A chord diagram displays relationships or flows between entities arranged around a circle's perimeter. Arcs (chords) connect related entities, with chord width proportional to the flow magnitude. This visualization excels at revealing the overall structure of connections and identifying the strongest relationships within a system.
#' anyplot.ai
#' chord-basic: Basic Chord Diagram
#' Library: ggplot2 3.5.1 | R 4.4.1
#' Quality: 92/100 | Created: 2026-06-17
library(ggplot2)
library(dplyr)
library(tidyr)
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"
# Imprint palette — one distinct hue per region, first sector brand green
IMPRINT_PALETTE <- c("#009E73", "#C475FD", "#4467A3", "#BD8233",
"#AE3030", "#2ABCCD", "#954477", "#99B314")
# --- Data: annual migration flows between world regions (millions) ----------
entities <- c("Africa", "Europe", "Asia", "Oceania", "N. America", "S. America")
flows <- tribble(
~source, ~target, ~value,
"Asia", "Europe", 3.2,
"Asia", "N. America", 2.8,
"Asia", "Oceania", 1.1,
"Africa", "Europe", 2.4,
"Africa", "Asia", 1.3,
"Africa", "N. America", 0.9,
"Europe", "N. America", 1.6,
"Europe", "Asia", 1.0,
"Europe", "Oceania", 0.7,
"S. America", "N. America", 2.1,
"S. America", "Europe", 1.2,
"N. America", "Europe", 0.8,
"N. America", "Asia", 0.6,
"Oceania", "Asia", 0.5,
"Oceania", "Europe", 0.4,
"S. America", "Oceania", 0.3
)
flows$id <- seq_len(nrow(flows))
# --- Geometry helpers (data prep only — plot stays top-level) ---------------
deg2rad <- function(d) d * pi / 180
pt_on_circle <- function(angle_deg, r) {
data.frame(x = r * cos(deg2rad(angle_deg)), y = r * sin(deg2rad(angle_deg)))
}
arc_seq <- function(a_from, a_to, r, n = 50) {
a <- seq(a_from, a_to, length.out = n)
data.frame(x = r * cos(deg2rad(a)), y = r * sin(deg2rad(a)))
}
# Quadratic bezier with control point pinned at the centre (0, 0) — this is
# what bends each chord toward the middle of the circle.
bezier_to_centre <- function(p0, p1, n = 40) {
t <- seq(0, 1, length.out = n)
data.frame(
x = (1 - t)^2 * p0$x + t^2 * p1$x,
y = (1 - t)^2 * p0$y + t^2 * p1$y
)
}
# --- Sector layout: each region gets an arc sized by its total flow ---------
R_IN <- 1.00 # inner radius — chords attach here
R_OUT <- 1.085 # outer radius — sector band thickness
R_LAB <- 1.20 # region labels
GAP_DEG <- 3 # blank gap between adjacent sectors
N <- length(entities)
sector_total <- sapply(entities, function(e) {
sum(flows$value[flows$source == e]) + sum(flows$value[flows$target == e])
})
avail <- 360 - N * GAP_DEG
sector_df <- data.frame(entity = entities, sec_total = sector_total)
sector_df$span <- sector_df$sec_total / sum(sector_total) * avail
sector_df$a_start <- NA_real_
sector_df$a_end <- NA_real_
cursor <- 90 # start at the top, lay sectors counter-clockwise
for (i in seq_len(N)) {
sector_df$a_start[i] <- cursor
sector_df$a_end[i] <- cursor + sector_df$span[i]
cursor <- sector_df$a_end[i] + GAP_DEG
}
# --- Flow ends: each flow occupies a slice on its source AND target sector --
ends <- bind_rows(
transmute(flows, entity = source, flow_id = id, role = "out", value, partner = target),
transmute(flows, entity = target, flow_id = id, role = "in", value, partner = source)
)
ends$entity <- factor(ends$entity, levels = entities)
ends$partner <- factor(ends$partner, levels = entities)
ends <- ends %>%
arrange(entity, role, partner) %>%
group_by(entity) %>%
mutate(cum_end = cumsum(value), cum_start = cum_end - value) %>%
ungroup() %>%
left_join(sector_df, by = "entity") %>%
mutate(
ang1 = a_start + cum_start / sec_total * span,
ang2 = a_start + cum_end / sec_total * span
)
# --- Build sector band polygons (annulus segments) --------------------------
sector_poly <- do.call(rbind, lapply(seq_len(N), function(i) {
outer <- arc_seq(sector_df$a_start[i], sector_df$a_end[i], R_OUT)
inner <- arc_seq(sector_df$a_end[i], sector_df$a_start[i], R_IN) # reversed
poly <- rbind(outer, inner)
poly$entity <- entities[i]
poly$group <- paste0("sector_", i)
poly
}))
# --- Build chord ribbons: source arc → bezier → target arc → bezier back ----
ribbon_df <- do.call(rbind, lapply(flows$id, function(fid) {
src <- ends[ends$flow_id == fid & ends$role == "out", ]
tgt <- ends[ends$flow_id == fid & ends$role == "in", ]
poly <- rbind(
arc_seq(src$ang1, src$ang2, R_IN, n = 20),
bezier_to_centre(pt_on_circle(src$ang2, R_IN), pt_on_circle(tgt$ang1, R_IN)),
arc_seq(tgt$ang1, tgt$ang2, R_IN, n = 20),
bezier_to_centre(pt_on_circle(tgt$ang2, R_IN), pt_on_circle(src$ang1, R_IN))
)
poly$group <- paste0("ribbon_", fid)
poly$src_entity <- as.character(src$entity)
poly
}))
# Draw widest chords first so thin ones stay visible on top
ribbon_order <- flows$id[order(flows$value, decreasing = TRUE)]
ribbon_df$group <- factor(ribbon_df$group,
levels = paste0("ribbon_", ribbon_order))
# --- Region labels at the sector mid-angle ----------------------------------
label_df <- sector_df %>%
mutate(
mid = (a_start + a_end) / 2,
x = R_LAB * cos(deg2rad(mid)),
y = R_LAB * sin(deg2rad(mid))
)
fill_values <- setNames(IMPRINT_PALETTE[seq_len(N)], entities)
# --- Plot -------------------------------------------------------------------
p <- ggplot() +
geom_polygon(
data = ribbon_df,
aes(x, y, group = group, fill = src_entity),
alpha = 0.55, color = NA
) +
geom_polygon(
data = sector_poly,
aes(x, y, group = group, fill = entity),
color = PAGE_BG, linewidth = 0.5
) +
geom_text(
data = label_df,
aes(x, y, label = entity),
color = INK, size = 5.2, fontface = "bold"
) +
scale_fill_manual(values = fill_values, guide = "none") +
coord_fixed(xlim = c(-1.62, 1.62), ylim = c(-1.62, 1.62), expand = FALSE) +
labs(
title = "chord-basic · r · ggplot2 · anyplot.ai",
subtitle = "Annual migration flows between world regions · chord width ∝ migrants, coloured by origin"
) +
theme_void(base_size = 8) +
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,
face = "bold", margin = margin(t = 6, b = 3)),
plot.subtitle = element_text(color = INK_SOFT, size = 8, hjust = 0.5,
margin = margin(b = 4)),
plot.margin = margin(10, 10, 10, 10)
)
# --- Save -------------------------------------------------------------------
ggsave(
filename = sprintf("plot-%s.png", THEME),
plot = p,
device = ragg::agg_png,
width = 6,
height = 6,
units = "in",
dpi = 400
)
Part of Basic Chord Diagram on anyplot.ai.