A tile grid map represents geographic regions (states, countries, provinces) as equally-sized tiles — squares or hexagons — arranged to approximate their real-world geographic positions. Unlike choropleth maps where large-area regions dominate visually, every region receives identical visual weight, making tile grid maps ideal for per-capita or per-region comparisons where the statistic matters more than physical area. Tiles are colored by a data variable and labeled with region abbreviations for identification.
#' anyplot.ai
#' map-tilegrid: Tile Grid Map for Equal-Area Geographic Comparison
#' Library: ggplot2 3.5.1 | R 4.4.1
#' Quality: 92/100 | Created: 2026-09-05
library(ggplot2)
library(dplyr)
library(ragg)
set.seed(42)
# --- Theme tokens (see prompts/default-style-guide.md "Theme-adaptive Chrome") ----
THEME <- Sys.getenv("ANYPLOT_THEME", "light")
PAGE_BG <- if (THEME == "light") "#FAF8F1" else "#1A1A17"
ELEVATED_BG <- if (THEME == "light") "#FFFDF6" else "#242420"
INK <- if (THEME == "light") "#1A1A17" else "#F0EFE8"
INK_SOFT <- if (THEME == "light") "#4A4A44" else "#B8B7B0"
# --- Data: US state tile grid + simulated per-capita income -----------------
# Row/col approximate each state's real-world position (0-indexed, top-left
# origin) so the tile layout still reads as a recognizable US map.
state_grid <- tibble::tribble(
~region, ~row, ~col,
"AK", 0, 0, "ME", 0, 10,
"WA", 1, 0, "MT", 1, 2, "ND", 1, 3, "MN", 1, 4, "WI", 1, 5,
"MI", 1, 7, "NY", 1, 8, "VT", 1, 9, "NH", 1, 10,
"OR", 2, 0, "ID", 2, 1, "WY", 2, 2, "SD", 2, 3, "IA", 2, 4,
"IL", 2, 5, "IN", 2, 6, "OH", 2, 7, "PA", 2, 8, "NJ", 2, 9,
"MA", 2, 10,
"CA", 3, 0, "NV", 3, 1, "UT", 3, 2, "CO", 3, 3, "NE", 3, 4,
"MO", 3, 5, "KY", 3, 6, "WV", 3, 7, "VA", 3, 8, "MD", 3, 9,
"CT", 3, 10,
"AZ", 4, 1, "NM", 4, 2, "KS", 4, 3, "AR", 4, 5, "TN", 4, 6,
"NC", 4, 8, "DE", 4, 9, "RI", 4, 10,
"TX", 5, 2, "OK", 5, 3, "LA", 5, 4, "MS", 5, 5, "AL", 5, 6,
"SC", 5, 8, "DC", 5, 9,
"HI", 6, 0, "GA", 6, 7,
"FL", 7, 7
)
df <- state_grid %>%
mutate(income_k = round(pmax(35, rnorm(n(), mean = 58, sd = 11)), 1))
# --- Outlier callouts (data-storytelling touch: national average + hi/lo) --
avg_income <- round(mean(df$income_k), 1)
top_state <- dplyr::slice_max(df, income_k, n = 1, with_ties = FALSE)
bottom_state <- dplyr::slice_min(df, income_k, n = 1, with_ties = FALSE)
df <- df %>%
mutate(
is_outlier = region %in% c(top_state$region, bottom_state$region),
tile_color = if_else(is_outlier, INK, PAGE_BG), # neutral anchor for callout ring
tile_stroke = if_else(is_outlier, 2.6, 1.2)
)
# --- Title (fontsize scales with title length, see plot-generator.md) -------
title_text <- "US Per-Capita Income by State · map-tilegrid · r · ggplot2 · anyplot.ai"
title_n <- nchar(title_text, type = "chars")
title_size <- max(8, round(12 * min(1, 67 / title_n)))
subtitle_text <- sprintf(
"National average $%.0fk · Highest: %s ($%.0fk) · Lowest: %s ($%.0fk)",
avg_income, top_state$region, top_state$income_k,
bottom_state$region, bottom_state$income_k
)
# --- Plot ---------------------------------------------------------------------
p <- ggplot(df, aes(x = col, y = -row)) +
geom_tile(aes(fill = income_k, color = tile_color, linewidth = tile_stroke),
width = 0.88, height = 0.88) +
geom_text(aes(label = region), color = "#FFFFFF", size = 3.4,
fontface = "bold") +
scale_fill_gradient(low = "#009E73", high = "#4467A3",
name = "Per-capita\nincome ($k)",
guide = guide_colorbar(title.position = "top",
barwidth = grid::unit(0.35, "cm"),
barheight = grid::unit(3.2, "cm"),
frame.colour = INK_SOFT,
frame.linewidth = 0.3,
ticks.colour = INK_SOFT)) +
scale_color_identity() +
scale_linewidth_identity() +
coord_fixed(ratio = 1, clip = "off") +
labs(title = title_text, subtitle = subtitle_text) +
theme_void(base_size = 8) +
theme(
plot.background = element_rect(fill = PAGE_BG, color = PAGE_BG),
panel.background = element_rect(fill = PAGE_BG, color = NA),
plot.title = element_text(color = INK, size = title_size,
hjust = 0.5,
margin = margin(b = 6)),
plot.subtitle = element_text(color = INK_SOFT, size = 9,
hjust = 0.5,
margin = margin(b = 16)),
legend.position = "right",
legend.background = element_rect(fill = ELEVATED_BG, color = NA),
legend.title = element_text(color = INK, size = 10),
legend.text = element_text(color = INK_SOFT, size = 8),
legend.key.height = grid::unit(1.1, "cm"),
plot.margin = margin(t = 20, r = 30, b = 20, l = 30)
)
# --- Save (both themes, ragg device, see prompts/library/ggplot2.md) --------
ggsave(
filename = sprintf("plot-%s.png", THEME),
plot = p,
device = ragg::agg_png,
width = 8,
height = 4.5,
units = "in",
dpi = 400
)
Runnable source as JSON, for any HTTP client: https://api.anyplot.ai/specs/map-tilegrid/ggplot2/code. Any spec id and library id listed in llms-full.txt fit the same URL shape; every URL below is complete and callable.
{
"spec_id": "map-tilegrid",
"language": "r",
"library": "ggplot2",
"page": "https://anyplot.ai/map-tilegrid/r/ggplot2",
"hub": "https://anyplot.ai/map-tilegrid",
"code_json": "https://api.anyplot.ai/specs/map-tilegrid/ggplot2/code",
"spec_json": "https://api.anyplot.ai/specs/map-tilegrid",
"render_light_png": "https://storage.googleapis.com/anyplot-images/plots/map-tilegrid/r/ggplot2/plot-light.png",
"render_dark_png": "https://storage.googleapis.com/anyplot-images/plots/map-tilegrid/r/ggplot2/plot-dark.png",
"quality_score": 92.0,
"license": "MIT",
"guide": "https://anyplot.ai/llms.txt"
}Part of Tile Grid Map for Equal-Area Geographic Comparison on anyplot.ai.