The #Poaceae family is called “#Süssgräser” in German. They have been our source of #sugar and #carbohydrates for over 10’000 years, and basis of the #Neolithic Revolution: rice, maize, wheat, millet, barley… And later #sugarcane,, with 2025.8 Megatons of harvested biomass per year!
▶ See the "sweet grasses" in the Tree of life: https://ourednik.info/OuroborosTree/app/visualization/index_tree3D.html?taxon=4479
#biosphere #taxonomy #food #nutrition #sustainability #dataviz #threejs #pixijs #d3
#GIS Workflows for #3D Terrain in Rhino https://tinyurl.com/32x94h3j
#dataviz #DEM #esri #arcgis #mapping #GISchat #geospatial #ArcGISPro #TheScienceOfWhere @esri @esrifederalgovt @esrislgov @esritraining @arcgispro
It's #TidyTuesday y'all! Show us what you made on our Slack at https://dslc.io/join (find the #chat-tidytuesday channel)!
RT @jonthegeek https://fosstodon.org/@jonthegeek/115803166257611623
It's the first Tuesday of 2026 which means it's time to kick-off another year of #TidyTuesday with "Bring Your Own Data" week!
Here's 4 abstract timeline charts summarising my 2025 made with #ggplot2 (assembled with {patchwork})
Code: https://github.com/nrennie/tidytuesday/tree/main/2026/2026-01-06
This set of functions modify data values outside a given range. The oob_*() functions are designed to be passed as the oob argument of ggplot2 continuous and binned scales, with oob_discard being an exception. These functions affect out of bounds values in the following ways: oob_censor() replaces out of bounds values with NAs. This is the default oob argument for continuous scales. oob_censor_any() acts like oob_censor(), but also replaces infinite values with NAs. oob_squish() replaces out of bounds values with the nearest limit. This is the default oob argument for binned scales. oob_squish_any() acts like oob_squish(), but also replaces infinite values with the nearest limit. oob_squish_infinite() only replaces infinite values by the nearest limit. oob_keep() does not adjust out of bounds values. In position scales, behaves as zooming limits without data removal. oob_discard() removes out of bounds values from the input. Not suitable for ggplot2 scales.
I saw this chart in the wild a few days ago and it's been on my mind because the longer I look at it, the more confused I become by it. A #DataViz thread 🧵
I'm fairly sure it's AI generated for a few reasons:
- The gridlines are positioned at slightly different widths
- The colours are odd combinations of gradients and different colours and don't mean anything.
- The flags aren't *quite* correct e.g. Slovenian flag has a different symbol
It's week 1 of 2026, which means it's Bring Your Own Data Week!
Ideas:
⏪ A previous #TidyTuesday dataset (https://tidytues.day/2025)
🫵 Personal metadata (TV shows watched, music listened, #RStats written, etc)
❓ Whatever else you want to use!
Submit a dataset! https://github.com/rfordatascience/tidytuesday/blob/main/.github/CONTRIBUTING.md
All Statistics Globe courses are now open again: https://statisticsglobe.com/courses
Especially check out the Missing Data Imputation in R course, which is currently running and has just entered its second half: https://statisticsglobe.com/online-course-missing-data-imputation-r
André Ourednik
Derek Law
DataScienceLearningCommunity
Nicola Rennie
Data Science
Michael Friendly
Jon Harmon
Data of New York 🗽
Statistics Globe