A horizontal bar chart where bars are sorted by influence magnitude, extending left and right from a base case vertical reference line. Each bar represents one input parameter and shows how varying that parameter between its low and high values affects the output, creating a characteristic tornado shape (widest bars at top, narrowest at bottom). Dual colors distinguish low-input from high-input effects, making it immediately clear which parameters drive the most uncertainty.
#' anyplot.ai
#' bar-tornado-sensitivity: Tornado Diagram for Sensitivity Analysis
#' Library: ggplot2 3.5.1 | R 4.4.1
#' Quality: 89/100 | Created: 2026-06-02
library(ggplot2)
library(dplyr)
library(ragg)
set.seed(42)
# 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"
# Imprint palette — Low Input (position 1) and High Input (position 2)
COLOR_LOW <- "#009E73" # brand green — first series
COLOR_HIGH <- "#C475FD" # lavender — second series
# Base case NPV for a solar energy project
base_npv <- 42.5
# Sensitivity analysis: NPV (USD millions) when each parameter is at its low/high bound
params <- tibble::tibble(
parameter = c(
"Electricity Price",
"Discount Rate",
"Construction Cost",
"Capacity Factor",
"Operating Cost",
"Project Lifetime",
"Financing Rate",
"Tax Rate",
"Land Lease Cost"
),
low_value = c(28.0, 58.5, 51.8, 34.8, 46.2, 37.5, 48.3, 46.0, 43.5),
high_value = c(57.0, 26.5, 33.2, 51.5, 38.8, 47.5, 37.2, 39.0, 41.8)
)
# Sort by range ascending — smallest range at bottom, widest at top (tornado shape)
df <- params |>
mutate(range = abs(high_value - low_value)) |>
arrange(range) |>
mutate(
parameter = factor(parameter, levels = parameter),
y_pos = as.integer(parameter)
)
# Bold the top parameter (widest range = most sensitive) to guide viewer's eye
y_faces <- c(rep("plain", nrow(df) - 1L), "bold")
# Build bar segments: one row per (parameter x scenario) with tip label coords
bar_h <- 0.35
df_bars <- bind_rows(
df |> transmute(
y_pos,
xmin = pmin(low_value, base_npv),
xmax = pmax(low_value, base_npv),
outer_x = low_value,
label_hjust = if_else(low_value > base_npv, 0, 1),
scenario = "Low Input"
),
df |> transmute(
y_pos,
xmin = pmin(high_value, base_npv),
xmax = pmax(high_value, base_npv),
outer_x = high_value,
label_hjust = if_else(high_value > base_npv, 0, 1),
scenario = "High Input"
)
) |>
mutate(
ymin = y_pos - bar_h,
ymax = y_pos + bar_h,
scenario = factor(scenario, levels = c("Low Input", "High Input")),
label = sprintf("$%.1fM", outer_x),
label_x = if_else(label_hjust == 0L, outer_x + 0.5, outer_x - 0.5)
)
title_text <- "bar-tornado-sensitivity · r · ggplot2 · anyplot.ai"
p <- ggplot(df_bars) +
geom_rect(
aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = scenario),
color = NA,
alpha = 0.88
) +
geom_text(
aes(x = label_x, y = y_pos, label = label, hjust = label_hjust),
color = INK_SOFT,
size = 1.9
) +
geom_vline(
xintercept = base_npv,
color = INK,
linewidth = 0.9
) +
annotate(
"text",
x = base_npv,
y = Inf,
label = sprintf("Base: $%.1fM", base_npv),
color = INK_MUTED,
size = 2.5,
hjust = 0.5,
vjust = 1.4
) +
scale_fill_manual(
values = c("Low Input" = COLOR_LOW, "High Input" = COLOR_HIGH),
name = "Input Scenario"
) +
scale_x_continuous(
labels = function(x) sprintf("$%gM", x),
expand = expansion(mult = 0.12)
) +
scale_y_continuous(
breaks = df$y_pos,
labels = levels(df$parameter),
expand = expansion(add = c(0.5, 0.8))
) +
labs(
title = title_text,
x = "Net Present Value (USD Millions)",
y = NULL
) +
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.major.x = element_line(color = INK_SOFT, linewidth = 0.2),
panel.grid.major.y = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
axis.line = element_blank(),
axis.title.x = element_text(color = INK, size = 10),
axis.text.x = element_text(color = INK_SOFT, size = 8),
axis.text.y = element_text(color = INK, size = 9, hjust = 1,
face = y_faces),
axis.ticks.y = element_blank(),
plot.title = element_text(color = INK, size = 12, hjust = 0.5),
legend.background = element_rect(fill = ELEVATED_BG, color = NA),
legend.text = element_text(color = INK_SOFT, size = 8),
legend.title = element_text(color = INK, size = 9),
legend.key.size = unit(0.4, "cm"),
legend.position = "bottom",
legend.direction = "horizontal",
legend.key = element_rect(fill = ELEVATED_BG, color = NA),
plot.margin = margin(t = 15, r = 25, b = 10, l = 10)
)
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/bar-tornado-sensitivity/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": "bar-tornado-sensitivity",
"language": "r",
"library": "ggplot2",
"page": "https://anyplot.ai/bar-tornado-sensitivity/r/ggplot2",
"hub": "https://anyplot.ai/bar-tornado-sensitivity",
"code_json": "https://api.anyplot.ai/specs/bar-tornado-sensitivity/ggplot2/code",
"spec_json": "https://api.anyplot.ai/specs/bar-tornado-sensitivity",
"render_light_png": "https://storage.googleapis.com/anyplot-images/plots/bar-tornado-sensitivity/r/ggplot2/plot-light.png",
"render_dark_png": "https://storage.googleapis.com/anyplot-images/plots/bar-tornado-sensitivity/r/ggplot2/plot-dark.png",
"quality_score": 89.0,
"license": "MIT",
"guide": "https://anyplot.ai/llms.txt"
}Part of Tornado Diagram for Sensitivity Analysis on anyplot.ai.