Life has been 'lifeing'. Everything is chaotic and I'm just patiently waiting for May for a vacation. In the meantime, I am slowly working on my artpack package. I'm creating convenience functions, group_sample() and group_slice() that will allow you to quickly sample/slice entire groups out of data frames. This is something I personally do a lot for my art. Being able to drop groups of data can lead to some cool visuals sometimes: #rtistry w/ #ggplot2 in #rstats.

Recent data doodle - arc diagram of morning peak trip flows on TTC Line 2

I'm super happy to see that several of my data visualisation projects were long-listed at the 2024 Information is Beautiful Awards!

Check out the full longlist here: https://www.informationisbeautifulawards.com/showcase?action=index&award=2024&controller=showcase&page=1&pcategory=long-list&type=awards [www.informationisbeautifulawards.com]

A set of percentage areas charts made with {geofacet} for #TidyTuesday this week! The chart explores patterns in data on which agencies report to the FBI's national reporting system.

Code: https://github.com/nrennie/tidytuesday/tree/main/2025/2025-02-18

Catching up on last week's #TidyTuesday with a simple Voronoi diagram of which health-related CDC datasets have been backed up to archive.org

Code: https://github.com/nrennie/tidytuesday/tree/main/2025/2025-02-11

I recently had fun making a new cover image for Mastodon by making treemaps of colours used in Bob Ross paintings (columns are seasons and rows are episodes)!

Painting data from #TidyTuesday
Image processing with {imager}
Colours extracted using {eyedroppeR}
Pixel analysis in #RStats
Plotting with {treemapify}

Another scrollytelling visualisation made with Closeread!

Visualising data from the {gapminder} R package
Animated bubble chart with {gganimate}
Zooming in natively with Closeread

Explore the scrollytelling visualisation: https://nrennie.rbind.io/scrollytelling/posts/gapminder/

Code: https://github.com/nrennie/scrollytelling

Uluṟu in lines.

#ggplot2 adventures, an #rstats tale

It's the Olympics for this week's #TidyTuesday

From 1896 to 2016, there have been more U.S. male athletes named John than U.S. female athletes in any single sport, except athletics.

Code: https://github.com/gkaramanis/tidytuesday/tree/master/2024/2024-week_32

Summer movies this week's #TidyTuesday

Code: https://github.com/gkaramanis/tidytuesday/tree/master/2024/2024-week_31

I usually prefer to make "scapes" (landscapes, seascapes, galaxies) in my art... but I've been curious about doing these types of generated patterns. For this session, I practiced using geom_polygon()'s subgroup argument, slicing out multiple chunks of data at a time to make a clean image, and geometric rotations. #rtistry made in #rstats with #ggplot2

It's been a while since I've had the time and/or energy to make art (I technically still don't have the energy or time at the moment), But sometimes, you just gotta do something. I'm working on a lot, but I will eventually get to a point where I can breathe later this year after Posit Conf. In the meantime, here's some #rtistry made in #rstats with #ggplot2

#30DayChartChallenge | Day 8 | Circular
Submarine cable map (+proj = laea)
Data: Telegeography, Natural Earth
#rstats #dataviz #ggplot2

In my head, the last few days have "felt" like Friday. In the midst of all the chaos, I miraculously am still chugging along with...everything I have to do. This week's #rtistry #ggplot2 work is for the "Wavescapes" chapter. In the last week, I've re-learned more about basic trigonometry than I care for. Here are some snapshots of some WIP outputs as I'm still trying to land on an example to go through step-by-step for the beginning of this chapter.

Week 6 of the Du Bois visualization challenge -- recreated in ggplot/R!

code found here https://github.com/makuhs/DuboisChallenge

Week 5 of the Du Bois visualization challenge!! Recreated in R with ggplot.

code/github https://github.com/makuhs/DuboisChallenge

My attempt at this week's Du Bois Visualization Challenge.

I would have liked to recreate the hand-painted texture of fills and the ragged left edge of the plot. The package `ggpattern` provides some functions for creating non-solid fills, but I didn't see a way to do it in a purely programmatic way. And, sadly, there doesn't seem to be any `ggplot2` extension that does ragged edges.