A pictogram chart represents quantities using repeated icons or symbols, where each icon stands for a fixed number of units. Inspired by Otto Neurath's ISOTYPE system, this visualization makes numerical comparisons more intuitive and engaging than plain bar charts. It is especially effective for public-facing data communication and infographics where visual appeal and immediate comprehension are important.
#' anyplot.ai
#' pictogram-basic: Pictogram Chart (Isotype Visualization)
#' Library: ggplot2 3.5.1 | R 4.4.1
#' Quality: 89/100 | Created: 2026-06-03
library(ggplot2)
library(ragg)
set.seed(42)
# Theme tokens (Imprint palette, 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"
INK_MUTED <- if (THEME == "light") "#6B6A63" else "#A8A79F"
# Imprint palette (first series always #009E73)
IMPRINT_PALETTE <- c(
"#009E73", "#C475FD", "#4467A3", "#BD8233",
"#AE3030", "#2ABCCD", "#954477", "#99B314"
)
# Data: illustrative fruit production (thousand tons)
ICON_UNIT <- 5 # 1 icon = 5 thousand tons
fruit_data <- data.frame(
category = c("Apples", "Grapes", "Oranges", "Mangoes", "Strawberries"),
value = c(38, 31, 24, 19, 12),
stringsAsFactors = FALSE
)
# Assign Imprint colors in descending value order (highest → brand green)
fruit_ordered <- fruit_data[order(fruit_data$value, decreasing = TRUE), ]
color_map <- setNames(
IMPRINT_PALETTE[seq_len(nrow(fruit_data))],
fruit_ordered$category
)
# Factor levels: ascending value → bottom-to-top y-axis order
cat_levels <- fruit_data$category[order(fruit_data$value)]
# Build icon grid: one row per (category x icon slot)
n_max <- ceiling(max(fruit_data$value) / ICON_UNIT) # 8 slots
icon_list <- lapply(seq_len(nrow(fruit_data)), function(i) {
v <- fruit_data$value[i]
cat <- fruit_data$category[i]
nf <- floor(v / ICON_UNIT)
frac <- (v / ICON_UNIT) - nf
hp <- frac > 0.05
n_empty <- n_max - nf - as.integer(hp)
data.frame(
category = cat,
icon_col = seq_len(n_max),
icon_type = c(rep("full", nf),
if (hp) "partial",
rep("empty", n_empty)),
fill_alpha = c(rep(1.0, nf),
if (hp) frac,
rep(0.0, n_empty)),
stringsAsFactors = FALSE
)
})
icons <- do.call(rbind, icon_list)
icons$category <- factor(icons$category, levels = cat_levels)
# Focal emphasis: identify the top category for storytelling
top_cat <- fruit_ordered$category[1]
ratio_str <- sprintf("%.1f", max(fruit_data$value) / min(fruit_data$value))
subtitle <- paste0(top_cat, " leads at ", max(fruit_data$value), " kt — ",
ratio_str, "× the smallest category")
# Value labels: exact totals positioned right of last icon column
label_df <- data.frame(
category = factor(fruit_data$category, levels = cat_levels),
x_pos = n_max + 0.75,
label = paste0(fruit_data$value, " kt"),
fontface = ifelse(fruit_data$category == top_cat, "bold", "plain"),
stringsAsFactors = FALSE
)
# Plot
p <- ggplot() +
# Background rings for all icon slots
geom_point(
data = icons,
aes(x = icon_col, y = category),
shape = 1, size = 5, color = INK_MUTED, stroke = 0.6
) +
# Full icons
geom_point(
data = icons[icons$icon_type == "full", ],
aes(x = icon_col, y = category, color = category),
shape = 19, size = 5
) +
# Partial icons: alpha-faded to indicate fractional unit
geom_point(
data = icons[icons$icon_type == "partial", ],
aes(x = icon_col, y = category, color = category, alpha = fill_alpha),
shape = 19, size = 5
) +
# Exact value labels at row end; top category bolded for focal emphasis
geom_text(
data = label_df,
aes(x = x_pos, y = category, label = label, fontface = fontface),
hjust = 0, color = INK_SOFT, size = 3.5
) +
scale_alpha_identity() +
scale_color_manual(values = color_map) +
scale_x_continuous(
limits = c(0.3, n_max + 2.1),
expand = expansion(mult = 0)
) +
labs(
title = "pictogram-basic · r · ggplot2 · anyplot.ai",
subtitle = subtitle,
caption = paste0("Each ● represents ", ICON_UNIT,
" thousand tons | faded icon = partial unit")
) +
theme_minimal(base_size = 8) +
theme(
plot.background = element_rect(fill = PAGE_BG, color = PAGE_BG),
panel.background = element_rect(fill = PAGE_BG, color = NA),
panel.grid = element_blank(),
axis.title = element_blank(),
axis.text.x = element_blank(),
axis.text.y = element_text(color = INK, size = 10, hjust = 1,
margin = margin(r = 6)),
axis.ticks = element_blank(),
plot.title = element_text(color = INK, size = 12, hjust = 0, face = "bold",
margin = margin(b = 4)),
plot.subtitle = element_text(color = INK_SOFT, size = 9, hjust = 0,
margin = margin(b = 14)),
plot.caption = element_text(color = INK_MUTED, size = 8, hjust = 0,
margin = margin(t = 12)),
legend.position = "none",
plot.margin = margin(22, 20, 16, 22, "pt")
)
# Save
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/pictogram-basic/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": "pictogram-basic",
"language": "r",
"library": "ggplot2",
"page": "https://anyplot.ai/pictogram-basic/r/ggplot2",
"hub": "https://anyplot.ai/pictogram-basic",
"code_json": "https://api.anyplot.ai/specs/pictogram-basic/ggplot2/code",
"spec_json": "https://api.anyplot.ai/specs/pictogram-basic",
"render_light_png": "https://storage.googleapis.com/anyplot-images/plots/pictogram-basic/r/ggplot2/plot-light.png",
"render_dark_png": "https://storage.googleapis.com/anyplot-images/plots/pictogram-basic/r/ggplot2/plot-dark.png",
"quality_score": 89.0,
"license": "MIT",
"guide": "https://anyplot.ai/llms.txt"
}Part of Pictogram Chart (Isotype Visualization) on anyplot.ai.