricity generation. Color = low-carbon share.

You can see France (95% clean) vs Poland (31%) at a glance.

energtx.com/visualizations

#RStats #ggplot2 #treemapify #Treemap #DataViz #TidyTuesday
March 19, 2026 at 10:51 PM
energtx.bsky.social
R packages behind energtx visuals:

ggplot2, ggstream, ggbump, treemapify, ggrepel, showtext, ggtext, scales, patchwork, ggforce.

10 packages. 50+ charts.

energtx.com/visualizations

#RStats #ggplot2 #TidyTuesday #DataViz
March 19, 2026 at 10:50 PM
energtx.bsky.social
Low-carbon electricity by country — a treemap.

Size = generation. Color = low-carbon share. Green = cleaner.

Built with R + treemapify
energtx.com/visualizations

#RStats #ggplot2 #treemapify #Treemap #LowCarbon #TidyTuesday
Treemap showing countries by electricity generation and low-carbon share
March 19, 2026 at 10:27 PM
philippbayer.bsky.social
library(treemapify)
ggplot(head(onyomi_clean, 15), aes(area = Freq, fill = Freq, label = Var1)) +
geom_treemap() +
geom_treemap_text(colour = "white", place = "centre", grow = TRUE) +
scale_fill_gradient(low = "lightblue", high = "darkblue") +
theme(legend.position = "bottom")
January 10, 2026 at 10:02 AM