A multi-line plot displays multiple data series on the same axes for direct comparison. Each series is represented by a distinct line with its own color and optional style, making it easy to identify trends, correlations, and divergences between variables. This visualization is essential for comparing related metrics over a common sequence or time period.
#' anyplot.ai
#' line-multi: Multi-Line Comparison Plot
#' Library: ggplot2 3.5.1 | R 4.4.1
#' Quality: 89/100 | Created: 2026-08-05
library(ggplot2)
library(dplyr)
library(tidyr)
library(ragg)
library(scales)
set.seed(42)
# --- Theme tokens -------------------------------------------------------
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, always first series
"#C475FD", # 2 — lavender
"#4467A3", # 3 — blue
"#BD8233" # 4 — ochre
)
# --- Data -----------------------------------------------------------------
# Average daily temperature (°C) across a year for four cities
day_of_year <- 1:365
seasonal <- function(peak_day, amplitude, mean_temp, noise_sd) {
mean_temp + amplitude * sin(2 * pi * (day_of_year - peak_day) / 365) +
rnorm(length(day_of_year), 0, noise_sd)
}
temps <- tibble(
day = day_of_year,
Reykjavik = seasonal(200, 6.5, 5, 1.4),
Berlin = seasonal(200, 10.5, 10, 1.6),
Marrakech = seasonal(200, 9.5, 20, 1.5),
Nairobi = seasonal(60, 2.0, 20, 1.0)
)
df <- temps %>%
pivot_longer(-day, names_to = "city", values_to = "temp_c") %>%
mutate(city = factor(city, levels = c("Reykjavik", "Berlin", "Marrakech", "Nairobi")))
# Smooth each series with a rolling mean to emphasize seasonal trend over daily noise
roll_mean <- function(x, k = 7) {
n <- length(x)
sapply(seq_len(n), function(i) {
lo <- max(1, i - k)
hi <- min(n, i + k)
mean(x[lo:hi])
})
}
df <- df %>%
group_by(city) %>%
arrange(day) %>%
mutate(temp_smooth = roll_mean(temp_c)) %>%
ungroup()
# --- Plot -------------------------------------------------------------------
title_text <- "Average City Temperatures · line-multi · r · ggplot2 · anyplot.ai"
title_fontsize <- round(12 * min(1, 67 / nchar(title_text)))
p <- ggplot(df, aes(x = day, y = temp_smooth, color = city, linetype = city)) +
geom_line(linewidth = 1.1) +
scale_color_manual(values = IMPRINT_PALETTE) +
scale_linetype_manual(values = c("solid", "dashed", "dotted", "dotdash")) +
scale_x_continuous(
breaks = c(1, 91, 182, 274, 365),
labels = c("Jan", "Apr", "Jul", "Oct", "Dec")
) +
labs(
title = title_text,
x = "Day of Year",
y = "Temperature (°C)",
color = "City",
linetype = "City"
) +
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_blank(),
panel.grid.minor = element_blank(),
panel.grid.major.y = element_line(color = scales::alpha(INK, 0.15), linewidth = 0.25),
axis.title = element_text(color = INK, size = 10),
axis.text = element_text(color = INK_SOFT, size = 8),
axis.ticks = element_blank(),
plot.title = element_text(color = INK, size = title_fontsize),
legend.background = element_blank(),
legend.key = element_blank(),
legend.text = element_text(color = INK_SOFT, size = 8),
legend.title = element_text(color = INK, size = 10),
legend.position = "right"
)
# --- 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 Multi-Line Comparison Plot on anyplot.ai.