Basic Error Bar Plot — ggplot2

An error bar plot displays data points with associated uncertainty or variability represented by bars extending above and below (or left and right of) each point. Error bars commonly represent standard deviation, standard error, confidence intervals, or min/max ranges. This visualization is essential for communicating the reliability and precision of measurements or statistical estimates.

Basic Error Bar Plot rendered with ggplot2

Renders

R source (ggplot2)

#' anyplot.ai
#' errorbar-basic: Basic Error Bar Plot
#' Library: ggplot2 3.5.1 | R 4.4.1
#' Quality: 90/100 | Created: 2026-06-30

library(ggplot2)
library(ragg)

# Theme tokens — Imprint palette, theme-adaptive chrome
THEME    <- Sys.getenv("ANYPLOT_THEME", "light")
PAGE_BG  <- if (THEME == "light") "#FAF8F1" else "#1A1A17"
INK      <- if (THEME == "light") "#1A1A17" else "#F0EFE8"
INK_SOFT <- if (THEME == "light") "#4A4A44" else "#B8B7B0"

IMPRINT_PALETTE <- c(
    "#009E73",  # 1 — brand green (first series)
    "#C475FD",  # 2 — lavender
    "#4467A3",  # 3 — blue
    "#BD8233",  # 4 — ochre
    "#AE3030",  # 5 — matte red
    "#2ABCCD",  # 6 — cyan
    "#954477",  # 7 — rose
    "#99B314"   # 8 — lime
)

# Data: enzyme activity across temperature conditions (mean ± 1 SD, n = 12 replicates)
conditions    <- c("20°C", "25°C", "30°C", "35°C", "40°C", "45°C", "50°C")
mean_activity <- c(12.4, 18.7, 27.3, 35.6, 28.4, 19.1, 8.3)
sd_activity   <- c(1.8,  2.1,  2.9,  3.2,  2.7,  1.9,  1.4)

df <- data.frame(
    temperature = factor(conditions, levels = conditions),
    mean_act    = mean_activity,
    lower       = mean_activity - sd_activity,
    upper       = mean_activity + sd_activity
)

# Plot
p <- ggplot(df, aes(x = temperature, y = mean_act)) +
    geom_errorbar(
        aes(ymin = lower, ymax = upper),
        width     = 0.22,
        linewidth = 1.0,
        color     = IMPRINT_PALETTE[1]
    ) +
    geom_point(
        size  = 3.5,
        color = IMPRINT_PALETTE[1]
    ) +
    # Enlarged marker highlights the enzyme optimum at 35°C
    geom_point(
        data  = df[df$temperature == "35°C", ],
        size  = 6.0,
        color = IMPRINT_PALETTE[1]
    ) +
    # Focal-point annotation at enzyme optimum
    annotate(
        "text",
        x     = 4,
        y     = 40.5,
        label = "enzyme optimum",
        color = INK_SOFT,
        size  = 3.2,
        hjust = 0.5
    ) +
    scale_y_continuous(expand = expansion(mult = c(0.05, 0.13))) +
    labs(
        x       = "Temperature",
        y       = "Enzyme Activity (μmol / min)",
        title   = "errorbar-basic · r · ggplot2 · anyplot.ai",
        caption = "Error bars: ±1 SD  (n = 12 replicates per condition)"
    ) +
    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.border       = element_blank(),
        panel.grid.major.y = element_line(
            color     = grDevices::adjustcolor(INK_SOFT, alpha.f = 0.45),
            linewidth = 0.4
        ),
        panel.grid.major.x = element_blank(),
        panel.grid.minor   = element_blank(),
        axis.line          = element_line(color = INK_SOFT, linewidth = 0.5),
        axis.title         = element_text(color = INK,      size = 10),
        axis.text          = element_text(color = INK_SOFT, size = 8),
        plot.title         = element_text(color = INK,      size = 12),
        plot.caption       = element_text(color = INK_SOFT, size = 7,  hjust = 0),
        plot.margin        = margin(20, 24, 16, 20)
    )

# 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 Error Bar Plot on anyplot.ai.

Other implementations