#ggtext
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cborstell.bsky.social
• Annotating outside of the panel
• Getting special Unicode characters to display/print (sometimes)
• Combining different font colors and faces without losing other manual tweaking opportunities: ggtext and marquee have different pros and cons
September 22, 2026 at 9:06 PM
nrennie.bsky.social
📊 New data viz blog post 📊

{ggtext} is one my favourite {ggplot2} extension packages! The new {marquee} package also provides functionality for rich text styling. So I've written a quick blog post comparing the two!

Blog post: nrennie.rbind.io/blog/coloure...

#RStats #DataViz #ggplot2
Coloured text in {ggplot2}: {ggtext} vs {marquee} | Nicola Rennie
An alternative to a traditional legend is using coloured text in a subtitle. In {ggplot2}, we can do this using the {ggtext} package. You can also do it using the new {marquee} package. How do they co...
nrennie.rbind.io
June 4, 2024 at 1:04 PM
nrennie.bsky.social
The making of last week's #TidyTuesday visualisation, recorded using {camcorder} in #RStats 📹

There was something weird going on with the interaction between {ggtext}/{marquee} and {ggpattern} for displaying images, so the hardest part ended up being arranging them with {patchwork}
February 12, 2025 at 9:34 AM
cborstell.bsky.social
The 5 #RStats packages that have improved my workflow and productivity the most in the last year:

{purrr} 😻
{patchwork} 🪟
{ggtext} 🔠
{tinytable} 🔢
{marginaleffects} 📊
April 10, 2025 at 8:19 PM
klauswiese.bsky.social
#Day7 | Distributions – Multiscale | #30DayChartChallenge | Comparison of NDVI distributions across two spatial scales. Built with #RStats using #ggplot2, #dplyr, #terra, #tidyterra, #patchwork, #ggtext, and #scales.
April 7, 2026 at 11:29 AM
tanyashapiro.bsky.social
ggplot, it's been a while...

supporting cast:
- gtrends - google trend data
- ggimage - plot images
- ggpattern - tied states
- ggtext - fancy subtitle
- patchwork - plot insets (legend, AK, HI)

code drop: github.com/tashapiro/ta...
February 3, 2024 at 4:55 PM
klauswiese.bsky.social
Día 14 – OpenStreetMap #30DayMapChallenge San Pedro Sula, Honduras. Herramientas: R usando los paquetes: sf, dplyr, ggplot2, osmdata, showtext y ggtext
November 14, 2025 at 3:17 AM
glue, patchwork & ggtext too.
January 21, 2026 at 8:21 PM
andrew.heiss.phd
The {ggh4x} package has neat support for nested facets for ggplot, but it wasn't quite working for a thing I was making, but I made a neat plot with fake nested facets with a combination of {ggtext} and {patchwork}! #rstats

(code here: gist.github.com/andrewheiss/...)
A plot with a top panel with a histogram showing all penguin weights, with a bottom faceted panel with species-specific weight histograms library(tidyverse) library(ggtext) library(patchwork) library(scales) top_plot <- ggplot(penguins, aes(x = body_mass)) + geom_histogram(binwidth = 100, color = "white", boundary = 0) + scale_x_continuous( breaks = seq(2500, 6500, by = 1000), limits = c(2500, 6500), labels = label_comma() ) + labs(title = "All penguins", x = NULL, y = "Count") + theme_bw() + theme( plot.title = element_textbox_simple( face = "bold", fill = "grey75", size = rel(0.85), halign = 0, linetype = 1, linewidth = 0.2, padding = margin(5, 5, 5, 5) ), strip.background = element_rect(fill = "grey92"), strip.text = element_text(hjust = 0), axis.title.y = element_text(hjust = 1) ) bottom_plot <- penguins |> ggplot(aes(x = body_mass, fill = species)) + geom_histogram(binwidth = 100, color = "white", boundary = 0) + scale_x_continuous( breaks = seq(2500, 6500, by = 1000), limits = c(2500, 6500), labels = label_comma() ) + guides(fill = "none") + facet_wrap(vars(species), ncol = 1) + labs(x = "Body mass (g)", y = "Count", title = "Specific penguin species") + theme_bw() + theme( plot.title = element_textbox_simple( face = "bold", fill = "grey75", size = rel(0.85), halign = 0, linetype = 1, linewidth = 0.2, padding = margin(5, 5, 5, 5) ), strip.background = element_rect(fill = "grey92"), strip.text = element_text(hjust = 0), axis.title.x = element_text(hjust = 0), axis.title.y = element_text(hjust = 1) ) (top_plot / bottom_plot) + plot_layout(heights = c(0.25, 0.75))
August 29, 2025 at 2:02 PM
klauswiese.bsky.social
Day 15 | Relationships – Complicated | #30DayChartChallenge. Visualization made with R using #tidyverse, #ggtext and #showtext . | Source: google trends trends.google.com/trends/explo...
April 15, 2025 at 12:45 AM
klauswiese.bsky.social
#Day10 | Distributions – Pop Culture | #30DayChartChallenge | Ballon d'Or — The Last 20 Years (2005-2025), source: France Football. Built with #RStats using #ggplot2, #patchwork, #ggtext and #scales.
April 11, 2026 at 2:07 AM
klauswiese.bsky.social
#Day9 | Distributions – Wealth | #30DayChartChallenge | Income Distribution in Central America, source World Bank. Built with #RStats using #ggplot2, #dplyr, #tidyr, #patchwork, #ggtext, #scales, #wbstats and #purrr.
April 9, 2026 at 4:45 AM
klauswiese.bsky.social
#Día23 | Series de Tiempo – Seasons (Temporadas) | #30DayChartChallenge | Malcolm in the Middle. Creada usando #Rstats con #ggplot2, #dplyr, #ggtext, #showtext, #patchwork, #scales y #glue.
April 23, 2026 at 4:28 AM
klauswiese.bsky.social
#Day8 | Distributions – Circular | #30DayChartChallenge | Elevation distribution in the most circular department of Honduras. Built with #RStats using #sf, #raster, #exactextractr, #ggplot2, #ggnewscale, #ggtext, #dplyr, #terra, #showtext, #scales, #patchwork and #ggspatial.
April 8, 2026 at 4:12 AM
hrbrmstr.dev
I cannot stress how much easier #RStats ggtext::element_textbox_simple makes dealing with the egregious # of facets I have for some plots of our data

```
strip .text.x.top = element_textbox_simple(height = unit(N, "lines"))
```

zero headaches getting the full strip text
60 faceted segment charts
August 1, 2025 at 11:53 AM
klauswiese.bsky.social
Day 2 | Comparisons – Slope | #30DayChartChallenge. Analysis develop with R using #ggplot2, #tidyverse, #ggpmisc, , #terra, #ggtext, #showtext y #sf. Data source: Sentinel-2 MSI (2019-2024)
April 2, 2025 at 2:48 PM
nrennie.bsky.social
For #TidyTuesday, we're looking at weekly gas prices in the USA from 1990 to present day ⛽

📊 Horizon plot made with {ggHoriPlot}
🎨 Colours from {PrettyCols}
✍️ Annotations with {ggtext}

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

#RStats #DataViz #ggplot2
Very long plot showing weekly gas prices from 1990 onwards. Each row represents a year, with higher prices shown in 2008, 2011-2014, and 2022 onwards.
July 1, 2025 at 10:01 AM
klauswiese.bsky.social
Day 5 | Comparisons – Ranking | #30DayChartChallenge. Visualization develop with R using #ggplot2, #dplyr, #ggtext, #showtext, #glue and #ggimage. Data source: Opta Analyst.
April 5, 2025 at 5:05 PM
klauswiese.bsky.social
Day 12 | Distributions – Data Day – Data.gov | #30DayChartChallenge. Visualization made with R using #sf, #tigris, #ggthemes, #patchwork, #tidyverse, #ggtext and #showtext . | Source: data.gov - catalog.data.gov/dataset/biod...
April 15, 2025 at 3:21 AM
stats33100.bsky.social
Happy #TidyTuesday 😊 I mirrored geom_density of lead samples collected in Flint by two different groups. I also learned the basics of ggtext and glue libraries.

Code: github.com/stats33100/t...

#ggplot2 #Rstats #DataViz
November 4, 2025 at 1:04 PM
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 1 | Comparaciones – Fracciones | #30DayChartChallenge. La visualización fue creada usando R basado en los paquetes #ggplot2, #dplyr, #scales, #ggtext, #patchwork, #showtext, #sf, #rnaturalearth, #rnaturalearthdata y #ggrepel. Fuente HDX - data.humdata.org/dataset/cod-...
April 1, 2025 at 12:09 PM
klauswiese.bsky.social
Day 24 | Timeseries – Data Day – WHO | #30DayChartChallenge. Visualization made with R using #ggplot2, #dplyr, #showtext, #patchwork, #ggrepel, #glue, #ggtext, #sf and #rnaturalearth. | Source: WHO.
April 24, 2025 at 12:21 PM
klauswiese.bsky.social
#Día6 | Comparaciones – RSF-Data Day | #30DayChartChallenge. Cambio en score de libertad de prensa 2024–2025 en paises de América. Creada usando R con #tidyverse, #ggtext, #scales, #rnaturalearth, #rnaturalearthdata y #patchwork.
April 6, 2026 at 11:20 AM
drandreahoward.bsky.social
Probably needs the ggtext package
October 9, 2023 at 12:11 AM