A gauge chart (also known as a speedometer chart) displays a single value within a defined range using a semi-circular or circular dial. It is ideal for showing progress toward a goal, performance metrics, or any KPI that needs to be evaluated against minimum and maximum bounds. The visual metaphor of a speedometer makes it intuitive to quickly assess whether a value is in an acceptable range.
#' anyplot.ai
#' gauge-basic: Basic Gauge Chart
#' Library: ggplot2 3.5.1 | R 4.4.1
#' Quality: 88/100 | Created: 2026-06-30
library(ggplot2)
library(ragg)
# Theme tokens
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"
# Zone colors — semantic exception applies: red=bad, amber=caution, green=good
# per the Imprint palette's semantic anchors and matte-red role
ZONE_COLORS <- c(bad = "#AE3030", caution = "#DDCC77", good = "#009E73")
# Data: quarterly sales attainment (%)
current_value <- 72
min_value <- 0
max_value <- 100
threshold_low <- 30
threshold_high <- 70
# Map a value to an angle on the semi-circle (pi = left/min, 0 = right/max)
val_to_angle <- function(v) {
pi * (1 - (v - min_value) / (max_value - min_value))
}
# Build a filled annular sector polygon (for zone arcs)
annular_sector <- function(a_start, a_end, r_inner, r_outer, n = 200) {
angles_out <- seq(a_start, a_end, length.out = n)
angles_in <- rev(angles_out)
data.frame(
x = c(r_outer * cos(angles_out), r_inner * cos(angles_in)),
y = c(r_outer * sin(angles_out), r_inner * sin(angles_in))
)
}
# Gauge radii
r_outer <- 1.00
r_inner <- 0.58
# Zone boundary angles
a_min <- val_to_angle(min_value)
a_low <- val_to_angle(threshold_low)
a_high <- val_to_angle(threshold_high)
a_max <- val_to_angle(max_value)
# Combined zones data frame — zone factor enables fill aesthetic mapping
# and scale_fill_manual(), leveraging ggplot2's grammar of graphics
zones_df <- rbind(
cbind(annular_sector(a_min, a_low, r_inner, r_outer), zone = "bad"),
cbind(annular_sector(a_low, a_high, r_inner, r_outer), zone = "caution"),
cbind(annular_sector(a_high, a_max, r_inner, r_outer), zone = "good")
)
zones_df$zone <- factor(zones_df$zone, levels = c("bad", "caution", "good"))
# Thin separator lines at zone boundaries
sep_angles <- c(a_low, a_high)
sep_df <- data.frame(
x = r_inner * cos(sep_angles),
y = r_inner * sin(sep_angles),
xend = r_outer * cos(sep_angles),
yend = r_outer * sin(sep_angles)
)
# Decorative boundary arcs (inner + outer rings) — grouped for single geom_path call
arc_angles <- seq(a_min, a_max, length.out = 300)
arcs_df <- data.frame(
x = c(r_outer * cos(arc_angles), r_inner * cos(arc_angles)),
y = c(r_outer * sin(arc_angles), r_inner * sin(arc_angles)),
ring = factor(rep(c("outer", "inner"), each = 300))
)
# Needle
needle_angle <- val_to_angle(current_value)
r_tip <- 0.90
r_tail <- 0.14
needle_df <- data.frame(
x = -r_tail * cos(needle_angle),
y = -r_tail * sin(needle_angle),
xend = r_tip * cos(needle_angle),
yend = r_tip * sin(needle_angle)
)
# Tick marks at every 20 units
tick_values <- c(0, 20, 40, 60, 80, 100)
tick_angles <- val_to_angle(tick_values)
tick_lines_df <- data.frame(
x = 1.04 * cos(tick_angles),
y = 1.04 * sin(tick_angles),
xend = 1.12 * cos(tick_angles),
yend = 1.12 * sin(tick_angles)
)
tick_labels_df <- data.frame(
x = 1.26 * cos(tick_angles),
y = 1.26 * sin(tick_angles),
label = as.character(tick_values)
)
plot_title <- "gauge-basic · r · ggplot2 · anyplot.ai"
# Build plot — zones mapped via fill aesthetic + scale_fill_manual (ggplot2 grammar)
p <- ggplot() +
# Colored zone arcs — fill mapped to zone factor, colors via scale
geom_polygon(
data = zones_df,
aes(x = x, y = y, fill = zone, group = zone),
alpha = 0.88
) +
scale_fill_manual(values = ZONE_COLORS, guide = "none") +
# Zone boundary separators (PAGE_BG camouflage for seamless look)
geom_segment(
data = sep_df, aes(x = x, y = y, xend = xend, yend = yend),
color = PAGE_BG, linewidth = 1.8
) +
# Decorative inner/outer boundary arcs — both rings in one geom_path call
geom_path(
data = arcs_df, aes(x = x, y = y, group = ring),
color = INK_SOFT, linewidth = 0.35, alpha = 0.4
) +
# Tick marks
geom_segment(
data = tick_lines_df, aes(x = x, y = y, xend = xend, yend = yend),
color = INK_SOFT, linewidth = 0.5
) +
# Tick labels (size=3.8mm for better mobile legibility)
geom_text(
data = tick_labels_df, aes(x = x, y = y, label = label),
color = INK_SOFT, size = 3.8
) +
# Needle
geom_segment(
data = needle_df, aes(x = x, y = y, xend = xend, yend = yend),
color = INK, linewidth = 1.4, lineend = "round"
) +
# Center pivot dot
annotate("point", x = 0, y = 0, size = 5, color = INK) +
# Current value (large, prominent)
annotate(
"text", x = 0, y = -0.22,
label = paste0(current_value, "%"),
color = INK, size = 17, fontface = "bold"
) +
# Subtitle below the value
annotate(
"text", x = 0, y = -0.44,
label = "Quarterly Sales Attainment",
color = INK_SOFT, size = 4.2
) +
labs(title = plot_title) +
coord_fixed(xlim = c(-1.7, 1.7), ylim = c(-0.65, 1.35)) +
theme_void() +
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 = 12, hjust = 0.5,
margin = margin(t = 12, b = 4)
),
plot.margin = margin(8, 16, 8, 16)
)
# Save
ggsave(
filename = sprintf("plot-%s.png", THEME),
plot = p,
device = ragg::agg_png,
width = 8,
height = 4.5,
units = "in",
dpi = 400
)
Part of Basic Gauge Chart on anyplot.ai.