Grilled Cheese

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Grilled Cheese is a product of Village Compute

Version devBuilt at: 2026-10-17 14:54:11 EDT

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library(tidyplots) energy |> tidyplot(y = energy, color = energy_source) |> add_donut()
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Logo for the #TidyTuesday Project. The words TidyTuesday, A weekly data project from the Data Science Learning Community (dslc.io) overlaying a black paint splash.
Heatmap of the mtcars dataset, scaled within each column. Code: https://github.com/grantmcdermott/tinyplot/blob/main/vignettes/gallery_figs/heatmap-mtcars.R
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Faceted scatter plot titled "Income looks like the divide. City density explains most of the gap." Four panels, one per World Bank income group, plot the share of residents within 1 km of a hospital against population density (log scale) for 6,427 urban centers. A large dot marks each group's typical city: 23% within 1 km in high-income countries, 33% in upper-middle, 36% in lower-middle, and 36% in low-income, even though high-income cities have about twice as many hospitals per person as low-income cities. The typical cities sit at rising densities, from about 3,000 people per km² (high income) to about 7,300 (low income), and all four lie close to one dashed curve showing the access–density relationship for all cities. Density strips above each panel show where cities fall on the density axis; cities without hospital data lean denser in low-income countries. Source: GHS Urban Centre Database R2024A, European Commission JRC.
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