A plot showing out-of-pocket payments as a percent of total health spending for many countries over time. Countries are grouped using 2022 World Bank income classifications. Reliance on out-of-pocket payments for health care is falling, but many countries still face heavy burdens

Yesterday we announced the alpha release of #ggsql 🎉 In celebration, here is a ggsql plot for #TidyTuesday Week 16 of 2026, using a dataset on global health spending! 💰

ggsql source: gist.github.com/georgestagg/...

I've been working on this over the last few months and in my opinion it is just beyond cool. Grammar of graphics for SQL users!

ggsql: A grammar of graphics for SQL Introducing ggsql, a grammar of graphics for SQL that lets you describe visualizations directly inside SQL queries.

I am excited beyond description to lift the veil on what we have been working on in 2026:

Please meet ggsql! A new extension of the SQL language for creating visualisations using the grammar of graphics. Read all about it in the blog post or visit the website at ggsql.org

ggplot2-extenders ggplot-extension-club · Discussions Explore the GitHub Discussions forum for ggplot2-extenders ggplot-extension-club. Discuss code, ask questions & collaborate with the developer community.

Folks over at github.com/ggplot2-exte... might be interested to give feedback :)

Four complex equations shown in a grid, with their LaTeX representation shown above and the rendered expression below

Some of the test cases for the native LaTeX math expression parser and renderer I've been working on for textshaping which will soon bring native math equation rendering to #rstats and marquee

You're absolutely right! Let me make a few changes to the countertop so we can drop a pitcher of orange juice instead

Example
```
library(ggplot2)

data.frame(cat = LETTERS[1:5], x = rnorm(5), xend = rnorm(5)) |>
ggplot(aes(x, xend = xend, cat)) +
ggarrow::geom_arrow_segment(
arrow_head = NULL,
stroke_colour = "black", colour = "red",
linewidth = 10
) +
coord_radial(theta = "y")
```

You can use `ggarrow::geom_arrow_segment(arrow_head = NULL)`. It distinguishes `stroke_colour` for the outline and regular `colour` for the interior. This confusing parametrisation was brought to you 'wanna be like `geom_segment`' 😁

You're feeling conflicted.r-lib.org about this?

A screenshot of two reply messages on bluesky commenting on the same post. The reply on top is very negative about the data.table package, saying 'it was just the worst'. The bottom reply instead claims that data.table's syntax is the best thing produced in #rstats.

Never change #rstats, never change

I've been charmed recently by ggiraph. It feels well-integrated and mostly works with extensions even if doesn't wrap them in interactivity. ggplotly sort of 'translates' ggplot figures and some of the more niche settings or extensions don't have a natural translation.

PDF has a horrible habit messing up font stuff. I'm an SVG enthusiast myself and I use ggrastr when my plot has too many points.

A humble suggestion:

```
`%xtab%` <- function(x, y) {
table(x, y, dnn = list(
deparse(substitute(x)),
deparse(substitute(y))
))
}
```

How can you say this when theme_barbie() exists? (cc @matthewbjane.bsky.social)

'ignored positional aesthetics' are so handy and cool, wanted to share on bsky! (as seen on mastodon 🙃) #rstats #ggplot2

ggplot2 styling This post discusses one function in ggplot2: `theme()`. Find out about the glamour of graphics in this deep-dive article.

You can use this instead of your `update_geom_defaults()`:
```
theme(geom = element_geom(linewidth = 0.25, borderwidth = 0.25, pointsize = 0.5))
```
And you can use `set_theme()` to globally apply a theme as the default theme.

I wrote some additional tricks here: tidyverse.org/blog/2025/10...

ONE OF US, ONE OF US, ONE OF US ✨github.com/ggplot2-extenders/ggplot... ✨

Look the use of the word 'extension' was very deliberate to absolve ggplot2 from having to absorb more functionality than it already does 😅

I like this use case for a facet extension!

I think this may come from Afrikaans/Dutch and means 'red forest', so bois (woods) wasn't too far of 🤷

dplyr 1.2.0 dplyr 1.2.0 fills in some important gaps in dplyr's API: we've added a new complement to `filter()` focused on dropping rows, and we've expanded the `case_when()` family with three new recoding and re...

dplyr 1.2.0 is out now and we are SO excited!

- `filter_out()` for dropping rows

- `recode_values()`, `replace_values()`, and `replace_when()` that join `case_when()` as a complete family of recoding/replacing tools

These are huge quality of life wins for #rstats!

tidyverse.org/blog/2026/02...

# pretty slick
l <- c(mpg = "Miles per gallon", wt = "Weight (1,000 lbs)", `mpg/2` = "yes this works")
ggplot(mtcars, aes(mpg, wt)) + labs(dictionary = l)
ggplot(mtcars, aes(wt, mpg)) + labs(dictionary = l)
ggplot(mtcars, aes(wt, mpg/2)) + labs(dictionary = l)

This is a very good primer on why we encounter breaking changes whenever ggplot2 has a meaningful update 🙃

A second crime is not putting these on the y-axis and displaying the names horizontally.

It is a (relatively) new thing 🎉

You can specify relative position in ggplot with I(x) I(y).

E.g. annotate("text", x = I(.5), y = I(.5), label = "hello!") will place the text in the middle of the plot.
This, combined with alignment arguments is like 87% of the magic for me.

They're alright if you have mutually inclusive categories, mostly as an alternative for large venn-diagram like data. Here, KO/WT are mutually exclusive and 8h/24h/48h are mutually exclusive. I'd opt for other ways of emphasising the experimental conditions.

Where'd be the artistry in deftly replacing `theme_gray()` with something more sensible? You gotta give the people some sense of accomplishment for free.

lukewarm take, but plotly is uggy and ggplotly should generally be avoided for disrespecting your static ggplot2 formatting (use ggiraph instead)

If there is a fear that some undocumented behaviour you rely on may break on accident, one thing you could do is PR a unit test for the behaviour. At least then, it'll only be broken purposefully 🙃